Most recent papers:

• Improving Markov switching models using realized variance.
  Jia Liu, John M. Maheu.
  Journal of Applied Econometrics. October 06, 2017
  This paper proposes a class of models that jointly model returns and ex post variance measures under a Markov switching framework. Both univariate and multivariate return versions of the model are introduced. Estimation can be conducted under a fixed dimension state space or an infinite one. The proposed models can be seen as nonlinear common factor models subject to Markov switching and are able to exploit the information content in both returns and ex post volatility measures. Applications to equity returns compare the proposed models to existing alternatives. The empirical results show that the joint models improve density forecasts for returns and point predictions of return variance. Using the information in ex post volatility measures can increase the precision of parameter estimates, sharpen the inference on the latent state variable, and improve portfolio decisions.

  October 06, 2017   doi: 10.1002/jae.2605   open full text
• Business, housing, and credit cycles.
  Gerhard Rünstler, Marente Vlekke.
  Journal of Applied Econometrics. October 06, 2017
  We use multivariate unobserved components models to estimate trend and cyclical components in gross domestic product (GDP), credit volumes, and house prices for the USA and the five largest European economies. With the exception of Germany, we find large and long cycles in credit and house prices, which are highly correlated with a medium‐term component in GDP cycles. Differences across countries in the length and size of cycles appear to be related to the properties of national housing markets. The precision of pseudo real‐time estimates of credit and house price cycles is roughly comparable to that of GDP cycles.

  October 06, 2017   doi: 10.1002/jae.2604   open full text
• An efficient Bayesian approach to multiple structural change in multivariate time series.
  John M. Maheu, Yong Song.
  Journal of Applied Econometrics. October 06, 2017
  This paper provides a feasible approach to estimation and forecasting of multiple structural breaks for vector autoregressions and other multivariate models. Owing to conjugate prior assumptions we obtain a very efficient sampler for the regime allocation variable. A new hierarchical prior is introduced to allow for learning over different structural breaks. The model is extended to independent breaks in regression coefficients and the volatility parameters. Two empirical applications show the improvements the model has over benchmarks. In a macro application with seven variables we empirically demonstrate the benefits from moving from a multivariate structural break model to a set of univariate structural break models to account for heterogeneous break patterns across data series.

  October 06, 2017   doi: 10.1002/jae.2606   open full text
• Self‐employment among women: Do children matter more than we previously thought?
  Anastasia Semykina.
  Journal of Applied Econometrics. September 04, 2017
  This paper presents an estimation approach that addresses the problems of sample selection and endogeneity of fertility decisions when estimating the effect of young children on women's self‐employment. Using data from the National Longitudinal Survey of Youth 1979, 1982–2006, we find that ignoring self‐selection and endogeneity leads to underestimating the effect of young children. Once both sources of biases are accounted for, the estimated effect of young children roughly triples when compared to uncorrected results. This finding is robust to several changes in the specification and to the use of a different dataset.

  September 04, 2017   doi: 10.1002/jae.2596   open full text
• Comparing cross‐country estimates of Lorenz curves using a Dirichlet distribution across estimators and datasets.
  Andrew C. Chang, Phillip Li, Shawn M. Martin.
  Journal of Applied Econometrics. August 31, 2017
  Chotikapanich and Griffiths (Journal of Business and Economic Statistics, 2002, 20(2), 290–295) introduced the Dirichlet distribution to the estimation of Lorenz curves. This distribution naturally accommodates the proportional nature of income share data and the dependence structure between the shares. Chotikapanich and Griffiths fit a family of five Lorenz curves to one year of Swedish and Brazilian income share data using unconstrained maximum likelihood and unconstrained nonlinear least squares. We attempt to replicate the authors' results and extend their analyses using both constrained estimation techniques and five additional years of data. We successfully replicate a majority of the authors' results and find that some of their main qualitative conclusions also hold using our constrained estimators and additional data.

  August 31, 2017   doi: 10.1002/jae.2595   open full text
• Do contractionary monetary policy shocks expand shadow banking?
  Benjamin Nelson, Gabor Pinter, Konstantinos Theodoridis.
  Journal of Applied Econometrics. August 31, 2017
  Using VAR models for the USA, we find that a contractionary monetary policy shock has a persistent negative impact on the level of commercial bank assets, but increases the assets of shadow banks and securitization activity. To explain this “waterbed” effect, we propose a standard New Keynesian model featuring both commercial and shadow banks, and we show that the model comes close to explaining the empirical results. Our findings cast doubt on the idea that monetary policy can usefully “get in all the cracks” of the financial sector in a uniform way.

  August 31, 2017   doi: 10.1002/jae.2594   open full text
• Binary response panel data models with sample selection and self‐selection.
  Anastasia Semykina, Jeffrey M. Wooldridge.
  Journal of Applied Econometrics. August 08, 2017
  We consider estimating binary response models on an unbalanced panel, where the outcome of the dependent variable may be missing due to nonrandom selection, or there is self‐selection into a treatment. In the present paper, we first consider estimation of sample selection models and treatment effects using a fully parametric approach, where the error distribution is assumed to be normal in both primary and selection equations. Arbitrary time dependence in errors is permitted. Estimation of both coefficients and partial effects, as well as tests for selection bias, are discussed. Furthermore, we consider a semiparametric estimator of binary response panel data models with sample selection that is robust to a variety of error distributions. The estimator employs a control function approach to account for endogenous selection and permits consistent estimation of scaled coefficients and relative effects.

  August 08, 2017   doi: 10.1002/jae.2592   open full text
• A sequential Monte Carlo approach to inference in multiple‐equation Markov‐switching models.
  Mark Bognanni, Edward Herbst.
  Journal of Applied Econometrics. August 07, 2017
  Vector autoregressions with Markov‐switching parameters (MS‐VARs) offer substantial gains in data fit over VARs with constant parameters. However, Bayesian inference for MS‐VARs has remained challenging, impeding their uptake for empirical applications. We show that sequential Monte Carlo (SMC) estimators can accurately estimate MS‐VAR posteriors. Relative to multi‐step, model‐specific MCMC routines, SMC has the advantages of generality, parallelizability, and freedom from reliance on particular analytical relationships between prior and likelihood. We use SMC's flexibility to demonstrate that model selection among MS‐VARs can be highly sensitive to the choice of prior.

  August 07, 2017   doi: 10.1002/jae.2582   open full text
• Sequentially testing polynomial model hypotheses using power transforms of regressors.
  Jin Seo Cho, Peter C. B. Phillips.
  Journal of Applied Econometrics. August 07, 2017
  We provide a methodology for testing a polynomial model hypothesis by generalizing the approach and results of Baek, Cho, and Phillips (Journal of Econometrics, 2015, 187, 376–384; BCP), which test for neglected nonlinearity using power transforms of regressors against arbitrary nonlinearity. We use the BCP quasi‐likelihood ratio test and deal with the new multifold identification problem that arises under the null of the polynomial model. The approach leads to convenient asymptotic theory for inference, has omnibus power against general nonlinear alternatives, and allows estimation of an unknown polynomial degree in a model by way of sequential testing, a technique that is useful in the application of sieve approximations. Simulations show good performance in the sequential test procedure in both identifying and estimating unknown polynomial order. The approach, which can be used empirically to test for misspecification, is applied to a Mincer (Journal of Political Economy, 1958, 66, 281–302; Schooling, Experience and Earnings, Columbia University Press, 1974) equation using data from Card (in Christofides, Grant, and Swidinsky (Eds.), Aspects of Labour Market Behaviour: Essays in Honour of John Vanderkamp, University of Toronto Press, 1995, 201‐222) and Bierens and Ginther (Empirical Economics, 2001, 26, 307–324). The results confirm that the standard Mincer log earnings equation is readily shown to be misspecified. The applications consider different datasets and examine the impact of nonlinear effects of experience and schooling on earnings, allowing for flexibility in the respective polynomial representations.

  August 07, 2017   doi: 10.1002/jae.2589   open full text
• Identifying contagion.
  Mardi Dungey, Eric Renault.
  Journal of Applied Econometrics. August 07, 2017
  Identifying contagion effects during periods of financial crisis is known to be complicated by the changing volatility of asset returns during periods of stress. To untangle this we propose a GARCH (generalized autoregressive conditional heteroskedasticity) common features approach, where systemic risk emerges from a common factor source (or indeed multiple factor sources) with contagion evident through possible changes in the factor loadings relating to the common factor(s). Within a portfolio mimicking factor framework this can be identified using moment conditions. We use this framework to identify contagion in three illustrations involving both single and multiple factor specifications: to the Asian currency markets in 1997–1998, to US sectoral equity indices in 2007–2009 and to the CDS (credit default swap) market during the European sovereign debt crisis of 2010–2013. The results reveal the extent to which contagion effects may be masked by not accounting for the sources of changed volatility apparent in simple measures such as correlation.

  August 07, 2017   doi: 10.1002/jae.2593   open full text
• Multivariate choices and identification of social interactions.
  Ethan Cohen‐Cole, Xiaodong Liu, Yves Zenou.
  Journal of Applied Econometrics. July 31, 2017
  This paper considers the identification of social interaction effects in the context of multivariate choices. First, we generalize the theoretical social interaction model to allow individuals to make interdependent choices in different activities. Based on the theoretical model, we propose a simultaneous equation network model and discuss the identification of social interaction effects in the econometric model. We also provide an empirical example to show the empirical salience of this model. Using the Add Health data, we find that a student's academic performance is not only affected by academic performance of his peers but also affected by screen‐related activities of his peers.

  July 31, 2017   doi: 10.1002/jae.2590   open full text
• Anchoring the yield curve using survey expectations.
  Carlo Altavilla, Raffaella Giacomini, Giuseppe Ragusa.
  Journal of Applied Econometrics. July 31, 2017
  The dynamic behavior of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have underperformed since the early 2000s. On the other hand, survey expectations can accurately predict yields, but they are typically not available for all maturities and/or forecast horizons. We show how survey expectations can be exploited to improve the accuracy of yield curve forecasts given by a base model. We do so by employing a flexible exponential tilting method that anchors the model forecasts to the survey expectations, and we develop a test to guide the choice of the anchoring points. The method implicitly incorporates into yield curve forecasts any information that survey participants have access to—such as information about the current state of the economy or forward‐looking information contained in monetary policy announcements—without the need to explicitly model it. We document that anchoring delivers large and significant gains in forecast accuracy relative to the class of models that are widely adopted by financial and policy institutions for forecasting the term structure of interest rates.

  July 31, 2017   doi: 10.1002/jae.2588   open full text
• Estimating global bank network connectedness.
  Mert Demirer, Francis X. Diebold, Laura Liu, Kamil Yilmaz.
  Journal of Applied Econometrics. July 31, 2017
  We use LASSO methods to shrink, select, and estimate the high‐dimensional network linking the publicly traded subset of the world's top 150 banks, 2003–2014. We characterize static network connectedness using full‐sample estimation and dynamic network connectedness using rolling‐window estimation. Statically, we find that global bank equity connectedness has a strong geographic component, whereas country sovereign bond connectedness does not. Dynamically, we find that equity connectedness increases during crises, with clear peaks during the Great Financial Crisis and each wave of the subsequent European Debt Crisis, and with movements coming mostly from changes in cross‐country as opposed to within‐country bank linkages.

  July 31, 2017   doi: 10.1002/jae.2585   open full text
• Estimating the effects of the minimum wage in a developing country: A density discontinuity design approach.
  Hugo Jales.
  Journal of Applied Econometrics. July 25, 2017
  This paper proposes a framework to identify the effects of the minimum wage on the joint distribution of sector and wage in a developing country. I show how the discontinuity of the wage distribution around the minimum wage identifies the extent of noncompliance with the minimum wage policy, and how the conditional probability of sector given wage recovers the relationship between latent sector and wages. I apply the method in the “PNAD,” a nationwide representative Brazilian cross‐sectional dataset for the years 2001–2009. The results indicate that the size of the informal sector is increased by around 39% compared to what would prevail in the absence of the minimum wage, an effect attributable to (i) unemployment effects of the minimum wage on the formal sector and (ii) movements of workers from the formal to the informal sector as a response to the policy.

  July 25, 2017   doi: 10.1002/jae.2586   open full text
• Estimating the distribution of welfare effects using quantiles.
  Stefan Hoderlein, Anne Vanhems.
  Journal of Applied Econometrics. July 18, 2017
  This paper proposes a framework to model welfare effects that are associated with a price change in a population of heterogeneous consumers. The framework is similar to that of Hausman and Newey (Econometrica, 1995, 63, 1445–1476), but allows for more general forms of heterogeneity. Individual demands are characterized by a general model that is nonparametric in the regressors, as well as monotonic in unobserved heterogeneity, allowing us to identify the distribution of welfare effects. We first argue why a decision maker should care about this distribution. Then we establish constructive identification, propose a sample counterparts estimator, and analyze its large‐sample properties. Finally, we apply all concepts to measuring the heterogeneous effect of a change of gasoline price using US consumer data and find very substantial differences in individual effects across quantiles.

  July 18, 2017   doi: 10.1002/jae.2587   open full text
• Difference‐in‐differences when the treatment status is observed in only one period.
  Irene Botosaru, Federico H. Gutierrez.
  Journal of Applied Econometrics. July 05, 2017
  This paper considers the difference‐in‐differences (DID) method when the data come from repeated cross‐sections and the treatment status is observed either before or after the implementation of a program. We propose a new method that point‐identifies the average treatment effect on the treated (ATT) via a DID method when there is at least one proxy variable for the latent treatment. Key assumptions are the stationarity of the propensity score conditional on the proxy and an exclusion restriction that the proxy must satisfy with respect to the change in average outcomes over time conditional on the true treatment status. We propose a generalized method of moments estimator for the ATT and we show that the associated overidentification test can be used to test our key assumptions. The method is used to evaluate JUNTOS, a Peruvian conditional cash transfer program. We find that the program significantly increased the demand for health inputs among children and women of reproductive age.

  July 05, 2017   doi: 10.1002/jae.2583   open full text
• Weak‐instrument robust inference for two‐sample instrumental variables regression.
  Jaerim Choi, Jiaying Gu, Shu Shen.
  Journal of Applied Econometrics. June 21, 2017
  Instrumental variable (IV) methods for regression are well established. More recently, methods have been developed for statistical inference when the instruments are weakly correlated with the endogenous regressor, so that estimators are biased and no longer asymptotically normally distributed. This paper extends such inference to the case where two separate samples are used to implement instrumental variables estimation. We also relax the restrictive assumptions of homoskedastic error structure and equal moments of exogenous covariates across two samples commonly employed in the two‐sample IV literature for strong IV inference. Monte Carlo experiments show good size properties of the proposed tests regardless of the strength of the instruments. We apply the proposed methods to two seminal empirical studies that adopt the two‐sample IV framework.

  June 21, 2017   doi: 10.1002/jae.2580   open full text
• Decomposing economic mobility transition matrices.
  Jeremiah Richey, Alicia Rosburg.
  Journal of Applied Econometrics. June 20, 2017
  We present a decomposition method for transition matrices to identify forces driving the persistence of economic status across generations. The method decomposes differences between an estimated transition matrix and a benchmark transition matrix into portions attributable to differences in characteristics between individuals from different households (a composition effect) and portions attributable to differing returns to these characteristics (a structure effect). A detailed decomposition based on copula theory further decomposes the composition effect into portions attributable to specific characteristics and their interactions. To examine potential drivers of economic persistence in the USA, we apply the method to white males from the 1979 US National Longitudinal Survey of Youth. Depending on the transition matrix entry of interest, differing characteristics between sons from different households explain between 40% and 70% of observed income persistence, with differing returns for these characteristics explaining the remaining gap. Further, detailed decompositions reveal significant heterogeneity in the role played by specific characteristics (e.g., education) across the income distribution.

  June 20, 2017   doi: 10.1002/jae.2578   open full text
• The evolution of scale economies in US banking.
  David C. Wheelock, Paul W. Wilson.
  Journal of Applied Econometrics. June 16, 2017
  Continued consolidation of the US banking industry and a general increase in the size of banks have prompted some policymakers to consider policies that discourage banks from getting larger, including explicit caps on bank size. However, limits on the size of banks could entail economic costs if they prevent banks from achieving economies of scale. This paper presents new estimates of returns to scale for US banks based on nonparametric, local‐linear estimation of bank cost, revenue, and profit functions. We report estimates for both 2006 and 2015 to compare returns to scale some 7 years after the financial crisis and 5 years after enactment of the Dodd–Frank Act with returns to scale before the crisis. We find that a high percentage of banks faced increasing returns to scale in cost in both years, including most of the 10 largest bank holding companies. Also, while returns to scale in revenue and profit vary more across banks, we find evidence that the largest four banks operate under increasing returns to scale.

  June 16, 2017   doi: 10.1002/jae.2579   open full text
• Loss functions for predicted click‐through rates in auctions for online advertising.
  Patrick Hummel, R. Preston McAfee.
  Journal of Applied Econometrics. June 09, 2017
  We characterize the optimal loss functions for predicted click‐through rates in auctions for online advertising. Whereas standard loss functions such as mean squared error or log likelihood severely penalize large mispredictions while imposing little penalty on smaller mistakes, a loss function reflecting the true economic loss from mispredictions imposes significant penalties for small mispredictions and only slightly larger penalties on large mispredictions. We illustrate that when the model is misspecified using such a loss function can improve economic efficiency, but the efficiency gain is likely to be small.

  June 09, 2017   doi: 10.1002/jae.2581   open full text
• Efficient estimation of Bayesian VARMAs with time‐varying coefficients.
  Joshua C.C. Chan, Eric Eisenstat.
  Journal of Applied Econometrics. June 07, 2017
  Empirical work in macroeconometrics has been mostly restricted to using vector autoregressions (VARs), even though there are strong theoretical reasons to consider general vector autoregressive moving averages (VARMAs). A number of articles in the last two decades have conjectured that this is because estimation of VARMAs is perceived to be challenging and proposed various ways to simplify it. Nevertheless, VARMAs continue to be largely dominated by VARs, particularly in terms of developing useful extensions. We address these computational challenges with a Bayesian approach. Specifically, we develop a Gibbs sampler for the basic VARMA, and demonstrate how it can be extended to models with time‐varying vector moving average (VMA) coefficients and stochastic volatility. We illustrate the methodology through a macroeconomic forecasting exercise. We show that in a class of models with stochastic volatility, VARMAs produce better density forecasts than VARs, particularly for short forecast horizons.

  June 07, 2017   doi: 10.1002/jae.2576   open full text
• Doubly robust uniform confidence band for the conditional average treatment effect function.
  Sokbae Lee, Ryo Okui, Yoon‐Jae Whang.
  Journal of Applied Econometrics. May 31, 2017
  In this paper, we propose a doubly robust method to estimate the heterogeneity of the average treatment effect with respect to observed covariates of interest. We consider a situation where a large number of covariates are needed for identifying the average treatment effect but the covariates of interest for analyzing heterogeneity are of much lower dimension. Our proposed estimator is doubly robust and avoids the curse of dimensionality. We propose a uniform confidence band that is easy to compute, and we illustrate its usefulness via Monte Carlo experiments and an application to the effects of smoking on birth weights.

  May 31, 2017   doi: 10.1002/jae.2574   open full text
• An endogenously clustered factor approach to international business cycles.
  Neville Francis, Michael T. Owyang, Ozge Savascin.
  Journal of Applied Econometrics. May 31, 2017
  Factor models have become useful tools for studying international business cycles. Block factor models can be especially useful as the zero restrictions on the loadings of some factors may provide some economic interpretation of the factors. These models, however, require the econometrician to predefine the blocks, leading to potential misspecification. In Monte Carlo experiments, we show that even a small misspecification can lead to substantial declines in fit. We propose an alternative model in which the blocks are chosen endogenously. The model is estimated in a Bayesian framework using a hierarchical prior, which allows us to incorporate series‐level covariates that may influence and explain how the series are grouped. Using international business cycle data, we find our country clusters differ in important ways from those identified by geography alone. In particular, we find that similarities in institutions (e.g., legal systems, language diversity) may be just as important as physical proximity for analyzing business cycle comovements.

  May 31, 2017   doi: 10.1002/jae.2577   open full text
• Combining density forecasts using focused scoring rules.
  Anne Opschoor, Dick van Dijk, Michel van der Wel.
  Journal of Applied Econometrics. May 29, 2017
  We investigate the added value of combining density forecasts focused on a specific region of support. We develop forecast combination schemes that assign weights to individual predictive densities based on the censored likelihood scoring rule and the continuous ranked probability scoring rule (CRPS) and compare these to weighting schemes based on the log score and the equally weighted scheme. We apply this approach in the context of measuring downside risk in equity markets using recently developed volatility models, including HEAVY, realized GARCH and GAS models, applied to daily returns on the S&P 500, DJIA, FTSE and Nikkei indexes from 2000 until 2013. The results show that combined density forecasts based on optimizing the censored likelihood scoring rule significantly outperform pooling based on equal weights, optimizing the CRPS or log scoring rule. In addition, 99% Value‐at‐Risk estimates improve when weights are based on the censored likelihood scoring rule.

  May 29, 2017   doi: 10.1002/jae.2575   open full text
• Nonparametric methods and local‐time‐based estimation for dynamic power law distributions.
  Ricardo T. Fernholz.
  Journal of Applied Econometrics. May 15, 2017
  This paper introduces nonparametric econometric methods that characterize general power law distributions under basic stability conditions. These methods extend the literature on power laws in the social sciences in several directions. First, we show that any stationary distribution in a random growth setting is shaped entirely by two factors: the idiosyncratic volatilities and reversion rates (a measure of cross‐sectional mean reversion) for different ranks in the distribution. This result is valid regardless of how growth rates and volatilities vary across different economic agents, and hence applies to Gibrat's law and its extensions. Second, we present techniques to estimate these two factors using panel data. Third, we describe how our results imply predictability as higher‐ranked processes must on average grow more slowly than lower‐ranked processes. We employ our empirical methods using data on commodity prices and show that our techniques accurately describe the empirical distribution of relative commodity prices. We also show that rank‐based out‐of‐sample forecasts of future commodity prices outperform random‐walk forecasts at a 1‐month horizon.

  May 15, 2017   doi: 10.1002/jae.2573   open full text
• Structural FECM: Cointegration in large‐scale structural FAVAR models.
  Anindya Banerjee, Massimiliano Marcellino, Igor Masten.
  Journal of Applied Econometrics. May 03, 2017
  Starting from the dynamic factor model for nonstationary data we derive the factor‐augmented error correction model (FECM) and its moving‐average representation. The latter is used for the identification of structural shocks and their propagation mechanisms. We show how to implement classical identification schemes based on long‐run restrictions in the case of large panels. The importance of the error correction mechanism for impulse response analysis is analyzed by means of both empirical examples and simulation experiments. Our results show that the bias in estimated impulse responses in a factor‐augmented vector autoregressive (FAVAR) model is positively related to the strength of the error correction mechanism and the cross‐section dimension of the panel. We observe empirically in a large panel of US data that these features have a substantial effect on the responses of several variables to the identified permanent real (productivity) and monetary policy shocks.

  May 03, 2017   doi: 10.1002/jae.2570   open full text
• Identifying relevant and irrelevant variables in sparse factor models.
  Sylvia Kaufmann, Christian Schumacher.
  Journal of Applied Econometrics. April 25, 2017
  This paper considers factor estimation from heterogeneous data, where some of the variables—the relevant ones—are informative for estimating the factors, and others—the irrelevant ones—are not. We estimate the factor model within a Bayesian framework, specifying a sparse prior distribution for the factor loadings. Based on identified posterior factor loading estimates, we provide alternative methods to identify relevant and irrelevant variables. Simulations show that both types of variables are identified quite accurately. Empirical estimates for a large multi‐country GDP dataset and a disaggregated inflation dataset for the USA show that a considerable share of variables is irrelevant for factor estimation.

  April 25, 2017   doi: 10.1002/jae.2566   open full text
• Efficient estimation of factor models with time and cross‐sectional dependence.
  Alexander Heinemann.
  Journal of Applied Econometrics. April 25, 2017
  This paper studies the efficient estimation of large‐dimensional factor models with both time and cross‐sectional dependence assuming (N,T) separability of the covariance matrix. The asymptotic distribution of the estimator of the factor and factor‐loading space under factor stationarity is derived and compared to that of the principal component (PC) estimator. The paper also considers the case when factors exhibit a unit root. We provide feasible estimators and show in a simulation study that they are more efficient than the PC estimator in finite samples. In application, the estimation procedure is employed to estimate the Lee–Carter model and life expectancy is forecast. The Dutch gender gap is explored and the relationship between life expectancy and the level of economic development is examined in a cross‐country comparison.

  April 25, 2017   doi: 10.1002/jae.2571   open full text
• Economies of diversification in the US credit union sector.
  Emir Malikov, Shunan Zhao, Subal C. Kumbhakar.
  Journal of Applied Econometrics. April 21, 2017
  Significant scale economies have been recently cited to rationalize a dramatic growth in the US retail credit union sector over the past few decades. In this paper, we explore another plausible supply‐side explanation for the growth of the industry, namely economies of diversification. We focus on the fact that credit unions differ among themselves in the range of financial services they offer to their members. Since larger credit unions tend to offer a more diversified financial service menu than credit unions of a smaller size, the incentive to grow in size may be fueled not only by present scale economies but also by economies of diversification. This paper provides the first robust estimates of such economies of diversification for the credit union sector. We estimate a flexible semiparametric smooth coefficient quantile panel data model with correlated effects that is capable of accommodating a four‐way heterogeneity among credit unions. Our results indicate the presence of non‐negligible economies of diversification in the industry. We find that as many as 27–91% (depending on the type and the cost quantile) of diversified credit unions enjoy substantial economies of diversification; the cost of most remaining credit unions is invariant to the scope of services. We also find overwhelming evidence of increasing returns to scale in the industry.

  April 21, 2017   doi: 10.1002/jae.2569   open full text
• A discrete‐choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance.
  Lena Boneva, Oliver Linton.
  Journal of Applied Econometrics. April 17, 2017
  What is the effect of funding costs on the conditional probability of issuing a corporate bond? We study this question in a novel dataset covering 5610 issuances by US firms over the period from 1990 to 2014. Identification of this effect is complicated because of unobserved, common shocks such as the global financial crisis. To account for these shocks, we extend the common correlated effects estimator to settings where outcomes are discrete. Both the asymptotic properties and the small‐sample behavior of this estimator are documented. We find that for non‐financial firms yields are negatively related to bond issuance but that the effect is larger in the pre‐crisis period.

  April 17, 2017   doi: 10.1002/jae.2568   open full text
• Model selection with estimated factors and idiosyncratic components.
  Jack Fosten.
  Journal of Applied Econometrics. April 09, 2017
  This paper provides consistent information criteria for the selection of forecasting models that use a subset of both the idiosyncratic and common factor components of a big dataset. This hybrid model approach has been explored by recent empirical studies to relax the strictness of pure factor‐augmented model approximations, but no formal model selection procedures have been developed. The main difference to previous factor‐augmented model selection procedures is that we must account for estimation error in the idiosyncratic component as well as the factors. Our main contribution is to show the conditions required for selection consistency of a class of information criteria that reflect this additional source of estimation error. We show that existing factor‐augmented model selection criteria are inconsistent in circumstances where N is of larger order than T, where N and T are the cross‐section and time series dimensions of the dataset respectively, and that the standard Bayesian information criterion is inconsistent regardless of the relationship between N and T. We therefore propose a new set of information criteria that guarantee selection consistency in the presence of estimated idiosyncratic components. The properties of these new criteria are explored through a Monte Carlo simulation study. The paper concludes with an empirical application to long‐horizon exchange rate forecasting using a recently proposed model with country‐specific idiosyncratic components from a panel of global exchange rates.

  April 09, 2017   doi: 10.1002/jae.2567   open full text
• Real exchange rate persistence and the excess return puzzle: The case of Switzerland versus the US.
  Katarina Juselius, Katrin Assenmacher.
  Journal of Applied Econometrics. February 23, 2017
  The PPP puzzle refers to the wide swings of nominal exchange rates around their long‐run equilibrium values whereas the excess return puzzle represents the persistent deviation of the domestic‐foreign interest rate differential from the expected change in the nominal exchange rate. Using the I(2) cointegrated VAR model, much of the excess return puzzle disappears when an uncertainty premium in the foreign exchange market, proxied by the persistent PPP gap, is introduced. Self‐reinforcing feedback mechanisms seem to cause the persistence in the Swiss‐US parity conditions. These results support imperfect knowledge based expectations rather than so‐called “rational expectations”.

  February 23, 2017   doi: 10.1002/jae.2562   open full text
• Unobserved selection heterogeneity and the gender wage gap.
  Cecilia Machado.
  Journal of Applied Econometrics. February 22, 2017
  Selection correction methods usually make assumptions about selection itself. In the case of gender wage gap estimation, those assumptions are especially tenuous because of high female nonparticipation and because selection could be different in different parts of the labor market. This paper proposes an estimator for the wage gap that allows for arbitrary and unobserved heterogeneity in selection. It applies to the subpopulation of “always employed” women, which is similar to men in labor force characteristics. Using CPS data from 1976 to 2005, I show that the gap has narrowed substantially from a −0.521 to a −0.263 log wage point differential for this population.

  February 22, 2017   doi: 10.1002/jae.2561   open full text
• Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances.
  Leopoldo Catania, Anna Gloria Billé.
  Journal of Applied Econometrics. February 22, 2017
  We propose a new class of models specifically tailored for spatiotemporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and heteroskedastic disturbances, that is, SARAR(1, 1), by exploiting the recent advancements in score‐driven (SD) models typically used in time series econometrics. In particular, we allow for time‐varying spatial autoregressive coefficients as well as time‐varying regressor coefficients and cross‐sectional standard deviations. We report an extensive Monte Carlo simulation study in order to investigate the finite‐sample properties of the maximum likelihood estimator for the new class of models as well as its flexibility in explaining a misspecified dynamic spatial dependence process. The new proposed class of models is found to be economically preferred by rational investors through an application to portfolio optimization.

  February 22, 2017   doi: 10.1002/jae.2565   open full text
• Fat tails and spurious estimation of consumption‐based asset pricing models.
  Alexis Akira Toda, Kieran James Walsh.
  Journal of Applied Econometrics. February 15, 2017
  The standard generalized method of moments (GMM) estimation of Euler equations in heterogeneous‐agent consumption‐based asset pricing models is inconsistent under fat tails because the GMM criterion is asymptotically random. To illustrate this, we generate asset returns and consumption data from an incomplete‐market dynamic general equilibrium model that is analytically solvable and exhibits power laws in consumption. Monte Carlo experiments suggest that the standard GMM estimation is inconsistent and susceptible to Type II errors (incorrect nonrejection of false models). Estimating an overidentified model by dividing agents into age cohorts appears to mitigate Type I and II errors.

  February 15, 2017   doi: 10.1002/jae.2564   open full text
• Monetary Policy and Asset Prices: A Markov‐Switching DSGE Approach.
  Joonyoung Hur.
  Journal of Applied Econometrics. January 11, 2017
  This paper estimates a Markov‐switching dynamic stochastic general equilibrium model by incorporating stock prices in monetary policy rules in order to identify the Federal Reserve's stance toward them. Based on the data from 1984:Q1 to 2009:Q2, I find that historical evidence of the policy reaction toward stock prices is weak except for the stock market bubble of the 1990s. A counterfactual exercise shows that the rapid growth in stock prices during that period would have been significantly higher if monetary policy had been independent of the stock market. However, unconditional macroeconomic volatility increases with the degree of policy responsiveness toward stock prices. Copyright © 2017 John Wiley & Sons, Ltd.

  January 11, 2017   doi: 10.1002/jae.2560   open full text
• The Effectiveness of Non‐Standard Monetary Policy Measures: Evidence from Survey Data.
  Carlo Altavilla, Domenico Giannone.
  Journal of Applied Econometrics. December 15, 2016
  We assess professional forecasters' perceptions of the effects of the unconventional monetary policy measures announced by the US Federal Reserve after the collapse of Lehman Brothers. Using survey data, collected at the individual level, we analyze the change in the forecasts for Treasury and corporate bond yields around the announcement dates of the non‐standard measures. We find that forecasters expected bond yields to drop significantly for at least 1 year after the announcement of accommodative policies. Copyright © 2016 John Wiley & Sons, Ltd.

  December 15, 2016   doi: 10.1002/jae.2559   open full text
• An Empirical Comparison Between the Synthetic Control Method and HSIAO et al.'s Panel Data Approach to Program Evaluation.
  Javier Gardeazabal, Ainhoa Vega‐Bayo.
  Journal of Applied Econometrics. December 04, 2016
  We compare two program evaluation methodologies: the synthetic control method and the panel data approach. We apply both methods to estimate the effect of the political and economic integration of Hong Kong. The results obtained differ depending on the methodology used. We then conduct a simulation that shows that the synthetic control method results in a post‐treatment mean squared error, mean absolute percentage error, and mean error with a smaller interquartile range, whenever there is a good enough match. Copyright © 2016 John Wiley & Sons, Ltd.

  December 04, 2016   doi: 10.1002/jae.2557   open full text
• Have Standard VARS Remained Stable Since the Crisis?
  Knut Are Aastveit, Andrea Carriero, Todd E. Clark, Massimiliano Marcellino.
  Journal of Applied Econometrics. November 10, 2016
  Small vector autoregressions are commonly used in macroeconomics for forecasting and evaluating shock transmission. This requires VAR parameters to be stable over the evaluation and forecast sample or modeled as time‐varying. Prior work has considered whether there were sizable parameter changes in the early 1980s and in the subsequent period until the beginning of the new century. This paper conducts a similar analysis focused on the period since the recent crisis. Using a range of techniques, we provide substantial evidence against parameter stability. The evolution of the unemployment rate seems particularly different relative to its past behavior. We also evaluate alternative methods to handle parameter instability in a forecasting context. Copyright © 2016 John Wiley & Sons, Ltd.

  November 10, 2016   doi: 10.1002/jae.2555   open full text
• Euromind‐ D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area.
  Tommaso Proietti, Martyna Marczak, Gianluigi Mazzi.
  Journal of Applied Econometrics. November 09, 2016
  EuroMInd‐ D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom‐up approach, pooling the density estimates of 11 GDP components, by output and expenditure type. The components' density estimates are obtained from a medium‐size dynamic factor model handling mixed frequencies of observation and ragged‐edged data structures. They reflect both parameter and filtering uncertainty and are obtained by implementing a bootstrap algorithm for simulating from the distribution of the maximum likelihood estimators of the model parameters, and conditional simulation filters for simulating from the predictive distribution of GDP. Both algorithms process the data sequentially as they become available in real time. The GDP density estimates for the output and expenditure approach are combined using alternative weighting schemes and evaluated with different tests based on the probability integral transform and by applying scoring rules. Copyright © 2016 John Wiley & Sons, Ltd.

  November 09, 2016   doi: 10.1002/jae.2556   open full text
• Inference on Self‐Exciting Jumps in Prices and Volatility Using High‐Frequency Measures.
  Worapree Maneesoonthorn, Catherine S. Forbes, Gael M. Martin.
  Journal of Applied Econometrics. November 04, 2016
  Dynamic jumps in the price and volatility of an asset are modelled using a joint Hawkes process in conjunction with a bivariate jump diffusion. A state‐space representation is used to link observed returns, plus nonparametric measures of integrated volatility and price jumps, to the specified model components, with Bayesian inference conducted using a Markov chain Monte Carlo algorithm. An evaluation of marginal likelihoods for the proposed model relative to a large number of alternative models, including some that have featured in the literature, is provided. An extensive empirical investigation is undertaken using data on the S&P 500 market index over the 1996–2014 period, with substantial support for dynamic jump intensities—including in terms of predictive accuracy—documented. Copyright © 2016 John Wiley & Sons, Ltd.

  November 04, 2016   doi: 10.1002/jae.2547   open full text
• Estimating the Competitive Storage Model with Trending Commodity Prices.
  Christophe Gouel, Nicolas Legrand.
  Journal of Applied Econometrics. October 25, 2016
  We present a method to estimate jointly the parameters of a standard commodity storage model and the parameters characterizing the trend in commodity prices. This procedure allows the influence of a possible trend to be removed without restricting the model specification, and allows model and trend selection based on statistical criteria. The trend is modeled deterministically using linear or cubic spline functions of time. The results show that storage models with trend are always preferred to models without trend. They yield more plausible estimates of the structural parameters, with storage costs and demand elasticities that are more consistent with the literature. They imply occasional stockouts, whereas without trend the estimated models predict no stockouts over the sample period for most commodities. Moreover, accounting for a trend in the estimation implies price moments closer to those observed in commodity prices. Our results support the empirical relevance of the speculative storage model, and show that storage model estimations should not neglect the possibility of long‐run price trends. Copyright © 2016 John Wiley & Sons, Ltd.

  October 25, 2016   doi: 10.1002/jae.2553   open full text
• Textual Analysis in Real Estate.
  Adam Nowak, Patrick Smith.
  Journal of Applied Econometrics. October 19, 2016
  This paper incorporates text data from MLS listings into a hedonic pricing model. We show that the comments section of the MLS, which is populated by real estate agents who arguably have the most local market knowledge and know what homebuyers value, provides information that improves the performance of both in‐sample and out‐of‐sample pricing estimates. Text is found to decrease pricing error by more than 25%. Information from text is incorporated into a linear model using a tokenization approach. By doing so, the implicit prices for various words and phrases are estimated. The estimation focuses on simultaneous variable selection and estimation for linear models in the presence of a large number of variables using a penalized regression. The LASSO procedure and variants are shown to outperform least‐squares in out‐of‐sample testing. Copyright © 2016 John Wiley & Sons, Ltd.

  October 19, 2016   doi: 10.1002/jae.2550   open full text
• On the Stability of the Excess Sensitivity of Aggregate Consumption Growth in the USA.
  Gerdie Everaert, Lorenzo Pozzi, Ruben Schoonackers.
  Journal of Applied Econometrics. October 18, 2016
  This paper investigates whether there is time variation in the excess sensitivity of aggregate consumption growth to anticipated aggregate disposable income growth using quarterly US data over the period 1953–2014. Our empirical framework contains the possibility of stickiness in aggregate consumption growth and takes into account measurement error and time aggregation. Our empirical specification is cast into a Bayesian state‐space model and estimated using Markov chain Monte Carlo (MCMC) methods. We use a Bayesian model selection approach to deal with the non‐regular test for the null hypothesis of no time variation in the excess sensitivity parameter. Anticipated disposable income growth is calculated by incorporating an instrumental variables estimation approach into our MCMC algorithm. Our results suggest that the excess sensitivity parameter in the USA is stable at around 0.23 over the entire sample period. Copyright © 2016 John Wiley & Sons, Ltd.

  October 18, 2016   doi: 10.1002/jae.2552   open full text
• Out‐of‐Sample Return Predictability: A Quantile Combination Approach.
  Luiz Renato Lima, Fanning Meng.
  Journal of Applied Econometrics. October 11, 2016
  This paper develops a novel forecasting method that minimizes the effects of weak predictors and estimation errors on the accuracy of equity premium forecasts. The proposed method is based on an averaging scheme applied to quantiles conditional on predictors selected by LASSO. The resulting forecasts outperform the historical average, and other existing models, by statistically and economically meaningful margins. Copyright © 2016 John Wiley & Sons, Ltd.

  October 11, 2016   doi: 10.1002/jae.2549   open full text
• Dynamic Panel Data Models With Irregular Spacing: With an Application to Early Childhood Development.
  Daniel L. Millimet, Ian K. McDonough.
  Journal of Applied Econometrics. October 06, 2016
  With the increased availability of longitudinal data, dynamic panel data models have become commonplace. Moreover, the properties of various estimators of such models are well known. However, we show that these estimators break down when the data are irregularly spaced along the time dimension. Unfortunately, this is an increasingly frequent occurrence as many longitudinal surveys are collected at non‐uniform intervals and no solution is currently available when time‐varying covariates are included in the model. In this paper, we propose two new estimators for dynamic panel data models when data are irregularly spaced and compare their finite‐sample performance to the näive application of existing estimators. We illustrate the practical importance of this issue in an application concerning early childhood development. Copyright © 2016 John Wiley & Sons, Ltd.

  October 06, 2016   doi: 10.1002/jae.2548   open full text
• Using a Structural‐Form Model to Analyze the Impact of Home Ownership on Unemployment Duration.
  Aico Van Vuuren.
  Journal of Applied Econometrics. October 04, 2016
  It is often found that the impact of home ownership on the hazard rate for leaving unemployment is positive, indicating that home ownership helps workers to leave unemployment for a paid job. However, little emphasis has been given to how such a relationship can be explained. This paper estimates a structural‐form model that allows for self‐selection into home ownership and the risk of home owners losing their property during a spell of unemployment. We find a substantial amount of self‐selection using indirect inference based on a mixed proportional hazards‐rate model and find virtually no impact of home ownership on individual labor market performance. Copyright © 2016 John Wiley & Sons, Ltd.

  October 04, 2016   doi: 10.1002/jae.2551   open full text
• Confronting Price Endogeneity in a Duration Model of Residential Subdivision Development.
  Douglas H. Wrenn, H. Allen Klaiber, David A. Newburn.
  Journal of Applied Econometrics. September 26, 2016
  Spatial equilibrium implies that distant factors are correlated with local prices through market mechanisms. Using this logic, we develop a novel approach for handling price endogeneity in land use models. We combine a control function approach with a duration model to identify the impact of prices in influencing land conversion. We find that failure to control for endogeneity results in large differences in elasticities. Specifically, we find an elasticity of 2.06 compared to 0.67 in a model without instrumentation. This difference is significant as it suggests that price‐based policies, such as ‘green taxes’, are likely more effective in altering development patterns than would be expected from a naïve estimation that ignores price endogeneity. Copyright © 2016 John Wiley & Sons, Ltd.

  September 26, 2016   doi: 10.1002/jae.2546   open full text
• Density Forecasts With Midas Models.
  Knut Are Aastveit, Claudia Foroni, Francesco Ravazzolo.
  Journal of Applied Econometrics. September 13, 2016
  We propose a parametric block wild bootstrap approach to compute density forecasts for various types of mixed‐data sampling (MIDAS) regressions. First, Monte Carlo simulations show that predictive densities for the various MIDAS models derived from the block wild bootstrap approach are more accurate in terms of coverage rates than predictive densities derived from either a residual‐based bootstrap approach or by drawing errors from a normal distribution. This result holds whether the data‐generating errors are normally independently distributed, serially correlated, heteroskedastic or a mixture of normal distributions. Second, we evaluate density forecasts for quarterly US real output growth in an empirical exercise, exploiting information from typical monthly and weekly series. We show that the block wild bootstrapping approach, applied to the various MIDAS regressions, produces predictive densities for US real output growth that are well calibrated. Moreover, relative accuracy, measured in terms of the logarithmic score, improves for the various MIDAS specifications as more information becomes available. Copyright © 2016 John Wiley & Sons, Ltd.

  September 13, 2016   doi: 10.1002/jae.2545   open full text
• The Millennium Peak in Club Convergence: A New Look at Distributional Changes in The Wealth of Nations.
  Melanie Krause.
  Journal of Applied Econometrics. August 23, 2016
  This paper proposes an easy‐to‐use nonparametric indicator for club convergence, or convergence within clusters of countries: it measures whether the modes of the gross domestic product (GDP) per capita distribution become more pronounced over time. Relying on changes in the critical bandwidth for unimodality, the indicator is a dynamic extension of concepts from often‐used multimodality tests. Its evolution suggests the new empirical result of a ‘millennium peak’ in club convergence in the worldwide GDP per capita distribution. The club convergence movements of the 1980s and 1990s, when groups of poor and rich countries converged to two separate points, was followed by a de‐clubbing movement after the turn of the millennium. Copyright © 2016 John Wiley & Sons, Ltd.

  August 23, 2016   doi: 10.1002/jae.2542   open full text
• Teacher Quality and Student Achievement: Evidence from a Sample of Dutch Twins.
  Sander Gerritsen, Erik Plug, Dinand Webbink.
  Journal of Applied Econometrics. August 10, 2016
  This paper examines the causal link that runs from classroom quality to student achievement using data on twin pairs who entered the same school but were allocated to different classrooms in an exogenous way. In particular, we apply twin fixed‐effects estimation to assess the effect of teacher quality on student test scores from second through eighth grade of primary education, arguing that a change in teacher quality is probably the most important classroom intervention within a twin context. In a series of estimations using measurable teacher characteristics, we find that (a) the test performance of all students improves with teacher experience; (b) teacher experience also matters for student performance after the initial years in the profession; (c) the teacher experience effect is most prominent in earlier grades; (d) the teacher experience effects are robust to the inclusion of other classroom quality measures, such as peer group composition and class size; and (e) an increase in teacher experience also matters for career stages with less labor market mobility, which suggests positive returns to on‐the‐job learning of teachers. Copyright © 2016 John Wiley & Sons, Ltd.

  August 10, 2016   doi: 10.1002/jae.2539   open full text
• Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion.
  Cem Ertur, Antonio Musolesi.
  Journal of Applied Econometrics. July 21, 2016
  This paper provides an econometric examination of technological knowledge spillovers among countries by focusing on the issue of error cross‐sectional dependence, particularly on the different ways—weak and strong—that this dependence may affect model specification and estimation. A preliminary analysis based on estimation of the exponent of cross‐sectional dependence provides a clear result in favor of strong cross‐sectional dependence. This result has relevant implications in terms of econometric modeling and suggests that a factor structure is preferable to a spatial error model. The common correlated effects approach is then used because it remains valid in a variety of situations that are likely to occur, such as the presence of both forms of dependence or the existence of nonstationary factors. According to the estimation results, richer countries benefit more from domestic R&D and geographic spillovers than poorer countries, while smaller countries benefit more from spillovers originating from trade. The results also suggest that when the problem of (possibly many) correlated unobserved factors is addressed the quantity of education no longer has a significant effect. Finally, a comparison of the results with those obtained from a spatial model provides interesting insights into the bias that may arise when we allow only for weak dependence, despite the presence of strong dependence in the data. Copyright © 2016 John Wiley & Sons, Ltd.

  July 21, 2016   doi: 10.1002/jae.2538   open full text
• Joint Bayesian Analysis of Parameters and States in Nonlinear non‐Gaussian State Space Models.
  István Barra, Lennart Hoogerheide, Siem Jan Koopman, André Lucas.
  Journal of Applied Econometrics. July 17, 2016
  We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear, non‐Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent Metropolis–Hastings algorithm or in importance sampling. Our method provides a computationally more efficient alternative to several recently proposed algorithms. We present extensive simulation evidence for stochastic intensity and stochastic volatility models based on Ornstein–Uhlenbeck processes. For our empirical study, we analyse the performance of our methods for corporate default panel data and stock index returns. Copyright © 2016 John Wiley & Sons, Ltd.

  July 17, 2016   doi: 10.1002/jae.2533   open full text
• Loan Supply Shocks and the Business Cycle.
  Luca Gambetti, Alberto Musso.
  Journal of Applied Econometrics. July 13, 2016
  This paper provides empirical evidence on the role played by loan supply shocks over the business cycle in the euro area, the UK and the USA from 1980 to 2011 by estimating time‐varying parameter vector autoregression models with stochastic volatility and identifying these shocks with sign restrictions consistent with the recent macroeconomic literature. The evidence suggests that in all three economic areas loan supply shocks appear to have a significant effect, with clear signs of an increasing impact over the past few years. Moreover, the role of loan supply shocks is estimated to be particularly important during recessions. Copyright © 2016 John Wiley & Sons, Ltd.

  July 13, 2016   doi: 10.1002/jae.2537   open full text
• Testing for Predictability in panels with General Predictors.
  Joakim Westerlund, Hande Karabiyik, Paresh Narayan.
  Journal of Applied Econometrics. June 29, 2016
  The difficulty of predicting returns has recently motivated researchers to start looking for tests that are either more powerful or robust to more features of the data. Unfortunately, the way that these tests work typically involves trading robustness for power or vice versa. The current paper takes this as its starting point to develop a new panel‐based approach to predictability that is both robust and powerful. Specifically, while the panel route to increased power is not new, the way in which the cross‐section variation is exploited also to achieve robustness with respect to the predictor is. The result is two new tests that enable asymptotically standard normal and chi‐squared inference across a wide range of empirically relevant scenarios in which the predictor may be stationary, moderately non‐stationary, nearly non‐stationary, or indeed unit root non‐stationary. The type of cross‐section dependence that can be permitted in the predictor is also very general, and can be weak or strong, although we do require that the cross‐section dependence in the regression errors is of the strong form. What is more, this generality comes at no cost in terms of complicated test construction. The new tests are therefore very user‐friendly. Copyright © 2016 John Wiley & Sons, Ltd.

  June 29, 2016   doi: 10.1002/jae.2535   open full text
• Granger Causality and Regime Inference in Markov Switching VAR Models with Bayesian Methods.
  Matthieu Droumaguet, Anders Warne, Tomasz Woźniak.
  Journal of Applied Econometrics. June 27, 2016
  In this paper, we derive restrictions for Granger noncausality in MS‐VAR models and show under what conditions a variable does not affect the forecast of the hidden Markov process. To assess the noncausality hypotheses, we apply Bayesian inference. The computational tools include a novel block Metropolis–Hastings sampling algorithm for the estimation of the underlying models. We analyze a system of monthly US data on money and income. The results of testing in MS‐VARs contradict those obtained with linear VARs: the money aggregate M1 helps in forecasting industrial production and in predicting the next period's state. Copyright © 2016 John Wiley & Sons, Ltd.

  June 27, 2016   doi: 10.1002/jae.2531   open full text
• Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes.
  Roman Liesenfeld, Jean‐François Richard, Jan Vogler.
  Journal of Applied Econometrics. June 27, 2016
  We develop a panel count model with a latent spatio‐temporal heterogeneous state process for monthly severe crimes at the census‐tract level in Pittsburgh, Pennsylvania. Our dataset combines Uniform Crime Reporting data with socio‐economic data. The likelihood is estimated by efficient importance sampling techniques for high‐dimensional spatial models. Estimation results confirm the broken‐windows hypothesis whereby less severe crimes are leading indicators for severe crimes. In addition to ML parameter estimates, we compute several other statistics of interest for law enforcement such as spatio‐temporal elasticities of severe crimes with respect to less severe crimes, out‐of‐sample forecasts, predictive distributions and validation test statistics. Copyright © 2016 John Wiley & Sons, Ltd.

  June 27, 2016   doi: 10.1002/jae.2534   open full text
• MM Algorithm for General Mixed Multinomial Logit Models.
  Jonathan James.
  Journal of Applied Econometrics. June 20, 2016
  This paper develops a new technique for estimating mixed logit models with a simple minorization–maximization (MM) algorithm. The algorithm requires minimal coding and is easy to implement for a variety of mixed logit models. Most importantly, the algorithm has a very low cost per iteration relative to current methods, producing substantial computational savings. In addition, the method is asymptotically consistent, efficient and globally convergent. Copyright © 2016 John Wiley & Sons, Ltd.

  June 20, 2016   doi: 10.1002/jae.2532   open full text
• Empirical Bayesball Remixed: Empirical Bayes Methods for Longitudinal Data.
  Jiaying Gu, Roger Koenker.
  Journal of Applied Econometrics. June 20, 2016
  Empirical Bayes methods for Gaussian and binomial compound decision problems involving longitudinal data are considered. A recent convex optimization reformulation of the nonparametric maximum likelihood estimator of Kiefer and Wolfowitz (Annals of Mathematical Statistics 1956; 27: 887–906) is employed to construct nonparametric Bayes rules for compound decisions. The methods are illustrated with an application to predict baseball batting averages, and the age profile of batting performance. An important aspect of the empirical application is the general bivariate specification of the distribution of heterogeneous location and scale effects for players that exhibits a weak positive association between location and scale attributes. Prediction of players' batting averages for 2012 based on performance in the prior decade using the proposed methods shows substantially improved performance over more naive methods with more restrictive treatment of unobserved heterogeneity. Comparisons are also made with nonparametric Bayesian methods based on Dirichlet process priors, which can be viewed as a regularized, or smoothed, version of the Kiefer–Wolfowitz method. Copyright © 2016 John Wiley & Sons, Ltd.

  June 20, 2016   doi: 10.1002/jae.2530   open full text
• Tests of Predictive Ability for Vector Autoregressions Used for Conditional Forecasting.
  Todd E. Clark, Michael W. McCracken.
  Journal of Applied Econometrics. June 14, 2016
  Many forecasts are conditional in nature. For example, a number of central banks routinely report forecasts conditional on particular paths of policy instruments. Even though conditional forecasting is common, there has been little work on methods for evaluating conditional forecasts. This paper provides analytical, Monte Carlo and empirical evidence on tests of predictive ability for conditional forecasts from estimated models. In the empirical analysis, we examine conditional forecasts obtained with a VAR in the variables included in the DSGE model of Smets and Wouters (American Economic Review 2007; 97: 586–606). Throughout the analysis, we focus on tests of bias, efficiency and equal accuracy applied to conditional forecasts from VAR models. Copyright © 2016 John Wiley & Sons, Ltd.

  June 14, 2016   doi: 10.1002/jae.2529   open full text
• Skewness Risk and Bond Prices.
  Francisco Ruge‐Murcia.
  Journal of Applied Econometrics. May 26, 2016
  This paper uses extreme value theory to study the implications of skewness risk for nominal loan contracts in a production economy. Productivity and inflation innovations are drawn from generalized extreme value distributions. The model is solved using a third‐order perturbation and estimated by the simulated method of moments. Results show that the data reject the hypothesis that innovations are drawn from normal distributions and favor instead the alternative that they are drawn from asymmetric distributions. Estimates indicate that skewness risk accounts for 12% of the risk premia and reduces bond yields by approximately 55 basis points. For a bond that pays 1 dollar at maturity, the adjustment factor associated with skewness risk ranges from 0.15 cents for a 3‐month bond to 2.05 cents for a 5‐year bond. Copyright © 2016 John Wiley & Sons, Ltd.

  May 26, 2016   doi: 10.1002/jae.2528   open full text
• Conventional Monetary Policy Transmission During Financial Crises: An Empirical Analysis.
  Tatjana Dahlhaus.
  Journal of Applied Econometrics. May 23, 2016
  This paper studies the effects of a conventional monetary policy shock in the USA during times of high financial stress. The analysis is carried out by introducing a smooth transition factor model where the transition between states (‘normal’ and high financial stress) depends on a financial conditions index. Employing a quarterly dataset over the period 1970:Q1 to 2008:Q4 containing 108 US macroeconomic and financial time series, I find that a monetary policy shock during periods of high financial stress has stronger and more persistent effects on macroeconomic variables such as output, consumption and investment than it has during ‘normal’ times. Differences in effects among the regimes seem to originate from nonlinearities in both components of the credit channel, i.e. the balance sheet channel and the bank‐lending channel. Copyright © 2016 John Wiley & Sons, Ltd.

  May 23, 2016   doi: 10.1002/jae.2524   open full text
• Spotting the Danger Zone: Forecasting Financial Crises With Classification Tree Ensembles and Many Predictors.
  Felix Ward.
  Journal of Applied Econometrics. May 18, 2016
  This paper introduces classification tree ensembles (CTEs) to the banking crisis forecasting literature. I show that CTEs substantially improve out‐of‐sample forecasting performance over best‐practice early‐warning systems. CTEs enable policymakers to correctly forecast 80% of crises with a 20% probability of incorrectly forecasting a crisis. These findings are based on a long‐run sample (1870–2011), and two broad post‐1970 samples which together cover almost all known systemic banking crises. I show that the marked improvement in forecasting performance results from the combination of many classification trees into an ensemble, and the use of many predictors. Copyright © 2016 John Wiley & Sons, Ltd.

  May 18, 2016   doi: 10.1002/jae.2525   open full text
• Average and Marginal Returns to Upper Secondary Schooling in Indonesia.
  Pedro Carneiro, Michael Lokshin, Nithin Umapathi.
  Journal of Applied Econometrics. May 18, 2016
  This paper estimates average and marginal returns to schooling in Indonesia using a semiparametric selection model. Identification of the model is given by geographic variation in access to upper secondary schools. We find that the return to upper secondary schooling varies widely across individuals: it can be as high as 50% per year of schooling for those very likely to enroll in upper secondary schooling, or as low as −10% for those very unlikely to do so. Average returns for the student at the margin are substantial, but they are also well below those for the average student attending upper secondary schooling. Copyright © 2016 John Wiley & Sons, Ltd.

  May 18, 2016   doi: 10.1002/jae.2523   open full text
• Estimation and Solution of Models with Expectations and Structural Changes.
  Mariano Kulish, Adrian Pagan.
  Journal of Applied Econometrics. May 16, 2016
  In this paper, we develop solutions for linearized models with forward‐looking expectations and structural changes under a variety of assumptions regarding agents' beliefs about those structural changes. For each solution, we show how its associated likelihood function can be constructed by using a ‘backward–forward’ algorithm. We illustrate the techniques with two examples. The first considers an inflationary program in which beliefs about the inflation target evolve differently from the inflation target itself, and the second applies the techniques to estimate a new Keynesian model through the Volcker disinflation. We compare our methodology with the alternative in which structural change is captured by switching between regimes via a Markov switching process. We show that our method can produce accurate results much faster than the Markov switching method as well as being easily adapted to handle beliefs departing from reality. Copyright © 2016 John Wiley & Sons, Ltd.

  May 16, 2016   doi: 10.1002/jae.2527   open full text
• Forecasting With the Standardized Self‐Perturbed Kalman Filter.
  Stefano Grassi, Nima Nonejad, Paolo Santucci De Magistris.
  Journal of Applied Econometrics. April 28, 2016
  We propose and study the finite‐sample properties of a modified version of the self‐perturbed Kalman filter of Park and Jun (Electronics Letters 1992; 28: 558–559) for the online estimation of models subject to parameter instability. The perturbation term in the updating equation of the state covariance matrix is weighted by the estimate of the measurement error variance. This avoids the calibration of a design parameter as the perturbation term is scaled by the amount of uncertainty in the data. It is shown by Monte Carlo simulations that this perturbation method is associated with a good tracking of the dynamics of the parameters compared to other online algorithms and to classical and Bayesian methods. The standardized self‐perturbed Kalman filter is adopted to forecast the equity premium on the S&P 500 index under several model specifications, and determines the extent to which realized variance can be used to predict excess returns. Copyright © 2016 John Wiley & Sons, Ltd.

  April 28, 2016   doi: 10.1002/jae.2522   open full text
• Global Credit Risk: World, Country and Industry Factors.
  Bernd Schwaab, Siem Jan Koopman, André Lucas.
  Journal of Applied Econometrics. April 20, 2016
  We investigate the dynamic properties of systematic default risk conditions for firms in different countries, industries and rating groups. We use a high‐dimensional nonlinear non‐Gaussian state‐space model to estimate common components in corporate defaults in a 41 country samples between 1980:Q1 and s2014:Q4, covering both the global financial crisis and euro area sovereign debt crisis. We find that macro and default‐specific world factors are a primary source of default clustering across countries. Defaults cluster more than what shared exposures to macro factors imply, indicating that other factors also play a significant role. For all firms, deviations of systematic default risk from macro fundamentals are correlated with net tightening bank lending standards, suggesting that bank credit supply and systematic default risk are inversely related. Copyright © 2016 John Wiley & Sons, Ltd.

  April 20, 2016   doi: 10.1002/jae.2521   open full text
• Modeling Financial Sector Joint Tail Risk in the Euro Area.
  André Lucas, Bernd Schwaab, Xin Zhang.
  Journal of Applied Econometrics. April 12, 2016
  We develop a novel high‐dimensional non‐Gaussian modeling framework to infer measures of conditional and joint default risk for numerous financial sector firms. The model is based on a dynamic generalized hyperbolic skewed‐t block equicorrelation copula with time‐varying volatility and dependence parameters that naturally accommodates asymmetries and heavy tails, as well as nonlinear and time‐varying default dependence. We apply a conditional law of large numbers in this setting to define joint and conditional risk measures that can be evaluated quickly and reliably. We apply the modeling framework to assess the joint risk from multiple defaults in the euro area during the 2008–2012 financial and sovereign debt crisis. We document unprecedented tail risks between 2011 and 2012, as well as their steep decline following subsequent policy actions. Copyright © 2016 John Wiley & Sons, Ltd.

  April 12, 2016   doi: 10.1002/jae.2518   open full text
• Penalized Quantile Regression with Semiparametric Correlated Effects: An Application with Heterogeneous Preferences.
  Matthew Harding, Carlos Lamarche.
  Journal of Applied Econometrics. April 07, 2016
  This paper proposes new ℓ1‐penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. Existing fixed‐effects estimators can potentially suffer from three limitations which are overcome by the proposed approach: (i) incidental parameters bias in nonlinear models with large N and small T; (ii) lack of efficiency; and (iii) inability to estimate the effects of time‐invariant regressors. We conduct Monte Carlo simulations to assess the small‐sample performance of the new estimators and provide comparisons of new and existing penalized estimators in terms of quadratic loss. We apply the technique to an empirical example of the estimation of consumer preferences for nutrients from a demand model using a large transaction‐level dataset of household food purchases. We show that preferences for nutrients vary across the conditional distribution of expenditure and across genders, and emphasize the importance of fully capturing consumer heterogeneity in demand modeling. Copyright © 2016 John Wiley & Sons, Ltd.

  April 07, 2016   doi: 10.1002/jae.2520   open full text
• Absenteeism, Gender and the Morbidity–Mortality Paradox.
  Daniel Avdic, Per Johansson.
  Journal of Applied Econometrics. April 05, 2016
  Women are, on average, more often absent from work for health reasons than men, but live longer. This conflicting pattern suggests that the gender absenteeism gap arises partly from factors unrelated to objective health. An overlooked explanation is that men and women might have different preferences for absenteeism due to different attitudes to, for example, risk. Using detailed administrative data on absenteeism, hospitalizations, and mortality, we evaluate the existence of gender‐specific preferences for absenteeism and analyze whether these differences are socially determined. We find robust evidence of gender differences in absenteeism that cannot be explained by poorer objective health among women. Copyright © 2016 John Wiley & Sons, Ltd.

  April 05, 2016   doi: 10.1002/jae.2516   open full text
• Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice.
  Laurent A. F. Callot, Anders B. Kock, Marcelo C. Medeiros.
  Journal of Applied Econometrics. March 31, 2016
  We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso‐type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast realized covariance matrices almost as precisely as if we had known the true driving dynamics of these in advance. We next investigate the sources of these driving dynamics as well as the performance of the proposed models for forecasting the realized covariance matrices of the 30 Dow Jones stocks. We find that the dynamics are not stable as the data are aggregated from the daily to lower frequencies. Furthermore, we are able beat our benchmark by a wide margin. Finally, we investigate the economic value of our forecasts in a portfolio selection exercise and find that in certain cases an investor is willing to pay a considerable amount in order get access to our forecasts. Copyright © 2016 John Wiley & Sons, Ltd.

  March 31, 2016   doi: 10.1002/jae.2512   open full text
• In Search of the Transmission Mechanism of Fiscal Policy in the Euro Area.
  Patrick Fève, Jean‐Guillaume Sahuc.
  Journal of Applied Econometrics. March 31, 2016
  This paper applies the DSGE‐VAR methodology to assess the size of fiscal multipliers in the data and the relative contributions of two transmission mechanisms of government spending shocks, namely hand‐to‐mouth consumers and Edgeworth complementarity. Econometric experiments show that a DSGE model with Edgeworth complementarity is a better representation of the transmission mechanism of fiscal policy as it yields dynamic responses close to those obtained with the flexible DSGE‐VAR model (i.e. an impact output multiplier larger than one and a crowding‐in of private consumption). The estimated share of hand‐to‐mouth consumers is too small to replicate the positive response of private consumption. Copyright © 2016 John Wiley & Sons, Ltd.

  March 31, 2016   doi: 10.1002/jae.2517   open full text
• How to Identify and Forecast Bull and Bear Markets?
  Erik Kole, Dick Dijk.
  Journal of Applied Econometrics. March 22, 2016
  Because the state of the equity market is latent, several methods have been proposed to identify past and current states of the market and forecast future ones. These methods encompass semi‐parametric rule‐based methods and parametric Markov switching models. We compare the mean‐variance utilities that result when a risk‐averse agent uses the predictions of the different methods in an investment decision. Our application of this framework to the S&P 500 shows that rule‐based methods are preferable for (in‐sample) identification of the state of the market, but Markov switching models for (out‐of‐sample) forecasting. In‐sample, only the mean return of the market index matters, which rule‐based methods exactly capture. Because Markov switching models use both the mean and the variance to infer the state, they produce superior forecasts and lead to significantly better out‐of‐sample performance than rule‐based methods. We conclude that the variance is a crucial ingredient for forecasting the market state. Copyright © 2016 John Wiley & Sons, Ltd.

  March 22, 2016   doi: 10.1002/jae.2511   open full text
• Forecasting Tail Risks.
  Gianni De Nicolò, Marcella Lucchetta.
  Journal of Applied Econometrics. March 17, 2016
  This paper presents an early warning system as a set of multi‐period forecasts of indicators of tail real and financial risks obtained using a large database of monthly US data for the period 1972:1–2014:12. Pseudo‐real‐time forecasts are generated from: (a) sets of autoregressive and factor‐augmented vector autoregressions (VARs), and (b) sets of autoregressive and factor‐augmented quantile projections. Our key finding is that forecasts obtained with AR and factor‐augmented VAR forecasts significantly underestimate tail risks, while quantile projections deliver fairly accurate forecasts and reliable early warning signals for tail real and financial risks up to a 1‐year horizon. Copyright © 2016 John Wiley & Sons, Ltd.

  March 17, 2016   doi: 10.1002/jae.2509   open full text
• State Prices of Conditional Quantiles: New Evidence on Time Variation in the Pricing Kernel.
  Konstantinos Metaxoglou, Aaron Smith.
  Journal of Applied Econometrics. March 01, 2016
  We develop a set of statistics to represent the option‐implied stochastic discount factor and we apply them to S&P 500 returns between 1990 and 2012. Our statistics, which we call state prices of conditional quantiles (SPOCQ), estimate the market's willingness to pay for insurance against outcomes in various quantiles of the return distribution. By estimating state prices at conditional quantiles, we separate variation in the shape of the pricing kernel from variation in the probability of a particular event. Thus, without imposing strong assumptions about the distribution of returns, we obtain a novel view of pricing‐kernel dynamics. We document six features of SPOCQ for the S&P 500. Most notably, and in contrast to recent studies, we find that the price of downside risk decreases when volatility increases. Under a standard asset pricing model, this result implies that most changes in volatility stem from fluctuations in idiosyncratic risk. Consistent with this interpretation, no known systematic risk factors such as consumer sentiment, liquidity or macroeconomic risk can account for the negative relationship between the price of downside risk and volatility. Copyright © 2016 John Wiley & Sons, Ltd.

  March 01, 2016   doi: 10.1002/jae.2515   open full text
• Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump.
  Christiane Baumeister, Lutz Kilian, Thomas K. Lee.
  Journal of Applied Econometrics. March 01, 2016
  Appropriate real‐time forecasting models for the US retail price of gasoline yield substantial reductions in the mean‐squared prediction error (MSPE) at horizons up to 2 years as well as substantial increases in directional accuracy. Even greater MSPE reductions are possible by constructing a pooled forecast that assigns equal weight to five of the most successful forecasting models. Pooled forecasts have lower MSPE than the US Energy Information Administration gasoline price forecasts and the gasoline price expectations in the Michigan Survey of Consumers. We also show that as much as 39% of the decline in gas prices between June and December 2014 was predictable. Copyright © 2016 John Wiley & Sons, Ltd.

  March 01, 2016   doi: 10.1002/jae.2510   open full text
• Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models.
  Anders Warne, Günter Coenen, Kai Christoffel.
  Journal of Applied Econometrics. February 28, 2016
  The predictive likelihood is useful for ranking models in forecast comparison exercises using Bayesian inference. We discuss how it can be estimated, by means of marzginalization, for any subset of the observables in linear Gaussian state‐space models. We compare macroeconomic density forecasts for the euro area of a DSGE model to those of a DSGE‐VAR, a BVAR and a multivariate random walk over 1999:Q1–2011:Q4. While the BVAR generally provides superior forecasts, its performance deteriorates substantially with the onset of the Great Recession. This is particularly notable for longer‐horizon real GDP forecasts, where the DSGE and DSGE‐VAR models perform better. Copyright © 2016 John Wiley & Sons, Ltd.

  February 28, 2016   doi: 10.1002/jae.2514   open full text
• Bubbles and Crises: The Role of House Prices and Credit.
  André K. Anundsen, Karsten Gerdrup, Frank Hansen, Kasper Kragh‐Sørensen.
  Journal of Applied Econometrics. February 21, 2016
  This paper utilizes quarterly panel data for 20 OECD countries over the period 1975:Q1–2014:Q2 to explore the importance of house prices and credit in affecting the likelihood of a financial crisis. Estimating a set of multivariate logit models, we find that booms in credit to both households and non‐financial enterprises are important to account for when evaluating the stability of the financial system. In addition, we find that global housing market developments have predictive power for domestic financial stability. Finally, econometric measures of bubble‐like behavior in housing and credit markets enter with positive and highly significant coefficients. Specifically, we find that the probability of a crisis increases markedly when bubble‐like behavior in house prices coincides with high household leverage. Copyright © 2016 John Wiley & Sons, Ltd.

  February 21, 2016   doi: 10.1002/jae.2503   open full text
• Wild Bootstrap Inference for Wildly Different Cluster Sizes.
  James G. Mackinnon, Matthew D. Webb.
  Journal of Applied Econometrics. February 21, 2016
  The cluster robust variance estimator (CRVE) relies on the number of clusters being sufficiently large. Monte Carlo evidence suggests that the ‘rule of 42’ is not true for unbalanced clusters. Rejection frequencies are higher for datasets with 50 clusters proportional to US state populations than with 50 balanced clusters. Using critical values based on the wild cluster bootstrap performs much better. However, this procedure fails when a small number of clusters is treated. We explain why CRVE t statistics and the wild bootstrap fail in this case, study the ‘effective number’ of clusters and simulate placebo laws with dummy variable regressors. Copyright © 2016 John Wiley & Sons, Ltd.

  February 21, 2016   doi: 10.1002/jae.2508   open full text
• Transitions at Different Moments in Time: A Spatial Probit Approach.
  J. Paul Elhorst, Pim Heijnen, Anna Samarina, Jan P. A. M. Jacobs.
  Journal of Applied Econometrics. February 16, 2016
  This paper adopts a spatial probit approach to explain interaction effects among cross‐sectional units when the dependent variable takes the form of a binary response variable and transitions from state 0 to 1 occur at different moments in time. The model has two spatially lagged variables: one for units that are still in state 0 and one for units that had already transferred to state 1. The parameters are estimated on observations for those units that are still in state 0 at the start of the different time periods, whereas observations on units after they transferred to state 1 are discarded, just as in the literature on duration modeling. Furthermore, neighboring units that had not yet transferred may have a different impact from units that had already transferred. We illustrate our approach with an empirical study of the adoption of inflation targeting for a sample of 58 countries over the period 1985–2008. Copyright © 2016 John Wiley & Sons, Ltd.

  February 16, 2016   doi: 10.1002/jae.2505   open full text
• Estimation of Poverty Transition Matrices with Noisy Data.
  Nayoung Lee, Geert Ridder, John Strauss.
  Journal of Applied Econometrics. February 15, 2016
  This paper investigates measurement error biases in estimated poverty transition matrices. We compare transition matrices based on survey expenditure data to transition matrices based on measurement‐error‐free simulated expenditure. The simulation model uses estimates that correct for measurement error in expenditure. We find that time‐varying measurement error in expenditure data magnifies economic mobility. Roughly 45% of households initially in poverty at time t − 1 are found to be out of poverty at time t using data from the Korean Labor and Income Panel Study. When measurement error is removed, this drops to between 26 and 31% of households initially in poverty. Copyright © 2016 John Wiley & Sons, Ltd.

  February 15, 2016   doi: 10.1002/jae.2506   open full text
• Forecasting with Global Vector Autoregressive Models: a Bayesian Approach.
  Jesús Crespo Cuaresma, Martin Feldkircher, Florian Huber.
  Journal of Applied Econometrics. February 11, 2016
  This paper develops a Bayesian variant of global vector autoregressive (B‐GVAR) models to forecast an international set of macroeconomic and financial variables. We propose a set of hierarchical priors and compare the predictive performance of B‐GVAR models in terms of point and density forecasts for one‐quarter‐ahead and four‐quarter‐ahead forecast horizons. We find that forecasts can be improved by employing a global framework and hierarchical priors which induce country‐specific degrees of shrinkage on the coefficients of the GVAR model. Forecasts from various B‐GVAR specifications tend to outperform forecasts from a naive univariate model, a global model without shrinkage on the parameters and country‐specific vector autoregressions. Copyright © 2016 John Wiley & Sons, Ltd.

  February 11, 2016   doi: 10.1002/jae.2504   open full text
• Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov‐Switching VAR Model.
  Monica Billio, Roberto Casarin, Francesco Ravazzolo, Herman K. Van Dijk.
  Journal of Applied Econometrics. January 21, 2016
  The proposed panel Markov‐switching VAR model accommodates changes in low and high data frequencies and incorporates endogenous time‐varying transition matrices of country‐specific Markov chains, allowing for interconnections. An efficient multi‐move sampling algorithm draws time‐varying Markov‐switching chains. Using industrial production growth and credit spread data, several important data features are obtained. Three regimes appear, with slow growth becoming persistent in the eurozone. Turning point analysis indicates the USA leading the eurozone cycle. Amplification effects influence recession probabilities for Eurozone countries. A credit shock results in temporary negative industrial production growth in Germany, Spain and the USA. Core and peripheral countries exist in the eurozone. Copyright © 2016 John Wiley & Sons, Ltd.

  January 21, 2016   doi: 10.1002/jae.2501   open full text
• Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand.
  John Coglianese, Lucas W. Davis, Lutz Kilian, James H. Stock.
  Journal of Applied Econometrics. January 21, 2016
  Least‐squares estimates of the response of gasoline consumption to a change in the gasoline price are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. Gasoline buyers increase purchases before tax increases and delay purchases before tax decreases, rendering the tax instrument endogenous. Including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower elasticity estimates. Copyright © 2016 John Wiley & Sons, Ltd.

  January 21, 2016   doi: 10.1002/jae.2500   open full text
• Optimal Portfolio Choice Under Decision‐Based Model Combinations.
  Davide Pettenuzzo, Francesco Ravazzolo.
  Journal of Applied Econometrics. January 18, 2016
  We propose a density combination approach featuring combination weights that depend on the past forecast performance of the individual models entering the combination through a utility‐based objective function. We apply this model combination scheme to forecast stock returns, both at the aggregate level and by industry, and investigate its forecasting performance relative to a host of existing combination methods, both within the class of linear and time‐varying coefficients, stochastic volatility models. Overall, we find that our combination scheme produces markedly more accurate predictions than the existing alternatives, both in terms of statistical and economic measures of out‐of‐sample predictability. Copyright © 2016 John Wiley & Sons, Ltd.

  January 18, 2016   doi: 10.1002/jae.2502   open full text
• Time Variation in Macro‐Financial Linkages.
  Esteban Prieto, Sandra Eickmeier, Massimiliano Marcellino.
  Journal of Applied Econometrics. January 11, 2016
  We analyze the contribution of credit spread, house and stock price shocks to the US economy based on a time‐varying parameter vector autoregressive model. We find that the contribution of financial shocks to gross domestic product growth fluctuates from about 20% in normal times to more than 50% during the Great Recession. The Great Recession and the subsequent weak recovery can largely be traced back to negative housing shocks. Housing shocks have become more important for the real economy since the early 2000s, and negative housing shocks are more important than positive ones. Unexpected increases in credit spreads have not been deflationary recently. Copyright © 2016 John Wiley & Sons, Ltd.

  January 11, 2016   doi: 10.1002/jae.2499   open full text
• Noncausal Bayesian Vector Autoregression.
  Markku Lanne, Jani Luoto.
  Journal of Applied Econometrics. January 08, 2016
  We consider Bayesian analysis of the noncausal vector autoregressive model that is capable of capturing nonlinearities and effects of missing variables. Specifically, we devise a fast and reliable posterior simulator that yields the predictive distribution as a by‐product. We apply the methods to postwar US inflation and GDP growth. The noncausal model is found superior in terms of both in‐sample fit and out‐of‐sample forecasting performance over its conventional causal counterpart. Economic shocks based on the noncausal model turn out to be highly anticipated in advance. We also find the GDP growth to have predictive power for future inflation, but not vice versa. Copyright © 2016 John Wiley & Sons, Ltd.

  January 08, 2016   doi: 10.1002/jae.2497   open full text
• Mismatch Shocks and Unemployment During the Great Recession.
  Francesco Furlanetto, Nicolas Groshenny.
  Journal of Applied Econometrics. January 08, 2016
  We investigate the macroeconomic consequences of fluctuations in the effectiveness of the labor market matching process with a focus on the Great Recession. We conduct our analysis in the context of an estimated medium‐scale dynamic stochastic general equilibrium model with sticky prices and equilibrium search unemployment that features a shock to the matching efficiency (or mismatch shock). We find that this shock is not important for unemployment fluctuations in normal times. However, it plays a somewhat larger role during the Great Recession when it contributes to raise the actual unemployment rate by around 1.3 percentage points and the natural rate by around 2 percentage points. The mismatch shock is the dominant driver of the natural rate of unemployment and explains part of the recent shift of the Beveridge curve. Copyright © 2016 John Wiley & Sons, Ltd.

  January 08, 2016   doi: 10.1002/jae.2498   open full text
• Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors.
  Kajal Lahiri, George Monokroussos, Yongchen Zhao.
  Journal of Applied Econometrics. November 27, 2015
  We study the role of consumer confidence in forecasting real personal consumption expenditure, and contribute to the extant literature in three substantive ways. First, we re‐examine existing empirical models of consumption and consumer confidence, not only at the quarterly frequency, but using monthly data as well. Second, we employ real‐time data in addition to commonly used revised vintages. Third, we investigate the role of consumer confidence in a rich information context. We produce forecasts of consumption expenditures with and without consumer confidence measures using a dynamic factor model and a large, real‐time, jagged‐edge dataset. In a robust way, we establish the important role of confidence surveys in improving the accuracy of consumption forecasts, manifesting primarily through the services component. During the recession of 2007–2009, sentiment is found to have a more pervasive effect on all components of aggregate consumption: durables, non‐durables and services. Copyright © 2015 John Wiley & Sons, Ltd.

  November 27, 2015   doi: 10.1002/jae.2494   open full text
• Nonlinear Granger Causality: Guidelines for Multivariate Analysis.
  Cees Diks, Marcin Wolski.
  Journal of Applied Econometrics. November 27, 2015
  We propose an extension of the bivariate nonparametric Diks–Panchenko Granger non‐causality test to multivariate settings. We first show that the asymptotic theory for the bivariate test fails to apply to the multivariate case, because the kernel density estimator bias and variance cannot both tend to zero at a sufficiently fast rate. To overcome this difficulty we propose to reduce the order of the bias by applying data sharpening prior to calculating the test statistic. We derive the asymptotic properties of the ‘sharpened’ test statistic and investigate its performance numerically. We conclude with an empirical application to the US grain market, using the price of futures on heating degree days as an additional conditioning variable. Copyright © 2015 John Wiley & Sons, Ltd.

  November 27, 2015   doi: 10.1002/jae.2495   open full text
• A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of us Banks in 2001–2010.
  Emir Malikov, Subal C. Kumbhakar, Mike G. Tsionas.
  Journal of Applied Econometrics. November 26, 2015
  This paper offers a methodology to address the endogeneity of inputs in the directional technology distance function (DTDF)‐based formulation of banking technology which explicitly accommodates the presence of undesirable nonperforming loans—an inherent characteristic of the bank's production due to its exposure to credit risk. Specifically, we model nonperforming loans as an undesirable output in the bank's production process. Since the stochastic DTDF describing banking technology is likely to suffer from the endogeneity of inputs, we propose addressing this problem by considering a system consisting of the DTDF and the first‐order conditions from the bank's cost minimization problem. The first‐order conditions also allow us to identify the ‘cost‐optimal’ directional vector for the banking DTDF, thus eliminating the uncertainty associated with an ad hoc choice of the direction. We apply our cost system approach to the data on large US commercial banks for the 2001–2010 period, which we estimate via Bayesian Markov chain Monte Carlo methods subject to theoretical regularity conditions. We document dramatic distortions in banks' efficiency, productivity growth and scale elasticity estimates when the endogeneity of inputs is assumed away and/or the DTDF is fitted in an arbitrary direction. Copyright © 2015 John Wiley & Sons, Ltd.

  November 26, 2015   doi: 10.1002/jae.2491   open full text
• On the Importance of Sectoral and Regional Shocks for Price‐Setting.
  Guenter W. Beck, Kirstin Hubrich, Massimiliano Marcellino.
  Journal of Applied Econometrics. November 12, 2015
  We use novel disaggregate sectoral‐regional euro‐area data to investigate the sources of price changes, introducing a new method to extract factors from overlapping data blocks that allows for estimation of aggregate, sectoral, country‐specific and regional components of price changes. Our sectoral component explains much less variation in disaggregate inflation rates and exhibits much less volatility and more persistence than previous findings for the US indicate. Country‐ and region‐specific factors play an important role, emphasizing heterogeneity of inflation dynamics along both sectoral and geographical dimensions. Our results are incompatible with basic sticky‐information or Calvo‐type price‐setting models, but require multi‐sector, multi‐country models. Copyright © 2015 John Wiley & Sons, Ltd.

  November 12, 2015   doi: 10.1002/jae.2490   open full text
• Identification and Estimation of Online Price Competition With an Unknown Number of Firms.
  Yonghong An, Michael R. Baye, Yingyao Hu, John Morgan, Matt Shum.
  Journal of Applied Econometrics. November 09, 2015
  This paper considers identification and estimation of a general model for online price competition. We show that when the number of competing firms is unknown the underlying parameters of the model can still be identified and estimated employing recently developed results on measurement errors. We illustrate our methodology using UK data for personal digital assistants and employ the estimates to simulate competitive effects. Our results reveal that heightened competition has differential effects on the prices paid by different consumer segments. Copyright © 2015 John Wiley & Sons, Ltd.

  November 09, 2015   doi: 10.1002/jae.2492   open full text
• Combining Time Variation and Mixed Frequencies: an Analysis of Government Spending Multipliers in Italy.
  Jacopo Cimadomo, Antonello D'Agostino.
  Journal of Applied Econometrics. November 09, 2015
  In this paper, we propose a time‐varying parameter vector autoregression (VAR) model with stochastic volatility which allows for estimation on data sampled at different frequencies. Our contribution is twofold. First, we extend the methodology developed by Cogley and Sargent (Drifts and volatilities: monetary policies and outcomes in the post WWII U.S. Review of Economic Studies 2005; 8: 262–302) and Primiceri (Time varying structural vector autoregressions and monetary policy. Review of Economic Studies 2005; 72: 821–852) to a mixed‐frequency setting. In particular, our approach allows for the inclusion of two different categories of variables (high‐frequency and low‐frequency) into the same time‐varying model. Second, we use this model to study the macroeconomic effects of government spending shocks in Italy over the 1988:Q4–2013:Q3 period. Italy—as well as most other euro area economies—is characterized by short quarterly time series for fiscal variables, whereas annual data are generally available for a longer sample before 1999. Our results show that the proposed time‐varying mixed‐frequency model improves on the performance of a simple linear interpolation model in generating the true path of the missing observations. Second, our empirical analysis suggests that government spending shocks tend to have positive effects on output in Italy. The fiscal multiplier, which is maximized at the 1‐year horizon, follows a U‐shape over the sample considered: it peaks at around 1.5 at the beginning of the sample; it then stabilizes between 0.8 and 0.9 from the mid 1990s to the late 2000s, before rising again to above unity during the recent crisis. Copyright © 2015 John Wiley & Sons, Ltd.

  November 09, 2015   doi: 10.1002/jae.2489   open full text
• Optimal Control of Heteroscedastic Macroeconomic Models.
  Vito Polito, Peter Spencer.
  Journal of Applied Econometrics. September 16, 2015
  This paper analyses the implications of heteroscedasticity for optimal macroeconomic policy and welfare. We find that changes in the variance structure driven by exogenous processes like generalized autoregressive conditional heteroscedasticity (GARCH) affect welfare but not the optimal feedback rule. However, changes in the variance structure driven by state‐dependent processes affect both. We also derive certainty‐equivalent transformations of state‐dependent volatility models that allow standard quadratic dynamic programming algorithms to be employed to study optimal policy. These results are illustrated numerically using a reduced‐form model of the US economy in which changes in volatility are driven by a GARCH process and the rate of inflation. Copyright © 2015 John Wiley & Sons, Ltd.

  September 16, 2015   doi: 10.1002/jae.2488   open full text
• Determination of Long‐run and Short‐run Dynamics in EC‐VARMA Models via Canonical Correlations.
  George Athanasopoulos, Donald S. Poskitt, Farshid Vahid, Wenying Yao.
  Journal of Applied Econometrics. September 16, 2015
  This article studies a simple, coherent approach for identifying and estimating error‐correcting vector autoregressive moving average (EC‐VARMA) models. Canonical correlation analysis is implemented for both determining the cointegrating rank, using a strongly consistent method, and identifying the short‐run VARMA dynamics, using the scalar component methodology. Finite‐sample performance is evaluated via Monte Carlo simulations and the approach is applied to modelling and forecasting US interest rates. The results reveal that EC‐VARMA models generate significantly more accurate out‐of‐sample forecasts than vector error correction models (VECMs), especially for short horizons. Copyright © 2015 John Wiley & Sons, Ltd.

  September 16, 2015   doi: 10.1002/jae.2484   open full text
• Reassessing the Relative Power of the Yield Spread in Forecasting Recessions.
  Dean Croushore, Katherine Marsten.
  Journal of Applied Econometrics. September 10, 2015
  In this paper, we replicate the main results of previous research showing that the use of the yield spread in a probit model can predict recessions better than the Survey of Professional Forecasters. We investigate the robustness of their results in several ways: extending the sample to include the 2007‐09 recession, changing the starting date of the sample, using rolling windows of data instead of just an expanding sample, and using alternative measures of the “actual” value of real output. Our results show that the Rudebusch‐Williams findings are robust in all dimensions. Copyright © 2015 John Wiley & Sons, Ltd.

  September 10, 2015   doi: 10.1002/jae.2485   open full text
• Effect of Online Dating on Assortative Mating: Evidence from South Korea.
  Soohyung Lee.
  Journal of Applied Econometrics. August 31, 2015
  Online dating services have increased in popularity around the world, but a lack of quality data hinders our understanding of their role in family formation. This paper studies the effect of online dating services on marital sorting, using a novel dataset with verified information on people and their spouses. Estimates based on matching techniques suggest that, relative to other spouse search methods, online dating promotes marriages that exhibit weaker sorting along occupation and geographical proximity but stronger sorting along education and other demographic traits. Sensitivity analysis, including the Rosenbaum Bounds approach, suggests that online dating's impact on marital sorting is robust to potential selection bias. Copyright © 2015 John Wiley & Sons, Ltd.

  August 31, 2015   doi: 10.1002/jae.2480   open full text
• Forecasting with Bayesian Vector Autoregressions Estimated Using Professional Forecasts.
  Christoph Frey, Frieder Mokinski.
  Journal of Applied Econometrics. August 26, 2015
  We propose a Bayesian shrinkage approach for vector autoregressions (VARs) that uses short‐term survey forecasts as an additional source of information about model parameters. In particular, we augment the vector of dependent variables by their survey nowcasts, and claim that each variable modelled in the VAR and its nowcast are likely to depend in a similar way on the lagged dependent variables. In an application to macroeconomic data, we find that the forecasts obtained from a VAR fitted by our new shrinkage approach typically yield smaller mean squared forecast errors than the forecasts obtained from a range of benchmark methods. Copyright © 2015 John Wiley & Sons, Ltd.

  August 26, 2015   doi: 10.1002/jae.2483   open full text
• Panicca: Panic on Cross‐Section Averages.
  Simon Reese, Joakim Westerlund.
  Journal of Applied Econometrics. August 26, 2015
  The cross‐section average (CA) augmentation approach of Pesaran (A simple panel unit root test in presence of cross‐section dependence. Journal of Applied Econometrics 2007; 22: 265–312) and Pesaran et al. (Panel unit root test in the presence of a multifactor error structure. Journal of Econometrics 2013; 175: 94–115), and the principal components‐based panel analysis of non‐stationarity in idiosyncratic and common components (PANIC) of Bai and Ng (A PANIC attack on unit roots and cointegration. Econometrica 2004; 72: 1127–1177; Panel unit root tests with cross‐section dependence: a further investigation. Econometric Theory 2010; 26: 1088–1114) are among the most popular ‘second‐generation’ approaches for cross‐section correlated panels. One feature of these approaches is that they have different strengths and weaknesses. The purpose of the current paper is to develop PANICCA, a combined approach that exploits the strengths of both CA and PANIC. Copyright © 2015 John Wiley & Sons, Ltd.

  August 26, 2015   doi: 10.1002/jae.2487   open full text
• Outlier‐Robust Bayesian Multinomial Choice Modeling.
  Dries F. Benoit, Stefan Van Aelst, Dirk Van den Poel.
  Journal of Applied Econometrics. August 19, 2015
  A Bayesian method for outlier‐robust estimation of multinomial choice models is presented. The method can be used for both correlated as well as uncorrelated choice alternatives and guarantees robustness towards outliers in the dependent and independent variables. To account for outliers in the response direction, the fat‐tailed multivariate Laplace distribution is used. Leverage points are handled via a shrinkage procedure. A simulation study shows that estimation of the model parameters is less influenced by outliers compared to non‐robust alternatives. An analysis of margarine scanner data shows how our method can be used for better pricing decisions. Copyright © 2015 John Wiley & Sons, Ltd.

  August 19, 2015   doi: 10.1002/jae.2482   open full text
• Bayesian Fuzzy Regression Discontinuity Analysis and Returns to Compulsory Schooling.
  Siddhartha Chib, Liana Jacobi.
  Journal of Applied Econometrics. August 19, 2015
  This paper is concerned with the use of a Bayesian approach to fuzzy regression discontinuity (RD) designs for understanding the returns to education. The discussion is motivated by the change in government policy in the UK in April of 1947, when the minimum school leaving age was raised from 14 to 15—a change that had a discontinuous impact on the probability of leaving school at age 14 for cohorts who turned 14 around the time of the policy change. We develop a Bayesian fuzzy RD framework that allows us to take advantage of this discontinuity to calculate the effect of an additional year of education on subsequent log earnings for the (latent) class of subjects that complied with the policy change. We illustrate this approach with a new dataset composed from the UK General Household Surveys. Copyright © 2015 John Wiley & Sons, Ltd.

  August 19, 2015   doi: 10.1002/jae.2481   open full text
• State Dependence and Stickiness of Sovereign Credit Ratings: Evidence from a Panel of Countries.
  Stefanos Dimitrakopoulos, Michalis Kolossiatis.
  Journal of Applied Econometrics. July 23, 2015
  Using data from Moody's, we examine three sources of sovereign credit ratings persistence: true state dependence, spurious state dependence and serial error correlation. Accounting for ratings persistence, we also examine whether ratings were sticky or procyclical for two major crises: the European debt crisis and the East Asian crisis. We set up a dynamic panel ordered probit model with autocorrelated disturbances and nonparametrically distributed random effects. An efficient Markov chain Monte Carlo algorithm is designed for model estimation. We find evidence of stickiness of ratings and of the three sources of ratings persistence, with the true state dependence being weak. Copyright © 2015 John Wiley & Sons, Ltd.

  July 23, 2015   doi: 10.1002/jae.2479   open full text
• Exponent of Cross‐Sectional Dependence: Estimation and Inference.
  Natalia Bailey, George Kapetanios, M. Hashem Pesaran.
  Journal of Applied Econometrics. July 16, 2015
  This paper provides a characterisation of the degree of cross‐sectional dependence in a two dimensional array, {xit,i = 1,2,...N;t = 1,2,...,T} in terms of the rate at which the variance of the cross‐sectional average of the observed data varies with N. Under certain conditions this is equivalent to the rate at which the largest eigenvalue of the covariance matrix of xt=(x1t,x2t,...,xNt)′ rises with N. We represent the degree of cross‐sectional dependence by α, which we refer to as the ‘exponent of cross‐sectional dependence’, and define it by the standard deviation, Std(x̄t)=ONα−1, where x̄t is a simple cross‐sectional average of xit. We propose bias corrected estimators, derive their asymptotic properties for α > 1/2 and consider a number of extensions. We include a detailed Monte Carlo simulation study supporting the theoretical results. We also provide a number of empirical applications investigating the degree of inter‐linkages of real and financial variables in the global economy. Copyright © 2015 John Wiley & Sons, Ltd.

  July 16, 2015   doi: 10.1002/jae.2476   open full text
• Error Correction Testing in Panels with Common Stochastic Trends.
  Christian Gengenbach, Jean‐Pierre Urbain, Joakim Westerlund.
  Journal of Applied Econometrics. July 14, 2015
  This paper develops panel data tests for the null hypothesis of no error correction in a model with common stochastic trends. The asymptotic distributions of the new test statistics are derived and simulation results are provided to suggest that they perform well in small samples. Copyright © 2015 John Wiley & Sons, Ltd.

  July 14, 2015   doi: 10.1002/jae.2475   open full text
• Sequential Monte Carlo Methods for Estimating Dynamic Microeconomic Models.
  Jason R. Blevins.
  Journal of Applied Econometrics. June 16, 2015
  This paper develops estimators for dynamic microeconomic models with serially correlated unobserved state variables using sequential Monte Carlo methods to estimate the parameters and the distribution of the unobservables. If persistent unobservables are ignored, the estimates can be subject to a dynamic form of sample selection bias. We focus on single‐agent dynamic discrete‐choice models and dynamic games of incomplete information. We propose a full‐solution maximum likelihood procedure and a two‐step method and use them to estimate an extended version of the capital replacement model of Rust with the original data and in a Monte Carlo study. Copyright © 2015 John Wiley & Sons, Ltd.

  June 16, 2015   doi: 10.1002/jae.2470   open full text
• Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance.
  Martin Huber, Lukas Laffers, Giovanni Mellace.
  Journal of Applied Econometrics. June 15, 2015
  In the presence of an endogenous binary treatment and a valid binary instrument, causal effects are point identified only for the subpopulation of compliers, given that the treatment is monotone in the instrument. With the exception of the entire population, causal inference for further subpopulations has been widely ignored in econometrics. We invoke treatment monotonicity and/or dominance assumptions to derive sharp bounds on the average treatment effects on the treated, as well as on other groups. Furthermore, we use our methods to assess the educational impact of a school voucher program in Colombia and discuss testable implications of our assumptions. Copyright © 2015 John Wiley & Sons, Ltd.

  June 15, 2015   doi: 10.1002/jae.2473   open full text
• Daily House Price Indices: Construction, Modeling, and Longer‐run Predictions.
  Tim Bollerslev, Andrew J. Patton, Wenjing Wang.
  Journal of Applied Econometrics. June 04, 2015
  We construct daily house price indices for 10 major US metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat‐sales method that closely mimics the methodology of the popular monthly Case–Shiller house price indices. Our new daily house price indices exhibit dynamic features similar to those of other daily asset prices, with mild autocorrelation and strong conditional heteroskedasticity of the corresponding daily returns. A relatively simple multivariate time series model for the daily house price index returns, explicitly allowing for commonalities across cities and GARCH effects, produces forecasts of longer‐run monthly house price changes that are superior to various alternative forecast procedures based on lower‐frequency data. Copyright © 2015 John Wiley & Sons, Ltd.

  June 04, 2015   doi: 10.1002/jae.2471   open full text
• Modelling Inflation Volatility.
  Eric Eisenstat, Rodney W. Strachan.
  Journal of Applied Econometrics. May 29, 2015
  This paper discusses estimation of US inflation volatility using time‐varying parameter models, in particular whether it should be modelled as a stationary or random walk stochastic process. Specifying inflation volatility as an unbounded process, as implied by the random walk, conflicts with priors beliefs, yet a stationary process cannot capture the low‐frequency behaviour commonly observed in estimates of volatility. We therefore propose an alternative model with a change‐point process in the volatility that allows for switches between stationary models to capture changes in the level and dynamics over the past 40 years. To accommodate the stationarity restriction, we develop a new representation that is equivalent to our model but is computationally more efficient. All models produce effectively identical estimates of volatility, but the change‐point model provides more information on the level and persistence of volatility and the probabilities of changes. For example, we find a few well‐defined switches in the volatility process and, interestingly, these switches line up well with economic slowdowns or changes of the Federal Reserve Chair. Moreover, a decomposition of inflation shocks into permanent and transitory components shows that a spike in volatility in the late 2000s was entirely on the transitory side and characterized by a rise above its long‐run mean level during a period of higher persistence. Copyright © 2015 John Wiley & Sons, Ltd.

  May 29, 2015   doi: 10.1002/jae.2469   open full text
• Borrowing Constraints and Credit Demand in a Developing Economy.
  Jaime Ruiz‐Tagle, Francis Vella.
  Journal of Applied Econometrics. May 01, 2015
  This paper investigates the determinants of credit demand in the presence of borrowing constraints in a developing economy. We model the determinants of observed debt for Chilean households while accounting for selection bias and the endogeneity of their income and specific household assets. Using a novel Chilean dataset, we estimate the relationship between household characteristics and consumer and mortgage debt. We find substantial differences in the nature of these relationships across the types of debt. For example, we find that the income elasticity for consumer debt is greater than 1 whereas for mortgage debt it is not. The results suggest the increased availability of credit, combined with the aging of the Chilean population, is likely to drastically change the distribution and level of Chilean debt. These findings are particularly relevant for other developing economies currently experiencing rapid income and debt growth. Copyright © 2015 John Wiley & Sons, Ltd.

  May 01, 2015   doi: 10.1002/jae.2465   open full text
• A Semi‐Parametric Analysis of Two‐Sided Markets: An Application to the Local Daily Newspapers in the USA.
  Senay Sokullu.
  Journal of Applied Econometrics. April 17, 2015
  This paper considers an empirical semiparametric model for two‐sided markets. Contrary to existing empirical literature on two‐sided markets, we specify network effects and probability distribution functions of net benefits of the two sides nonparametrically. We then estimate the model by nonparametric instrumental variables regression for local daily newspapers from the USA. We show that semiparametric specification is supported by the data and the network effects are neither linear nor monotonic. With a numerical illustration we demonstrate that the mark‐up of the newspaper on each side changes drastically with the nonlinearly specified network effects from the case with linear network effects. Copyright © 2015 John Wiley & Sons, Ltd.

  April 17, 2015   doi: 10.1002/jae.2464   open full text
• Factor‐Based Identification‐Robust Interference in IV Regressions.
  Georges Kapetanios, Lynda Khalaf, Massimiliano Marcellino.
  Journal of Applied Econometrics. April 17, 2015
  Robust methods for instrumental variable inference have received considerable attention recently. Their analysis has raised a variety of problematic issues such as size/power trade‐offs resulting from weak or many instruments. We show that information reduction methods provide a useful and practical solution to this and related problems. Formally, we propose factor‐based modifications to three popular weak‐instrument‐robust statistics, and illustrate their validity asymptotically and in finite samples. Results are derived using asymptotic settings that are commonly used in both the factor and weak‐instrument literature. For the Anderson–Rubin statistic, we also provide analytical finite‐sample results that do not require any underlying factor structure. An illustrative Monte Carlo study reveals the following. Factor‐based tests control size regardless of instruments and factor quality. All factor‐based tests are systematically more powerful than standard counterparts. With informative instruments and in contrast to standard tests: (i) power of factor‐based tests is not affected by k even when large; and (ii) weak factor structure does not cost power. An empirical study on a New Keynesian macroeconomic model suggests that our factor‐based methods can bridge a number of gaps between structural and statistical modeling. Copyright © 2015 John Wiley & Sons, Ltd.

  April 17, 2015   doi: 10.1002/jae.2466   open full text
• Estimating Health Demand for an Aging Population: A Flexible and Robust Bayesian Joint Model.
  Arnab Mukherji, Satrajit Roychoudhury, Pulak Ghosh, Sarah Brown.
  Journal of Applied Econometrics. April 16, 2015
  We analyse two frequently used measures of the demand for health—hospital visits and out‐of‐pocket health care expenditure—which have been analysed separately in the existing literature. Given that these two measures of health demand are highly likely to be closely correlated, we propose a framework to jointly model hospital visits and out‐of‐pocket medical expenditure, which allows for the presence of nonlinear effects of covariates using splines to capture the effects of aging on health demand. The findings from our empirical analysis of the US Health and Retirement Survey indicate that the demand for health varies with age. © 2015 The Authors. Journal of Applied Econometrics published by John Wiley & Sons Ltd.

  April 16, 2015   doi: 10.1002/jae.2463   open full text
• Accounting for the Political Uncertainty Factor.
  Eric M. Scheffel.
  Journal of Applied Econometrics. April 10, 2015
  We build our analysis upon previous work by Bloom et al. (Measuring the Effect of Political Uncertainty. Working Paper, Stanford University, 2012) and Baker et al. (Political Uncertainty: A New Indicator. CentrePiece 2012; 16(3): 21–23), who estimate the dynamic effects of a shock to a newly constructed surrogate measure of political uncertainty (PU) on the US economy. Comparable to their results we demonstrate that a shock to PU has pervasive effects on the dynamic evolution of the US economy. Using an estimated structural dynamic factor model we find that more globally integrated markets exhibit significantly more pronounced responses than other measures of real economic activity. Impulse responses reveal a small but statistically significant ‘flight‐to‐safety’ effect, depressing government bond yields across the entire term structure following a shock to PU. Forecast error variance decompositions are predominantly composed of supply, demand, and PU shocks over all horizons, with PU shocks contributing less and supply shocks contributing more to forecast errors at longer horizons. Technology shocks, by contrast, are found to affect forecast accuracy closer to impact with quickly decaying contributions over extended forecast horizons. Copyright © 2015 John Wiley & Sons, Ltd.

  April 10, 2015   doi: 10.1002/jae.2455   open full text
• Maintaining (Locus of) Control? Data Combination for the Identification and Inference of Factor Structure Models.
  Rémi Piatek, Pia Pinger.
  Journal of Applied Econometrics. April 10, 2015
  Factor structure models are widely used in economics to extract latent variables, such as personality traits, and to measure their impact on outcomes of interest. The identification and inference of these models, however, highly depend on the availability of rich longitudinal data. To overcome the common problem of data scarcity, this paper proposes to combine datasets that each identify some part of the likelihood, thereby recovering the identification of the complete model. The performance of the approach is demonstrated by a Monte Carlo experiment. We apply this technique empirically to study the impact of locus of control on education and wages. Our strategy allows us to elicit the distribution of pre‐market locus of control from a sample of young individuals, and to measure its impact on education and wages in a sample of adults. Our findings indicate that the effect of locus of control on wages mainly operates through education. Copyright © 2015 John Wiley & Sons, Ltd.

  April 10, 2015   doi: 10.1002/jae.2456   open full text
• Econometric Methods for Modelling Systems With a Mixture of i(1) and i(0) Variables.
  Lance A. Fisher, Hyeon‐Seung Huh, Adrian R. Pagan.
  Journal of Applied Econometrics. April 07, 2015
  This paper considers structural models with both I(1) and I(0) variables. The structural shocks associated with either set of variables could be permanent or transitory. We classify the shocks as (P1,P0) and (T1,T0), where P/T distinguishes permanent/transitory, while 1/0 means they are attached to structural equations with either I(1) or I(0) variables as their ‘dependent’ variable. We show that P0 shocks can affect cointegration analysis and provide a formula to compute the permanent component if they are present. Finally, we reformulate a well‐known empirical structural vector autoregression showing the impact of P0 shocks when there are just long‐run parametric and sign restrictions. Copyright © 2015 John Wiley & Sons, Ltd.

  April 07, 2015   doi: 10.1002/jae.2459   open full text
• A Smooth Transition Logit Model of The Effects of Deregulation in the Electricity Market.
  A. Stan Hurn, Annastiina Silvennoinen, Timo Teräsvirta.
  Journal of Applied Econometrics. March 18, 2015
  This paper introduces the smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties, together with a Lagrange multiplier test of the null hypothesis of linearity in the underlying latent index. The development of the STL model is motivated by the desire to assess the impact of deregulation in the Queensland electricity market and ascertain whether increased competition has resulted in significant changes in the behaviour of the spot price of electricity, specifically with respect to the occurrence of periodic abnormally high prices. The model allows the timing of any change to be endogenously determined and also market participants' behaviour to change gradually over time. The main results provide clear evidence in support of a structural change in the nature of price events, and the endogenously determined timing of the change is consistent with the process of deregulation in Queensland. Copyright © 2015 John Wiley & Sons, Ltd.

  March 18, 2015   doi: 10.1002/jae.2452   open full text
• Modelling Hospital Admission and Length of Stay by Means of Generalised Count Data Models.
  Helmut Herwartz, Nadja Klein, Christoph Strumann.
  Journal of Applied Econometrics. March 06, 2015
  For a large heterogeneous group of patients, we analyse probabilities of hospital admission and distributional properties of lengths of hospital stay conditional on individual determinants. Bayesian structured additive regression models for zero‐inflated and overdispersed count data are employed. In addition, the framework is extended towards hurdle specifications, providing an alternative approach to cover particularly large frequencies of zero quotes in count data. As a specific merit, the model class considered embeds linear and nonlinear effects of covariates on all distribution parameters. Linear effects indicate that the quantity and severity of prior illness are positively correlated with the risk of hospital admission, while medical prevention (in the form of general practice visits) and rehabilitation reduce the expected length of future hospital stays. Flexible nonlinear response patterns are diagnosed for age and an indicator of a patients' socioeconomic status. We find that social deprivation exhibits a positive impact on the risk of admission and a negative effect on the expected length of future hospital stays of admitted patients. Copyright © 2015 John Wiley & Sons, Ltd.

  March 06, 2015   doi: 10.1002/jae.2454   open full text
• ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates.
  Lars Winkelmann, Markus Bibinger, Tobias Linzert.
  Journal of Applied Econometrics. March 06, 2015
  This paper proposes a new econometric approach to disentangle two distinct response patterns of the yield curve to monetary policy announcements. Based on cojumps in intraday tick data of short‐ and long‐term interest rate futures, we develop a day‐wise test that detects the occurrence of a significant policy surprise and identifies the market perceived source of the surprise. The new test is applied to 133 policy announcements of the European Central Bank (ECB) in the period from 2001 to 2012. Our main findings indicate a good predictability of ECB policy decisions and remarkably stable perceptions about the ECB's policy preferences. Copyright © 2015 John Wiley & Sons, Ltd.

  March 06, 2015   doi: 10.1002/jae.2453   open full text
• The Zero Lower Bound and Parameter Bias in an Estimated DSGE Model.
  Yasuo Hirose, Atsushi Inoue.
  Journal of Applied Econometrics. February 25, 2015
  This paper examines how and to what extent parameter estimates can be biased in a dynamic stochastic general equilibrium (DSGE) model that omits the zero lower bound (ZLB) constraint on the nominal interest rate. Our Monte Carlo experiments using a standard sticky‐price DSGE model show that no significant bias is detected in parameter estimates and that the estimated impulse response functions are quite similar to the true ones. However, as the frequency of being at the ZLB or the duration of ZLB spells increases, the parameter bias becomes larger and therefore leads to substantial differences between the estimated and true impulse responses. It is also demonstrated that the model missing the ZLB causes biased estimates of structural shocks even with the virtually unbiased parameters. Copyright © 2015 John Wiley & Sons, Ltd.

  February 25, 2015   doi: 10.1002/jae.2447   open full text
• Empirical Tests of the Pollution Haven Hypothesis When Environmental Regulation is Endogenous.
  Daniel L. Millimet, Jayjit Roy.
  Journal of Applied Econometrics. February 24, 2015
  The pollution haven hypothesis (PHH) posits that production within polluting industries will shift to locations with lax environmental regulation. While straightforward, the existing empirical literature is inconclusive owing to two shortcomings. First, unobserved heterogeneity and measurement error are typically ignored due to the lack of a credible, traditional instrumental variable for regulation. Second, geographic spillovers have not been adequately incorporated into tests of the PHH. We overcome these issues utilizing two novel identification strategies within a model incorporating spillovers. Using US state‐level data, own environmental regulation negatively impacts inbound foreign direct investment. Moreover, endogeneity is both statistically and economically relevant. Copyright © 2015 John Wiley & Sons, Ltd.

  February 24, 2015   doi: 10.1002/jae.2451   open full text
• GMM with Multiple Missing Variables.
  Saraswata Chaudhuri, David K. Guilkey.
  Journal of Applied Econometrics. February 04, 2015
  We consider efficient estimation in moment conditions models with non‐monotonically missing‐at‐random (MAR) variables. A version of MAR point‐identifies the parameters of interest and gives a closed‐form efficient influence function that can be used directly to obtain efficient semi‐parametric generalized method of moments (GMM) estimators under standard regularity conditions. A small‐scale Monte Carlo experiment with MAR instrumental variables demonstrates that the asymptotic superiority of these estimators over the standard methods carries over to finite samples. An illustrative empirical study of the relationship between a child's years of schooling and number of siblings indicates that these GMM estimators can generate results with substantive differences from standard methods. Copyright © 2015 John Wiley & Sons, Ltd.

  February 04, 2015   doi: 10.1002/jae.2444   open full text
• Rare Shocks, Great Recessions.
  Vasco Cúrdia, Marco Negro, Daniel L. Greenwald.
  Journal of Applied Econometrics. May 28, 2014
  We estimate a DSGE (dynamic stochastic general equilibrium) model where rare large shocks can occur, by replacing the commonly used Gaussian assumption with a Student's t‐distribution. Results from the Smets and Wouters (American Economic Review 2007; 97: 586–606) model estimated on the usual set of macroeconomic time series over the 1964–2011 period indicate that (i) the Student's t specification is strongly favored by the data even when we allow for low‐frequency variation in the volatility of the shocks, and (ii)) the estimated degrees of freedom are quite low for several shocks that drive US business cycles, implying an important role for rare large shocks. This result holds even if we exclude the Great Recession period from the sample. We also show that inference about low‐frequency changes in volatility—and, in particular, inference about the magnitude of Great Moderation—is different once we allow for fat tails. Copyright © 2014 John Wiley & Sons, Ltd.

  May 28, 2014   doi: 10.1002/jae.2395   open full text
• Mixed‐Frequency Structural Models: Identification, Estimation, And Policy Analysis.
  Claudia Foroni, Massimiliano Marcellino.
  Journal of Applied Econometrics. May 14, 2014
  The mismatch between the timescale of DSGE (dynamic stochastic general equilibrium) models and the data used in their estimation translates into identification problems, estimation bias, and distortions in policy analysis. We propose an estimation strategy based on mixed‐frequency data to alleviate these shortcomings. The virtues of our approach are explored for two monetary policy models. Copyright © 2014 John Wiley & Sons, Ltd.

  May 14, 2014   doi: 10.1002/jae.2396   open full text
• When Does The Stepping‐Stone Work? Fixed‐Term Contracts Versus Temporary Agency Work In Changing Economic Conditions.
  Pauline Givord, Lionel Wilner.
  Journal of Applied Econometrics. May 13, 2014
  This paper emphasizes differences among short‐term contracts in terms of career prospects. Using French data over the 2002–2010 period, we rely on a dynamic model with fixed effects to disentangle state dependence from unobserved heterogeneity. Although fixed‐term contracts may provide a ‘stepping‐stone’ to permanent positions, temporary agency work is hardly better than unemployment in this regard. The Great Recession of 2008 has changed the dynamics on the labor market and amplified the difference between fixed‐term contracts and temporary agency work. For both types of temporary workers, providing overtime work does not significantly increase the transition to permanent employment. Copyright © 2014 John Wiley & Sons, Ltd.

  May 13, 2014   doi: 10.1002/jae.2394   open full text
• Simple Identification And Specification Of Cointegrated Varma Models.
  Christian Kascha, Carsten Trenkler.
  Journal of Applied Econometrics. April 22, 2014
  We bring together some recent advances in the literature on vector autoregressive moving‐average models, creating a simple specification and estimation strategy for the cointegrated case. We show that in this case with fixed initial values there exists a so‐called final moving‐average representation. We prove that the specification strategy is consistent. The performance of the proposed method is investigated via a Monte Carlo study and a forecasting exercise for US interest rates. We find that our method performs well relative to alternative approaches for cointegrated series and methods which do not allow for moving‐average terms. Copyright © 2014 John Wiley & Sons, Ltd.

  April 22, 2014   doi: 10.1002/jae.2393   open full text
• Realized Beta Garch: A Multivariate Garch Model With Realized Measures Of Volatility.
  Peter Reinhard Hansen, Asger Lunde, Valeri Voev.
  Journal of Applied Econometrics. April 14, 2014
  We introduce a multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model that incorporates realized measures of variances and covariances. Realized measures extract information about the current levels of volatilities and correlations from high‐frequency data, which is particularly useful for modeling financial returns during periods of rapid changes in the underlying covariance structure. When applied to market returns in conjunction with returns on an individual asset, the model yields a dynamic model specification of the conditional regression coefficient that is known as the beta. We apply the model to a large set of assets and find the conditional betas to be far more variable than usually found with rolling‐window regressions based exclusively on daily returns. In the empirical part of the paper, we examine the cross‐sectional as well as the time variation of the conditional beta series during the financial crises. Copyright © 2014 John Wiley & Sons, Ltd.

  April 14, 2014   doi: 10.1002/jae.2389   open full text
• Purchasing Power Parity And The Taylor Rule.
  Hyeongwoo Kim, Ippei Fujiwara, Bruce E. Hansen, Masao Ogaki.
  Journal of Applied Econometrics. April 03, 2014
  It is well known that there is a large degree of uncertainty around Rogoff's consensus half‐life of the real exchange rate. To obtain a more efficient estimator, we develop a system method that combines the Taylor rule and a standard exchange rate model to estimate half‐lives. Further, we propose a median unbiased estimator for the system method based on the generalized method of moments with non‐parametric grid bootstrap confidence intervals. Applying the method to real exchange rates of 18 developed countries against the US dollar, we find that most half‐life estimates from the single equation method fall in the range of 3–5 years, with wide confidence intervals that extend to positive infinity. In contrast, the system method yields median‐unbiased estimates that are typically shorter than 1 year, with much sharper 95% confidence intervals. Our Monte Carlo simulation results are consistent with an interpretation of these results that the true half‐lives are short but long half‐life estimates from single‐equation methods are caused by the high degree of uncertainty of these methods. Copyright © 2014 John Wiley & Sons, Ltd.

  April 03, 2014   doi: 10.1002/jae.2391   open full text
• Speculation In The Oil Market.
  Luciana Juvenal, Ivan Petrella.
  Journal of Applied Econometrics. March 18, 2014
  The run‐up in oil prices since 2004 coincided with growing investment in commodity markets and increased price co‐movement among different commodities. We assess whether speculation in the oil market played a role in driving this salient empirical pattern. We identify oil shocks from a large dataset using a dynamic factor model. This method is motivated by the fact that a small‐scale vector autoregression is not informationally sufficient to identify the shocks. The main results are as follows. (i) While global demand shocks account for the largest share of oil price fluctuations, speculative shocks are the second most important driver. (ii) The increase in oil prices over the last decade is mainly driven by the strength of global demand. However, speculation played a significant role in the oil price increase between 2004 and 2008 and its subsequent collapse. (iii) The co‐movement between oil prices and the prices of other commodities is mainly explained by global demand shocks. Our results support the view that the recent oil price increase is mainly driven by the strength of global demand but that the financialization process of commodity markets also played a role. Copyright © 2014 John Wiley & Sons, Ltd.

  March 18, 2014   doi: 10.1002/jae.2388   open full text
• Priors And Posterior Computation In Linear Endogenous Variable Models With Imperfect Instruments.
  Joshua C. C. Chan, Justin L. Tobias.
  Journal of Applied Econometrics. March 18, 2014
  In this paper we, like several studies in the recent literature, employ a Bayesian approach to estimation and inference in models with endogeneity concerns by imposing weaker prior assumptions than complete excludability. When allowing for instrument imperfection of this type, the model is only partially identified, and as a consequence standard estimates obtained from the Gibbs simulations can be unacceptably imprecise. We thus describe a substantially improved ‘semi‐analytic’ method for calculating parameter marginal posteriors of interest that only require use of the well‐mixing simulations associated with the identifiable model parameters and the form of the conditional prior. Our methods are also applied in an illustrative application involving the impact of body mass index on earnings. Copyright © 2014 John Wiley & Sons, Ltd.

  March 18, 2014   doi: 10.1002/jae.2390   open full text
• Doubly Robust Estimation Of Causal Effects With Multivalued Treatments: An Application To The Returns To Schooling.
  S. Derya Uysal.
  Journal of Applied Econometrics. March 14, 2014
  This paper provides doubly robust estimators for treatment effect parameters which are defined in a multivalued treatment effect framework. We apply this method to the unique dataset of the 1970 British Cohort Study (BCS70) to estimate returns to various levels of schooling. The analysis is carried out for female and male samples separately to capture possible gender differences. Average returns are estimated for the entire population, as well as conditional on having a specific educational achievement. For males, relative to no qualification, we find an average return to O‐levels of 6.3%, to A‐levels of 7.9% and to higher education of 25.4%. The estimated average returns to O‐level and A‐level relative to no qualification are insignificant for females, whereas the return to higher education is 19.9%.Copyright © 2014 John Wiley & Sons, Ltd.

  March 14, 2014   doi: 10.1002/jae.2386   open full text
• The Contribution Of Structural Break Models To Forecasting Macroeconomic Series.
  Luc Bauwens, Gary Koop, Dimitris Korobilis, Jeroen V.K. Rombouts.
  Journal of Applied Econometrics. March 12, 2014
  This paper compares the forecasting performance of models that have been proposed for forecasting in the presence of structural breaks. They differ in their treatment of the break process, the model applied in each regime and the out‐of‐sample probability of a break. In an extensive empirical evaluation, we demonstrate the presence of breaks and their importance for forecasting. We find no single model that consistently works best in the presence of breaks. In many cases, the formal modeling of the break process is important in achieving a good forecast performance. However, there are also many cases where rolling window forecasts perform well. Copyright © 2014 John Wiley & Sons, Ltd.

  March 12, 2014   doi: 10.1002/jae.2387   open full text
• Sparse Partial Least Squares In Time Series For Macroeconomic Forecasting.
  Julieta Fuentes, Pilar Poncela, Julio Rodríguez.
  Journal of Applied Econometrics. March 12, 2014
  Factor models have been applied extensively for forecasting when high‐dimensional datasets are available. In this case, the number of variables can be very large. For instance, usual dynamic factor models in central banks handle over 100 variables. However, there is a growing body of literature indicating that more variables do not necessarily lead to estimated factors with lower uncertainty or better forecasting results. This paper investigates the usefulness of partial least squares techniques that take into account the variable to be forecast when reducing the dimension of the problem from a large number of variables to a smaller number of factors. We propose different approaches of dynamic sparse partial least squares as a means of improving forecast efficiency by simultaneously taking into account the variable forecast while forming an informative subset of predictors, instead of using all the available ones to extract the factors. We use the well‐known Stock and Watson database to check the forecasting performance of our approach. The proposed dynamic sparse models show good performance in improving efficiency compared to widely used factor methods in macroeconomic forecasting. Copyright © 2014 John Wiley & Sons, Ltd.

  March 12, 2014   doi: 10.1002/jae.2384   open full text
• Regression Discontinuity Applications With Rounding Errors In The Running Variable.
  Yingying Dong.
  Journal of Applied Econometrics. March 11, 2014
  Many empirical applications of regression discontinuity (RD) models use a running variable that is rounded and hence discrete, e.g. age in years, or birth weight in ounces. This paper shows that standard RD estimation using a rounded discrete running variable leads to inconsistent estimates of treatment effects, even when the true functional form relating the outcome and the running variable is known and is correctly specified. This paper provides simple formulas to correct for this discretization bias. The proposed approach does not require instrumental variables, but instead uses information regarding the distribution of rounding errors, which is easily obtained and often close to uniform. Bounds can be obtained without knowing the distribution of the rounding error. The proposed approach is applied to estimate the effect of Medicare on insurance coverage in the USA, and to investigate the retirement‐consumption puzzle in China, utilizing the Chinese mandatory retirement policy. Copyright © 2014 John Wiley & Sons, Ltd.

  March 11, 2014   doi: 10.1002/jae.2369   open full text
• Replacing Sample Trimming With Boundary Correction In Nonparametric Estimation Of First‐Price Auctions.
  Brent R. Hickman, Timothy P. Hubbard.
  Journal of Applied Econometrics. March 10, 2014
  Two‐step nonparametric estimators have become standard in empirical auctions. A drawback concerns boundary effects which cause inconsistencies near the endpoints of the support and bias in finite samples. To cope, sample trimming is typically used, which leads to non‐random data loss. Monte Carlo experiments show this leads to poor performance near the support boundaries and on the interior due to bandwidth selection issues. We propose a modification that employs boundary correction techniques, and we demonstrate substantial improvement in finite‐sample performance. We implement the new estimator using oil lease auctions data and find that trimming masks a substantial degree of bidder asymmetry and inefficiency in allocations. Copyright © 2014 John Wiley & Sons, Ltd.

  March 10, 2014   doi: 10.1002/jae.2385   open full text
• A Bayesian Semiparametric Competing Risk Model With Unobserved Heterogeneity.
  Martin Burda, Matthew Harding, Jerry Hausman.
  Journal of Applied Econometrics. March 03, 2014
  This paper generalizes existing econometric models for censored competing risks by introducing a new flexible specification based on a piecewise linear baseline hazard, time‐varying regressors, and unobserved individual heterogeneity distributed as an infinite mixture of generalized inverse Gaussian (GIG) densities, nesting the gamma kernel as a special case, A common correlated latent time effect induces dependence among risks, Our model is based on underlying latent exit decisions in continuous time while only a time interval containing the exit time is observed, as is common in economic data, We do not make the simplifying assumption of discretizing exit decisions—our competing risk model setup allows for latent exit times of different risk types to be realized within the same time period. In this setting, we derive a tractable likelihood based on scaled GIG Laplace transforms and their higher‐order derivatives. We apply our approach to analyzing the determinants of unemployment duration with exits to jobs in the same industry or a different industry among unemployment insurance recipients on nationally representative individual‐level survey data from the US Department of Labor. Our approach allows us to conduct a counterfactual policy experiment by changing the replacement rate: we find that the impact of its change on the probability of exit from unemployment is inelastic. Copyright © 2014 John Wiley & Sons, Ltd.

  March 03, 2014   doi: 10.1002/jae.2368   open full text
• Hedonic Housing Prices In Paris: An Unbalanced Spatial Lag Pseudo‒Panel Model With Nested Random Effects.
  BADI H. Baltagi, GEORGES Bresson, JEAN‒MICHEL Etienne.
  Journal of Applied Econometrics. February 27, 2014
  This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990–2003. This is done using maximum likelihood estimation, taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements, each divided into four quartiers (quarters), which in turn contain between 15 and 169 blocks (îlot, in French) per quartier. This is an unbalanced pseudo‒panel data containing 156,896 transactions. Despite the richness of the data, many neighborhood characteristics are not observed, and we attempt to capture these neighborhood spillover effects using a spatial lag model. Using likelihood ratio tests, we find significant spatial lag effects as well as significant nested random error effects. The empirical results show that the hedonic housing estimates and the corresponding marginal effects are affected by taking into account the nested aspects of the Paris housing data as well as the spatial neighborhood effects.Copyright © 2014 John Wiley & Sons, Ltd.

  February 27, 2014   doi: 10.1002/jae.2377   open full text
• Effect Of Fdi And Time On Catching Up: New Insights From A Conditional Nonparametric Frontier Analysis.
  Camilla Mastromarco, Léopold Simar.
  Journal of Applied Econometrics. February 24, 2014
  We use an appropriate nonparametric two‐step approach on conditional efficiencies to investigate how foreign direct investment (FDI) and time affect the process of catching up. By using a dataset of 44 countries over 1970–2007, we explore the channels under which FDI fosters productivity by disentangling the impact of this factor on the production process and its components: impact on the attainable production set (input–output space) and the impact on the distribution of efficiencies. We extend existing methodological tools—conditional nonparametric efficiency measures—to examine these interrelationships. We emphasize the usefulness of smoothing over time to better analyze the potential dynamic influence of FDI on efficiency. We find that both FDI and time play an important role as influencing efficiency distribution and affecting, to a smaller extend, the production set. This effect of FDI does not seem to vary much over time. By the second‐stage nonparametric regression of the conditional efficiencies over FDI and time we identify clearly the effect of time and FDI on conditional efficiency and we determine idiosyncratic efficiency, which represents the‘Solow residual’, measured by looking to the unexplained part of the conditional efficiencies. Copyright © 2014 John Wiley & Sons, Ltd.

  February 24, 2014   doi: 10.1002/jae.2382   open full text
• Visual Attention And Attribute Attendance In Multi‐Attribute Choice Experiments.
  Kelvin Balcombe, Iain Fraser, Eugene McSorley.
  Journal of Applied Econometrics. January 29, 2014
  Decision strategies in multi‐attribute choice experiments are investigated using eye‐tracking. The visual attention towards, and attendance of, attributes is examined. Stated attendance is found to diverge substantively from visual attendance of attributes. However, stated and visual attendance are shown to be informative, non‐overlapping sources of information about respondent utility functions when incorporated into model estimation. Eye‐tracking also reveals systematic nonattendance of attributes only by a minority of respondents. Most respondents visually attend most attributes most of the time. We find no compelling evidence that the level of attention is related to respondent certainty, or that higher or lower value attributes receive more or less attention. Copyright © 2014 John Wiley & Sons, Ltd.

  January 29, 2014   doi: 10.1002/jae.2383   open full text
• Unraveling The Relationship Between Presidential Approval And The Economy: A Multidimensional Semiparametric Approach.
  Michael Berlemann, Sören Enkelmann, Torben Kuhlenkasper.
  Journal of Applied Econometrics. January 27, 2014
  Empirical studies analyzing the determinants of US presidential popularity have delivered quite inconclusive results concerning the role of economic variables by assuming linear relationships. We employ penalized spline smoothing in the context of semiparametric additive mixed models and allow for flexible functional forms and thus possible nonlinear effects for the economic determinants. By controlling for the well‐known politically motivated covariables, we find strong evidence for nonlinear and negative effects of unemployment, inflation and government consumption on presidential approval. Additionally, we present new results in favor of nonparametric trivariate interaction effects between the macroeconomic covariables. Copyright © 2014 John Wiley & Sons, Ltd.

  January 27, 2014   doi: 10.1002/jae.2380   open full text
• Local Adaptive Multiplicative Error Models For High‐Frequency Forecasts.
  Wolfgang K. Härdle, Nikolaus Hautsch, Andrija Mihoci.
  Journal of Applied Econometrics. January 27, 2014
  We propose a local adaptive multiplicative error model (MEM) accommodating time‐varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data‐driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analysing 1‐minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis. Copyright © 2014 John Wiley & Sons, Ltd.

  January 27, 2014   doi: 10.1002/jae.2376   open full text
• Dsge Models In The Frequency Domain.
  Luca Sala.
  Journal of Applied Econometrics. January 23, 2014
  We use frequency domain techniques to estimate a medium‐scale dynamic stochastic general equilibrium (DSGE) model on different frequency bands. We show that goodness of fit, forecasting performance and parameter estimates vary substantially with the frequency bands over which the model is estimated. Estimates obtained using subsets of frequencies are characterized by significantly different parameters, an indication that the model cannot match all frequencies with one set of parameters. In particular, we find that: (i) the low‐frequency properties of the data strongly affect parameter estimates obtained in the time domain; (ii) the importance of economic frictions in the model changes when different subsets of frequencies are used in estimation. This is particularly true for the investment adjustment cost and habit persistence: when low frequencies are present in the estimation, the investment adjustment cost and habit persistence are estimated to be higher than when low frequencies are absent. Copyright © 2014 John Wiley & Sons, Ltd.

  January 23, 2014   doi: 10.1002/jae.2375   open full text
• ESTIMATING PERSON‐CENTERED TREATMENT (PeT) EFFECTS USING INSTRUMENTAL VARIABLES: AN APPLICATION TO EVALUATING PROSTATE CANCER TREATMENTS.
  Anirban Basu.
  Journal of Applied Econometrics. October 07, 2013
  This paper builds on the methods of local instrumental variables developed by Heckman and Vytlacil (1999, 2001, 2005) to estimate person‐centered treatment (PeT) effects that are conditioned on the person's observed characteristics and averaged over the potential conditional distribution of unobserved characteristics that lead them to their observed treatment choices. PeT effects are more individualized than conditional treatment effects from a randomized setting with the same observed characteristics. PeT effects can be easily aggregated to construct any of the mean treatment effect parameters and, more importantly, are well suited to comprehend individual‐level treatment effect heterogeneity. The paper presents the theory behind PeT effects, and applies it to study the variation in individual‐level comparative effects of prostate cancer treatments on overall survival and costs. Copyright © 2013 John Wiley & Sons, Ltd.

  October 07, 2013   doi: 10.1002/jae.2343   open full text
• Who Benefits From Job Corps? A Distributional Analysis Of An Active Labor Market Program.
  Ozkan Eren, Serkan Ozbeklik.
  Journal of Applied Econometrics. September 19, 2013
  Using recently developed econometric techniques to estimate quantile treatment effects (QTE) and experimental data, we examine the impact of Job Corps on earnings distribution. Our results indicate a great deal of heterogeneity in the effects of Job Corps. The QTEs show an increasing pattern along the earnings distribution, with much more pronounced differences at the upper quantiles for males, whites, and ages 20–24. Moreover, we find the QTEs to be very small at quantiles below the median for males, ages 16–17 and 18–19, and non‐resident students. We propose strong economic conditions and skill hypotheses to explain the heterogeneity observed over the earnings distribution. Copyright © 2013 John Wiley & Sons, Ltd.

  September 19, 2013   doi: 10.1002/jae.2345   open full text
• Uncovering The Common Risk‐Free Rate In The European Monetary Union.
  Rien J. L. M. Wagenvoort, Sanne Zwart.
  Journal of Applied Econometrics. July 31, 2013
  We introduce longitudinal factor analysis (LFA) to extract the common risk‐free (CRF) rate from a sample of sovereign bonds of countries in a monetary union. Since LFA exploits the typically very large longitudinal dimension of bond data, it performs better than traditional factor analysis methods that rely on the much smaller cross‐sectional dimension. European sovereign bond yields for the period 2006–2011 are decomposed into a CRF rate, a default risk premium and a liquidity risk premium. Our empirical findings suggest that investors chase both credit quality and liquidity, and that they price double default risk on credit default swaps. Copyright © 2013 John Wiley & Sons, Ltd.

  July 31, 2013   doi: 10.1002/jae.2335   open full text
• Applying Beta‐Type Size Distributions To Healthcare Cost Regressions.
  Andrew M. Jones, James Lomas, Nigel Rice.
  Journal of Applied Econometrics. July 08, 2013
  This paper extends the literature on modelling healthcare cost data by applying the generalised beta of the second kind (GB2) distribution to English hospital inpatient cost data. A quasi‐experimental design, estimating models on a sub‐population of the data and evaluating performance on another sub‐population, is used to compare this distribution with its nested and limiting cases. While for these data the beta of the second kind (B2) distribution and generalised gamma (GG) distribution outperform the GB2, our results illustrate that the GB2 can be used as a device for choosing among competing parametric distributions for healthcare cost data. Copyright © 2013 John Wiley & Sons, Ltd.

  July 08, 2013   doi: 10.1002/jae.2334   open full text
• Identifying Causal Mechanisms (Primarily) Based On Inverse Probability Weighting.
  Martin Huber.
  Journal of Applied Econometrics. June 30, 2013
  This paper demonstrates the identification of causal mechanisms of a binary treatment under selection on observables, (primarily) based on inverse probability weighting; i.e. we consider the average indirect effect of the treatment, which operates through an intermediate variable (or mediator) that is situated on the causal path between the treatment and the outcome, as well as the (unmediated) direct effect. Even under random treatment assignment, subsequent selection into the mediator is generally non‐random such that causal mechanisms are only identified when controlling for confounders of the mediator and the outcome. To tackle this issue, units are weighted by the inverse of their conditional treatment propensity given the mediator and observed confounders. We show that the form and applicability of weighting depend on whether some confounders are themselves influenced by the treatment or not. A simulation study gives the intuition for these results and an empirical application to the direct and indirect health effects (through employment) of the US Job Corps program is also provided. Copyright © 2013 John Wiley & Sons, Ltd.

  June 30, 2013   doi: 10.1002/jae.2341   open full text
• The Role Of Conditional Heteroskedasticity In Identifying And Estimating Linear Triangular Systems, With Applications To Asset Pricing Models That Include A Mismeasured Factor.
  Todd Prono.
  Journal of Applied Econometrics. June 26, 2013
  A new estimator is proposed for linear triangular systems, where identification results from the model errors following a bivariate and diagonal GARCH(1,1) process with potentially time‐varying error covariances. This estimator applies when traditional instruments are unavailable. I demonstrate its usefulness on asset pricing models like the capital asset pricing model and Fama–French three‐factor model. In the context of a standard two‐pass cross‐sectional regression approach, this estimator improves the pricing performance of both models. Set identification bounds and an associated estimator are also provided for cases where the conditions supporting point identification fail. Copyright © 2013 John Wiley & Sons, Ltd.

  June 26, 2013   doi: 10.1002/jae.2340   open full text
• Modelling Regime Switching And Structural Breaks With An Infinite Hidden Markov Model.
  Yong Song.
  Journal of Applied Econometrics. June 26, 2013
  This paper proposes an infinite hidden Markov model to integrate the regime switching and structural break dynamics in a unified Bayesian framework. Two parallel hierarchical structures, one governing the transition probabilities and another governing the parameters of the conditional data density, keep the model parsimonious and improve forecasts. This flexible approach allows for regime persistence and estimates the number of states automatically. An application to US real interest rates compares the new model to existing parametric alternatives. Copyright © 2013 John Wiley & Sons, Ltd.

  June 26, 2013   doi: 10.1002/jae.2337   open full text
• The Dynamics Of Real Exchange Rates: A Reconsideration.
  Hendrik Kaufmann, Florian Heinen, Philipp Sibbertsen.
  Journal of Applied Econometrics. June 26, 2013
  In this paper we offer a bootstrap‐based version of the Cox specification test for non‐nested hypothesis to discriminate between ESTAR and MSAR models. Both models are commonly used for modeling real exchange rates dynamics. We show that thetest has good size and power properties in finite samples. In an application, we analyze several major real exchange rates to shed light on the question of which model describes these processes best. This allows us to draw conclusions about the driving forces of real exchange rates. Copyright © 2013 John Wiley & Sons, Ltd.

  June 26, 2013   doi: 10.1002/jae.2336   open full text
• Is Economic Recovery A Myth? Robust Estimation Of Impulse Responses.
  Coen N. Teulings, Nikolay Zubanov.
  Journal of Applied Econometrics. June 20, 2013
  We estimate the impulse response function (IRF) of GDP to a banking crisis using an extension of the local projections method. We demonstrate that, though robust to misspecifications of the data‐generating process, this method suffers from a hitherto unnoticed bias which increases with the forecast horizon. We propose a correction to this bias and show through simulations that it works well. Applying our corrected local projections estimator to the data from a panel of 99 countries observed between 1974 and 2001, we find that an average banking crisis yields a GDP loss of just under 10% in 10 years, with little sign of recovery. Like the original local projections method, our extension of it is widely applicable. Copyright © 2013 John Wiley & Sons, Ltd.

  June 20, 2013   doi: 10.1002/jae.2333   open full text
• Does Coresidence Improve An Elderly Parent's Health?
  Meliyanni Johar, Shiko Maruyama.
  Journal of Applied Econometrics. June 19, 2013
  It is generally believed that intergenerational coresidence by elderly parents and adult children provides old‐age security for parents. Although such coresidence is still the most common living arrangement in many countries, empirical evidence of its benefits to parental health is scarce. Using Indonesian data and a program evaluation technique that accounts for non‐random selection and heterogeneous treatment effect, we find robust evidence of a negative coresidence effect. We also find heterogeneity in the coresidence effect. Socially active elderly parents are less likely to be in coresidence, and when they do live with a child they experience a better coresidence effect. Copyright © 2013 John Wiley & Sons, Ltd.

  June 19, 2013   doi: 10.1002/jae.2339   open full text
• The Predictability Of Aggregate Consumption Growth In Oecd Countries: A Panel Data Analysis.
  Gerdie Everaert, Lorenzo Pozzi.
  Journal of Applied Econometrics. June 19, 2013
  We examine aggregate consumption growth predictability. We derive a dynamic consumption equation which encompasses relevant predictability factors: habit formation, intertemporal substitution, current income consumption and non‐separabilities between private consumption and both hours worked and government consumption. We estimate this equation for a panel of 15 OECD countries over the period 1972–2007, taking into account parameter heterogeneity, endogeneity and error cross‐sectional dependence using a GMM version of the common correlated effects mean group estimator. Small‐sample properties are demonstrated using Monte Carlo simulations. The estimation results support income growth as the only variable with significant predictive power for aggregate consumption growth. Copyright © 2013 John Wiley & Sons, Ltd.

  June 19, 2013   doi: 10.1002/jae.2338   open full text
• Cost And Preference Heterogeneity In Risky Financial Markets.
  Graciela Sanroman.
  Journal of Applied Econometrics. June 19, 2013
  This paper estimates the magnitude of participation costs and preference parameters exploiting information on households’ participation decisions in the equities market. A structural model for portfolio choices over the life cycle is solved numerically. The parameters of interest are estimated using an Indirect Inference approach which makes use of the computed participation gains/losses. Participation costs are found to be significant, education and lagged participation being the major sources of heterogeneity. Also, the least educated are the least risk averse, and the positive effect of risk aversion on wealth accumulation dominates its negative influence on the risky asset demand. Copyright © 2013 John Wiley & Sons, Ltd.

  June 19, 2013   doi: 10.1002/jae.2328   open full text
• Identifying The Response Of Fertility To Financial Incentives.
  Guy Laroque, Bernard Salanié.
  Journal of Applied Econometrics. June 17, 2013
  While using financial incentives to increase fertility has become relatively common, the effects of such policies are difficult to assess. We propose an identification strategy that relies on the fact that the variation in wages induces variation in benefits and tax credits among ‘comparable’ households. We implement our approach by estimating a discrete‐choice model of female participation and fertility using individual data from the French Labor Force Survey and a detailed representation of the French tax–benefit system. Our results suggest that financial incentives have had a significant effect on fertility decisions in France. As an example, we simulate the effects of an additional, unconditional child credit of 150 euros per month. The effects are strongest for the third child. Copyright © 2013 John Wiley & Sons, Ltd.

  June 17, 2013   doi: 10.1002/jae.2332   open full text
• Smooth Dynamic Factor Analysis With Application To The Us Term Structure Of Interest Rates.
  Borus Jungbacker, Siem Jan Koopman, Michel Wel.
  Journal of Applied Econometrics. June 03, 2013
  We consider the dynamic factor model and show how smoothness restrictions can be imposed on factor loadings by using cubic spline functions. We develop statistical procedures based on Wald, Lagrange multiplier and likelihood ratio tests for this purpose. The methodology is illustrated by analyzing a newly updated monthly time series panel of US term structure of interest rates. Dynamic factor models with and without smooth loadings are compared with dynamic models based on Nelson–Siegel and cubic spline yield curves. We conclude that smoothness restrictions on factor loadings are supported by the interest rate data and can lead to more accurate forecasts. Copyright © 2013 John Wiley & Sons, Ltd.

  June 03, 2013   doi: 10.1002/jae.2319   open full text
• Multiple Event Incidence And Duration Analysis For Credit Data Incorporating Non‐Stochastic Loan Maturity.
  John G. T. Watkins, Andrey L. Vasnev, Richard Gerlach.
  Journal of Applied Econometrics. May 29, 2013
  Applications of duration analysis in economics and finance exclusively employ methods for events of stochastic duration. In application to credit data, previous research incorrectly treats the time to predetermined maturity events as censored stochastic event times. The medical literature has binary parametric ‘cure rate’ models that deal with populations that never experienced the modelled event. We propose and develop a multinomial parametric incidence and duration model, incorporating such populations. In the class of cure rate models, this is the first fully parametric multinomial model and is the first framework to accommodate an event with predetermined duration. The methodology is applied to unsecured personal loan credit data provided by one of Australia's largest financial services organizations. This framework is shown to be more flexible and predictive through a simulation and empirical study that reveals: simulation results of estimated parameters with a large reduction in bias; superior forecasting of duration; explanatory variables can act in different directions upon incidence and duration; and variables exist that are statistically significant in explaining only incidence or duration. Copyright © 2013 John Wiley & Sons, Ltd.

  May 29, 2013   doi: 10.1002/jae.2329   open full text
• Disentangling Demand And Supply Shocks In The Crude Oil Market: How To Check Sign Restrictions In Structural Vars.
  Helmut Lütkepohl, Aleksei NetŠunajev.
  Journal of Applied Econometrics. May 28, 2013
  Sign restrictions have become increasingly popular for identifying shocks in structural vector autoregressive (SVAR) models. So far there are no techniques for validating the shocks identified via such restrictions. Although in an ideal setting the sign restrictions specify shocks of interest, sign restrictions may be invalidated by measurement errors, data adjustments or omitted variables. We model changes in the volatility of the shocks via a Markov switching (MS) mechanism and use this device to give the data a chance to object to sign restrictions. The approach is illustrated by considering a small model for the market of crude oil. Earlier findings that oil supply shocks explain only a very small fraction of movements in the price of oil are confirmed and it is found that the importance of aggregate demand shocks for oil price movements has declined since the mid 1980s. Copyright © 2013 John Wiley & Sons, Ltd.

  May 28, 2013   doi: 10.1002/jae.2330   open full text
• Strategic Asset Allocation For Long‐Term Investors: Parameter Uncertainty And Prior Information.
  Roy P. P. M. Hoevenaars, Roderick D. J. Molenaar, Peter C. Schotman, Tom B. M. Steenkamp.
  Journal of Applied Econometrics. May 28, 2013
  We study the effect of parameter uncertainty on the long‐run risk for three asset classes: stocks, bills and bonds. Using a Bayesian vector autoregression with an uninformative prior we find that parameter uncertainty raises the annualized long‐run volatilities of all three asset classes proportionally with the same factor relative to volatilities that are conditional on maximum likelihood parameter estimates. As a result, the horizon effect in optimal asset allocations is much weaker compared to models in which only equity returns are subject to parameter uncertainty. Results are sensitive to alternative informative priors, but generally the term structure of risk for stocks and bonds is relatively flat for investment horizons up to 15 years. Copyright © 2013 John Wiley & Sons, Ltd.

  May 28, 2013   doi: 10.1002/jae.2331   open full text
• Multiple Testing And Heterogeneous Treatment Effects: Re‐Evaluating The Effect Of Progresa On School Enrollment.
  Soohyung Lee, Azeem M. Shaikh.
  Journal of Applied Econometrics. April 28, 2013
  The effect of a program or treatment may vary according to observed characteristics. In such a setting, it may not only be of interest to determine whether the program or treatment has an effect on some sub‐population defined by these observed characteristics, but also to determine for which sub‐populations, if any, there is an effect. This paper treats this problem as a multiple testing problem in which each null hypothesis in the family of null hypotheses specifies whether the program has an effect on the outcome of interest for a particular sub‐population. We develop our methodology in the context of PROGRESA, a large‐scale poverty‐reduction program in Mexico. In our application, the outcome of interest is the school enrollment rate and the sub‐populations are defined by gender and highest grade completed. Under weak assumptions, the testing procedure we construct controls the familywise error rate—the probability of even one false rejection—in finite samples. Similar to earlier studies, we find that the program has a significant effect on the school enrollment rate, but only for a much smaller number of sub‐populations when compared to results that do not adjust for multiple testing. Copyright © 2013 John Wiley & Sons, Ltd.

  April 28, 2013   doi: 10.1002/jae.2327   open full text
• Estimation Of Censored Panel‐Data Models With Slope Heterogeneity.
  Jason Abrevaya, Shu Shen.
  Journal of Applied Econometrics. April 28, 2013
  This paper considers estimation of censored panel‐data models with individual‐specific slope heterogeneity. The slope heterogeneity may be random (random slopes model) or related to covariates (correlated random slopes model). Maximum likelihood and censored least‐absolute deviations estimators are proposed for both models. The estimators are simple to implement and, in the case of maximum likelihood, lead to straightforward estimation of partial effects. The rescaled bootstrap suggested by Andrews (Econometrica 2000; 68: 399–405) is used to deal with the possibility of variance parameters being equal to zero. The methodology is applied to an empirical study of Dutch household portfolio choice, where the outcome variable (portfolio share in safe assets) has corner solutions at zero and one. As predicted by economic theory, there is strong evidence of correlated random slopes for the age profiles, indicating a heterogeneous age profile of portfolio adjustment that varies significantly with other household characteristics. Copyright © 2013 John Wiley & Sons, Ltd.

  April 28, 2013   doi: 10.1002/jae.2325   open full text
• Using Ols To Estimate And Test For Structural Changes In Models With Endogenous Regressors.
  Pierre Perron, Yohei Yamamoto.
  Journal of Applied Econometrics. April 28, 2013
  We consider the problem of estimating and testing for multiple breaks in a single‐equation framework with regressors that are endogenous, i.e. correlated with the errors. We show that even in the presence of endogenous regressors it is still preferable, in most cases, to simply estimate the break dates and test for structural change using the usual ordinary least squares (OLS) framework. Except for some knife‐edge cases, it delivers estimates of the break dates with higher precision and tests with higher power compared to those obtained using an instrumental variable (IV) method. Also, the OLS method avoids potential weak identification problems caused by weak instruments. To illustrate the relevance of our theoretical results, we consider the stability of the New Keynesian hybrid Phillips curve. IV‐based methods only provide weak evidence of instability. On the other hand, OLS‐based ones strongly indicate a change in 1991:Q1 and that after this date the model loses all explanatory power. Copyright © 2013 John Wiley & Sons, Ltd.

  April 28, 2013   doi: 10.1002/jae.2320   open full text
• A Tip Of The Iceberg? The Probability Of Catching Cartels.
  Peter L. Ormosi.
  Journal of Applied Econometrics. April 25, 2013
  Reliable estimates of crime detection probabilities could help in designing better sanctions and improve our understanding of the efficiency of law enforcement. For cartels, we only have limited knowledge on the rate at which these illegal practices are discovered. In comparison to previous works, this paper offers a more parsimonious and simple‐to‐use method to estimate time‐dependent cartel discovery rates, while allowing for heterogeneity across firms. It draws on capture–recapture methods that are frequently used in ecology to make inferences on various wildlife population characteristics. An application of this method provides evidence that less than a fifth of cartelising firms are discovered. Copyright © 2013 John Wiley & Sons, Ltd.

  April 25, 2013   doi: 10.1002/jae.2326   open full text
• Monetary Policy And The Housing Market: A Structural Factor Analysis.
  Matteo Luciani.
  Journal of Applied Econometrics. April 18, 2013
  This paper studies the role of the Federal Reserve's policy in the recent boom and bust of the housing market, and in the ensuing recession. By estimating a structural dynamic factor model on a panel of 109 US quarterly variables from 1982 to 2010, we find that, although the Federal Reserve's policy between 2002 and 2004 was slightly expansionary, its contribution to the recent housing cycle was negligible. We also show that a more restrictive policy would have smoothed the cycle but not prevented the recession. We thus find no role for the Federal Reserve in causing the recession. Copyright © 2013 John Wiley & Sons, Ltd.

  April 18, 2013   doi: 10.1002/jae.2318   open full text
• Modelling Large Open Economies With International Linkages: The Usa And Euro Area.
  Mardi Dungey, Denise R. Osborn.
  Journal of Applied Econometrics. April 18, 2013
  Empirical modelling of the linkages between the euro area and the USA requires an open economy framework. The methodology proposed in this paper achieves identification of a structural vector error correction model by supplementing restrictions from economic theory with assumptions for the direction of causality in cross‐country contemporaneous relationships. Our baseline model assumes contemporaneous causality runs from the USA to the euro area for both output and inflation, with monetary policy domestically focused. The role of the USA as leading the euro area business cycle is reinforced by our results, but strong bidirectional cross‐country interactions are uncovered for inflation and interest rates. Copyright © 2013 John Wiley & Sons, Ltd.

  April 18, 2013   doi: 10.1002/jae.2323   open full text
• The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil.
  Lutz Kilian, Daniel P. Murphy.
  Journal of Applied Econometrics. April 10, 2013
  We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short‐run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.

  April 10, 2013   doi: 10.1002/jae.2322   open full text
• Rounding, Focal Point Answers And Nonresponse To Subjective Probability Questions.
  Kristin J. Kleinjans, Arthur Van Soest.
  Journal of Applied Econometrics. April 10, 2013
  We develop a panel data model explaining answers to subjective probabilities about binary events and estimate it using data from the Health and Retirement Study on six such probabilities. The model explicitly accounts for several forms of ‘reporting behavior’: rounding, focal point ‘50%’ answers and item nonresponse. We find observed and unobserved heterogeneity in the tendencies to report rounded values or a focal answer, explaining persistency in 50% answers over time. Focal 50% answers matter for some of the probabilities. Incorporating reporting behavior does not have a large effect on the estimated distribution of the genuine subjective probabilities. Copyright © 2013 John Wiley & Sons, Ltd.

  April 10, 2013   doi: 10.1002/jae.2321   open full text
• Bayesian Vars: Specification Choices And Forecast Accuracy.
  Andrea Carriero, Todd E. Clark, Massimiliano Marcellino.
  Journal of Applied Econometrics. March 26, 2013
  In this paper we discuss how the point and density forecasting performance of Bayesian vector autoregressions (BVARs) is affected by a number of specification choices. We adopt as a benchmark a common specification in the literature, a BVAR with variables entering in levels and a prior modeled along the lines of Sims and Zha (International Economic Review 1998; 39: 949–968). We then consider optimal choice of the tightness, of the lag length and of both; evaluate the relative merits of modeling in levels or growth rates; compare alternative approaches to h‐step‐ahead forecasting (direct, iterated and pseudo‐iterated); discuss the treatment of the error variance and of cross‐variable shrinkage; and assess rolling versus recursive estimation. Finally, we analyze the robustness of the results to the VAR size and composition (using also data for France, Canada and the UK, while the main analysis is for the USA). We obtain a large set of empirical results, but the overall message is that we find very small losses (and sometimes even gains) from the adoption of specification choices that make BVAR modeling quick and easy, in particular for point forecasting. This finding could therefore further enhance the diffusion of the BVAR as an econometric tool for a vast range of applications. Copyright © 2013 John Wiley & Sons, Ltd.

  March 26, 2013   doi: 10.1002/jae.2315   open full text
• The Effects Of Expanding The Generosity Of The Statutory Sickness Insurance System.
  Nicolas R. Ziebarth, Martin Karlsson.
  Journal of Applied Econometrics. March 25, 2013
  This article evaluates an expansion of employer‐mandated sick leave from 80% to 100% of forgone gross wages in Germany. We employ and compare parametric difference‐in‐difference (DID), matching DID and mixed approaches. Overall workplace absences increased by at least 10% or 1 day per worker per year. We show that taking partial compliance into account increases coefficient estimates. Further, heterogeneity in response behavior was of great importance. There is no evidence that the increase in sick leave improved employee health, a finding that supports a shirking explanation. Finally, we provide evidence on potential labor market adjustments to the reform. Copyright © 2013 John Wiley & Sons, Ltd.

  March 25, 2013   doi: 10.1002/jae.2317   open full text
• Tests Of Equal Forecast Accuracy For Overlapping Models.
  Todd E. Clark, Michael W. Mccracken.
  Journal of Applied Econometrics. March 21, 2013
  This paper examines the asymptotic and finite‐sample properties of tests of equal forecast accuracy when the models being compared are overlapping in the sense of Vuong (Econometrica 1989; 57: 307–333). Two models are overlapping when the true model contains just a subset of variables common to the larger sets of variables included in the competing forecasting models. We consider an out‐of‐sample version of the two‐step testing procedure recommended by Vuong but also show that an exact one‐step procedure is sometimes applicable. When the models are overlapping, we provide a simple‐to‐use fixed‐regressor wild bootstrap that can be used to conduct valid inference. Monte Carlo simulations generally support the theoretical results: the two‐step procedure is conservative, while the one‐step procedure can be accurately sized when appropriate. We conclude with an empirical application comparing the predictive content of credit spreads to growth in real stock prices for forecasting US real gross domestic product growth. Copyright © 2013 John Wiley & Sons, Ltd.

  March 21, 2013   doi: 10.1002/jae.2316   open full text
• How Sensitive Are Retirement Decisions To Financial Incentives? A Stated Preference Analysis.
  Arthur Van Soest, Hana Vonkova.
  Journal of Applied Econometrics. January 24, 2013
  We study the effects of financial incentives on retirement decisions using stated preference data. Dutch survey respondents were given hypothetical retirement scenarios describing age(s) of (partial and full) retirement and replacement rate(s). A stylized model is estimated in which utility is the discounted sum of within‐period utilities that depend on employment status and income. Parameters of the utility function vary with observed and unobserved characteristics. Simulations show that the income and substitution effects of pensions as a function of the retirement age are substantial and larger than according to studies using data on actual retirement decisions in the Netherlands. Copyright © 2013 John Wiley & Sons, Ltd.

  January 24, 2013   doi: 10.1002/jae.2313   open full text
• The Demand For Gasoline: Evidence From Household Survey Data.
  Dongfeng Chang, Apostolos Serletis.
  Journal of Applied Econometrics. January 21, 2013
  In this paper we investigate the demand for gasoline in Canada using recent annual expenditure data from the Canadian Survey of Household Spending, over a 13‐year period from 1997 to 2009, on three expenditure categories in the transportation sector: gasoline, local transportation, and intercity transportation. In doing so, we use three of the most widely used locally flexible functional forms, the Almost Ideal Demand System (AIDS) of Deaton and Muellbauer (1980), the quadratic AIDS (QUAIDS) of Banks et al. (1997)—an extension of the simple AIDS model that can generate quadratic Engel curves—and the Minflex Laurent model of Barnett (1983), which can also generate quadratic Engel curves. We pay explicit attention to economic regularity, argue that unless regularity is attained by luck, flexible functional forms should always be estimated subject to regularity as suggested by Barnett (2002), and impose local curvature to produce inference consistent with neoclassical microeconomic theory. Our findings indicate that the curvature‐constrained Minflex Laurent model is the only model that is able to provide theoretically consistent estimates of the Canadian demand for gasoline. Our estimates show that the own‐price elasticity for gasoline demand in Canada is between − 0.738 and − 0.570 —less elastic than previously reported in the literature. Copyright © 2013 John Wiley & Sons, Ltd.

  January 21, 2013   doi: 10.1002/jae.2312   open full text
• Exchange Rate Fundamentals, Forecasting, And Speculation: Bayesian Models In Black Markets.
  Robert Gramacy, Samuel W. Malone, Enrique Ter Horst.
  Journal of Applied Econometrics. January 21, 2013
  Although speculative activity is central to black markets for currency, the out‐of‐sample performance of structural models in those settings is unknown. We substantially update the literature on empirical determinants of black market rates and evaluate the out‐of‐sample performance of linear models and non‐parametric Bayesian treed Gaussian process (BTGP) models against the random walk benchmark. Fundamentals‐based models outperform the benchmark in out‐of‐sample prediction accuracy and trading rule profitability measures given future values of fundamentals. In simulated real‐time trading exercises, however, the BTGP achieves superior realized profitability, accuracy and market timing, while linear models do no better than a random walk. Copyright © 2013 John Wiley & Sons, Ltd.

  January 21, 2013   doi: 10.1002/jae.2314   open full text
• Nonlinear Growth Effects Of Taxation: A Semi‐Parametric Approach Using Average Marginal Tax Rates.
  K. Peren Arin, Michael Berlemann, Faik Koray, Torben Kuhlenkasper.
  Journal of Applied Econometrics. January 21, 2013
  One of the major challenges of empirical tax research is the identification and calculation of appropriate tax data. While there is consensus that average marginal tax rates are most suitable for studying the effects of tax policy on economic growth, because of data limitations the calculation of marginal tax rates has been limited to the USA and the UK. This paper provides calculations of average marginal tax rates for the four Scandinavian countries using the methodologies of Seater (1982, 1985) and Barro and Sahasakul (1983, 1986). Then, by pooling the newly calculated tax rates for the Scandinavian countries with the data for the USA and the UK, we investigate the effects of tax policy shocks on the per capita GDP growth rate. Our results suggest that an increase in average marginal tax rates has a negative impact on economic growth. Employing additive mixed panel models with penalized splines as estimation approach, we show that changes in tax rates have nonlinear effects. Increasing average marginal tax rates turn out to be the most distorting at relatively moderate tax rates. Copyright © 2013 John Wiley & Sons, Ltd.

  January 21, 2013   doi: 10.1002/jae.2311   open full text
• Divorce Law Reforms And Divorce Rates In The Usa: An Interactive Fixed‐Effects Approach.
  Dukpa Kim, Tatsushi Oka.
  Journal of Applied Econometrics. January 07, 2013
  This paper estimates the effects of unilateral divorce laws on divorce rates in the USA from a panel of state‐level divorce rates. We use the interactive fixed‐effects model to address the issue of endogeneity due to the association between cross‐state unobserved heterogeneity and divorce law reforms. We document that earlier studies in the literature do not fully control for unobserved heterogeneity and result in mixed empirical evidence on the effects of divorce law reforms. While reconciling these conflicting results, our results suggest that divorce law reforms have temporal positive effects on divorce rates, thus confirming the 2006 findings of Wolfers. Via simulation experiments, we assess the degree to which faulty inclusion or faulty exclusion of interactive fixed effects affects the policy effect estimators. Our results suggest that faulty inclusion only results in efficiency loss whereas faulty exclusion causes bias. Copyright © 2012 John Wiley & Sons, Ltd.

  January 07, 2013   doi: 10.1002/jae.2310   open full text
• Maximum Likelihood Estimation Of Factor Models On Datasets With Arbitrary Pattern Of Missing Data.
  Marta Bańbura, Michele Modugno.
  Journal of Applied Econometrics. November 12, 2012
  In this paper we modify the expectation maximization algorithm in order to estimate the parameters of the dynamic factor model on a dataset with an arbitrary pattern of missing data. We also extend the model to the case with a serially correlated idiosyncratic component. The framework allows us to handle efficiently and in an automatic manner sets of indicators characterized by different publication delays, frequencies and sample lengths. This can be relevant, for example, for young economies for which many indicators have been compiled only recently. We evaluate the methodology in a Monte Carlo experiment and we apply it to nowcasting of the euro area gross domestic product. Copyright © 2012 John Wiley & Sons, Ltd.

  November 12, 2012   doi: 10.1002/jae.2306   open full text
• Information In The Yield Curve: A Macro‐Finance Approach.
  Hans Dewachter, Leonardo Iania, Marco Lyrio.
  Journal of Applied Econometrics. October 16, 2012
  We use a macro‐finance model, incorporating macroeconomic and financial factors, to study the term premium in the US bond market. Estimating the model using Bayesian techniques, we find that a single factor explains most of the variation in bond risk premiums. Furthermore, the model‐implied risk premiums account for up to 40% of the variability of one‐ and two‐year excess returns. Using the model to decompose yield spreads into an expectations and a term premium component, we find that, although this decomposition does not seem important to forecast economic activity, it is crucial to forecast inflation for most forecasting horizons. Copyright © 2012 John Wiley & Sons, Ltd.

  October 16, 2012   doi: 10.1002/jae.2305   open full text
• Firm Heterogeneity, Persistent And Transient Technical Inefficiency: A Generalized True Random‐Effects Model.
  Efthymios G. Tsionas, Subal C. Kumbhakar.
  Journal of Applied Econometrics. September 25, 2012
  This paper considers a panel data stochastic frontier model that disentangles unobserved firm effects (firm heterogeneity) from persistent (time‐invariant/long‐term) and transient (time‐varying/short‐term) technical inefficiency. The model gives us a four‐way error component model, viz., persistent and time‐varying inefficiency, random firm effects and noise. We use Bayesian methods of inference to provide robust and efficient methods of estimating inefficiency components in this four‐way error component model. Monte Carlo results are provided to validate its performance. We also present results from an empirical application that uses a large panel of US commercial banks. Copyright © 2012 John Wiley & Sons, Ltd.

  September 25, 2012   doi: 10.1002/jae.2300   open full text
• Comparing Alternative Models Of Heterogeneity In Consumer Choice Behavior.
  Michael Keane, Nada Wasi.
  Journal of Applied Econometrics. September 24, 2012
  When modeling demand for differentiated products, it is vital to adequately capture consumer taste heterogeneity, But there is no clearly preferred approach. Here, we compare the performance of six alternative models. Currently, the most popular are mixed logit (MIXL), particularly the version with normal mixing (N‐MIXL), and latent class (LC), which assumes discrete consumer types. Recently, several alternative models have been developed. The 'generalized multinomial logit' (G‐MNL) extends N‐MIXL by allowing for heterogeneity in the logit scale coefficient. Scale heterogeneity logit (S‐MNL) is a special case of G‐MNL with scale heterogeneity only. The 'mixed‐mixed' logit (MM‐MNL) assumes a discrete mixture‐of‐normals heterogeneity distribution. Finally, one can modify N‐MIXL by imposing theoretical sign constraints on vertical attributes. We call this 'T‐MIXL'. We find that none of these models dominates the others, but G‐MNL, MM‐MNL and T‐MIXL typically outperform the popular N‐MIXL and LC models. Copyright © 2012 John Wiley & Sons, Ltd.

  September 24, 2012   doi: 10.1002/jae.2304   open full text
• Semiparametric Vector Mem.
  Fabrizio Cipollini, Robert F. Engle, Giampiero M. Gallo.
  Journal of Applied Econometrics. September 18, 2012
  Financial time series are often non‐negative‐valued (volumes, trades, durations, realized volatility, daily range) and exhibit clustering. When joint dynamics is of interest, the vector multiplicative error model (vMEM; the element‐by‐element product of a vector of conditionally autoregressive scale factors and a multivariate i.i.d. innovation process) is a suitable strategy. Its parameters can be estimated by generalized method of moments, bypassing the problem of specifying a multivariate distribution for the errors. Simulated results show the gains in efficiency relative to an equation‐by‐equation approach. A vMEM on several measures of volatility justifies a joint approach revealing full interdependence. Copyright © 2012 John Wiley & Sons, Ltd.

  September 18, 2012   doi: 10.1002/jae.2292   open full text
• State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator.
  Jesus M. Carro, Alejandra Traferri.
  Journal of Applied Econometrics. September 02, 2012
  This paper estimates a dynamic ordered probit model of self‐assessed health with two fixed effects: one in the linear index equation and one in the cut‐points. This robustly controls for heterogeneity in unobserved health status and in reporting behavior, although we cannot separate both sources of heterogeneity. We find important state dependence effects, and small but significant effects of income and other socioeconomic variables. Having dynamics and flexibly accounting for unobserved heterogeneity matters for those estimates. We also contribute to the bias correction literature in nonlinear panel models by comparing and applying two of the existing proposals to our model. Copyright © 2012 John Wiley & Sons, Ltd.

  September 02, 2012   doi: 10.1002/jae.2301   open full text
• Numerical Distribution Functions Of Fractional Unit Root And Cointegration Tests.
  James G. MacKinnon, Morten Ørregaard Nielsen.
  Journal of Applied Econometrics. September 02, 2012
  We calculate, by simulations, numerical asymptotic distribution functions of likelihood ratio tests for fractional unit roots and cointegration rank. Because these distributions depend on a real‐valued parameter b which must be estimated, simple tabulation is not feasible. Partly owing to the presence of this parameter, the choice of model specification for the response surface regressions used to obtain the numerical distribution functions is more involved than is usually the case. We deal with model uncertainty by model averaging rather than by model selection. We make available a computer program which, given the dimension of the problem, q, and a value of b, provides either a set of critical values or the asymptotic P‐value for any value of the likelihood ratio statistic. Copyright © 2012 John Wiley & Sons, Ltd.

  September 02, 2012   doi: 10.1002/jae.2295   open full text
• Estimation Of Time‐Varying Adjusted Probability Of Informed Trading And Probability Of Symmetric Order‐Flow Shock.
  Daniel Preve, Yiu‐Kuen Tse.
  Journal of Applied Econometrics. August 31, 2012
  Recently, Duarte and Young (2009) studied the probability of informed trading (PIN) proposed by Easley et al. (2002) and decomposed it into two parts: the adjusted PIN (APIN) as a measure of asymmetric information and the probability of symmetric order‐flow shock (PSOS) as a measure of illiquidity. They provide some cross‐section estimates of these measures using daily data over annual periods. In this paper we propose a method to estimate daily APIN and PSOS by extending the method in Tay et al. (2009) using high‐frequency transaction data. Our empirical results show that while PIN is positively contemporaneously correlated with variance, APIN is not. On the other hand, PSOS is positively correlated with daily average effective spread and variance, which is consistent with the interpretation of PSOS as a measure of illiquidity. Compared to APIN, PSOS exhibits clustering and sporadic bursts over time. Copyright © 2012 John Wiley & Sons, Ltd.

  August 31, 2012   doi: 10.1002/jae.2302   open full text
• Do Peers Affect Student Achievement? Evidence From Canada Using Group Size Variation.
  Vincent Boucher, Yann Bramoullé, Habiba Djebbari, Bernard Fortin.
  Journal of Applied Econometrics. August 30, 2012
  We provide the first empirical application of a new approach proposed by Lee (Journal of Econometrics 2007; 140(2), 333–374) to estimate peer effects in a linear‐in‐means model when individuals interact in groups. Assumingsufficient group size variation, this approach allows to control for correlated effects at the group level and to solve the simultaneity (reflection) problem. We clarify the intuition behind identification of peer effects in the model. We investigate peer effects in student achievement in French, Science, Mathematics and History in secondary schools in the Province of Québec (Canada). We estimate the model using conditional maximum likelihood and instrumental variables methods. We find some evidence of peer effects. The endogenous peer effect is large and significant in Mathematics but imprecisely estimated in the other subjects. Some contextual peer effects are also significant. In particular, for most subjects, the average age of peers has a negative effect on own test score. Using calibrated Monte Carlo simulations, we find that high dispersion in group sizes helps with potential issues of weak identification. Copyright © 2012 John Wiley & Sons, Ltd.

  August 30, 2012   doi: 10.1002/jae.2299   open full text
• An Empirical Growth Model For Major Oil Exporters.
  Hadi Salehi Esfahani, Kamiar Mohaddes, M. Hashem Pesaran.
  Journal of Applied Econometrics. August 10, 2012
  This paper develops a long‐run output relation for a major oil‐exporting economy where the oil income‐to‐output ratio remains sufficiently high over a prolonged period. It extends the stochastic growth model developed in Binder and Pesaran (1999) by including oil exports as an additional factor in the capital accumulation process. The paper distinguishes between the two cases where the growth of oil income, go, is less than the natural growth rate (the sum of the population growth, n, and the growth of technical progress, g), and when go ≥ g + n. Under the former, the effects of oil income on the economy's steady growth rate will vanish eventually, while under the latter oil income enters the long‐run output equation with a coefficient which is equal to the share of capital if it is further assumed that the underlying production technology can be represented by a Cobb–Douglas production function. The long‐run theory is tested using quarterly data on nine major oil economies. Overall, the test results support the long‐run theory, with the existence of long‐run relations between real output, foreign output and real oil income established for six of the nine economies considered. Copyright © 2012 John Wiley & Sons, Ltd.

  August 10, 2012   doi: 10.1002/jae.2294   open full text
• Time Variation In The Dynamics Of Worker Flows: Evidence From North America And Europe.
  Michele Campolieti, Deborah Gefang, Gary Koop.
  Journal of Applied Econometrics. August 07, 2012
  Vector autoregressive methods have been used to model the interrelationships between job vacancy rates, job separation rates and job‐finding rates using tools such as impulse response analysis. We investigate whether such impulse responses change across the business cycle or over time, by estimating time‐varying parameter–vector autoregressions for data from North America (the USA and Canada) and Europe (France, Spain and the UK). While the adjustment process of the labour market to shocks in Canada and the USA is similar, we find the adjustment process differs much more across the European countries, with greater persistence in shocks relative to the USA and Canada. Copyright © 2012 John Wiley & Sons, Ltd.

  August 07, 2012   doi: 10.1002/jae.2296   open full text
• Are The Current Account Imbalances Between Emu Countries Sustainable? Evidence From Parametric And Non‐Parametric Tests.
  Christian Schoder, Christian R. Proaño, Willi Semmler.
  Journal of Applied Econometrics. July 25, 2012
  Using parametric and non‐parametric estimation techniques, we analyze the sustainability of the recently growing current account imbalances in the euro area and test whether the European Monetary Union has aggravated these imbalances. Two alternative criteria for the assessment of external debt sustainability are considered: one based on the transversality condition of intertemporal optimization, and the other based on the stationarity properties of the stochastic process of the debt–GDP ratio. Econometric sustainability tests are performed using the pooled mean‐group estimator and panel unit root tests, respectively. Variants of both test procedures with varying coefficients using penalized splines estimation are applied. We find empirical evidence suggesting that the introduction of the euro is associated with a regime shift from sustainability to unsustainability of external debt accumulation for the euro area. Copyright © 2012 John Wiley & Sons, Ltd.

  July 25, 2012   doi: 10.1002/jae.2291   open full text
• Semi‐Nonparametric Estimation Of Consumer Search Costs.
  José Luis Moraga‐González, Zsolt Sándor, Matthijs R. Wildenbeest.
  Journal of Applied Econometrics. June 26, 2012
  This paper studies the estimation of the distribution of non‐sequential search costs. We show that the search cost distribution is identified by combining data from multiple markets with common search technology but varying consumer valuations, firms' costs, and numbers of competitors. To exploit such data optimally, we provide a new method based on semi‐nonparametric estimation. We apply our method to a dataset of online prices for memory chips and find that the search cost density is essentially bimodal, such that a large fraction of consumers searches very little, whereas a smaller fraction searches a relatively large number of stores. Copyright © 2012 John Wiley & Sons, Ltd.

  June 26, 2012   doi: 10.1002/jae.2290   open full text
• Panel Probit With Flexible Correlated Effects: Quantifying Technology Spillovers In The Presence Of Latent Heterogeneity.
  Martin Burda, Matthew Harding.
  Journal of Applied Econometrics. June 26, 2012
  In this paper, we introduce a Bayesian panel probit model with two flexible latent effects: first, unobserved individual heterogeneity that is allowed to vary in the population according to a nonparametric distribution; and second, a latent serially correlated common error component. In doing so, we extend the approach developed in Albert and Chib (Journal of the American Statistical Association 1993; 88: 669–679; in Bayesian Biostatistics, Berry DA, Stangl DK (eds), Marcel Dekker: New York, 1996), and in Chib and Carlin (Statistics and Computing 1999; 9: 17–26) by releasing restrictive parametric assumptions on the latent individual effect and eliminating potential spurious state dependence with latent time effects. The model is found to outperform more traditional approaches in an extensive series of Monte Carlo simulations. We then apply the model to the estimation of a patent equation using firm‐level data on research and development (R&D). We find a strong effect of technology spillovers on R&D but little evidence of product market spillovers, consistent with economic theory. The distribution of latent firm effects is found to have a multimodal structure featuring within‐industry firm clustering. Copyright © 2012 John Wiley & Sons, Ltd.

  June 26, 2012   doi: 10.1002/jae.2285   open full text
• The Role Of Time‐Varying Price Elasticities In Accounting For Volatility Changes In The Crude Oil Market.
  Christiane Baumeister, Gert Peersman.
  Journal of Applied Econometrics. June 26, 2012
  There has been a systematic increase in the volatility of the real price of crude oil since 1986, followed by a decline in the volatility of oil production since the early 1990s. We explore reasons for this evolution. We show that a likely explanation of this empirical fact is that both the short‐run price elasticities of oil demand and of oil supply have declined considerably since the second half of the 1980s. This implies that small disturbances on either side of the oil market can generate large price responses without large quantity movements, which helps explain the latest run‐up and subsequent collapse in the price of oil. Our analysis suggests that the variability of oil demand and supply shocks actually has decreased in the more recent past, preventing even larger oil price fluctuations than observed in the data. Copyright © 2012 John Wiley & Sons, Ltd.

  June 26, 2012   doi: 10.1002/jae.2283   open full text
• Conditionally Heteroskedastic Factor Models With Skewness And Leverage Effects.
  Prosper Dovonon.
  Journal of Applied Econometrics. June 19, 2012
  Conditional heteroskedasticity, skewness and leverage effects are well‐known features of financial returns. The literature on factor models has often made assumptions that preclude the three effects to occur simultaneously. In this paper I propose a conditionally heteroskedastic factor model that takes into account the presence of both the conditional skewness and leverage effects. This model is specified in terms of conditional moment restrictions and unconditional moment conditions are proposed allowing inference by the generalized method of moments (GMM). The model is also shown to be closed under temporal aggregation. An application to daily excess returns on sectorial indices from the UK stock market provides strong evidence for dynamic conditional skewness and leverage with a sharp efficiency gain resulting from accounting for both effects. The estimated volatilitypersistence from the proposed model is lower than that estimated from models that rule out such effects. I also find that the longer the returns' horizon, the fewer conditionally heteroskedastic factors may be required for suitable modeling and the less strong is the evidence for dynamic leverage. Some of these results are in line with the main findings of Harvey and Siddique (1999) and Jondeau and Rockinger (2003), namely that accounting for conditional skewness impacts the persistence in the conditional variance of the return process. Copyright © 2012 John Wiley & Sons, Ltd.

  June 19, 2012   doi: 10.1002/jae.2281   open full text
• Factor Analysis Of A Large Dsge Model.
  Alexei Onatski, Francisco Ruge‐Murcia.
  Journal of Applied Econometrics. June 19, 2012
  We study the workings of the factor analysis of high‐dimensional data using artificial series generated from a large, multi‐sector dynamic stochastic general equilibrium (DSGE) model. The objective is to use the DSGE model as a laboratory that allows us to shed some light on the practical benefits and limitations of using factor analysis techniques on economic data. We explain in what sense the artificial data can be thought of having a factor structure, study the theoretical properties of the principal components estimates of the factor space, investigate the substantive reason(s) for the good performance of diffusion index forecasts, and assess the quality of the factor analysis of highly disaggregated data. In all our exercises, we explain the precise relationship between the factors and the basic macroeconomic shocks postulated by the model. Copyright © 2012 John Wiley & Sons, Ltd.

  June 19, 2012   doi: 10.1002/jae.2287   open full text
• How Effective Are Unemployment Benefit Sanctions? Looking Beyond Unemployment Exit.
  Patrick Arni, Rafael Lalive, Jan C. Van Ours.
  Journal of Applied Econometrics. June 19, 2012
  This paper provides a comprehensive evaluation of the effects of benefit sanctions on post‐unemployment outcomes such as post‐unemployment employment stability and earnings. We use rich register data which allow us to distinguish between a warning that a benefit reduction may take place in the near future and the actual withdrawal of unemployment benefits. Adopting a multivariate mixed proportional hazard approach to address selectivity, we find that warnings do not affect subsequent employment stability but do reduce post‐unemployment earnings. Actual benefit reductions lower the quality of post‐unemployment jobs both in terms of job duration as well as in terms of earnings. Copyright © 2012 John Wiley & Sons, Ltd.

  June 19, 2012   doi: 10.1002/jae.2289   open full text
• Estimation of Treatment Effects without an Exclusion Restriction: with an Application to the Analysis of the School Breakfast Program.
  Daniel L. Millimet, Rusty Tchernis.
  Journal of Applied Econometrics. May 28, 2012
  The increase in childhood obesity has garnered the attention of many in policymaking circles. Consequently, school nutrition programs such as the School Breakfast Program (SBP) have come under scrutiny. The identification of the causal effects of such programs, however, is difficult owing to non‐random selection into the program and the lack of exclusion restrictions. Here, we propose two new estimators aimed at addressing this situation. We compare our new estimators to existing approaches using simulated data. We show that while correlations might suggest that SBP causes childhood obesity, SBP is likely to reduce childhood obesity once selection is addressed. Copyright © 2012 John Wiley & Sons, Ltd.

  May 28, 2012   doi: 10.1002/jae.2286   open full text
• Multivariate Volatility Modeling Of Electricity Futures.
  Luc Bauwens, Christian M. Hafner, Diane Pierret.
  Journal of Applied Econometrics. May 17, 2012
  We model the dynamic volatility and correlation structure of electricity futures of the European Energy Exchange index. We use a new multiplicative dynamic conditional correlation (mDCC) model to separate long‐run from short‐run components. We allow for smooth changes in the unconditional volatilities and correlations through a multiplicative component that we estimate nonparametrically. For the short‐run dynamics, we use a GJR‐GARCH model for the conditional variances and augmented DCC models for the conditional correlations. We also introduce exogenous variables to account for congestion and delivery date effects in short‐term conditional variances. We find different correlation dynamics for long‐ and short‐term contracts and the new model achieves higher forecasting performance compared \to a standard DCC model. Copyright © 2012 John Wiley & Sons, Ltd.

  May 17, 2012   doi: 10.1002/jae.2280   open full text
• Non‐Linear Dsge Models And The Central Difference Kalman Filter.
  Martin M. Andreasen.
  Journal of Applied Econometrics. May 17, 2012
  This paper introduces a quasi maximum likelihood approach based on the central difference Kalman filter to estimate non‐linear dynamic stochastic general equilibrium (DSGE) models with potentially non‐Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models solved up to third order. These properties are verified in a Monte Carlo study for a DSGE model solved to second and third order with structural shocks that are Gaussian, Laplace distributed, or display stochastic volatility. Copyright © 2012 John Wiley & Sons, Ltd.

  May 17, 2012   doi: 10.1002/jae.2282   open full text
• Unemployment, Human Capital Depreciation, And Unemployment Insurance Policy.
  Andreas Pollak.
  Journal of Applied Econometrics. May 16, 2012
  This paper presents a structural estimation of a life cycle model with unemployment risk. The model allows for human capital depreciation during unemployment. It is estimated using German and US household‐level data. The data suggest that the adverse impact of unemployment on individual productivity is important in both countries, but quantitatively more relevant in Germany. Moreover, simulations show that the combination of skill depreciation with the generous unemployment insurance system that was in place in Germany until recently is a key factor in explaining the differences in labour market performance between these countries. Copyright © 2012 John Wiley & Sons, Ltd.

  May 16, 2012   doi: 10.1002/jae.2275   open full text
• How Important Are Endogenous Peer Effects In Group Lending? Estimating A Static Game Of Incomplete Information.
  Shanjun Li, Yanyan Liu, Klaus Deininger.
  Journal of Applied Econometrics. May 14, 2012
  We quantify the importance of endogenous peer effects in group lending programs by estimating a static game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich dataset from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The preferred model suggests that the probability of a member making a full repayment would be 12 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity. Copyright © 2012 John Wiley & Sons, Ltd.

  May 14, 2012   doi: 10.1002/jae.2276   open full text
• Evaluating Real‐Time Var Forecasts With An Informative Democratic Prior.
  Jonathan H. Wright.
  Journal of Applied Econometrics. March 08, 2012
  This paper proposes Bayesian forecasting in a vector autoregression using a democratic prior. This prior is chosen to match the predictions of survey respondents. In particular, the unconditional mean for each series in the vector autoregression is centered around long‐horizon survey forecasts. Heavy shrinkage toward the democratic prior is found to give good real‐time predictions of a range of macroeconomic variables, as these survey projections are good at quickly capturing endpoint shifts. Copyright © 2012 John Wiley & Sons, Ltd.

  March 08, 2012   doi: 10.1002/jae.2268   open full text
• Nonparametric Estimation Of Entry Cost In First‐Price Procurement Auctions.
  Pai Xu.
  Journal of Applied Econometrics. March 05, 2012
  In this paper, I investigate Samuelson's low‐price auction model with entry costs. The model's equilibrium implies that the distribution of bids is truncated at the threshold for participation. I use the model to estimate the cost of participation in Michigan highway procurement auctions. The null hypothesis of zero entry costs is rejected. Using my empirical results, I then construct an estimate of the optimal auction, which employs regular policy tools such as entry fees. Finally, I demonstrate the savings that the Michigan government could have made on payments if optimal auctions had been employed. Copyright © 2012 John Wiley & Sons, Ltd.

  March 05, 2012   doi: 10.1002/jae.2264   open full text
• The Effect Of Parental Employment On Child Schooling.
  John Ermisch, Marco Francesconi.
  Journal of Applied Econometrics. January 20, 2012
  This paper presents a model that provides conditions under which a causal interpretation can be given to the association between childhood parental employment and subsequent educational attainments of children. The key parameter comes from theconditional demand function for children's future earning capacity. Its identification rests on having data on siblings and assumptions about the timing of parents' knowledge of their children's endowments. In addition to sibling differences, the useof a fixed‐effects instrumental‐variables estimator identifies the parameter under weaker conditions. Empirical analysis informed by the model reveals a negative and significant effect on the child's educational attainment of the months of the mother's full‐time employment when the child was aged 0–5. The effect of the mother's part‐time employment is smaller and less well determined, but again negative. These results suggest that the substitution effect of the mother's employment dominates the income effects. Stronger adverse effects are found for children of less‐educated mothers. Copyright © 2012 John Wiley & Sons, Ltd.

  January 20, 2012   doi: 10.1002/jae.2260   open full text
• Generalized Autoregressive Score Models With Applications.
  Drew Creal, Siem Jan Koopman, André Lucas.
  Journal of Applied Econometrics. January 20, 2012
  We propose a class of observation‐driven time series models referred to as generalized autoregressive score (GAS) models. The mechanism to update the parameters over time is the scaled score of the likelihood function. This new approach provides a unified and consistent framework for introducing time‐varying parameters in a wide class of nonlinear models. The GAS model encompasses other well‐known models such as the generalized autoregressive conditional heteroskedasticity, autoregressive conditional duration, autoregressive conditional intensity, and Poisson count models with time‐varying mean. In addition, our approach can lead to new formulations of observation‐driven models. We illustrate our framework by introducing new model specifications for time‐varying copula functions and for multivariate point processes with time‐varying parameters. We study the models in detail and provide simulation and empirical evidence. Copyright © 2012 John Wiley & Sons, Ltd.

  January 20, 2012   doi: 10.1002/jae.1279   open full text
• Tax‐Limited Reaction Functions.
  Edoardo Di Porto, Federico Revelli.
  Journal of Applied Econometrics. October 27, 2011
  This paper models for the first time a spatial process in local tax policies in the presence of centrally imposed fiscal limitations. Focusing on the frequently encountered case of a tax rate cap, we evaluate three empirical approaches to the analysis of spatially dependent limited tax policies: (i) a Bayesian spatial approach for censored dependent variables; (ii) a Tobit corner solution model augmented with a spatial lag; (iii) a spatial discrete hazard model. The evidence arising from an investigation of severely state‐constrained local vehicle taxes in Italy suggests that ignoring tax limitations can lead to substantial underestimation of inter‐jurisdictional fiscal interaction. Copyright © 2011 John Wiley & Sons, Ltd.

  October 27, 2011   doi: 10.1002/jae.1275   open full text