Real‐Time Data And Fiscal Policy Analysis: A Survey Of The Literature
Published online on November 12, 2014
Abstract
This paper surveys the empirical research on fiscal policy analysis based on real‐time data. This literature can be broadly divided into four groups that focus on: (1) the statistical properties of revisions in fiscal data; (2) the political and institutional determinants of projection errors by governments; (3) the reaction of fiscal policies to the business cycle and (4) the use of real‐time fiscal data in structural vector autoregression (VAR) models. It emerges that, first, fiscal revisions are large and initial releases are biased estimates of final values. Secondly, strong fiscal rules and institutions lead to more accurate releases of fiscal data and smaller deviations of fiscal outcomes from government plans. Thirdly, the cyclical stance of fiscal policies is estimated to be more ‘counter‐cyclical’ when real‐time data are used instead of ex post data. Fourthly, real‐time data can be useful for the identification of fiscal shocks. Finally, it is shown that existing real‐time fiscal data sets cover only a limited number of countries and variables. For example, real‐time data for developing countries are generally unavailable. In addition, real‐time data on European countries are often missing, especially with respect to government revenues and expenditures. Therefore, more work is needed in this field.