The aim of this study is to develop an eclectic but robust model that allows for a better measure of expected inflation and facilitates testing for all sorts of biases. Improving the measure of expected inflation is of critical importance for conducting monetary policy. In many circumstances, indicators of expected inflation move in opposite directions, and this divergence may be critical for the setting of the interest rate. I estimate the model for a special set of Israeli data via the Kalman filter methodology and then test for systematic biases, a better normalization of the model, liquidity problems and inflation risk – which could all be present in current measures of expected inflation.