Supply shocks and the rationality of inflation forecasts (original) (raw)

CREATES Research Paper 2008-56 Disagreement and Biases in Inflation Expectations

2008

Disagreement in inflation expectations observed from survey data varies systematically over time in a way that reflects the level and variance of current inflation. This paper offers a simple explanation for these facts based on asymmetries in the forecasters’ costs of overand under-predicting inflation. Our model implies (i) biased forecasts; (ii) positive serial correlation in forecast errors; (iii) a cross-sectional dispersion that rises with the level and the variance of the inflation rate; and (iv) predictability of forecast errors at different horizons by means of the spread between the shortand long-term variance of inflation. We find empirically that these patterns are present in inflation forecasts from the Survey of Professional Forecasters. A constant bias component, not explained by asymmetric loss and rational expectations, is required to explain the shift in the sign of the bias observed for a substantial portion of forecasters around 1982.

Inflation Expectations: Does the Market Beat Professional Forecasts?

2009

The present paper compares expected inflation to (econometric) inflation forecasts based on a number of forecasting techniques from the literature using a panel of ten industrialized countries during the period of 1988 to 2007. To capture expected inflation we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect. The extracted unexpected inflation is compared to the forecasting errors of ten econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.

Rationality of Survey Based Inflation Expectations of Eighteen

2014

This study investigates rationality of inflation expectations of 18 emerging countries inflation rates using ten years (11/2001 – 5/2012) of inflation data. Given the nature of the data, we use the panel method to assess the relation between actual and the expected inflation rates. We perform various diagnostic tests to identify the appropriate panel test for the data. We use a recently developed panel regression method based on simple OLS techniques but derive standard errors corrected for serial correlation, panel heterogeneity and cross-sectional dependence. Results of the unbiasedness test and the efficiency test indicate that forecasts are rational for one month ahead forecast horizon. 1 Work-in-progress. Please do not cite. 2 Corresponding author. Tel: 478-301-5541; Email: rahman_ms@mercer.edu