Testing for Money Illusion Hypothesis in Aggregate Consumption Function: Mixed Data Sampling Approach

Abstract

Testing for the money illusion hypothesis in aggregate consumption function generally involves a regression model that projects real consumption onto nominal income and a consumer price index. While consumption and income data are typically sampled at a quarterly level, price data are often available at a monthly level. This paper takes advantage of mixed data sampling (MIDAS) techniques in order to exploit monthly price data. We show via local power analysis and Monte Carlo simulations that our approach yields deeper economic insights and higher statistical precision than the previous single-frequency approach that aggregates price data into a quarterly level. In particular, the MIDAS approach allows for heterogeneous effects of monthly prices on real consumption within each quarter. In empirical applications we find that the heterogeneous effects indeed exist in Japan and the U.S.