Expectations, Heterogeneous Forecast Errors, and Consumption: Micro Evidence from the Michigan Consumer Sentiment Surveys

By Souleles, Nicholas S. | Journal of Money, Credit & Banking, February 2004 | Go to article overview

Expectations, Heterogeneous Forecast Errors, and Consumption: Micro Evidence from the Michigan Consumer Sentiment Surveys


Souleles, Nicholas S., Journal of Money, Credit & Banking


Debate over the usefulness of consumer sentiment surveys in forecasting economic activity began soon after their introduction in the 1940s. The possibility that a decline in consumer confidence helped cause or worsen the 1990-91 recession renewed interest in the debate. Most recent studies of sentiment have focused on the time-series relationship between aggregate consumption and the two main aggregate indices of sentiment, the Michigan Index of Consumer Sentiment (ICS) and the Conference Board Consumer Confidence Index. This paper, by contrast, provides perhaps the first comprehensive analysis of the household-level data that underlies the ICS, the Michigan Survey of Consumer Attitudes and Behavior (CAB). The attention that the ICS receives, from policymakers, academics, and the business community, itself warrants an analysis of the underlying data. There are also a number of methodological advantages to such an analysis.

First, with micro data one can assess the rationality of household expectations. Most previous rationality tests have limited their focus to inflation expectations, just one of the many variables that will be examined here. Also, the tests have generally used aggregated data or at most short micro panels. But when agents' information sets differ, aggregation can lead to spurious rejections of rationality. The average of rational individual forecasts need not be a rational forecast conditional on any single information set (Keane and Runkle 1990). And, even if individual forecasts are perfectly rational, it might take a long time--perhaps multiple business cycles--for forecast errors to average out. Hence, to test rationality, it is important to use micro data on expectations over long sample periods. Unfortunately, such data are not usually available. The CAB survey, however, is unique in containing almost 20 years of monthly household expectations data. This paper exploits its panel aspect to test more cleanly than usual whether expectations are unbiased and efficient. The results can also be interpreted as explicitly characterizing the time-series and cross-sectional properties of the shocks that have bit different types of households over time, across business cycles, and policy regimes. In addition to its welfare implications, such a characterization is of methodological interest because both theoretical and empirical models are generally sensitive to the assumptions made about shock processes. In particular, many models assume that "aggregate" shocks affect all households equally.

Second, this paper assesses whether the sentiment surveys are useful in predicting behavior, specifically household spending. The canonical permanent income (or life cycle) hypothesis (PIH) provides a natural setting for this assessment. One of the central implications of the PIH is that current consumption should incorporate all the information available to an agent. However, the econometrician does not independently observe the contents of agents' information sets, so tests of this implication usually need to make strong assumptions, inferring agents' expectations econometrically. This paper instead uses direct measures of expectations from the CAB data. This data is matched, using a rich set of demographic variables, with the Consumer Expenditure Survey (CEX), which has the most comprehensive micro data on expenditure. The resulting test is whether the expectations data contain additional information, beyond that in current consumption, that helps predict future consumption. Previous studies of the excess sensitivity of consumption to sentiment have used aggregate sentiment data but aggregation can induce spurious excess sensitivity even when there is none at the micro level (Attanasio and Weber 1995). The construction of the ICS is not necessarily consistent with the construction of aggregate consumption. For instance, the ICS is an equal-weighted average of the sentiment of the CAB survey respondents, which ignores differences in the scale of consumption across respondents. …

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