Testing Forecast Rationality for Measures of Central Tendency

TL;DR

This paper develops tests to identify which measure of central tendency respondents use in forecast reports, addressing identification issues, and applies these tests to income forecasts revealing heterogeneity in forecast rationality and measures used.

Contribution

It introduces novel tests for forecast rationality that can identify the measure of central tendency used, even when it is unknown or nearly equal to others, and applies them to real survey data.

Findings

Forecasts are consistent with mode predictions but not with mean or median.

Heterogeneity exists in the central tendency measure used based on respondent characteristics.

Respondents' forecast rationality varies with income, age, and survey experience.

Abstract

Rational respondents to economic surveys may report as a point forecast any measure of the central tendency of their (possibly latent) predictive distribution, for example the mean, median, mode, or any convex combination thereof. We propose tests of forecast rationality when the measure of central tendency used by the respondent is unknown. We overcome an identification problem that arises when the measures of central tendency are equal or in a local neighborhood of each other, as is the case for (exactly or nearly) symmetric distributions. As a building block, we also present novel tests for the rationality of mode forecasts. We apply our tests to income forecasts from the Federal Reserve Bank of New York's Survey of Consumer Expectations. We find these forecasts are rationalizable as mode forecasts, but not as mean or median forecasts. We also find heterogeneity in the measure of centrality used by respondents when stratifying the sample by past income, age, job stability, and survey experience.