Timo Dimitriadis, Andrew J. Patton, Patrick W. Schmidt
arXiv 28 Oct 2019 · Econometrics · publishedThe Review of Economics and Statistics (2019) · 3 citations (OpenAlex)
arXiv:1910.12545 · PDF · DOI · OpenAlex · Extracted main text
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.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Elliott, G., Komunjer, I., and Timmermann, A (2005) Estimation and testing of forecast rationality under flexible loss | 1.000 | 17 | 6 | 100% |
| 2 | Kemp, G. C. and Silva, J. S (2012) Regression towards the mode | 1.000 | 7 | 4 | 100% |
| 3 | Kemp, G. C., Parente, P. M., and Silva, J. S (2020) Dynamic vector mode regression | 1.000 | 7 | 4 | 100% |
| 4 | Gneiting, T (2011) Making and evaluating point forecasts | 1.000 | 7 | 3 | 100% |
| 5 | Davidson, J (1994) Stochastic Limit Theory: An Introduction for Econometricians | 1.000 | 7 | 3 | 100% |
| 6 | Stock, J. H. and Wright, J. H (2000) GMM with weak identification | 1.000 | 6 | 4 | 100% |
| 7 | Heinrich, C (2014) The mode functional is not elicitable | 0.928 | 4 | 3 | 100% |
| 8 | Kim, G. and Binder, C (2023) Learning-through-survey in inflation expectations | 0.928 | 4 | 3 | 100% |
| 9 | Mincer, J. and Zarnowitz, V (1969) The Evaluation of Economic Forecasts | 0.843 | 3 | 3 | 100% |
| 10 | Reifschneider, D. and Tulip, P (2019) Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve's approach | 0.843 | 3 | 3 | 100% |
Showing the top 10 of 73 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | The Efficiency Gap | 0.405 | 1 | 1 |
| 2 | Generalised Covariances and Correlations | 0.405 | 1 | 1 |
| 3 | Characterizing M-estimators | 0.000 | 1 | 1 |