Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts

Alexandros Botsis, Christoph Görtz and Plutarchos Sakellaris

Discussion Papers from Department of Economics, University of Birmingham

Abstract: Using a novel dataset that combines firms’ qualitative survey-based sales forecasts with quantitative balance-sheet data on realized sales, we document that only major forecast errors (those in the two distribution tails) are predictable and autocorrelated. This is a particular violation of the Full Information Rational Expectations hypothesis that requires explanation. In contrast, minor forecast errors are neither predictable nor autocorrelated. To arrive at this finding, we develop a novel methodology to quantify qualitative survey data on firm forecasts of own growth. It is generally applicable when quantitative information is available on the realization of the forecasted variable, for example from firm balance sheets. The method can also be applied to panel data on qualitative household expectations.

Keywords: Expectations; Firm Data; Forecast Errors; Panel Threshold Models; Survey Data. (search for similar items in EconPapers)
JEL-codes: C53 C83 D22 D84 E32 (search for similar items in EconPapers)
Pages: 94 pages
Date: 2023-07
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https://repec.cal.bham.ac.uk/pdf/23-06.pdf

Related works:
Working Paper: Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts (2021)
Working Paper: Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:bir:birmec:23-06

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