On the timing of relevant weather conditions in agriculture

A growing literature is analyzing the effects of weather on agricultural outcomes. In these studies, constructing weather variables requires researchers to define a “season,” a period over which weather conditions are considered relevant to the outcome. We explore the consequences of assuming an inc...

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Bibliographic Details
Published inJournal of the Agricultural and Applied Economics Association Vol. 1; no. 2; pp. 180 - 195
Main Authors Li, Zhiyun, Ortiz‐Bobea, Ariel
Format Journal Article
LanguageEnglish
Published Davis John Wiley & Sons, Inc 01.08.2022
Subjects
Agricultural production
agriculture
Climate change
Error analysis
grid search approach
Monte Carlo simulation
nonclassical measurement error
Seasonal variations
Seasons
Variables
Weather
United States > US
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Summary:A growing literature is analyzing the effects of weather on agricultural outcomes. In these studies, constructing weather variables requires researchers to define a “season,” a period over which weather conditions are considered relevant to the outcome. We explore the consequences of assuming an incorrect season in such analyses. We show in simulations that imposing an incorrect season introduces nonclassical measurement error in weather regressors, bias in unknown directions. We propose an approach to recover the “true” underlying season and apply it to a US state‐level panel of agricultural Total Factor Productivity. We find that accounting for seasonality can lead to substantially different estimates.
ISSN:2769-2485
2769-2485
DOI:10.1002/jaa2.21