Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/305228 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
I4R Discussion Paper Series No. 180
Verlag: 
Institute for Replication (I4R), s.l.
Zusammenfassung: 
Liu et al. (2023) examines the effect of climate change on labor allocation in India over a long time span. The authors find that rising temperatures are correlated with lower shares of workers in non agricultural sectors. They also identify a likely mechanism: falling agricultural productivity leads to a reduction in demand for non-agricultural goods or services, leading to a reduction in labor demand in non-agricultural sectors. We undertake a reproduction and extension of Liu et al. (2023), and find that we are able to computationally reproduce all the numbers produced by the authors up to marginal differences in the calculation of standard errors. We describe a set of data issues that hindered full reproduction of the original dataset, and, in one case, contradicts a claim of data availability made by the authors. Finally, we test the robustness of the main results to a more consistent use of fixed effects and the use of Poisson regression, following Chen and Roth (2024). The Poisson regression approach does not alter the results, but in several of the new fixed effects specifications the author's original results are less conclusive and lose statistical significance.
Dokumentart: 
Working Paper

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