A Comment on "Winter is Coming: Early-Life Experiences and Politicians' Decisions" - Farida Akhtar; David Kreitmeir; Luke Newman; Florian Ploeckl; Boyd Tarlinton (Institute for Replication (I4R), 2024)
Guo et al. (2023) examine the impact of early-life experiences of politicians on their policy implementations. They utilize differential exposure of Chinese county party secretaries to the Great Famine of 1959-1961 as a natural experiment and investigate the impact on their policy preferences, in particular fiscal expenditure on agriculture and social security. In their baseline analytical specification, the authors find that exposure to a one percentage point more severe famine led counties governed by these politicians to a 0.8% higher fiscal expenditure on agriculture and a 1.1% higher expenditure on social security subsidies. Their point estimates are statistically significant at the 1%, respective 5% levels depending on the included set of controls. First, we successfully computationally reproduce all quantitative claims, more precisely all tables and figures, of the paper, using the provided replication files. We uncover a minor coding error in a specification in a robustness check, though correcting it does actually strengthen the studies' main result, as well as a typo and rounding error in another robustness check. Additionally, the summary statistics and exploratory data analysis of the paper were also computationally reproduced using a different software package. Second, we directly replicate the results by systematically varying the sample size in two ways. One, we drop one individual control variable which increases the sample by retaining the observations that have missing values for that control variable, and two, we restrict the sample for the estimation of the impact on social security subsidies to only those observations that also report values for the agricultural fiscal subsidies. We find that retaining the observations with missing educational information values reduces the magnitude of all coefficients of interest (so interactions of famine severity with birth year indicators) with the impact on agricultural expenditure remaining statistically significant while the impact on social security subsidies is no longer statistically significant in three specifications and remains weakly significant in one. Similarly, the impact of estimating the impact on social security subsidies with the restricted sample of observations that have agricultural subsidy values also reduces the magnitude substantially and turns the coefficient statistically insignificant.
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