Climate effects on the diversification strategy of export firms: Evidence from China

regression coefficient β1. When β1 is significantly negative, it indicates an inverted U-shaped relationship between temperature and export product diversification, suggesting that both very low and very high temperatures inhibit firms’ diversification strategies. The regression results are presented in column (2) of Table 4, where β1 is indeed significantly negative, con- firming the robustness of the baseline conclusion. Outlier impact mitigation. To mitigate the potential influence of extreme values, we implement winsorization on the dependent variable, a technique that trims data points at the 0.5% and 99.5% percentiles. This process aims to reduce the influence of firms with extreme levels of diversification. The regression analysis using the modified sample data, based on Eq (11), is presented in Table 4, column (3). The results confirm the baseline conclusion, with sta- tistically significant negative regression coefficients observed consistently across all tempera- ture bins. Changing the cluster level of standard errors. In the baseline regression, we account for the potential autocorrelation present in the error terms at both the firm and city-year levels. Subsequently, we refine our approach by relaxing this assumption and acknowledging the pos- sibility of intra-city correlation among error terms. To address this, we adjust the standard errors to be clustered at the city level, as illustrated in Table 4, column (4). This slightly reduces the statistical significance, but maintains the inverted U-shaped relationship between tempera-

ture and export diversification. Most temperature bins pass statistical significance tests at the 10% level, underscoring the robustness of the baseline regression conclusions. Weekday data examination. In accordance with Chinese labor laws, a two-day weekend system is implemented on Saturdays and Sundays, concentrating production and labor activi- ties mainly on weekdays. Consequently, we focus on weekdays for a more nuanced analysis of temperature effects. Eq (11) is regressed again using temperature bin variables constructed from Monday to Friday data, as shown in Table 4 column (5). The results consistently show negative regression coefficients for all temperature bins, with the majority achieving statistical significance at the 5% level, consistent with previous analyses. Notably, the absolute values of the regression coefficients increase compared to the baseline, emphasizing that temperature predominantly affects export diversification mainly during weekdays. Altering temperature bins length. In the baseline regression, we divide temperature into 5˚C bins. Here, we refine our assumption by assuming a uniform effect on export product diversification within 3˚C temperature bins. Under this premise, we redefine temperature bins ranging from days below -6˚C (m = 1) to days �27˚C (m = 13). Specifically, if m = 1, it repre- sents the number of days in a year with an average daily temperature below -6˚C. m = 2 repre- sents the days with an average daily temperature between -6 and -3˚C, and so on. if m = 13, it

means the days with daily average temperature �27˚C. The regression with 12~15˚C bin as the baseline group shows an inverted U-shaped relationship between temperature and export diversification. The regression coefficients in Fig 3 show a trend of initial increase and subse- quent decrease with increasing temperatures, confirming the baseline conclusions. This con- firms that the length of the temperature bin specified in the model does not affect the research results. Climate adaptation Following the Industrial Revolution, rapid technological advances have provided multiple opportunities for climate adaptation. The widespread adoption of indoor work environments, coupled with innovations such as air conditioning and heating systems, enables individuals to regulate ambient temperatures, thereby increasing comfort and potentially productivity, miti- gating the impact of climate variability. At the same time, improved financial systems, PLOS ONE Climate effects on the diversification strategy of export firms PLOS ONE | https://doi.org/10.1371/journal.pone.0308391 August 16, 2024 13 / 28