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

Sensitivity analysis Endogeneity issue. This section considers the potential problem of omitted variables, selection bias, and bidirectional causality in the model specification. Firstly, we discuss the potential problem of omitted variables. In the baseline regression, we follow the common prac- tice in the existing literature by controlling for other meteorological variables that are highly correlated with temperature in the model [27]. We also include province-year fixed effects to control for regional economic development levels and policy effects, and firm fixed effects to control for time-invariant firm characteristics. The above model is designed to mitigate the issue of omitted variable problem. To further validate the robustness of the conclusions, we extend the model (11) by adding city-year level economic variables, including: economic development level (Eco), represented by the logarithm of the city’s GDP; population size (Pop), represented by the total population at the end of the year; green innovation capacity (Envinno), represented by the logarithm of the number of green invention patents filed in the city in the current year; city openness (Open), represented by the logarithm of the actual foreign invest- ment in the city in the current year; and local government capacity (Gov), represented by the share of local fiscal budget expenditure in local GDP. These additional control variables cover aspects such as market, government, factor endowment, and technological development, pro-

viding a comprehensive control for the economic development trends at the city-year level. The regression result with these additional variables is shown in column (1) of Table 3. The result shows that the addition of these control variables does not change the conclusions of the baseline regression, indicating that the baseline model has good explanatory power. Given that Dell et al. (2014) [37] point out that the impact of climate on economic markets is multifaceted, controlling for economic variables may lead to “over-control” problems. Fig 1. The U-shaped relationship between temperature and the product diversification of export firms. The graph is created based on the regression coefficients and standard deviation data for each temperature bin from column (3) of Table 2. https://doi.org/10.1371/journal.pone.0308391.g001 PLOS ONE Climate effects on the diversification strategy of export firms PLOS ONE | https://doi.org/10.1371/journal.pone.0308391 August 16, 2024 9 / 28