_HOTTER PLANET, HOTTER FACTORIES_ _17_ Table 2—: Pooled OLS estimation on sales per worker: Whole Sample

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|WBT Deviation_×_Zone<sup>_Q_2</sup><br>(23_._7<sup>0</sup>_C,_24_._9<sup>0</sup>_C_]|0.526<sup>_∗∗∗_</sup>|0.520<sup>_∗∗∗_</sup>|0.199<sup>_∗∗∗_</sup>|0.210<sup>_∗∗∗_</sup>|0.234<sup>_∗∗∗_</sup>|0.231<sup>_∗∗∗_</sup>|0.224<sup>_∗∗∗_</sup>|0.224<sup>_∗∗∗_</sup>|
||(0.028)|(0.028)|(0.026)|(0.026)|(0.027)|(0.027)|(0.027)|(0.027)|
|WBT Deviation_×_Zone<sup>_Q_3</sup><br>(24_._9<sup>0</sup>_C,_25_._7<sup>0</sup>_C_]|-0.136<sup>_∗∗∗_</sup>|0.103<sup>_∗∗∗_</sup>|-0.075<sup>_∗∗_</sup>|-0.060<sup>_∗_</sup>|-0.073<sup>_∗∗_</sup>|-0.031|-0.040|-0.041|
||(0.036)|(0.036)|(0.036)|(0.036)|(0.037)|(0.037)|(0.037)|(0.037)|
|WBT Deviation_×_Zone<sup>_Q_4</sup><br>(25_._7<sup>0</sup>_C,max_)|-1.330<sup>_∗∗∗_</sup>|-1.060<sup>_∗∗∗_</sup>|-0.205<sup>_∗∗∗_</sup>|-0.169<sup>_∗∗∗_</sup>|-0.225<sup>_∗∗∗_</sup>|-0.222<sup>_∗∗∗_</sup>|-0.228<sup>_∗∗∗_</sup>|-0.234<sup>_∗∗∗_</sup>|
||(0.059)|(0.058)|(0.059)|(0.059)|(0.059)|(0.059)|(0.059)|(0.059)|
|Sector dummy|No|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Country FE|No|No|Yes|Yes|Yes|Yes|Yes|Yes|
|Year FE|No|No|No|Yes|Yes|Yes|Yes|Yes|
|Country x year FE|No|No|No|No|No|Yes|Yes|Yes|
|Population (25km radius)|No|No|No|No|No|Yes|Yes|Yes|
|Road infrastructure (25km radius)|No|No|No|No|No|No|Yes|Yes|
|Pollution (25km radius)|No|No|No|No|No|No|No|Yes|
|_Observations_|88,876|86,467|86,467|86,467|86,467|86,467|86,467|86,467|
|R<sup>2</sup>|0.057|0.146|0.357|0.359|0.370|0.371|0.373|0.373|

_Note:_ Standard errors are in parentheses. All models control for firm age, ownership, export status, firm size (employment), proportion of permanent workers, proportion of skilled workers, 55 dummy variables indicating a narrow industry classification, and dummies indicating World Bank regions. All WBT categories are included separately in the model, in addition to the interaction terms. The reference category for climate zone is the bottom quartile in the distribution of WBT which is less than or equal to 23.7<sup>0</sup> _C_ . The minimum WBT in our sample is 14.5<sup>0</sup> C. FE = fixed effect; km = kilometers; OLS = ordinary least squares; WBT = wet-bulb temperature. _∗∗∗ ∗∗ ∗ p <_ 0 _._ 01, _p <_ 0 _._ 05, _p <_ 0 _._ 1 representing different climate zones. Following Equation 4<sup>13</sup> the coefficients on the interaction term between the climate zones and the deviations in temperature capture the nonlinear impacts of temperatures that vary across the climate zones. The marginal effects are obtained by taking the partial derivatives of log sales per worker with respect to climate zone ( _Zone_<sup>_Qq_</sup> ) and WBT, where _q_ = _{_ 1 _,_ 2 _,_ 3 _,_ 4 _}_ represents the quartile. The coefficient estimates ( _βQq_ ) can then be interpreted as the impact on productivity of a unit (1<sup>0</sup> _C_ ) deviation in WBT from the longterm average compared to firms in the coldest zone.<sup>14</sup> Table 2 presents the main results. Table 8 in the appendix presents the complete results.

Specification (1) presents the results for the baseline model with no controls or essential fixed effects, and hence they are less reliable. The specification ignores many factors, both observable and unobservable, that could bias our estimates, which could be captured by a set of controls and fixed effects. To address this, we estimate a series of models by including key controls that potentially explain

> 13We also estimate the basic model specified in Equation 3 and including the squared value of WBT deviation. The results are shown in Table 7, in the appendix.

> 14The marginal effects are obtained by taking the partial derivatives of log sales per worker with respect to climate zone ( _Zone_<sup>_Qq_</sup> ) and WBT i.e., _∂∂_ <u>(</u> _ln_ ( _Zone_ <u>(</u> _yijkcQqjkc,t_<sup>)</sup> <u>))</u> _· ∂∂_ ((∆ _Zone_<sup>_W BT_</sup> _jkc,tQqjkc_<sup>)).</sup>