We report results from the estimation of the parametric spline specifications presented in equations (2) and (3) in table 2. Columns 1 and 2 report estimates of $βL$ and $βH$ from equation (2), with column 2 estimates corresponding to a specification with an additional control for precipitation. The precipitation control ensures that impacts are being driven by temperature exposure alone and are not composite effects reflecting the impacts of other correlated weather conditions. Columns 3 and 4 report estimates of $β1L$, $β1H$, $β2$, $β3L$, and $β3H$ from equation (3), once again with column 4 reporting results after controlling for precipitation.
 1 2 3 4 Efficiency (Actual Production / Targeted Production) $×$ 100 Wet bulb globe temperature $<$19 −0.299 −0.318 −0.0940 −0.105 [−1.803, 0.532] [−1.813, 0.510] [−1.017, 0.421] [−1.008, 0.404] Wet bulb globe temperature $≥$19 $-2.135***$ $-2.169***$ $-1.953**$ $-1.981***$ [$-3.312,-$1.395] [$-3.369,-$1.399] [$-3.00,-$1.206] [$-3.020,-$1.230] 1(LED) $×$ (Wet bulb globe temperature $<$19) −0.106 −0.103 [−0.847, 0.852] [−0.843, 0.853] 1(LED) $×$ (Wet bulb globe temperature $≥$19) 1.671$***$ 1.681$***$ [0.718, 2.787] [0.725, 2.809] 1(LED) 3.447 3.393 [−18.34, 16.85] [−18.39, 16.85] Factory $×$ Year, Factory $×$ Calendar Month Fixed effects Production Line, Day of the Week Precipitation control N Y N Y Observations 74,939 74,939 239,680 239,680 Mean of dependent variable 53.73 53.73 55.234 55.234
 1 2 3 4 Efficiency (Actual Production / Targeted Production) $×$ 100 Wet bulb globe temperature $<$19 −0.299 −0.318 −0.0940 −0.105 [−1.803, 0.532] [−1.813, 0.510] [−1.017, 0.421] [−1.008, 0.404] Wet bulb globe temperature $≥$19 $-2.135***$ $-2.169***$ $-1.953**$ $-1.981***$ [$-3.312,-$1.395] [$-3.369,-$1.399] [$-3.00,-$1.206] [$-3.020,-$1.230] 1(LED) $×$ (Wet bulb globe temperature $<$19) −0.106 −0.103 [−0.847, 0.852] [−0.843, 0.853] 1(LED) $×$ (Wet bulb globe temperature $≥$19) 1.671$***$ 1.681$***$ [0.718, 2.787] [0.725, 2.809] 1(LED) 3.447 3.393 [−18.34, 16.85] [−18.39, 16.85] Factory $×$ Year, Factory $×$ Calendar Month Fixed effects Production Line, Day of the Week Precipitation control N Y N Y Observations 74,939 74,939 239,680 239,680 Mean of dependent variable 53.73 53.73 55.234 55.234
Wild-cluster bootstrap 95% CIs in brackets: significant at $***$1%, $**$5%, and $*$10%. Clustering is done at the factory level. All measures of temperature are in degrees Celsius. All regressions include daily budgeted efficiency as a control variable.