online appendix Table A8: Mask manufacturing exposure increases purchases of masks from manufacturers, decreases mask prices, and reduces COVID-19 infections across alternative approaches to including controls

|||||||_Dependen_|_t variable:_||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||log buy|er price|||Ef mask Q from<br>Ef m|manufacturers<br>ask Q|||# paraceta|mol receipts||
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
||0.445|0.437|0.219|0.263|-0.016|0.256|-0.088|0.155|0.588|-0.021|0.611|0.029|
|Mask manufacturing exposure_d ×_Nov_t_|(0.680)|(0.640)|(0.654)|(0.666)|(0.123)|(0.198)|(0.156)|(0.202)|(1.040)|(0.961)|(0.957)|(0.859)|
||[0.514]|[0.496]|[0.738]|[0.694]|[0.897]|[0.200]|[0.573]|[0.444]|[0.572]|[0.983]|[0.524]|[0.973]|
||0.173|-0.601|0.293|0.199|0.035|0.281|-0.042|0.135|0.267|-0.182|0.132|-0.194|
|Mask manufacturing exposure_d ×_Dec_t_|(0.732)|(0.734)|(0.648)|(0.717)|(0.114)|(0.202)|(0.142)|(0.214)|(0.734)|(0.690)|(0.612)|(0.618)|
||[0.814]|[0.415]|[0.653]|[0.782]|[0.760]|[0.168]|[0.770]|[0.531]|[0.716]|[0.792]|[0.829]|[0.753]|
||0.296|0.107|0.060|-0.101|0.057|0.237|0.034|0.224|0.254|0.366|0.058|0.415|
|Mask manufacturing exposure_d ×_Jan_t_|(0.383)|(0.349)|(0.390)|(0.343)|(0.115)|(0.208)|(0.143)|(0.211)|(0.685)|(0.760)|(0.558)|(0.685)|
||[0.441]|[0.760]|[0.878]|[0.769]|[0.620]|[0.259]|[0.815]|[0.290]|[0.711]|[0.630]|[0.917]|[0.545]|
||0.367|0.273|0.482|0.393|0.046|0.189|-0.008|0.130|-0.080|0.413|-0.175|0.524|
|Mask manufacturing exposure_d ×_Feb_t_|(0.374)|(0.330)|(0.337)|(0.318)|(0.089)|(0.185)|(0.114)|(0.181)|(0.723)|(0.857)|(0.615)|(0.752)|
||[0.328]|[0.410]|[0.156]|[0.219]|[0.608]|[0.308]|[0.947]|[0.475]|[0.912]|[0.629]|[0.775]|[0.485]|
|Mask manufacturing exposure_d ×_Mar_t_|-|-|-|-|-|-|-|-|-|-|-|-|
||-0.521|-0.574|-0.606|-0.600|1.095|1.377|0.697|0.973|0.208|0.110|-0.174|-0.393|
|Mask manufacturing exposure_d ×_Apr_t_|(0.311)|(0.321)|(0.289)|(0.300)|(0.252)|(0.285)|(0.356)|(0.413)|(0.832)|(0.888)|(0.809)|(0.953)|
||[0.098]|[0.078]|[0.039]|[0.049]|[0.000]|[0.000]|[0.054]|[0.021]|[0.803]|[0.901]|[0.829]|[0.680]|
||-0.613|-0.611|-0.772|-0.673|0.533|0.724|0.404|0.464|-1.178|-0.689|-1.405|-1.056|
|Mask manufacturing exposure_d ×_May_t_|(0.327)|(0.292)|(0.344)|(0.290)|(0.179)|(0.276)|(0.221)|(0.303)|(0.730)|(0.584)|(0.752)|(0.565)|
||[0.064]|[0.040]|[0.027]|[0.023]|[0.004]|[0.010]|[0.071]|[0.130]|[0.107]|[0.238]|[0.062]|[0.062]|
||-0.671|-0.723|-0.792|-0.792|0.196|0.581|0.212|0.513|-1.968|-1.561|-1.824|-1.669|
|Mask manufacturing exposure_d ×_Jun_t_|(0.391)|(0.418)|(0.396)|(0.423)|(0.194)|(0.349)|(0.215)|(0.293)|(0.728)|(0.626)|(0.698)|(0.571)|
||[0.089]|[0.088]|[0.049]|[0.065]|[0.316]|[0.099]|[0.328]|[0.083]|[0.007]|[0.013]|[0.009]|[0.003]|
||-0.210|-0.295|-0.396|-0.316|0.438|0.656|0.237|0.398|-1.973|-1.668|-1.785|-1.619|
|Mask manufacturing exposure_d ×_Jul_t_|(0.309)|(0.319)|(0.317)|(0.314)|(0.136)|(0.262)|(0.188)|(0.262)|(0.825)|(0.841)|(0.749)|(0.753)|
||[0.499]|[0.357]|[0.215]|[0.318]|[0.002]|[0.014]|[0.211]|[0.132]|[0.017]|[0.047]|[0.017]|[0.032]|
||-0.460|-0.663|-0.498|-0.606|-0.138|0.174|-0.318|0.031|-1.734|-1.531|-1.600|-1.564|
|Mask manufacturing exposure_d ×_Aug_t_|(0.272)|(0.284)|(0.251)|(0.251)|(0.197)|(0.315)|(0.253)|(0.311)|(0.918)|(1.007)|(0.785)|(0.862)|
||[0.095]|[0.022]|[0.050]|[0.018]|[0.485]|[0.583]|[0.212]|[0.920]|[0.059]|[0.129]|[0.041]|[0.070]|
|Estimation method|OLS|OLS|OLS|OLS|OLS|OLS|OLS|OLS|Poisson|Poisson|Poisson|Poisson|
|Firm-product FE|X|X|X|X|||||||||
|Destination sub-District FE|X|X|X|X|X|X|X|X|X|X|X|X|
|Month FE|X|X|X|X|X|X|X|X|X|X|X|X|
|Residualized shocks||X||X||X||X||X||X|
|Controls _×_ Month FE|||X|X|||X|X|||X|X|
|# observations|3,937|3,937|3,937|3,937|506|506|506|506|780|780|780|780|
|# clusters (sub-Districts)|86|86|86|86|86|86|86|86|78|78|78|78|

# **F.4 Price aggregation**

In Section 3.3, we found that mask manufacturing exposure causes persistent decreases in mask prices after licensing. Because comparing prices across distinct products is challenging, we used as outcomes mean log buyer prices at the firm-productby-month-by-destination (buyer) sub-District level, and included firm-product fixed effects in our analysis of impacts on prices. This construction of log buyer price is different from our other outcomes, for which we simply aggregated to the monthby-destination sub-District level. To test robustness of this construction, we instead leave the outcome log buyer price at the firm-product-by-receipt level (rather than aggregating), and present impacts on this outcome in Table A9. The patterns in the A29