||||**Table**|**9 Labor**|**demand a**|**nd Broadb**|**and use**|||||
|---|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|
|VARIABLES|Total|Direct|Outsourced|Laborer|Professional|Production|Management|Permanent|Temporary|Women|Men|
|Broadband (1=Yes)|0.022***|0.023***|‐0.007|0.021***|0.015**|0.023***|0.006|0.008|0.037**|0.018***|0.021***|
||[0.005]|[0.006]|[0.018]|[0.005]|[0.007]|[0.005]|[0.006]|[0.007]|[0.017]|[0.005]|[0.006]|
|TFP|‐0.332***|‐0.291***|‐0.745**|‐0.341***|‐0.099**|‐0.304***|‐0.195***|‐0.204***|‐0.328***|‐0.253***|‐0.277***|
||[0.056]|[0.049]|[0.324]|[0.078]|[0.049]|[0.055]|[0.037]|[0.039]|[0.083]|[0.041]|[0.051]|
|Observations|50,753|50,255|13,479|48,805|27,910|49,823|48,020|44,098|33,711|49,050|50,186|
|R‐squared|0.071|0.042|0.027|0.046|0.004|0.047|0.021|0.015|0.013|0.029|0.040|
|Number of plants|9,139|9,082|2,716|8,837|5,759|8,989|8,809|8,196|6,593|8,920|9,064|
|Plant FE|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|
|Year FE|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|
|Sector FE|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|
|City FE|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|
|Std. Errors|||||Clu|ster Plant/St|ate|||||
|model||||||fe||||||

Robust standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1 Table 10 shows the results of my instrumental variables approach. As discussed, I used the log average download speeds at the state level interacted with the lagged average broadband use at the industry level. While other potential instruments such as the number of broadband subscriptions and the upload speed were available, the preferred specification uses download speed given the results of statistical tests which can be seen in Table 15 and Table 16 in the Appendix.<sup>8</sup> Except for outsourced and professional workers, the first‐stage statistics are well above the conventional levels of statistical significance. This is also true about the weak instruments and weak instrument robust inference statistics.

Correcting for the possible endogeneity in broadband adoption suggests strong positive effects on labor demand of broadband use. The point estimate on total labor demand is around 22 log points, but it is not statistically significant. Lack of significance may be due to the use of two‐way clustered standard errors and the fact that variation of the instrument is at the state and industry level. The fact that most point estimates are strictly greater than zero provides some evidence of a positive effect, which nonetheless is not precisely identified.

Alternatively, given the model assumptions under which TFP was estimated, the underlying labor demand should only be a function of input prices and TFP. Thus, under these assumptions, the effect of broadband adoption should only be observed through its indirect effect on TFP. Therefore, lack of statistical significance in the 2SLS estimation is consistent with this theoretical model.<sup>9</sup>

> 8 See Table 15 which shows the first‐stage regression and Table 16 which shows relevance, and weak inference statistics.

> 9 I thank the participants at the applied microeconomics seminar at Banco de la República in Cali, especially Juan Esteban Carranza, Camila Casas and Salvador Navarro for pointing out this alternative explanation.

15