**Table A7.4: Impact on Anexo K on Same Samples as WMS and MOPS**

||Balanced Panel|WMS S|ample|MOPS|Sample|
|---|---|---|---|---|---|
||Anexo K|Anexo K|WMS|Anexo K|MOPS|
|Individual Treatment*During Intervention|9.413***|8.350***||9.669***||
||(1.760)|(2.229)||(1.879)||
|Individual Treatment*Post Intervention|9.309***|8.325***|‐0.210|9.657***|0.017|
||(1.821)|(2.368)|(0.176)|(1.856)|(0.036)|
|Group Treatment*During Intervention|11.384***|7.602**||11.143***||
||(2.202)|(3.164)||(2.438)||
|Group Treatment*Post Intervention|8.155***|3.911|‐0.132|7.549***|0.040|
||(2.124)|(3.091)|(0.174)|(2.318)|(0.034)|
|Sample Size|202|104|52|172|86|
|Control Mean|55.98|60.1|2.93|57.44|0.49|
|Control SD|10.79|6.98|0.41|10.23|0.12|
|_Implied 95% confidence intervals in S.D._||||||
|Individual Treatment*Post Intervention|[0.53,1.19]|[0.53,1.86]|[‐1.35,0.33]|[0.59,1.30]|[‐0.45,0.73]|
|GroupTreatment* Post Intervention|[0.37,1.14]|[‐0.31,1.42]|[‐1.15,0.51]|[0.29,1.18]|[‐0.22,0.89]|

Notes: Column 1 is for the 101 firms for which Anexo K management practices are measured both during and post intervention. Columns 2 and 3 restrict to the subset of 52 firms that also had the WMS measured in 2016, Columns 4 and 5 restrict to the subset of 86 firms that also had the MOPS measured in 2017. Regressions control for baseline (December 2013) Anexo K mean, time fixed effects, and controls for region baseline labor productivity, baseline number of employees, and for being a small firm at baseline. Robust standard errors in parentheses, clustered at the firm level.

*, **, *** denote significance at the 10, 5, 1 percent levels respectively.

A more compelling explanation for the lack of impact on the WMS is due to this measure not being as able to pick up the types of changes in management practices that come from this intervention. A first reason for this is just the general noise in the measure, as discussed above. This noise means that much of the change in the WMS over time may reflect measurement error, making it difficult to detect treatment effects. But a second reason is that the WMS measures practices at a more general level than the level of specificity at which interventions are focused. Evidence in support of the idea that the WMS is not able to pick up the specific changes in practices that these consulting type interventions bring about comes from the India experiment that initially motivated this work. Bloom et al. (2013) report that their treatment plants increased their use of the 38 specific management practices they measure by 37.8 percentage points, significantly larger than the change for the control firms. They asked Accenture to also apply the WMS survey instrument to these firms during this post-intervention measurement phase. However, Accenture did not receive the LSE training on applying this survey instrument, and appears to have graded firms more harshly, with a mean WMS score of 1.45, compared to a baseline mean of 2.69 when conducted by the LSE team. Despite the large change in management practices observed in the 38 management practices used in Bloom et al. (2013), there is no significant difference in the followup WMS scores in this case (mean of 1.43 for the treated firms, 1.49 for the control firms, p-value = 0.693). So, as with our Colombian case, if one were to rely on the WMS to measure whether changes in management had occurred, the conclusion would have been that the Indian interventions had no significant effect on management.

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