corresponding change for the 50+ control category. The specification is estimated separately for each of the three synthetic age cohorts and their outcomes are compared with the corresponding plant cohort when the GQ was completed in 2009. For example, the outcomes of 0-5 year-old plant cohort in 2000 are compared with 9-14 year-old cohorts in 2009.

All estimations include as a control the initial level of ( 2000) in the district, although the results are little affected by its inclusion. The vector contains district-level controls: national highway access, state ii YY YY highway access, broad-gauge railroad access and district-level measures from the 2000 Census of log total ii XX population, age profile (measured as demographic dividend),<sup>9</sup> female-male sex ratio, population share in urban areas, population share in scheduled castes or tribes, literacy rates and an index of within-district infrastructure measuring local access to electricity, roads, telecom, and water/sanitation facilities (see Ghani et al., 2012 for details).

Panels A-C in Table 1 present the results from estimation of specification (1) across the three age groups and for each of the seven outcome variables, reported across columns in the three panels. Columns 1-3 report district-level aggregate changes in logged output, employment and plant count; columns 4 and 5 report changes in average plant size measured as employment or output; columns 6 and 7 report average plant performance measured as labor productivity and revenue TFP. These results are robust to splitting the residual category of 50 plus kilometer distance band into finer groupings (Annex Table A.2).

Panel A shows that the arrival of the GQ had a positive and significant impact for the young cohort on output, average plant size, measured by both employment and output levels (columns 4 and 5), and on median plant performance, measured as labor productivity and TFP (columns 6 and 7). By comparison, for mature and older cohorts we observe either no significant positive or adverse effects in Panels B and C.<sup>10</sup> The results suggest that the positive aggregate responses to the GQ observed by Ghani et al. (2016a, 2016b) were largely driven by the young cohort of plants.<sup>11</sup> Because of the imprecision of the estimates for the older plants, it is difficult to reject equivalence in the coefficients in most cases, with only three test rejecting

> 9 We construct the demographic dividend measure as the ratio of working age population to non-working age population using 2001 population census counts.

> 10 Effects in terms of employment for non-nodal districts within 0-10 kilometers of GQ are consistently positive and insignificant across all age classes. Thus, there is overall a minimal effect on labor demand among any age group, although these estimates are noisily measured. These results are in line with Sedláček and Sterk (2017) who estimate a general equilibrium firm dynamics model that suggests that aggregate conditions at birth, rather than post-entry choices, drive the majority of cohort-level employment variation.

> 11 Notice that the results on new establishments (or activity cropping along the GQ network) in Ghani et al. (2016) are distinct from our results on the average effects being driven by the young cohort of plants because: (i) these plants are not young by the time of completion of GQ; (ii) Unlike Ghani et al. they _do not_ represent new activity as our dataset drops all new plants that were born after the GQ upgrades began.

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