integrated into global production chains.<sup>4</sup> Global integration provides a channel for technological diffusion, and also imposes competitive pressure on lagging firms.

Starting with this hypothesis, this study uses data at the department–sector level to examine regional labor productivity convergence in different sectors in Peru during 2002‐2012. Our main findings are supportive of the idea that there is productivity convergence in sectors with greater scope for national and global integration. Specifically, we find that labor productivity, measured as value added per worker, has converged unconditionally across Peruvian departments within the secondary sector (especially in manufacturing) and the mining sector. Our estimated rate of convergence within manufacturing is comparable to the corresponding cross‐country estimate from Rodrik (2013).

There is weak evidence of labor productivity convergence within services in Peru. Furthermore, for agriculture, the estimated rate of the unconditional convergence is relatively low, and not statistically significant.

We find that the convergence in labor productivity within manufacturing and mining has been sizable enough to lead to convergence in aggregate departmental labor productivity. But this aggregate convergence is slower than that in manufacturing alone. The reason for this is that services and agriculture – within which convergence is either non‐existent, or weak at best – continue to employ the majority of workers in Peru. As we show, while there is labor outflow from agriculture during this period, the bulk of it is apparently directed towards the services sector. Thus, the secondary sector continues to account for a relatively small share of employment (around 17%). This sectorial pattern of labor allocation is even stronger in lagging regions.

Convergence in regional GDP per capita and poverty rates is also examined. There is some evidence for convergence in GDP per capita, but this is not robust. In a period where output per worker is converging across regions, the much weaker convergence in output per capita suggests different rates of change in the ratio of the employed population to total population across regions.

More intriguingly, we find that poverty rates are not converging across departments. Why, when labor productivity is converging, do we find no evidence for poverty convergence? The literature offers a possible explanation. Loayza and Raddatz (2010) argue that the composition of growth matters for poverty reduction. Their evidence suggests that growth coming from labor‐intensive sectors (such as agriculture, construction, and manufacturing) is most supportive of poverty reduction. Hence, it could be that the relatively weak productivity convergence in agriculture, combined with the lack of labor outflow from agriculture, is hindering poverty convergence. This is consistent with our results that even after conditioning on the growth in output per worker, there is no poverty convergence.

The limited impact of convergence in labor productivity within manufacturing and mining on poverty convergence can be explained with limited labor reallocation towards manufacturing. While going into the reasons behind such slow labor reallocation is beyond the scope of this study, it is important to note that this finding links our study to the literature on “structural transformation”. The starting point of this literature is the stylized fact that as countries develop, there is a movement of labor out of agriculture and into manufacturing and services (Herrendorf et al., 2013). Understanding how this process is playing

> 4 Productivity in farming, mining and certain industries may depend, to a large extent, on location‐specific factors such as climate and soil quality. In such sectors, it is not obvious that labor productivity should converge across regions.

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