# **1 Introduction**

We estimate labor mobility costs across sectors and regions for a large number of developing countries. Given that labor surveys in developing countries rarely provide longitudinal data, the methodology we developed only requires cross-sectional data. We rely on the assumption, borrowed from the urban literature, that workers’ intertemporal utility net of mobility cost is equalized across sectors and regions. We start by estimating for each worker in our sample their hypothetical wage in other sectors and regions given their observed characteristics. We then compare their level of intertemporal utility in each location or sector. Differences in intertemporal utility capture mobility costs, which are identified using the time horizon faced by each worker in their intertemporal maximization, i.e., the number of years until retirement. After correcting for self-selection of workers into regions and sectors, we find that the sector mobility costs are larger than regional mobility costs and represent about 1.4 times the average annual wage. The cost of moving across sectors and regions simultaneously is larger and represents almost 1.8 times the average annual real wage. We also find that workers in poorer countries face higher mobility costs. In addition, we provide evidence suggesting that information costs partly explain labor mobility costs, which can be mitigated by better access to the Internet.

Estimating labor mobility costs across sectors and regions is important for several reasons. First, moving sector and location is often a joint decision in less developed countries. As economies get richer, the share of jobs in agriculture shrinks and workers migrate to urban areas to find job opportunities in other sectors. Bustos et al. (2016a) provide evidence that technological change in agriculture that is labor-saving can foster industrialization and labor reallocation towards manufacturing. These gains are also extended to other sectors and regions by capital reallocation through bank branch networks (Bustos et al., 2016b). However, if the workforce is not sufficiently mobile across sectors and regions, the gains from labor-saving technological change are unlikely to be realized to their fullest extent, which may slow the speed of structural transformation. Gollin et al. (2014) suggest that even after controlling for sector differences in hours worked and human capital per worker, there is still a large productivity gap in agriculture across developing countries associated with misallocation of factors across sectors. Their findings are supported by Hsieh and Klenow (2009) who suggest that resource misallocation is also existent in manufacturing.<sup>1</sup> Second, for the gains from trade to materialize, workers and capital must be able to move freely within countries into sectors in which the country has a comparative advantage. Significant gains from trade integration accrue from the reallocation of labor from declining sectors into booming sectors. While capital can move relatively freely within a country, the same cannot be said about workers’ mobility. Workers are endowed with sector-specific skills that are not easily transferable

> 1The authors use microdata on manufacturing firms to quantify the potential extent of misallocation of labor and capital across plants within industries in China and India compared to the United States.

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