agricultural sector also have higher mobility costs (columns 1-3). Results in columns (4-6) suggest that, as the share of the agricultural sector declined in most countries over time, so did on the average the mobility costs. Symmetrically, we obtain opposite results when considering the share of the manufacturing sector in the economy. More industrialized countries face lower sector mobility costs. Results are similar when considering the share of the service sector, but with a much smaller magnitude than for the manufacturing sector. Although we do not claim any causal link, our results suggest that larger mobility costs are correlated with the level and speed of structural change.

One constraint of our analysis is that the definition of a region is not identical across countries and we had to restrict ourselves to a limited number of regions for computational reasons, which means that large countries may have too few regions compared to smaller countries. We re-estimated the regression using only small countries (we dropped countries for which the average internal distance is above 1,000 km). The intuition is simple and merely assumes that greater distances between regions increases the cost of moving.Larger countries may also have developed denser road and railway networks, which would ease regional mobility. To capture these two effects, we use data on internal distance from CEPII.<sup>8</sup> and data on the length (in km) of the railway network from the World Development Indicators. Results presented in table 3 show that internal distance is positively correlated with the regional mobility costs, but results are less precisely estimated when using only statistically significant estimates of reginal mobility costs. The size of the railway network (which we interpret here as a proxy for transport infrastructure) is negatively correlated with regional mobility costs. Yet, when controlling for both variables (distance and railway network), none of them are statistically significant.<sup>9</sup>

# **5 Information costs and Internet access**

For policy makers it is not only important to know whether sector or regional mobility costs are larger, but it is also key to understand what is driving these costs and what policies are available to reduce them. We explore this question by putting forward a potential explanation associated with information costs and analyze how access to the Internet may mitigate them. Other determinants (e.g. retraining costs and social network) have also been explored by the literature. For example, Dix-Carneiro (2014) suggests a moving subsidy as a better policy than retraining to compensate the fact that sector-specific experience is not perfectly transferable across sectors.<sup>10</sup> A potential driver of mobility costs is lack of information associated with searching costs. Work-

> 8Mayer and Zignago (2011).

> 9These results are not fully comparable due to limitation of observations available for rail lines, which significantly reduces the sample.

> 10In a simulation of welfare change as a function of shocks in prices of high-tech manufacturing, he finds that moving subsidy policies seem to be more effective than retraining.

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