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We investigate the role of sectoral differences in labor productivity in explaining the process of structural transformation -the secular reallocation of labor across sectors -and the time path of aggregate productivity across countries. Using a simple model of the structural transformation that is calibrated to the growth experience of the United States, we measure sectoral labor productivity differences across countries. Productivity differences between rich and poor countries are large in agriculture and services and smaller in manufacturing. Moreover, over time, productivity gaps have been substantially reduced in agriculture and industry but not nearly as much in services. In the model, these sectoral productivity patterns generate implications that are broadly consistent with the cross-country evidence on the structural transformation, aggregate productivity paths, and relative prices. We show that productivity catch-up in industry explains about 50 percent of the gains in aggregate productivity across countries, while low relative productivity in services and the lack of catch-up explains all the experiences of slowdown, stagnation, and decline observed across countries.Keywords: labor productivity, structural transformation, sectoral productivity, employment, hours, cross-country data. JEL Classification: O1,O4. † We thank the editor and three referees for very useful and detailed comments. We also thank comments and suggestions from

We formulate a version of the growth model in which production is carried out by heterogeneous plants and calibrate it to US data. In the context of this model we argue that differences in the allocation of resources across heterogeneous plants may be an important factor in accounting for crosscountry differences in output per capita. In particular, we show that policies which create heterogeneity in the prices faced by individual producers can lead to sizeable decreases in output and measured TFP in the range of 30 to 50 percent. We show that these effects can result from policies that do not rely on aggregate capital accumulation or aggregate relative price differences. More generally, the model can be used to generate differences in capital accumulation, relative prices, and measured TFP.

Using internationally comparable data from the World Agricultural Census, we document a factor of 36 difference in average farm size between rich and poor countries. Small farms of less than 2 hectares represent more than 70% of farms in poor countries but only 15% in rich countries, whereas large farms of more than 20 hectares represent none of the farms in poor countries and almost 40% in rich countries. Two questions emerge. First, what explains the striking differences in farm size across countries? Second, are farm-size differences important in understanding agricultural and aggregate productivity gaps across countries? We develop a two sector model with agriculture and non-agriculture that features a non-degenerate size distribution of farms. The theory embeds a Lucas (1978) span-of-control model of farm size into a standard sectoral model with non-homothetic preferences. In the model calibrated to the United States, a reduction in economy-wide productivity from 1 to 1/4 produces an increase in the share of employment in agriculture from 2.5% to 53%, a 21-fold reduction in average farm size, and a 25-fold reduction in agricultural labor productivity. These results are broadly consistent with data on the sectoral allocation of labor and the size distribution of farms across countries.JEL classification: O11, O14, O4.