Structural transformation in most currently developing countries takes the form of a rapid rise in services but limited industrialization. In this paper, we propose a new methodology to structurally estimate productivity growth in service industries that circumvents the notorious difficulties in measuring quality improvements. In our theory, the expansion of the service sector is both a consequence—due to income effects—and a cause— due to productivity growth— of the development process. We estimate the model using Indian household data. We find that productivity growth in non-tradable consumer services such as retail, restaurants, or residential real estate, was an important driver of structural transformation and rising living standards between 1987 and 2011. However, the welfare gains were heavily skewed toward high-income urban dwellers.
Structural transformation in most currently developing countries takes the form of a rapid rise in services but limited industrialization. In this paper, we propose a new methodology to structurally estimate productivity growth in service industries that circumvents the notorious difficulties in measuring quality improvements. In our theory, the expansion of the service sector is both a consequence—due to income effects—and a cause—due to productivity growth—of the development process. We estimate the model using Indian household data. We find that productivity growth in nontradable consumer services such as retail, restaurants, or residential real estate was an important driver of structural transformation and rising living standards between 1987 and 2011. However, the welfare gains were heavily skewed toward high-income urban dwellers.
Virtually all theories of economic growth predict a positive relationship between population size and productivity. In this paper, I study a particular historical episode to provide direct evidence for the empirical relevance of such scale effects. In the af- termath of the Second World War, 8 million ethnic Germans were expelled from their domiciles in Eastern Europe and transferred to West Germany. This inflow increased the German population by almost 20%. Using variation across counties, I show that the settlement of refugees had large and persistent effects on the size of the local popula- tion, manufacturing employment, and income per capita. These findings are quantita- tively consistent with an idea-based model of spatial growth if population mobility is subject to frictions and productivity spillovers occur locally. The estimated model im- plies that the refugee settlement increased aggregate income per capita by about 12% after 25 years and triggered a process of industrialization in rural areas.
We study the role of European Immigration on local and aggregate economic growth in the United States between 1880 and 1920. We employ a big data approach and link, at the individual-level, information from the Population Census, the universe of patents and millions of historical immigration records. We find that immigrants were more prolific innovators than natives, and document large differences in innovation potential across nationalities and regions in the United States. To measure the importance of immigrants for the creation of new ideas and economic growth, we develop a new spatial model of growth through dissemination of knowledge and workers’ mobility. The model allows us to use our micro and regional empirical findings to measure immigrants’ innovation human capital and the degree of knowledge diffusion which regulates scale effects. We quantitatively analyze the effects of imposing major immigration restrictions on American economic growth in the 19th and early 20th century. We find large, accumulating, losses from these restrictions. Both the scale effects and the exclusion of high-human capital immigrants contribute significantly to these losses.