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Abstract

Chapter 2 empirically examines how labor-saving technological change in agriculture affects labor reallocation across sectors in economies with sizable informal sectors, and how labor regulations enforcement shapes this process. To identify the causal effect, I exploit the 2003 legalization of genetically modified (GM) soybeans in Brazil and cross-municipality variation in potential yield gains. Between 2000 and 2010, municipalities with greater potential productivity gains from GM soy experienced larger reallocation of labor from agriculture to formal manufacturing, accompanied by declines in informal manufacturing employment. Further analysis of heterogeneous effects by interacting the GM soybean shock with enforcement capacity shows that the reallocation is significantly less pronounced in areas with stricter enforcement of labor regulations. In Chapter 3, I develop and calibrate a two-sector general equilibrium model that qualitatively replicates the empirical findings from Chapter 2. Agricultural production is modeled using a constant elasticity of substitution (CES) function that allows for differential technological progress of labor and land, capturing the factor-biased nature of GM soy. The manufacturing sector features heterogeneous firms that self-select into being formal or informal. Counterfactual exercises show that intensifying enforcement to halve manufacturing informality reduces labor reallocations to manufacturing by 4.5%. Additional simulations suggest that lowering entry and fixed costs for formal firms promotes labor movement into manufacturing while reducing informality. Chapter 4 analyzes how structural changes in the global input-output networks have influenced economic growth across countries at different stages of development. We find that shifts in global supply chains between 1965 and 2000 benefited developing countries while disadvantaging advanced economies. Counterfactual analysis shows that, without these changes, TFP growth would have been 26.6% and 9.7% lower in China and India, and 4.0% and 16.8% higher in the US and Australia. We further demonstrate that a simple statistic, the domestic intermediate input cost share, effectively captures how global networks amplify productivity shocks. Our findings highlight the importance of supply chain integration and the use of intermediate inputs for economic growth.