The US steel industry experienced a great decline between 1950-1985. Influenced by several government policies, the industry was first cartelized during the great depression and then subjected to an extremely powerful organized labor force. Due to high demand between and…
The US steel industry experienced a great decline between 1950-1985. Influenced by several government policies, the industry was first cartelized during the great depression and then subjected to an extremely powerful organized labor force. Due to high demand between and during WWII and the Korean War, the industry expanded capacity using existing technologies. Simultaneously, organized labor was able to secure increased wages and large severance costs for firms that decided to shutdown existing steel mills. In the post war years this prevented firms from innovating through investing in newer, more efficient, technologies. Eventually US steel firms had no advantage against foreign producers who could produce steel cheaper and more efficiently.
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The U.S. Automobile industry was once the crown jewel of America's industrial empire, nothing symbolized American industrial might like the auto plants of Detroit and the millions of cars it put on the road. However, after a spectacular rise in…
The U.S. Automobile industry was once the crown jewel of America's industrial empire, nothing symbolized American industrial might like the auto plants of Detroit and the millions of cars it put on the road. However, after a spectacular rise in power and wealth after the Second World War, the Big 3 of the automotive industry, General Motors, Ford and Chrysler, have declined to the point of needing a government bailout to continue operation. This paper examines this decline by examining two narratives that describe its fall, and examines the theoretical and empirical evidence for both stories.
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This dissertation consists of three essays that broadly deal with the growth and development of economies across time and space. Chapter one is motivated by the fact that agricultural labor productivity is key for understanding aggregate cross-country income differences. One…
This dissertation consists of three essays that broadly deal with the growth and development of economies across time and space. Chapter one is motivated by the fact that agricultural labor productivity is key for understanding aggregate cross-country income differences. One important proximate cause of low agricultural productivity is the low use of intermediate inputs, such as fertilizers, in developing countries. This paper argues that farmers in poor countries rationally choose to use fewer intermediate inputs because it limits their exposure to large uninsurable risks. I formalize the idea in a dynamic general equilibrium model with incomplete markets, subsistence requirements, and idiosyncratic productivity shocks. Quantitatively, the model accounts for two-thirds of the difference in intermediate input shares between the richest and poorest countries. This has important implications for cross-country productivity. Relative to an identical model with no productivity shocks, the addition of agricultural shocks amplifies per capita GDP differences between the richest and poorest countries by nearly eighty percent. Chapter two deals with the changes in college completion in the United States over time. In particular, this paper develop a dynamic lifecycle model to study the increases in college completion and average IQ of college students in cohorts born from 1900 to 1972. I discipline the model by constructing historical data on real college costs from printed government reports covering this time period. The main finding is that that increases in college completion of 1900 to 1950 birth cohorts are due primarily to changes in college costs, which generate a large endogenous increase in college enrollment. Additionally, evidence is found that supports cohorts born after 1950 underpredicted sharp increases in the college earnings premium they eventually received. Combined with increasing college costs during this time period, this generates a slowdown in college completion, consistent with empirical evidence for cohorts born after 1950. Lastly, the rise in average college student IQ cannot be accounted for without a decrease in the variance of ability signals. This is attributed the increased precision of ability signals primarily to the rise of standardized testing. Chapter three again deals with cross-country income differences. In particular, it is concerned with the fact that cross-country income differences are primarily accounted for by total factor productivity (TFP) differences. Motivated by cross-country empirical evidence, this paper investigates the importance individuals who operate their own firms because of a lack of other job opportunities (need-based entrepreneurs). I develop a dynamic general equilibrium labor search model with with entrepreneurship to rationalize this misallocation across occupations and assess its role for understanding cross-country income differences. Developing countries are assumed to have tighter collateral constraints on entrepreneurs and lower unemployment benefits. Because these need-based entrepreneurs actually have a comparative advantage as workers, they operate smaller and less productive firms, lowering aggregate TFP in developing countries.
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This dissertation consists of two essays. The first measures the degree to which schooling accounts for differences in industry value added per worker. Using a sample of 107 economies and seven industries, the paper considers the patterns in the education…
This dissertation consists of two essays. The first measures the degree to which schooling accounts for differences in industry value added per worker. Using a sample of 107 economies and seven industries, the paper considers the patterns in the education levels of various industries and their relative value added per worker. Agriculture has notably less schooling and is less productive than other sectors, while a group of services including financial services, education and health care has higher rates of schooling and higher value added per worker. The essay finds that in the case of these specific industries education is important in explaining sector differences, and the role of education all other industries are less defined. The second essay provides theory to investigate the relationship between agriculture and schooling. During structural transformation, workers shift from the agriculture sector with relatively low schooling to other sectors which have more schooling. This essay explores to what extent changes in the costs of acquiring schooling drive structural transformation using a multi-sector growth model which includes a schooling choice. The model is disciplined using cross country data on sector of employment and schooling constructed from the IPUM International census collection. Counterfactual exercises are used to determine how much structural transformation is accounted for by changes in the cost of acquiring schooling. These changes account for small shares of structural transformation in all economies with a median near zero.
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