abstract: 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. / Dissertation/Thesis / Ph.D. Economics 2013

本研究採用1995-2009年的WIOD 資料庫 World Input-Output Table(WIOT)、WIOD Socio Economic Accounts (SEAs)資料，將勞工使用教育程度分成三種技術勞工:高技術勞工、中技術勞工、低技術勞工與資本，五種要素的貿易要素內涵(Factor Content of Trade, FCT)，利用sign test檢測貿易要素內涵假說Vanek prediction，而不同於其他文獻，本文進一步討論貿易要素內涵假說Vanek prediction的sign test檢測結果與產業比例、貿易壁壘、國家地區別等因素之間的關聯性。實證結果為當討論貿易要素內涵時，將勞工要素使用教育程度細分，會與單一勞工要素有不同的影響，而地區的人力資本特性也是影響貿易要素內涵假說檢測結果之因素，美、歐洲相較於亞洲，對於勞工的貿易要素內涵假說檢測結果有正向的影響，區域性之經濟問題與貿易壁壘皆對於檢測結果有負向的影響，而供給面的附加價值中間投入使用量造成貿易要素內涵假說檢測結果正確性影響與預測有些許差異，此外，資本因要素特性移動自由性較高，不受到開放程度、做生意難易程度變數的影響，相反之，開放程度越高以及做生意難易度越容易，皆能增加勞工貿易要素內涵假說檢測結果的正確性；資本只易受到供給面影響，而勞工則供給面及需求面的因素皆會對其貿易要素內涵造成影響。

A indústria de transformação, que havia liderado o crescimento econômico do Brasil nas cinco décadas precedentes a 1981 na fase de industrialização, perdeu dinamismo desde início dos anos oitenta. Desde 1981, o produto manufatureiro brasileiro cresceu pouco e abaixo da modesta taxa de crescimento do Produto Interno Bruto (PIB) do Brasil. Com isso, o setor manufatureiro tem contribuído cada vez menos para a formação do PIB brasileiro e encolhido bastante relativo a indústria global, desde 1981 até 2017. Esta pesquisa realiza uma avaliação da estrutura produtiva e tecnológica bem desagregada setorialmente da indústria de transformação brasileira, desse modo, ela oferece um diagnóstico mais detalhado da perda de dinamismo industrial. Esta pesquisa procurou responder as seguintes perguntas: i) os setores manufatureiros diminuíram participação no PIB de maneira uniforme ou foi concentrado setorialmente? ii) os setores intensivos em conhecimento e tecnologia seguem uma trajetória de desindustrialização normal ou prematura? (iii) o tecido industrial do país está mais oco ou rarefeito nos anos 2000? (iv) o país é um montador que faz pouca transformação industrial em algum segmento manufatureiro? (v) os segmentos industriais que mais importaram insumos e componentes são também aqueles que mais exportaram? Ou seja, o Brasil tem uma inserção ativa nas cadeias globais de valor (CGV)? (vi) os setores de serviços são relevantes na realização de pesquisa e desenvolvimento (P&D) no país de modo que a desindustrialização é irrelevante da perspectiva tecnológica? Para responder essas perguntas foram criadas sérias inéditas de longo prazo da participação dos setores manufatureiros no PIB. Também foi obtida uma tabulação especial do IBGE com informações para 258 subsetores industriais que permitiu avaliar o grau de adensamento produtivo deles. E por fim foram utilizados dados das Contas Nacionais do Brasil, das matrizes de insumo-produto e de investimento setor por setor para fazer um retrato setorial da produção e uso de P&D, através de técnicas de insumo-produto. Os resultados encontrados permitem concluir que o desenvolvimento industrial brasileiro está estagnado desde 1981 e a manufatura apresenta uma retração de longo prazo do produto manufatureiro real per capita. Esta pesquisa também apresentou uma abordagem setorial da desindustrialização pelo PIB de forma inédita, revelando que parte da desindustrialização brasileira é normal (ou esperada) e parte é prematura (e indesejada), dado o nível de desenvolvimento do Brasil. A desindustrialização prematura ocorreu nos setores intensivos em tecnologia, que também possuem baixo grau de adensamento produtivo ao importar parcela substantiva dos insumos e componentes intensivos em P&D. Também foi constatado que o Brasil se insere de forma passiva nas CGV, pois as classes industriais que mais importaram insumos e componentes não exportaram. Por fim, os setores de serviços - que ganharam bastante peso no PIB nas últimas décadas - conduzem no Brasil poucos investimentos em P&D e em menor magnitude que os setores manufatureiros. Portanto, da perspectiva tecnológica, a prematura mudança estrutural rumo aos serviços tem implicações relevantes quanto ao progresso tecnológico futuro do Brasil. / Brazilian manufacturing sector, which had led Brazil\'s economic growth in the five decades preceding 1981 in the industrialization phase, lost dynamism since the early 1980s. Since 1981, Brazilian manufacturing product grew slightly below the modest growth rate of Brazil\'s Gross Domestic Product (GDP). With this, manufacturing sector has contributed less and less to the formation of the GDP. Brazilian manufacturing sector has also shrunk a lot relative to the global manufacturing from 1981 to 2017. This research makes an evaluation of the productive and technological structure well disaggregated sectorally of the Brazilian manufacturing industry, thus offering a detailed diagnosis of the loss of industrial dynamism. This research sought to answer the following questions: i) have the manufacturing sectors decreased their share in GDP uniformly, or have been sectorally concentrated? ii) are knowledge and technology intensive sectors following a trajectory of normal or premature de-industrialization? iii) are the production chains of the country more hollow or rarefied in the 2000s? iv) is the country an assembler who does little industrial transformation in some manufacturing subsector? v) are the manufacturing subsectors that more imported inputs and components also the ones that more exported? That is, Brazil has an active insertion in global value chains (GVC)? vi) are services sectors relevant in conducting research and development (R&D) in Brazil so that de-industrialization is irrelevant from the technological perspective? To answer these questions, the author created an unpublished long-term series of the participation of manufacturing sectors in GDP. A special tabulation of Brazilian Institute of Geography and Statistics was also obtained, with data for 258 manufacturing subsectors, which allowed evaluating the degree of productive densification. Finally, data from Brazil\'s National Accounts, input-output matrices, and investment matrices were used to make a sectoral portrait of the production and use of R&D, through input-output techniques. Results showed that Brazilian manufacturing development is stagnant and occurs a long-term retraction of real per capita manufacturing output since 1981. This research also presented a sectoral approach to deindustrialization by GDP in an unpublished way, reporting that part of Brazilian deindustrialization is normal (or expected) and part is premature (and undesirable) given the level of development of Brazil. Premature deindustrialization occurred in the technology-intensive sectors, which also have a low degree of productive densification by importing a substantial portion of the inputs and R&D-intensive components. It was also observed that Brazil inserts passively in the GVC since the manufacturing classes that more import inputs and components do not export. Finally, service sectors - which have gained considerable weight in GDP in recent decades - conducted little investment in R&D in Brazil and to a lesser extent than manufacturing sectors. Therefore, from the technological perspective, the premature structural change towards services has relevant implications for the future technological progress of Brazil.