Author(s): Santos, Marcelo Serra
Date: 2015
Persistent ID: http://hdl.handle.net/10400.6/3956
Origin: uBibliorum
Subject(s): História económica - Desenvolvimento económico; Desenvolvimento económico - Inovação tecnológica; Desigualdade de rendimentos - Análise de pobreza; Desenvolvimento económico - Capital humano; Desenvolvimento económico - Tecnologia; Domínio/Área Científica::Ciências Sociais::Economia e Gestão
This thesis investigates the relationship between human capital and technology, by one side and the ancestral genetic diversity of populations, by the other. Then, it seeks to understand the determinants of several inventions that occurred during the process of industrial revolutions. Finally, it presents evidence on the determinants of inequality, a clear overlooked issue in the empirical literature. The rst chapter, Introduction, provides a critical revision of the literature and stresses the contributions of the thesis. The second chapter highlights theoretically a new channel through which genetic diversity can affect development: human capital. It also shows strong empirical evidence of a hump-shaped relationship between genetic diversity and human capital. This means that some of the human capital achievements today may stem from the genetic diversity mostly determined many centuries ago. Results are robust to the introduction of several controls and to IV estimation. The third chapter investigates the relationship between technology in 1500 and the ancestral genetic diversity of populations. It highlights a strong hump-shaped relationship between genetic diversity and technological developments in 1500. This means that some of the technological achievements may stem from the genetic diversity mostly determined more than a millennium ago. Results are robust to the introduction of several controls, and to IV estimation. The fourth chapter contributes to answer to the question "why inventions that shaped industrial revolutions have been discovered in some countries and not in others?". We access the determinants of more than a hundred inventions around the world, explaining why they occurred in a given country and why some occurred earlier than others. We con rm the importance of scale and dismiss the importance of education as triggers of inventions. Geographic and genetic distance from the UK and the USA have proven to be signi cant. Both distance from the UK and proximity to the USA seem to have signi cant effect on the rise of the probability to invent. A fruitful recent theoretical literature has related human capital and technological development with income (and wages) inequality. However, empirical assessments on the relationship are still scarce. In the fth chapter, we relate human capital, total factor productivity (TFP), and openness with inequality and discover that, when countries are assumed as heterogeneous and dependent cross-sections, human capital is the most robust determinant of inequality, contributing to increase inequality, as predicted by theory. TFP and Openness revealed to be non-signi cantly related to inequality. These new empirical results open prospects for theoretical research on the country-speci c features conditioning the causal relationship from human capital, technology and trade to inequality. In the last chapter of the thesis, we relate technological adoption (of different technologies) with income inequality. We discovered that some technologies such as aviation, cell phones, electric production, internet, telephone, and TV are skill-complementary in raising inequality. We constructed standardized indexes of skill-complementary technological adoption for modern Information and Communication Technologies (ICT), older ICT, production and transport technologies. We found strong evidence that older ICT and transport technologies (and less frequently modern ICT) tend to increase inequality. Additionally, we discovered that results are much stronger in rich countries than in poor ones. Our results are quite robust to a series of changes in speci cations, estimators, samples, and measurement of technology adoption. These results may bring insights to the design of incentive-schemes for technology adoption.
