Essays on inequality in developing countries (Colombia)

In the first chapter I develop a framework that provides a simple and explicit mechanism for understanding and quantifying the role of trade and technology in the rise of the skill premium in developing countries.; The distinguishing features of the model can be summarized as follows: Under capital-skill complementarity, a rise in the demand for capital will increase the wage gap. Three different forces may spur demand for capital. First, increased trade, which may raise output as well as lower the cost of imported machinery and equipment. Second, technological change, understood as a decrease in the price of capital. Finally, structural reforms may also affect the demand for capital by changing its relative price. Based on the model, an empirical methodology is developed to quantify the contribution of each of these factors to the rise in the skill premium of the Colombian manufacturing sector. I find that trade liberalization accounted for a 17% of the rise in the skill premium and exogenous technological change explains 32%. The rest is explained by other structural reforms implemented as part of the general process of globalization, mainly changes in the exchange rate and foreign investment regimes.; In the second chapter I analyze the effect of inequality on school enrollment in developing countries. I present a model in which parents make schooling decisions for their children, weighting the utility benefit of having a child with formal education versus the forgone income from child labor or household work. Agents vote over the preferred tax rate to finance freely provided public education. The utility benefit of an educated child is proportional to expenditure per student, so that there is congestion in the public good. The results show that, for a given level of GDP per capita, both the preferred tax rate and school enrollment will decrease as inequality increases. Although expenditure per student rises, the effect on school enrollment dominates the later so that total human capital in the economy decreases. Evidence using data of 59 developing countries between 1960 and 1990, supports the qualitative implications of the model. Some policy implication for the design of aid are also analyzed.