Essays in applied microeconomics and networks

Abstract

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 153-167).Chapter 1 focuses on the recent dramatic shift in attitudes toward LGBT individuals in the U.S. and the accompanying rise in the number of Americans who have openly come out. We develop a model of stigma with Schelling-style tipping dynamics. Regions may be stuck in equilibria with low LGBT support and few openly gay individuals. These equilibria can be escaped via trigger events, that by causing even a small number of individuals to display their support for LGBT causes, can cause more individuals to come out, leading to more support, etc. We then evaluate our model with a large, online archival dataset on the timing of coming out decisions and public displays of support for LGBT causes for several million Americans. Using state-specific shocks to each, aggregate network data, and instrumental variables, we show how increases in LGBT support lead to elevated coming out rates in highly connected areas, and vice-versa. Chapter 2 studies a recent hypothesis that posits maternal vitamin D levels during pregnancy may affect the probability the fetus later develops asthma. Employing two large-scale studies, we test this hypothesis using a natural experiment afforded by historical variation in sunlight, a major source of vitamin D. Specifically, holding the birth location and month fixed, we see how exogenous within-location variation in sunlight across birth years affects the probability of asthma onset. We find highly significant evidence in both datasets that increased sunlight during the second trimester substantially lowers the subsequent probability of asthma. Finally, Chapter 3 is an evolutionary game theory paper about population structure. We provide a general, modularity-based framework for studying evolutionary games on structured populations under 'weak selection' that includes many previously known results as special cases. Our framework helps to show how these past disparate results are connected, and we exploit this insight to develop a general method for quantifying in closed form the effect of population structure on evolutionary dynamics. We illustrate our framework by proposing and solving a new model that generates a simple rule for the evolution of cooperation on endogenous dynamic networks.by Nils Christian Wernerfelt.Ph. D