Doctor of Philosophy in Economics (PhD)
Using computational text analysis to gather new data on the behavior of various actors in political systems
Chapter 1 estimates how an individual's expressed sentiment responds to messages from their social network connections. I use machine learning to code messages for expressions of one type of sentiment: happiness. Because network link formation is not random, I use exogenous shifters to instrument for the message volume of each of a user’s neighboring nodes. Specifically, I interact neighbor daylight with average neighbor sentiment, and aggregate this across neighbors to construct an instrument for viewed messages. A user with neighbors in different places with different average sentiment receives a shock to their feed when light levels differ across those places. I find that a user's happiness increases by 3.4% when the happiness of incoming messages increases by 10%.Chapter 2 presents a general framework for estimating the causal effect of social interactions on online social networks. This context presents two challenges for causal estimation beyond the endogeneity problem discussed above. First, social networks are dynamic: users are affected not only by contemporaneous messages but also by past messages. Second, some data is missing. These networks have relatively low levels of clustering, which means that it is computationally infeasible to collect all of the neighbors of a sample of the network. I introduce an estimation strategy for addressing these two challenges. I also construct six new instruments within this framework and compare their strength. Chapter 3 develops a method for estimating the impact of voter demobilization efforts on voter turnout. We exploit two facts: a) demobilization is typically targeted to avoid the supporters of the intended beneficiary, and b) voting results are available at the sub-district (poll) level. Omitted variables will generally be constant across a district, while the impact of the violations will be decreasing in the level of support for the violating party. Our method is general in the sense that it does not require a natural experiment and is robust to countrywide shifts in voter support (”swing”). We apply this method to allegations of fraud in the 2011 Canadian federal election, and estimate that illegal demobilization efforts reduced turnout by 3.9% in affected districts.
This thesis studies topics in political economy and the economics of networks. In Chapter 2, we present and structurally estimate a model of endogenous network formation and legislative activity of politicians. Employing data on social and legislative effort of members of the 105th-110th U.S. Congresses (1997-2009), we find that there are substantial complementarities between the efforts of politicians, both within and across parties. Chapter 3 considers the econometrics of incomplete information games on networks. This chapter develops a tractable empirical model of linear interactions where each agent, after observing part of his neighbors' types, not knowing the full network of how information is transmitted, uses linear best responses. This allows the researcher to perform asymptotic inference without having to observe all the players in the game or having to know precisely the sampling process. The usefulness of this procedure is shown with an application to the provision of public goods across municipalities in Colombia.Chapter 4 studies the sources of party polarization in the U.S. Congress. Polarization is not just the result of changes in the ideology of individual legislators, but also of changes in the ability of political parties to discipline (whip) their members and of the deliberate agenda setting by their leadership. This chapter evaluates quantitatively the importance of these three components in driving polarization through a novel identification approach based on previously untapped whip count data and a structural model of legislative activity. In the final chapter, I turn my attention to the voters' side in political economy models. Surveys, polling data and media reports indicate that voters often choose whom to vote for at different stages in the political campaign. I develop a model of costly information acquisition that rationalizes these observations. The model implies a key tradeoff between the cost of acquiring information, and the gain such information brings. Under this framework, I show that information blackouts (i.e. forbidding release of campaigning or polling information before the election) generates welfare losses of around 1-2%.
Conditional cash transfers (CCT) are currently one of the most popular poverty reduction policies worldwide. Nevertheless, there is still limited evidence of their impact on the local political dynamics of developing nations plagued by corruption, clientelism, and vote buying. This thesis studies this issue using data from Brazil's Bolsa Família, the largest CCT program in the world.Abstract Chapter 2 proposes a theoretical mechanism to illustrate how a CCT program could affect local politics in such institutional setting, when local politicians cannot manipulate program eligibility. In a nutshell, when mayors are able to buy votes by diverting public resources into private payments to swing voters, a CCT program works as an income shock that reduces the voter's marginal utility coming from vote buying. Abstract Chapter 3 uses data from Brazil's Bolsa Família to test the theoretical predictions from the first Chapter. It shows that, when transfers are shielded from the influence of political intermediaries, they trigger a reduction in incumbency advantage, an increase in both political competition and the quality of candidates, and a reduction in the support for high-clientelism parties. Transfers also lead incumbents to shift spending toward redistributive health and education services. These results are estimated with a nonparametric multivariate regression discontinuity design. Abstract Despite of the improvements brought out by the CCT program, when politicians can control access to the program, some of these political impacts might be negative in the short-term. Chapter 4 tells this other side of the story: what happens when politicians are able to manipulate program enrollment. Using administrative data from the Bolsa Família registry, and a regression discontinuity design in close elections, this Chapter shows that mayors with reelection incentives are more likely to promote income underreporting fraud by households, for the purpose of eligibility to CCT. This fraud is rewarded by voters, as corrupt mayors have a higher reelection probability. Finally, the Chapter also shows the need for disciplining devices to reduce this type of corruption. A higher risk of audits by the federal government is shown to drastically reduce the effects of reelection incentives on fraud.
This dissertation studies the incentives of economic agents to acquire informationabout financial assets when it must be acquired through time consumingresearch. When information can not be obtained instantaneously,agents face a tradeoff between acting immediately and performing morethorough research. Better information allows for more informed tradingdecisions, but research is costly because other agents' trades move pricesadversely as time passes.The first chapter develops a theoretical model in which agents sequentiallytrade a single financial asset. Each agent receives weak, private informationwhen they arrive to the market and may trade immediately, orinstead wait for additional information. Should they wait, other agentshave an opportunity to trade before the first agent receives their additionalinformation, which creates an endogenous cost to waiting. The analysisdetermines the conditions under which equilibrium behavior involves immediatetrades ("panics"), and then studies the quantitative impacts of weaklyinformed trades on the ability of prices to aggregate information.The second chapter experimentally tests the theoretical model in a laboratorysetting, in order to determine whether or not subjects understandthe tradeoff between better quality information and potential adverse pricemovements. Comparative static results establish that the theory broadlyexplains when panics, and the corresponding informational losses, occur.However, additional, "heuristic" panics are also frequently observed. Specifically,subjects exhibit a strong tendency to wait for more information whenhighly uncertain about asset values, but switch to trading as soon as possibleonce values become more certain.Motivated by the findings of the second chapter, the third chapter extends both the theory of the first chapter and the experimental results of thesecond chapter to a second, richer environment. Different from the sequentialstructure of the first model, agents may trade simultaneously in the richermodel. Experimental results with the richer model produce trade clusteringand serial correlations in returns, as predicted by the heuristic behavioridentified in the second chapter. These phenomena are well-established featuresof real financial markets, suggesting that the heuristic subjects followin the laboratory may provide a novel explanation for these phenomena.
Recent research has stressed the role of political institutions in economic development. This thesis aims at shedding light on this issue by empirically analyzing the political determinants of policymaking and its consequences to living standards in a developing economy setting.Each of its three chapters presents a separate essay. The first chapter addresses how the political participation of disadvantaged groups can be fostered. It studies the introduction of electronic technology that facilitated voting for the less educated in Brazilian elections. Using a regression discontinuity design embedded in its phase-in, it provides evidence that electronic voting reduced residual (uncounted) votes and generated the de facto enfranchisement of a large fraction of the less educated (poorer) parts of the electorate. The second chapter tests if this additional political participation of poorer voters shifted public policymaking in a way that benefited them. It finds evidence that electronic voting increased the number of state legislators that are themselves less educated and shifted government spending towards public health care, a government policy that disproportionately benefits the less educated, leading to improved utilization (number of pre-natal visits) and lower prevalence of low-weight births in this group. No effects on health care utilization by the more educated and on the weight of their newborns are found, suggesting that electronic voting indeed empowered the less educated.Lastly, the third chapter addresses the empirical relevance of strategic voting, a key issue in theoretical and policy analysis of political institutions. It uses exogenous variation in electoral rules to test the predictionsof strategic voting models and the causal validity of Duverger's Law. Estimations based on a regression discontinuity design in the assignment of single-ballot and dual-ballot electoral systems in Brazilian mayoral races indicate that, in accordance to Duverger's Law, single-ballotplurality rule causes voters to desert third placed candidates and vote for the two most popular ones. It finds that the effects are stronger in close elections, and that candidates' characteristics and entry cannot account for the results, suggesting that strategic voting is the driving force behind these findings.