Trade and American Politics
The Shifting Effects of Trade-Related Job Losses on Americans’ Attitudes about Free Trade (2017) Under Review
Do voters care about trade? Traditionally, the answer has been "no" with trade occupying a low-salience space in American politics. The election of Donald Trump, who campaigned on a protectionist platform, suggests that trade is re-emerging as a politically important issue. I explore the shifting salience of trade policy between 2000 and 2016 using individual survey data combined with estimates of trade-related layoffs in the county where the respondent lives. I generate exogenous variation in layoffs by using Chinese exports to developed countries to identify a robust causal link between trade-related layoffs and negative views of trade, suggesting that individuals update their policy preferences in a rationally coherent manner. However, by exploiting the similar policy positions espoused by George W. Bush and Barack Obama, I also show that partisans base their opinions on what their co-partisan / out-partisan president says. Specifically, while Democrats trade policy preferences are consistently sensitive to trade-related layoffs across both presidential administrations, Republicans become significantly more protectionist during Obama's term, a result consistent with elite communication and motivated reasoning. I connect these changing opinions to presidential vote shares, finding that counties with more sensitive trade opinions recorded significantly higher vote shares for Donald Trump. These results speak to the individual preferences on trade, the mechanisms by which preferences are formed, and the connection between costless survey responses and costly voting behavior during a period in which trade underwent a shift in political salience, culminating in the election of Donald Trump.
Responsive Politicians: Local Trade Shocks and Congressional Support for Free Trade (2017) Working Paper
Do politicians adjust their positions on trade policy in response to trade shocks? I examine the effect of trade shocks on US Congressional support for free trade between 1994 and 2005, finding that members of the House of Representatives are less likely to support free trade legislation following trade-related layoffs in their District. This effect is stronger during election years and in contested Congressional Districts, suggesting that electorally vulnerable politicians are more responsive to their constituents than those in "safe seats". Importantly, the changes in roll call votes I identify are produced by Representatives changing their position on trade (a responsiveness mechanism), and not by voters replacing free traders with protectionists (a selection mechanism). However, the responsiveness of elected politicians is muted as they receive more funding from interest groups.
Trade and Crime: Connecting Trade-Related Layoffs with Criminal Activity (2017) Working Paper
The decline in crime rates over the last three decades has enlivened the debate over the preferred methods of combating deviant behavior. Simple regressions of crime on income have documented a strong negative relationship, suggesting that crime is a problem of the poor. However, this research has been unable to adjudicate between the competing theories for this negative relationship. One of the most entrenched debates is over the mediating effects of the state. Do changes in income cause declines in deviant behavior because the government is better able to deter crime with expanded budgets? Or is the causal effect primarily the result of increased opportunity costs? I test these competing theories on county-level crime data from the United States between 1982 and 2007, using trade shocks as a source of exogenous variation in income. I conclude that the majority of the income-crime relationship is explained by the direct effects of opportunity costs. However, there is evidence of a small but significant mediation effect in the form of government expenditures on police.
International Political Economy
The Millennium Development Goals and Education: Accountability and Substitution in Global Assessment with James R. Hollyer, James Raymond Vreeland, and Peter B. Rosendorff (2017) Under Review
Precise international metrics and assessments may induce governments to alter policies in pursuit of more favorable assessments according to these metrics. In this paper, we explore a secondary effect of global performance assessments (GPAs): Insofar as governments have finite resources and make trade-offs in public goods investments, a GPA that precisely targets the provision of a particular public good may cause governments to substitute away from the provision of other, related, public goods. We argue that both the main effect of the GPA (on the measured public good) and this substitution effect vary systematically based on the domestic political institutions and informational environments of targeted states. Specifically, we contend that both the main and substitution effects of GPAs should be largest for governments that are least accountable (opaque and non-democratic) and should be smallest for those that are most accountable. We test these claims using data on primary and secondary enrollment rates across 114 countries. We find that countries substitute toward primary (which is targeted by the MDGs) and away from secondary (which is not), and that these effects are mitigated as accountability rises.
Local Instruments, Global Extrapolation: External Validity of the Labor Supply-Fertility Local Average Treatment Effect with Rajeev Dehejia, Cristian Pop-Eleches, and Cyrus Samii. Journal of Labor Economics (2017) vol. 35, no. S1
We investigate the external validity of local average treatment effects (LATEs), specifically Angrist and Evans’ (1998) use of same sex of the two first children as an instrumental variable for the effect of fertility on labor supply. We estimate their specification in 139 country-year censuses using Integrated Public Use Micro Sample International data. We compare each country-year's actual LATE to the extrapolated LATE from other country-years. We find that, with a sufficiently large reference sample, we extrapolate the treatment effect reasonably well, but the degree of accuracy depends on the extent of covariate similarity between the target and reference settings. [Paper]
Testing Social Science Network Theories with Online Network Data: An Evaluation of External Validity with Jennifer M. Larson. American Political Science Review (2017) 1-20
To answer questions about the origins and outcomes of collective action, political scientists increasingly turn to datasets with social network information culled from online sources. However, a fundamental question of external validity remains untested: are the relationships measured between a person and her online peers informative of the kind of offline, "real-world" relationships to which network theories typically speak? This article offers the first direct comparison of the nature and consequences of online and offline social ties, using data collected via a novel network elicitation technique in an experimental setting. We document strong, robust similarity between online and offline relationships. This parity is not driven by shared identity of online and offline ties, but a shared nature of relationships in both domains. Our results affirm that online social tie data offer great promise for testing long-standing theories in the social sciences about the role of social networks. [Paper]
BARP: Using Bayesian Additive Regression Trees to Improve Multi-Level Regression and Post-Stratification (2017) Working Paper
Multi-level regression and post-stratification (MRP) is the current gold standard for extrapolating opinion data from nationally representative surveys to smaller geographic units. However, MRP requires researchers to model opinion as a linear function of individual- and state-level covariates, risking errors due to mis-specification. I propose a modified version of MRP that replaces the multi-level model with a non-parametric classification method called Bayesian Additive Regression Trees (BART or, when combined with post-stratification, BARP). I compare both methods across a number of data contexts, finding that BARP consistently outperforms MRP mainly due to its insulation from mis-specification. Both methods are equally vulnerable to data quality issues, affirming previous research on the limitations of MRP. In addition, I present evidence of systematic bias in MRP estimates when opinion is correlated with population, a novel finding with implications for applied research on representation.