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Maria Carreri is a PhD Candidate in Politics at NYU (defending Spring 2018). She studies Comparative Politics and uses original survey data, historical data and rigorous quasi-experimental methods, to investigate the implications of politicians’ individual characteristics for political selection. In her job market paper, she employs an original survey methodology to develop a new measure of politicians’ competence and studies whether competent politicians can offset the negative effect of weak institutions on policy. In another paper, she moves from the quality of politicians to their personal experiences and the effect that these have on the policies they enact. She collects a novel dataset on the biographies of U.S. Members of Congress over the 1957-2012 period, and she shows that politicians who grew up during a recession are less supportive of redistribution.  Given empirical evidence that recessions make voters more supportive of redistribution, this shows that recessions can create a wedge between voters and their representatives. In a paper published in the Journal of Politics, she studies the negative impact on political selection of natural resources in conflict-affected contexts. The paper shows that natural resources, coupled with armed conflict, promote the rise to power of corrupt politicians who restrict electoral competition through the use of force. As a TA Maria has supervised students working on theses in political science and taught causal inference.  Maria can teach any course in quantitative methods or comparative politics at the graduate or undergraduate levels.


Kevin Munger is a PhD Candidate in the Department of Politics at NYU and a member of the NYU Social Media and Political Participation (SMaPP) lab. Kevin's dissertation studies the political implications of new forms of communication enabled by the internet and social media. This work involves developing innovative methods for performing online behavioral experiments. In Tweetment Effects on the Tweeted (published in Political Behavior), he pioneered the use of Twitter bots to intervene in instances of racist harassment; his job market paper extends this method to promote civil political discourse in an experiment conducted during the 2016 US Presidential election. 
Kevin's research also explores the implications of new media technologies on elite political communication. Matching panel survey data to objective measures of social media consumption, he finds that tweets by politicians and journalists enhance political learning during elections. Elite communication in authoritarian contexts plays out differnetly; in work with the SMaPP lab (conditionally accepted at Political Science Research and Methods), he finds that the Venezuelan regime used Twitter to distract from large-scale protests.
This work has entailed innovation in the use of Text as Data, and Kevin is also working (with Ken Benoit and Arthur Spirling) on developing a new measure of political sophistication from text. Kevin has been an active member of the Data Science community at NYU, and has helped teach four semesters of courses at the Center for Data Science: one semester of (Master's-level) Text as Data and three semesters of (Master's-level) Intro to Data Science.


Hande Mutlu-Eren completed her Ph.D. in Politics at NYU in 2011 and is currently teaching several undergraduate and graduate courses in comparative politics and political economy at NYU and Columbia University. Between 2010 and 2014 she was a Fellow in the Department of Government at the London School of Economics. Hande specializes in comparative politics and political economy focusing on comparative political institutions, party competition, coalitions, and national and local governments. Her doctoral research explores, using game theoretic models and quantitative methods, the conditions under which a sizable faction decides to break away from a partyin parliamentary systems (published in Public Choice), the conditions under which party members decide to replace their leader (revise and resubmit received from the Journal of Theoretical Politics), and the link between cabinet duration and cabinet reshuffles (under review). In a recent article (published in the Journal of Politics) she shows that in political systems with party-centered elections parties use intergovernmental transfers to advance their electoral fortunes via performance spillovers across different levels of government. Hande’s current research examines the impact of supranational integration such as the European Union on party system polarization (under review). In a second line of research, she analyzes whether the procedures for party leadership changes and their timing affect parties’ electoral performance.

Other projects that Hande is working on include a book manuscript on party splits, aiming at providing a comprehensive account of endogenous party splits in advanced industrialized countries as well as a paper on the politics of opposition where she explores the different ways in which opposition parties can influence policy and constrain government parties from gaining too much control over minorities. She has additional work on government formationcabinet dynamics in Turkey, and networks, which has appeared in Public ChoiceStudies in Conflict and Terrorism, and as a chapter in a book. Hande is prepared to teach courses in comparative politics, political economy, European politics, Middle Eastern politics, as well as formal models and quantitative research methods.


Renard Sexton is a PhD candidate in Politics at NYU (defending Spring 2017). He studies the political economy of conflict using field experimental and rigorous observational methods. In particular, his work explores how local political institutions determine how external shocks and interventions affect local level conflict. In a forthcoming article in the American Political Science Review, for example, he shows that multi-million dollar aid distributions by pro-government forces in Afghanistan increase violence in contested districts, but decreases violence in districts already controlled by counter-insurgents. Renard’s current research examines how electoral accountability and government capacity moderate the effect of commodity price shocks on extractive industries-related violence in Peru. He is conducting a companion field experiment in Peru to determine whether village-level trainings can improve the accountability and performance of local elected officials and if this has conflict-mitigating consequences. He is co-founder of the Northeastern Workshop in Empirical Political Science (NEWEPS), a junior fellow at the Association for Analytical Learning about Islam and Muslim Societies (AALIMS). He has experience teaching comparative politics and international relations at an undergraduate level and quantitative methods at a graduate level.


Gabor Simonovits is a PhD Candidate in Politics at NYU (defending in June 2017). His current research, situated in the intersection of public opinion and political economy, studies the interrelationship between mass opinion and public policy. In his dissertation, Public Opinion, and Redistributive Policies, Gabor uses survey data on preferences about tax progressivity and the minimum wage to describe the representation of mass opinion in redistributive policies in American states. Gabor finds evidence that contrary to existing empirical research, while policy outcomes are related to public opinion across states, they exhibit a conservative bias within states and in general are far from the outcomes preferred by most citizens. Beyond his dissertation, Gabor has published papers on diverse topics including electoral politics, political extremism, and quantitative methodology. These papers have appeared in Science, the Journal of Politics, Political Behavior, and Political Analysis, among other places.



Denis Stukal is a PhD Candidate in Politics at NYU (defending in May 2018) and a Graduate Research Associate of the NYU Social Media and Political Participation (SMaPP) Lab. He studies Comparative Politics and Political Methodology. His primary research is on applying modern machine learning tools to newly available sources of big data to uncover political processes in non-democratic regimes. In his dissertation, Misinformation in Non-democracies: Evidence from Russia, Denis shows how a non-democratic regime manipulates its informational environment and political institutions to ensure its survival. In particular, Denis develops the concept of a decoy non-ruling party and shows how the public rhetoric of decoy parties in Russia is used to lead voters away from opposition parties while avoiding to challenge the country leader (paper). Denis also uses supervised machine learning tools to develop a methodology to uncover government strategies for shaping online public opinion using bots. The application of that methodology to the Russian political Twitter shows an extensive use of bots to spread messages from loyal news agencies. 

Other projects that Denis is working on include a co-authored paper on how the Russian state-controlled television (mis)informs citizens about the economic performance of the regime, and another co-authored paper about the international agenda-setting efforts by the Russian state-controlled news agency Russia Today. He also develops software that facilitates research on the political use of social media (in particular, an R package to scrape VK: Rvk). 

Denis has extensive experience in teaching introductory and advanced quantitative methods, and introductory courses in Comparative Politics.