![]() “Matching Methods for Causal Inference with Time-Series Cross-Section Data” Forthcoming at American Journal of Political Science (with Kosuke Imai and Erik Wang) Teaching 17.“The food on your table comes with a price you can’t see, but that somebody has to pay. ![]() Machine Learning and Data Science in Politics Quantitative Research Methods IV: Advanced Topics Quantitative Research Methods III: Generalized Linear Models and Extensions Quantitative Research Methods I: Regression “Matching Methods for Causal Inference with Time-Series Cross-Section Data” Forthcoming at American Journal of Political Science (with Kosuke Imai and Erik Wang) Teaching 17.464 (2021) (with Jiseon Kim, Elden Griggs, and Alice Oh) “Learning Bill Similarity with Annotated and Augmented Corpora of Bills” Empirical Methods in Natural Language Processing (EMNLP). “On the Use of Two-way Fixed Effects Regression Models for Causal Inference with Panel Data” Political Analysis, (2021), Vol.29, No.3, pp.405-415 (with Kosuke Imai) “Mapping Political Communities: A Statistical Analysis of Lobbying Networks in Legislative Politics” Political Analysis, (2021), Vol.29, No.3, pp.317-336 (with Dmitriy Kunisky) “Measuring Trade Profile with Granular Product-level Trade Data” American Journal of Political Science, (2020), Vol 64, No. “The Effects of Political Institutions on the Extensive and Intensive Margins of Trade” International Organization, (2019), Vol 73, No. “Firms in Trade and Trade Politics” Annual Review of Political Science (2019), Vol 22, pp. “When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?” American Journal of Political Science (2019), Vol 63, No. Milner, Thomas Bernauer, Iain Osgood, Gabrielle Spilker, and Dustin Tingley) “Firms and Global Value Chains: Identifying Firms’ Multidimensional Trade Preferences” International Studies Quarterly (2019), Vol 63, No. “Estimating Spatial Preferences from Votes and Text” Political Analysis (2018), Vol. ![]() (with Iain Osgood, Dustin Tingley, Thomas Bernauer, Helen V. “The Charmed Life of Superstar Exporters: Survey Evidence on Firms and Trade Policy” Journal of Politics (2017), Vol. “Political Cleavages within Industry: Firm-level Lobbying for Trade Liberalization” American Political Science Review (2017), Vol. He is developing a large-scale database on lobbying supported by the National Science Foundation. Professor Kim is also interested in the development of quantitative methods for causal inference with panel data, "big data" analysis, network models, and estimating political actors' preferred policy outcomes. His current research interests include firm-level lobbying on trade policies, product-level trade policy-making, and the interaction between domestic political institutions and international trade. ![]() Professor Kim is broadly interested in international political economy and political methodology. His work has appeared and is forthcoming in various academic journals, including the American Political Science Review, American Journal of Political Science, Annual Review of Political Science, International Organization, International Studies Quarterly, Political Analysis, and The Journal of Politics. He is developing methods for dimension reduction and visualization to investigate how the structure of international trade around the globe has evolved over time. In Song Kim conducts Big Data analysis of international trade. An article version of this research received the 2018 Michael Wallerstein Award for the best published article in political economy. His dissertation won the 2015 Mancur Olson Award for the Best Dissertation in political economy. His research focuses on the political economy of lobbying and campaign donation, estimation of political preferences, and causal inference with panel data. His research interests include International Political Economy and Formal and Quantitative Methodology. In Song Kim is Associate Professor of Political Science at the Massachusetts Institute of Technology. ![]()
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