Empirical International Relations: Research and Methods
A.Y. 2020/2021
Learning objectives
The course has three crucial aims. The first goal is to provide students with a detailed overview of contemporary research topics in IR. In particular, the course highlights the peculiarities of conducting research in this field by employing a rigorous empirical perspective. The second objective is to show students how to structure an effective research article, building in an effective way all the components of the design, from an appealing research question to a solid theoretical framework, and from the use of new data to the employment of adequate methods. Finally, the third aim is to acquaint students with state-of-the-art quantitative and qualitative methods, from text-analysis to Bayesian process tracing, and from multivariate analysis to natural experiments. These methodological skills will be very helpful for students not only to conduct academic research and to write their term papers and dissertations, but also for their future careers in NGOs, International Organizations, think tanks, and the private sector.
Expected learning outcomes
At the end of the course, students will be familiar with the empirical language of International Relations, and with all the components of a scientific article's research design. They will be able to distinguish solid from weak research and they will have the tools to discuss thoroughly their scientific work and that of others. Furthermore, students will acquire a basic knowledge of various up-to-date quantitative and qualitative research methods and of statistical software. Thus, they will have sufficient skills to perform basic tasks with R and to produce simple empirical analyses employing different methods.
Lesson period: Third trimester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
Third trimester
All classes are on Microsoft Teams
Course syllabus
The course consists of four parts. The introduction presents the main differences between IR and Political Science, highlighting the main questions that contemporary IR addresses and the importance of quantitative methods inside and outside academia. The second section focuses on research design, showing how to structure a solid research plan, from the research question to case selection, and from the theoretical framework to data analysis. Then, the third section offers an overview of the most effective and up-to-date quantitative methods in IR, from text-analysis to natural experiments. Finally, the last section is devoted to an open debate, where students are asked to present a brief research proposal to be discussed together
Prerequisites for admission
Basic knowledge of statistics
Teaching methods
Classes and individual and group exercises
Teaching Resources
Class 1 - Introduction: Empirical IR
Students are asked to present themselves and to briefly talk about their research interests. Then, we provide an introduction on contemporary IR, highlighting the main questions that the discipline has tackled. Second, we discuss the importance of quantitative methods inside and outside academia, briefly presenting the specific methods we will teach during the seminar.
Required readings
/
Suggested readings
Curini, L. and R. Franzese (eds.) (2020). The SAGE Handbook of Research Methods in Political Science and International Relations. Los Angeles: SAGE
King, G., Keohane, R. and S. Verba (1994). Designing Social Inquiry. Princeton: Princeton University Press
Weiner, P. and A. Noland (1958). Roots of Scientific Thought. New York: Basic Books
Classes 2 and 3 - Research Design
We offer a detailed overview of every "component" of a successful research design in IR: the research question, the relevance of the inquiry, the theoretical framework, the hypotheses, data, case selection and the method. During the discussion of every research step, students are called to actively participate in the debate, coming up with original research questions and proposing ways to test expectations using given data and methods.
Required readings
Gustafsson, K., and L. Hagström (2018). What is the point? Teaching graduate students how to construct political science research puzzles. European Political Science 17(1), 1-15. (Class 2)
McCauley, A. and A. Ruggeri (2019). Formulating Research Questions & Designing Research Projects in International Relations. In L. Curini and R. Franzese (eds.) The Handbook of Research Methods in Political Science and International Relations, Los Angeles: SAGE (Class 2)
Mahoney, J. and G. Goertz (2006). A tale of two cultures: Contrasting quantitative and qualitative research. Political Analysis, 14(3), 227-249 (Class III)
Suggested readings
Geddes, B. (2003). Big questions, little answers: How the questions you choose affect the answers you get. In Paradigms and sand castles: Theory building and research design in comparative politics. Ann Arbour: University of Michigan Press
Keohane, R. O. (2008). Big questions in the study of world politics. In R. E. Goodin The Oxford Handbook of Political Science. Oxford: Oxford University Press
Kertzer, J. D. (2017). Microfoundations in International Relations conflict. Management and Peace Science 34(1), 81-97
Mearsheimer, J. J., and S. M. Walt (2013). Leaving theory behind: Why simplistic hypothesis testing is bad for International Relations. European Journal of International Relations 19(3), 427-457
Waltz, K. (1979). Laws and Theories, Chapter 1 in Theory of international politics. New York: McGraw-Hill
International Organization (journal), 55(2), 2001. Research Design and Method in International Relations. Special Issue
Classes 4 and 5: Statistics and multivariate analysis
These classes will highlight how recent IR research has employed statistics and multivariate analysis methods in its studies. In particular, through the discussion and replication of top research articles, the two classes will explore forms of data, variables and models that have become distinctive features of quantitative research in the discipline. The first class will focus on the ubiquitous use of dyadic variables in IR scholarship, especially in the democratic peace literature. The second class will instead be devoted to those attempts of accounting for geographic and spatial factors in models that employ events-data.
Required readings
Neumayer E. and Plümper T. (2020) Dyadic data analysis. In Curini L. and Franzese R. (2020) The SAGE Handbook of Research Methods in Political Science and International Relations, 717-729
Maoz, Z., & Russett, B. (1993). Normative and structural causes of democratic peace, 1946 1986. American Political Science Review, 624-638.
Elkins, Z., Guzman, A. T., & Simmons, B. A. (2006). Competing for capital: The diffusion of bilateral investment treaties, 1960-2000. International organization, 811-846.
Eck, K. (2012). In data we trust? A comparison of UCDP GED and ACLED conflict events datasets. Cooperation and Conflict, 47(1), 124-141.
Balcells, L. (2010). Rivalry and revenge: Violence against civilians in conventional civil wars. International Studies Quarterly, 54(2), 291-313.
Fjelde, H., & von Uexkull, N. (2012). Climate triggers: Rainfall anomalies, vulnerability and communal conflict in sub-Saharan Africa. Political Geography, 31(7), 444-453.
Suggested readings
Cranmer, S. J., & Desmarais, B. A. (2016). A critique of dyadic design. International Studies Quarterly, 60(2), 355-362.
Diehl, P. F., & Wright, T. M. (2016). A conditional defense of the dyadic approach. International Studies Quarterly, 60(2), 363-368.
Poast, P. (2016). Dyads are dead, long live dyads! The limits of dyadic designs in international relations research. International Studies Quarterly, 60(2), 369-374.
Sundberg, R., & Melander, E. (2013). Introducing the UCDP georeferenced event dataset. Journal of Peace Research, 50(4), 523-532.
Raleigh, C., Linke, A., Hegre, H., & Karlsen, J. (2010). Introducing ACLED: an armed conflict location and event dataset: special data feature. Journal of peace research, 47(5), 651-660.
Weidmann, N. B. (2015). On the accuracy of media-based conflict event data. Journal of Conflict Resolution, 59(6), 1129-1149.
Classes 6 and 7: Quantitative text-analysis
These classes will provide to the students an overview of "text as data" methods and point out how they can be effectively used to study IR and its sub-discipline of Foreign Policy Analysis (FPA). It will be also emphasized how these methods can be used to test hypothesis deriving from different theoretical perspectives and approaches, from rational choice theory to constructivism. The first class will concentrate on presenting these methods and provide examples of how FPA scholars have analysed political leaders' psychology on the basis of the frequency of their words, employing scaling methods and Wordfish in particular. The second class will focus on more sophisticated techniques and, in particular on Topic Models.
Required readings
Benoit K. (2020) Text as data: an Overview. In Curini L. and Franzese R. (2020) The SAGE Handbook of Research Methods in Political Science and International Relations, 461-497
Egerod B.C.K. and Klemmensen (2020) Scaling political positions from Text: assumptions, methods and pitfalls. In Curini L. and Franzese R. (2020) The SAGE Handbook of Research Methods in Political Science and International Relations, 498-521
Genovese, F. (2014). States' interests at international climate negotiations: new measures of bargaining positions. Environmental Politics, 23(4), 610-631.
Roberts, M. E., Stewart, B. M., Tingley, D., Lucas, C., Leder‐Luis, J., Gadarian, S. K., ... & Rand, D. G. (2014). Structural topic models for open‐ended survey responses. American Journal of Political Science, 58(4), 1064-1082.
Bagozzi, B. E., & Berliner, D. (2018). The politics of scrutiny in human rights monitoring: evidence from structural topic models of US State Department human rights reports. Political Science Research and Methods, 6(4), 661-677.
Baerg, N., & Lowe, W. (2020). A textual Taylor rule: estimating central bank preferences combining topic and scaling methods. Political Science Research and Methods, 8(1), 106-122.
Suggested readings
Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political analysis, 21(3), 267-297.
Slapin, J. B., & Proksch, S. O. (2008). A scaling model for estimating time‐series party positions from texts. American Journal of Political Science, 52(3), 705-722.
Laver, M., Benoit, K., & Garry, J. (2003). Extracting policy positions from political texts using words as data. American political science review, 311-331.
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. the Journal of machine Learning research, 3, 993-1022.
Grimmer, J. (2010). A Bayesian hierarchical topic model for political texts: Measuring expressed agendas in Senate press releases. Political Analysis, 18(1), 1-35.
Schönfeld, M., Eckhard, S., Patz, R., & van Meegdenburg, H. (2018). Discursive landscapes and unsupervised topic modeling in IR: A validation of text-as-data approaches through a new corpus of UN Security Council speeches on Afghanistan. arXiv preprint arXiv:1810.05572.
Class 8: Bayesian process tracing
After an introduction of process tracing, students are introduced to Bayesian process tracing (BPT). Through a series of examples, we present the main mechanisms that characterize the Bayesian approach to qualitative methods in IR. Finally, students participate in a group exercise on the employment of BPT on various International Political Economy puzzles.
Required readings
Bennett, Andrew and J. Checkel (2015). Process Tracing: From Metaphor to Analytical Tool. Cambridge: Cambridge University Press. Introduction
Fairfield, T. and A. Charman (2017). Explicit Bayesian analysis for process tracing: Guidelines, opportunities, and caveats. Political Analysis, 25(3), 363-380
Suggested readings
Bennett, A. (2015). Using Process Tracing to Improve Policy Making: The (Negative) Case of the 2003 Intervention in Iraq, Security Studies, 24:2, 228-238
Bennett, A. and C. Elman (2007). Case study methods in International Relations subfield. Comparative Political Studies, 40(2), 170‐195
Fairfield, T. and A. Charman (2019). A dialogue with the data: The bayesian foundations of iterative research in qualitative social science. Perspectives on Politics, 17(1), 154-167
Fairfield T. and C. Garay (2017). Redistribution Under the Right in Latin America: Electoral Competition and Organized Actors in Policymaking. Comparative Political Studies. 50(14), 1871-1906
Rink A. (2018). Do Protestant Missionaries Undermine Political Authority? Evidence From Peru. Comparative Political Studies. 51(4), 477-513
Zaks, S. (2021). Updating Bayesian(s): A Critical Evaluation of Bayesian Process Tracing. Political Analysis, 29(1), 58-74
Class 9: Experiments
After a brief discussion of randomized control trials (RCTs) and their implications for Social Science research, we focus on experiments in Political Science and IR. Through various examples, we present students the characteristics and the advantages of both natural and survey experiments. Finally, students participate in a group exercise in which they are asked to image the Covid-19 crisis as a natural experiment.
Required readings
Dunning T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach (Strategies for Social Inquiry). Cambridge: Cambridge University Press. Introduction
Diaz, G., Grady, C. and J. H. Kuklinski. Survey Experiments and the Quest for Valid Interpretation. In L. Curini and R. Franzese (eds.) The Handbook of Research Methods in Political Science and International Relations, Los Angeles: SAGE
Suggested readings
TBD
Class 10: Discussion
We discuss with students their brief research proposals (to be sent to us one week before the class). In particular, simulating a discussion during an academic conference, we highlight the strengths and weaknesses of each proposal, asking students to comment on each other's work.
Required readings
/
Suggested readings
/
Students are asked to present themselves and to briefly talk about their research interests. Then, we provide an introduction on contemporary IR, highlighting the main questions that the discipline has tackled. Second, we discuss the importance of quantitative methods inside and outside academia, briefly presenting the specific methods we will teach during the seminar.
Required readings
/
Suggested readings
Curini, L. and R. Franzese (eds.) (2020). The SAGE Handbook of Research Methods in Political Science and International Relations. Los Angeles: SAGE
King, G., Keohane, R. and S. Verba (1994). Designing Social Inquiry. Princeton: Princeton University Press
Weiner, P. and A. Noland (1958). Roots of Scientific Thought. New York: Basic Books
Classes 2 and 3 - Research Design
We offer a detailed overview of every "component" of a successful research design in IR: the research question, the relevance of the inquiry, the theoretical framework, the hypotheses, data, case selection and the method. During the discussion of every research step, students are called to actively participate in the debate, coming up with original research questions and proposing ways to test expectations using given data and methods.
Required readings
Gustafsson, K., and L. Hagström (2018). What is the point? Teaching graduate students how to construct political science research puzzles. European Political Science 17(1), 1-15. (Class 2)
McCauley, A. and A. Ruggeri (2019). Formulating Research Questions & Designing Research Projects in International Relations. In L. Curini and R. Franzese (eds.) The Handbook of Research Methods in Political Science and International Relations, Los Angeles: SAGE (Class 2)
Mahoney, J. and G. Goertz (2006). A tale of two cultures: Contrasting quantitative and qualitative research. Political Analysis, 14(3), 227-249 (Class III)
Suggested readings
Geddes, B. (2003). Big questions, little answers: How the questions you choose affect the answers you get. In Paradigms and sand castles: Theory building and research design in comparative politics. Ann Arbour: University of Michigan Press
Keohane, R. O. (2008). Big questions in the study of world politics. In R. E. Goodin The Oxford Handbook of Political Science. Oxford: Oxford University Press
Kertzer, J. D. (2017). Microfoundations in International Relations conflict. Management and Peace Science 34(1), 81-97
Mearsheimer, J. J., and S. M. Walt (2013). Leaving theory behind: Why simplistic hypothesis testing is bad for International Relations. European Journal of International Relations 19(3), 427-457
Waltz, K. (1979). Laws and Theories, Chapter 1 in Theory of international politics. New York: McGraw-Hill
International Organization (journal), 55(2), 2001. Research Design and Method in International Relations. Special Issue
Classes 4 and 5: Statistics and multivariate analysis
These classes will highlight how recent IR research has employed statistics and multivariate analysis methods in its studies. In particular, through the discussion and replication of top research articles, the two classes will explore forms of data, variables and models that have become distinctive features of quantitative research in the discipline. The first class will focus on the ubiquitous use of dyadic variables in IR scholarship, especially in the democratic peace literature. The second class will instead be devoted to those attempts of accounting for geographic and spatial factors in models that employ events-data.
Required readings
Neumayer E. and Plümper T. (2020) Dyadic data analysis. In Curini L. and Franzese R. (2020) The SAGE Handbook of Research Methods in Political Science and International Relations, 717-729
Maoz, Z., & Russett, B. (1993). Normative and structural causes of democratic peace, 1946 1986. American Political Science Review, 624-638.
Elkins, Z., Guzman, A. T., & Simmons, B. A. (2006). Competing for capital: The diffusion of bilateral investment treaties, 1960-2000. International organization, 811-846.
Eck, K. (2012). In data we trust? A comparison of UCDP GED and ACLED conflict events datasets. Cooperation and Conflict, 47(1), 124-141.
Balcells, L. (2010). Rivalry and revenge: Violence against civilians in conventional civil wars. International Studies Quarterly, 54(2), 291-313.
Fjelde, H., & von Uexkull, N. (2012). Climate triggers: Rainfall anomalies, vulnerability and communal conflict in sub-Saharan Africa. Political Geography, 31(7), 444-453.
Suggested readings
Cranmer, S. J., & Desmarais, B. A. (2016). A critique of dyadic design. International Studies Quarterly, 60(2), 355-362.
Diehl, P. F., & Wright, T. M. (2016). A conditional defense of the dyadic approach. International Studies Quarterly, 60(2), 363-368.
Poast, P. (2016). Dyads are dead, long live dyads! The limits of dyadic designs in international relations research. International Studies Quarterly, 60(2), 369-374.
Sundberg, R., & Melander, E. (2013). Introducing the UCDP georeferenced event dataset. Journal of Peace Research, 50(4), 523-532.
Raleigh, C., Linke, A., Hegre, H., & Karlsen, J. (2010). Introducing ACLED: an armed conflict location and event dataset: special data feature. Journal of peace research, 47(5), 651-660.
Weidmann, N. B. (2015). On the accuracy of media-based conflict event data. Journal of Conflict Resolution, 59(6), 1129-1149.
Classes 6 and 7: Quantitative text-analysis
These classes will provide to the students an overview of "text as data" methods and point out how they can be effectively used to study IR and its sub-discipline of Foreign Policy Analysis (FPA). It will be also emphasized how these methods can be used to test hypothesis deriving from different theoretical perspectives and approaches, from rational choice theory to constructivism. The first class will concentrate on presenting these methods and provide examples of how FPA scholars have analysed political leaders' psychology on the basis of the frequency of their words, employing scaling methods and Wordfish in particular. The second class will focus on more sophisticated techniques and, in particular on Topic Models.
Required readings
Benoit K. (2020) Text as data: an Overview. In Curini L. and Franzese R. (2020) The SAGE Handbook of Research Methods in Political Science and International Relations, 461-497
Egerod B.C.K. and Klemmensen (2020) Scaling political positions from Text: assumptions, methods and pitfalls. In Curini L. and Franzese R. (2020) The SAGE Handbook of Research Methods in Political Science and International Relations, 498-521
Genovese, F. (2014). States' interests at international climate negotiations: new measures of bargaining positions. Environmental Politics, 23(4), 610-631.
Roberts, M. E., Stewart, B. M., Tingley, D., Lucas, C., Leder‐Luis, J., Gadarian, S. K., ... & Rand, D. G. (2014). Structural topic models for open‐ended survey responses. American Journal of Political Science, 58(4), 1064-1082.
Bagozzi, B. E., & Berliner, D. (2018). The politics of scrutiny in human rights monitoring: evidence from structural topic models of US State Department human rights reports. Political Science Research and Methods, 6(4), 661-677.
Baerg, N., & Lowe, W. (2020). A textual Taylor rule: estimating central bank preferences combining topic and scaling methods. Political Science Research and Methods, 8(1), 106-122.
Suggested readings
Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political analysis, 21(3), 267-297.
Slapin, J. B., & Proksch, S. O. (2008). A scaling model for estimating time‐series party positions from texts. American Journal of Political Science, 52(3), 705-722.
Laver, M., Benoit, K., & Garry, J. (2003). Extracting policy positions from political texts using words as data. American political science review, 311-331.
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. the Journal of machine Learning research, 3, 993-1022.
Grimmer, J. (2010). A Bayesian hierarchical topic model for political texts: Measuring expressed agendas in Senate press releases. Political Analysis, 18(1), 1-35.
Schönfeld, M., Eckhard, S., Patz, R., & van Meegdenburg, H. (2018). Discursive landscapes and unsupervised topic modeling in IR: A validation of text-as-data approaches through a new corpus of UN Security Council speeches on Afghanistan. arXiv preprint arXiv:1810.05572.
Class 8: Bayesian process tracing
After an introduction of process tracing, students are introduced to Bayesian process tracing (BPT). Through a series of examples, we present the main mechanisms that characterize the Bayesian approach to qualitative methods in IR. Finally, students participate in a group exercise on the employment of BPT on various International Political Economy puzzles.
Required readings
Bennett, Andrew and J. Checkel (2015). Process Tracing: From Metaphor to Analytical Tool. Cambridge: Cambridge University Press. Introduction
Fairfield, T. and A. Charman (2017). Explicit Bayesian analysis for process tracing: Guidelines, opportunities, and caveats. Political Analysis, 25(3), 363-380
Suggested readings
Bennett, A. (2015). Using Process Tracing to Improve Policy Making: The (Negative) Case of the 2003 Intervention in Iraq, Security Studies, 24:2, 228-238
Bennett, A. and C. Elman (2007). Case study methods in International Relations subfield. Comparative Political Studies, 40(2), 170‐195
Fairfield, T. and A. Charman (2019). A dialogue with the data: The bayesian foundations of iterative research in qualitative social science. Perspectives on Politics, 17(1), 154-167
Fairfield T. and C. Garay (2017). Redistribution Under the Right in Latin America: Electoral Competition and Organized Actors in Policymaking. Comparative Political Studies. 50(14), 1871-1906
Rink A. (2018). Do Protestant Missionaries Undermine Political Authority? Evidence From Peru. Comparative Political Studies. 51(4), 477-513
Zaks, S. (2021). Updating Bayesian(s): A Critical Evaluation of Bayesian Process Tracing. Political Analysis, 29(1), 58-74
Class 9: Experiments
After a brief discussion of randomized control trials (RCTs) and their implications for Social Science research, we focus on experiments in Political Science and IR. Through various examples, we present students the characteristics and the advantages of both natural and survey experiments. Finally, students participate in a group exercise in which they are asked to image the Covid-19 crisis as a natural experiment.
Required readings
Dunning T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach (Strategies for Social Inquiry). Cambridge: Cambridge University Press. Introduction
Diaz, G., Grady, C. and J. H. Kuklinski. Survey Experiments and the Quest for Valid Interpretation. In L. Curini and R. Franzese (eds.) The Handbook of Research Methods in Political Science and International Relations, Los Angeles: SAGE
Suggested readings
TBD
Class 10: Discussion
We discuss with students their brief research proposals (to be sent to us one week before the class). In particular, simulating a discussion during an academic conference, we highlight the strengths and weaknesses of each proposal, asking students to comment on each other's work.
Required readings
/
Suggested readings
/
Assessment methods and Criteria
Attendance (at least 80%), participation, and final essay
SPS/04 - POLITICAL SCIENCE - University credits: 3
Laboratory activity: 20 hours
Professor:
Casiraghi Matteo Cesare Mario