Bush 631 - Quantitative Methods

Lecturer

Dr. Rotem Dvir

Email: rdvir@tamu.edu.

Website: https://rotemdvir.wixsite.com/mysite

Course Description

This is a graduate course in quantitative social science research methods that covers the tools and techniques of quality research design and an introduction to basic statistical skills to conduct research in the social sciences. We will discuss multiple methods to design a research and use quantitative data to tackle a variety of questions in politics as a whole, and international affairs in particular. For example, What is the best way to predict election outcomes? What factors drive the onset of wars? What is the likelihood of a successful sanctions regime? Which type of leaders are more prone to concede in an international dispute? and how public opinion may shape the decision to begin negotiations?
The course integrates discussions about research design and data analysis with the focus on causal reasoning. It also emphasizes learning and practicing the skills to become proficient in the use of statistical software to manage and analyze data. Finally, as a writing course, we explore the essentials of writing professional documents such as technical and background reports, or executive summaries. Students submit tasks in which they design research relevant to their field of interest, practice programming, and prepare a final project that combines data analysis with policy relevance into a data-oriented infographic as well as a professional document📃 .

Course Material

Textbook: Imai, Kosuke. (2017). Quantitative Social Science: An Introduction.

Syllabus: Bush631.

Assignments and Tasks:

• Swirl homework assignments: Instructions.
• R Markdown document: Instructions.
• R Markdown template instructions: TempInst.
• R Markdown template: rmdFile.
• Research Task I (Unpacking methods in the literature): Instructions.
• Research Task II (Working with R): Instructions&Questions.
• Research Task II (Working with R): ScoringRubric.
• Research Task II (Working with R): Data.

Final Project:

• Instructions document: Instructions.
• Datasets folder: Data.
• Codebooks for data: Codebooks
• Research proposal tips:

Writing resources.

• Critical pillars of writing assignment: 5Ptoolkit.
• Mentor reflection on assignment: MentorText.
• Project proposal: ProposalMemo.
• Self-assessment guidelines: Rubric.
• Writing policy documents: PolicyBrief.
• More resources on Bush school writing website: BushWriting_Link.

International Affairs Analysis:

• Recommended websites: War on the Rocks; Political Violence at a Glance;Monkey Cage; The Conversation.
• Recommended podcasts: Paul Poast Pod; Intellignece Matters; IS: Off the Page; Chain Reaction(FPRI); Brookings Cafeteria; WOTR Pod.

Week 1 (01.18.2022)

• Required reading: QSS, Chapter 1 (pp. 1-31).
• Slides: QSS & Intro to R
• R code: Week1
• Data: Week1

Week 2 (01.25.2022)

• Required reading: QSS, Chapter 2 (pp. 32-54, sections 2.1-2.4).
• Recommended reading: Mattes, Michaela and Jessica Weeks (2019). “Hawks, Doves, and Peace: An Experimental Approach” American Journal of Political Science, 63 (1), pp. 53-66.
• Slides: Causality: vol. I
• R code: Week2
• Data: Week2.

Week 3 (02.01.2022)

• Required reading: QSS, Chapter 2 (pp. 54-74, sections 2.5-2.8).
• Recommended reading: Fuhrmann, M., and Michael Horowitz. (2015). “When leaders matter: Rebel experience and nuclear proliferation.” The Journal of Politics, 77(1), 72-87.
• Slides: Causality: vol. II
• R code: Week3
• Data: Rebels.
• Data: DomesticTerrorism.

Week 4 (02.08.2022)

• Required reading: QSS, Chapter 3 (pp. 75-96, sections 3.1-3.4).
• Recommended reading: Sagan, S., & Benjamin Valentino. (2018). “Not just a war theory: American public opinion on ethics in combat.” International Studies Quarterly, 62(3), 548-561.
• Recommended reading: Dvir, R., Geva, N., & Arnold Vedlitz. (2021). “Unpacking Public Perceptions of Terrorism: Does Type of Attack Matter?.” Studies in Conflict & Terrorism, 1-21.
• Slides: Measurement: vol. I.
• R Code: Week4.
• Data: TerrorismSurvey.
• Data: WarEthics.
• Data: Afghanistan.

Week 5 (02.15.2022)

• Required reading: QSS, Chapter 3 (pp. 96-122, sections 3.5-3.8).
• Recommended reading: Huff, C., and Joshua Kertzer. (2018). “How the public defines terrorism.” American Journal of Political Science, 62(1), 55-71.
• Slides: Measurement: vol. II.
• R Code: Week5.
• Data: CongressVoting.
• Data: UNVoting.
• Data: QBcontracts.

Week 6 (02.22.2022)

• Required reading: QSS, Chapter 4 (pp. 123-139, section 4.1).
• Recommended reading: GAO Report. (2021). “Defense Budget: Opportunities Exist to Improve DOD’s Management of Defense Spending.” US government accountability office website.
• Slides: Prediction: vol. I.
• R Code: Week6.
• Data: MilitarySpending1.
• Data: MilitarySpending2.
• Data: MilitaryAidUS.

Week 7 (03.01.2022)

• Required reading: QSS, Chapter 4 (pp. 139-161, section 4.2).
• Recommended reading: Lin-Greenberg, E. (2019). “Backing up, not backing down: Mitigating audience costs through policy substitution.” Journal of Peace Research, 56(4), 559-574.
• Slides: Prediction: vol. II.
• R Code: Week7.
• Data: Face.
• Data: FloridaVoting.
• Data: Health.
• Data: AC Backup-Backdown.

Week 8 (03.08.2022)

• Required reading: QSS, Chapter 4 (pp. 161-182, section 4.3).
• Recommended reading: Wood, T., Hoy, C., and Pryke, J. (2021). “The Effect of Geostrategic Competition on Public Attitudes to Aid.”, Journal of Experimental Political Science, 8(3), 285-295.
• Recommended reading: Fuhrmann, M. (2020). “When Do Leaders Free-Ride? Business Experience and Contributions to Collective Defense.”, American Journal of Political Science, 64(2), 416-431.
• Slides: Prediction: vol. III.
• R Code: Week8.
• Data: WomenLeadersIndia.
• Data: AussieData.
• Data: SpendNATO.
• Data: SpendLeadersNATO.
• Data: ICB.

Week 9 (03.22.2022)

• Required reading: QSS, Chapter 6 (pp. 242-277, sections 6.1-6.2).
• Recommended reading: Edry, J., Johnson, J. and Ashley Leeds. (2021). “Threats at Home and Abroad: Interstate War, Civil War, and Alliance Formation.” International Organization”, 75(3), 837-957.
• Slides: Probability: vol. I.
• R Code: Week9.
• Data: AggiesNFL.
• Data: ATOP.
• Data: CountryCodes.

Week 10 (03.29.2022)

• Required reading: QSS, Chapter 6 (pp. 277-313, sections 6.3-6.5).
• Recommended reading: Horowitz, M., McDermott, R., and Alan Stam. (2005). “Leader age, regime type, and violent international relations.” Journal of Conflict Resolution, 49(5), 661-685.
• Slides: Probability: vol. II.
• R Code: Week10.
• Data: AggiesNFL2.
• Data: Leaders.

Week 11 (04.05.2022)

• Required reading: QSS, Chapter 7 (pp. 314-342, sections 7.1).
• Recommended reading: Robinson, Kali. (2021). “What is the the Iran Nuclear Deal?” Council of Foreign Relations website.
• Recommended reading: Smeltz, D., Farmanesh, A., and Brendon Helm. (2021). “Iranians and Americans Support A Mutual Return to JCPOA”, The Chicago Council on Global Affairs Report.
• Slides: Uncertainty: vol. I.
• R Code: Week11.

Week 12 (04.12.2022)

• Required reading: QSS, Chapter 7 (pp. 342-369, section 7.2).
• Recommended reading: Scotto, T. J., & Reifler, J. (2017). “Getting tough with the dragon? The comparative correlates of foreign policy attitudes toward China in the United States and UK.” International Relations of the Asia-Pacific, 17(2), 265-299.
• Slides: Uncertainty: vol. II.
• R Code: Week12.

Week 13 (04.19.2022)

• Required reading: QSS, Chapter 7 (pp. 370-390, section 7.3).
• Recommended reading: Miller, S. (2014). “Reading a Regression Table: A Guide for Students”, Steven Miller blog.
• Slides: Uncertainty: vol. III.

Week 14 (04.26.2022)

• Recomended reading: Avey, P. C., Desch, M. C., Parajon, E., Peterson, S., Powers, R., & Tierney, M. J. (2021). “Does Social Science Inform Foreign Policy Evidence from a Survey of US National Security, Trade, and Development Officials.” International Studies Quarterly.
• Slides: Summary&Review.
• Data in the real world: Documentary