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Plan II Honors

S S 302C • Hon Soc Sci:methods/Theory

42405 • Chapman, Terrence
Meets TTH 9:30AM-11:00AM MEZ 1.120
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This course will serve as a broad introduction to international relations topics and research.  The course will be framed around a series of questions or topics, including (but not limited to) the following:

-       Is there an order to the international system?  If so, what are the determinants of that order?

-       Why do wars occur?  If war is costly in terms of lives and resources, when and why do governments fail to solve their differences by other means?

-       How has globalization changed the landscape of international politics?  What aspects of globalization are most important for understanding contemporary trends in national and international politics?

-       What role do international institutions and international law play in facilitating cooperation and order in the international system?

The course will analyze these questions through the lens of modern social scientific approaches, meaning we will spend time thinking rigorously about theoretical explanations and evidence based approaches to adjudicating between multiple explanations.  In that vein, students will be exposed to common research strategies employed by modern international relations scholars, ranging from qualitative historical and case study accounts to statistical analysis to experimental methods.  Likewise, students will be exposed to a variety of theoretical approaches, including formal models of interstate interactions (i.e. game theory), psychological explanations of foreign policy-making, and ideational or sociological approaches to understanding the international system. 


The primary text will be Patrick McDonald, Terrence Chapman, and Robert Moser, Opening the Global System: An Introduction to International Relations, Pearson books.  The modules for use in this class will be made available on Canvas by Professor Chapman

Assorted articles and news items made available through the library’s electronic subscriptions.

Course Requirements:

The course will consist of the following grades:

15% participation

25% midterm

25% final

20% expert reading assignment and paper (2-4 page analytical “thought” paper)

15% group debate


Terrence Chapman is an associate professor of Government.  He is also a distinguished scholar of the Strauss Center on International Law and Security a faculty affiliate of the Clements Center on International History and the European Studies Center.  During 2009-2010, Professor Chapman served as a visiting associate research scholar at the Niehaus Center for Globalization and Governance at Princeton University.  His book, Securing Approval: Domestic Politics and Multilateral Authorization for War, received the 2011-2012 American Political Science Association Conflict Processes Best Book Award.  His work appears in the Journal of Politics, the British Journal of Political ScienceInternational OrganizationInternational Studies Quarterly, the Journal of Conflict Resolution, the Journal of Theoretical PoliticsInternational Interactions, Perspectives on Politics and Political Science Quarterly.  His current work uses game theory, statistics, survey experiments, and case studies to examine diverse topics such as cross-national attitudes toward the International Criminal Court, financial market reactions to International Monetary Fund Lending, the politics of legal arbitration in foreign direct investment disputes, the effects of balanced budget rules in national constitutions, and the links between domestic bargaining over taxation and international diplomacy.  Professor Chapman also serves as an associate editor for International Studies Quarterly, the flagship journal of the International Studies Association.  Aside from his professional career, he stays occupied with two-year old twin daughters.

S S 302F • Hon Social Sci: Economics

42410 • Boyarchenko, Svetlana
Meets MW 2:00PM-3:30PM PAR 1
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Prerequisites:  Calculus (required) and Probability/Statistics (strongly recommended) 


Leadership and decision making go hand in hand. The goal of the course is to provide an introduction to the modern decision theory, in which mathematical methods of statistics and economics are integrated with findings from psychology. The course will offer tools for improving individual decision making, avoiding mistakes when taking calculated risks, and better understanding the decisions of others. We will start with the decision theory in case of the objective uncertainty, or risk, which deals with situations where we do not know the outcome of a given situation, but can accurately measure the odds. We will discuss risk attitude of individuals and then look at various examples, mainly provided by psychologists, in which the classical decision theory is violated. We will also discuss mistakes which people make when working with statistical data. Decision making is rather a process than a one-time event. Optimal timing of actions is an essential part of decision making. We will consider such examples as timing fixed size investment in a risky project, strategic default on corporate debt, optimal switching from one cash flow to another, and investment with and embedded option of default. The recent financial crisis happened partly due to inability of financial institutions to evaluate the riskiness of their investment decisions. In particular, this crisis has cast new attention on subjective uncertainty. The second part of the course will be dedicated to the subjective uncertainty, i.e., situations where we cannot infer all the information we need in order to set accurate odds statistically from existing data. We will discuss by which extent the mathematical tools of probability theory can be used in such situations. Single and multiple subjective priors models will be presented. The course will culminate with a flexible expected utility theory, which incorporates several well known models of expected utility.

Possible Readings:

The required text book is I. Gilboa, “Making Better Decisions: Decision Theory in Practice,” Wiley-Blackwell, 2011 

Also, required readings are Lecture notes posted in due time on Canvas Additional text books: 
• A useful complementary text for those who have more philosophical state of mind is M. Peterson, “An Introduction to Decision Theory,” Cambridge University Press, 2009 1 2 
• A useful complementary text for those who have more analytical state of mind is K. Binmore, “Rational Decisions,” Princeton University Press, 2009

Course Requirements:

Course Expectations: By the end of the course, students should be able to 
• understand the difference between objective and subjective uncertainty 
• solve basic decision problems that involve maximization of expected utility 
• solve basic problems of optimal timing of decisions 
• understand various behavioral biases in decision making process 

• regular problem sets that allow students to sharpen their analytical and quantitative skills; 
• in-class group and individual assignments; 
• one midterm exam (8th week of the semester) to test problem solving skills; 
• two writing assignments; 
• the final writing project. 

Two weeks after we finish the topic on optimal timing of decisions, each student has to submit two copies a research proposal (two A4 pages single spaced), where one of the real life timing problems is to be analyzed. Proposals may include, but are not limited to, real investment opportunities or insurance contracts, entry into a new market, capital accumulation, product or project innovations, default on household or sovereign debt, exit from a declining industry, quitting an old job and accepting a new offer, natural resource extraction. Each student is supposed to clearly formulate the nature of the problem and argue its importance, discuss which model of risk is appropriate to solve the problem and sketch the method of solution. One copy will be revised by me and returned to the student with comments. Another copy should be a blind copy; it will be assigned by me to an “anonymous referee” (another student in class), and the “referee” is expected to write a detailed report on the proposal (one A4 page single spaced) with comments and suggestions a week after (s)he gets the assignment. “Referee reports” will be given to students as additional feedback and will be evaluated by me. 

During the last week of the class, students will submit their final projects (five-six A4 pages single spaced), where they will present solution to the model they proposed earlier taking into account suggestions by their “referee” and my comments; moreover, students are supposed to evaluate at least one of the following modifications: (i) how conclusions of their model may change if one replaces risk with a subjective uncertainty model, or (ii) what happens in case of a multiple priors model, or (iii) what happens if one of the behavioral biases is present. All writing assignments will be judged by me both by content and writing skills. In addition to writing skills, the final project should also demonstrate strong quantitative and analytical skills. 

There will be no make-up date for the midterm. In case a student misses the exam for a documented illness, emergency, a religious observance or other university-approved reason, (s)he will be given an additional “referee report” to write. The final score will be the weighted sum of the following: 
• problem sets 10% (total) 
• class assignments 10% (total) 
• midterm 20% 
• research proposal 20% 
• referee report 20% 
• final project 20% 

I will use Plus/Minus grading for the final grade. “A” range will cover scores 80-100, “B” range will cover scores 60-80, “C” range will cover scores 40-60, “D” range will cover scores 20-40. Students who get a score less than 20 will be assigned “F”s.


I received an MSc in Mathematics (1978) and a PhD in Mathematics (1983) from the Rostov State University (now part of the South Federal University), Rostov-on-Don, Russia. I had a 10 year teaching experience, starting as an assistant professor and ending as an associate professor, at the Don State Technical University, Rostov-on-Don-Russia. I earned my MA degree in Economics (1997) from the Central European University, Budapest Hungary, and was admitted that year into a PhD program in Economics at the University of Pennsylvania, Philadelphia, U.S.A. Upon completion of my Ph.D. in Economics in 2001, I co-authored a novel approach to optimal stopping problems that works for wide classes of L´evy processes with regime shifts and random walks, and general payoff functions. This method is more efficient than the standard technique even in the case of Gaussian processes. It can be explained to different audiences, from undergraduate students to professionals, at an appropriate level of rigorousness. Furthermore, the method provides solutions to optimal stopping problems in a more meaningful form. To be more specific, in a paper published in the American Economic Review (2004), I formulated the record setting news principles that extend and generalize Bernanke’s bad news principle. 

I also co-authored the generalized Black-Scholes equation for a wide class of non-Gaussian processes and the KoBol model of asset prices, which is quite popular in finance, and subclass of which is known as the CGMY model. 

The results were published in two monographs and a number of papers in peer-reviewed journals, including American Economic Review, Games and Economic Behavior, Economic Theory, International Economic Review, and Journal of Mathematical Economics. My results were also presented at numerous international conferences . I have been recently asked to write a survey paper on the frontiers of Real Options by the Editor-in-Chief of The B.E. Journal of Theoretical Economics. 

While teaching at the Economics Department at UT Austin, I was awarded an NSF grant (2006, 24 months), College of Liberal Arts Research Fellowship Award 2016-17, Big XII Faculty Fellowship 2006-07, and Faculty Development Program Summer Research Assignment award, 2005 and 2002. 

My current research interests are efficient option pricing methods, optimal stopping problems under risk and uncertainty, stopping time games and experimentation and learning models. My non-academic interests include reading, classical music and traveling.


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