Tsemin Lin
Associate Professor — Ph.D., University of Minnesota
Contact
 Email: tml@austin.utexas.edu
 Phone: 5122327248
 Office: BAT 4.144
 Campus Mail Code: A1800
Biography
An Associate Professor at the Department of Government at the University of Texas at Austin, Professor Lin has taught or visited at State University of New York at Stony Brook, Duke University, Michigan State University, and the Institute of Political Science at Academia Sinica. His teaching and research interests cover methodology, formal theory, and American and comparative political behavior.
He has published in American Journal of Political Science, American Political Science Review, Democratization, Journal of Democracy, Journal of Politics, Political Analysis, Political Research Quarterly, Public Choice, Social Science History, Taiwan Journal of Democracy, World Politics, as well as in edited volumes. His recent work includes "The Dynamics of the Partisan Gender Gap" (American Political Science Review, Vol. 98, No. 3, August 2004), "Neighborhood Influence on the Formation of National Identity in Taiwan: Spatial Regression with Disjoint Neighborhoods" (Political Research Quarterly, Vol. 59, No. 1, March 2006), "Markets and Politics: The 2000 Taiwanese Presidential Election" (in Melvin Hinich and William A. Barnett, eds., Topics in Analytical Political Economy. Amsterdam: Elsevier, 2007), and “The Structure of Taiwan’s Political Cleavages toward the 2004 Presidential Election: A Spatial Analysis” (Taiwan Journal of Democracy, Vol. 4, No. 2, December 2008). Conference papers include “The MinimumSum Point as a Solution Concept in Spatial Voting,” “Spatial Regression, Increasing Returns, and Regionalism,” “The Spatial Organization of Elections and the Cube Law,” and “Modeling Rebellion Intensity with a ZeroInflated Ordered Probit Model.”
Courses
GOV 355M • Human Behav As Rational Actn
38685 • Spring 2017
Meets TTH 11:00AM12:30PM SZB 286
Semester Spring 2017
GOV 355M – Title: Human Behavior as Rational Action
Writing Flag & Quantitative Reasoning Flag
Unique Days Time Bldg/Room Instructor
38685 TTH 11:0012:30pm BEN 1.126 LIN
Course Description
The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.
In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “FreeRider Problem” a contrast between rational man and irrational society. Selfserving behavior of individuals does not usually lead to collectively satisfactory results.
So this course is about the stories of the Prisoners, the Herdsmen, and the FreeRiders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story  a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.
Prerequisites
Upperdivision standing required.
6 semester hours of lowerdivision coursework in government.
Grading Policy
1. First Paper (68 pages): 25% 2. Second Paper (79 pages): 25%
3. Third Paper (810 pages): 30% 4. Presentation: 10%
5. Attendance: 10%
Texts
1. Thomas C. Schelling (1978), Micromotives and Macrobehavior (Norton).
2. Robert Axelrod (1984), The Evolution of Cooperation (Basic Books).
3. Dennis Chong (1991), Collective Action and the Civil Rights Movement (Chicago).
4. Elinor Ostrom (1990), Governing the Commons (Cambridge).
5. Howard Rheingold (2002), Smart Mobs: The Next Social Revolution (Basic Books).
GOV 385L • Panel/Multilevel Data Anly
38929 • Spring 2017
Meets T 3:30PM6:30PM BAT 5.102
The University of Texas at Austin
Government 385L
Panel and Multilevel Data Analysis
Spring 2017
TseMin Lin and Christopher Wlezien
Tuesdays 3:306:30
tml@austin.utexas.edu and Wlezien@austin.utexas.edu
Course Description
The course provides a detailed introduction to pooled time series cross section (TSCS) data analysis and multilevel data analysis. To begin with, it focuses on the techniques for analysis of various TSCS data sets, from those where the number of time series observations exceeds the number of cross sectional units to those where the number of cross sectional units exceeds the number of time serial observations. The course then turns to multilevel (ML) data, in which analysis explicitly models the effects of units within which observations are contained. In both parts of the course, there will be an emphasis both on both the logic of analysis and estimation, the latter of which will involve use of Stata software.
Course Format
All students are required to do a research paper. This should contribute to political science knowledge, not (necessarily) TSCS or ML methodology per se. The paper needs to be in the form of a journal article and ready for submission. Since this is a methods course, you are encouraged to choose a topic that relates to another class or even a paper that that could use a more sophisticated reanalysis. As it will be prepared for journal submission, the paper should be written for a general audience and need not delve too deeply into methodological issues.
Grades
The main assignment for this class is the preparation of an original research paper, about which more detailed information will be provided in class.
Performance in the class likely will be assessed as follows:
25% General class performance
75% Research paper
 5% Hypothesis
 20% Proposal
 50% Final Paper.
NOTE: Although we do not plan on having a final examination, because we think it distracts from the research paper, we reserve the right to add one if necessary—it depends entirely on student performance in class.
Readings
The course readings will include two books:
Hsiao, Cheng. 2014. Analysis of Panel Data, 3^{rd} Ed. Cambridge University Press.
D. A. Luke. 2004. Multilevel Modeling. Sage Publications.
Numerous articles and book chapters also will be required.
GOV 350K • Statistical Anly In Polit Sci
38450 • Fall 2016
Meets MWF 2:00PM3:00PM PHR 2.114
Semester Fall 2016
GOV 350K – Statistical Analysis in Political Science
Quantitative Reasoning Flag
Unique Days Time Bldg/Room Instructor
38450 MWF 2:003:00pm PHR 2.114 LIN
Course Description
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.
Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.
Prerequisites
None
Grading Policy
Homework Assignments (67 sets): 30%
InClass Midterm Exam: 30%
InClass Final Exam: 30%
Instructor Discretion (Attendance, Participation, etc.): 10%
Required Texts
* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)
Optional Texts
* S. B. Green and N. J. Salkind, 2013. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 7th Ed. Prentice Hall.
GOV 385L • Advanced Statistical Analysis
38680 • Fall 2016
Meets MW 5:00PM6:30PM BAT 1.104
(also listed as SDS 385)
Semester Fall 2016
GOV 385L – Title Advanced Statistical Analysis
SDS 385.14 – Title Maximum Likelihood Estimation
Substantial Writing Component: NO
Unique Days Time Bldg/Room Instructor
38680/56970 MW 5:006:30p BAT 1.104 LIN
Course Description
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis.
Prerequisites
Statistical Analysis in Political Science II or its equivalent
Grading Policy
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.
Required Texts:
* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference.
Michigan.
* J. S. Long and J. Freese. 2014. Regression Models for Categorical Dependent
Variables Using Stata. 3nd ed. Stata Press.
Recommended Texts:
* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.
* W. H. Greene. 2012. Econometric Analysis. 7th ed. Pearson & Prentice Hall.
* T. F. Liao. 1994. Interpreting Probability Models. Sage.
* A packet of journal articles and book chapters.
GOV 355M • Human Behav As Rational Actn
37940 • Spring 2016
Meets TTH 2:00PM3:30PM CLA 1.102
Semester Spring 2016
GOV 355M – Title: Human Behavior as Rational Action
Writing Flag & Quantitative Reasoning Flag
Unique Days Time Bldg/Room Instructor
37940 TTH 2:003:30pm CLA 1.102 LIN
Course Description
The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.
In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “FreeRider Problem” a contrast between rational man and irrational society. Selfserving behavior of individuals does not usually lead to collectively satisfactory results.
So this course is about the stories of the Prisoners, the Herdsmen, and the FreeRiders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story  a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.
Prerequisites
Upperdivision standing required.
6 semester hours of lowerdivision coursework in government.
Grading Policy
1. First Paper (68 pages): 25% 2. Second Paper (79 pages): 25%
3. Third Paper (810 pages): 30% 4. Presentation: 10%
5. Attendance: 10%
Texts
1. Thomas C. Schelling (1978), Micromotives and Macrobehavior (Norton).
2. Robert Axelrod (1984), The Evolution of Cooperation (Basic Books).
3. Dennis Chong (1991), Collective Action and the Civil Rights Movement (Chicago).
4. Elinor Ostrom (1990), Governing the Commons (Cambridge).
5. Howard Rheingold (2002), Smart Mobs: The Next Social Revolution (Basic Books).
GOV 380R • Math Methods For Pol Analysis
38110 • Spring 2016
Meets TTH 5:00PM6:30PM BAT 1.104
(also listed as SDS 381)
Semester
Spring 2016
GOV 380R – Title: Mathematical Methods for Political Analysis
Unique Days Time Bldg/Room Instructor
38110 TTH 5:00PM  6:30 PM BAT 1.104 LIN
Course Description
This course introduces the mathematical concepts and methods essential for multivariate statistical analysis and formal political theory. Mathematical topics include reviews of basic calculus and linear algebra, eigenvalues and eigenvectors, quadratic forms, vector and matrix differentiation, unconstrained optimization, constrained optimization, and difference and differential equations. Applications in multivariate statistical analysis include multiple regression, principal component analysis, factor analysis, etc., and their estimation in matrix form. Applications in formal political theory include equilibrium analysis and spatial analysis.
Course Requirements
Statistical Analysis in Political Science I&II (or, equivalently, Basic Statistics & Regression)
Grading Policy
1. Homework Assignments: 40% 2. Final Project: 60%
Texts
1. Alpha C. Chiang and Kevin Wainwright. 2004. Fundamental Methods of Mathematical Economics, 4th ed. McGrawHill/Irwin.
2. J. Douglas Carroll and Paul E. Green. 1997. Mathematical Tools for Applied Multivariate Analysis. Revised ed. Academic Press.
3. (Optional) Jeff Gill. 2006. Essential Mathematics for Political and Social Research. Cambridge.
4. (Optional) John Fox. 2009. A Mathematical Primer for Social Statistics. Sage.
5. (Optional) Will H. Moore and David A. Siegel. 2013. A Mathematics Course for Political & Social Research. Princeton.
GOV 350K • Statistical Anly In Polit Sci
37744 • Fall 2015
Meets TTH 2:00PM3:30PM BUR 136
Semester Fall 2015
GOV 350K – Statistical Analysis in Political Science
Quantitative Reasoning Flag
Unique Days Time Bldg/Room Instructor
37744 LIN
Course Description
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.
Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.
Prerequisites
None
Grading Policy
Homework Assignments (67 sets): 30%
InClass Midterm Exam: 30%
InClass Final Exam: 30%
Instructor Discretion (Attendance, Participation, etc.): 10%
Required Texts
* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)
Optional Texts
* S. B. Green and N. J. Salkind, 2013. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 7th Ed. Prentice Hall.
GOV 385L • Advanced Statistical Analysis
37945 • Fall 2015
Meets TTH 5:00PM6:30PM MEZ 4.144
(also listed as SDS 385)
Semester Fall 2015
GOV 385L – Title Advanced Statistical Analysis
SDS 385.14 – Title Maximum Likelihood Estimation
Substantial Writing Component: NO
Unique Days Time Bldg/Room Instructor
37945 (56290) TTH 5:006:30p MEZ 1.204 LIN
Course Description
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis.
Prerequisites
Statistical Analysis in Political Science II or its equivalent
Grading Policy
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.
Required Texts:
* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference.
Michigan.
* J. S. Long and J. Freese. 2014. Regression Models for Categorical Dependent
Variables Using Stata. 3nd ed. Stata Press.
Recommended Texts:
* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.
* W. H. Greene. 2012. Econometric Analysis. 7th ed. Pearson & Prentice Hall.
* T. F. Liao. 1994. Interpreting Probability Models. Sage.
* P. H. Pollock, III. 2010. A STATA Companion to Political Analysis. 2nd ed. CQ Press.
* A packet of journal articles and book chapters.
GOV 350K • Statistical Anly In Polit Sci
37950 • Spring 2015
Meets TTH 11:00AM12:30PM BUR 112
Quantitative Reasoning Flag
Unique Days Time Bldg/Room Instructor
37950 TTH 11:00am12:30pm BUR 112 LIN
Course Description
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.
Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.
Prerequisites
None
Grading Policy
Homework Assignments (67 sets): 30%
InClass Midterm Exam: 30%
InClass Final Exam: 30%
Instructor Discretion (Attendance, Participation, etc.): 10%
Required Texts
* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)
Optional Texts
* S. B. Green and N. J. Salkind, 2011. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 6th Ed. Prentice Hall.
GOV 355M • Human Behav As Rational Actn
37990 • Spring 2015
Meets TTH 3:30PM5:00PM MEZ 1.216
Writing Flag & Quantitative Reasoning Flag
Unique Days Time Bldg/Room Instructor
37990 TTH 3:305:00pm MEZ 1.216 LIN
Course Description
The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.
In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “FreeRider Problem” a contrast between rational man and irrational society. Selfserving behavior of individuals does not usually lead to collectively satisfactory results.
So this course is about the stories of the Prisoners, the Herdsmen, and the FreeRiders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story  a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.
Prerequisites
Upperdivision standing required.
6 semester hours of lowerdivision coursework in government.
Grading Policy
1. First Paper (68 pages): 25% 2. Second Paper (79 pages): 25%
3. Third Paper (810 pages): 30% 4. Presentation: 10%
5. Attendance: 10%
Texts
1. Thomas C. Schelling (1978), Micromotives and Macrobehavior (Norton).
2. Robert Axelrod (1984), The Evolution of Cooperation (Basic Books).
3. Dennis Chong (1991), Collective Action and the Civil Rights Movement (Chicago).
4. Elinor Ostrom (1990), Governing the Commons (Cambridge).
5. Howard Rheingold (2002), Smart Mobs: The Next Social Revolution (Basic Books).
6. Clay Shirky (2009), Here Comes Everybody (Penguin Books).
GOV 385L • Advanced Statistical Analysis
39080 • Fall 2014
Meets TTH 5:00PM6:30PM MEZ 1.204
(also listed as SDS 385)
Semester Fall 2014
GOV 385L – Title Advanced Statistical Analysis
Substantial Writing Component: NO
Course Description
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis.
Prerequisites
Statistical Analysis in Political Science II or its equivalent
Grading Policy
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal (510 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.
Required Texts:
* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.
* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference.
Michigan.
* T. F. Liao. 1994. Interpreting Probability Models. Sage.
* A packet of journal articles and book chapters.
Recommended Texts:
* W. H. Greene. 2012. Econometric Analysis. 7th ed. Pearson & Prentice Hall.
* J. S. Long and J. Freese. 2006. Regression Models for Categorical Dependent
Variables Using Stata. 2nd ed. Stata Press.
GOV 385L • TimeSeries Analysis
39082 • Fall 2014
Meets M 3:30PM6:30PM GAR 1.134
Writing Flag: NO
Course Description
This course is designed to examine the formal and statistical structure of techniques useful for analyzing dynamic processes. Subtopics include difference equations; stationary ARMA processes; persistent and/or nonstationary processes including integrated, fractionally integrated, and nearintegrated processes; the estimation and forecasting of time series single equation regression; cointegration and error correction; Granger causality and vector autoregression; timevarying parameter regression, and timeseries crosssection models.
Prerequisites
Statistical Analysis in Political Science II or its equivalent
Grading Policy
 Homework Assignments (20%)
 Project/Paper Proposal (20%)
 Final Project/Paper (60%)
Required Texts:
 Walter Enders. 2009. Applied Econometric Time Series, 3e. Wiley.
 Patrick T. Brandt and John T. Williams. 2007. Multiple Time Series. Sage.
 A packet of journal articles and book chapters.
Recommended Texts
 C. Chatfield. 1996. The Analysis of Time Series: An Introduction, 5e. Chapman and Hall.
 Samuel Goldberg. 2010. Introduction to Difference Equations: With Illustrative Examples from Economics, Psychology, and Sociology. Dover.
 John M. Gottman. 1981. TimeSeries Analysis: A Comprehensive Introduction for Social Scientists. Cambridge
 Damodar N. Gujarati. 2003. Basic Econometrics, 4e. McGrawHill & Irwin.
 G. S. Maddala and InMoo Kim. 1998. Unit Roots, Cointegration, and Structural Change. Cambridge.
 Richard McCleary and Richard A. Hay, Jr. 1980. Applied Time Series Analysis for the Social Sciences. Sage.
 Robert S. Pindyck and Daniel L. Rubinfeld. 1997. Econometric Models and Economic Forecasts, 4e. McGrawHill.
GOV 355M • Human Behav As Rational Actn
39210 • Spring 2014
Meets TTH 3:30PM5:00PM MEZ 1.216
Course Description
The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.
In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “FreeRider Problem” a contrast between rational man and irrational society. Selfserving behavior of individuals does not usually lead to collectively satisfactory results.
So this course is about the stories of the Prisoners, the Herdsmen, and the FreeRiders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story  a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.
Prerequisites
Upperdivision standing required.
6 semester hours of lowerdivision coursework in government.
Grading Policy
1. First Paper (68 pages): 25% 2. Second Paper (79 pages): 25%
3. Third Paper (810 pages): 30% 4. Presentation: 10%
5. Attendance: 10%
Texts
1. Thomas C. Schelling (1978), Micromotives and Macrobehavior (Norton).
2. Robert Axelrod (1984), The Evolution of Cooperation (Basic Books).
3. Dennis Chong (1991), Collective Action and the Civil Rights Movement (Chicago).
4. Elinor Ostrom (1990), Governing the Commons (Cambridge).
5. Howard Rheingold (2002), Smart Mobs: The Next Social Revolution (Basic Books).
6. Clay Shirky (2009), Here Comes Everybody (Penguin Books).
FLAG: Writing
GOV 380R • Math Methods For Pol Analysis
39405 • Spring 2014
Meets TTH 12:30PM2:00PM BAT 1.104
Course Description
This course introduces the mathematical concepts and methods essential for multivariate statistical analysis and formal political theory. Mathematical topics include reviews of basic calculus and linear algebra, eigenvalues and eigenvectors, quadratic forms, vector and matrix differentiation, unconstrained optimization, constrained optimization, and difference and differential equations. Applications in multivariate statistical analysis include multiple regression, principal component analysis, factor analysis, etc., and their estimation in matrix form. Applications in formal political theory include equilibrium analysis, dynamic analysis, and spatial analysis.
Course Requirements
Statistical Analysis in Political Science I
Grading Policy
1. Homework Assignments: 40% 2. Final Project: 60%
Texts
1. Alpha C. Chiang and Kevin Wainwright. 2004. Fundamental Methods of Mathematical Economics, 4th ed. McGrawHill/Irwin.
2. J. Douglas Carroll and Paul E. Green. 1997. Mathematical Tools for Applied Multivariate Analysis. Revised ed. Academic Press.
3. (Optional) Jeff Gill. 2006. Essential Mathematics for Political and Social Research. Cambridge.
4. (Optional) Will H. Moore and David A. Siegel. 2013. A Mathematics Course for Political & Social Research. Princeton.
4. (Optional) John Fox. 2009. A Mathematical Primer for Social Statistics. Sage.
GOV 350K • Statistical Anly In Polit Sci
39195 • Fall 2013
Meets MWF 1:00PM2:00PM BUR 208
Prerequisites
None
Course Description
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.
Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.
Grading Policy
Homework Assignments (67 sets): 30%
InClass Midterm Exam: 30%
InClass Final Exam: 30%
Instructor Discretion (Attendance, Participation, etc.): 10%
Required Texts
* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)
Optional Texts
* S. B. Green and N. J. Salkind, 2011. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 6th Ed. Prentice Hall.
GOV 385L • Advanced Statistical Analysis
39390 • Fall 2013
Meets TTH 5:00PM6:30PM MEZ 1.204
(also listed as SSC 385)
Prerequisites
Statistical Analysis in Political Science II or its equivalent
Course Description
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis
Grading Policy
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal (510 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.
Required Texts
* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.
* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference.
Michigan.
* T. F. Liao. 1994. Interpreting Probability Models. Sage.
* A packet of journal articles and book chapters.
Recommended Texts
* W. H. Greene. 2012. Econometric Analysis. 7th ed. Pearson & Prentice Hall.
* J. S. Long and J. Freese. 2006. Regression Models for Categorical Dependent
Variables Using Stata. 2nd ed. Stata Press.
GOV 355M • Human Behav As Rational Actn
38865 • Spring 2013
Meets TTH 2:00PM3:30PM MEZ 1.216
Prerequisites
Upperdivision standing required.
6 semester hours of lowerdivision coursework in government.
Course Description
The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.
In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “FreeRider Problem” a contrast between rational man and irrational society. Selfserving behavior of individuals does not usually lead to collectively satisfactory results.
So this course is about the stories of the Prisoners, the Herdsmen, and the FreeRiders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story  a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.
Grading Policy
1. First Paper (68 pages): 25% 2. Second Paper (79 pages): 25%
3. Third Paper (810 pages): 30% 4. Presentation: 10%
5. Attendance: 10%
Texts
1. Thomas C. Schelling (1978), Micromotives and Macrobehavior (Norton).
2. Robert Axelrod (1984), The Evolution of Cooperation (Basic Books).
3. Dennis Chong (1991), Collective Action and the Civil Rights Movement (Chicago).
4. Elinor Ostrom (1990), Governing the Commons (Cambridge).
5. Howard Rheingold (2002), Smart Mobs: The Next Social Revolution (Basic Books).
6. Clay Shirky (2009), Here Comes Everybody (Penguin Books).
GOV 385L • TimeSeries Analysis
39105 • Spring 2013
Meets MW 12:30PM2:00PM BAT 1.104
Prerequisites
Statistical Analysis in Political Science II or its equivalent
Course Description
This course is designed to examine the formal and statistical structure of techniques useful for analyzing dynamic processes. Subtopics include difference equations; stationary ARMA processes; persistent and/or nonstationary processes including integrated, fractionally integrated, and nearintegrated processes; the estimation and forecasting of time series single equation regression; cointegration and error correction; Granger causality and vector autoregression; timevarying parameter regression, and timeseries crosssection models.
Grading Policy
 Homework Assignments (20%)
 Project/Paper Proposal (20%)
 Final Project/Paper (60%)
Required Texts:
 Walter Enders. 2009. Applied Econometric Time Series, 3e. Wiley.
 Patrick T. Brandt and John T. Williams. 2007. Multiple Time Series. Sage.
 A packet of journal articles and book chapters.
Recommended Texts
 C. Chatfield. 1996. The Analysis of Time Series: An Introduction, 5e. Chapman and Hall.
 Samuel Goldberg. 2010. Introduction to Difference Equations: With Illustrative Examples from Economics, Psychology, and Sociology. Dover.
 John M. Gottman. 1981. TimeSeries Analysis: A Comprehensive Introduction for Social Scientists. Cambridge
 Damodar N. Gujarati. 2003. Basic Econometrics, 4e. McGrawHill & Irwin.
 G. S. Maddala and InMoo Kim. 1998. Unit Roots, Cointegration, and Structural Change. Cambridge.
 Richard McCleary and Richard A. Hay, Jr. 1980. Applied Time Series Analysis for the Social Sciences. Sage.
 Robert S. Pindyck and Daniel L. Rubinfeld. 1997. Econometric Models and Economic Forecasts, 4e. McGrawHill.
GOV 350K • Statistical Anly In Polit Sci
38705 • Fall 2012
Meets MW 3:00PM4:30PM BUR 208
Course Description
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.
Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.
Grading Policy
Homework Assignments (67 sets): 30%
InClass Midterm Exam: 30%
InClass Final Exam: 30%
Instructor Discretion (Attendance, Participation, etc.): 10%
Required Texts
* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)
Optional Texts
* S. B. Green and N. J. Salkind, 2011. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 6th Ed. Prentice Hall.
GOV 385L • Advanced Statistical Analysis
38925 • Fall 2012
Meets TTH 12:30PM2:00PM MEZ 2.120
(also listed as SSC 385)
Prerequisites
Statistical Analysis in Political Science II or its equivalent.
Course Description
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis.
Grading Policy
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal (510 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.
Required Texts
* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.
* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference.
Michigan.
* T. F. Liao. 1994. Interpreting Probability Models. Sage.
* A packet of journal articles and book chapters.
Strongly Recommended Texts
* W. H. Greene. 2012. Econometric Analysis. 7th ed. Pearson & Prentice Hall.
* J. S. Long and J. Freese. 2006. Regression Models for Categorical Dependent
Variables Using Stata. 2nd ed. Stata Press.
GOV 355M • Human Behav As Rational Actn
38710 • Spring 2012
Meets MWF 1:00PM2:00PM PAR 201
Course Description
The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.
In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “FreeRider Problem” a contrast between rational man and irrational society. Selfserving behavior of individuals does not usually lead to collectively satisfactory results.
So this course is about the stories of the Prisoners, the Herdsmen, and the FreeRiders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story  a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.
Course Requirements
Upperdivision standing required. 6 semester hours of lowerdivision coursework in government.
Grading Policy
1. First Paper (68 pages): 25% 2. Second Paper (79 pages): 25%3. Third Paper (810 pages): 30% 4. Presentation: 10%5. Attendance: 10%
Texts
1. Thomas C. Schelling (1978), Micromotives and Macrobehavior (Norton).
2. Robert Axelrod (1984), The Evolution of Cooperation (Basic Books).
3. Dennis Chong (1991), Collective Action and the Civil Rights Movement (Chicago).
4. Elinor Ostrom (1990), Governing the Commons (Cambridge).
5. Howard Rheingold (2002), Smart Mobs: The Next Social Revolution (Basic Books)
GOV 380R • Math Methods For Pol Analysis
38895 • Spring 2012
Meets MW 11:00AM12:30PM BAT 1.104
(also listed as SSC 384)
Course Description
This course introduces the mathematical concepts and methods essential for multivariate statistical analysis and formal political theory. Mathematical topics include reviews of basic calculus and linear algebra, eigenvalues and eigenvectors, quadratic forms, vector and matrix differentiation, unconstrained optimization, constrained optimization, and difference and differential equations. Applications in multivariate statistical analysis include multiple regression, principal component analysis, factor analysis, etc., and their estimation in matrix form. Applications in formal political theory include equilibrium analysis, dynamic analysis, and spatial analysis.
Course Requirements
None
Grading Policy
1. Homework Assignments: 40%
2. Final Project: 60%
Texts
1. Alpha C. Chiang and Kevin Wainwright. 2004. Fundamental Methods of Mathematical Economics, 4th ed. McGrawHill/Irwin.
2. J. Douglas Carroll and Paul E. Green. 1997. Mathematical Tools for Applied Multivariate Analysis. Revised ed. Academic Press.
3. (Optional) Jeff Gill. 2006. Essential Mathematics for Political and Social Research. Cambridge.
4. (Optional) John Fox. 2009. A Mathematical Primer for Social Statistics. Sage.
GOV 350K • Statistical Anly In Polit Sci
38725 • Fall 2011
Meets MW 3:30PM5:00PM BUR 208
Course Description
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.
Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.
Grading Policy
Homework Assignments (67 sets): 30% InClass Midterm Exam: 30% InClass Final Exam: 30%Instructor Discretion (Attendance, Participation, etc.): 10%
Required Texts
* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)
Optional
* S. B. Green and N. J. Salkind, 2011. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 6th Ed. Prentice Hall.
GOV 385L • Advanced Statistical Analysis
38935 • Fall 2011
Meets TTH 11:00AM12:30PM BAT 1.104
Course Description
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, models for timeseries crosssection data, and models for hierarchical data. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MAPLE or MATHEMATICA for symbolic algebra.
Course Requirements
Statistical Analysis in Political Science II or its equivalent
Grading Policy
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By Week 8, you should turn in a paper proposal (510 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.
Required Texts:
* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference. Michigan.* T. F. Liao. 1994. Interpreting Probability Models. Sage.* A packet of journal articles and book chapters.
Strongly Recommended:
* W. H. Greene. 2012. Econometric Analysis. 7th ed. Pearson & Prentice Hall.* J. S. Long and J. Freese. 2006. Regression Models for Categorical Dependent Variables Using Stata. 2nd ed. Stata Press.
GOV 350K • Statistical Anly In Polit Sci
38920 • Spring 2011
Meets MW 3:30PM5:00PM PAR 201
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statisticalcourses you may have taken, the emphasis here will be on applications in political science. The objective ofthis course is to help students acquire the literacy for understanding political science literatures based on thescientific approach, as well as to prepare interested students for more advanced methods courses.Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution,point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, correlation,and simple regression. Computing will be an integral part of this course. You will use SPSS to analyze datafrom Gallup Survey, General Social Survey, and/or National Election Study in homework assignments. Inparticular, you will be asked to replicate results reported in journal articles and book chapters. You are alsoencouraged to develop and work out your own research problems.
GOV 355M • Human Behav As Rational Actn
38935 • Spring 2011
Meets MWF 1:00PM2:00PM PAR 201
The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “FreeRider Problem” a contrast between rational man and irrational society. Selfserving behavior of individuals does not usually lead to collectively satisfactory results.So this course is about the stories of the Prisoners, the Herdsmen, and the FreeRiders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story  a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.Course RequirementsUpperdivision standing required.6 semester hours of lowerdivision coursework in government.
GOV 385L • Advanced Statistical Analysis
38810 • Fall 2010
Meets TTH 11:00AM12:30PM MEZ 2.120
Course Description
In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, models for timeseries crosssection data, and models for hierarchical data. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MAPLE for symbolic algebra.
Course Requirements
Statistical Analysis in Political Science II or its equivalent
Grading Policy
You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By Week 8, you should turn in a paper proposal (510 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.
Required Texts:
* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.
* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference.
Michigan.
* T. F. Liao. 1994. Interpreting Probability Models. Sage.
* A packet of journal articles and book chapters.
Strongly Recommended:
* J. M. BoxSteffensmeier and B. S. Jones. 2004. Event History Analysis. Cambridge.
* W. H. Greene. 2008. Econometric Analysis. 6th ed. Pearson & Prentice Hall.
* J. S. Long and J. Freese. 2006. Regression Models for Categorical Dependent
Variables Using Stata. 2nd ed. Stata Press.
GOV 391J • Statistical Anly In Pol Sci I
38870 • Fall 2010
Meets TTH 2:00PM3:30PM BUR 124
Course Description
This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.
Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, correlation, and simple regression. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.
Course Requirements
Grading Policy
Homework Assignments (57 sets): 30%
InClass Midterm Exam: 30%
InClass Final Exam: 30%
Instructor Discretion (Attendance, Participation, etc.): 10%
Required Texts
* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)
Optional
* S. B. Green and N. J. Salkind, 2008. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 5th Ed. Prentice Hall.
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