Econometrics 2. Course Syllabus

CEU, MA in Economics, 1^st year core course

Winter 2011

Instructor: Gabor Kezdi	Teaching Assistant: Peter Farkas
kezdig@ceu.hu Office: 404, Nador 11, Economics Department Office hours: Monday 4 to 5 PM	farkas_peter@ceu-budapest.edu Office: 416/B, Nador 11, Economics Dept. Office hours: TBA

Course prerequisite: Econometrics 1 (CEU MA 1^st)

Credits: 5 CEU credits (10 ECTS credits)

Course website: http://www.personal.ceu.hu/staff/Gabor_Kezdi/Econometrics-2/econometrics-2.htm

Main text: Wooldridge, Jeffrey M., Introductory Econometrics, 2^nd ed. Thompson, 2003.

Goals. Econometrics 2 provides the basic tools of applied econometric analysis. The course is based on regression analysis (covered in Econometrics 1), and it gives a thorough introduction to the problem of endogeneity with possible treatments, time series regressions, linear panel models, and nonlinear probability and censored-outcomes models.

Learning outcomes. Successful completion of the course enables students to

Understand how econometric methods are used to estimate causal relationships from observational data.

Possess a critical understanding of identification and estimation problems in economics and other social sciences.

Formulate simple research questions and carry out independent analyses in order to answer those.

Understand and evaluate the identification and estimation strategy of simpler papers, whether academic publications or applied works

Prove consistency or find asymptotic bias of estimators.

Understand the logic of sampling variance and distribution of estimators, and carry out simple hypothesis tests in linear models.

Understand the role of stationarity and know various deviations from it.

Understand the properties of specific time-series.

Use econometric software in simple applications, estimate the models covered in the course, and interpret their results.

Course outline

Week 1	Review of regression. Carrying out an empirical project. Term paper topic. Chapter 19. Specification and data problems. Proxy variables, measurement error. Chapter 9.
Week 2	Continue with proxy variables and measurement error, Chapter 9. A refresher to time-series regression. Chapter 10.
Week 3	Specific univariate series. Chapter 11.
Week 4	Regression on time-series data. Chapter 12.
Week 5	Continue with regression on time-series data. Chapter 12.
Week 6	Panel data methods: Pooled cross-sections, difference in differences Chapter 13
Week 7	Panel data methods: Fixed effects and random effects Chapter 14
Week 8	Instrumental variables: Identification. Chapter 15
Week 9	Instrumental variables: Estimation. Weak instruments. Chapter 15
Week 10	Probability models Chapter 17.1
Week 11	Corner solution and censored models Chapter 17.2, 17.4.
Week 12	Summary and review

Assessment

Grading

10% from problem sets

25% from term paper

65% from final exam

Formative assessment

Individual consultations about the term paper

Term paper

An individual term paper is required at the end of the course. The paper should consist of a simple empirical analysis, and it should be at most 10 pages long (incl. tables and figures), text 1.5 or double spaced, font size 11 or larger. There will be two due dates:

(1) One for handing in for review at the Center for Academic Writing (DATE TBA), and

(2) One for handing in to me (DATE TBA). I will need the paper both electronically and in a hard copy. File name should be of this format: Lastname_Firstname_term_paper.pdf

Formal requirements will be strictly enforced: no paper will be accepted that does not meet all requirements.

Find a research question that interests you. See a list with suggested topics below. The good paper asks a question of the form “What is the effect of X on Y?” Questions like “The determinants of Y” or “Testing the … model” are not preferred in this course.

The term paper may use any econometric method we studied in class, except for time-series analysis. Use the appropriate method: it is not always the most complicated one (a simple OLS may be your best choice). You should be clear about the research question, its motivation (why you think it is interesting – but literature review is not necessary), what data you use and why. You should think about what assumptions your estimation technique requires (functional form, exogeneity, etc.), and whether they are likely to be satisfied in your data. If not, try to sign the bias and think about what you would need for better estimation.

Everyone should consult me about the topic and the data (and possibly about the first results).

A few topics from the past years (in random order)

• The effect of film being a sequel on its box office revenues
• The effect of having a child on smoking
• Does marriage affect the weight of married people?
• The effect of a film’s budget on its chances of winning a Best Picture Academy Award
• Does smoking ban in bars have an effect on smoking habits?
• To what extent is artist popularity reflected in auction prices?
• The effect of age on religiosity and church attendance
• The effect of parental effort on school performance of Roma and non-Roma children
• Does popularity of football affect the performance of the national team?
• The worldwide price elasticity of cigarette demand
• Do heavy metal bands price their concert tickets to location?
• The nonlinear effect of wine consumption on wages
• Social network Capital: How much do we benefit from our friends and relatives?
• Does foreign ownership improve companies’ export performance?
• The impact of female participation in the political elite on state aggression
• The effect of corporate income tax on foreign direct investment
• Estimating the effect of increasing drinking water access on the life expectancy
• Do more educated Americans save more? Why?
• On the impact of psychological motivation on unemployment
• Does capital punishment have a deterrent effect?
• Estimating the causal effect of family income on individuals’ health
• The effect of distance to motorway on FDI
• The effect of minimum wage on unemployment
• Border effect on price differentials in central eastern Europe
• Does “getting older” mean “getting alone”?
• Does unemployment give birth to more children?
• The effect of poverty on infant mortality rate
• Racial wage discrimination in the nba revisited
• The effect of unions on earnings
• Does countries’ wealth affect their performance in football?
• The effect of work time on the time devoted to sleep
• The influence of education on tobacco expenditure decisions
• Small children and the incidence of male overtime