Applied Empirical Microeconomics

Instructors

GRIFFEN, Andrew

Credits / Language / Semester

2Credits / English / Winter

Objectives/Overview

In this course, we will focus on building the economists' toolkit with a variety of microeconometric techniques to answer policy relevant, causal questions from observational data. Our strategy will be as follows. First, we will discuss different methods of microeconometric estimation and read papers that implement the methods. The idea will be to understand both the theory and the application of the technique. Second, I will assign the students empirical exercises in which I will create different data sets and ask the students to program a series of estimators for the parameters of interest.
The goal is for students to learn "hands on" how different econometric estimators work and to gain computer programming experience. Appropriate programming languages for the exercises might include Matlab, R or FORTRAN. Third, I will ask students to present one published paper from a reading list, which will require a very detailed reading of the paper and preparing for a class presentation. Dierent empirical microeconometric methods covered will include regression, IV, panel data methods, regression discontinuity designs, propensity score matching, and program evaluation estimators.
Hopefully a byproduct of the course will be research ideas for students. The grading will be based on the paper presentation (50 points) and the empirical exercises (50 points). There are no prerequistes for the course but the material is at the level of a masters course. However, advanced economics undergraduates are welcome to attend.
The lectures will be conducted in English. We will proceed paper by paper without any mandatory textbook and the course will have the avor of a grabbag of empirical methods and papers in empirical microeconomics.

Schedule

Topics
1 Causal models, path diagrams and regression analysis
2 Instrumental variables
3 Sample selection
4 Panel data estimators
5 Regression discontinuity
6 Propensity score matching and program evaluation
7 Evaluating active labor market programs

Teaching Methods

lecture,discussion,exercise

Grading

The grading will be based on the paper presentation (50 points) and the
empirical exercises (50 points).

Required Text

J. A Smith and P. E Todd. Does matching overcome lalonde's critique of nonexperimental estimators? Journal of econometrics, 125(1):305{353, 2005.
R.H. Dehejia and S. Wahba. Causal eects in nonexperimental studies: Reevaluating
the evaluation of training programs. Journal of the American statistical Association,
94(448):1053{1062, 1999.
J.J. Heckman. Sample selection bias as a specication error. Econometrica: Journal of the econometric society, pages 153{161, 1979.
R.J. LaLonde. Evaluating the econometric evaluations of training programs with experimental data. The American Economic Review, pages 604{620, 1986.
M.R. Rosenzweig and K.I. Wolpin. Natural" natural experiments" in economics. Journal of Economic Literature, pages 827{874, 2000.
J.A. Smith and P.E. Todd. Reconciling conicting evidence on the performance of propensity-score matching methods. The American Economic Review, 91(2):112{118, 2001.
D.L. Thistlethwaite and D.T. Campbell. Regression-discontinuity analysis: An alternative to the ex post facto experiment. Journal of Educational Psychology, 51(6):309, 1960.

Notes on Taking the Course

provision for taking course: None but Masters level material. Advanced undergraduates can attend if they can do the work.

Related Resources

Courses