Syllabus

APPLIED ECONOMETRICS

Bonn Graduate School of Economics
WS 1999/2000

Prof. Dr. Klaus F. Zimmermann
Dr. Rainer Winkelmann
Dr. Rob Euwals

The course in Applied Econometrics at the Bonn Graduate School will be held from October 1999 to February 2000. After a general introduction into the methods used in econometrics, the course deals with the use of models for discrete and limited dependent variables, and models for panel data. The second half of the course will exist of case studies with respect to earnings.

1. Objectives

One objective of the course is to provide the students with a good understanding of econometric models for discrete and limited dependent variables, and models for panel data. These models are widely used in the empirical literature, and a good understanding of these models is crucial for the second objective of the course: to provide the students with the ability to evaluate recent empirical studies. The third objective of the course is to develop practical skills, which are necessary to perform independent research using microdata.

2. Prerequisites

You are expected to have a good knowledge in matrix algebra, probability and distribution theory, statistical inference, the classical multiple linear regression model (OLS) and the problems related to the assumptions of this model (multicollinearity, measurement error, heteroscedasticity, serial correlation), and the maximum likelihood method. To acquire this knowledge you should study:

· Greene, William H. (1997): Econometric Analysis, 3rd edition, London, Prentice Hall.
Chapters 2.1-2.3, 2.5, 2.9, 3.1-3.6, 4.1-4.5, 4.9, 5.5, 6.1-6.8, 8.1, 8.2, 8.4

You should try to do the respective exercises at the end of each chapter.

3. Examination

The examination of the course Applied Econometrics consists of three parts.

· An empirical assignment. After about two weeks you have to do an empirical analysis using a provided data set. You have about six weeks to hand in a report with results and interpretations.

· A presentation. Before the start of the case studies, you will be assigned to an empirical study from the literature (see reading list). In each session on the case studies, about 2 students will present an empirical study and lead a discussion by all participants. Your result will depend on your presentation and your participation in the discussions (also of the presentations by others).

· A written exam (closed book).

4. Time and place of course

Wintersemester: October 11, 1999 to February 11, 2000
Time: Friday, 9:15 - 12:15
Place: Conference Room (1.1), IZA, Schaumburg-Lippe-Str. 9

5. Content

Methods and models

1. Consistent estimation (OLS, IV)

2. Efficient estimation (ML)

3. Binary choice models (logit/probit)

4. Limited dependent variables models (tobit)

5. Panel data models (fixed/random effects)

Case studies with respect to earnings

6. Theory, choice of regressors, functional form and identification

7. Adjusted wage differentials and inequality decompositions

8. Sample selection

9. Endogeneity and causal effects

10. Panel and twin data

11. Aggregation

6. Reading list

1. Greene (1997) Econometric Analysis, ch. 6.1-6.8.

Schmidt and Zimmermann (1991) Work Characteristics, Firm Size and Wages, Review of Economics and Statistics, Vol. 73, pp. 705-710.

2. Greene (1997) Econometric Analysis, ch. 4.5.

3. Greene (1997) Econometric Analysis, ch. 19.1-19.4.

Amemiya (1981) Qualitative Response Models: A Survey, Journal of Economic Literature, Vol. 19, pp. 1483-1536.

4. Greene (1997) Econometric Analysis, ch. 20.3.

Amemiya (1984) Tobit Models: A Survey, Journal of Econometrics, Vol. 24, pp. 3-16.

5. Greene (1997) Econometric Analysis, ch. 14.1-14.4.

Chowdhury and Nickell (1985) Household Earnings in the United States: Another Look at Unionization, Schooling, Sickness, and Unemployment Using PSID Data, Journal of Labour Economics, Vol. 3, pp. 38-63.

6. Berndt, E.R. (1991) The practice of econometrics: Classic and contemporary, Chapter on earnings functions, Reading, Mass.: Addison-Wesley.

Griliches, Z. (1977) Estimating the Returns to Schooling: Some Econometric Problems, Econometrica, Vol. 45, 1-22.

Bloom, D.E., G. Grenier, and M. Gunderson (1995) The Changing Labor Market Position of Canadian Immigrants, Canadian Journal of Economics, Vol. 28, 987-1005.

Winkelmann, R. (1998) The Economic Benefits of Schooling in New Zealand: Comment and Update, New Zealand Economic Papers, 32, 187-195.

Winkelmann, R. (1999) The Estimation of Relative Wage Differentials Under Heteroskedasticity, mimeo.

7. Krueger, A. (1993) How Computers Have Changed the Wage Structure: Evidence from Microdata, 1984-1989, Quarterly Journal of Economics, 108(1), 33-60.

Oaxaca, R. (1979) Male-Female Wage Differentials in Urban Labor Markets, International Economic Review, 14(3), 693-709.

Blau, F. and L. Kahn (1992) The Gender Earnings Gap: Learning from International Comparisons, American Economic Review (P&P), 82, 533-538.

Freeman, R. (1993) How much has de-unionization contributed to the rise in male earnings inequality? In: S. Danziger and P. Gottschalk (eds.) Uneven tides: rising inequality in America, New York: Russell-Sage Foundation.

8. Heckman, J. (1979) Sample selection bias as a specification error, Econometrica, 47(1), 153-161.

Ermisch, J.F. and R. Wright (1994) Interpretation of Negative Sample Selection Effects in Wage Offer Equations, Applied Economics Letters, 1(11), 187-89.

Heckman, J. (1974) Shadow Prices, Market Wages, and Labor Supply, Econometrica, 42(4), 679-94.

Heckman, J. (1990) Varieties of selection bias, American Economic Review, Vol. 80 (P&P), 313-318.

9. Greene (1997) Econometric Analysis, ch. 22.4.4.

Moffitt, R. (1991) Program evaluation with non-experimental data, Evaluation Review, 15, 291-314.

Angrist, J.D. and A.B. Krueger (1991), Does Compulsory School Attendance Affect Schooling and Earnings? Quarterly Journal of Economics, 106(4), 979-1014.

Willis, R.J. and S. Rosen (1979) Education and Self-Selection, Journal of Political Economy, 87(5), 7-36.

10. Ashenfelter, O. and A. Krueger (1994) Estimates of the economic return to schooling from a new sample of twins, American Economic Review, 84(5): 1157-1173.

Hausman, J.E. and W.E. Taylor (1981) Panel Data and Unobservable Individual Effects, Econometrica, 49(6), 1377-98.

11. Lang, K.L. and P. Gottschalk (1996) The loss in efficiency from using grouped data to
estimate coefficients of group level variables, Computational Economics 9: 355-361.

Moulton, B.R. 1990, An illustration of a pitfall in estimating the effects of aggregate
variables on micro units, Review of Economics and Statistics 72, 334-338.

Kmenta, J. 1997 (reprint) Elements of econometrics, Chapter 9.2. Estimation from grouped data