MICROECONOMETRICS
Manuel Arellano
CEMFI,
2009-2010
Lectures: Mon. 12:00-13:30, Wed. 10:00-11:30.
Exercise classes: Wed. 12:00-13:30. Conducted by Laura
Crespo (crespo@cemfi.es)
Workshop (Almuerzos):
13:30-15:30 on weeks 5 (Wed.), 7 (Wed.), and 9 (Wed.).
Grades will be based on class exercises (10%), presentation
(20%), and final exam (70%).
Problem Sets: GMM,
Panel
Data, Nonlinear
Models
M. Arellano, Panel Data Econometrics, Oxford
University Press, 2003.
C. Cameron and P. Trivedi, Microeconometrics,
Cambridge University Press, 2005.
C. Cameron and P. Trivedi, Microeconometrics Using
Stata, Stata Press, 2009.
J. Wooldridge, Econometric Analysis of Cross
Section and Panel Data, MIT Press, 2002.
1. Generalized method of moments
1.1 Conditional
expectations, linear predictors, and instrumental variables.
1.2 Generalized
method of moments: General formulation.
1.3 Examples:
Simultaneous equations and covariance structures.
1.4 Tests
of overidentifying restrictions.
1.5 GMM
with nonsmooth moments.
2. Optimal instruments in
conditional models
2.1 Introduction:
Linear regression.
2.2 Nonlinear
regression.
2.3 Nonlinear
structural equation.
2.4 Multivariate
regression.
2.5 Nonlinear
simultaneous equations.
Arellano, Appendices A and B.
Cameron and Trivedi, Chapters 4, 5, 6.
Wooldridge, Chapter 14.
Hansen, L. P. (1982): “Large Sample Properties of
Generalized Method of Moments Estimators”, Econometrica, 49, 1029-1054.
Newey, W. and D. McFadden (1995): “Large Sample
Estimation and Hypothesis Testing”, in R. Engle and D. McFadden (eds.), Handbook
of Econometrics, Vol. 4, Elsevier.
Sargan, J. D. (1958): “The Estimation of Economic
Relationships Using Instrumental Variables”, Econometrica, 26, 393-415.
3. Static models
3.1 Unobserved
heterogeneity: within-group estimation.
3.2 Error
components.
3.3 Specification
tests.
3.4 Error
in variables.
4. Dynamic models
4.1 Covariance
structures with error components.
4.2 Autoregressive
models with individual effects.
4.3 Strict
exogeneity and predetermined variables.
4.4 Partial
adjustment models.
Arellano, Chapters 2-4 (static models) and 5-8
(dynamic models).
Arellano, M. and S. Bond (1991): “Some Tests of
Specification for Panel Data: Monte Carlo Evidence and an Application to
Employment Equations”, Review of Economic Studies, 58, 277-297.
Arellano, M. and O. Bover (1995): “Another Look at the
Instrumental-Variable Estimation of Error-Components Models”, Journal of Econometrics, 68, 29-51.
Chamberlain, G. (1984): “Panel Data”, in Z. Griliches
and M. D. Intriligator (eds.), Handbook of Econometrics, Vol. 2,
Elsevier Science.
Griliches, Z. and J. A. Hausman (1986): “Error in
Variables in Panel Data”, Journal of Econometrics, 31, 93-118.
Hausman, J. A. and W. E. Taylor (1981): “Panel Data
and Unobservable Individual Effects”, Econometrica,
49, 1377-1398.
Hsiao, C. (2003): Analysis
of Panel Data, Cambridge University Press, Second Edition.
5. Discrete choice
5.1 Binary
models.
5.2
Multinomial
models.
5.3
Endogenous
explanatory variables.
5.4 Binary
models for panel data.
Cameron and Trivedi, Chapters 14, 15.
Wooldridge, Chapter 15.
Amemiya, T. (1985): Advanced Econometrics,
Blackwell, Chapter 9.
Arellano, M. and B. Honoré (2001): “Panel Data Models.
Some Recent Developments”, in J. Heckman and E. Leamer (eds.), Handbook of
Econometrics, Vol. 5, Ch. 53.
Blundell, R. and J. L.
Powell, (2004): “Endogeneity in Semiparametric Binary Response Models”, Review
of Economic Studies, 71, 655-679.
Chamberlain, G. (1980): “Analysis of Covariance with
Qualitative Data”, Review of Economic Studies, 47, 225-238.
McFadden, D. (1981): “Econometric Models of
Probabilistic Choice”, in C. Manski and D. McFadden (eds), Structural Analysis
of Discrete Data with Econometric Applications, MIT Press, Ch. 5.
6. Duration models
8.1 The
hazard function. Proportional hazard models.
8.2 Unobserved
heterogeneity versus state dependence.
8.3 Discrete
time duration models.
8.4 Illustration:
Unemployment duration.
Cameron and Trivedi, Chapters 17, 18, 19.
Wooldridge, Chapter 19.
Bover, O., M. Arellano and S. Bentolila (2002):
“Unemployment Duration, Benefit Duration, and the Business Cycle”, The
Economic Journal, 112, 223-265.
Lancaster, T. (1979): “Econometric Models for the
Duration of Unemployment”, Econometrica, 47, 939-956.
Lancaster, T. (1990): The Econometric Analysis of
Transition Data, Cambridge.
Meyer, B. (1990): “Unemployment Insurance and
Unemployment Spells”, Econometrica, 58, 757-782.
Van den Berg, G. (2001): “Duration Models: Specification,
Identification and Multiple Durations”, in Heckman and Leamer (eds.), Handbook
of Econometrics, Vol. 5, Ch. 55.
7. Quantile methods
7.1 Medians,
quantiles and optimal predictors.
7.2 Quantile
regression.
7.3 Asymptotic
results.
7.4 Endogenous
quantile methods.
Amemiya, T. (1985): Advanced Econometrics,
Blackwell, 4.6.
Chamberlain, G. (1994): “Quantile Regression,
Censoring, and the Structure of Wages”, in C.A. Sims (ed.), Advances in
Econometrics, Sixth World Congress, vol. 1, Cambridge.
Chernozhukov V. and C. Hansen (2006): “Instrumental
Quantile Regression Inference for Structural and Treatment Effect Models,” Journal
of Econometrics, 132, 491-525.
Koenker, R. and
G. Basset (1978): “Regression Quantiles”, Econometrica, 46, 33-50.
Koenker, R. (2005): Quantile Regression,
Cambridge University Press.
8. Models with censored variables
6.1 Tobit
and truncated models.
6.2 Censored
quantile regression.
6.3 Generalized
selectivity models.
Wooldridge, Chapter 16.
Amemiya, T. (1985): Advanced Econometrics,
Blackwell, Chapter 10.
Das, M., W. K.
Newey, and F. Vella (2003): “Nonparametric Estimation of Sample Selection
Models”, Review of Economic Studies, 70, 33-58.
Heckman, J. (1979): “Sample Selection Bias as a
Specification Error”, Econometrica, 47, 153-161.
Maddala, G. S. (1983): Limited-dependent and
Qualitative Variables in Econometrics, Cambridge University Press.
Powell, J. L. (1986): “Censored Regression Quantiles”,
Journal of Econometrics, 32, 143-155.
9. Endogenous selection and
treatment effects
7.1 Switching
regression models.
7.2 Selection
bias and identification.
7.3 Estimation
methods.
Wooldridge, Chapter 18.
Angrist, J. and A. B. Krueger (1999): “Empirical
Strategies in Labor Economics” in O. Ashenfelter, and D. Card (eds.), Handbook
of Labor Economics, Vol. 3, Elsevier Science.
Heckman, J. (1990): “Varieties of Selection Bias”, American
Economic Review Papers and Proceedings, 80, 313-323.
Heckman, J. and E. Vytlacil (2005): “Structural
Equations, Treatment Effects, and Econometric Policy Evaluation”, Econometrica,
73, 669-738.
Imbens, G. W. and J. Angrist (1994): “Identification
and Estimation of Local Average Treatment Effects”, Econometrica, 62,
467-475.