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Home | Courses | Advanced Microeconometrics
Course

Advanced Microeconometrics


  • Teacher(s)
  • Research field
    Econometrics
  • Dates
    Period 2 - Oct 26, 2020 to Dec 18, 2020
  • Course type
    Field
  • Program year
    Second
  • Credits
    3

Course description

For maximum likelihood methods that are employed to analyze limited dependent variables, we discuss semi-parametric methods which allow one to replace sometimes restrictive distributional assumptions on the errors. For GMM, which is already a semi-parametric estimation method, we discuss how to replace the Jacobian identification method. The resulting GMM procedures are so called weak instrument robust and we discuss several papers in this area. We also discuss linear and non-linear panel data methods which are commonly applied. Here we focus on the identification of the parameters with a special emphasis on linear dynamic panel data models.

Topics: semi-parametric estimation, (linear dynamic) panel data models, weak instruments in linear instrumental variables regression models and GMM, empirical likelihood methods.

Prerequisites

A strong background in statistics and econometrics

Course literature

Primary reading
- Newey, W.K. and D. McFadden. Large Sample Estimation and hypothesis testing, Handbook of Econometrics, Chap. 36., Vol. 4, Eds: R.F. Engle and D. MacFadden
- Powell, J.L. Estimation of Semiparametric Models, Handbook of Econometrics, Chap. 41, Vol. 4, Eds: R.F. Engle and D. MacFadden
- Arellano, M. and B. Honore. Panel date models: Some recent developments, Handbook of Econometrics, Chap. 53, Vol. 5, Eds: J.J. Heckman and E. Leamer
- Nelson, C.R., and R. Startz (1990). Some Further Results on the Exact Small Sample Properties of the Instrumental Variables Estimator, Econometrica, 4, 967-976
- Bekker, P. (1994). Alternative Approximations to the Distributions of Instrumental Variable Estimators, Econometrica, 62, 657-681
- Staiger, D, and J. H. Stock (1997). Instrumental Variables Regression with Weak Instruments, Econometrica, 65, 557-586
- Stock, J.H. and J.H. Wright (2000). GMM with Weak Identification, Econometrica, 68, 1055-1096
- Kleibergen, F. (2002). Pivotal statistics for testing structural parameters in instrumental variables regression, Econometrica, 2002, 1781-2003
- Moreira, M.J. (2003). A conditional likelihood ratio test for structural models, Econometrica, 71, 1027-1048
- Andrews, D.W.K, M.J. Moreira and J.H. Stock (2006). Optimal Two-sided invariant similar tests for instrumental variables regression, Econometrica, 2006, 74, 715-752.
- Kleibergen, F. (2005). Testing parameters in GMM without assuming that they are identified, Econometrica, 73, 1103-1123.
- Kleibergen, F. (2005). Generalizing weak instrument robust IV statistics towards multiple parameters, unrestricted covariance matrices and identification statistics, Forthcoming in the Journal of Econometrics
- Kleibergen, F. (2008). Size correct subset statistics for the linear IV regression model, Brown University
- Kleibergen, F. and S. Mavroeidis (2008). Inference on subsets of parameters in GMM without assuming identification, Brown University
- Newey, W. and R.J. Smith (2004). Higher order properties of GMM and Generalized Empirical Likelihood Estimators, Econometrica, 74, 219-255