UNIVERSITY OF CALIFORNIA Spring Economics 241A Econometrics

Similar documents
Course Description. Course Requirements

Econ 273B Advanced Econometrics Spring

Course Description. Course Requirements

Course Description. Course Requirements

Simple Estimators for Semiparametric Multinomial Choice Models

APEC 8212: Econometric Analysis II

1. GENERAL DESCRIPTION

Simple Estimators for Monotone Index Models

Microeconometrics. C. Hsiao (2014), Analysis of Panel Data, 3rd edition. Cambridge, University Press.

IDENTIFICATION OF THE BINARY CHOICE MODEL WITH MISCLASSIFICATION

UNIVERSITY OF MARYLAND Department of Economics. Part A: Guido Kuersteiner Econ 722 Part B: Ingmar R. Prucha Spring 2018

Quantile methods. Class Notes Manuel Arellano December 1, Let F (r) =Pr(Y r). Forτ (0, 1), theτth population quantile of Y is defined to be

WHITNEY K. NEWEY July 2017

Conditions for the Existence of Control Functions in Nonseparable Simultaneous Equations Models 1

What s New in Econometrics? Lecture 14 Quantile Methods

Identification in Nonparametric Limited Dependent Variable Models with Simultaneity and Unobserved Heterogeneity

Informational Content in Static and Dynamic Discrete Response Panel Data Models

Syllabus. By Joan Llull. Microeconometrics. IDEA PhD Program. Fall Chapter 1: Introduction and a Brief Review of Relevant Tools

Censored Regression Quantiles with Endogenous Regressors

Simple Estimators for Invertible Index Models

Semiparametric Estimation of a Sample Selection Model in the Presence of Endogeneity

Generated Covariates in Nonparametric Estimation: A Short Review.

Flexible Estimation of Treatment Effect Parameters

Truncated Regression Model and Nonparametric Estimation for Gifted and Talented Education Program

Control Functions in Nonseparable Simultaneous Equations Models 1

13 Endogeneity and Nonparametric IV

Working Paper No Maximum score type estimators

11. Bootstrap Methods

Tobit and Interval Censored Regression Model

A Local Generalized Method of Moments Estimator

Robust covariance estimation for quantile regression

New Developments in Econometrics Lecture 16: Quantile Estimation

Unconditional Quantile Regression with Endogenous Regressors

Jinyong Hahn. Department of Economics Tel: (310) Bunche Hall Fax: (310) Professional Positions

Rank Estimation of Partially Linear Index Models

NBER WORKING PAPER SERIES A NOTE ON ADAPTING PROPENSITY SCORE MATCHING AND SELECTION MODELS TO CHOICE BASED SAMPLES. James J. Heckman Petra E.

The Influence Function of Semiparametric Estimators

Birkbeck Working Papers in Economics & Finance

Survival of the Smartest: Robust Rank-based Regression model for truncated data

Econometric Analysis of Cross Section and Panel Data

Identification and Estimation Using Heteroscedasticity Without Instruments: The Binary Endogenous Regressor Case

A Monte Carlo Comparison of Various Semiparametric Type-3 Tobit Estimators

Do Markov-Switching Models Capture Nonlinearities in the Data? Tests using Nonparametric Methods

DEPARTAMENTO DE ECONOMÍA DOCUMENTO DE TRABAJO. Nonparametric Estimation of Nonadditive Hedonic Models James Heckman, Rosa Matzkin y Lars Nesheim

Simple Estimators for Invertible Index Models

A dynamic model for binary panel data with unobserved heterogeneity admitting a n-consistent conditional estimator

Identification and Estimation of Partially Linear Censored Regression Models with Unknown Heteroscedasticity

Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models

Binary Models with Endogenous Explanatory Variables

12E016. Econometric Methods II 6 ECTS. Overview and Objectives

Nonparametric Identi cation of a Binary Random Factor in Cross Section Data

A Note on Adapting Propensity Score Matching and Selection Models to Choice Based Samples

Practical Bayesian Quantile Regression. Keming Yu University of Plymouth, UK

Comments on: Panel Data Analysis Advantages and Challenges. Manuel Arellano CEMFI, Madrid November 2006

Identification and Estimation Using Heteroscedasticity Without Instruments: The Binary Endogenous Regressor Case

A Course in Applied Econometrics Lecture 14: Control Functions and Related Methods. Jeff Wooldridge IRP Lectures, UW Madison, August 2008

Nonparametric Identi cation and Estimation of Truncated Regression Models with Heteroskedasticity

Dummy Endogenous Variables in Weakly Separable Models

Parametric identification of multiplicative exponential heteroskedasticity ALYSSA CARLSON

Econometrics I G (Part I) Fall 2004

Exclusion Restrictions in Dynamic Binary Choice Panel Data Models

Parametric Identification of Multiplicative Exponential Heteroskedasticity

An Overview of the Special Regressor Method

Semiparametric Efficiency in Irregularly Identified Models

A Bootstrap Test for Conditional Symmetry

Nonseparable multinomial choice models in cross-section and panel data

ESTIMATION OF NONPARAMETRIC MODELS WITH SIMULTANEITY

Maximum score estimation of preference parameters for a binary choice model under uncertainty

Irregular Identification, Support Conditions, and Inverse Weight Estimation

A Simple Estimator for Binary Choice Models With Endogenous Regressors

Identification and Estimation of Regression Models with Misclassification

Identification of Instrumental Variable. Correlated Random Coefficients Models

Economics 551-B: ECONOMETRIC METHODS II: Professor John Rust

Information Structure and Statistical Information in Discrete Response Models

NBER WORKING PAPER SERIES ESTIMATING DERIVATIVES IN NONSEPARABLE MODELS WITH LIMITED DEPENDENT VARIABLES

Department of Economics. Working Papers

BOOTSTRAP INFERENCES IN HETEROSCEDASTIC SAMPLE SELECTION MODELS: A MONTE CARLO INVESTIGATION

ON ILL-POSEDNESS OF NONPARAMETRIC INSTRUMENTAL VARIABLE REGRESSION WITH CONVEXITY CONSTRAINTS

A Simple Estimator for Binary Choice Models With Endogenous Regressors

Harvard University. A Note on the Control Function Approach with an Instrumental Variable and a Binary Outcome. Eric Tchetgen Tchetgen

Density estimation Nonparametric conditional mean estimation Semiparametric conditional mean estimation. Nonparametrics. Gabriel Montes-Rojas

ECO 2403 TOPICS IN ECONOMETRICS

Teruko Takada Department of Economics, University of Illinois. Abstract

Identification and Estimation of Semiparametric Two Step Models

QUANTILE REGRESSION WITH CENSORING AND ENDOGENEITY

On IV estimation of the dynamic binary panel data model with fixed effects

Nonparametric Identi cation of Regression Models Containing a Misclassi ed Dichotomous Regressor Without Instruments

Quantile regression and heteroskedasticity

Simple Estimators for Binary Choice Models With Endogenous Regressors

EMPIRICALLY RELEVANT CRITICAL VALUES FOR HYPOTHESIS TESTS: A BOOTSTRAP APPROACH

Partial Rank Estimation of Transformation Models with General forms of Censoring

A Goodness-of-fit Test for Copulas

The Identification Zoo - Meanings of Identification in Econometrics: PART 3

Identification and Estimation of a Triangular model with Multiple

Models, Testing, and Correction of Heteroskedasticity. James L. Powell Department of Economics University of California, Berkeley

Locally Robust Semiparametric Estimation

ECONOMETRICS II (ECO 2401S) University of Toronto. Department of Economics. Spring 2013 Instructor: Victor Aguirregabiria

Regensburger DISKUSSIONSBEITRÄGE zur Wirtschaftswissenschaft

Identification in Triangular Systems using Control Functions

Nonparametric Identication of a Binary Random Factor in Cross Section Data and

Transcription:

DEPARTMENT OF ECONOMICS R. Smith, J. Powell UNIVERSITY OF CALIFORNIA Spring 2006 Economics 241A Econometrics This course will cover nonlinear statistical models for the analysis of cross-sectional and panel data, with applications in microeconomics. It is intended both for students specializing in econometric theory and for students interested in applying statistical methods to economic data. Economics 240A-B (or equivalent) is prerequisite. The grade for the second half of the semester will be based upon problem sets and an in-class midterm (on May 8). TENTATIVE COURSE OUTLINE FOR SECOND HALF OF SEMESTER 1. Nonparametric density and regression estimation Powell, J.L., Notes on Nonparametric Density Estimation. Powell, J.L., Notes on Nonparametric Regression Estimation. Pagan, A.P. and A. Ullah (1999), Nonparametric Econometrics (Cambridge University Press), chapters 1-3 Powell, Estimation of Semiparametric Models, Sec. 1. *Hardle, W. and O. Linton (1994), "Applied Nonparametric Methods," in R.F. Engle and D.L. McFadden, eds., Handbook of Econometrics, Vol. 4 (North-Holland), chapter 38. *Silverman, B.W. (1986), Density Estimation for Statistics and Data Analysis (Chapman-Hall), chapters 2,3. *Manski, C.F. (1989), Analog Estimation Methods in Econometrics (Chapman-Hall), sections 2.2, 3.4. *Bierens, H.J. (1987), "Kernel Estimators of Regression Functions," in T.F. Bewley, ed., Advances in Econometrics, Fifth World Congress, Vol. 1, (Cambridge University Press).

2. Review of conditional moment restrictions Powell, J.L., ``Notes on Method of Moments Estimation. Powell, J.L. (1994), Estimation of Semiparametric Models, in Engle, R.F. and D.L. McFadden, eds., Handbook of Econometrics, Vol. 4 (North Holland), Sec. 2.1. *Chamberlain, G. (1992), Efficiency Bounds for Semiparametric Regression, Econometrica, 60, 597-626. *Newey, W.K. (1994), The Asymptotic Variance of Semiparametric Estimators, Econometrica, 62: 1349-1382. 3. Quantile regression Powell, J.L., Notes on Median and Quantile Regression. Amemiya, T. (1984) Advanced Econometrics (Harvard University Press),.section 4.6. Powell, Estimation of Semiparametric Models, Sec. 2.2. *Koenker R. and G.S. Bassett Jr. (1978), "Regression Quantiles," Econometrica, 46, 33-50. *Koenker R. and G.S. Bassett Jr. (1982), "Robust Tests for Heteroskedasticity Based on Regression Quantiles," Econometrica, 50, 43-62. 4. Semiparametric binary response models Pagan and Ullah, Nonparametric Econometrics, Sec. 7.1-7.3, Sec. 7.5.1-7.5.4. Powell, Estimation of Semiparametric Models, Sec. 3.1. Amemiya, Advanced Econometrics, chapter 9. *Manski, C.F. (1985), "Semiparametric Analysis of Discrete Response, Asymptotic Properties of the Maximum Score Estimator," Journal of Econometrics, 27, 205-228. *Han, A.K. (1987a), "Non-Parametric Analysis of a Generalized Regression Model: The

Maximum Rank Correlation Estimator," Journal of Econometrics, 35, 303-316. *Cosslett, S.R. (1983), "Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model," Econometrica, 51, 765-782. *Horowitz, J.L. (1992), "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, 60, 505-531. 5. Single index regression models Pagan and Ullah, Nonparametric Econometrics, Sec. 7.4, 7.5.6. Powell, Estimation of Semiparametric Models, Sec. 3.2. *Stoker, T.M. (1986), "Consistent Estimation of Scaled Coefficients," Econometrica, 54, 1461-1481. *Powell, J.L., J.H. Stock and T.M. Stoker (1989), "Semiparametric Estimation of Weighted Average Derivatives," Econometrica, 57, 1403-1430. *Hardle, W. and T.M. Stoker (1989) "Investigating Smooth Multiple Regression by the Method of Average Derivatives," Journal of the American Statistical Association, 84, 986-995. *Ruud, P. (1986), "Consistent Estimation of Limited Dependent Variable Models Despite Misspecification of Distribution," Journal of Econometrics, 32, 157-187. *Klein, R.W. and R.H. Spady (1993), "An Efficient Semiparametric Estimator for Discrete Choice Models," Econometrica, 61, 387-421. *Ichimura, H. (1993), "Semiparametric Least Squares (SLS) and Weighted SLS Estimation of Single Index Models," Journal of Econometrics, 58, 71-120. 6. Semiparametric censored and truncated regression models Pagan and Ullah, Nonparametric Econometrics, Sec. 9.5-9.7. Powell, Estimation of Semiparametric Models, Sec. 3.3. Amemiya, Advanced Econometrics, chapter 10.

*Powell, J.L. (1984), "Least Absolute Deviations Estimation for the Censored Regression Model," Journal of Econometrics, 25, 303-325. *Powell, J.L. (1986), "Symmetrically Trimmed Least Squares Estimation of Tobit Models," Econometrica, 54, 1435-1460. *Horowitz, J.L. (1986), "A Distribution-Free Least Squares Estimator for Censored Linear Regression Models," Journal of Econometrics, 32, 59-84. *Buchinsky, M. and J. Hahn (1998), An Alternative Estimator for the Censored Quantile Regression Model, Econometrica, 66, 653-672. 7. Semilinear regression and semiparametric selection models Pagan and Ullah, Nonparametric Econometrics, Sec. 5.1-5.2, 8.1-8.3. Powell, Estimation of Semiparametric Models, Sec. 3.4. *Robinson, P. (1988b), "Root-N-Consistent Semiparametric Regression," Econometrica, 56, 931-954. *Cosslett, S.R. (1991), "Distribution-Free Estimator of a Regression Model with Sample Selectivity," in Barnett, W.A., J.L. Powell, and G. Tauchen, eds., Nonparametric and Semiparametric Methods in Econometrics and Statistics (Cambridge University Press). *Powell, J.L. (2001), Semiparametric Estimation of Censored Selection Models, in Hsiao, C., K. Morimune, and J.L. Powell, eds., Nonlinear Statistical Modeling (Cambridge University Press). *Ahn, H. and J.L. Powell (1993), "Semiparametric Estimation of Censored Selection Models with a Nonparametric Selection Mechanism," Journal of Econometrics, 58, 3-29. 8. Semiparametric panel data models Powell, Estimation of Semiparametric Models, Sec. 3.5. *Manski, C.F. (1987), "Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data," Econometrica, 55, 357-362.

*Honoré, B.E. (1992), "Trimmed LAD and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects," Econometrica, 60, 533-565. *Kyriazidou, E. (1997), Estimation of a Panel Data Sample Selection Model, Econometrica, 65, 1335-1364. *Honoré, B.E. and E. Kyriazidou (2000), Panel Data Discrete Choice Models with Lagged Dependent Variables, Econometrica, 68, 839-874. 9. Nonparametric and semiparametric models with endogeneity Pagan and Ullah, Nonparametric Econometrics, Sec. 6.5. Blundell R. and J.L. Powell (2003), Endogeneity in Nonparametric and Semiparametric Regression Models, in Dewatripont, M., L.P. Hansen, and S.J. Turnovsky, eds., Advances in Economics and Econometrics: Theory and Applications, Eighth World Congress, Vol. II (Cambridge University Press). Newey, W.K. and J.L. Powell (2003), Instrumental Variables Estimation for Nonparametric Models, Econometrica, 71: 1565-1578. Ai, C. and X. Chen (2003), Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions, Econometrica, 71: 1795-1843. *Newey, W.K., J.L. Powell, and F. Vella (1999), Nonparametric Estimation of Triangular Simultaneous Equations Models, Econometrica, 67, 565-604. *Lewbel, A. (1998), Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors, Econometrica, 66, 105-122. *Das, M., W.K. Newey, and F. Vella (2003), Nonparametric Estimation of Sample Selection Models,'' Review of Economic Studies, 70, 33-58. *Blundell, R. and J.L. Powell (2004), Endogeneity in Semiparametric Binary Response Models, Review of Economic Studies, 71, 581-913. *Imbens, G.W. and W.K. Newey (2002), Nonparametric Identification of Triangular Simultaneous Equation Models Without Additivity, NBER Technical Working Papers No, 0285. *Blundell, R. and J.L. Powell (2004), Censored Quantile Regression with Endogenous Regressors, manuscript, Department of Economics, UC Berkeley.