Implementations of tests on the exogeneity of selected. variables and their Performance in practice ACADEMISCH PROEFSCHRIFT

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1 Implementations of tests on the exogeneity of selected variables and their Performance in practice ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. D.C. van den Boom ten overstaan van een door het College voor promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op vrijdag 29 mei 2015, te 14:00 uur door Milan Pleus geboren te Naarden

2 Contents 1 Introduction Outline of the thesis 4 2 The performan.ee of tests on endogeneity of subsets of explanatory variables scanned by Simulation Introduction Testing the orthogonality of subsets of explanatory variables The model and setting The source of any estimator discrepancy Testing based on the source of any discrepancy Testing based on the discrepancy as such Testing based on covariance of structural and reduced form disturbances Testing by an incremental Sargan test Concerns for practitioners Earlier Monte Carlo designs and results A more comprehensive Monte Carlo design The simulated data generating process Simulation design parameter space Simulation Undings on rejection probabilities At least one exogenous regressor Both regressors endogenous Results for bootstrapped tests A bootstrap routine for subset DWH test statistics Simulation results for bootstrapped test statistics Empirical case study Conclusions 42 iii

3 3 On overidentifying restrictions tests and their incremental versions Introduction Testing overidentifying restrictions Test statistics and distributions Power properties Neglecting heteroskedasticity A higher order refinement to the Sargan test Simulation design Simulation Undings on rejection probabilities Conclusions 73 Appendix 3.A Proofs of theorems 75 Appendix 3.B Details on the correeted statistic 77 4 Accuracy and efficiency of various GMM inference techniques in dynamic micro panel data models: theory Introduction Basic GMM results for linear models Model and estimators Some algebraic peculiarities Particular test procedures Implementations for dynamic micro panel models Model and assumptions Removing individual effects by Erst differencing Respecting the equation in levels as well Coefficient restriction tests Tests of overidentification restrictions Modilied GMM Intermediate conclusions 111 Appendix 4.A Correeted variance estimation for 2-step GMM 112 Appendix 4.B Partialling out and GMM 114 Appendix 4.C Extracting redundant moment conditions Accuracy and efficiency of various GMM inference techniques in dynamic micro panel data models: practice Introduction Simulation design Simulation results 125 iv

4 5.3.1 DGPs under effect stationarity Nonstationarity Empirical results Major Undings 151 Appendix 5.A Derivations for (5.17) Refined exogeneity tests in dynamic panel data models Introduction Exogeneity tests Estimators and assumptions Incremental Sargan-Hansen test Hausman test Some possible refinements Diagonal Sargan-Hansen test Finite sample corrected variance for the Hausman test Testing exogeneity in dynamic panel data models Model and assumptions Füll comprehensive internal Instrument matrices Estimators Establishing endogeneity Establishing weak exogeneity Simulation design Simulation results Results under strict exogeneity Results under weak exogeneity Results under endogeneity Empirical case study Conclusions 184 Appendix 6.A Non-negativeness of Jj 2 ' 186 Appendix 6.B Proof of Theorem Appendix 6.C Estimating the variance of the vector of contrasts 189 Appendix 6.D Correcting H 190 Bibliography 197 Surnmary 207 v

5 Samenvatting (Summary in Dutch) vi

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