Testing endogeneity with high dimensional covariates
暂无分享,去创建一个
Dylan S. Small | T. Tony Cai | Hyunseung Kang | Zijian Guo | T. Cai | T. T. Cai | D. Small | Hyunseung Kang | Zijian Guo
[1] A. Belloni,et al. Inference for High-Dimensional Sparse Econometric Models , 2011, 1201.0220.
[2] J. Angrist,et al. Identification and Estimation of Local Average Treatment Effects , 1994 .
[3] Dylan S. Small,et al. Sensitivity Analysis for Instrumental Variables Regression With Overidentifying Restrictions , 2007 .
[4] F. Fisher. Approximate Specification and the Choice of a k-Class Estimator , 1967 .
[5] Cun-Hui Zhang,et al. Scaled sparse linear regression , 2011, 1104.4595.
[6] James Durbin,et al. Errors in variables , 1954 .
[7] Marcelo J. Moreira. A Conditional Likelihood Ratio Test for Structural Models , 2003 .
[8] Dylan S. Small,et al. Confidence intervals for causal effects with invalid instruments by using two‐stage hard thresholding with voting , 2016, 1603.05224.
[9] A. Belloni,et al. Program evaluation with high-dimensional data , 2013 .
[10] D. Katz. The American Statistical Association , 2000 .
[11] A. Tsybakov,et al. High-dimensional instrumental variables regression and confidence sets -- v2/2012 , 2018, 1812.11330.
[12] F. D. Tchatoka. On bootstrap validity for specification tests with weak instruments , 2015 .
[13] L. Hansen. Large Sample Properties of Generalized Method of Moments Estimators , 1982 .
[14] Frank Kleibergen,et al. Pivotal statistics for testing structural parameters in instrumental variables regression , 2002 .
[15] Richard Startz,et al. Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator , 1988 .
[16] M. Baiocchi,et al. Instrumental variable methods for causal inference , 2014, Statistics in medicine.
[17] Mehmet Caner. Near Exogeneity and Weak Identification in Generalized Empirical Likelihood Estimators: Fixed and Many Moment Asymptotics , 2006 .
[18] P. Holland. CAUSAL INFERENCE, PATH ANALYSIS AND RECURSIVE STRUCTURAL EQUATIONS MODELS , 1988 .
[19] W. Newey,et al. Generalized method of moments specification testing , 1985 .
[20] Harrison H. Zhou,et al. Quantile coupling inequalities and their applications , 2012 .
[21] Michael P. Murray. Avoiding Invalid Instruments and Coping with Weak Instruments , 2006 .
[22] F. Fisher. The Relative Sensitivity to Specification Error of Different k-Class Estimators , 1966 .
[23] Norman R. Swanson,et al. Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity , 2010 .
[24] De-Min Wu,et al. Alternative Tests of Independence between Stochastic Regressors and Disturbances , 1973 .
[25] Chirok Han,et al. Detecting Invalid Instruments Using L1-GMM , 2007 .
[26] J. Robins,et al. Instruments for Causal Inference: An Epidemiologist's Dream? , 2006, Epidemiology.
[27] Jonathan H. Wright,et al. GMM WITH WEAK IDENTIFICATION , 2000 .
[28] Roberto S. Mariano,et al. Approximations to the Distribution Functions of Theil's K-Class Estimators , 1973 .
[29] Yoonseok Lee,et al. Hahn-Hausman test as a specification test , 2012 .
[30] Adel Javanmard,et al. Confidence intervals and hypothesis testing for high-dimensional regression , 2013, J. Mach. Learn. Res..
[31] Patrik Guggenberger. ON THE ASYMPTOTIC SIZE DISTORTION OF TESTS WHEN INSTRUMENTS LOCALLY VIOLATE THE EXOGENEITY ASSUMPTION , 2011, Econometric Theory.
[32] A. Hall,et al. A Consistent Method for the Selection of Relevant Instruments , 2003 .
[33] T. Tony Cai,et al. Confidence intervals for high-dimensional linear regression: Minimax rates and adaptivity , 2015, 1506.05539.
[34] Peter E. Rossi,et al. Plausibly Exogenous , 2012, Review of Economics and Statistics.
[35] A. Belloni,et al. Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming , 2011 .
[36] Donald W. K. Andrews,et al. Performance of Conditional Wald Tests in IV Regression with Weak Instruments , 2007 .
[37] Jianqing Fan,et al. Endogeneity in High Dimensions. , 2012, Annals of statistics.
[38] Christian Hansen,et al. Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments , 2015, 1501.03185.
[39] Donald W. K. Andrews,et al. Consistent Moment Selection Procedures for Generalized Method of Moments Estimation , 1999 .
[40] 秀俊 松井,et al. Statistics for High-Dimensional Data: Methods, Theory and Applications , 2014 .
[41] David Card. The Causal Effect of Education on Learning , 1999 .
[42] C. Meyerhoefer,et al. The Impact of Physical Education on Obesity Among Elementary School Children , 2012, Journal of health economics.
[43] Roman Vershynin,et al. Introduction to the non-asymptotic analysis of random matrices , 2010, Compressed Sensing.
[44] John C. Ham,et al. The Hausman Test and Weak Instruments , 2011 .
[45] Eric Zivot,et al. Inference on a Structural Parameter in Instrumental Variables Regression with Weak Instruments , 1996 .
[46] J. Hahn,et al. Estimation with Valid and Invalid Instruments , 2005 .
[47] Lee H. Dicker,et al. Variance estimation in high-dimensional linear models , 2014 .
[48] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[49] Christian Hansen,et al. Estimation with many instrumental variables , 2006 .
[50] Christian Hansen,et al. Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach , 2015 .
[51] J. MacKinnon,et al. Estimation and inference in econometrics , 1994 .
[52] Jean-Marie Dufour,et al. Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models , 1997 .
[53] Motohiro Yogo,et al. Asymptotic Properties of the Hahn-Hausman Test for Weak Instruments , 2004 .
[54] Peter Schmidt,et al. Redundancy of moment conditions , 1999 .
[55] Paul A. Bekker,et al. ALTERNATIVE APPROXIMATIONS TO THE DISTRIBUTIONS OF INSTRUMENTAL VARIABLE ESTIMATORS , 1994 .
[56] J. Hausman. Specification tests in econometrics , 1978 .
[57] Christian Hansen,et al. High-Dimensional Methods and Inference on Structural and Treatment Effects , 2013 .
[58] Jianqing Fan,et al. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties , 2001 .
[59] Zhipeng Liao,et al. ADAPTIVE GMM SHRINKAGE ESTIMATION WITH CONSISTENT MOMENT SELECTION , 2012, Econometric Theory.
[60] Dylan S. Small,et al. Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization , 2014, 1401.5755.
[61] B. M. Pötscher,et al. MODEL SELECTION AND INFERENCE: FACTS AND FICTION , 2005, Econometric Theory.
[62] A. Belloni,et al. SPARSE MODELS AND METHODS FOR OPTIMAL INSTRUMENTS WITH AN APPLICATION TO EMINENT DOMAIN , 2012 .
[63] Peng Zhao,et al. On Model Selection Consistency of Lasso , 2006, J. Mach. Learn. Res..
[64] Daniel Berkowitz,et al. The Validity of Instruments Revisited , 2008 .
[65] J. Sargan. THE ESTIMATION OF ECONOMIC RELATIONSHIPS USING INSTRUMENTAL VARIABLES , 1958 .
[66] Harrison H. Zhou,et al. Asymptotic normality and optimalities in estimation of large Gaussian graphical models , 2013, 1309.6024.
[67] Gábor Lugosi,et al. Concentration Inequalities - A Nonasymptotic Theory of Independence , 2013, Concentration Inequalities.
[68] Norman R. Swanson,et al. Consistent Estimation with a Large Number of Weak Instruments , 2005 .
[69] K. Morimune. Approximate Distributions of k-Class Estimators when the Degree of Overidentifiability is Large Compared with the Sample Size , 1983 .
[70] Achim Zeileis,et al. Applied Econometrics with R , 2008 .
[71] Eric Zivot,et al. Valid Confidence Intervals and Inference in the Presence of Weak Instruments , 1998 .
[72] R. C. Campbell,et al. The Hausman test, and some alternatives, with heteroskedastic data , 2012 .
[73] J. Angrist,et al. Identification and Estimation of Local Average Treatment Effects , 1995 .
[74] Raj Chetty,et al. Identification and Inference With Many Invalid Instruments , 2011 .
[75] Cun-Hui Zhang,et al. Confidence intervals for low dimensional parameters in high dimensional linear models , 2011, 1110.2563.
[76] Patrik Guggenberger. THE IMPACT OF A HAUSMAN PRETEST ON THE ASYMPTOTIC SIZE OF A HYPOTHESIS TEST , 2009, Econometric Theory.
[77] J. Stock,et al. Instrumental Variables Regression with Weak Instruments , 1994 .
[78] P. Holland. Causal Inference, Path Analysis and Recursive Structural Equations Models. Program Statistics Research, Technical Report No. 88-81. , 1988 .
[79] Donald W. K. Andrews,et al. Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models , 2001 .
[80] K. Kosec. The child health implications of privatizing Africa's urban water supply. , 2014, Journal of health economics.
[81] Jinyong Hahn,et al. A New Specification Test for the Validity of Instrumental Variables , 2000 .
[82] Martin J. Wainwright,et al. Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting , 2007, IEEE Transactions on Information Theory.
[83] David A. Jaeger,et al. Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak , 1995 .
[84] Zhipeng Liao,et al. Select the Valid and Relevant Moments: An Information-Based LASSO for GMM with Many Moments , 2013 .
[85] Chirok Han,et al. GMM with Many Moment Conditions , 2005 .
[86] Jeffrey M. Wooldridge,et al. Solutions Manual and Supplementary Materials for Econometric Analysis of Cross Section and Panel Data , 2003 .
[87] Masao Nakamura,et al. On the Relationships among Several Specification Error Tests Presented by Durbin, Wu, and Hausman , 1981 .
[88] S. Geer,et al. On asymptotically optimal confidence regions and tests for high-dimensional models , 2013, 1303.0518.