Using matching, instrumental variables and control functions to estimate economic choice models
暂无分享,去创建一个
[1] James J. Heckman,et al. Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males , 1998, Journal of Political Economy.
[2] James J. Heckman,et al. The relationship between treatment parameters within a latent variable framework , 2000 .
[3] Songnian Chen. Distribution-free estimation of the random coefficient dummy endogenous variable model , 1999 .
[4] R. Lalonde. Evaluating the Econometric Evaluations of Training Programs with Experimental Data , 1984 .
[5] J J Heckman,et al. Local instrumental variables and latent variable models for identifying and bounding treatment effects. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[6] J. Heckman. Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations. , 1997 .
[7] Petra E. Todd,et al. Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme , 1997 .
[8] John Yinger,et al. Does School District Consolidation Cut Costs? , 2001 .
[9] Donald W. K. Andrews,et al. Semiparametric Estimation of the Intercept of a Sample Selection Model , 1998 .
[10] D. Rubin,et al. The central role of the propensity score in observational studies for causal effects , 1983 .
[11] Myoung-jae Lee,et al. QUADRATIC MODE REGRESSION , 1993 .
[12] J. Heckman,et al. Longitudinal Analysis of Labor Market Data: Alternative methods for evaluating the impact of interventions , 1985 .
[13] M. Sobel. Discussion: ‘The Scientific Model of Causality’ , 2005 .
[14] Petra E. Todd,et al. Matching As An Econometric Evaluation Estimator , 1998 .
[15] M. Lechner,et al. A Microeconometric Evaluation of Active Labor Market Policy in Switzerland , 2001 .
[16] James J. Heckman,et al. Four Parameters of Interest in the Evaluation of Social Programs , 2001 .
[17] J. Heckman,et al. Making the Most out of Programme Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts , 1997 .
[18] Alberto Abadie. Semiparametric Difference-in-Differences Estimators , 2005 .
[19] G. Imbens,et al. Bias-Corrected Matching Estimators for Average Treatment Effects , 2011 .
[20] James L. Powell,et al. Estimation of semiparametric models , 1994 .
[21] H. James. VARIETIES OF SELECTION BIAS , 1990 .
[22] T. Andrén,et al. Assessing the employment effects of vocational training using a one-factor model , 2006 .
[23] Jeffrey A. Smith,et al. Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators? , 2000 .
[24] J. Heckman. Rejoinder: Response to Sobel , 2005 .
[25] Petra E. Todd,et al. Reconciling Conflicting Evidence on the Performance of Propensity-Score Matching Methods , 2001 .
[26] J. Heckman. Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture , 2001, Journal of Political Economy.
[27] D. Rubin,et al. Reducing Bias in Observational Studies Using Subclassification on the Propensity Score , 1984 .
[28] A. Pakes,et al. The Dynamics of Productivity in the Telecommunications Equipment Industry , 1992 .
[29] J. Angrist,et al. Identification and Estimation of Local Average Treatment Effects , 1995 .
[30] J. Powell,et al. Semiparametric estimation of censored selection models with a nonparametric selection mechanism , 1993 .
[31] James M. Robins,et al. Causal inference for complex longitudinal data: the continuous case , 2001 .
[32] J. Heckman,et al. Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice , 2003, SSRN Electronic Journal.
[33] G. Imbens. The Role of the Propensity Score in Estimating Dose-Response Functions , 1999 .
[34] E. Vytlacil. Independence, Monotonicity, and Latent Index Models: An Equivalence Result , 2002 .
[35] P. Davies,et al. Local Extremes, Runs, Strings and Multiresolution , 2001 .
[36] M. Lechner. Identification and Estimation of Causal Effects of Multiple Treatments Under the Conditional Independence Assumption , 1999, SSRN Electronic Journal.
[37] P. Rosenbaum. Model-Based Direct Adjustment , 1987 .
[38] James J. Heckman,et al. Characterizing Selection Bias Using Experimental Data , 1998 .
[39] A. Prakash,et al. Covenants with weak swords: ISO 14001 and facilities' environmental performance , 2005 .
[40] Donald B. Rubin,et al. Characterizing the effect of matching using linear propensity score methods with normal distributions , 1992 .
[41] James J. Heckman,et al. Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs , 2005 .
[42] Richard Harris,et al. Economics of the Workplace: Special Issue Editorial , 2005 .
[43] James J. Heckman,et al. 1. The Scientific Model of Causality , 2005 .
[44] James J. Heckman,et al. Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: the Case of Manpower Training , 1989 .
[45] James J. Heckman,et al. Randomization and Social Policy Evaluation , 1991 .
[46] J. Heckman. Dummy Endogenous Variables in a Simultaneous Equation System , 1977 .
[47] Wim P. M. Vijverberg,et al. Measuring the unidentified parameter of the extended Roy model of selectivity , 1993 .
[48] R. Sparrow. Protecting Education for the Poor in Times of Crisis: An Evaluation of a Scholarship Programme in Indonesia , 2004 .
[49] J. Heckman,et al. Removing the Veil of Ignorance in Assessing the Distributional Impacts of Social Policies , 2002, SSRN Electronic Journal.
[50] Edward Vytlacil,et al. Local Instrumental Variables , 2000 .
[51] J. Hahn. On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects , 1998 .
[52] Robert A. Moffitt,et al. The Estimation of Wage Gains and Welfare Gains in Self-selection , 1987 .
[53] James J. Heckman,et al. Alternative methods for solving the problem of selection bias in evaluating the impact of treatments , 1986 .
[54] P. Veazie,et al. Another look at observational studies in rehabilitation research: going beyond the holy grail of the randomized controlled trial. , 2005, Archives of physical medicine and rehabilitation.