The Econometric SocietyEdited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262
This directory contains the stata do-files used to generate the results presented in "Experimental Analysis of Neighborhood Effects" by Jeffrey Kling, Jeffrey Liebman,and Lawrence Katz. The names of the do-files correspond to the figures and tables in the paper. (The data is not publicly available, in order to preserve the confidentiality of the respondents. See readme file).
This web appendix contains the following sections:B. Summary indices and mean effect sizesC. Calculation of adjusted p-valuesD. Comparison of outcomes to the National Longitudinal Survey of YouthE. Additional discussion of internal validityF. Additional results for adultsG. Additional results for youth
In this appendix we provide the complete theoretical analysis of Section 5. The propositions in the main part of the paper follow immediately from the propositions proved here. We also provide some additional experimental data at the end of the appendix.
This file contains the complete instructions of the Bonus-Incentive Treatment (sessions S3 and S4) translated from German to English. The instructions of the Trust-Incentive Treatment (S1 and S2) and the Control Treatment (S5 and S6) are structured similarly and are not reported here for space reasons, but they and all the original instructions in German are available from the authors upon request.
This file contains description of the following data files:MS5182-S1andS2.txtMS5182-S3andS4.txtMS5182-S5andS6.txt
File MS5182-S1andS2.txt: Data of sessions S1 and S2 (Trust versus Incentive Treatment).
File MS5182-S3andS4.txt: Data of sessions S3 and S4 (Bonus versus Incentive Treatment).
File MS5182-S5andS6.txt: Data of sessions S5 and S6 (Control Treatment).
This Supplementary Material contains some of the more technical details omitted from the paper ?Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models?. First, a brief review of the Theory of Generalized Functions is presented. Second, proofs regarding some basic properties of Fourier transforms as well as the asymptotics of the proposed GMMestimator are given. Third, the proposed estimator is compared with the one suggested in Hausman, Newey, Ichimura, Powell (1991). Fourth, an alternative derivation of the moment conditions necessitating weaker regularity conditions is provided. Fifth, the details of the Monte Carlo simulations are described. Sixth, an application of the proposed methodology to the estimation of the black-white income gap is presented. Finally, some computational aspects of the implementation of the estimator are described.
This supplement follows the paper entitled "Efficient Semiparametric Estimation of Quantile Treatment Effects". We present here (i) detailed results from an empirical example, (ii) results of a Monte Carlo exercise, (iii) details of the variance estimation, and (iv) proofs of the theoretical results.
