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Analysis of the bias of Matching and Difference-in-Difference under alternative earnings and selection processes

Chabé-Ferret, Sylvain - In: Journal of Econometrics 185 (2015) 1, pp. 110-123

Matching and Difference in Difference (DID) are two widespread methods that use pre-treatment outcomes to correct for … values. I find that Matching generally underestimates the average causal effect of the program and gets closer to the true … still performs better than Matching, especially in the middle of the life-cycle. These results are consistent with estimates …

Persistent link: https://www.econbiz.de/10011190717

Set identification via quantile restrictions in short panels

Rosen, Adam M. - In: Journal of Econometrics 166 (2012) 1, pp. 127-137

This paper studies the identifying power of conditional quantile restrictions in short panels with fixed effects. In contrast to classical fixed effects models with conditional mean restrictions, conditional quantile restrictions are not preserved by taking differences in the regression equation...

Persistent link: https://www.econbiz.de/10010597565

Asymptotics for panel quantile regression models with individual effects

Kato, Kengo; F. Galvao, Antonio; Montes-Rojas, Gabriel V. - In: Journal of Econometrics 170 (2012) 1, pp. 76-91

This paper studies panel quantile regression models with individual fixed effects. We formally establish sufficient conditions for consistency and asymptotic normality of the quantile regression estimator when the number of individuals, n, and the number of time periods, T, jointly go to...

Persistent link: https://www.econbiz.de/10010664692

Inference with dependent data using cluster covariance estimators

Bester, C. Alan; Conley, Timothy G.; Hansen, Christian B. - In: Journal of Econometrics 165 (2011) 2, pp. 137-151

This paper presents an inference approach for dependent data in time series, spatial, and panel data applications. The method involves constructing t and Wald statistics using a cluster covariance matrix estimator (CCE). We use an approximation that takes the number of clusters/groups as fixed...

Persistent link: https://www.econbiz.de/10010577508

Pseudo-Gaussian and rank-based optimal tests for random individual effects in large n small T panels

Bennala, Nezar; Hallin, Marc; Paindaveine, Davy - In: Journal of Econometrics 170 (2012) 1, pp. 50-67

We consider the problem of detecting unobserved heterogeneity, that is, the problem of testing the absence of random individual effects in an n×T panel. We establish a local asymptotic normality property–with respect to intercept, regression coefficient, the scale parameter σ of the error,...

Persistent link: https://www.econbiz.de/10011052340

Multiplicative-error models with sample selection

Jochmans, Koen - In: Journal of Econometrics 184 (2015) 2, pp. 315-327

This paper presents a simple approach to deal with sample selection in models with multiplicative errors. Models for non-negative limited dependent variables such as counts fit this framework. The approach builds on a specification of the conditional mean of the outcome only and is, therefore,...

Persistent link: https://www.econbiz.de/10011117417

QML estimation of dynamic panel data models with spatial errors

Su, Liangjun; Yang, Zhenlin - In: Journal of Econometrics 185 (2015) 1, pp. 230-258

We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the cross-sectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models, and prove consistency and derive the limiting...

Persistent link: https://www.econbiz.de/10011190720

Inference on higher-order spatial autoregressive models with increasingly many parameters

Gupta, Abhimanyu; Robinson, Peter M. - In: Journal of Econometrics 186 (2015) 1, pp. 19-31

This paper develops consistency and asymptotic normality of parameter estimates for a higher-order spatial autoregressive model whose order, and number of regressors, are allowed to approach infinity slowly with sample size. Both least squares and instrumental variables estimates are examined,...

Persistent link: https://www.econbiz.de/10011209282

A spatial autoregressive model with a nonlinear transformation of the dependent variable

Xu, Xingbai; Lee, Lung-fei - In: Journal of Econometrics 186 (2015) 1, pp. 1-18

This paper develops a nonlinear spatial autoregressive model. Of particular interest is a structural interaction model for share data. We consider possible instrumental variable (IV) and maximum likelihood estimation (MLE) for this model, and analyze asymptotic properties of the IV and MLE based...

Persistent link: https://www.econbiz.de/10011209283

A general method for third-order bias and variance corrections on a nonlinear estimator

Yang, Zhenlin - In: Journal of Econometrics 186 (2015) 1, pp. 178-200

Motivated by a recent study of Bao and Ullah (2007a) on finite sample properties of MLE in the pure SAR (spatial autoregressive) model, a general method for third-order bias and variance corrections on a nonlinear estimator is proposed based on stochastic expansion and bootstrap. Working with...

Persistent link: https://www.econbiz.de/10011209286

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