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On the bootstrap for Moran’s I test for spatial dependence

Jin, Fei; Lee, Lung-fei - In: Journal of Econometrics 184 (2015) 2, pp. 295-314

This paper is concerned with the use of the bootstrap for statistics in spatial econometric models, with a focus on the … test statistic for Moran’s I test for spatial dependence. We show that, for many statistics in spatial econometric models … refinements of the bootstrap are most commonly studied using Edgeworth expansions. For spatial econometric models, we may …

Persistent link: https://www.econbiz.de/10011117413

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 …

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

Limit theory for panel data models with cross sectional dependence and sequential exogeneity

Kuersteiner, Guido M.; Prucha, Ingmar R. - In: Journal of Econometrics 174 (2013) 2, pp. 107-126

accommodate situations where cross sectional dependence stems from spatial interactions and/or from the presence of common factors …

Persistent link: https://www.econbiz.de/10010664695

Bounds for best response functions in binary games

Kline, Brendan; Tamer, Elie - In: Journal of Econometrics 166 (2012) 1, pp. 92-105

This paper studies the identification of best response functions in binary games without making strong parametric assumptions about the payoffs. The best response function gives the utility maximizing response to a decision of the other players. This is analogous to the response function in the...

Persistent link: https://www.econbiz.de/10010597561

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

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 … has the advantage of accommodating some asymptotic regimes that are suggested by certain spatial settings, several of …

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 …, and analyze asymptotic properties of the IV and MLE based on the notion of spatial near-epoch dependence. We also design a …

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 …

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

Empirical likelihood for regression discontinuity design

Otsu, Taisuke; Xu, Ke-Li; Matsushita, Yukitoshi - In: Journal of Econometrics 186 (2015) 1, pp. 94-112

This paper proposes empirical likelihood based inference methods for causal effects identified from regression discontinuity designs. We consider both the sharp and fuzzy regression discontinuity designs and treat the regression functions as nonparametric. The proposed inference procedures do...

Persistent link: https://www.econbiz.de/10011209288

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 selection bias. I detail the sources of bias of both estimators in a model of earnings dynamics and entry into a Job Training Program (JTP) and I assess their performances using...

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