Economics at your fingertips  

Irregular N2SLS and LASSO estimation of the matrix exponential spatial specification model

Fei Jin and Lung-Fei Lee ()

Journal of Econometrics, 2018, vol. 206, issue 2, 336-358

Abstract: In this paper, we consider estimation of the matrix exponential spatial specification model with the Durbin and endogenous regressors. We find that the nonlinear two-stage least squares (N2SLS) estimator is in general consistent and asymptotically normal. However, when the Durbin and endogenous regressors are irrelevant, the gradient vector of the N2SLS criterion function has a singular covariance matrix with probability approaching one (w.p.a.1.). Some components of the N2SLS estimator have slower rates of convergence and their asymptotic distributions are nonstandard. The distance difference and gradient test statistics, which have irregular asymptotic distributions, are derived to test for the irrelevance of the Durbin and endogenous regressors. As an alternative estimation and model selection approach, we propose the adaptive group LASSO, which penalizes the coefficients of the Durbin and endogenous explanatory variables. We show that the estimator has the oracle properties, so the true model can be selected w.p.a.1. and the estimator always has the n-rate of convergence and asymptotic normal distribution. We propose to select the tuning parameter for the adaptive group LASSO by minimizing an information criterion.

Keywords: Matrix exponential spatial specification; Unknown heteroskedasticity; Nonlinear two-stage least squares; Singular covariance matrix; Irregular estimates and test statistics; LASSO; Oracle properties (search for similar items in EconPapers)
JEL-codes: C12 C13 C21 R15 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2019-05-27
Handle: RePEc:eee:econom:v:206:y:2018:i:2:p:336-358