Estimation of Spatial Sample Selection Models: A Partial Maximum Likelihood Approach

Renata Rabovic and Pavel Cizek

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: Estimation of a sample selection model with a spatial lag of a latent dependent variable or a spatial error in both the selection and outcome equations is considered in the presence of cross-sectional dependence. Since there is no estimation framework for the spatial lag model and the existing estimators for the spatial error model are either computationally demanding or have poor small sample properties, we suggest to estimate these models by the partial maximum likelihood estimator, following Wang et al. (2013)'s framework for a spatial error probit model. We show that the estimator is consistent and asymptotically normally distributed. To facilitate easy and precise estimation of the variance matrix without requiring the spatial stationarity of errors, we propose the parametric bootstrap method. Monte Carlo simulations demonstrate the advantages of the estimators.

Keywords: asymptotic distribution; maximum likelihood; near epoch dependence; sample selection model; spatial autoregressive model (search for similar items in EconPapers)
JEL-codes: C13 C31 C34 (search for similar items in EconPapers)
Date: 2020-02-27
New Economics Papers: this item is included in nep-ore
Note: rr574
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econ.cam.ac.uk/sites/default/files/pub ... pe-pdfs/cwpe2012.pdf

Related works:
Journal Article: Estimation of spatial sample selection models: A partial maximum likelihood approach (2023)
Working Paper: Estimation of Spatial Sample Selection Models: A Partial Maximum Likelihood Approach (2016)
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: https://EconPapers.repec.org/RePEc:cam:camdae:2012

Access Statistics for this paper

More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
Bibliographic data for series maintained by Jake Dyer ().