Estimation and testing for a partially linear single-index spatial regression model
Yan Sun and
Yueqin Wu
Spatial Economic Analysis, 2018, vol. 13, issue 4, 473-489
Abstract:
Observations recorded on ‘locations’ usually exhibit spatial dependence. In an effort to take into account both the spatial dependence and the possible underlying non-linear relationship, a partially linear single-index spatial regression model is proposed. This paper establishes the estimators of the unknowns. Moreover, it builds a generalized F-test to determine whether or not the data provide evidence on using linear settings in empirical studies. Their asymptotic properties are derived. Monte Carlo simulations indicate that the estimators and test statistic perform well. The analysis of Chinese house price data shows the existence of both spatial dependence and a non-linear relationship.
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://hdl.handle.net/10.1080/17421772.2018.1506150 (text/html)
Access to full text is restricted to subscribers.
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: https://EconPapers.repec.org/RePEc:taf:specan:v:13:y:2018:i:4:p:473-489
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RSEA20
DOI: 10.1080/17421772.2018.1506150
Access Statistics for this article
Spatial Economic Analysis is currently edited by Bernie Fingleton and Danilo Igliori
More articles in Spatial Economic Analysis from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().