A Spatial Sample Selection Model

Bibliographic Data

ID21512908
AuthorsYong Bao (0000-0003-3975-8567, Department of Economics Purdue University West Lafayette Indiana 47907 USA), Gucheng Li (Department of Agricultural Economics Huazhong Agricultural University Wuhan Hubei 430070 China), Xiaotian Liu (0009-0009-6737-5353, Department of Agricultural Economics Huazhong Agricultural University Wuhan Hubei 430070 China)
Year2024
Volume86
Issue4
Pages928-950
Publication date2024-08-01
Open AccessYes
TypeARTICLE
VenueOxford Bulletin of Economics and Statistics (JOURNAL)
Journal identifiersISSN: 0305-9049 • E-ISSN: 1468-0084
PublisherWiley (PUBLISHER • GB)
DOI10.1111/obes.12599
OpenAlexW4391280707
LanguageEN
References cited41

This paper presents a sample selection model with spatial correlation in the selection and outcome variables and studies the maximum likelihood method of estimation. Consistency and asymptotic normality of the maximum likelihood estimator are established by the spatial near‐epoch dependent properties of the variables. Monte Carlo simulations show its good finite‐sample performance. This model is used to examine the impact of climate change on cereal yields in Southeast Asia and projects that climate change may cause a reduction in cereal yields by () in the minimum‐change (maximum‐change) scenario

Chromatography · Econometrics · Model selection · Statistics · Agricultural Economics and Policy · Chemistry · Computer Science · Economics of Agriculture and Food Markets · Mathematics · Spatial and Panel Data Analysis · Artificial Intelligence

Tools

Open DOI