Cross-sectional dependence model specifications in a static trade panel data setting

James LeSage and Manfred Fischer ()

Journal of Geographical Systems, 2020, vol. 22, issue 1, No 3, 5-46

Abstract: Abstract The focus is on cross-sectional dependence in panel trade flow models. We propose alternative specifications for modeling time-invariant factors such as sociocultural indicator variables, e.g., common language and currency. These are typically treated as a source of heterogeneity that is eliminated using fixed effects transformations, but we find evidence of cross-sectional dependence after eliminating country-specific and time-specific effects. These findings suggest use of alternative simultaneous dependence model specifications that accommodate cross-sectional dependence, which we set forth along with Bayesian estimation methods. Ignoring cross-sectional dependence implies biased estimates from panel trade flow models that rely on fixed effects.

Keywords: Bayesian; MCMC estimation; Sociocultural distance; Origin–destination flows; Treatment of time-invariant variables; Panel models (search for similar items in EconPapers)
JEL-codes: C18 C51 R11 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Related works:
Working Paper: Cross-sectional dependence model specifications in a static trade panel data setting (2019)
Working Paper: Cross-sectional dependence model specifications in a static trade panel data setting (2017)
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DOI: 10.1007/s10109-019-00298-y

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