Spatial econometric STAR models: Lagrange multiplier tests, Monte Carlo simulations and an empirical application

Valerien Pede (), Raymond Florax and Dayton Lambert

Regional Science and Urban Economics, 2014, vol. 49, issue C, 118-128

Abstract: This paper investigates nonlinearity in parametric spatial process models that incorporate regime-switching by means of a smooth transition autoregressive process. We derive a Lagrange Multiplier (LM) test for nonlinearity as well as several joint LM tests for nonlinearity and the traditional spatial processes of autoregressive errors and an erroneously omitted spatially lagged dependent variable. Monte Carlo simulations demonstrate the size and power of the tests in finite samples. In an empirical application, we demonstrate that the suggested approach can be used to test for spatial heterogeneity in the form of spatial regimes or for the appropriateness of the spatial cross-regressive model containing spatially lagged exogenous variables.

Keywords: Spatial econometrics; Nonlinearity; Autoregressive smooth transition (search for similar items in EconPapers)
JEL-codes: C12 C21 C51 O18 R11 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:49:y:2014:i:c:p:118-128

DOI: 10.1016/j.regsciurbeco.2014.07.001

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