Bayesian Estimation of the Semiparametric Spatial Lag Model

Kunming Li and Liting Fang ()
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Kunming Li: College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Liting Fang: School of Economics and Management, Fuzhou University, Fuzhou 350108, China

Mathematics, 2024, vol. 12, issue 14, 1-17

Abstract: This paper proposes a semiparametric spatial lag model and develops a Bayesian estimation method for this model. In the estimation of the model, the paper combines Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm, random walk Metropolis sampler, and Gibbs sampling techniques to sample all the parameters. The paper conducts numerical simulations to validate the proposed Bayesian estimation theory using a numerical example. The simulation results demonstrate satisfactory estimation performance of the parameter part and the fitting performance of the nonparametric function under different spatial weight matrix settings. Furthermore, the paper applies the constructed model and its estimation method to an empirical study on the relationship between economic growth and carbon emissions in China, illustrating the practical application value of the theoretical results.

Keywords: semiparametric spatial lag model; Bayesian estimation; polynomial spline; RJMCMC (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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