Dynamic Panel Threshold Spatial Durbin Model with an Application to the Relationship between Financial Development and Green Growth
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Lili Wei
Abstract
This paper studies computation, estimation, inference and specification testing in dynamic panel threshold spatial Durbin (DPTSD) model with multiple thresholds. We first develop a new Markov chain Monte Carlo (MCMC) based algorithm to jointly estimate the threshold parameters and simultaneously construct the confidence intervals for the parameters, after suggesting a within-group spatial two-stage least squares estimator. We then construct test statistics for threshold effect and the number of thresholds. Monte Carlo experiments indicate that the proposed estimator and tests have desired performance in finite samples. We finally apply the DPTSD model to investigate the relationship between financial development and green growth, and find that the empirical results based on the DPTSD model are quite different from these based on the dynamic panel threshold model.
Funding source: National Social Science Fund of China
Award Identifier / Grant number: 23BJY239
Acknowledgments
The authors would like to thank the Editor Professor Jeremy Piger and two anonymous referees for their very constructive comments and suggestions. We also thank Professor Lixiong Yang for helpful discussions and suggestions. Any remaining errors are solely our responsibility.
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Research ethics: This article does not contain any studies with human participants or animals performed by the authors.
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Competing interests: The authors declare that they have no potential competing interests.
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Research funding: This study is supported by the National Social Science Fund of China (Grant No. 23BJY239).
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Data availability: Codes and data are available from the authors on request.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/snde-2023-0033).
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