IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v188y2020ics0165176520300094.html
   My bibliography  Save this article

Bayesian estimation and model selection of threshold spatial Durbin model

Author

Listed:
  • Zhu, Yanli
  • Han, Xiaoyi
  • Chen, Ying

Abstract

We consider a threshold spatial Durbin model that allows for threshold effects in both endogenous and exogenous spatial interactions among cross-sectional units. We develop a computationally tractable Markov Chain Monte Carlo (MCMC) algorithm to estimate the model. We also propose a nested model selection procedure to test for spatial threshold effects, based upon the Bayes factor computed from the Savage–Dickey Density Ratio in Verdinelli and Wasserman (1995). Simulation studies suggest that the Bayesian estimator is more precise than the spatial 2SLS (S2SLS) estimator in Deng (2018). The model selection procedure works well when the sample size increases and the difference between spatial parameters enlarges.

Suggested Citation

  • Zhu, Yanli & Han, Xiaoyi & Chen, Ying, 2020. "Bayesian estimation and model selection of threshold spatial Durbin model," Economics Letters, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:ecolet:v:188:y:2020:i:c:s0165176520300094
    DOI: 10.1016/j.econlet.2020.108956
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176520300094
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2020.108956?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Koop, Gary & Potter, Simon M, 1999. "Dynamic Asymmetries in U.S. Unemployment," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 298-312, July.
    2. Caner, Mehmet & Hansen, Bruce E., 2004. "Instrumental Variable Estimation Of A Threshold Model," Econometric Theory, Cambridge University Press, vol. 20(5), pages 813-843, October.
    3. Victor Lavy & Analia Schlosser, 2011. "Mechanisms and Impacts of Gender Peer Effects at School," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 1-33, April.
    4. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    5. Deng, Ying, 2018. "Estimation for the spatial autoregressive threshold model," Economics Letters, Elsevier, vol. 171(C), pages 172-175.
    6. Mithat Gönen & Wesley O. Johnson & Yonggang Lu & Peter H. Westfall, 2019. "Comparing Objective and Subjective Bayes Factors for the Two-Sample Comparison: The Classification Theorem in Action," The American Statistician, Taylor & Francis Journals, vol. 73(1), pages 22-31, January.
    7. Lee, Lung-fei, 2007. "The method of elimination and substitution in the GMM estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 140(1), pages 155-189, September.
    8. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    9. Chih‐Sheng Hsieh & Hans van Kippersluis, 2018. "Smoking initiation: Peers and personality," Quantitative Economics, Econometric Society, vol. 9(2), pages 825-863, July.
    10. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
    11. Min Wang & Guangying Liu, 2016. "A Simple Two-Sample Bayesian t -Test for Hypothesis Testing," The American Statistician, Taylor & Francis Journals, vol. 70(2), pages 195-201, May.
    12. Gonen, Mithat & Johnson, Wesley O. & Lu, Yonggang & Westfall, Peter H., 2005. "The Bayesian Two-Sample t Test," The American Statistician, American Statistical Association, vol. 59, pages 252-257, August.
    13. Fangwen Lu & Michael L. Anderson, 2015. "Peer Effects in Microenvironments: The Benefits of Homogeneous Classroom Groups," Journal of Labor Economics, University of Chicago Press, vol. 33(1), pages 91-122.
    14. John Geweke & Nobuhiko Terui, 1993. "Bayesian Threshold Autoregressive Models For Nonlinear Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(5), pages 441-454, September.
    15. Lu, Fangwen & Anderson, Michael L, 2015. "Peer Effects in Microenvironments: The Benefits of Homogeneous Classroom Groups," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt0872n398, Department of Agricultural & Resource Economics, UC Berkeley.
    16. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    17. Victor Lavy & Analía Schlosser, 2011. "Corrigendum: Mechanisms and Impacts of Gender Peer Effects at School," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 268-268, July.
    18. Yu, Jihai & Zhou, Li-An & Zhu, Guozhong, 2016. "Strategic interaction in political competition: Evidence from spatial effects across Chinese cities," Regional Science and Urban Economics, Elsevier, vol. 57(C), pages 23-37.
    19. Lee, Lung-fei, 2007. "GMM and 2SLS estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 137(2), pages 489-514, April.
    20. Chen, Rong & Guo, Re-Jin & Lin, Ming, 2010. "Self-Selectivity in Firm’s Decision to Withdraw IPO: Bayesian Inference for Hazard Models of Bankruptcy With Feedback," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1297-1309.
    21. Lung-fei Lee & Xiaodong Liu & Xu Lin, 2010. "Specification and estimation of social interaction models with network structures," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 145-176, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Meseret Chanieabate & Hai He & Chuyue Guo & Betelhem Abrahamgeremew & Yuanji Huang, 2023. "Examining the Relationship between Transportation Infrastructure, Urbanization Level and Rural-Urban Income Gap in China," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    2. Wei, Lili & Zhang, Chunli & Su, Jen-Je & Yang, Lixiong, 2021. "Panel threshold spatial Durbin models with individual fixed effects," Economics Letters, Elsevier, vol. 201(C).
    3. Francesco Riccioli & Roberto Fratini & Fabio Boncinelli, 2021. "The Impacts in Real Estate of Landscape Values: Evidence from Tuscany (Italy)," Sustainability, MDPI, vol. 13(4), pages 1-17, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Konstantinidi, Antri & Kourtellos, Andros & Sun, Yiguo, 2023. "Social threshold regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2057-2081.
    2. Liu, Xiaodong & Lee, Lung-fei, 2010. "GMM estimation of social interaction models with centrality," Journal of Econometrics, Elsevier, vol. 159(1), pages 99-115, November.
    3. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.
    4. Osman Doğan, 2015. "Heteroskedasticity of Unknown Form in Spatial Autoregressive Models with a Moving Average Disturbance Term," Econometrics, MDPI, vol. 3(1), pages 1-27, February.
    5. Li, Kunpeng, 2022. "Threshold spatial autoregressive model," MPRA Paper 113568, University Library of Munich, Germany.
    6. Zhou, Yiwei & Wang, Xiaokun & Holguín-Veras, José, 2016. "Discrete choice with spatial correlation: A spatial autoregressive binary probit model with endogenous weight matrix (SARBP-EWM)," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 440-455.
    7. Mustafa Koroglu & Yiguo Sun, 2016. "Functional-Coefficient Spatial Durbin Models with Nonparametric Spatial Weights: An Application to Economic Growth," Econometrics, MDPI, vol. 4(1), pages 1-16, February.
    8. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    9. Huang, Danyang & Wang, Feifei & Zhu, Xuening & Wang, Hansheng, 2020. "Two-mode network autoregressive model for large-scale networks," Journal of Econometrics, Elsevier, vol. 216(1), pages 203-219.
    10. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2022. "Bayesian estimation of multivariate panel probits with higher‐order network interdependence and an application to firms' global market participation in Guangdong," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1356-1378, November.
    11. Seul-Ki Kim & Young-Chul Kim, 2021. "Coed vs Single-Sex Schooling: An Empirical Study on Mental Health Outcomes," Working Papers 2103, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    12. Qu, Xi & Lee, Lung-fei & Yang, Chao, 2021. "Estimation of a SAR model with endogenous spatial weights constructed by bilateral variables," Journal of Econometrics, Elsevier, vol. 221(1), pages 180-197.
    13. Zhang Yuanqing, 2014. "Estimation of Partially Specified Spatial Autoregressive Model," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 226-235, June.
    14. Debarsy, Nicolas & Jin, Fei & Lee, Lung-fei, 2015. "Large sample properties of the matrix exponential spatial specification with an application to FDI," Journal of Econometrics, Elsevier, vol. 188(1), pages 1-21.
    15. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
    16. Liu, Xiaodong & Saraiva, Paulo, 2015. "GMM estimation of SAR models with endogenous regressors," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 68-79.
    17. Dewan, Prerna & Ray, Tridip & Roy Chaudhuri, Arka & Tater, Kirti, 2024. "Gender peer effects in high schools: Evidence from India," Journal of Economic Behavior & Organization, Elsevier, vol. 220(C), pages 470-494.
    18. Fang Lu & Jing Yang & Xuewen Lu, 2022. "One-step oracle procedure for semi-parametric spatial autoregressive model and its empirical application to Boston housing price data," Empirical Economics, Springer, vol. 62(6), pages 2645-2671, June.
    19. Hu, Feng, 2015. "Do girl peers improve your academic performance?," Economics Letters, Elsevier, vol. 137(C), pages 54-58.
    20. Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.

    More about this item

    Keywords

    Threshold spatial Durbin model; Bayesian estimation; Bayes factor; Savage–Dickey density ratio;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:188:y:2020:i:c:s0165176520300094. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.