Efficient GMM estimation of a spatial autoregressive model with an endogenous spatial weights matrix
Author
Abstract
Suggested Citation
DOI: 10.1016/j.econlet.2021.110090
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Breusch, Trevor & Qian, Hailong & Schmidt, Peter & Wyhowski, Donald, 1999. "Redundancy of moment conditions," Journal of Econometrics, Elsevier, vol. 91(1), pages 89-111, July.
- Kelejian, Harry H. & Piras, Gianfranco, 2014.
"Estimation of spatial models with endogenous weighting matrices, and an application to a demand model for cigarettes,"
Regional Science and Urban Economics, Elsevier, vol. 46(C), pages 140-149.
- Harry H. Kelejian & Gianfranco Piras, 2012. "Estimation of Spatial Models with Endogenous Weighting Matrices and an Application to a Demand Model for Cigarettes," Working Papers Working Paper 2013-02, Regional Research Institute, West Virginia University.
- 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.
- Nicolas DEBARSY & Fei JIN & Lung-fei LEE, 2014. "Large Sample Properties of the Matrix Exponential Spatial Specification with an Application to FDI," LEO Working Papers / DR LEO 2244, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Nicolas Debarsy & Fei Jin & Lung-Fei Lee, 2015. "Large sample properties of the matrix exponential spatial specification with an application to FDI," Post-Print hal-00858174, HAL.
- Nicolas Debarsy & Fei Jin & Lung-Fei Lee, 2014. "Large sample properties of the matrix exponential spatial specification with an application to FDI," Working Papers hal-01069198, HAL.
- Qu, Xi & Lee, Lung-fei, 2015. "Estimating a spatial autoregressive model with an endogenous spatial weight matrix," Journal of Econometrics, Elsevier, vol. 184(2), pages 209-232.
- Liu, Xiaodong & Lee, Lung-fei & Bollinger, Christopher R., 2010. "An efficient GMM estimator of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 159(2), pages 303-319, December.
- Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
- Jenish, Nazgul & Prucha, Ingmar R., 2012. "On spatial processes and asymptotic inference under near-epoch dependence," Journal of Econometrics, Elsevier, vol. 170(1), pages 178-190.
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.- 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.
- Shi, Wei & Lee, Lung-fei, 2018. "A spatial panel data model with time varying endogenous weights matrices and common factors," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 6-34.
- Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
- Sophie Béreau & Nicolas Debarsy & Cyrille Dossougoin & Jean-Yves Gnabo, 2022. "Contagion in the Banking Industry: a Robust-to-Endogeneity Analysis," Working Papers halshs-03513049, HAL.
- Bing Su & Fukang Zhu & Ke Zhu, 2023. "Statistical inference for the logarithmic spatial heteroskedasticity model with exogenous variables," Papers 2301.06658, arXiv.org.
- Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
- Qu, Xi & Lee, Lung-fei, 2015. "Estimating a spatial autoregressive model with an endogenous spatial weight matrix," Journal of Econometrics, Elsevier, vol. 184(2), pages 209-232.
- 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.
- Guido M. Kuersteiner & Ingmar R. Prucha, 2015. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," CESifo Working Paper Series 5445, CESifo.
- Lee, Jiyon, 2018. "A spatial latent class model," Economics Letters, Elsevier, vol. 162(C), pages 62-68.
- Borsky, Stefan & Kalkschmied, Katja, 2019.
"Corruption in space: A closer look at the world's subnations,"
European Journal of Political Economy, Elsevier, vol. 59(C), pages 400-422.
- Stefan Borsky & Katja Kalkschmied, 2018. "Corruption in space: A closer look at the world's subnations," Graz Economics Papers 2018-18, University of Graz, Department of Economics.
- Gupta, Abhimanyu, 2019.
"Estimation Of Spatial Autoregressions With Stochastic Weight Matrices,"
Econometric Theory, Cambridge University Press, vol. 35(2), pages 417-463, April.
- Gupta, A, 2015. "Estimation of Spatial Autoregressions with Stochastic Weight Matrices," Economics Discussion Papers 15617, University of Essex, Department of Economics.
- 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.
- Nicolas DEBARSY & Fei JIN & Lung-fei LEE, 2014. "Large Sample Properties of the Matrix Exponential Spatial Specification with an Application to FDI," LEO Working Papers / DR LEO 2244, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Nicolas Debarsy & Fei Jin & Lung-Fei Lee, 2015. "Large sample properties of the matrix exponential spatial specification with an application to FDI," Post-Print hal-00858174, HAL.
- Nicolas Debarsy & Fei Jin & Lung-Fei Lee, 2014. "Large sample properties of the matrix exponential spatial specification with an application to FDI," Working Papers hal-01069198, HAL.
- 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.
- Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.
- Jeong, Hanbat & Lee, Lung-fei, 2024. "Maximum likelihood estimation of a spatial autoregressive model for origin–destination flow variables," Journal of Econometrics, Elsevier, vol. 242(1).
- Dai, Lu & Zhang, Jiajun & Luo, Shougui, 2022. "Effective R&D capital and total factor productivity: Evidence using spatial panel data models," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
- Cheng, Wei & Lee, Lung-fei, 2017. "Testing endogeneity of spatial and social networks," Regional Science and Urban Economics, Elsevier, vol. 64(C), pages 81-97.
- repec:esx:essedp:772 is not listed on IDEAS
- Huyugüzel Kışla, Gül & Özlem Önder, A., 2018. "Spatial analysis of sovereign risks: The case of emerging markets," Finance Research Letters, Elsevier, vol. 26(C), pages 47-55.
- Rabovič, Renata & Čížek, Pavel, 2023.
"Estimation of spatial sample selection models: A partial maximum likelihood approach,"
Journal of Econometrics, Elsevier, vol. 232(1), pages 214-243.
- Rabovic, Renata & Cizek, Pavel, 2016. "Estimation of Spatial Sample Selection Models : A Partial Maximum Likelihood Approach," Other publications TiSEM 8a4b2e5d-6787-4685-8b9e-1, Tilburg University, School of Economics and Management.
- Rabovic, Renata & Cizek, Pavel, 2016. "Estimation of Spatial Sample Selection Models : A Partial Maximum Likelihood Approach," Discussion Paper 2016-013, Tilburg University, Center for Economic Research.
- Rabovic, R. & Cizek, P., 2020. "Estimation of Spatial Sample Selection Models: A Partial Maximum Likelihood Approach," Cambridge Working Papers in Economics 2012, Faculty of Economics, University of Cambridge.
- Liu, Xiaodong & Prucha, Ingmar R., 2018. "A robust test for network generated dependence," Journal of Econometrics, Elsevier, vol. 207(1), pages 92-113.
More about this item
Keywords
Generalized method of moment; Endogenous spatial weights matrix; Estimation efficiency;All these keywords.
JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Statistics
Access and download statisticsCorrections
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:208:y:2021:i:c:s0165176521003670. 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.