Xi Qu

Personal Details

First Name:	Xi
Middle Name:
Last Name:	Qu
Suffix:
RePEc Short-ID:	pqu175
	https://www.acem.sjtu.edu.cn/en/faculty/quxi.html

Affiliation

Antai College of Economics and Management
Shanghai Jiao Tong University

Shanghai, China
http://www.acem.sjtu.edu.cn/
RePEc:edi:acsjtcn (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Arthur Lewbel & Xi Qu & Xun Tang, 2019. "Social Networks with Unobserved Links," Boston College Working Papers in Economics 1004, Boston College Department of Economics, revised 15 Jul 2022.
   • Arthur Lewbel & Xi Qu & Xun Tang, 2023. "Social Networks with Unobserved Links," Journal of Political Economy, University of Chicago Press, vol. 131(4), pages 898-946.

   Cited by:

   1. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: Theory and an application to tax competition," CeMMAP working papers 21/23, Institute for Fiscal Studies.
      • Áureo de Paula & Imran Rasul & Pedro CL Souza, 2019. "Identifying network ties from panel data: theory and an application to tax competition," CeMMAP working papers CWP55/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
      • Imran Rasul & Pedro Souza & Aureo de Paula, 2023. "Identifying Network Ties from Panel Data: Theory and an application to tax competition," POID Working Papers 081, Centre for Economic Performance, LSE.
      • Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: theory and an application to tax competition," IFS Working Papers WCWP21/23, Institute for Fiscal Studies.
      • Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: theory and an application to tax competition," CeMMAP working papers 02/23, Institute for Fiscal Studies.
      • de Paula, Aureo & Rasul, Imran & Souza, Pedro, 2018. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," CEPR Discussion Papers 12792, C.E.P.R. Discussion Papers.
      • Aureo de Paula & Imran Rasul & Pedro Souza, 2019. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," Papers 1910.07452, arXiv.org, revised Oct 2023.
   2. Federico Martellosio, 2020. "Non-Identifiability in Network Autoregressions," Papers 2011.11084, arXiv.org, revised Jun 2022.
   3. Promit K. Chaudhuri & Sudipta Sarangi & Hector Tzavellas, 2023. "Games Under Network Uncertainty," Papers 2305.03124, arXiv.org, revised Jul 2023.

2. Arthur Lewbel & Samuel Norris & Krishna Pendakur & Xi Qu, 2018. "Consumption Peer Effects and Utility Needs in India," Boston College Working Papers in Economics 958, Boston College Department of Economics, revised 15 Sep 2021.
   • Arthur Lewbel & Samuel Norris & Krishna Pendakur & Xi Qu, 2022. "Consumption peer effects and utility needs in India," Quantitative Economics, Econometric Society, vol. 13(3), pages 1257-1295, July.

   Cited by:

   1. Bramoullé, Y. & Ghiglino, C., 2024. "Status Consumption in Networks: A Reference Dependent Approach," Cambridge Working Papers in Economics 2414, Faculty of Economics, University of Cambridge.
   2. Cheti Nicoletti & Kjell Salvanes & Emma Tominey, 2020. "Mothers Working during Preschool Years and Child Skills: Does Income Compensate," Working Papers 2020-015, Human Capital and Economic Opportunity Working Group.
      • Cheti Nicoletti & Kjell G. Salvanes & Emma Tominey, 2023. "Mothers Working during Preschool Years and Child Skills: Does Income Compensate?," Journal of Labor Economics, University of Chicago Press, vol. 41(2), pages 389-429.
      • Cheti Nicoletti & Kjell Salvanes & Emma Tominey, 2020. "Mothers working during preschool years and child skills. Does income compensate?," CEPEO Working Paper Series 20-08, UCL Centre for Education Policy and Equalising Opportunities, revised Mar 2020.
      • Salvanes, Kjell G & Tominey, Emma & Nicoletti, Cheti, 2020. "Mothers working during preschool years and child skills. Does income compensate?," CEPR Discussion Papers 14749, C.E.P.R. Discussion Papers.
      • Nicoletti, Cheti & Salvanes, Kjell G. & Tominey, Emma, 2020. "Mothers Working during Preschool Years and Child Skills. Does Income Compensate?," IZA Discussion Papers 13079, Institute of Labor Economics (IZA).
      • Cheti Nicoletti & Kjell G. Salvanes & Emma Tominey, 2020. "Mothers working during preschool years and child skills. Does income compensate?," CHILD Working Papers Series 76 JEL Classification: I2, Centre for Household, Income, Labour and Demographic Economics (CHILD) - CCA.
   3. Bramoullé, Y. & Ghiglino, C., 2024. "Status Consumption in Networks: A Reference Dependent Approach," Janeway Institute Working Papers 2409, Faculty of Economics, University of Cambridge.
   4. Kourtellos, Andros & Petrou, Kyriakos, 2022. "The role of social interactions in preferences for redistribution," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 716-737.

Articles

1. 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.

   Cited by:

   1. Levent Kutlu, 2022. "Spatial stochastic frontier model with endogenous weighting matrix," Empirical Economics, Springer, vol. 63(4), pages 1947-1968, October.
   2. Maria Lucia Parrella & Giuseppina Albano & Cira Perna & Michele La Rocca, 2021. "Bootstrap joint prediction regions for sequences of missing values in spatio-temporal datasets," Computational Statistics, Springer, vol. 36(4), pages 2917-2938, December.
   3. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Dec 2023.
   4. Chen, Na & Jin, Xiu, 2023. "Cross-industry asset allocation with the spatial interaction on multiple risk transmission channels," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
   5. HAMAGUCHI Nobuaki & KONDO Keisuke, 2022. "Spatial Gaps in Minimum Wages and Job Search of Young Workers," Discussion papers 22022, Research Institute of Economy, Trade and Industry (RIETI).
   6. Mahyudin Ahmad & Stephen G. Hall, 2023. "The growth effects of economic and political institutions: new evidence from spatial econometrics analysis using historical-based institutional matrix," Economic Change and Restructuring, Springer, vol. 56(2), pages 749-780, April.
   7. Ahmad, Mahyudin & Siong Hook, Law, 2022. "Financial development, institutions, and economic growth nexus: A spatial econometrics analysis using geographical and institutional proximities," MPRA Paper 114471, University Library of Munich, Germany.
   8. Huijuan Xiao & Sheng Bao & Jingzheng Ren & Zhenci Xu & Song Xue & Jianguo Liu, 2024. "Global transboundary synergies and trade-offs among Sustainable Development Goals from an integrated sustainability perspective," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
   9. Rezgar FEIZI & Sahar AMIDI & Thais NUNEZ-ROCHA & Isabelle RABAUD, 2022. "Carbon Tax and Emissions Transfer: a Spatial Analysis," LEO Working Papers / DR LEO 2965, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
   10. Mohamad Adfar & Patta Tope & Muchtar Lutfi, 2022. "Analysis of Resource Ownership of Small Medium Industry and Their Effect on Natural Disaster Preparedness in the Beach Area (Study on SMEs Food Industry Branch)," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 6(02), pages 146-156, February.

2. Yufei Liu & Xi Qu & Wei Wang & Xiaokun Chang, 2020. "Does Population Aging Hinder the Accumulation of Human Capital? Evidence from China," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 15(2), pages 257-281, June.

   Cited by:

   1. Qiling Lu & Jing Hua, 2023. "Micro-Household Human Capital Investment Decisions and a Simulation Study from the Intergenerational Conflict Perspective," IJERPH, MDPI, vol. 20(3), pages 1-21, January.

3. Guo, Juncong & Qu, Xi, 2020. "Fixed effects spatial panel data models with time-varying spatial dependence," Economics Letters, Elsevier, vol. 196(C).

   Cited by:

   1. 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).

4. Zhao, Chuanmin & Qu, Xi & Luo, Shougui, 2019. "Impact of the InnoCom program on corporate innovation performance in China: Evidence from Shanghai," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 103-118.

   Cited by:

   1. Zhang, Dongyang & Guo, Rui & He, Xiaodan, 2022. "How does the exclusive license stimulate firm’s subsequent innovation? The role of innovation financial input," Research in International Business and Finance, Elsevier, vol. 60(C).
   2. Maoyan She & Die Hu & Yuandi Wang & Li Li, 2023. "How do top management team characteristics affect government R&D subsidy grants? Evidence from an information economics perspective," Asian Business & Management, Palgrave Macmillan, vol. 22(1), pages 330-353, February.

5. Guo, Juncong & Qu, Xi, 2019. "Spatial interactive effects on housing prices in Shanghai and Beijing," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 147-160.

   Cited by:

   1. Ling Li & Fangzhou Xia, 2023. "City subcenter as a regional development policy: Impact on the property market," Journal of Regional Science, Wiley Blackwell, vol. 63(3), pages 643-673, June.
   2. Lulin Xu & Zhongwu Li, 2021. "A New Appraisal Model of Second-Hand Housing Prices in China’s First-Tier Cities Based on Machine Learning Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 617-637, February.
   3. Fan, Ying & Fu, Yuqi & Yang, Zan, 2024. "Door-in-the-face heuristics: Intermediaries’ diversion in rental markets," Working Paper Series 24/2, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
   4. Gabriel S. Lee & Stefanie Braun, 2021. "Agglomeration Spillover Effects in German Land and House Prices at the City and County Levels," Working Papers 207, Bavarian Graduate Program in Economics (BGPE).
   5. Yang, Zhenbing & Chen, Zhuo & Shao, Shuai & Yang, Lili, 2022. "Can housing price regulation improve R&D performance in universities? Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
   6. Chen, Jie & Chen, Yu & Hill, Robert J. & Hu, Pei, 2022. "The user cost of housing and the price-rent ratio in Shanghai," Regional Science and Urban Economics, Elsevier, vol. 92(C).
      • Jie Chen & Yu Chen & Robert J. Hill & Pei Hu, 2020. "The User Cost of Housing and the Price-Rent Ratio in Shanghai," Graz Economics Papers 2020-19, University of Graz, Department of Economics.
   7. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2021. "Time-varying inter-urban housing price spillovers in China: Causes and consequences," Journal of Asian Economics, Elsevier, vol. 77(C).
   8. Yunlong Gong & Jan de Haan & Peter Boelhouwer, 2020. "Cross‐city spillovers in Chinese housing markets: From a city network perspective," Papers in Regional Science, Wiley Blackwell, vol. 99(4), pages 1065-1085, August.
   9. Ling Li & Wayne Xinwei Wan & Shenjing He, 2021. "The Heightened ‘Security Zone’ Function of Gated Communities during the COVID-19 Pandemic and the Changing Housing Market Dynamic: Evidence from Beijing, China," Land, MDPI, vol. 10(9), pages 1-21, September.
   10. Sisman, S. & Aydinoglu, A.C., 2022. "A modelling approach with geographically weighted regression methods for determining geographic variation and influencing factors in housing price: A case in Istanbul," Land Use Policy, Elsevier, vol. 119(C).
   11. Fan, Ying & Fu, Yuqi & Yang, Zan & Chen, Ming, 2023. "Search Frictions in Rental Markets: Evidence from Urban China," Working Paper Series 23/11, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.

6. Yang, Chao & Lee, Lung-fei & Qu, Xi, 2018. "Tobit models with social interactions: Complete vs incomplete information," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 30-50.

   Cited by:

   1. Xuanzhi Yang & Zhaofang Zhang & Wei Luo & Zhen Tang & Xin Gao & Zhongchi Wan & Xin Zhang, 2019. "The Impact of Government Role on High-Quality Innovation Development in Mainland China," Sustainability, MDPI, vol. 11(20), pages 1-19, October.

7. 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.

   Cited by:

   1. Jieun Lee, 2022. "Testing Endogeneity of Spatial Weights Matrices in Spatial Dynamic Panel Data Models," Papers 2209.05563, arXiv.org.
   2. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
   3. Guido M. Kuersteiner & Ingmar R. Prucha, 2015. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," CESifo Working Paper Series 5445, CESifo.
      • 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.
   4. 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.
   5. Bera Anil K. & Doğan Osman & Taşpınar Süleyman, 2019. "Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-33, January.
   6. Jie Liu & Chao Bi, 2019. "Effects of Higher Education Levels on Total Factor Productivity Growth," Sustainability, MDPI, vol. 11(6), pages 1-12, March.
   7. Lee, Jiyon, 2018. "A spatial latent class model," Economics Letters, Elsevier, vol. 162(C), pages 62-68.
   8. Giuseppe Arbia & Anil K. Bera & Osman Doğan & Süleyman Taşpınar, 2020. "Testing Impact Measures in Spatial Autoregressive Models," International Regional Science Review, , vol. 43(1-2), pages 40-75, January.
   9. Li, Jianan & Han, Xiaoyi, 2019. "Bayesian Lassos for spatial durbin error model with smoothness prior: Application to detect spillovers of China's treaty ports," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 38-74.
   10. Monica Billio & Massimiliano Caporin & Lorenzo Frattarolo & Loriana Pelizzon, 2016. "Networks in risk spillovers: a multivariate GARCH perspective," Working Papers 2016:03, Department of Economics, University of Venice "Ca' Foscari".
       • Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2023. "Networks in risk spillovers: A multivariate GARCH perspective," Econometrics and Statistics, Elsevier, vol. 28(C), pages 1-29.
       • Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2018. "Networks in risk spillovers: A multivariate GARCH perspective," SAFE Working Paper Series 225, Leibniz Institute for Financial Research SAFE.
       • Monica Billio & Massimiliano Caporin & Lorenzo Frattarolo & Loriana Pelizzon, 2020. "Networks in risk spillovers: A multivariate GARCH perspective," Working Papers 2020:16, Department of Economics, University of Venice "Ca' Foscari".
   11. Ye Yang & Osman Doğan & Süleyman Taşpınar, 2023. "Observed-data DIC for spatial panel data models," Empirical Economics, Springer, vol. 64(3), pages 1281-1314, March.
   12. Ma, Yingying & Guo, Shaojun & Wang, Hansheng, 2023. "Sparse spatio-temporal autoregressions by profiling and bagging," Journal of Econometrics, Elsevier, vol. 232(1), pages 132-147.
   13. 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.
   14. 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.
   15. Danqing Chen & Jianbao Chen & Shuangshuang Li, 2021. "Instrumental Variable Quantile Regression of Spatial Dynamic Durbin Panel Data Model with Fixed Effects," Mathematics, MDPI, vol. 9(24), pages 1-24, December.
   16. Xiaoling Wang & Hongling Yu & Peng Lv & Cheng Wang & Jun Zhang & Jia Yu, 2019. "Seepage Safety Assessment of Concrete Gravity Dam Based on Matter-Element Extension Model and FDA," Energies, MDPI, vol. 12(3), pages 1-21, February.
   17. Pouliot, Guillaume Allaire, 2023. "Spatial econometrics for misaligned data," Journal of Econometrics, Elsevier, vol. 232(1), pages 168-190.
   18. Jeong, Hanbat & Lee, Lung-fei, 2021. "Spatial dynamic game models for coevolution of intertemporal economic decision-making and spatial networks," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
   19. Kong, Wei & Yang, Kai, 2021. "Efficient GMM estimation of a spatial autoregressive model with an endogenous spatial weights matrix," Economics Letters, Elsevier, vol. 208(C).
   20. Huijuan Xiao & Sheng Bao & Jingzheng Ren & Zhenci Xu & Song Xue & Jianguo Liu, 2024. "Global transboundary synergies and trade-offs among Sustainable Development Goals from an integrated sustainability perspective," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
   21. Guillaume Allaire Pouliot, 2022. "Spatial Econometrics for Misaligned Data," Papers 2207.04082, arXiv.org.
   22. 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).

8. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.

   Cited by:

   1. Gao, Min & Yang, Wenzhi & Wu, Shipeng & Yu, Wei, 2022. "Asymptotic normality of residual density estimator in stationary and explosive autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
   2. Jungyoon Lee & Peter C.B. Phillips & Francesca Rossi, 2020. "Consistent Misspecification Testing in Spatial Autoregressive Models," Cowles Foundation Discussion Papers 2256, Cowles Foundation for Research in Economics, Yale University.
   3. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.
   4. Sun, Yiguo & Malikov, Emir, 2017. "Estimation and Inference in Functional-Coefficient Spatial Autoregressive Panel Data Models with Fixed Effects," MPRA Paper 83671, University Library of Munich, Germany.
      • Sun, Yiguo & Malikov, Emir, 2018. "Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 203(2), pages 359-378.
   5. Liu, Li & Bu, Ruijun & Pan, Zhiyuan & Xu, Yuhua, 2019. "Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test," Economic Modelling, Elsevier, vol. 81(C), pages 124-135.
   6. Lu, Xun & Su, Liangjun, 2020. "Determining individual or time effects in panel data models," Journal of Econometrics, Elsevier, vol. 215(1), pages 60-83.

9. Xi Qu & Xiaoliang Wang & Lung‐fei Lee, 2016. "Instrumental variable estimation of a spatial dynamic panel model with endogenous spatial weights when T is small," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 261-290, October.

   Cited by:

   1. Sebastian Langer, 2019. "Expenditure interactions between municipalities and the role of agglomeration forces: a spatial analysis for North Rhine-Westphalia," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 497-527, June.
   2. 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.
   3. Bera Anil K. & Doğan Osman & Taşpınar Süleyman, 2019. "Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-33, January.
   4. Lee, Jiyon, 2018. "A spatial latent class model," Economics Letters, Elsevier, vol. 162(C), pages 62-68.
   5. Chen, Xin & Xuan, Chao & Qiu, Rui, 2021. "Understanding spatial spillover effects of airports on economic development: New evidence from China’s hub airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 143(C), pages 48-60.
   6. Ioannis Skevas, 2023. "A novel modeling framework for quantifying spatial spillovers on total factor productivity growth and its components," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1221-1247, August.
   7. Li, Liyao & Yang, Zhenlin, 2018. "Spatial Dynamic Panel Data Models with Correlated Random Effects," Economics and Statistics Working Papers 15-2018, Singapore Management University, School of Economics.
      • Li, Liyao & Yang, Zhenlin, 2021. "Spatial dynamic panel data models with correlated random effects," Journal of Econometrics, Elsevier, vol. 221(2), pages 424-454.
   8. 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.
   9. 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.
   10. Massimiliano Cerciello, 2021. "Spatial patterns in food waste at the local level. A preliminary analysis for Italian data," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 83-101, February.
   11. T. M. Tonmoy Islam, 2020. "The impact of population agglomeration of an area on its neighbors: evidence from the USA," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(1), pages 1-26, August.
   12. Huijuan Xiao & Sheng Bao & Jingzheng Ren & Zhenci Xu & Song Xue & Jianguo Liu, 2024. "Global transboundary synergies and trade-offs among Sustainable Development Goals from an integrated sustainability perspective," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

10. 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.

    Cited by:

    1. Maria Adelaida Lopera & Steeve Marchand, 2017. "Peer effects and risk-taking among entrepreneurs: Lab-in-the-field evidence," Working Papers PIERI 2017-21, PEP-PIERI.
       • Steeve Marchand & Maria Adelaida Lopera, 2017. "Peer Effects and Risk-Taking Among Entrepreneurs: Lab-in-the-Field Evidence," Cahiers de recherche 1703, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
       • Lopera, Maria Adelaida & Marchand, Steeve, 2018. "Peer effects and risk-taking among entrepreneurs: Lab-in-the-field evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 182-201.
    2. Gupta, A & Robinson, PM, 2015. "Pseudo Maximum Likelihood Estimation of Spatial Autoregressive Models with Increasing Dimension," Economics Discussion Papers 22698, University of Essex, Department of Economics.
       • Gupta, Abhimanyu & Robinson, Peter M., 2017. "Pseudo maximum likelihood estimation of spatial autoregressive models with increasing dimension," LSE Research Online Documents on Economics 84085, London School of Economics and Political Science, LSE Library.
       • Gupta, Abhimanyu & Robinson, Peter M., 2018. "Pseudo maximum likelihood estimation of spatial autoregressive models with increasing dimension," Journal of Econometrics, Elsevier, vol. 202(1), pages 92-107.
    3. Ana Angulo & Peter Burridge & Jes�s Mur, 2017. "Testing for breaks in the weighting matrix," Documentos de Trabajo dt2017-01, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
       • Angulo, Ana & Burridge, Peter & Mur, Jesús, 2018. "Testing for breaks in the weighting matrix," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 115-129.
    4. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2019. "Peer Effects in Networks: a Survey," Working Papers halshs-02440709, HAL.
       • Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2020. "Peer Effects in Networks: A Survey," IZA Discussion Papers 12947, Institute of Labor Economics (IZA).
       • Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
       • Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2019. "Peer Effects in Networks: a Survey," CEPR Discussion Papers 14260, C.E.P.R. Discussion Papers.
       • Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: a Survey," AMSE Working Papers 1936, Aix-Marseille School of Economics, France.
       • Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," CIRANO Working Papers 2020s-02, CIRANO.
       • Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Post-Print hal-03072119, HAL.
    5. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers CWP52/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
       • Áureo de Paula, 2016. "Econometrics of network models," CeMMAP working papers 06/16, Institute for Fiscal Studies.
       • Áureo de Paula, 2016. "Econometrics of network models," CeMMAP working papers CWP06/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
       • Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers 52/15, Institute for Fiscal Studies.
    6. Qin, Quande & Yu, Ying & Liu, Yuan & Zhou, Jianqing & Chen, Xiude, 2023. "Industrial agglomeration and energy efficiency: A new perspective from market integration," Energy Policy, Elsevier, vol. 183(C).
    7. 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.
    8. 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.
    9. Chen, Na & Jin, Xiu, 2023. "Cross-industry asset allocation with the spatial interaction on multiple risk transmission channels," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    10. Patacchini, Eleonora & Bisin, Alberto, 2019. "Dynamic Social Interactions and Health Risk Behavior," CEPR Discussion Papers 13918, C.E.P.R. Discussion Papers.
        • Tiziano Arduini & Alberto Bisin & Onur Özgür & Eleonora Patacchini, 2019. "Dynamic Social Interactions and Health Risk Behavior," NBER Working Papers 26223, National Bureau of Economic Research, Inc.
    11. Vincent Boucher, 2014. "Conformism and Self-Selection in Social Networks," Cahiers de recherche 1424, CIRPEE.
        • Boucher, Vincent, 2016. "Conformism and self-selection in social networks," Journal of Public Economics, Elsevier, vol. 136(C), pages 30-44.
        • Vincent Boucher, 2014. "Conformism and Self-Selection in Social Networks," Cahiers de recherche 1402, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    12. HAMAGUCHI Nobuaki & KONDO Keisuke, 2022. "Spatial Gaps in Minimum Wages and Job Search of Young Workers," Discussion papers 22022, Research Institute of Economy, Trade and Industry (RIETI).
    13. Dubey, Subodh & Sharma, Ishant & Mishra, Sabyasachee & Cats, Oded & Bansal, Prateek, 2022. "A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 63-95.
    14. Marcos-Martinez, Raymundo & Measham, Thomas G. & Fleming-Muñoz, David A., 2019. "Economic impacts of early unconventional gas mining: Lessons from the coal seam gas industry in New South Wales, Australia," Energy Policy, Elsevier, vol. 125(C), pages 338-346.
    15. Nicolas Debarsy & James Lesage, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Post-Print halshs-03319303, HAL.
        • Debarsy, Nicolas & LeSage, James, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 48-68.
    16. Glass, Anthony J. & Kenjegaliev, Amangeldi & Kenjegalieva, Karligash, 2020. "Spatial scale and product mix economies in U.S. banking with simultaneous spillover regimes," European Journal of Operational Research, Elsevier, vol. 284(2), pages 693-711.
    17. Giuseppe Arbia & Anil K. Bera & Osman Doğan & Süleyman Taşpınar, 2020. "Testing Impact Measures in Spatial Autoregressive Models," International Regional Science Review, , vol. 43(1-2), pages 40-75, January.
    18. Konstantinidi, Antri & Kourtellos, Andros & Sun, Yiguo, 2023. "Social threshold regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2057-2081.
    19. Sun, Yiguo, 2016. "Functional-coefficient spatial autoregressive models with nonparametric spatial weights," Journal of Econometrics, Elsevier, vol. 195(1), pages 134-153.
    20. Liu, Xiaodong & Prucha, Ingmar R., 2018. "A robust test for network generated dependence," Journal of Econometrics, Elsevier, vol. 207(1), pages 92-113.
    21. 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.
    22. 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.
        • 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.
    23. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    24. Xu, Xingbai & Lee, Lung-fei, 2015. "Maximum likelihood estimation of a spatial autoregressive Tobit model," Journal of Econometrics, Elsevier, vol. 188(1), pages 264-280.
    25. Li, Kunpeng, 2017. "Fixed-effects dynamic spatial panel data models and impulse response analysis," Journal of Econometrics, Elsevier, vol. 198(1), pages 102-121.
    26. 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.
    27. Hoshino, Tadao, 2022. "Sieve IV estimation of cross-sectional interaction models with nonparametric endogenous effect," Journal of Econometrics, Elsevier, vol. 229(2), pages 263-275.
    28. Vincent Boucher & Finagnon A. Dedewanou & Arnaud Dufays, 2018. "Peer-Induced Beliefs Regarding College Participation," Cahiers de recherche 1817, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    29. 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.
    30. Rainone, Edoardo, 2020. "The network nature of over-the-counter interest rates," Journal of Financial Markets, Elsevier, vol. 47(C).
    31. 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.
    32. Wang, Wei & Lee, Lung-Fei & Bao, Yan, 2018. "GMM estimation of the spatial autoregressive model in a system of interrelated networks," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 167-198.
    33. Krisztin, Tamás, 2018. "Semi-parametric spatial autoregressive models in freight generation modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 121-143.
    34. Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
    35. Diemer, Andreas, 2022. "Endogenous peer effects in diverse friendship networks: Evidence from Swedish classrooms," Economics of Education Review, Elsevier, vol. 89(C).
    36. Subodh Dubey & Ishant Sharma & Sabyasachee Mishra & Oded Cats & Prateek Bansal, 2021. "A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles," Papers 2109.06169, arXiv.org.
    37. Lina Zhang, 2020. "Spillovers of Program Benefits with Missing Network Links," Papers 2009.09614, arXiv.org, revised Apr 2023.
    38. Desbordes, Rodolphe, 2021. "Spatial dynamics of major infectious diseases outbreaks: A global empirical assessment," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    39. 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.
    40. Boucher, Vincent & Dedewanou, F. Antoine & Dufays, Arnaud, 2022. "Peer-induced beliefs regarding college participation," Economics of Education Review, Elsevier, vol. 90(C).
    41. Xiaowen Dai & Shidan Huang & Libin Jin & Maozai Tian, 2023. "Wild Bootstrap-Based Bias Correction for Spatial Quantile Panel Data Models with Varying Coefficients," Mathematics, MDPI, vol. 11(9), pages 1-16, April.
    42. Debarsy, Nicolas & Yang, Zhenlin, 2018. "Editorial for the special issue entitled: New advances in spatial econometrics: Interactions matter," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 1-5.
    43. Glass, Anthony J. & Kenjegalieva, Karligash & Douch, Mustapha, 2020. "Uncovering spatial productivity centers using asymmetric bidirectional spillovers," European Journal of Operational Research, Elsevier, vol. 285(2), pages 767-788.
    44. Kong, Wei & Yang, Kai, 2021. "Efficient GMM estimation of a spatial autoregressive model with an endogenous spatial weights matrix," Economics Letters, Elsevier, vol. 208(C).
    45. Adriana Lleras-Muney & Matthew Miller & Shuyang Sheng & Veronica Sovero, 2022. "Party On: The Labor Market Returns to Social Networks in Adolescence," Papers 2210.09426, arXiv.org, revised Mar 2024.
    46. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).
    47. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin & Jiang, Hongdian, 2022. "How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China," Energy Economics, Elsevier, vol. 105(C).
    48. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    49. 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).
    50. Glass, Anthony J. & Kenjegalieva, Karligash, 2019. "A spatial productivity index in the presence of efficiency spillovers: Evidence for U.S. banks, 1992–2015," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1165-1179.

11. Qu, Xi & Lee, Lung-fei, 2013. "Locally most powerful tests for spatial interactions in the simultaneous SAR Tobit model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 307-321.

    Cited by:

    1. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
    2. 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.
    3. Ievoli Corrado & Belliggiano Angelo & Basile Roberto Giovanni, 2017. "The Spatial Patterns of Dairy Farming In Molise," European Countryside, Sciendo, vol. 9(4), pages 729-745, December.
    4. Yang, Chao & Lee, Lung-fei & Qu, Xi, 2018. "Tobit models with social interactions: Complete vs incomplete information," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 30-50.
    5. Bera Anil K. & Doğan Osman & Taşpınar Süleyman, 2019. "Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-33, January.
    6. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    7. Kim, Changjoo & Parent, Olivier, 2016. "Modeling individual travel behaviors based on intra-household interactions," Regional Science and Urban Economics, Elsevier, vol. 57(C), pages 1-11.
    8. Xu, Xingbai & Lee, Lung-fei, 2018. "Sieve maximum likelihood estimation of the spatial autoregressive Tobit model," Journal of Econometrics, Elsevier, vol. 203(1), pages 96-112.
    9. Helen Naughton & Pehr-Johan Norbäck & Ayça Tekin-Koru, 2016. "Aggregation Issues of Foreign Direct Investment Estimation in an Interdependent World," The World Economy, Wiley Blackwell, vol. 39(12), pages 2046-2073, December.
    10. Xu, Xingbai & Lee, Lung-fei, 2015. "Maximum likelihood estimation of a spatial autoregressive Tobit model," Journal of Econometrics, Elsevier, vol. 188(1), pages 264-280.
    11. Wan, Qunchao & Chen, Jin & Yao, Zhu & Yuan, Ling, 2022. "Preferential tax policy and R&D personnel flow for technological innovation efficiency of China's high-tech industry in an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    12. Wei Cheng, 2022. "Consistent EM algorithm for a spatial autoregressive probit model," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-23, December.
    13. Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.
    14. Xu, Xingbai & Lee, Lung-fei, 2015. "A spatial autoregressive model with a nonlinear transformation of the dependent variable," Journal of Econometrics, Elsevier, vol. 186(1), pages 1-18.
    15. Hsieh, Chih-Sheng & Lin, Xu, 2017. "Gender and racial peer effects with endogenous network formation," Regional Science and Urban Economics, Elsevier, vol. 67(C), pages 135-147.

12. Qu, Xi & Lee, Lung-fei, 2012. "LM tests for spatial correlation in spatial models with limited dependent variables," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 430-445.

    Cited by:

    1. Ying Han & Baoling Jin & Xiaoyuan Qi & Huasen Zhou, 2021. "Influential Factors and Spatiotemporal Characteristics of Carbon Intensity on Industrial Sectors in China," IJERPH, MDPI, vol. 18(6), pages 1-18, March.
    2. Qu, Xi & Lee, Lung-fei, 2013. "Locally most powerful tests for spatial interactions in the simultaneous SAR Tobit model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 307-321.
    3. T. Arduini, 2016. "Distribution Free Estimation of Spatial Autoregressive Binary Choice Panel Data Models," Working Papers wp1052, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Claudine Desrieux & Romain Espinosa & Michael Visser, 2022. "Simultaneous Decision Making of Juries: Evidence From the Paris Labor Court," CIRED Working Papers hal-04104190, HAL.
       • Claudine Desrieux & Romain Espinosa & Michael Visser, 2022. "Simultaneous Decision Making of Juries: Evidence From the Paris Labor Court," Working Papers hal-04104190, HAL.
    5. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
    6. Taupo, Tauisi & Cuffe, Harold & Noy, Ilan, 2016. "Household vulnerability on the frontline of climate change: The Pacific atoll nation of Tuvalu," Working Paper Series 19500, Victoria University of Wellington, School of Economics and Finance.
       • Tauisi Taupo & Harold Cuffe & Ilan Noy, 2016. "Household Vulnerability on the Frontline of Climate Change: The Pacific Atoll Nation of Tuvalu," CESifo Working Paper Series 6128, CESifo.
       • Tauisi Taupo & Harold Cuffe & Ilan Noy, 2018. "Household vulnerability on the frontline of climate change: the Pacific atoll nation of Tuvalu," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(4), pages 705-739, October.
    7. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    8. Xu, Xingbai & Lee, Lung-fei, 2018. "Sieve maximum likelihood estimation of the spatial autoregressive Tobit model," Journal of Econometrics, Elsevier, vol. 203(1), pages 96-112.
    9. Xu, Xingbai & Lee, Lung-fei, 2015. "Maximum likelihood estimation of a spatial autoregressive Tobit model," Journal of Econometrics, Elsevier, vol. 188(1), pages 264-280.
    10. Heijnen, P. & Samarina, A.. & Jacobs, J.P.A.M. & Elhorst, J.P., 2013. "State transfers at different moments in time," Research Report 13006-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    11. Ming He & Kuan-Pin Lin, 2015. "Testing in a Random Effects Panel Data Model with Spatially Correlated Error Components and Spatially Lagged Dependent Variables," Econometrics, MDPI, vol. 3(4), pages 1-36, November.
    12. Yang, Kai & Lee, Lung-fei, 2017. "Identification and QML estimation of multivariate and simultaneous equations spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 196(1), pages 196-214.
    13. 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.
    14. He, Ming & Lin, Kuan-Pin, 2013. "Locally adjusted LM test for spatial dependence in fixed effects panel data models," Economics Letters, Elsevier, vol. 121(1), pages 59-63.
    15. 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.
    16. Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.
    17. He, Ming & Lin, Kuan-Pin, 2015. "Testing spatial effects and random effects in a nested panel data model," Economics Letters, Elsevier, vol. 135(C), pages 85-91.
    18. Guo, Juncong & Qu, Xi, 2022. "Competition in household human capital investments: Strength, motivations and consequences," Journal of Development Economics, Elsevier, vol. 158(C).
    19. Lei, J., 2014. "Essays on nonlinear panel data models," Other publications TiSEM 302d1ae7-0310-43b0-b253-6, Tilburg University, School of Economics and Management.

13. Qu, Xi & de Jong, Robert, 2012. "Sums Of Exponentials Of Random Walks With Drift," Econometric Theory, Cambridge University Press, vol. 28(4), pages 915-924, August.

    Cited by:

    1. Zadourian, Rubina & Klümper, Andreas, 2018. "Exact probability distribution function for the volatility of cumulative production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 59-66.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (3) 2015-12-28 2020-05-25 2021-02-15
2. NEP-URE: Urban and Real Estate Economics (2) 2015-12-28 2020-05-25
3. NEP-ETS: Econometric Time Series (1) 2015-12-28
4. NEP-NET: Network Economics (1) 2020-05-25
5. NEP-SEA: South East Asia (1) 2015-12-28
6. NEP-SOC: Social Norms and Social Capital (1) 2020-05-25

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