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An extension of Kelejian's J-test for non-nested spatial models

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  • Kelejian, Harry H.
  • Piras, Gianfranco

Abstract

In 2008 Kelejian extended the J-test procedure to a spatial framework. In that paper he considered a null model which could, but need not, contain spatial lags in both the dependent variable and disturbance term. Under the alternative, he considered one or more non-nested spatial models which could, but need not, also contain spatial lags. Although his suggested test was computationally simple and intuitive, it did not use the available information in an efficient manner. In this paper we suggest a modification of Kelejian's J-test which uses the available information in a more efficient way. We give large sample, as well as small sample Monte Carlo results. Perhaps counter to intuition, we also demonstrate that the "J-test procedure" cannot be used to establish a test for the structure of the error term.

Suggested Citation

  • Kelejian, Harry H. & Piras, Gianfranco, 2011. "An extension of Kelejian's J-test for non-nested spatial models," Regional Science and Urban Economics, Elsevier, vol. 41(3), pages 281-292, May.
  • Handle: RePEc:eee:regeco:v:41:y:2011:i:3:p:281-292
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    References listed on IDEAS

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    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
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    Cited by:

    1. Masayoshi Hayashi & Wataru Yamamoto, 2017. "Information sharing, neighborhood demarcation, and yardstick competition: an empirical analysis of intergovernmental expenditure interaction in Japan," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 24(1), pages 134-163, February.
    2. Miguel A. Delgado & Peter M Robinson, 2013. "Non-Nested Testing of Spatial Correlation," STICERD - Econometrics Paper Series 568, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Burridge, Peter, 2011. "A research agenda on general-to-specific spatial model search," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 71-90.
    4. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    5. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves, 2013. "Peer Effects: Social Multiplier or Social Norms?," CEPR Discussion Papers 9366, C.E.P.R. Discussion Papers.
    6. Marcos Herrera & Jesus Mur & Manuel Ruiz-Marin, 2017. "A Comparison Study on Criteria to Select the Most Adequate Weighting Matrix," Working Papers 18, Instituto de Estudios Laborales y del Desarrollo Económico (IELDE) - Universidad Nacional de Salta - Facultad de Ciencias Económicas, Jurídicas y Sociales.
    7. Han, Xiaoyi & Lee, Lung-fei, 2013. "Model selection using J-test for the spatial autoregressive model vs. the matrix exponential spatial model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 250-271.
    8. Harry H. Kelejian & Gianfranco Piras, 2016. "A J test for dynamic panel model with fixed effects, and nonparametric spatial and time dependence," Empirical Economics, Springer, vol. 51(4), pages 1581-1605, December.
    9. Seya, Hajime & Yamagata, Yoshiki & Tsutsumi, Morito, 2013. "Automatic selection of a spatial weight matrix in spatial econometrics: Application to a spatial hedonic approach," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 429-444.
    10. Jin, Fei & Lee, Lung-fei, 2015. "On the bootstrap for Moran’s I test for spatial dependence," Journal of Econometrics, Elsevier, vol. 184(2), pages 295-314.
    11. Sun, Yiguo, 2016. "Functional-coefficient spatial autoregressive models with nonparametric spatial weights," Journal of Econometrics, Elsevier, vol. 195(1), pages 134-153.
    12. Nicolas Debarsy & Cem Ertur, 2016. "Interaction matrix selection in spatial econometrics with an application to growth theory," Working Papers halshs-01278545, HAL.
    13. repec:cep:stiecm:/2013/568 is not listed on IDEAS
    14. Delgado, Miguel A. & Robinson, Peter M., 2013. "Non-nested testing of spatial correlation," LSE Research Online Documents on Economics 58169, London School of Economics and Political Science, LSE Library.
    15. Delgado, Miguel A. & Robinson, Peter, 2015. "Non-nested testing of spatial correlation," LSE Research Online Documents on Economics 61433, London School of Economics and Political Science, LSE Library.
    16. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves, 2014. "Endogenous peer effects: local aggregate or local average?," Journal of Economic Behavior & Organization, Elsevier, vol. 103(C), pages 39-59.
    17. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves, 2011. "Peer Effects in Education, Sport, and Screen Activities: Local Aggregate or Local Average?," CEPR Discussion Papers 8477, C.E.P.R. Discussion Papers.
    18. Delgado, Miguel A. & Robinson, Peter M., 2015. "Non-nested testing of spatial correlation," Journal of Econometrics, Elsevier, vol. 187(1), pages 385-401.
    19. Jin, Fei & Lee, Lung-fei, 2013. "Cox-type tests for competing spatial autoregressive models with spatial autoregressive disturbances," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 590-616.
    20. repec:rri:wpaper:201301 is not listed on IDEAS

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