IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v55y2018i1d10.1007_s00181-017-1414-3.html
   My bibliography  Save this article

Important overlooked IVs in spatial models

Author

Listed:
  • Harry H. Kelejian

    (University of Maryland College Park)

  • Gianfranco Piras

    (The Catholic University of America)

Abstract

Spatial models often contain additional endogenous variables as regressors. The complete system determining these variables is typically not known to the researcher, and so maximum likelihood or Bayesian estimation methods are precluded. This leaves instrumental variable estimation. In all likelihood, the system may contain certain forms of nonlinearities. These nonlinearities might arise because of endogenous weighting matrices, functional form differences in the endogenous variables, etc. The existence of such nonlinearities strongly suggests the use of nonlinear forms of the instruments. Issues of this sort were pointed out in Kelejian and Piras (Spatial econometrics, Elsevier, Amsterdam, 2017) and Kelejian (Lett Spat Resour Sci 9(1):113–136, 2016). However, thus far Monte Carlo results relating to efficiencies gained by the use of nonlinear instrumental variables are not available. This is unfortunate because these efficiencies can be quite extensive. The purpose of this paper is to fill this void.

Suggested Citation

  • Harry H. Kelejian & Gianfranco Piras, 2018. "Important overlooked IVs in spatial models," Empirical Economics, Springer, vol. 55(1), pages 69-83, August.
    • Handle: RePEc:spr:empeco:v:55:y:2018:i:1:d:10.1007_s00181-017-1414-3
    DOI: 10.1007/s00181-017-1414-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-017-1414-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-017-1414-3?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. Bernard Fingleton, 2008. "A Generalized Method of Moments Estimator for a Spatial Panel Model with an Endogenous Spatial Lag and Spatial Moving Average Errors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(1), pages 27-44.
    2. Mukerji, Purba, 2009. "Ready for capital account convertibility?," Journal of International Money and Finance, Elsevier, vol. 28(6), pages 1006-1021, October.
    3. 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.
    4. Jeanty, P. Wilner & Partridge, Mark & Irwin, Elena, 2010. "Estimation of a spatial simultaneous equation model of population migration and housing price dynamics," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 343-352, September.
    5. Bernard Fingleton & Julie Le Gallo, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 319-339, August.
    6. Julie Le Gallo & Bernard Fingleton, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances : finite sample properties," Post-Print hal-00485035, HAL.
    7. Harry H. Kelejian & Gianfranco Piras, 2016. "An Extension of the J‐Test to a Spatial Panel Data Framework," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 387-402, March.
    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. Harry Kelejian & Gianfranco Piras, 2020. "Spillover effects in spatial models: Generalizations and extensions," Journal of Regional Science, Wiley Blackwell, vol. 60(3), pages 425-442, June.
    2. Bernard Fingleton, 2023. "Estimating dynamic spatial panel data models with endogenous regressors using synthetic instruments," Journal of Geographical Systems, Springer, vol. 25(1), pages 121-152, January.

    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. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    2. Marius C. O. Amba & Taoufiki Mbratana & Julie Gallo, 2023. "Spatial panel simultaneous equations models with error components," Empirical Economics, Springer, vol. 65(3), pages 1149-1196, September.
    3. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2014. "Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices," Journal of Urban Economics, Elsevier, vol. 80(C), pages 76-86.
    4. Gianfranco Piras, 2013. "Efficient GMM Estimation of a Cliff and Ord Panel Data Model with Random Effects," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 370-388, September.
    5. Bernard Fingleton & Manfred Fischer, 2010. "Neoclassical theory versus new economic geography: competing explanations of cross-regional variation in economic development," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(3), pages 467-491, June.
    6. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.
    7. You, Jing & Nie, Huihua, 2017. "Who determines Chinese firms' engagement in corruption: Themselves or neighbors?," China Economic Review, Elsevier, vol. 43(C), pages 29-46.
    8. Arbués, Pelayo & Baños, José F. & Mayor, Matías, 2015. "The spatial productivity of transportation infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 166-177.
    9. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    10. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    11. Elena G. Irwin & P. Wilner Jeanty & Mark D. Partridge, 2014. "Amenity Values versus Land Constraints: The Spatial Effects of Natural Landscape Features on Housing Values," Land Economics, University of Wisconsin Press, vol. 90(1), pages 61-78.
    12. Fingleton, Bernard & Palombi, Silvia, 2013. "Spatial panel data estimation, counterfactual predictions, and local economic resilience among British towns in the Victorian era," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 649-660.
    13. Yongqing Nan & Qin Li & Jinxiang Yu & Haiya Cai & Qin Zhou, 2020. "Has the emissions intensity of industrial sulphur dioxide converged? New evidence from China’s prefectural cities with dynamic spatial panel models," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5337-5369, August.
    14. 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.
    15. P. Wilner Jeanty, 2012. "Stata implementation of the non-parametric spatial heteroskedasticity and autocorrelation consistent estimator," SAN12 Stata Conference 24, Stata Users Group.
    16. Bernard Fingleton, 2023. "Estimating dynamic spatial panel data models with endogenous regressors using synthetic instruments," Journal of Geographical Systems, Springer, vol. 25(1), pages 121-152, January.
    17. Marrocu, Emanuela & Paci, Raffaele, 2011. "They arrive with new information. Tourism flows and production efficiency in the European regions," Tourism Management, Elsevier, vol. 32(4), pages 750-758.
    18. Quentin Frère & Matthieu Leprince & Sonia Paty, 2014. "The Impact of Intermunicipal Cooperation on Local Public Spending," Urban Studies, Urban Studies Journal Limited, vol. 51(8), pages 1741-1760, June.
    19. Badi H. Baltagi & Georges Bresson & Jean‐Michel Etienne, 2015. "Hedonic Housing Prices in Paris: An Unbalanced Spatial Lag Pseudo‐Panel Model with Nested Random Effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 509-528, April.
    20. Fuess, Roland & Lerbs, Oliver, 2017. "Do Local Governments Tax Homeowner Communities Differently?," Working Papers on Finance 1714, University of St. Gallen, School of Finance.

    More about this item

    Keywords

    Spatial econometrics; Nonlinear IV; Endogeneity;
    All these keywords.

    JEL classification:

    • 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
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

    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:spr:empeco:v:55:y:2018:i:1:d:10.1007_s00181-017-1414-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.