IDEAS home Printed from https://ideas.repec.org/p/ipe/ipetds/0154.html
   My bibliography  Save this paper

Estimation of Multiequation Cross-section Models in the Presence of Spatial Autocorrelation

Author

Listed:
  • Alexandre Carvalho
  • Daniel da Mata
  • Kenneth M. Chomitz

Abstract

We describe econometric techniques to treat spatial autocorrelation in multiequation cross-section models. The cross-section approaches discussed here are heavily based on the spatial GMM procedure, proposed by Conley (1999). An extension for fullinformation instrumental variable models is presented. Monte Carlo simulations are employed in order to verify some asymptotic properties of the Spatial GMM approach. The simulations suggest that, even in the presence of spatial nonstationarity, the spatial GMM still delivers valid standard errors. Besides, usual t-statistics appear to have a standard normal distribution. An application for estimating labor and wage equations to study regional growth and development of the Brazilian municipalities, between 1991 and 2000, is presented. Neste artigo, nós descrevemos técnicas econométricas para tratar autocorrelação espacial em modelos multiequacionais, com dados em cross-section. Os procedimentos abordados aqui se baseiam no método de momentos generalizados espacial (GMM espacial) proposto em Conley (1999). Uma extensão para estimação com variáveis instrumentais com informação plena é apresentada. Nós empregamos simulações de Monte Carlo para verificar as propriedades assintóticas dos estimadores descritos. As simulações sugerem que, mesmo na presença de heterogeneidade espacial, o GMM espacial apresenta erros padrões apropriados. Além disso, estatísticas t usuais parecem seguir a distribuição normal padronizada. Finalmente, nós apresentamos uma aplicação, em que são estimadas equações de salário para estudar crescimento e desenvolvimento regional nos municípios brasileiros, entre 1991 e 2000.

Suggested Citation

  • Alexandre Carvalho & Daniel da Mata & Kenneth M. Chomitz, 2015. "Estimation of Multiequation Cross-section Models in the Presence of Spatial Autocorrelation," Discussion Papers 0154, Instituto de Pesquisa Econômica Aplicada - IPEA.
    • Handle: RePEc:ipe:ipetds:0154
    as

    Download full text from publisher

    File URL: http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/ingles/dp_154.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ferreira, Pedro Cavalcanti Gomes & Jr., Roberto de Goes Ellery, 1996. "Convergência Entre a Renda Per-Capita dos Estados Brasileiros," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 16(1), November.
    2. Viliam Druska & William C. Horrace, 2003. "Generalized Moments Estimation for Panel Data," NBER Technical Working Papers 0291, National Bureau of Economic Research, Inc.
    3. Kathleen P. Bell & Nancy E. Bockstael, 2000. "Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Microlevel Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 72-82, February.
    4. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    5. Matyas,Laszlo (ed.), 1999. "Generalized Method of Moments Estimation," Cambridge Books, Cambridge University Press, number 9780521669672.
    6. Kelejian, Harry H. & Prucha, Ingmar R., 2004. "Estimation of simultaneous systems of spatially interrelated cross sectional equations," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 27-50.
    7. Frees, Edward W., 1995. "Assessing cross-sectional correlation in panel data," Journal of Econometrics, Elsevier, vol. 69(2), pages 393-414, October.
    8. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    9. Baicker, Katherine, 2005. "The spillover effects of state spending," Journal of Public Economics, Elsevier, vol. 89(2-3), pages 529-544, February.
    10. Afonso Henriques Borges Ferreira & Clélio Campolina Diniz, 1994. "Convergência entre as rendas per capita estaduais no Brasil," Textos para Discussão Cedeplar-UFMG 079, Cedeplar, Universidade Federal de Minas Gerais.
    11. Alexandre Manoel Angelo da Silva & Guilherme Mendes Resende, 2006. "Crescimento Econômico Comparado dos Municípios Alagoanos e Mineiros: Uma Análise Espacial," Discussion Papers 1162, Instituto de Pesquisa Econômica Aplicada - IPEA.
    12. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    13. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    14. Matyas,Laszlo (ed.), 1999. "Generalized Method of Moments Estimation," Cambridge Books, Cambridge University Press, number 9780521660136.
    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. Alessandra Faggian & Mark Partridge & Edward J. Malecki, 2017. "Creating an Environment for Economic Growth: Creativity, Entrepreneurship or Human Capital?," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 41(6), pages 997-1009, November.
    2. Alexandre Carvalho & Daniel da Mata & Kenneth M. Chomitz & João Carlos Magalhães, 2005. "Spatial Dynamics of Labor Markets in Brazil," Discussion Papers 1110, Instituto de Pesquisa Econômica Aplicada - IPEA.

    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. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    2. Christian A. Vossler, 2013. "Analyzing repeated-game economics experiments: robust standard errors for panel data with serial correlation," Chapters, in: John A. List & Michael K. Price (ed.), Handbook on Experimental Economics and the Environment, chapter 3, pages 89-112, Edward Elgar Publishing.
    3. Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005. "A New Asymptotic Theory For Heteroskedasticity-Autocorrelation Robust Tests," Econometric Theory, Cambridge University Press, vol. 21(6), pages 1130-1164, December.
    4. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2013. "Estimation of the spatial weights matrix under structural constraints," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 617-634.
    5. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    6. Arnab Bhattacharjee & Sean Holly, 2013. "Understanding Interactions in Social Networks and Committees," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(1), pages 23-53, March.
    7. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
    8. Gebremeskel Gebremariam & Tesfa Gebremedhin & Peter Schaeffer & Tim Phipps & Randall Jackson, 2007. "A Spatial Panel Simultaneous-Equations Model of Business Growth, Migration Behavior, Local Public Services and Household Income in Appalachia," Working Papers Working Paper 2007-11, Regional Research Institute, West Virginia University.
    9. Kojevnikov, Denis & Marmer, Vadim & Song, Kyungchul, 2021. "Limit theorems for network dependent random variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 882-908.
    10. Arnab Bhattacharjee & Sean Holly, 2011. "Structural interactions in spatial panels," Empirical Economics, Springer, vol. 40(1), pages 69-94, February.
    11. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    12. Harald Badinger & Peter Egger, 2015. "Fixed Effects and Random Effects Estimation of Higher-order Spatial Autoregressive Models with Spatial Autoregressive and Heteroscedastic Disturbances," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(1), pages 11-35, March.
    13. Andreas P. Kyriacou & Leonel Muinelo-Gallo & Oriol Roca-Sagalés, 2015. "Regional inequalities, fiscal decentralization and government quality: empirical evidence from simultaneous equations," Working Papers. Collection A: Public economics, governance and decentralization 1501, Universidade de Vigo, GEN - Governance and Economics research Network.
    14. Kim, GwanSeon & Schieffer, Jack & Mark, Tyler, 2020. "Do superfund sites affect local property values? Evidence from a spatial hedonic approach," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 15-28.
    15. Denis Kojevnikov, 2021. "The Bootstrap for Network Dependent Processes," Papers 2101.12312, arXiv.org.
    16. Arnab Bhattacharjee & Sean Holly, 2013. "Understanding Interactions in Social Networks and Committees," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(1), pages 23-53, March.
    17. Harald Badinger & Peter Egger, 2009. "Estimation of Higher-Order Spatial Autoregressive Panel Data Error Component Models," CESifo Working Paper Series 2556, CESifo.
    18. Sebastian Hauptmeier & Ferdinand Mittermaier & Johannes Rincke, 2008. "Fiscal Competition over Taxes and Public Inputs: Theory and Evidence," CESifo Working Paper Series 2499, CESifo.
    19. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    20. Harald Badinger & Peter Egger, 2008. "GM Estimation of Higher-Order Spatial Autoregressive Processes in Cross-Section Models with Heteroskedastic Disturbances," CESifo Working Paper Series 2356, CESifo.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ipe:ipetds:0154. 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: Fabio Schiavinatto (email available below). General contact details of provider: https://edirc.repec.org/data/ipeaabr.html .

    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.