IDEAS home Printed from https://ideas.repec.org/a/spr/lsprsc/v13y2020i3d10.1007_s12076-020-00257-y.html
   My bibliography  Save this article

Dynamic panel estimation of a regional adjustment model with spatial-temporal robust covariance

Author

Listed:
  • Dayton M. Lambert

    (Oklahoma State University)

Abstract

This paper extends the Arellano-Bond dynamic panel regression model’s covariance estimator to one robust to spatial autocovariance and heteroskedasticity. We apply Kelejian and Prucha’s semi-parametric procedure for estimating covariance matrices that accommodate spatial heteroskedastic autocovariance processes to augment the usual Arellano-Bond covariance estimator. The empirical application examines the jobs-to-people/people-to-jobs conundrum with Carlino and Mill’s regional adjustment model using employment and population data from 2001 to 2018 for Oklahoma’s 77 counties.

Suggested Citation

  • Dayton M. Lambert, 2020. "Dynamic panel estimation of a regional adjustment model with spatial-temporal robust covariance," Letters in Spatial and Resource Sciences, Springer, vol. 13(3), pages 245-265, December.
    • Handle: RePEc:spr:lsprsc:v:13:y:2020:i:3:d:10.1007_s12076-020-00257-y
    DOI: 10.1007/s12076-020-00257-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12076-020-00257-y
    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/s12076-020-00257-y?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. Kim, Min Seong & Sun, Yixiao, 2013. "Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 177(1), pages 85-108.
    2. Daniel C. Monchuk & Dermot J. Hayes & John A. Miranowski & Dayton M. Lambert, 2011. "Inference Based On Alternative Bootstrapping Methods In Spatial Models With An Application To County Income Growth In The United States," Journal of Regional Science, Wiley Blackwell, vol. 51(5), pages 880-896, December.
    3. Thomas de Graaff & Frank G. van Oort & Raymond J.G.M. Florax, 2012. "Regional Population–Employment Dynamics Across Different Sectors Of The Economy," Journal of Regional Science, Wiley Blackwell, vol. 52(1), pages 60-84, February.
    4. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    5. Giuseppe Arbia & Bernard Fingleton, 2008. "New spatial econometric techniques and applications in regional science," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 311-317, August.
    6. D. M. Lambert & C. N. Boyer & L. He, 2016. "Spatial-temporal heteroskedastic robust covariance estimation for Markov transition probabilities: an application examining land use change," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 353-362, October.
    7. Marlon G. Boarnet & Saksith Chalermpong & Elizabeth Geho, 2005. "Specification issues in models of population and employment growth," Papers in Regional Science, Wiley Blackwell, vol. 84(1), pages 21-46, March.
    8. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    9. Pede, Valerien O. & Florax, Raymond J.G.M. & de Groot, Henri L.F., 2006. "The Role of Knowledge Externalities in the Spatial Distribution of Economic Growth: A Spatial Econometric Analysis for US Counties, 1969-2003," 2006 Annual meeting, July 23-26, Long Beach, CA 21157, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    11. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    12. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    13. Jason P. Brown & Dayton M. Lambert & Raymond J. G. M. Florax, 2013. "The Birth, Death, and Persistence of Firms: Creative Destruction and the Spatial Distribution of U.S. Manufacturing Establishments, 2000–2006," Economic Geography, Clark University, vol. 89(3), pages 203-226, July.
    14. James P. LeSage & R. Kelley Pace, 2014. "The Biggest Myth in Spatial Econometrics," Econometrics, MDPI, vol. 2(4), pages 1-33, December.
    15. Lambert, Dayton M. & Boyer, Christopher N. & He, Lixia L., 2016. "Markov Transition Probabilities and Robust Spatial-temporal Covariance Estimation," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229863, Southern Agricultural Economics Association.
    16. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    17. David A. McGranahan & Timothy R. Wojan & Dayton M. Lambert, 2011. "The rural growth trifecta: outdoor amenities, creative class and entrepreneurial context -super-§," Journal of Economic Geography, Oxford University Press, vol. 11(3), pages 529-557, May.
    18. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    19. Joris Pinkse & Margaret E. Slade, 2010. "The Future Of Spatial Econometrics," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 103-117, February.
    20. G F Mulligan & A C Vias & S M Glavac, 1999. "Initial Diagnostics of a Regional Adjustment Model," Environment and Planning A, , vol. 31(5), pages 855-876, May.
    21. Gebremeskel H. Gebremariam & Tesfa G. Gebremedhin & Peter V. Schaeffer, 2011. "Employment, Income, And Migration In Appalachia: A Spatial Simultaneous Equations Approach," Journal of Regional Science, Wiley Blackwell, vol. 51(1), pages 102-120, February.
    Full references (including those not matched with items on IDEAS)

    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. Dayton M. Lambert & Wan Xu & Raymond J. G. M. Florax, 2014. "Partial Adjustment Analysis of Income and Jobs, and Growth Regimes in the Appalachian Region with Smooth Transition Spatial Process Models," International Regional Science Review, , vol. 37(3), pages 328-364, July.
    2. Peppel-Srebrny, Jemima, 2021. "Not all government budget deficits are created equal: Evidence from advanced economies' sovereign bond markets," Journal of International Money and Finance, Elsevier, vol. 118(C).
    3. Jason P. Brown & Dayton M. Lambert & Raymond J. G. M. Florax, 2013. "The Birth, Death, and Persistence of Firms: Creative Destruction and the Spatial Distribution of U.S. Manufacturing Establishments, 2000–2006," Economic Geography, Clark University, vol. 89(3), pages 203-226, July.
    4. Frank Davenport, 2017. "Estimating standard errors in spatial panel models with time varying spatial correlation," Papers in Regional Science, Wiley Blackwell, vol. 96, pages 155-177, March.
    5. Dilla, Diana, 2017. "Staatsverschuldung und Verschuldungsmentalität [Public Debt and Debt Mentality]," MPRA Paper 79432, University Library of Munich, Germany.
    6. Mohanty, Biswajit & Bhanumurthy, N. R. & Dastidar, Ananya Ghosh, 2017. "What explains Regional Imbalances in Infrastructure?: Evidence from Indian States," Working Papers 17/197, National Institute of Public Finance and Policy.
    7. Hyunseok Kim & GianCarlo Moschini, 2018. "The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era," Land Economics, University of Wisconsin Press, vol. 94(4), pages 593-613.
    8. de Souza, Joao Paulo A., 2015. "Evidence of growth complementarity between agriculture and industry in developing countries," Structural Change and Economic Dynamics, Elsevier, vol. 34(C), pages 1-18.
    9. Joseph L. Dieleman & Michael Hanlon, 2014. "Measuring The Displacement And Replacement Of Government Health Expenditure," Health Economics, John Wiley & Sons, Ltd., vol. 23(2), pages 129-140, February.
    10. Özlem Onaran & Valerie Boesch, 2014. "The Effect of Globalization on the Distribution of Taxes and Social Expenditures in Europe: Do Welfare State Regimes Matter?," Environment and Planning A, , vol. 46(2), pages 373-397, February.
    11. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    12. Gupta, Abhimanyu, 2018. "Autoregressive spatial spectral estimates," Journal of Econometrics, Elsevier, vol. 203(1), pages 80-95.
    13. Raul Caruso & Marco Di Domizio & Domenico Rossignoli, 2017. "Aggregate wages of players and performance in Italian Serie A," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(3), pages 515-531, December.
    14. Armey, Laura E. & McNab, Robert M., 2018. "Expenditure decentralization and natural resources," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 52-61.
    15. Min Seong Kim, 2021. "Robust Inference for Diffusion-Index Forecasts with Cross-Sectionally Dependent Data," Working papers 2021-04, University of Connecticut, Department of Economics.
    16. Marbuah, George & Gren, Ing-Marie & Tirkaso, Wondmagegn Tafesse, 2021. "Social capital, economic development and carbon emissions: Empirical evidence from counties in Sweden," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    17. Jiatao Li & Haoyuan Ding & Yichuan Hu & Guoguang Wan, 2021. "Dealing with dynamic endogeneity in international business research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(3), pages 339-362, April.
    18. Frondel, Manuel & Kaestner, Kathrin & Sommer, Stephan & Vance, Colin, 2022. "Photovoltaics and the solar rebound: Evidence for Germany," Ruhr Economic Papers 954, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    19. Ejike Udeogu (a) , Uzochukwu Amakom (b) and Shampa Roy-Mukherjee (a), 2021. "Empirical Analysis of an Augmented Schumpeterian Endogenous Growth Model," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 46(1), pages 53-84, March.
    20. Olaoye, Olumide O. & Eluwole, Oluwatosin O. & Ayesha, Aziz & Afolabi, Olugbenga O., 2020. "Government spending and economic growth in ECOWAS: An asymmetric analysis," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).

    More about this item

    Keywords

    Dynamic panel; Spatial-temporal covariance; Regional adjustment model; Instrumental variables;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

    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:lsprsc:v:13:y:2020:i:3:d:10.1007_s12076-020-00257-y. 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.