IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v118y2013i1p19-22.html
   My bibliography  Save this article

The spatial dynamics of growth and inequality: Evidence using U.S. county-level data

Author

Listed:
  • Atems, Bebonchu

Abstract

Based on an estimated dynamic spatial Durbin model, we find that the direct effect of a one-point increase in a county’s inequality is associated with a 3.3% decrease in its growth, while one-point increases in inequality in a county’s neighbors decrease its growth by 4.8%.

Suggested Citation

  • Atems, Bebonchu, 2013. "The spatial dynamics of growth and inequality: Evidence using U.S. county-level data," Economics Letters, Elsevier, vol. 118(1), pages 19-22.
    • Handle: RePEc:eee:ecolet:v:118:y:2013:i:1:p:19-22
    DOI: 10.1016/j.econlet.2012.09.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512005113
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2012.09.004?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. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    2. Panizza, Ugo, 2002. "Income Inequality and Economic Growth: Evidence from American Data," Journal of Economic Growth, Springer, vol. 7(1), pages 25-41, March.
    3. Florax, Raymond J. G. M. & Folmer, Hendrik & Rey, Sergio J., 2003. "Specification searches in spatial econometrics: the relevance of Hendry's methodology," Regional Science and Urban Economics, Elsevier, vol. 33(5), pages 557-579, September.
    4. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, September.
    5. Anil Rupasingha & Stephan J. Goetz & David Freshwater, 2002. "Social and institutional factors as determinants of economic growth: Evidence from the United States counties," Papers in Regional Science, Springer;Regional Science Association International, vol. 81(2), pages 139-155.
    6. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    7. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    8. Banerjee, Abhijit V & Duflo, Esther, 2003. "Inequality and Growth: What Can the Data Say?," Journal of Economic Growth, Springer, vol. 8(3), pages 267-299, September.
    9. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    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. Bebonchu Atems, 2013. "A Note On The Differential Regional Effects Of Income Inequality: Empirical Evidence Using U.S. County-Level Data," Journal of Regional Science, Wiley Blackwell, vol. 53(4), pages 656-671, October.
    2. Masako Oyama, 2014. "How does income distribution affect economic growth? --Evidence from Japanese prefectural data--," ISER Discussion Paper 0910, Institute of Social and Economic Research, Osaka University.
    3. Domenico Rossignoli, 2015. "Too many and too much? Special-interest groups and inequality at the turn of the century," Rivista Internazionale di Scienze Sociali, Vita e Pensiero, Pubblicazioni dell'Universita' Cattolica del Sacro Cuore, vol. 130(3), pages 337-366.
    4. Atems, Bebonchu, 2018. "Regional heterogeneity in the relationship between inequality and growth: Evidence from panel vector autoregressions," The Journal of Economic Asymmetries, Elsevier, vol. 17(C), pages 41-47.
    5. Caijing Zhao & Yuming Wu & Xinyue Ye & Baijun Wu & Sonali Kudva, 2019. "The direct and indirect drag effects of land and energy on urban economic growth in the Yangtze River Delta, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(6), pages 2945-2962, December.
    6. Up Lim & Donghyun Kim, 2015. "Toward Sustainable Economic Growth: A Spatial Panel Data Analysis of Regional Income Convergence in US BEA Economic Areas," Sustainability, MDPI, vol. 7(8), pages 1-17, July.
    7. Bebonchu Atems & Grayden Shand, 2018. "An empirical analysis of the relationship between entrepreneurship and income inequality," Small Business Economics, Springer, vol. 51(4), pages 905-922, December.

    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. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    2. Andrew Ojede & Bebonchu Atems & Steven Yamarik, 2018. "The Direct and Indirect (Spillover) Effects of Productive Government Spending on State Economic Growth," Growth and Change, Wiley Blackwell, vol. 49(1), pages 122-141, March.
    3. Roger Bivand & Giovanni Millo & Gianfranco Piras, 2021. "A Review of Software for Spatial Econometrics in R," Mathematics, MDPI, vol. 9(11), pages 1-40, June.
    4. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    5. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    6. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    7. repec:rri:wpaper:201303 is not listed on IDEAS
    8. 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.
    9. Philipp Otto & Wolfgang Schmid, 2018. "Spatiotemporal analysis of German real-estate prices," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 41-72, January.
    10. Borck, Rainald & Fossen, Frank M. & Freier, Ronny & Martin, Thorsten, 2015. "Race to the debt trap? — Spatial econometric evidence on debt in German municipalities," Regional Science and Urban Economics, Elsevier, vol. 53(C), pages 20-37.
    11. Triki, Mohamed Bilel, 2019. "The Italian wage curve revisited: A local and spatial cointegration," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 73-90.
    12. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
    13. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2019. "A time-space dynamic panel data model with spatial moving average errors," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 13-31.
    14. Debarsy, Nicolas & Ertur, Cem, 2010. "Testing for spatial autocorrelation in a fixed effects panel data model," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 453-470, November.
    15. Su, Liangjun & Yang, Zhenlin, 2015. "QML estimation of dynamic panel data models with spatial errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 230-258.
    16. Mengqi Zhang & Boping Tian, 2023. "Profile Maximum Likelihood Estimation of Single-Index Spatial Dynamic Panel Data Model," Mathematics, MDPI, vol. 11(13), pages 1-16, July.
    17. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2012. "Estimation for spatial dynamic panel data with fixed effects: The case of spatial cointegration," Journal of Econometrics, Elsevier, vol. 167(1), pages 16-37.
    18. Lung‐fei Lee & Jihai Yu, 2012. "Spatial Panels: Random Components Versus Fixed Effects," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(4), pages 1369-1412, November.
    19. Millo, Giovanni, 2014. "Maximum likelihood estimation of spatially and serially correlated panels with random effects," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 914-933.
    20. Hanen Ragoubi & Zouheir Mighri, 2021. "Spillover effects of trade openness on CO2 emissions in middle‐income countries: A spatial panel data approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 835-877, June.
    21. Yu, Dalei & Bai, Peng & Ding, Chang, 2015. "Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 116-135.

    More about this item

    Keywords

    Income inequality; Growth; Dynamic panels; Spatial Durbin model;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

    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:eee:ecolet:v:118:y:2013:i:1:p:19-22. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.