IDEAS home Printed from https://ideas.repec.org/a/sae/inrsre/v43y2020i1-2p10-39.html
   My bibliography  Save this article

Inference for Income Mobility Measures in the Presence of Spatial Dependence

Author

Listed:
  • Wei Kang
  • Sergio J. Rey

Abstract

Income mobility measures provide convenient and concise ways to reveal the dynamic nature of regional income distributions. Statistical inference about these measures is important especially when it comes to a comparison of two regional income systems. Although the analytical sampling distributions of relevant estimators and test statistics have been asymptotically derived, their properties in small sample settings and in the presence of contemporaneous spatial dependence within a regional income system are underexplored. We approach these issues via a series of Monte Carlo experiments that require the proposal of a novel data generating process capable of generating spatially dependent time series given a transition probability matrix and a specified level of spatial dependence. Results suggest that when sample size is small, the mobility estimator is biased while spatial dependence inflates its asymptotic variance, raising the Type I error rate for a one-sample test. For the two-sample test of the difference in mobility between two regional economic systems, the size tends to become increasingly upward biased with stronger spatial dependence in either income system, which indicates that conclusions about differences in mobility between two different regional systems need to be drawn with caution as the presence of spatial dependence can lead to false positives. In light of this, we suggest adjustments for the critical values of relevant test statistics.

Suggested Citation

  • Wei Kang & Sergio J. Rey, 2020. "Inference for Income Mobility Measures in the Presence of Spatial Dependence," International Regional Science Review, , vol. 43(1-2), pages 10-39, January.
  • Handle: RePEc:sae:inrsre:v:43:y:2020:i:1-2:p:10-39
    DOI: 10.1177/0160017619826291
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0160017619826291
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0160017619826291?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
    ---><---

    References listed on IDEAS

    as
    1. Trede Mark, 1999. "Statistical Inference for Measures of Income Mobility / Statistische Inferenz zur Messung der Einkommensmobilität," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 218(3-4), pages 473-490, June.
    2. Sergio J. Rey & Wei Kang & Levi Wolf, 2016. "The properties of tests for spatial effects in discrete Markov chain models of regional income distribution dynamics," Journal of Geographical Systems, Springer, vol. 18(4), pages 377-398, October.
    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. Fiaschi, Davide & Lavezzi, Andrea Mario, 2003. "Distribution Dynamics and Nonlinear Growth," Journal of Economic Growth, Springer, vol. 8(4), pages 379-401, December.
    2. Andrés Vallone & Coro Chasco, 2020. "Spatiotemporal methods for analysis of urban system dynamics: an application to Chile," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 421-454, April.
    3. Zhongxun Zhang & Kaifang Shi & Zhiyong Zhu & Lu Tang & Kangchuan Su & Qingyuan Yang, 2022. "Spatiotemporal Evolution and Influencing Factors of the Rural Natural Capital Utilization Efficiency: A Case Study of Chongqing, China," Land, MDPI, vol. 11(5), pages 1-29, May.
    4. Yi Chen & Frank A. Cowell, 2017. "Mobility in China," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(2), pages 203-218, June.
    5. Wei Kang & Sergio J. Rey, 2018. "Conditional and joint tests for spatial effects in discrete Markov chain models of regional income distribution dynamics," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(1), pages 73-93, July.
    6. Gaston Yalonetzky, 2009. "Comparing Economic Mobility with Heterogeneity Indices: An Application to Education in Peru," OPHI Working Papers 33, Queen Elizabeth House, University of Oxford.
    7. Formby, John P. & Smith, W. James & Zheng, Buhong, 2004. "Mobility measurement, transition matrices and statistical inference," Journal of Econometrics, Elsevier, vol. 120(1), pages 181-205, May.

    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:sae:inrsre:v:43:y:2020:i:1-2:p:10-39. 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: SAGE Publications (email available below). General contact details of provider: .

    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.