IDEAS home Printed from https://ideas.repec.org/a/spr/jeicoo/v16y2021i2d10.1007_s11403-020-00294-2.html
   My bibliography  Save this article

The nonlinear distribution of employment across municipalities

Author

Listed:
  • Faustino Prieto

    (University of Cantabria)

  • José María Sarabia

    (University of Cantabria)

  • Enrique Calderín-Ojeda

    (The University of Melbourne)

Abstract

In this paper, the nonlinear distribution of employment across Spanish municipalities is analyzed. Also, we explore new properties of the family of generalized power law (GPL) distributions and explore its hierarchical structure, then we test its adequacy for modeling employment data. A new subfamily of heavy-tailed GPL distributions that is right tail equivalent to a Pareto (power-law) model is derived. Our findings show on the one hand that the distribution of employment across Spanish municipalities follows a power-law behavior in the upper tail and, on the other hand, the adequacy of GPL models for modeling employment data in the whole range of the distribution.

Suggested Citation

  • Faustino Prieto & José María Sarabia & Enrique Calderín-Ojeda, 2021. "The nonlinear distribution of employment across municipalities," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 287-307, April.
  • Handle: RePEc:spr:jeicoo:v:16:y:2021:i:2:d:10.1007_s11403-020-00294-2
    DOI: 10.1007/s11403-020-00294-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11403-020-00294-2
    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/s11403-020-00294-2?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. Jan Eeckhout, 2004. "Gibrat's Law for (All) Cities," American Economic Review, American Economic Association, vol. 94(5), pages 1429-1451, December.
    2. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April.
    3. Sarabia, José María & Prieto, Faustino, 2009. "The Pareto-positive stable distribution: A new descriptive model for city size data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4179-4191.
    4. Fujiwara, Yoshi & Di Guilmi, Corrado & Aoyama, Hideaki & Gallegati, Mauro & Souma, Wataru, 2004. "Do Pareto–Zipf and Gibrat laws hold true? An analysis with European firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(1), pages 197-216.
    5. Dariusz Wójcik & Duncan MacDonald-Korth, 2015. "The British and the German financial sectors in the wake of the crisis: size, structure and spatial concentration," Journal of Economic Geography, Oxford University Press, vol. 15(5), pages 1033-1054.
    6. Xavier Gabaix, 2016. "Power Laws in Economics: An Introduction," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 185-206, Winter.
    7. Alessia Matano & Paolo Naticchioni, 2012. "Wage distribution and the spatial sorting of workers," Journal of Economic Geography, Oxford University Press, vol. 12(2), pages 379-408, March.
    8. Klaus Desmet & Marcel Fafchamps, 2005. "Changes in the spatial concentration of employment across US counties: a sectoral analysis 1972--2000," Journal of Economic Geography, Oxford University Press, vol. 5(3), pages 261-284, June.
    9. Lyócsa, Štefan & Výrost, Tomáš, 2018. "Scale-free distribution of firm-size distribution in emerging economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 501-505.
    10. Nash, John C. & Varadhan, Ravi, 2011. "Unifying Optimization Algorithms to Aid Software System Users: optimx for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i09).
    11. Guillen, Montserrat & Prieto, Faustino & Sarabia, José María, 2011. "Modelling losses and locating the tail with the Pareto Positive Stable distribution," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 454-461.
    12. Barry C. Arnold, 2008. "Pareto and Generalized Pareto Distributions," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 7, pages 119-145, Springer.
    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. Stephen P. Jenkins, 2017. "Pareto Models, Top Incomes and Recent Trends in UK Income Inequality," Economica, London School of Economics and Political Science, vol. 84(334), pages 261-289, April.
    2. Segarra, Agustí & Teruel, Mercedes, 2012. "An appraisal of firm size distribution: Does sample size matter?," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 314-328.
    3. Lyócsa, Štefan & Výrost, Tomáš, 2018. "Scale-free distribution of firm-size distribution in emerging economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 501-505.
    4. Wang, Yuanjun & You, Shibing, 2016. "An alternative method for modeling the size distribution of top wealth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 443-453.
    5. Christian Düben & Melanie Krause, 2021. "Population, light, and the size distribution of cities," Journal of Regional Science, Wiley Blackwell, vol. 61(1), pages 189-211, January.
    6. Desmet, Klaus & Henderson, J. Vernon, 2015. "The Geography of Development Within Countries," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 1457-1517, Elsevier.
    7. Desmet, Klaus & Fafchamps, Marcel, 2006. "Employment concentration across U.S. counties," Regional Science and Urban Economics, Elsevier, vol. 36(4), pages 482-509, July.
    8. Combes, Pierre-Philippe & Gobillon, Laurent, 2015. "The Empirics of Agglomeration Economies," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 247-348, Elsevier.
    9. Mark D. Partridge & Dan S. Rickman & Kamar Ali & M. Rose Olfert, 2009. "Do New Economic Geography agglomeration shadows underlie current population dynamics across the urban hierarchy?," Papers in Regional Science, Wiley Blackwell, vol. 88(2), pages 445-466, June.
    10. Mario Polèse & Richard Shearmur, 2006. "Growth and Location of Economic Activity: The Spatial Dynamics of Industries in Canada 1971–2001," Growth and Change, Wiley Blackwell, vol. 37(3), pages 362-395, September.
    11. Fenske, James & Kala, Namrata & Wei, Jinlin, 2021. "Railways and cities in India," The Warwick Economics Research Paper Series (TWERPS) 1349, University of Warwick, Department of Economics.
    12. Klaus Desmet & Esteban Rossi-Hansberg, 2014. "Spatial Development," American Economic Review, American Economic Association, vol. 104(4), pages 1211-1243, April.
    13. Beltrán Tapia, Francisco J. & Díez-Minguela, Alfonso & Martinez-Galarraga, Julio, 2018. "Tracing the Evolution of Agglomeration Economies: Spain, 1860–1991," The Journal of Economic History, Cambridge University Press, vol. 78(1), pages 81-117, March.
    14. Xu, Yan & Wang, Yougui & Tao, Xiaobo & Ližbetinová, Lenka, 2017. "Evidence of Chinese income dynamics and its effects on income scaling law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 143-152.
    15. Kwong, Hok Shing & Nadarajah, Saralees, 2019. "A note on “Pareto tails and lognormal body of US cities size distribution”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 55-62.
    16. Sáez, Antonio José & Prieto, Faustino & Sarabia, José María, 2012. "A two-tail version of the PPS distribution with application to current account balance data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5160-5171.
    17. repec:hal:spmain:info:hdl:2441/1kv8mtgl748r0ahh12air9erdc is not listed on IDEAS
    18. Behzod B. Ahundjanov & Sherzod B. Akhundjanov & Botir B. Okhunjanov, 2022. "Power law in COVID‐19 cases in China," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(2), pages 699-719, April.
    19. Partridge, Mark D. & Rickman, Dan S. & Ali, Kamar & Olfert, M. Rose, 2010. "Recent spatial growth dynamics in wages and housing costs: Proximity to urban production externalities and consumer amenities," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 440-452, November.
    20. Fenske, James & Kala, Namrata & Wei, Jinlin, 2021. "Railways and cities in India," CAGE Online Working Paper Series 559, Competitive Advantage in the Global Economy (CAGE).
    21. Arshad, Sidra & Hu, Shougeng & Ashraf, Badar Nadeem, 2019. "Zipf’s law, the coherence of the urban system and city size distribution: Evidence from Pakistan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 87-103.

    More about this item

    Keywords

    Labor market; Municipalities; Generalized power-law models; Complex adaptive systems;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • F16 - International Economics - - Trade - - - Trade and Labor Market Interactions
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    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:jeicoo:v:16:y:2021:i:2:d:10.1007_s11403-020-00294-2. 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.