IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v563y2021ics0378437120307561.html
   My bibliography  Save this article

The distribution of strike size: Empirical evidence from Europe and North America in the 19th and 20th centuries

Author

Listed:
  • Campolieti, Michele
  • Ramos, Arturo

Abstract

We study the distribution of strike size, which we measure as lost-person-days, for a long period in several countries of Europe and America. When we consider the full samples, the mixtures of two or three lognormals arise as very convenient models. When restricting to the upper tails, the Pareto power law becomes almost indistinguishable of the truncated lognormal.

Suggested Citation

  • Campolieti, Michele & Ramos, Arturo, 2021. "The distribution of strike size: Empirical evidence from Europe and North America in the 19th and 20th centuries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    • Handle: RePEc:eee:phsmap:v:563:y:2021:i:c:s0378437120307561
    DOI: 10.1016/j.physa.2020.125424
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120307561
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2020.125424?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cirillo, Pasquale, 2013. "Are your data really Pareto distributed?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5947-5962.
    2. Campolieti, Michele, 2020. "The distribution of union size: Canada, 1913–2014," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    3. 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.
    4. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    5. Cederman, Lars-Erik, 2003. "Modeling the Size of Wars: From Billiard Balls to Sandpiles," American Political Science Review, Cambridge University Press, vol. 97(1), pages 135-150, February.
    6. Michele Campolieti, 2019. "Power Law Distributions and the Size Distribution of Strikes," Sociological Methods & Research, , vol. 48(3), pages 561-587, August.
    7. Vasicek, Oldrich, 1977. "An equilibrium characterization of the term structure," Journal of Financial Economics, Elsevier, vol. 5(2), pages 177-188, November.
    8. Rafael Gonz�lez-Val & Arturo Ramos & Fernando Sanz-Gracia, 2013. "The accuracy of graphs to describe size distributions," Applied Economics Letters, Taylor & Francis Journals, vol. 20(17), pages 1580-1585, November.
    9. John Pencavel, 2014. "The Changing Size Distribution of U.S. Trade Unions and its Description by Pareto's Distribution," ILR Review, Cornell University, ILR School, vol. 67(1), pages 138-170, January.
    10. Băncescu, Irina & Chivu, Luminiţa & Preda, Vasile & Puente-Ajovín, Miguel & Ramos, Arturo, 2019. "Comparisons of log-normal mixture and Pareto tails, GB2 or log-normal body of Romania’s all cities size distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    11. B. D. McCullough & H. D. Vinod, 2003. "Verifying the Solution from a Nonlinear Solver: A Case Study," American Economic Review, American Economic Association, vol. 93(3), pages 873-892, June.
    12. Richard B. Freeman, 1998. "Spurts in Union Growth: Defining Moments and Social Processes," NBER Chapters, in: The Defining Moment: The Great Depression and the American Economy in the Twentieth Century, pages 265-296, National Bureau of Economic Research, Inc.
    13. Amemiya, Takeshi, 1980. "Selection of Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 331-354, June.
    14. Campolieti, Michele, 2018. "Heavy-tailed distributions and the distribution of wealth: Evidence from rich lists in Canada, 1999–2017," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 263-272.
    15. Dashti Moghaddam, M. & Mills, Jeffrey & Serota, R.A., 2020. "From a stochastic model of economic exchange to measures of inequality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    16. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    17. Miguel Puente-Ajovín & Arturo Ramos & Fernando Sanz-Gracia, 2020. "Is there a universal parametric city size distribution? Empirical evidence for 70 countries," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(3), pages 727-741, December.
    18. Marco Bee & Massimo Riccaboni & Stefano Schiavo, 2011. "Pareto versus lognormal: a maximum entropy test," Department of Economics Working Papers 1102, Department of Economics, University of Trento, Italia.
    19. Vasicek, Oldrich Alfonso, 1977. "Abstract: An Equilibrium Characterization of the Term Structure," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(4), pages 627-627, November.
    20. Tomaschitz, Roman, 2020. "Multiply broken power-law densities as survival functions: An alternative to Pareto and lognormal fits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    21. Gualandi, Stefano & Toscani, Giuseppe, 2019. "Size distribution of cities: A kinetic explanation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 221-234.
    22. Su, Hsuan-Li, 2020. "On the city size distribution: A finite mixture interpretation," Journal of Urban Economics, Elsevier, vol. 116(C).
    23. Bee, Marco & Riccaboni, Massimo & Schiavo, Stefano, 2013. "The size distribution of US cities: Not Pareto, even in the tail," Economics Letters, Elsevier, vol. 120(2), pages 232-237.
    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. Peña, Guillermo & Puente-Ajovín, Miguel & Ramos, Arturo & Sanz-Gracia, Fernando, 2022. "Log-growth rates of CO2: An empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    2. Arturo Ramos & Till Massing & Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2023. "Composite distributions in the social sciences: A comparative empirical study of firms' sales distribution for France, Germany, Italy, Japan, South Korea, and Spain," Papers 2301.09438, arXiv.org.
    3. Băncescu, Irina & Chivu, Luminiţa & Massing, Till & Preda, Vasile & Puente-Ajovín, Miguel & Ramos, Arturo, 2024. "On the parametric description of log-growth rates of Romanian city sizes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).

    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. Peña, Guillermo & Puente-Ajovín, Miguel & Ramos, Arturo & Sanz-Gracia, Fernando, 2022. "Log-growth rates of CO2: An empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    2. Băncescu, Irina & Chivu, Luminiţa & Massing, Till & Preda, Vasile & Puente-Ajovín, Miguel & Ramos, Arturo, 2024. "On the parametric description of log-growth rates of Romanian city sizes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    3. Arturo Ramos & Till Massing & Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2023. "Composite distributions in the social sciences: A comparative empirical study of firms' sales distribution for France, Germany, Italy, Japan, South Korea, and Spain," Papers 2301.09438, arXiv.org.
    4. Tomaschitz, Roman, 2020. "Multiply broken power-law densities as survival functions: An alternative to Pareto and lognormal fits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    5. Campolieti, Michele, 2020. "The distribution of union size: Canada, 1913–2014," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    6. Asif, Muhammad & Hussain, Zawar & Asghar, Zahid & Hussain, Muhammad Irfan & Raftab, Mariya & Shah, Said Farooq & Khan, Akbar Ali, 2021. "A statistical evidence of power law distribution in the upper tail of world billionaires’ data 2010–20," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    7. Miguel Puente-Ajovín & Arturo Ramos & Fernando Sanz-Gracia, 2020. "Is there a universal parametric city size distribution? Empirical evidence for 70 countries," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(3), pages 727-741, December.
    8. Arturo Ramos & Till Massing & Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2024. "Mixtures of log-normal distributions in the mid-scale range of firm-size variables," Evolutionary and Institutional Economics Review, Springer, vol. 21(2), pages 249-260, September.
    9. Driessen, Joost & Melenberg, Bertrand & Nijman, Theo, 2005. "Testing affine term structure models in case of transaction costs," Journal of Econometrics, Elsevier, vol. 126(1), pages 201-232, May.
    10. Aït-Sahalia, Yacine & Kimmel, Robert L., 2010. "Estimating affine multifactor term structure models using closed-form likelihood expansions," Journal of Financial Economics, Elsevier, vol. 98(1), pages 113-144, October.
    11. M. Rypdal & O. L{o}vsletten, 2011. "Multifractal modeling of short-term interest rates," Papers 1111.5265, arXiv.org.
    12. Jakub Growiec & Fabio Pammolli & Massimo Riccaboni, 2020. "Innovation and Corporate Dynamics: A Theoretical Framework," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(1), pages 1-45, March.
    13. Arturo Ramos, 2017. "Are the log-growth rates of city sizes distributed normally? Empirical evidence for the USA," Empirical Economics, Springer, vol. 53(3), pages 1109-1123, November.
    14. Ramos, Arturo, 2015. "Are the log-growth rates of city sizes normally distributed? Empirical evidence for the US," MPRA Paper 65584, University Library of Munich, Germany.
    15. Choi, Hwan-sik & Jeong, Minsoo & Park, Joon Y., 2014. "An asymptotic analysis of likelihood-based diffusion model selection using high frequency data," Journal of Econometrics, Elsevier, vol. 178(P3), pages 539-557.
    16. Bee, Marco & Riccaboni, Massimo & Schiavo, Stefano, 2017. "Where Gibrat meets Zipf: Scale and scope of French firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 265-275.
    17. Alan Genaro & Adilson Simonis, 2015. "Estimating doubly stochastic Poisson process with affine intensities by Kalman filter," Statistical Papers, Springer, vol. 56(3), pages 723-748, August.
    18. Ruben Dewitte & Michel Dumont & Glenn Rayp & Peter Willemé, 2022. "Unobserved heterogeneity in the productivity distribution and gains from trade," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(3), pages 1566-1597, August.
    19. Massing, Till & Puente-Ajovín, Miguel & Ramos, Arturo, 2020. "On the parametric description of log-growth rates of cities’ sizes of four European countries and the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    20. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:phsmap:v:563:y:2021:i:c:s0378437120307561. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.