IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v179y2019icp29-32.html

Asymmetric competition, risk, and return distribution

Author

Listed:
  • Mundt, Philipp
  • Oh, Ilfan

Abstract

We propose a parsimonious statistical model of firm competition where structural differences in the strength of competitive pressure and the magnitude of return fluctuations above and below the system-wide benchmark translate into a skewed Subbotin or asymmetric exponential power (AEP) distribution of returns to capital. Empirical evidence from US data illustrates that the AEP distribution compares favorably to popular alternative models such as the symmetric or asymmetric Laplace density in terms of goodness of fit when entry and exit dynamics of markets are taken into account.

Suggested Citation

  • Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.
    • Handle: RePEc:eee:ecolet:v:179:y:2019:i:c:p:29-32
    DOI: 10.1016/j.econlet.2019.03.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176519300953
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2019.03.016?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Giulio Bottazzi & Angelo Secchi & Federico Tamagni, 2014. "Financial constraints and firm dynamics," Small Business Economics, Springer, vol. 42(1), pages 99-116, January.
    2. Giorgio Fagiolo & Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2010. "On the distributional properties of household consumption expenditures: the case of Italy," Empirical Economics, Springer, vol. 38(3), pages 717-741, June.
    3. Foley Duncan K., 1994. "A Statistical Equilibrium Theory of Markets," Journal of Economic Theory, Elsevier, vol. 62(2), pages 321-345, April.
    4. Giulio Bottazzi & Angelo Secchi & Federico Tamagni, 2014. "Financial constraints and firm dynamics," Small Business Economics, Springer, vol. 42(1), pages 99-116, January.
    5. Zhu, Dongming & Zinde-Walsh, Victoria, 2009. "Properties and estimation of asymmetric exponential power distribution," Journal of Econometrics, Elsevier, vol. 148(1), pages 86-99, January.
    6. Giulio Bottazzi & Angelo Secchi, 2011. "A new class of asymmetric exponential power densities with applications to economics and finance," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 20(4), pages 991-1030, August.
    7. Bernanke, Ben & Gertler, Mark & Gilchrist, Simon, 1996. "The Financial Accelerator and the Flight to Quality," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 1-15, February.
    8. Mara Faccio & Maria-Teresa Marchica & Roberto Mura, 2011. "Large Shareholder Diversification and Corporate Risk-Taking," The Review of Financial Studies, Society for Financial Studies, vol. 24(11), pages 3601-3641.
    9. Alfarano, Simone & Milakovic, Mishael, 2008. "Does classical competition explain the statistical features of firm growth?," Economics Letters, Elsevier, vol. 101(3), pages 272-274, December.
    10. Kose John & Lubomir Litov & Bernard Yeung, 2008. "Corporate Governance and Risk‐Taking," Journal of Finance, American Finance Association, vol. 63(4), pages 1679-1728, August.
    11. Toke Reichstein & Morten Berg Jensen, 2005. "Firm size and firm growth rate distributions--The case of Denmark," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 14(6), pages 1145-1166, December.
    12. Alfarano, Simone & Milaković, Mishael & Irle, Albrecht & Kauschke, Jonas, 2012. "A statistical equilibrium model of competitive firms," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 136-149.
    13. Bruce C. Greenwald & Joseph E. Stiglitz, 1993. "Financial Market Imperfections and Business Cycles," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 77-114.
    14. Steven M. Fazzari & R. Glenn Hubbard & Bruce C. Petersen, 1988. "Financing Constraints and Corporate Investment," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(1), pages 141-206.
    15. Jess Benhabib & Alberto Bisin, 2018. "Skewed Wealth Distributions: Theory and Empirics," Journal of Economic Literature, American Economic Association, vol. 56(4), pages 1261-1291, December.
    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. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    2. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    3. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    4. Juan Melo, 2024. "Decentralized Finance and Local Public Goods: A Bayesian Maximum Entropy Model of School District Spending in the U.S," Papers 2404.17700, arXiv.org.
    5. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.

    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. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    2. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    3. Thomas Brenner & Matthias Duschl, 2018. "Modeling Firm and Market Dynamics: A Flexible Model Reproducing Existing Stylized Facts on Firm Growth," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 745-772, October.
    4. Halvarsson, Daniel, 2013. "Identifying High-Growth Firms," Ratio Working Papers 215, The Ratio Institute.
    5. Vitezić Vanja & Srhoj Stjepan & Perić Marko, 2018. "Investigating Industry Dynamics in a Recessionary Transition Economy," South East European Journal of Economics and Business, Sciendo, vol. 13(1), pages 43-67, June.
    6. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," BERG Working Paper Series 145, Bamberg University, Bamberg Economic Research Group.
    7. Thomas Brenner & Matthias Duschl, 2014. "Modelling Firm and Market Dynamics - A Flexible Model Reproducing Existing Stylized Facts," Working Papers on Innovation and Space 2014-07, Philipps University Marburg, Department of Geography.
    8. Falavigna, Greta & Ippoliti, Roberto, 2023. "SMEs’ behavior under financial constraints: An empirical investigation on the legal environment and the substitution effect with tax arrears," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    9. Kusnadi, Yuanto, 2015. "Insider trading restrictions and corporate risk-taking," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 125-142.
    10. Francesco Aiello & Graziella Bonanno & Stefania P. S. Rossi, 2020. "How firms finance innovation. Further empirics from European SMEs," Metroeconomica, Wiley Blackwell, vol. 71(4), pages 689-714, November.
    11. Jiang, Tianjiao & Levine, Ross & Lin, Chen & Wei, Lai, 2020. "Bank deregulation and corporate risk," Journal of Corporate Finance, Elsevier, vol. 60(C).
    12. Galindo, Arturo & Schiantarelli, Fabio, 2002. "Credit Constraints in Latin America: An Overview of the Micro Evidence," IDB Publications (Working Papers) 1438, Inter-American Development Bank.
    13. Cristina Guillamón & Enrique Moral-Benito & Sergio Puente, 2017. "High growth firms in employment and productivity: dynamic interactions and the role of financial constraints?," Working Papers 1718, Banco de España.
    14. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    15. Bacchetta, Philippe & Caminal, Ramon, 2000. "Do capital market imperfections exacerbate output fluctuations?," European Economic Review, Elsevier, vol. 44(3), pages 449-468, March.
    16. Thomas Brenner & Matthias Duschl, 2015. "Causal dynamic effects in regional systems of technological activities: a SVAR approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 55(1), pages 103-130, October.
    17. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    18. Giulio Bottazzi & Taewon Kang & Federico Tamagni, 2023. "Persistence in firm growth: inference from conditional quantile transition matrices," Small Business Economics, Springer, vol. 61(2), pages 745-770, August.
    19. Daniele Moschella & Federico Tamagni & Xiaodan Yu, 2019. "Persistent high-growth firms in China’s manufacturing," Small Business Economics, Springer, vol. 52(3), pages 573-594, March.
    20. Reiner Franke, 2015. "How Fat-Tailed is US Output Growth?," Metroeconomica, Wiley Blackwell, vol. 66(2), pages 213-242, May.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

    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:179:y:2019:i:c:p:29-32. 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.