IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v46y2014i4p1521-1544.html
   My bibliography  Save this article

Testing for complementarities among countable strategies

Author

Listed:
  • Eugenio Miravete

Abstract

I study whether the pricing strategies of competing duopolists in the early US cellular telephone industry can be considered strategic complements or substitutes. In order to do so, I present a multivariate count data regression model that is suitable to test for the existence of strategic complementarities when firms make use of countable strategies. The estimator, which accommodates the underdispersion that characterizes the data, is shown to have better small-sample properties than common estimators based on the Gaussian copula. It also allows for correlations of any sign among counts independently of the dispersion parameters. Results show that in addition to screening consumers, competing firms imitated each other in the number of tariff options offered to their customers. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
  • Handle: RePEc:spr:empeco:v:46:y:2014:i:4:p:1521-1544
    DOI: 10.1007/s00181-013-0729-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00181-013-0729-y
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00181-013-0729-y?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. Philip M. Parker & Lars-Hendrik Roller, 1997. "Collusive Conduct in Duopolies: Multimarket Contact and Cross-Ownership in the Mobile Telephone Industry," RAND Journal of Economics, The RAND Corporation, vol. 28(2), pages 304-322, Summer.
    2. Winkelmann, Rainer, 1995. "Duration Dependence and Dispersion in Count-Data Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 467-474, October.
    3. repec:taf:jnlbes:v:30:y:2012:i:2:p:265-274 is not listed on IDEAS
    4. Rainer Winkelmann, 2000. "Seemingly Unrelated Negative Binomial Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(4), pages 553-560, September.
    5. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    6. Donald W. K. Andrews, 2002. "Higher-Order Improvements of a Computationally Attractive "k"-Step Bootstrap for Extremum Estimators," Econometrica, Econometric Society, vol. 70(1), pages 119-162, January.
    7. Meghan R. Busse, 2000. "Multimarket Contact and Price Coordination in the Cellular Telephone Industry," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 9(3), pages 287-320, June.
    8. Shiferaw Gurmu & John Elder, 2011. "Flexible Bivariate Count Data Regression Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 265-274, August.
    9. Hausman, Jerry A. & Leonard, Gregory K. & McFadden, Daniel, 1995. "A utility-consistent, combined discrete choice and count data model Assessing recreational use losses due to natural resource damage," Journal of Public Economics, Elsevier, vol. 56(1), pages 1-30, January.
    10. Donald W. K. Andrews, 2000. "Inconsistency of the Bootstrap when a Parameter Is on the Boundary of the Parameter Space," Econometrica, Econometric Society, vol. 68(2), pages 399-406, March.
    11. Donald W. K. Andrews, 1999. "Estimation When a Parameter Is on a Boundary," Econometrica, Econometric Society, vol. 67(6), pages 1341-1384, November.
    12. Armstrong, Mark & Vickers, John, 2001. "Competitive Price Discrimination," RAND Journal of Economics, The RAND Corporation, vol. 32(4), pages 579-605, Winter.
    13. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    14. Jung, Robert C & Winkelmann, Rainer, 1993. "Two Aspects of Labor Mobility: A Bivariate Poisson Regression Approach," Empirical Economics, Springer, vol. 18(3), pages 543-556.
    15. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.
    16. Vives, Xavier, 1990. "Nash equilibrium with strategic complementarities," Journal of Mathematical Economics, Elsevier, vol. 19(3), pages 305-321.
    17. Murat K. Munkin & Pravin K. Trivedi, 1999. "Simulated maximum likelihood estimation of multivariate mixed-Poisson regression models, with application," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 29-48.
    18. Meghir, Costas & Robin, Jean-Marc, 1992. "Frequency of purchase and the estimation of demand systems," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 53-85.
    19. , & ,, 2008. "Nonlinear pricing, market coverage, and competition," Theoretical Economics, Econometric Society, vol. 3(1), March.
    20. Andreas Million & Regina T. Riphahn & Achim Wambach, 2003. "Incentive effects in the demand for health care: a bivariate panel count data estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 387-405.
    21. Lung-Fei Lee, 1982. "Some Approaches to the Correction of Selectivity Bias," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(3), pages 355-372.
    22. Gurmu, Shiferaw & Elder, John, 2000. "Generalized bivariate count data regression models," Economics Letters, Elsevier, vol. 68(1), pages 31-36, July.
    23. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    24. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    25. Gurmu, Shiferaw & Elder, John, 2008. "A bivariate zero-inflated count data regression model with unrestricted correlation," Economics Letters, Elsevier, vol. 100(2), pages 245-248, August.
    26. Terza, Joseph V & Wilson, Paul W, 1990. "Analyzing Frequencies of Several Types of Events: A Mixed Multinomial-Poisson Approach," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 108-115, February.
    27. Heinen, Andreas & Rengifo, Erick, 2007. "Multivariate autoregressive modeling of time series count data using copulas," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 564-583, September.
    28. Jean-Charles Rochet & Lars A. Stole, 2002. "Nonlinear Pricing with Random Participation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(1), pages 277-311.
    29. Windmeijer, F A G & Silva, J M C Santos, 1997. "Endogeneity in Count Data Models: An Application to Demand for Health Care," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 281-294, May-June.
    30. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    31. van Ophem, Hans, 1999. "A General Method To Estimate Correlated Discrete Random Variables," Econometric Theory, Cambridge University Press, vol. 15(2), pages 228-237, April.
    32. Matthias Fischer & Ingo Klein, 2007. "Constructing Generalized FGM Copulas by Means of Certain Univariate Distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 65(2), pages 243-260, February.
    33. Denuit, Michel & Lambert, Philippe, 2005. "Constraints on concordance measures in bivariate discrete data," Journal of Multivariate Analysis, Elsevier, vol. 93(1), pages 40-57, March.
    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. Eugenio J. Miravete, 2009. "Competing with Menus of Tariff Options," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 188-205, March.
    2. Miravete, Eugenio, 2009. "Multivariate Sarmanov Count Data Models," CEPR Discussion Papers 7463, C.E.P.R. Discussion Papers.
    3. Eugenio J. Miravete, 2004. "The Doubtful Profitability of Foggy Pricing," Working Papers 04-07, NET Institute.
    4. Tzougas, George & Makariou, Despoina, 2022. "The multivariate Poisson-Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters," LSE Research Online Documents on Economics 117197, London School of Economics and Political Science, LSE Library.
    5. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
    6. Pravin Trivedi & David Zimmer, 2017. "A Note on Identification of Bivariate Copulas for Discrete Count Data," Econometrics, MDPI, vol. 5(1), pages 1-11, February.
    7. Mothafer, Ghasak I.M.A. & Yamamoto, Toshiyuki & Shankar, Venkataraman N., 2018. "A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 84-105.
    8. George Tzougas & Despoina Makariou, 2022. "The multivariate Poisson‐Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(4), pages 401-417, December.
    9. A. Colin Cameron & Per Johansson, 2004. "Bivariate Count Data Regression Using Series Expansions: With Applications," Working Papers 9815, University of California, Davis, Department of Economics.
    10. Atella, Vincenzo & Deb, Partha, 2008. "Are primary care physicians, public and private sector specialists substitutes or complements? Evidence from a simultaneous equations model for count data," Journal of Health Economics, Elsevier, vol. 27(3), pages 770-785, May.
    11. Rainer Winkelmann, 2015. "Counting on count data models," IZA World of Labor, Institute of Labor Economics (IZA), pages 148-148, May.
    12. William Greene, 2007. "Correlation in Bivariate Poisson Regression Model," Working Papers 07-14, New York University, Leonard N. Stern School of Business, Department of Economics.
    13. José Murteira & Óscar Lourenço, 2011. "Health care utilization and self-assessed health: specification of bivariate models using copulas," Empirical Economics, Springer, vol. 41(2), pages 447-472, October.
    14. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    15. Greene, William, 2008. "Functional forms for the negative binomial model for count data," Economics Letters, Elsevier, vol. 99(3), pages 585-590, June.
    16. Tom Van Ourti, 2004. "Measuring horizontal inequity in Belgian health care using a Gaussian random effects two part count data model," Health Economics, John Wiley & Sons, Ltd., vol. 13(7), pages 705-724, July.
    17. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    18. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
    19. Canan GÜNEŞ & Mustafa ÜNLÜ & Yasin BÜYÜKKÖR & Şenay ÜÇDOĞRUK BİRECİKLİ, 2016. "Türkiye’de Sağlık Hizmetleri Talebinin Sayma Veri Modelleriyle İncelenmesi: İçsellik Sorunu," Sosyoekonomi Journal, Sosyoekonomi Society, issue 24(30).
    20. Katja Seim & V. Brian Viard, 2003. "The Effect Of Entry And Market Structure On Cellular Pricing Tactics," Working Papers 03-13, NET Institute, revised Nov 2003.

    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:empeco:v:46:y:2014:i:4:p:1521-1544. 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.