IDEAS home Printed from https://ideas.repec.org/p/jrp/jrpwrp/2010-024.html
   My bibliography  Save this paper

Product Quality, Product Price, and Share Dynamics in the German Compact Car Market

Author

Listed:
  • Uwe Cantner

    () (School of Economics and Business Administration, Friedrich-Schiller-University Jena)

  • Jens J. Krüger

    () (Technical University Darmstadt, Fachbereich Rechts- und Wirtschaftswissenschaften)

  • Rene Söllner

    () (Friedrich Schiller University Jena, DFG-RTG "The Economics of Innovative Change")

Abstract

The present paper examines one of the central elements of evolutionary thinking - competition formalized by the replicator dynamics mechanism. Using data on product characteristics of automobiles sold on the German domestic market over the period 2001-2006, we construct a competitiveness or fitness variable for each car model applying non-parametric efficiency measurement techniques. The basic question we intend to answer is whether cars providing a higher quality-price ratio for consumers tend to increase their market share compared to variants with lower quality-price ratios. The relationship between a car models' fitness and its market performance is empirically tested in a regression framework. The results show that the principle of `growth of the fitter' is working as suggested by evolutionary theory. In particular, we find that car models with considerably lower fitness than the market average lose, whereas models with above-average fitness gain additional market shares.

Suggested Citation

  • Uwe Cantner & Jens J. Krüger & Rene Söllner, 2010. "Product Quality, Product Price, and Share Dynamics in the German Compact Car Market," Jena Economic Research Papers 2010-024, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2010-024
    as

    Download full text from publisher

    File URL: http://www2.wiwi.uni-jena.de/Papers/jerp2010/wp_2010_024.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kalirajan, K P & Shand, R T, 1999. "Frontier Production Functions and Technical Efficiency Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 13(2), pages 149-172, April.
    2. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    3. Devetag, M Giovanna, 1999. "From Utilities to Mental Models: A Critical Survey on Decision Rules and Cognition in Consumer Choice," Industrial and Corporate Change, Oxford University Press, vol. 8(2), pages 289-351, June.
    4. Léopold Simar & Valentin Zelenyuk, 2011. "Stochastic FDH/DEA estimators for frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(1), pages 1-20, August.
    5. Metcalfe, J S, 1994. "Competition, Fisher's Principle and Increasing Returns in the Selection Process," Journal of Evolutionary Economics, Springer, vol. 4(4), pages 327-346, November.
    6. Frenken, Koen & Saviotti, Paolo P. & Trommetter, Michel, 1999. "Variety and niche creation in aircraft, helicopters, motorcycles and microcomputers," Research Policy, Elsevier, vol. 28(5), pages 469-488, June.
    7. Giovanni Dosi, 2008. "Statistical Regularities in the Evolution of Industries. A Guide through Some Evidence and Challenges for the Theory," L'industria, Società editrice il Mulino, issue 2, pages 185-220.
    8. Andrea Bonaccorsi & Paola Giuri & Francesca Pierotti, 2005. "Technological frontiers and competition in multi-technology sectors," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(1-2), pages 23-42.
    9. Giulio Bottazzi & Angelo Secchi & Federico Tamagni, 2008. "Productivity, profitability and financial performance," Industrial and Corporate Change, Oxford University Press, vol. 17(4), pages 711-751, August.
    10. Léopold Simar, 2007. "How to improve the performances of DEA/FDH estimators in the presence of noise?," Journal of Productivity Analysis, Springer, vol. 28(3), pages 183-201, December.
    11. Inha Oh & Jeong-Dong Lee & Seogwon Hwang & Almas Heshmati, 2010. "Analysis of product efficiency in the Korean automobile market from a consumer’s perspective," Empirical Economics, Springer, vol. 38(1), pages 119-137, February.
    12. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    13. Sidney Winter & Yuri Kaniovski & Giovanni Dosi, 2003. "A baseline model of industry evolution," Journal of Evolutionary Economics, Springer, vol. 13(4), pages 355-383, October.
    14. Winter, S. G. & Kaniovski, Y. M. & Dosi, G., 2000. "Modeling industrial dynamics with innovative entrants," Structural Change and Economic Dynamics, Elsevier, vol. 11(3), pages 255-293, September.
    15. Uwe Cantner & Jens Krüger, 2008. "Micro-heterogeneity and aggregate productivity development in the German manufacturing sector," Journal of Evolutionary Economics, Springer, vol. 18(2), pages 119-133, April.
    16. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    17. Saviotti, P P & Mani, G S, 1995. "Competition, Variety and Technological Evolution: A Replicator Dynamics Model," Journal of Evolutionary Economics, Springer, vol. 5(4), pages 369-392, December.
    18. Lucia Foster & John C. Haltiwanger & C. J. Krizan, 2001. "Aggregate Productivity Growth: Lessons from Microeconomic Evidence," NBER Chapters, in: New Developments in Productivity Analysis, pages 303-372, National Bureau of Economic Research, Inc.
    19. Mazzucato, Mariana, 1998. "A computational model of economies of scale and market share instability," Structural Change and Economic Dynamics, Elsevier, vol. 9(1), pages 55-83, March.
    20. Angel S. Fernandez-Castro & Peter C. Smith, 2002. "Lancaster's characteristics approach revisited: product selection using non-parametric methods," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 23(2), pages 83-91.
    21. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    22. Wilson, Paul W., 2008. "FEAR: A software package for frontier efficiency analysis with R," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 247-254, December.
    23. Matthias Staat & Maik Hammerschmidt, 2005. "Product performance evaluation: a super-efficiency model," International Journal of Business Performance Management, Inderscience Enterprises Ltd, vol. 7(3), pages 304-319.
    24. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    25. Krüger, Jens, 2008. "Intra-Sectoral Structural Change and Aggregate Productivity Development: A Robust Stochastic Nonparametric Frontier Function Approach," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 34397, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    26. Christos Papahristodoulou, 1997. "A DEA model to evaluate car efficiency," Applied Economics, Taylor & Francis Journals, vol. 29(11), pages 1493-1508.
    27. Kwasnicki, Witold & Kwasnicka, Halina, 1992. "Market, innovation, competition: An evolutionary model of industrial dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 19(3), pages 343-368, December.
    28. Saviotti, P. P. & Metcalfe, J. S., 1984. "A theoretical approach to the construction of technological output indicators," Research Policy, Elsevier, vol. 13(3), pages 141-151, June.
    29. Grupp, Hariolf, 1994. "The measurement of technical performance of innovations by technometrics and its impact on established technology indicators," Research Policy, Elsevier, vol. 23(2), pages 175-193, March.
    30. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
    31. David C. Wheelock & Paul W. Wilson, 2003. "Robust nonparametric estimation of efficiency and technical change in U.S. commercial banking," Working Papers 2003-037, Federal Reserve Bank of St. Louis.
    32. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
    33. Frenken, Koen & Leydesdorff, Loet, 2000. "Scaling trajectories in civil aircraft (1913-1997)," Research Policy, Elsevier, vol. 29(3), pages 331-348, March.
    34. Jeffrey M. Wooldridge, 2003. "Cluster-Sample Methods in Applied Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 133-138, May.
    35. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    36. Gibbons, M. & Coombs, R. & Saviotti, P. & Stubbs, P. C., 1982. "Innovation and technical change : A case study of the U.K. tractor industry, 1957 1977," Research Policy, Elsevier, vol. 11(5), pages 289-310, October.
    37. Zvi Griliches & Haim Regev, 1992. "Productivity and Firm Turnover in Israeli Industry: 1979-1988," NBER Working Papers 4059, National Bureau of Economic Research, Inc.
    38. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    39. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    40. H. H. Bauer & M. Staat & M. Hammerschmidt, 2003. "Value Based Benchmarking and Market Partitioning," Microeconomics 0309004, University Library of Munich, Germany.
    41. Matthias Staat & Hans H. Bauer & Maik Hammerschmidt, 2004. "Structuring Product-Markets: An Approach Based On Customer Value," Microeconomics 0401002, University Library of Munich, Germany.
    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. Uwe Cantner & Ivan Savin & Simone Vannuccini, 2019. "Replicator dynamics in value chains: explaining some puzzles of market selection," Industrial and Corporate Change, Oxford University Press, vol. 28(3), pages 589-611.
    2. Antti Simola, 2018. "Government payments, market profits and structural change in agriculture," Journal of Evolutionary Economics, Springer, vol. 28(4), pages 837-857, September.
    3. Kaldasch, Joachim, 2015. "Dynamic Model of Markets of Homogenous Non-Durables," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 1-12.
    4. Giovanni Dosi & Emanuele Pugliese & Pietro Santoleri, 2017. "Growth and survival of the `fitter'? Evidence from US new-born firms," LEM Papers Series 2017/06, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Flavio Calvino & Maria Enrica Virgillito, 2016. "The Innovation-Employment nexus: a critical survey of theory and empirics," LEM Papers Series 2016/10, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Jan-Dirk Schmöcker & Tsuyoshi Hatori & David Watling, 2014. "Dynamic process model of mass effects on travel demand," Transportation, Springer, vol. 41(2), pages 279-304, March.
    7. Kaldasch, Joachim, 2014. "Evolutionary Model of Moore’s Law," MPRA Paper 54397, University Library of Munich, Germany.
    8. Claussen, Jörg & Essling, Christian & Kretschmer, Tobias, 2015. "When less can be more – Setting technology levels in complementary goods markets," Research Policy, Elsevier, vol. 44(2), pages 328-339.
    9. Zhao Rong & David C. Broadstock & Yuanyuan Peng, 2018. "Initial submarket positioning and firm survival: evidence from the British automobile industry, 1895–1970," Small Business Economics, Springer, vol. 51(4), pages 965-993, December.
    10. Uwe Cantner, 2016. "Foundations of economic change—an extended Schumpeterian approach," Journal of Evolutionary Economics, Springer, vol. 26(4), pages 701-736, October.
    11. van der Vooren, A. & Alkemade, F. & Hekkert, M.P., 2013. "Environmental performance and firm strategies in the dutch automotive sector," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 111-126.

    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. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    2. Massimo Finocchiaro Castro & Calogero Guccio & Ilde Rizzo, 2014. "An assessment of the waste effects of corruption on infrastructure provision," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 21(4), pages 813-843, August.
    3. Krüger, Jens J., 2012. "A Monte Carlo study of old and new frontier methods for efficiency measurement," European Journal of Operational Research, Elsevier, vol. 222(1), pages 137-148.
    4. Andreas Pyka & Uwe Cantner & Alfred Greiner & Thomas Kuhn (ed.), 2009. "Recent Advances in Neo-Schumpeterian Economics," Books, Edward Elgar Publishing, number 12982.
    5. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    6. Keshvari, Abolfazl & Kuosmanen, Timo, 2013. "Stochastic non-convex envelopment of data: Applying isotonic regression to frontier estimation," European Journal of Operational Research, Elsevier, vol. 231(2), pages 481-491.
    7. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2014. "La spesa sanitaria delle Regioni in Italia - Saniregio 3," Working Papers CERM 02-2014, Competitività, Regole, Mercati (CERM).
    8. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    9. Isabel Narbón-Perpiñá & Mª Teresa Balaguer-Coll & Marko Petrovic & Emili Tortosa-Ausina, 2017. "Which estimator to measure local governments’ cost efficiency? An application to Spanish municipalities," Working Papers 2017/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    10. Isabel Narbón-Perpiñá & Maria Teresa Balaguer-Coll & Marko Petrović & Emili Tortosa-Ausina, 2020. "Which estimator to measure local governments’ cost efficiency? The case of Spanish municipalities," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 11(1), pages 51-82, March.
    11. Andor, Mark A. & Parmeter, Christopher & Sommer, Stephan, 2019. "Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes," European Journal of Operational Research, Elsevier, vol. 274(1), pages 240-252.
    12. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    13. Calogero Guccio & Marco Ferdinando Martorana & Luisa Monaco, 2016. "Evaluating the impact of the Bologna Process on the efficiency convergence of Italian universities: a non-parametric frontier approach," Journal of Productivity Analysis, Springer, vol. 45(3), pages 275-298, June.
    14. Alex Coad & Tom Broekel, 2012. "Firm growth and productivity growth: evidence from a panel VAR," Applied Economics, Taylor & Francis Journals, vol. 44(10), pages 1251-1269, April.
    15. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2015. "La spesa sanitaria delle Regioni in Italia - Saniregio 2015," Working Papers CERM 01-2015, Competitività, Regole, Mercati (CERM), revised 04 Jan 2016.
    16. Halkos, George & Tzeremes, Nickolaos, 2009. "Exploring the effect of countries’ economic prosperity on their biodiversity performance," MPRA Paper 32102, University Library of Munich, Germany.
    17. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
    18. Ghulam, Yaseen & Jaffry, Shabbar, 2015. "Efficiency and productivity of the cement industry: Pakistani experience of deregulation and privatisation," Omega, Elsevier, vol. 54(C), pages 101-115.
    19. González, Eduardo & Cárcaba, Ana & Ventura, Juan, 2015. "How car dealers adjust prices to reach the product efficiency frontier in the Spanish automobile market," Omega, Elsevier, vol. 51(C), pages 38-48.
    20. Marijn Verschelde & Michel Dumont & Glenn Rayp & Bruno Merlevede, 2016. "Semiparametric stochastic metafrontier efficiency of European manufacturing firms," Journal of Productivity Analysis, Springer, vol. 45(1), pages 53-69, February.

    More about this item

    Keywords

    Replicator Dynamics; Product Characteristics; Data Envelopment Analysis;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

    NEP fields

    This paper has been announced in the following NEP Reports:

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Studies on the automobile industry

    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:jrp:jrpwrp:2010-024. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Markus Pasche). General contact details of provider: http://www.wiwiss.uni-jena.de/ .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.