Advanced Search
MyIDEAS: Login to save this paper or follow this series

Estimating Product Characteristics and Spatial Competition in the Network Television Industry

Contents:

Author Info

  • Ronald Goettler

    (Carnegie Mellon University)

  • Ron Shachar

    (Tel Aviv University)

Registered author(s):

    Abstract

    Assessing the demand for products with characteristics that are unobservable or difficult to measure is becoming increasingly important with the growing proliferation and value of such products. Analyzing industry performance and firm competition in these sectors is hindered by the failure of traditional empirical methods to estimate demand for the products of these sectors. This paper focuses on the network television industry to present: (a) an empirical analysis of spatial competition, and (b) a structural approach to estimating product characteristics and consumer preferences in such industries, and (c) optimal network programming and scheduling given the estimated demand system. We use maximum simulated likelihood to estimate a structural model of viewer choice, yielding estimates of the latent characteristics of each show, the distribution of consumers' preferences for these characteristics, and the state dependence of choices. Results indicate the attribute space spans four dimensions of horizontal differentiation and one vertically differentiated dimension. Interpretations of these dimensions reflect the traditional show labels. For example, one of the dimensions represents the degree of realism in a show. Furthermore, the clustering of shows based on the estimated characteristics corresponds to traditional show labels. We identify four clusters --- sitcoms for mature viewers, sitcoms for younger viewers, reality based dramas, and fictional dramas. Regarding strategic behavior, our model suggests the networks should use counter-programming (i.e., differentiated products) within each time slot and homogeneous programming through each night. The estimated show locations reveal an extensive use of these strategies, as well as a limited degree of branding. Nonetheless, by unilaterally changing their schedules to increase both counter-programming and homogeneity, ABC, CBS, and NBC are able to increase their weekly ratings by 16%, 12%, and 15%, respectively. In a Nash equilibrium of the static scheduling game, these gains are reduced to 15%, 6%, and 12% increases.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://fmwww.bc.edu/RePEc/es2000/1691.pdf
    File Function: main text
    Download Restriction: no

    Bibliographic Info

    Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 1691.

    as in new window
    Length:
    Date of creation: 01 Aug 2000
    Date of revision:
    Handle: RePEc:ecm:wc2000:1691

    Contact details of provider:
    Phone: 1 212 998 3820
    Fax: 1 212 995 4487
    Email:
    Web page: http://www.econometricsociety.org/pastmeetings.asp
    More information through EDIRC

    Related research

    Keywords:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Goettler, R., 1999. "Advertising Rates, Audience Composition, and Competition in the Network Television Industry," GSIA Working Papers, Carnegie Mellon University, Tepper School of Business 1999-28, Carnegie Mellon University, Tepper School of Business.
    2. V A Hajivassiliou, 1997. "Some Practical Issues in Maximum Simulated Likelihood," STICERD - Econometrics Paper Series, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE /1997/340, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, Econometric Society, vol. 63(4), pages 841-90, July.
    4. Daniel McFadden, 1987. "A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration," Working papers, Massachusetts Institute of Technology (MIT), Department of Economics 464, Massachusetts Institute of Technology (MIT), Department of Economics.
    5. John Rust, 1997. "A Comparison of Policy Iteration Methods for Solving Continuous-State, Infinite-Horizon Markovian Decision Problems Using Random, Quasi-random, and Deterministic Discretizations," Computational Economics, EconWPA 9704001, EconWPA.
    6. A. Papageorgiou & J. F. Traub, 1996. "New Results on Deterministic Pricing of Financial Derivatives," Working Papers, Santa Fe Institute 96-06-040, Santa Fe Institute.
    7. Roland T. Rust & Mark I. Alpert, 1984. "An Audience Flow Model of Television Viewing Choice," Marketing Science, INFORMS, INFORMS, vol. 3(2), pages 113-124.
    8. Hajivassiliou, Vassilis A & Ruud, Paul A., 1993. "Classical Estimation Methods for LDV Models Using Simulation," Department of Economics, Working Paper Series, Department of Economics, Institute for Business and Economic Research, UC Berkeley qt3cg196fr, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    9. James J. Heckman & James M. Snyder, Jr., 1996. "Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators," NBER Working Papers 5785, National Bureau of Economic Research, Inc.
    10. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, Econometric Society, vol. 57(5), pages 1027-57, September.
    11. Spence, A Michael & Owen, Bruce, 1977. "Television Programming, Monopolistic Competition, and Welfare," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 91(1), pages 103-26, February.
    12. Terry Elrod, 1988. "Choice Map: Inferring a Product-Market Map from Panel Data," Marketing Science, INFORMS, INFORMS, vol. 7(1), pages 21-40.
    13. Wagner A. Kamakura & Rajendra K. Srivastava, 1986. "An Ideal-Point Probabilistic Choice Model for Heterogeneous Preferences," Marketing Science, INFORMS, INFORMS, vol. 5(3), pages 199-218.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ecm:wc2000:1691. 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: (Christopher F. Baum).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.