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Network Effects in Alternative Fuel Adoption: Empirical Analysis of the Market for Ethanol

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Abstract

This paper investigates the importance of network effects in the demand for ethanol-compatible vehicles and the supply of ethanol fuel retailers. An indirect network effect, or positive feedback loop, arises in this context due to spatially-dependent complementarities in the availability of ethanol fuel and the installed base of ethanol-compatible vehicles. Marketers and social planners are interested in whether these effects exist, and if so, how policy might accelerate adoption of the ethanol fuel standard within a targeted population. To measure these feedback effects, I develop an econometric framework that considers the simultaneous determination of ethanol-compatible vehicle demand and ethanol fuel supply in local markets. The demand-side of the model considers the automobile purchase decisions of consumers and fleet operators, and the supply-side model considers the ethanol market entry decisions of competing fuel retailers. I propose new estimators that address the endogeneity induced by the co-determination of alternative fuel vehicle demand and alternative fuel supply. I estimate the model using zip code level panel data from six states over a six year period. I find the network effect to be highly significant, both statistically and economically. Under typical market conditions, entry of an additional ethanol fuel retailer leads to a 12% increase in consumer demand for ethanol-compatible vehicles. The entry model estimates imply that a monopolist requires a local installed base of at least 204 ethanol-compatible vehicles to be profitable. As an application, I demonstrate how the model estimates can inform the promotional strategy of a vehicle manufacturer. Counterfactual simulations indicate that subsidizing fuel retailers to offer ethanol can be an effective policy to indirectly increase ethanol-compatible vehicle sales.

Suggested Citation

  • Scott K. Shriver, 2010. "Network Effects in Alternative Fuel Adoption: Empirical Analysis of the Market for Ethanol," Working Papers 10-20, NET Institute.
    • Handle: RePEc:net:wpaper:1020
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Matthew T. Clements & Hiroshi Ohashi, 2004. "Indirect Network Effects and the Product Cycle: Video Games in the U.S., 1994-2002," CIRJE F-Series CIRJE-F-261, CIRJE, Faculty of Economics, University of Tokyo.
    3. Steven T. Berry & Joel Waldfogel, 1999. "Free Entry and Social Inefficiency in Radio Broadcasting," RAND Journal of Economics, The RAND Corporation, vol. 30(3), pages 397-420, Autumn.
    4. Harikesh Nair & Pradeep Chintagunta & Jean-Pierre Dubé, 2004. "Empirical Analysis of Indirect Network Effects in the Market for Personal Digital Assistants," Quantitative Marketing and Economics (QME), Springer, vol. 2(1), pages 23-58, March.
    5. Hiroshi Ohashi, 2003. "The Role of Network Effects in the US VCR Market, 1978-1986," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 12(4), pages 447-494, December.
    6. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    7. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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    Cited by:

    1. Paul B. Ellickson & Sanjog Misra, 2011. "Structural Workshop Paper --Estimating Discrete Games," Marketing Science, INFORMS, vol. 30(6), pages 997-1010, November.

    More about this item

    Keywords

    ethanol; flex-fuel vehicles; indirect network e¤ects; market entry;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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