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Estimating Internet Users' Demand Characteristics

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  • Mingzhi Li

    ()
    (University of Texas at Austin)

  • Alok Gupta

    ()
    (University of Connecticut)

  • Boris Jukic

    ()
    (George Mason University)

  • Dale O. Stahl

    ()
    (University of Texas at Austin)

  • Andrew B. Whinston

    ()
    (University of Texas at Austin)

Abstract

In this paper we investigate two parametric approaches and one non-parametric approach to estimating Internet users' value of time, an important characteristic of demand for Internet services. The advantages of these approaches are brought out, and the limitations are discussed. The models are tested using data generated from our simulation model of the Internet economy. First, we set up parametric count-data models given the characteristics of the data. While reasonably good results are obtained on all medium and large sized jobs, the method fails on small sized jobs. Second, we develop a nonparametric quasi-Bayesian update algorithm of retrieving the underlying distribution function of Internet users' value of time purely from observations of their choices. Compared with the parametric count data models, good results are obtained on all jobs.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 523.

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Date of creation: 01 Mar 1999
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Handle: RePEc:sce:scecf9:523

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  1. Gupta, Alok & Stahl, Dale O. & Whinston, Andrew B., 1997. "A stochastic equilibrium model of internet pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 21(4-5), pages 697-722, May.
  2. 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 909-38, July.
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