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    The forecasting accuracy of models of post-award network deployment: An application of maximum score tests

    Access Status
    Fulltext not available
    Authors
    Madden, Gary
    Mayer, W.
    Wu, Chen
    Tran, T.
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Madden, G. and Mayer, W. and Wu, C. and Tran, T. 2015. The forecasting accuracy of models of post-award network deployment: An application of maximum score tests. International Journal of Forecasting. 31: pp. 1153-1158.
    Source Title
    International Journal of Forecasting
    DOI
    10.1016/j.ijforecast.2013.01.002
    ISSN
    0169-2070
    School
    School of Economics and Finance
    URI
    http://hdl.handle.net/20.500.11937/33255
    Collection
    • Curtin Research Publications
    Abstract

    Each mobile network operator’s spectrum is assigned by national governments. Licenses awarded by auctions are tied to post-award network deployment obligations. Using data on 18 countries for the period 2000–2007, this study is the first to empirically forecast aftermarket performance by analysing whether these conditions are met in a timely fashion. The forecasts are conditioned on macroeconomic and market conditions, and package attributes. The models are evaluated based on Mayer and Wu’s (in press) maximum score tests. Traditional probit models are not robust to error misspecifications. However, Manski, 1975 and Manski, 1985 maximum score estimator only imposes median independence, and allows arbitrary heteroskedasticity. One obstacle to empirical implementation is the fact that the asymptotic distribution of the estimator cannot be used for hypothesis testing. Mayer and Wu address the problem using a ‘discretisation’ procedure. The tests do not impose additional assumptions on the data generating process, require a shorter computational time than subsampling, and allow the models to be misspecified. The test statistics reflect differences in forecasting accuracy under the null and alternative hypotheses.

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