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Polynomial Regressions and Nonsense Inference

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  • Daniel Ventosa-Santaulària

    ()
    (División de Economía, CIDE)

  • Carlos Vladimir Rodríguez-Caballero

    ()
    (Aarhus University and CREATES)

Abstract

Polynomial specifications are widely used, not only in applied economics, but also in epidemiology, physics, political analysis, and psychology, just to mention a few examples. In many cases, the data employed to estimate such estimations are time series that may exhibit stochastic nonstationary behavior. We extend Phillips’ (1986) results by proving an inference drawn from polynomial specifications, under stochastic nonstationarity, is misleading unless the variables cointegrate. We use a generalized polynomial specification as a vehicle to study its asymptotic and finite-sample properties. Our results, therefore, lead to a call to be cautious whenever practitioners estimate polynomial regressions.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2013-40.

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Length: 16 Daniel Ventosa-Santaulària and Carlos Vladimir Rodríguez-Caballero
Date of creation: 11 2013
Date of revision:
Handle: RePEc:aah:create:2013-40

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Polynomial Regression; misleading Inference; Integrated Processes;

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