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Reducing Approximation Error in the Fourier Flexible Functional Form

Department of Agricultural and Resource Economics, College of Agriculture and Bioresources, Agriculture Building, University of Saskatchewan, Rm 3D24, Saskatoon, SK S7N 5A8, Canada
Academic Editor: Marc S. Paolella
Econometrics 2017, 5(4), 53; https://doi.org/10.3390/econometrics5040053
Received: 29 August 2017 / Revised: 16 November 2017 / Accepted: 22 November 2017 / Published: 4 December 2017
The Fourier Flexible form provides a global approximation to an unknown data generating process. In terms of limiting function specification error, this form is preferable to functional forms based on second-order Taylor series expansions. The Fourier Flexible form is a truncated Fourier series expansion appended to a second-order expansion in logarithms. By replacing the logarithmic expansion with a Box-Cox transformation, we show that the Fourier Flexible form can reduce approximation error by 25% on average in the tails of the data distribution. The new functional form allows for nested testing of a larger set of commonly implemented functional forms. View Full-Text
Keywords: Fourier series; Box-Cox; functional form selection; specification bias Fourier series; Box-Cox; functional form selection; specification bias
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Skolrud, T.D. Reducing Approximation Error in the Fourier Flexible Functional Form. Econometrics 2017, 5, 53.

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