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Open AccessEditorial

Nonparametric Econometric Methods and Applications

Department of Economics and Finance, University of Guelph, Guelph, ON N1G 2W1, Canada
J. Risk Financial Manag. 2019, 12(4), 180;
Received: 28 November 2019 / Accepted: 28 November 2019 / Published: 30 November 2019
(This article belongs to the Special Issue Nonparametric Econometric Methods and Application)
An area of very active research in econometrics over the last 30 years has been that of non- and semi-parametric methods. These methods have provided ways to complement more-traditional parametric approaches in terms of robust alternatives, as well as preliminary data analysis. The present Special Issue collects a number of new contributions, both theoretical and empirical that cover a wide spectrum of areas such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth as well as statistical theory and methodology. View Full-Text
Keywords: nonparametric methods; semiparametric methods; local smoothing; wavelets nonparametric methods; semiparametric methods; local smoothing; wavelets
MDPI and ACS Style

Stengos, T. Nonparametric Econometric Methods and Applications. J. Risk Financial Manag. 2019, 12, 180.

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