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Nonparametric Econometric Methods and Application Journal of Nonparametric Econometric Methods and Application Edited by Thanasis Stengos Printed Edition of the Special Issue Published in Journal of Risk and Financial Management www.mdpi.com/journal/jrfm Nonparametric Econometric Methods and Application Nonparametric Econometric Methods and Application Special Issue Editor Thanasis Stengos MDPI • Basel • Beijing • Wuhan • Barcelona • Belgrade Special Issue Editor Thanasis Stengos University of Guelph Canada Editorial Office MDPI St. Alban-Anlage 66 4052 Basel, Switzerland This is a reprint of articles from the Special Issue published online in the open access journal Journal of Risk and Financial Management (ISSN 1911-8074) from 2018 to 2019 (available at: https:// www.mdpi.com/journal/jrfm/special issues/nonparametric econometric). For citation purposes, cite each article independently as indicated on the article page online and as indicated below: LastName, A.A.; LastName, B.B.; LastName, C.C. Article Title. Journal Name Year, Article Number, Page Range. ISBN 978-3-03897-964-7 (Pbk) ISBN 978-3-03897-965-4 (PDF) c 2019 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND. Contents About the Special Issue Editor ...................................... vii Preface to ”Nonparametric Econometric Methods and Application” ................ ix Yiguo Sun and Ximing Wu Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study Reprinted from: JRFM 2018, 11, 29, doi:10.3390/jrfm11020029 .................... 1 Pantelis Kalaitzidakis, Theofanis P. Mamuneas and Thanasis Stengos Greenhouse Emissions and Productivity Growth Reprinted from: JRFM 2018, 11, 38, doi:10.3390/jrfm11030038 .................... 21 Karen X. Yan and Qi Li Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data Model Reprinted from: JRFM 2018, 11, 44, doi:10.3390/jrfm11030044 .................... 35 Nickolaos G. Tzeremes Financial Development and Countries’ Production Efficiency: A Nonparametric Analysis Reprinted from: JRFM 2018, 11, 46, doi:10.3390/jrfm11030046 .................... 45 Burak Alparslan Ero˜glu and Barı¸s Soybilgen On the Performance of Wavelet Based Unit Root Tests Reprinted from: JRFM 2018, 11, 47, doi:10.3390/jrfm11030047 .................... 58 Chaoyi Chen and Yiguo Sun Monte Carlo Comparison for Nonparametric Threshold Estimators Reprinted from: JRFM 2018, 11, 49, doi:10.3390/jrfm11030049 .................... 80 Mark J. Jensen and John M. Maheu Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis Reprinted from: JRFM 2018, 11, 52, doi:10.3390/jrfm11030052 .................... 95 Chuong Luong and Nikolai Dokuchaev Forecasting of Realised Volatility with the Random Forests Algorithm Reprinted from: JRFM 2018, 11, 61, doi:10.3390/jrfm11040061 ....................124 Mustafa Koroglu Growth and Debt: An Endogenous Smooth Coefficient Approach Reprinted from: JRFM 2019, 12, 23, doi:10.3390/jrfm12010023 ....................139 Sadat Reza and Paul Rilstone Smoothed Maximum Score Estimation of Discrete Duration Models Reprinted from: JRFM 2019, 12, 64, doi:10.3390/jrfm12020064 ....................161 Luk´aˇs Melecky,´ Michaela Stan´ıˇckov´a and Jana Hanˇclov´a Nonparametric Approach to Evaluation of Economic and Social Development in the EU28 Member States by DEA Efficiency Reprinted from: JRFM 2019, 12, 72, doi:10.3390/jrfm12020072 ....................177 v About the Special Issue Editor Thanasis Stengos is a member of the Department of Economics and Finance of the University of Guelph, Canada, where he has held a University Research Chair position since 2004. He received his B.Sc. and M.Sc. in Economics from the London School of Economics and his Ph.D. from Queen’s University, Canada. He currently serves as an Associate Editor of the Journal of Applied Econometrics, Empirical Economics, and Economics Letters, he is a member of the editorial board of the Journal of Risk and Financial Management, and he is coeditor of the Review of Economic Analysis. His research has been published in journals including the Review of Economic Studies, European Economic Review, International Economic Review, Economic Journal, Journal of Monetary Economics, Journal of Econometrics, Econometric Theory, The Review of Economic and Statistics, Journal of Applied Econometrics, Journal of Business and Economic Statistics, and the Journal of Economic Growth. vii Preface to ”Nonparametric Econometric Methods and Application” An area of very active research in econometrics over the last 30 years has been that of non- and semiparametric methods. These methods have provided ways to complement more traditional parametric approaches in terms of robust alternatives as well as preliminary data analysis. The field has expanded with important advances both in time series and cross-sectional frameworks and more recently in panel data settings, allowing for data-driven flexibility that has proved invaluable in applied research. The methodology has been enhanced by software developments that have made these methods easy to apply, which has opened up a variety of potentially important and relevant applications in all areas of economics: microeconomics, macroeconomics, economic growth, finance, and labor, etc. The present Special Issue collects a number of new contributions both at the theoretical level and in terms of applications. The papers in the collection cover a number of different topics. Sun and Wu study the contemporaneous relationship between S&P 500 index returns and log increments of the market volatility index (VIX) via a nonparametric copula method, where they propose a conditional dependence index to investigate how the dependence between the two series varies across different segments of the market return distribution. Kalaitzidakis, Mamuneas and Stengos use a smooth coefficient semiparametric model to examine the effect of emissions, as measured by carbon dioxide (CO2), on economic growth among a set of OECD countries during the period 1981–1998 and directly estimate the output elasticity of emissions. Yan and Li develop a nonparametric method to estimate a conditional quantile function for a panel data model with an additive individual fixed effects, a model that can be applied to a variety of circumstances. Tzeremes examines the effect of financial development on countries’ production efficiency levels and develops robust (order-m) time-dependent conditional nonparametric frontier estimators in order to measure 87 countries’ production efficiency levels over the period 1970–2014. Eroglu and Soybilgen apply wavelet methods in the popular augmented Dickey–Fuller and M types of unit root tests, and they perform an extensive comparison of the wavelet-based unit root tests, which also includes the recent contributions in the literature. Chen and Sun compare the finite sample performance of three nonparametric threshold estimators via the Monte Carlo method, and they find that the finite sample performance of the three estimators is not robust to the position of the threshold level along the distribution of the threshold variable, especially when a structural change occurs at the tail part of the distribution. Jensen and Maheu examine the presence of volatility feedback in the often-debated risk–return relationship by modeling the contemporaneous relationship between market excess returns and log-realized variances with a nonparametric, infinitely ordered, mixture representation of the observables’ joint distribution. Luong and Dokuchaev address the forecasting of realized volatility for financial time series using the heterogeneous autoregressive model (HAR) and machine learning techniques, and they find that their proposed model offers improvements when applied to historical high-frequency data. Koroglu investigates the public debt and economic growth relationship using the semiparametric smooth coefficient approach that allows democracy to influence this relationship and parameter heterogeneity in the unknown functional form and addresses the endogeneity of variables. Reza and Rilstone extend Horowitz’s smoothed maximum score estimator to discrete-time duration models. They derive both asymptotic properties and examine finite sample performance through Monte Carlo simulations. Finally, Melecky, Stanickova ix and Hanclova apply data envelopment analysis (DEA) methodology to compare the dynamic efficiency of European countries over the last decade. All of the above papers cover many diverse applications and contributions of nonparametric methods that we hope will add to the already rich literature and become useful additions to applied and theoretical econometricians alike. Thanasis Stengos Special Issue Editor x Journal of Risk and Financial Management Article Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study Yiguo Sun 1,* and Ximing Wu 2 1 Department of Economics and Finance, University of Guelph, Guelph, ON N1G2W1, Canada 2 Department of Agricultural Economics, Texas A&M University, College Station, TX 77843, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-519-824-4120 Received: 5 April 2018; Accepted:
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