Recent Advances in Estimating Nonlinear Models: With Applications in Economics and Finance

ISBN-13: 9781493952595 / Angielski / Miękka / 2017 / 299 str.

Jun Ma; Mark Wohar

Opis

Featuring current research in economics, finance and management, this book surveys nonlinear estimation techniques and offers new methods and insights into nonlinear time series analysis. Covers Markov Switching Models for analyzing economics series and more.

Spis treści

Chapter 1 Stock Return and Inflation: An Analysis Based on the State-Space Framework.- Chapter 2 Diffusion Index Model Specification and Estimation: Using Mixed Frequency Datasets.- Chapter 3 Testing for Neglected Nonlinearity Using Regularized Artificial Neural Networks.- Chapter 4 On the Use of the Flexible Fourier Form in Unit Roots Tests, Endogenous Breaks, and Parameter Instability.- Chapter 5 Testing for a Markov-Switching Mean in Serially-Correlated Data.- Chapter 6 Nonlinear Time Series Models and Model Selection.- Chapter 7 Nonstationarities and Markov Switching Models.- Chapter 8 Has Wealth Effect Changed Over Time? Evidence from Four Industrial Countries.- Chapter 9 A Simple Specification Procedure for the Transition Function in Persistent Nonlinear Times Series Models.- Chapter 10 Small Area Estimation with Correctly Specified Linking Models.- Chapter 11 Forecasting Stock Returns: Does Switching between Models Help?.- Chapter 12 The Global Joint Distribution of Income and Health.

O autorze

Jun Ma

Professor Ma’s primary research interests are Macroeconomics, International Finance, Asset Pricing, and Time Series Econometrics. He has published in journals such as Journal of International Economics, Journal of Money, Credit, and Banking, Journal of Economic Dynamics and Control, Studies in Nonlinear Dynamics and Econometrics, Journal of Banking and Finance, and European Journal of Finance. He was a visiting scholar at Norges Bank (the central bank of Norway) and has been invited to present his research work at central banks and universities, including Norges Bank, Federal Reserve Bank of St. Louis, University of Washington, Virginia Tech, University of Houston, University of Kansas, and University of Nebraska at Omaha.

Department of Economic, Finance, and Legal Studies University of Alabama Tuscaloosa, AL 35487 USA jma@cba.ua.edu Mark E. Wohar Department of Economics University of Nebraska-Omaha RH 512K Omaha, NE 68182 mwohar@mail.unomaha.edu

Mark E. Wohar

Professor Wohar's areas of research include, Domestic and International Macroeconomics, International Finance, Monetary Theory and Financial Economics, Financial Institutions, and Applied Time Series Econometrics. He has published over 120 refereed journal articles. Some of his more noteworthy publications have appeared in journals such as the American Economic Review, Economic Journal, Journal of Finance, Journal of International Economics, Economic Inquiry, Journal of Applied Econometrics, Journal of Forecasting, International Journal of Forecasting, Review of Economics and Statistics, and Journal of Money, Credit and Banking. His research has been cited by more than 950 papers of other authors. He has received many awards for research excellence. Wohar has presented his research at a number of Universities (both in the US and abroad), including Kansas State University, Michigan State University, University of New Orleans, University of Notre Dame, Ohio State University, University of Washington, University of California-San Diego, Southern Methodist University, University of Wisconsin-Madison, University of Syracuse, University of Illinois, University of Essex, Cambridge University, University of Warwick, University of Nottingham, University of Durham, Cass Business School-London, University of Kansas, University of California at Davis, among others.

Blurb

This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. The focus is on such topics as state-space model and the identification issue, use of Markov Switching Models and Smooth Transition Models to analyze economic series, and how best to distinguish between competing nonlinear models. Most economic theory suggests that the economic relationships among economic variables in the real world are fairly complex and nonlinear. Nonlinear models are necessary to capture these important channels through which economic variables can influence each other and various policies can affect economic activities. This volume features cutting-edge research from leading academics in economics, finance, and business management. The principles and techniques used here will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.