Published since April 1, 1996

Studies in Nonlinear Dynamics & Econometrics

ISSN: 1558-3708

Edited by: Bruce Mizrach

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About this journal

Objective
A peer-reviewed journal since 1996, Studies in Nonlinear Dynamics & Econometrics (SNDE) is at the forefront of statistical and theoretical approaches to economics. The journal studies ways in which econometrics and dynamical systems theory increase our understanding of economic and financial markets. The journal disseminates authors' algorithms, programs, and data sets, allowing other scholars to replicate empirical results. Authors include econometricians such as Clive Granger, James Hamilton, and Halbert White, and theorists Jess Benhabib, Alan Kirman, and Kazuo Nishimura.

Best Paper Award
Since 2015, the Society has awarded $500 each year to the best paper published in the Society’s journal: Studies in Nonlinear Dynamics and Econometrics.

The Best Paper in 2022 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Szabolcs Blazsek, Alvaro Escribano and Adrian Licht. for their paper: "Multivariate Markov-switching score-driven models: an application to the global crude oil market" Studies in Nonlinear Dynamics & Econometrics, vol. 26, no. 3, 2022, pp. 313-335.

The Best Paper in 2021 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Eric Mark Aldrich and Howard Kung for their paper: “Computational Methods for Production-Based Asset Pricing Models with Recursive Utility”, published in Volume 25, Issue 1.

The Best Paper in 2020 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Gregor Bäurle, Daniel Kaufmann, Sylvia Kaufmann and Rodney Strachan for their paper: “Constrained interest rates and changing dynamics at the zero lower bound”, published in Volume 24, Issue 2.

The Best Paper in 2019 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Chang-Jin Kim and Yunmi Kim for their paper: “A unified framework jointly explaining business conditions, stock returns, volatility and “volatility feedback news” effects”, published in Volume 23, Issue 2.

The Best Paper in 2018 for Studies in Nonlinear Dynamics and Econometrics, has been awarded to Luiggi Donayre, Yunjong Eo and James Morley for their paper: “Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples”,published in Volume 22, Issue 1 (Feb 2018)

The Best Paper in 2017 for Studies in Nonlinear Dynamics and Econometrics has been awarded to Julien Chevallier and Stephane Goutte for their paper: “On the estimation of regime-switching Levy models”, published in Volume 21, Issue 1 (Feb 2017).

The Best Paper in 2016 for Studies in Nonlinear Dynamics and Econometrics has been awarded to Mark J. Jensen for his paper: “Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility?”, published in Volume 20, Issue 4 (Sept. 2016).

The Best Paper in 2015 for Studies in Nonlinear Dynamics and Econometrics has been awarded to Markus Jochmann and Gary Koop for their paper: “Regime-switching cointegration?”, published in Volume 19, Issue 1 (Feb 2015).

Topics

Probability
Statistics
Macroeconomics
Finance
Forecasting
Econometrics

Article formats
Research articles

Information on submission process

Your Benefits

Your benefits:

Theoretical and applied studies that characterize and motivate nonlinear phenomena
State-of the-art research results that increase understanding of economic and financial markets
Novel tools that allow replication of empirical results
High quality peer-review
International and renowned editorial board

History

Content available since 1996 (Volume 1, Issue 1)

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External Links

Online Submission of Manuscripts

Volume 27 Issue 2

April 2023

Publicly Available April 24, 2023

Frontmatter

Page range: i-ii

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Research Articles

April 13, 2022

Asymmetry in stochastic volatility models with threshold and time-dependent correlation

Torben Schäfers, Long Teng

Page range: 131-146

Abstract

In this work we study the effects by including threshold, constant and time-dependent correlation in stochastic volatility (SV) models to capture the asymmetry relationship between stock returns and volatility. We develop SV models which include only time-dependent correlated innovations and both threshold and time-dependent correlation, respectively. It has been shown in literature that the SV model with only constant correlation does a better job of capturing asymmetry than threshold stochastic volatility (TSV) model. We show here that the SV model with time-dependent correlation performs better than the model with constant correlation on capturing asymmetry, and the comprehensive model with both threshold and time-dependently correlated innovations dominates models with pure threshold, constant and time-dependent correlation, and both threshold and constant correlation as well. In our comprehensive model, volatility and returns are time-dependently correlated, where the time-varying correlation is negative, and the volatility is more persistent, less volatile and higher following negative returns as expected. An empirical study is provided to illustrate our findings.

April 21, 2022

Financial crisis spread, economic growth and unemployment: a mathematical model

Calvin Tadmon, Eric Rostand Njike Tchaptchet

Page range: 147-170

Abstract

The unemployment is the main channel through which the economic and financial crises influence the social development. In this paper, we propose a mathematical model to study the interactions between financial crisis spread, economic growth and unemployment. We also solve an optimal control problem focusing on the minimization, at the lowest cost, of the adverse effects of the financial crisis. The analysis of the model leads us to two equilibria: (1) a stress free equilibrium, where the economy and the employment are optimal, and (2) a stressed equilibrium. We obtain a theoretical confirmation of Okun’s law and a formula to compute the minimum reservation wage in terms of model parameters. Numerical simulations are performed to illustrate the theoretical results obtained.

Article

Open Access August 10, 2022

Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects

Ioannis Papantonis, Leonidas S. Rompolis, Elias Tzavalis, Orestis Agapitos

Page range: 171-198

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Abstract

This paper extends the Realized-GARCH framework, by allowing the conditional variance equation to incorporate exogenous variables related to intra-day realized measures. The choice of these measures is motivated by the so-called heterogeneous auto-regressive (HAR) class of models. Our augmented model is found to outperform both the Realized-GARCH and the various HAR models in terms of in-sample fitting and out-of-sample forecasting accuracy. The new model specification is examined under alternative parametric density assumptions for the return innovations. Non-normality seems to be very important for filtering the return innovations to which variance responds and helps significantly upon the prediction performance of the suggested model.

Research Articles

April 21, 2022

Unrestricted, restricted, and regularized models for forecasting multivariate volatility

Stanislav Anatolyev, Filip Staněk

Page range: 199-218

Abstract

We perform an extensive investigation of different specifications of the BEKK-type multivariate volatility models for a moderate number of assets, focusing on how the degree of parametrization affects forecasting performance. Because the unrestricted specification may be too generously parameterized, often one imposes restrictions on coefficient matrices constraining them to have a diagonal or even scalar structure. We frame all three model variations (full, diagonal, scalar) as special cases of a ridge-type regularized estimator, where the off-diagonal elements are shrunk towards zero and the diagonal elements are shrunk towards homogeneity. Our forecasting experiments with BEKK-type Conditional Autoregressive Wishart model for realized volatility confirm the superiority of the more parsimonious scalar and diagonal model variations. Even though sometimes a moderate degree of regularization of the diagonal and off-diagonal parameters may be beneficial for forecasting performance, it does not regularly lead to tangible performance improvements irrespective of how precise is tuning of regularization intensity. Additionally, our results highlight the crucial importance of frequent model re-estimation in improving the forecast precision, and, perhaps paradoxically, a slight advantage of shorter estimation windows compared to longer windows.

Open Access April 21, 2022

Controlling chaos in New Keynesian macroeconomics

William A. Barnett, Giovanni Bella, Taniya Ghosh, Paolo Mattana, Beatrice Venturi

Page range: 219-236

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Abstract

In a New Keynesian model, it is believed that combining active monetary policy using a Taylor rule with a passive fiscal rule can achieve local equilibrium determinacy. However, even with such policies, indeterminacy can occur from the emergence of a Shilnikov chaotic attractor in the region of the feasible parameter space. That result, shown by Barnett et al. (2022a), “Shilnikov Chaos, Low Interest Rates, and New Keynesian Macroeconomics ,” Journal of Economic Dynamics and Control 134, and again by Barnett et al. (2022b), “Is Policy Causing Chaos in the United Kingdom,” Economic Modeling 108, implies that the presence of the Shilnikov chaotic attractor can cause the economy to drift towards and finally become stuck in the vicinity of lower-than-targeted inflation and nominal interest rates. The result can become the source of a liquidity trap phenomenon. We propose policy options for eliminating or controlling Shilnikov chaotic dynamics to help the economy escape from the liquidity trap or avoid drifting into it in the first place. We consider ways to eliminate or control the chaos by replacing the usual Taylor rule by an alternative policy design without interest rate feedback, such as a Taylor rule with monetary quantity feedback, an active fiscal policy rule with passive monetary rule, or an open loop policy without feedback. We also consider approaches that retain the Taylor rule with interest rate feedback and the associated Shilnikov chaos, while controlling the chaos through a well-known engineering algorithm using a second policy instrument. We find that a second instrument is needed to incorporate a long-run terminal condition missing from the usual myopic Taylor rule.

March 31, 2022

Conservatorship, quantitative easing, and mortgage spreads: a new multi-equation score-driven model of policy actions

Szabolcs Blazsek, Virag Blazsek, Adam Kobor

Page range: 237-264

Abstract

In this paper, the effects of United States (US) policy actions on mortgage-backed security and mortgage loan spreads are measured, by using data before, during, and after the US subprime mortgage crisis. We study the effects of the following policy actions: (i) the placement of Fannie Mae and Freddie Mac into US Government conservatorship; (ii) the US Federal Reserve quantitative easing (QE) programs. We provide the following contributions to the literature: (i) for a robust measurement of policy effects, a new multi-equation score-driven t -QVARMA (quasi-vector autoregressive moving average) model is used. (ii) In addition to the measurement of the effects of QE, the effects of government conservatorship are also measured in this paper. (iii) Furthermore, the data period of the relevant literature is extended to the period of June 1998 to March 2020.

Open Access February 2, 2022

Expected, unexpected, good and bad aggregate uncertainty

Jorge M. Uribe, Helena Chuliá

Page range: 265-284

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Abstract

We study aggregate uncertainty and its linear and nonlinear impact on real and financial markets. By distinguishing between four general notions of aggregate uncertainty (good-expected, bad-expected, good-unexpected, bad-unexpected) within a simple, common framework, we show that it is bad-unexpected uncertainty shocks that generate a negative reaction of economic variables (such as investment and consumption) and asset prices. Our results help to elucidate the real, complex nature of uncertainty, which can be both a backward- or forward-looking expected or unexpected event, with markedly different consequences for the economy. We also document nonlinearities in the propagation of uncertainty to both real and financial markets, which calls for the close monitoring of the evolution of uncertainty so as to help mitigate the adverse effects of its occurrence.

Ahead of Print / Just Accepted

Ahead of Print / Just Accepted

Volume 27 (2023)

Volume 26 (2022)

Volume 25 (2021)

Volume 24 (2020)

Volume 23 (2019)

Volume 22 (2018)

Volume 21 (2017)

Volume 20 (2016)

Volume 19 (2015)

Volume 18 (2014)

Volume 17 (2013)

Volume 16 (2012)

Volume 15 (2011)

Volume 14 (2010)

Volume 13 (2009)

Volume 12 (2008)

Volume 11 (2007)

Volume 10 (2006)

Volume 9 (2005)

Volume 8 (2004)

Volume 7 (2003)

Volume 6 (2003)

Volume 5 (2002)

Volume 4 (2001)

Volume 3 (1999)

Volume 2 (1998)

Volume 1 (1997)

5-year Journal Impact Factor	1.266
CiteScore	1.3
European Reference Index for the Humanities
Journal Impact Factor	1.032
Journal Citation Indicator	0.37
Mathematical Citation Quotient	0.06
SCImago Journal Rank	0.383
Source Normalized Impact per Paper	0.742

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Editorial

Editor-in-Chief

Bruce Mizrach, Rutgers University

Associate Editors
Heather Anderson, Monash University
Robert A. Becker, Indiana University
Hilde C. Bjørnland, BI Norwegian Business School
Francesco Ravazzolo, University of Bolzano
Yoosoon Chang, Indiana University
Robert de Jong, Ohio State University
Cees Diks, CeNDEF, U. of Amsterdam
Alvaro Escribano, Universidad Carlos III de Madrid
Giancarlo Gandolfo, CIDEI, Universitá di Roma "La Sapienza"
René Garcia, EDHEC Business School
Massimo Guidolin, Bocconi University
Christian Hafner, Université catholique de Louvain
Gary Koop, University of Strathclyde
Dimitris Korobilis, University of Glasgow
Tae-Hwy Lee, University of California-Riverside
Vance Martin, University of Melbourne
Stefan Mittnik, University of Munich
James Morley, University of New South Wales
Kazuo Nishimura, Kyoto University
Michael T. Owyang, Assistant Vice President, Federal Reserve Bank of St. Louis
Jeremy Piger, University of Oregon
Philip Rothman, East Carolina University
Tatevik Sekhposyan, Texas A&M University
Martin Sola, Birkbeck College
Gerhard Sorger, University of Vienna
Ruey Tsay, University of Chicago
Dick van Dijk, Erasmus University
Anastasios Xepapadeas, Athens University of Economics and Business

Advisory Panel

Jess Benhabib, New York University
William A. Brock, University of Wisconsin-Madison
Jean-Michel Grandmont, CREST-CNRS
James D. Hamilton, University of California-San Diego
Jose Scheinkman, Princeton University

(Deutsch)

Online ISSN: 1558-3708
Type: Journal
Language: English
Publisher: De Gruyter
First published: April 1, 1996
Publication Frequency: 5 Issues per Year
Audience: Researchers and professionals in the field of econometrics, economic and financial markets