Testing for sign and amplitude asymmetries using threshold autoregressions

Coakley, Jerry; Fuertes, Ana-Marı́a

doi:10.1016/j.jedc.2005.03.007

Cited by 28 publications

(3 citation statements)

References 57 publications

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“…These authors observe that for small fluctuations these macroeconomic variables can depart from equilibrium conditions, however, as the fluctuations become more important exchange rates adjust so as to eliminate profit opportunities and restore equilibrium conditions in assets and exchange rate markets. A related study exploring asymmetries in the dynamics of exchange rates using TAR models is Coakley and Fuertes (2006). For series of unemployment Coakley et al.…”

Section: Empirical Applicationmentioning

confidence: 99%

Threshold quantile autoregressive models

Galvao

Montes‐Rojas

Olmo

2010

Journal of Time Series Analysis

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We study in this article threshold quantile autoregressive processes. In particular we propose estimation and inference of the parameters in nonlinear quantile processes when the threshold parameter defining nonlinearities is known for each quantile, and also when the parameter vector is estimated consistently. We derive the asymptotic properties of the nonlinear threshold quantile autoregressive estimator. In addition, we develop hypothesis tests for detecting threshold nonlinearities in the quantile process when the threshold parameter vector is not identified under the null hypothesis. In this case we propose to approximate the asymptotic distribution of the composite test using a p-value transformation. This test contributes to the literature on nonlinearity tests by extending Hansen's (Econometrica 64, 1996, pp.413-430) methodology for the conditional mean process to the entire quantile process. We apply the proposed methodology to model the dynamics of US unemployment growth after the Second World War. The results show evidence of important heterogeneity associated with unemployment, and strong asymmetric persistence on unemployment growth.

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Section: Empirical Applicationmentioning

confidence: 99%

Threshold quantile autoregressive models

Galvao

Montes‐Rojas

Olmo

2010

Journal of Time Series Analysis

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“…Using nonparametric techniques, the seminal paper of Neftci (1984) finds unemployment rises to be sudden, and falls to be gradual; see also Sichel (1989) and Rothman (1991). Various parametric nonlinear time series models of unemployment have also been estimated in the literature by Hansen (1997), Bianchi and Zoega (1998), Koop and Potter (1999), Papell et al (2000), Caner and Hansen (2001), Skalin and Teräsvirta (2002), Coakley and Fuertes (2006), Caporale and Gil-Alana (2007), among others. All these studies assume Markov-switching, threshold or smooth transition specifications.…”

Section: Introductionmentioning

confidence: 99%

Unemployment and Hysteresis: A Nonlinear Unobserved Components Approach

Sanzo¹,

Pérez-Alonso²

2010

Studies in Nonlinear Dynamics &Amp; Econometrics

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A new test for hysteresis based on a nonlinear unobserved components model is proposed. Observed unemployment rates are decomposed into a natural rate component and a cyclical component. Threshold type nonlinearities are introduced by allowing past cyclical unemployment to have a different impact on the natural rate depending on the regime of the economy. The impact of lagged cyclical shocks on the current natural component is the measure of hysteresis. To derive an appropriate p-value for a test for hysteresis two alternative bootstrap algorithms are proposed: the first is valid under homoskedastic errors and the second allows for heteroskedasticity of unknown form. A Monte Carlo simulation study shows the good performance of both bootstrap algorithms. The bootstrap testing procedure is applied to data from Italy, France and the United States. We find evidence of hysteresis for all countries under study.JEL classification: C12; C13; C15; C32; E24.

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“…These maps are often referred to as TAR(1)-models and are frequently used in several applied scientific branches for describing nonlinearities encountered in data, see e. g. Hansen (2001, 2004), Coakley and Fuertes (2006), Strikholm and Teräsvirta (2006), and Stenseth, Chan, Framstad, and Tong (1998), Tong (1990) and references therein.…”

Section: Introductionmentioning

confidence: 99%

An elementary approach to dynamics and bifurcations of skew tent maps

Lindström¹,

Thunberg

2008

Journal of Difference Equations and Applications

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In this paper the dynamics of skew tent maps are classified in terms of two bifurcation parameters. In time series analysis such maps are usually referred to as continuous threshold autoregressive models (TAR(1) models) after Tong (1990). This study contains results simplifying the use of TAR(1) models considerably, e. g. if a periodic attractor exists it is unique. On the other hand we also claim that care must be exercised when threshold autoregressive (TAR) models are used. In fact, they possess a very special type of dynamical pattern with respect to the bifurcation parameters and their transition to chaos is far from standard.

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Testing for sign and amplitude asymmetries using threshold autoregressions

Cited by 28 publications

References 57 publications

Threshold quantile autoregressive models

Threshold quantile autoregressive models

Unemployment and Hysteresis: A Nonlinear Unobserved Components Approach

An elementary approach to dynamics and bifurcations of skew tent maps

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