Detecting Mean Reversion in Real Exchange Rates from a Multiple Regime STAR Model

Bec, Frédérique; Salem, Mélika Ben; Carrasco, Marine

doi:10.2139/ssrn.556738

Cited by 11 publications

(5 citation statements)

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“…Enders and Granger (1998), Caner and Hansen (2001), and Bec et al (2008) conduct tests in the context of the threshold autoregressive model. Kapetanios et al (2003), Park and Shintani (2005), Bec et al (2010), and Kiliç (2011) propose a unit root test based on the STAR model.…”

Section: Unit Root Testmentioning

confidence: 99%

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Modeling the Phillips Curve in China: A Nonlinear Perspective

Zhang

2016

Macroecon. Dynam.

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This paper investigates the nonlinear dynamics of the inflation–output type of Phillips curve based on a multiple-regime smooth transition regression model using data from China. The empirical results indicate significant nonlinearities in China's Phillips curve. The relationship between inflation and output can be modeled by a four-regime smooth transition regression model in which the responses of inflation to output depend on both inflation and economic growth rates. The inflation–output type Phillips curve may be positively sloped, negatively sloped, or even vertical in the short term, depending on different business cycles. Furthermore, we analyze business cycle fluctuations based on the nonlinear Phillips curve, indicating a coexisting zone of stable inflation rate and rapid growth rate.

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Section: Unit Root Testmentioning

confidence: 99%

“…To make the test results more robust, this paper applies traditional linear and nonlinear unit root tests proposed by Kapetanios et al (2003), Park and Shintani (2005), Bec et al (2010), and Kiliç (2011) (denoted by t N , inf-t, W sup , and t ESTAR , respectively). 5 Table 1 displays the test results.…”

Section: Unit Root Testmentioning

confidence: 99%

Modeling the Phillips Curve in China: A Nonlinear Perspective

Zhang

2016

Macroecon. Dynam.

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“…Bec et al proposed the BBC URT which considers a three‐regime SETAR model. They allow a unit root in the middle regime in the middle regime under the alternative hypothesis, but not for the high and low regimes.…”

Section: Stationary Time Seriesmentioning

confidence: 99%

Unit root tests

Herranz

2017

WIREs Computational Stats

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Unit roots are nonstationary autoregressive (AR) or autoregressive moving average (ARMA) time series processes which may include an intercept and/or a trend. These processes are used often in economics and finance, but can also be found in other scientific fields. Unit root tests address the null hypothesis of a unit root, and an alternative hypothesis of a stationary (or trend stationary) time series. Critical values for unit root tests are typically derived via simulation of limiting distributions expressed as functionals of Brownian motions. The critical values for the Dickey Fuller unit root test with a constant and linear trend are derived via simulation in the R language. Simulation studies are presented showing that linear regressions with unit root processes often produce spurious results. Additional simulation studies are reviewed providing statistical evidence that near-unit roots can often result in spurious cointegration relationships. Various unit root tests are presented, including ones that allow for structural breaks in intercept and/or trend. Threshold unit root tests are introduced. Simulation studies are used to compare the unit root tests under various scenarios. The case where the analyzed time series may have stationary and nonstationary segments is also considered.

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“…Other studies on unit root tests based on the second approach include Caner and Hansen (2001), Bec et al (2008) and Bec et al (2010). where q = (k, g), k Ն 0 and g ∈ R. The parameter g in the logistic transition function h(z t-d , g) controls the degree of asymmetry.…”

Section: Test Statistics 21 Asymmetric Exponential Transition Functionmentioning

confidence: 99%

“…3 There are many other possibilities for introducing asymmetric U-shaped transition functions. For example, Shintani et al (2013) modify the three-regime logistic smooth transition autoregressive model used in Bec et al (2010) and consider the asymmetric adjustment by allowing the parameter difference between two logistic functions.…”

Section: Test Statistics 21 Asymmetric Exponential Transition Functionmentioning

confidence: 99%

THE INF-TTEST FOR A UNIT ROOT AGAINST ASYMMETRIC EXPONENTIAL SMOOTH TRANSITION AUTOREGRESSIVE MODELS

Shintani

2013

Japanese Economic Review

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This paper proposes a new test for a unit root against an alternative of asymmetric exponential smooth transition autoregressive models, by extending the infimum test developed by Park and Shintani. Simulation results suggest that the test performs reasonably well in finite samples. The proposed test is also applied to real exchange rates to examine their asymmetric and nonlinear mean-reverting properties. JEL Classification Numbers: C12, C22, F31.

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Detecting Mean Reversion in Real Exchange Rates from a Multiple Regime STAR Model

Cited by 11 publications

References 0 publications

Modeling the Phillips Curve in China: A Nonlinear Perspective

Modeling the Phillips Curve in China: A Nonlinear Perspective

Unit root tests

THE INF-TTEST FOR A UNIT ROOT AGAINST ASYMMETRIC EXPONENTIAL SMOOTH TRANSITION AUTOREGRESSIVE MODELS

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