Nonlinear adjustment to purchasing power parity in the post-Bretton Woods era

Baum, Christopher F.; Barkoulas, John; Çağlayan, Mustafa

doi:10.1016/s0261-5606(00)00043-7

Cited by 189 publications

(137 citation statements)

References 46 publications

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“…6 When the test is applied to a linear but nonstationary or highly persistent DGP, the null hypothesis of linearity is rejected too often. Sandberg (2008), for example, …nds that the null is rejected 31 percent of the time for a test with 5 percent level of signi…cance.…”

Section: Results Of Nonlinearity Testsmentioning

confidence: 99%

Causes of nonlinearities in low-order models of the real exchange rate

Ahmad

Mykhaylova

2013

Journal of International Economics

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This paper investigates the extent to which modern DSGE models, which feature local currency pricing, home bias, nontraded goods and incomplete markets, can generate nonlinear real exchange rate dynamics that are consistent with those found in the time series literature using data from the current ‡oating period. Our key …ndings are as follows. First, if the solution to the DSGE model is approximated to the …rst order, then linearity tests that utilize univariate autoregressions of the real exchange rate su¤er from an omitted variables problem, which leads them to overestimate the true incidence of nonlinearity. Consequently, studies that fail to control for this problem may spuriously …nd evidence of nonlinearities in the data, despite the fact that the data generating process may be linear. Second, we propose a strategy that can largely eliminate this distortion. Finally, we …nd that DSGE models solved using higher order approximations are capable of generating true structural nonlinearities in real exchange rates both asymptotically and in short samples.JEL Classi…cation: C15 C32 F41 F47

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Section: Results Of Nonlinearity Testsmentioning

confidence: 99%

Causes of nonlinearities in low-order models of the real exchange rate

Ahmad

Mykhaylova

2013

Journal of International Economics

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“…Since then, the model has been applied to study nonlinearity in business cycle (Teräsvirta and Anderson, 1992); Skalin and Teräsvirta 1996; and real exchange rates (Baum et al, 1998;Liew et al, 2002). The connection between business cycle-regimes and nonlinearity in the UK labour market is studied in Acemoglu and Scotts (1994).…”

Section: The Mean Equation: Star Modelmentioning

confidence: 99%

Specifying Asymmetric STAR models with Linear and Nonlinear GARCH Innovations: Monte Carlo Approach

Yaya

Shittu

2014

J. Mod. App. Stat. Meth.

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Economic and finance time series are typically asymmetric and are expected to be modeled using asymmetrical nonlinear time series models. Smooth Transition Autoregressive (STAR) models: Logistic (LSTAR) and Exponential (ESTAR) are known to be asymmetric and symmetric respectively. Under non-normal and heteroscedastic innovations, the residuals of these models are estimated using Generalized Autoregressive Conditionally Heteroscedastic (GARCH) models with variants which include linear and nonlinear forms. The small sample properties of STAR-GARCH variants are yet to be established but these properties are investigated using Monte Carlo (MC) simulation. An MC investigation was conducted to investigate the performance of selections of STAR-GARCH models by classical nonlinear selection approaches. The ARCH(1) and GARCH(1,1) models were the linear GARCH specifications while the Logistic Smooth Transition-ARCH (LST-ARCH(1,1)), Logistic Smooth Transition-GARCH (LST-GARCH(1,1)) and Asymmetric Nonlinear Smooth Transition-GARCH (ANST-GARCH(1,1)) models were the nonlinear GARCH specifications. The nonlinearity parameter in the variance equations and Autoregressive (AR) parameters were varied along with different sample sizes. With the assumption of normality, the results showed that the selection of LSTAR models were actually affected by the structure of the innovations and this improved as sample size increased. Misspecification tests showed that these models cannot be misrepresented in the real sense.

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“…En partant des travaux de Dumas (1992) et Sercu, Uppal et van Hulle (1995) qui testent l'hypothèse de la parité des pouvoirs d'achat (PPA) à long terme, de nombreuses études récentes (Michael, Nobay et Peel (1997), Sarrantis (1999), Taylor et Peel (2000), Taylor, Peel et Sarno (2001), Baum, Barkoulas et Caglayan (2001), O'Connell et Wei (2002) et Kilian et Taylor (2001)) montrent la supériorité de cette représentation sur les modèles LSTAR. Pour représenter la non linéarité caractérisant les taux de change, il est préférable de spécifier la fonction de transition en fonction de la taille de la déviation par rapport à l'équilibre (modèle ESTAR) plutôt qu'en fonction du signe de cette même déviation (cas LSTAR).…”

Section: La Théorie Du Modèle Stecmunclassified

Structure non-linéaire du taux de change et une proposition de modélisation

Usupbeyli¹

2012

Ankara Üniversitesi SBF Dergisi

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ResuméLe marché de change est composé par de différents types d'agents et les anticipations sont un processus mixte qui varie en fonction de ces différents types des agents. L'interaction entre ces différentes catégories d'opérateurs peut impliquer une alternance de périodes de hausse et de baisse ainsi qu'un délai dans l'ajustement à la valeur d'équilibre. En plus, la présence des coûts de transactions dans le marché de change entraîne des déséquilibres restant non corrigés. Ces facteurs ont des implications importantes sur le processus d'ajustement du taux de change vers sa valeur d'équilibre et y injectent un caractère non linéaire en provoquant de l'incertitude sur les marchés des changes. Dans ce cas, il est difficile d'analyser la dynamique des taux de change en présence de frictions dans le marché des changes en retenant le cadre empirique des modèles linéaires standards. Par contre, le modèle STECM nous fournit une méthodologie qui permet d'étudier la non linéarité d'ajustement du taux de change vers sa valeur d'équilibre.Mots clés: Marché de change, coût de transaction, taux d'équilibre, dynamique d'ajustement, STECM Döviz Kurunun Doğrusal Olmayan Yapısı ve Bir Modelleme Önerisi ÖzetDöviz piyasası farklı davranışa sahip ekonomik oyunculardan oluşur ve beklentiler bu oyuncuların davranışlarına bağlı olarak değişiklik gösteren bir ortak süreçtir. Farklı yapıdaki bu oyuncuların etkileşimi kurun denge değerine intibak sürecinde aşağı veya yukarı yönlü dalgalanmalara ve gecikmelere yol açar. Ayrıca, döviz piyasasındaki işlem maliyetlerinin varlığı da düzeltilmemiş kalıcı dengesizliklere neden olmaktadır. Bu faktörler, döviz kurunun denge değerine intibak sürecini önemli düzeyde etkiler ve döviz piyasasında belirsizliğe yol açan doğrusal olmayan bir durum yaratır. Bu durumda, piyasadaki pürüzlerin varlığı döviz kuru dinamiğini standart doğrusal modellerle analiz etmemizi güçleştirir. Ancak, STECM modeli, bize döviz kurunun denge değerine intibakını inceleyebileceğimiz doğrusal olmayan bir yöntem sağlamaktadır.. Anahtar Sözcükler: Döviz kuru piyasası, işlem maliyetleri, denge oranı, intibak dinamiği, STECM

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Nonlinear adjustment to purchasing power parity in the post-Bretton Woods era

Cited by 189 publications

References 46 publications

Causes of nonlinearities in low-order models of the real exchange rate

Causes of nonlinearities in low-order models of the real exchange rate

Specifying Asymmetric STAR models with Linear and Nonlinear GARCH Innovations: Monte Carlo Approach

Structure non-linéaire du taux de change et une proposition de modélisation

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