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The bilateral J-Curve hypothesis between Turkey and her 9 trading partners Author info | Abstract | Publisher info | Download info | Related research | Statistics Kimbugwe, Hassan
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Applying ARDL Cointegration, Johansen modelling and generalised impulse response function analyses in this paper, we provide new evidence for the Turkish Bilateral J-curve hypothesis in the short and long-run using both annual aggregated and disaggregated data over 1960 and 2000 period between Turkey and 9 of her major trading partners. We adopt a model that models the real trade balance directly as a function of real exchange rate and real domestic and foreign incomes to test for existence of any cointegration relationship and J-curve pattern. We apply the impulse response function analysis to determine whether shocks to real exchange rate induce the trade balance to follow the J-curve pattern. The results indicate that there is cointegration relationship between the above variables. We were unable to find any support for Turkish bilateral J-Curve hypothesis. However the generalised impulse response functions reveal that in some cases depreciation of the Turkish lira seems to improve the trade balance beyond the equilibrium level in the long-run.
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number
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Date of creation: 12 May 2006Date of revision:
Handle: RePEc:pra:mprapa:4254Contact details of provider: Postal: Schackstr. 4, D-80539 Munich, Germany Phone: +49-(0)89-2180-2219 Fax: +49-(0)89-2180-3900 Web page: http://mpra.ub.uni-muenchen.de More information through EDIRC
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Keywords: J-curve hypothesis ; balance of trade ; generalised impulse response function ; Error Correction Model VAR model ; Find related papers by JEL classification: C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General F18 - International Economics - - Trade - - - Trade and Environment C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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