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Investigating Non-Linearities in the Relationship Between Real Exchange Rate Volatility and Agricultural Trade Author info | Abstract | Publisher info | Download info | Related research | Statistics Jean-Philippe Gervais (CRÉA, Laval University)
Bruno Larue (CRÉA, Laval University)
Olivier Bonroy (CRÉA, Laval University)
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The article analyzes production and marketing lags in agri-food supply chains that force competitive producers and processors to commit to output targets before prices and exchange rates are realized. We show that export markets act as put options for exporters and an increase in the volatility of the real exchange rate will generally increase exports. Relaxing the assumptions about the real exchange rate distribution and risk preferences of producers and/or processors can introduce non-linearities in the relationship between exports and real exchange rate volatility. This relationship is investigated using the flexible non-linear inference framework of Hamilton (2001). Bilateral export equations for Canadian pork exports to the U.S. and Japan are specified. The empirical model shows that real exchange rate volatility has statistically significant non-linear effects on aggregate pork exports. Moreover, bilateral pork exports are less sensitive to country- specific variables than aggregate volatility in the real exchange rate.
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Paper provided by EconWPA in its series International Trade with number
0407004.
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Length: 34 pages
Date of creation: 13 Jul 2004Date of revision:
Handle: RePEc:wpa:wuwpit:0407004Note: Type of Document - pdf; pages: 34Contact details of provider: Web page: http://129.3.20.41
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Keywords: Real exchange rate volatility ; non-linear flexible inference ; production lags ; pork exports ; Other versions of this item:
Find related papers by JEL classification: F31 - International Economics - - International Finance - - - Foreign Exchange Q17 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agriculture in International Trade C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
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