Adaptive learning with a unit root: An application to the current account
AbstractThis paper develops a simple two-country, two-good model of international trade and borrowing that suppresses all previous sources of current account dynamics. Under rational expectations, international debt follows a random walk. Under adaptive learning, however, the model's unit root is eliminated and international debt is either a stationary or an explosive process, depending on agents' specific learning algorithm. Some stationary learning algorithms result in debt following an AR(1) process with an autoregressive coefficient less than 0.8. Because unit roots are a common and problematic feature of many international business cycle models, our results offer a new approach for generating stationarity.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 34 (2010)
Issue (Month): 2 (February)
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Web page: http://www.elsevier.com/locate/jedc
Current account International debt movements Expectations Adaptive learning;
Other versions of this item:
- Ronald B. Davies & Paul Shea, 2003. "Adaptive Learning with a Unit Root: An Application to the Current Account," University of Oregon Economics Department Working Papers 2006-15, University of Oregon Economics Department, revised 10 Jun 2003.
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
- F11 - International Economics - - Trade - - - Neoclassical Models of Trade
- F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements
- F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
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