Reliability of Structural Shocks Estimates from a Bivariate SVAR Model - The Case of Southeast Asian Countries
AbstractIn order to assess the symmetry in the nature of structural shocks for a bloc of countries to form a currency union, long-run identifying restrictions to simple bivariate models are often used. This study attempts to assess the reliability of the estimated structural shocks produced from applications of these kinds of models by looking at their consistency in representing the designated shocks. The case examined covers some countries in the Southeast Asian bloc. The finding suggests that the commingling shocks problems exist. Exercise using larger models and higher frequency data is then advisable.
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Bibliographic InfoPaper provided by East Asian Bureau of Economic Research in its series Macroeconomics Working Papers with number 22305.
Date of creation: Jan 2006
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Structural Shocks Estimates; Bivariate SVAR Model; South East Asia;
Other versions of this item:
- Arief Ramayandi, 2006. "Reliability of Structural Shocks Estimates from a Bivariate SVAR Model: The Case of Southeast Asian Countries," Asia Pacific Economic Papers 357, Australia-Japan Research Centre, Crawford School of Public Policy, The Australian National University.
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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- Arief Ramayandi, 2008. "Simple Model for a Small Open Economy: An Application to the ASEAN-5 Countries," Working Papers in Economics and Development Studies (WoPEDS) 200801, Department of Economics, Padjadjaran University, revised May 2008.
- Omotor, Douglason G. & Niringiye, Aggrey, 2011. "Optimum Currency Area and Shock Asymmetry: A Dynamic Analysis of the West African Monetary Zone (WAMZ)," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 71-82, September.
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