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The Assessment Of Parameter Uncertainty In A Vector Error Correction Model For Romania

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  • Mihaela SIMIONESCU

    ()
    (Bucharest University of Economics)

Abstract

The assessment of uncertainty that characterizes the econometric model parameters is an important input for policymakers that have to establish more alternative policies to protect against persistent shocks of the economy. The objective of this useful research for policymakers is to evaluate the parameter uncertainty in the behavioural equations of a vector error correction model for Romania. A positive impact of the foreign direct investment and exports on GDP real rate was measured on the horizon Q1:2000-Q4:2012. A permanent shock was observed in parameters. The error correction vector explains quarterly around 10.6% of the desequilibrium. The necessary period for reducing the gap between the value of GDP in the last quarter of 2012 and that in the steady-state is 14 quarters, till the second quarter of 2016.

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Bibliographic Info

Article provided by Institute of National Economy in its journal Romanian Journal of Economics.

Volume (Year): 37 (2013(XXIII))
Issue (Month): 2(46) (December)
Pages: 124-134

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Handle: RePEc:ine:journl:v:2:y:2013:i:44:p:124-134

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Related research

Keywords: parameters uncertainty; vector error correction model; behavioural equations; steady-state; GDP rate; foreign direct investments; exports;

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  1. Debby Lanser & Henk Kranendonk, 2008. "Investigating uncertainty in macroeconomic forecasts by stochastic simulation," CPB Discussion Paper 112, CPB Netherlands Bureau for Economic Policy Analysis.
  2. Athanasios Orphanides & John C. Williams, 2003. "Inflation scares and forecast-based monetary policy," Working Paper Series 2003-11, Federal Reserve Bank of San Francisco.
  3. Glenn D. Rudebusch, 2001. "Is The Fed Too Timid? Monetary Policy In An Uncertain World," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 203-217, May.
  4. Söderström, Ulf, 1999. "Monetary policy with uncertain parameters," Working Paper Series 83, Sveriges Riksbank (Central Bank of Sweden).
  5. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
  6. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
  7. Ray Fair, 2001. "Optimal Control and Stochastic Simulation of Large Nonlinear Models with Rational Expectations," Yale School of Management Working Papers ysm202, Yale School of Management, revised 24 Sep 2001.
  8. Matteo Ciccarelli & Kirstin Hubrich, 2010. "Forecast uncertainty: sources, measurement and evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 509-513.
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