Output gap and inflation nexus: the case of United Arab Emirates
AbstractOutput gap is generally used in assessing both the inflationary pressures and the cyclical position of a nation's economy. However, this variable is not observable and must be estimated. In this article, we accomplish two tasks. First, we estimate the output gap for the United Arab Emirates (UAE) using four different statistical methods. Second, we evaluate to what extent do the fluctuations of output gap, however measured, are a good predictors of inflation in the UAE. This is carried out by comparing the out-of-sample forecasts generated by the output gap-based models to those of the model with alternative indicators and the benchmark models. Interestingly, although the different measures of output gap produce a broadly similar profile of the UAE business cycles, we could not find any statistical evidence that this variable is a useful predictor of inflation in the UAE.
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Bibliographic InfoArticle provided by Inderscience Enterprises Ltd in its journal Int. J. of Economics and Business Research.
Volume (Year): 1 (2009)
Issue (Month): 1 ()
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forecasting; forecast accuracy; forecast encompassing; inflation; output gap; United Arab Emirates; UAE.;
Other versions of this item:
- Osman, Mohammad & Jean Louis, Rosmy & Balli, Faruk, 2008. "Output gap and inflation nexus: the case of United Arab Emirates," MPRA Paper 34006, University Library of Munich, Germany, revised 2009.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
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