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150128 ||| eng |
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|a 9781451875546
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| 100 |
1 |
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|a Leigh, Daniel
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| 245 |
0 |
0 |
|a Leading Indicators of Growth and Inflation in Turkey
|c Daniel Leigh, Marco Rossi
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| 260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2002
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| 300 |
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|a 26 pages
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| 651 |
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4 |
|a Turkey
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| 653 |
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|a Business cycles
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| 653 |
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|a Price indexes
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| 653 |
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|a Inflation
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| 653 |
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|a Economywide Country Studies: Europe
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| 653 |
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|a Cyclical indicators
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| 653 |
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|a Economic Forecasting
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| 653 |
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|a Deflation
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| 653 |
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|a Consumer price indexes
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| 653 |
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|a Economic forecasting
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| 653 |
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|a Prices, Business Fluctuations, and Cycles: Forecasting and Simulation
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| 653 |
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|a Economic Growth of Open Economies
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| 653 |
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|a Forecasting
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| 653 |
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|a Asset prices
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| 653 |
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|a Price Level
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| 653 |
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|a Cycles
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| 653 |
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|a Forecasting and Other Model Applications
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| 653 |
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|a Economic growth
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| 653 |
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|a Prices
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| 653 |
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|a Macroeconomics
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| 653 |
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|a Business Fluctuations
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| 653 |
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|a Central Banks and Their Policies
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| 653 |
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|a Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data)
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| 700 |
1 |
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|a Rossi, Marco
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b IMF
|a International Monetary Fund
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| 490 |
0 |
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|a IMF Working Papers
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| 028 |
5 |
0 |
|a 10.5089/9781451875546.001
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| 856 |
4 |
0 |
|u https://elibrary.imf.org/view/journals/001/2002/231/001.2002.issue-231-en.xml?cid=16221-com-dsp-marc
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 330
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| 520 |
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|a Growth and inflation in Turkey have been volatile over the last two decades. It would, therefore, be useful to identify indicators that anticipate economic conditions and inflation. This paper investigates the predictive performance of economic indicators for inflation and real output growth in Turkey. We find that (i) the forecasting ability of individual indicators is unstable; but that (ii) a suitable combination of these unstable forecasts yields a forecast that reliably outperforms that generated by an autoregressive model. We then propose a two-stage combination forecast obtained by taking the median of the top five performing individual forecasts. This two-stage forecast reliably improves on autoregressive benchmarks and outperforms the combination forecast based on all the individual forecasts
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