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150128 ||| eng |
| 020 |
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|a 9781451850444
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| 100 |
1 |
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|a Sekine, Toshitaka
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| 245 |
0 |
0 |
|a Modeling and Forecasting Inflation in Japan
|c Toshitaka Sekine
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| 260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2001
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| 300 |
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|a 35 pages
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| 651 |
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4 |
|a Japan
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| 653 |
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|a Inflation
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| 653 |
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|a Energy: Demand and Supply
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| 653 |
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|a Oil prices
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| 653 |
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|a Dynamic Treatment Effect Models
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| 653 |
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|a Output gap
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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 Purchasing power parity
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| 653 |
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|a Production
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| 653 |
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|a Currency
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| 653 |
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|a Diffusion Processes
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| 653 |
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|a Economic forecasting
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| 653 |
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|a Vector autoregression
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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 Time-Series Models
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| 653 |
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|a Model Construction and Estimation
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| 653 |
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|a Forecasting
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| 653 |
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|a Macroeconomics: Production
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| 653 |
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|a Price Level
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| 653 |
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|a Foreign Exchange
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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 Prices
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| 653 |
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|a Macroeconomics
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| 653 |
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|a Dynamic Quantile Regressions
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| 653 |
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|a Econometrics
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| 653 |
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|a Economic theory
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| 653 |
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|a Econometrics & economic statistics
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| 653 |
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|a Foreign exchange
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| 653 |
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|a Production and Operations Management
|
| 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 10.5089/9781451850444.001
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| 856 |
4 |
0 |
|u https://elibrary.imf.org/view/journals/001/2001/082/001.2001.issue-082-en.xml?cid=15123-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 This paper estimates an inflation function and forecasts one-year ahead inflation for Japan. It finds that (i) markup relationships, excess money and the output gap are particularly relevant long-run determinants for an equilibrium correction model (EqCM) of inflation; (ii) with intercept corrections, one-year ahead inflation forecast performance of the EqCM is good; and (iii) forecast accuracy can be improved by combining forecasts of the EqCM with those made by rival models. The EqCM obtained would serve for structural model-based inflation forecasting. It also highlights the importance of adjustment to a pure model-based forecast by utilizing information of alternative models. The methodology employed is applicable to a wider range of countries including some emerging market economies
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