Statistical Inference on Long-Memory Time Series and its Applications to Economic Data
| Project/Area Number |
23730209
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Economic statistics
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| Research Institution | Okayama University (2012-2013)
Tohoku University (2011) |
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Principal Investigator |
NARUKAWA Masaki 岡山大学, 社会文化科学研究科, 准教授 (30588489)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2013: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2012: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 長期記憶 / セミパラメトリック推定 / 周期性 / 確率的ボラティリティ / 実数差分過程 / 多変量時系列 / 非定常過程 / 季節変動 / パネルデータ / Broadband / 季節変動時系列 |
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| Research Abstract |
In this research, we proposed semiparametric statistical inference on various long-memory time series, such as long-memory signal plus noise processes and cyclical long-memory time series. By applying the proposed method to a long-memory stochastic volatility model, we examined long-memory in the volatility of exchange rates. We also provided an empirical analysis of the growth rate of Japan's industrial production index and detected its cyclical persistence.
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Report
(4 results)
Research Products
(15 results)
