Arbeitspapier
An adaptive approach to forecasting three key macroeconomic variables for transitional China
We propose the use of a local autoregressive (LAR) model for adaptive estimation and forecasting of three of China's key macroeconomic variables: GDP growth, inflation and the 7-day interbank lending rate. The approach takes into account possible structural changes in the data-generating process to select a local homogeneous interval for model estimation, and is particularly well-suited to a transition economy experiencing ongoing shifts in policy and structural adjustment. Our results indicate that the proposed method outperforms alternative models and forecast methods, especially for forecast horizons of 3 to 12 months. Our 1-quarter ahead adaptive forecasts even match the performance of the well-known CMRC Langrun survey forecast. The selected homogeneous intervals indicate gradual changes in growth of industrial production driven by constant evolution of the real economy in China, as well as abrupt changes in interestrate and inflation dynamics that capture monetary policy shifts.
- Sprache
-
Englisch
- Erschienen in
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Series: SFB 649 Discussion Paper ; No. 2015-023
- Klassifikation
-
Wirtschaft
Interest Rates: Determination, Term Structure, and Effects
Money and Interest Rates: Forecasting and Simulation: Models and Applications
- Thema
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Chinese economy
local parametric models
forecasting
- Ereignis
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Geistige Schöpfung
- (wer)
-
Niu, Linlin
Xu, Xiu
Chen, Ying
- Ereignis
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Veröffentlichung
- (wer)
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Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
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Berlin
- (wann)
-
2015
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Niu, Linlin
- Xu, Xiu
- Chen, Ying
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2015