期刊文献+

基于TEI@I方法论的通货膨胀问题分析与预测 被引量:13

Inflation forecasting method based on TEI@I methodology
原文传递
导出
摘要 基于TEI@I方法论提出了通货膨胀预测的研究框架.首先对通货膨胀的相关影响因素进行了分析,然后建立了因子预测模型、ARIMA模型、向量自回归模型以及马尔可夫状态转移模型,并分别进行了预测.然后采用Boostrap方法进行了集成,得到了每种预测方法的权重,并利用载止2007年12月的数据对2008年的月度通货膨胀率进行了集成预测,实证结果表明新的集成方法使预测结果更为稳定. Based on TEI@I methodology, this paper proposes a inflation forecasting method. Firstly, we analyze the factors that attribute to China's inflation, then set up factor forecasting model, ARIMA model, VAR model, Markov Regime Switching model to forecast China's inflation rate respectively. Bootstrap methodology is used to integrate these models, and we also forecast the monthly inflation rate for 2008. Forecasting results show that the integrated result can make the forecast more stable and credible.
出处 《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2010年第12期2157-2164,共8页 Systems Engineering-Theory & Practice
基金 国家自然科学基金委员会创新研究群体科学基金(70221001)
关键词 TEI@I方法论 通货膨胀 BOOTSTRAP 预测 TEI@I methodology inflation Bootstrap forecasting
  • 相关文献

参考文献6

二级参考文献83

  • 1徐剑刚,唐国兴.我国股票市场报酬与波动的GARCH-M模型[J].数量经济技术经济研究,1995,12(12):28-32. 被引量:32
  • 2Brouwer, D. G. and Ericsson, N. R. , 1995. Modelling Inflation in Australia , International Finance Discussion Paper No. 530, Board of Governors of the Federal Reserve System, Washington, D.C..November.
  • 3Evans, M. and Wachtel, P. , 1993. Inflation Regimes and the Sources of Inflation Uncertainty,Journal of Money, Credit and Banking, 25 (3), 475~511.
  • 4Friedman, B. M. and Kutter, K. N., 1992. Money, income, prices, and interest rates, American Economic Reviews 82, 6, 472-492.
  • 5Hamilton, J. D. , 1989. A new approach to the economic analysis of nonstationary time series andthe business cycle, Econometrica, 57 (2), 357-384.
  • 6Kim, C - J, 1993. Unobserved - component time series models with Markov - switching heteroscedasticity : Changes in regime and the link between inflation rates and inflation uncertainty, Journal of Business and Economic Statistics, 11, 341-349.
  • 7Ricketts, N. and Rose, D. , 1995. Inflation, Learning and Monetary Policy Regimes in the G - 7 Economies, Bank of Canada Working Paper No. 95/6.
  • 8G.P.Zhang, E. B. Patuwo, M. Y. Hu, A simulation study of artificial neural networks for nonlinear time-series forecasting, Computers and Operations Research, 2001, 28: 381-396.
  • 9A. S. Chen, M. T. Leung, Regression neural network for error correction in foreign exchange rate forecasting and trading, Computers and Operations Research, 2004, 31(7): 1049-1068.
  • 10J. W. Denton, How good axe neural networks for causal forecasting?, Journal of Business Forecasting, 1995, 14: 17-20.

共引文献235

同被引文献213

引证文献13

二级引证文献79

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部