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外商直接投资趋势研究——基于灰色马尔可夫预测模型与时间序列模型的对比
引用本文:郑岩岩,舒彤,陈收,黎建强.外商直接投资趋势研究——基于灰色马尔可夫预测模型与时间序列模型的对比[J].系统工程理论与实践,2016,36(4):897-909.
作者姓名:郑岩岩  舒彤  陈收  黎建强
作者单位:1. 湖南大学工商管理学院, 长沙 410082;2. 华北电力大学经济与管理学院, 北京 102206;3. 香港城市大学管理科学系, 香港
基金项目:国家自然科学基金(71172194,71221001,71390330,71390331)
摘    要:外商直接投资是影响中国经济发展的重要因素,而未来外商直接投资的预测是其发展和决策的基础.文章在阐述外商直接投资对中国经济发展的作用以及对未来中国利用外资水平预测的必要性的基础上,选取2000-2013年度中国利用外商直接投资(FDI)的数据,通过建立灰色马尔可夫(GMM)和时间序列模型,对中国利用FDI的趋势进行预测,并对预测结果精度进行比较,以得出较优的预测模型.研究结果表明:传统灰色模型合格,但仍有可提升的空间;在此基础上,建立GMM预测模型对结果进行修正,所得模型的灰色关联度有很大提升,且与真实值差距进一步缩小;建立时间序列模型,并据此对数据进行预测;比较GMM与时间序列模型预测结果的精度,可知,GMM的预测精度较高,拟合效果较好.为验证这一结果的可信度,文章选取1990-2013年度北京市和重庆市FDI水平的数据,建立GMM和时间序列预测模型,再次发现GMM预测效果优于时间序列模型的预测效果.基于此,GMM对中国利用外资水平的预测结果较为可信,预测结果对完善中国直接利用外商投资的机制具有一定参考价值.

关 键 词:外商直接投资  灰色马尔可夫模型  时间序列模型  
收稿时间:2014-10-29

A study on the forecasting trend of foreign direct investment chain system-Based on the comparison between grey Markov forecasting model and time series forecasting model
ZHENG Yanyan,SHU Tong,CHEN Shou,LAI Kinkeung.A study on the forecasting trend of foreign direct investment chain system-Based on the comparison between grey Markov forecasting model and time series forecasting model[J].Systems Engineering —Theory & Practice,2016,36(4):897-909.
Authors:ZHENG Yanyan  SHU Tong  CHEN Shou  LAI Kinkeung
Institution:1. Business School, Hunan University, Changsha 410082, China;2. School of Economics and Management, North China Electric Power University, Beijing 102206, China;3. Department of Management Sciences, City University of Hong Kong, Hong Kong, China
Abstract:Foreign direct investment (FDI) is one of the important factors that affect China's economic development. Therefore, the prediction of which is the basic of its development and decision-making. Based on elaborating the significant role in the growth of China's economy and the current situation of utilizing foreign investment, with the data of 2000-2013, the article attempts to build grey-Markov model (GMM) and time series model to forecast the trend of China's utilization of foreign direct investment (FDI), and then compares the two different precision to get a better predicting model. The research results suggest that: traditional grey model needs to be optimized, although it is qualified; based on the grey model, to build a Markov forecasting model can help correct the result, improve grey relational degree and narrow the gap with real value; to build a first-order autoregressive time series model (AR(1)) forecasts the data; by comparing the accuracy of grey-Markov model (GMM) and that of time series model, the prediction accuracy of grey-Markov model (GMM) is higher, and its fitting effect is better. In order to further strengthen the credibility of the results, the paper selects the data of Beijing and Chongqing from 1990 to 2013, establishes the grey-Markov model (GMM) and time series prediction model and finds that the fitting effect of grey-Markov model (GMM) is superior to the time series prediction model. In short, for the prediction result of Chinese foreign capital utilization level, grey-Markov model (GMM) is more credible, which has a certain reference value to improve the system mechanism for the utilization of foreign direct investment (FDI).
Keywords:foreign direct investment (FDI)  grey-Markov model (GMM)  time series model
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