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

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).