摘要
目的探讨中国卫生总费用的预测方法,寻找数据之间的规律,更加科学的预测卫生费用值。方法利用协整回归的方法,建立GDP(Gross Domestic Product)与卫生总费用之间的协整回归关系,并进行短期预测。结果经协整回归预测可知,2013年、2014年中国卫生总费用分别为6002.4、7012.0亿元,卫生总费用继续保持快速增长的趋势,但2014年增长速度有所减缓。结论利用协整回归模型,预测1980-2012年中国卫生总费用,与其他学者预测值相比,误差较小,说明模型比较适合;预测2013年、2014年卫生总费用占GDP的比例分别为6.4%、6.9%,此数值预测误差较小。同时,长期预测精度则取决于GDP数据的可靠性,预测误差会因GDP数据准确性的下降而增大,此外,预测结果还会因政府卫生政策调整、个人支付卫生费用比例等因素缺乏预期性而导致其更加偏离真实值。因此,协整回归模型不太适合长期预测。
Objective To study the method of predicting total health expenditure in China and find laws between the data so as to scientifically forecast the health cost value. Methods The co-integration regression relationship between GDP and total health expenditure was built by using the method of co-integration regression, which could also be used for short-term predictions. Results By the co-integration regression predic- tion,China total health expenses were 600. 24 billion yuan and 701.2 billion yuan in 2013 and 2014. Total health costs continue to maintain rapid growth trend. But the growth rate had slowed down in 2014. Conclusions Using co-integration regression model to estimate the total health expenses in China from 1980 to 2012 ,the error is smaller. The total health expenditure proportion of GDP is predicted to be 6. 4% and 6.9% in 2013 and 2014, which is close to the real value. The prediction accuracy is higher. The long-term prediction accuracy depends on the credibility of GDP data. The prediction error will increase due to the decline in GDP data accuracy. The prediction results will deviate more from the true value because of the unpredictable factors such as Government health policy adjustment and the changes in the individual health fee ratio. Therefore, co-integration regression model is not suitable for long-term forecast.
出处
《沈阳药科大学学报》
CAS
CSCD
北大核心
2015年第3期240-244,共5页
Journal of Shenyang Pharmaceutical University
基金
沈阳市科技协会国家思想库项目(Sxk-201402A)
关键词
国内生产总值
卫生总费用
协整回归
GDP
The total health expenses
cointegration regression
