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南京医科大学学报(社会科学版)京医科大学学报(社会科学版)
             第5期 总第106期                           南
               2021年10月                     Journal of Nanjing Medical University(Social Sciences)of Nanjing Medical University(Social Sciences)  · 423  ·
                                            Journal



                 Forecast analysis of Shanghai’s total health expenditure based on

                                        ARIMA and GM(1,1)models

                                                  DING Haifeng,LI Liqing
                         School of Public Administration and Law,Hunan Agricultural University,Changsha 410128,China
                 Abstract:Total health expenditure is an important index to evaluate the health investment level and fund
             utilization status of a country or region. Based on the data of Shanghai Statistical Yearbook from 2005 to 2018,
             ARIMA model and grey GM(1,1) model were used to forecast and analyze the development trend of total
             health expenditure and its proportion in GDP in Shanghai. The study found that the total health expenditure and
             its proportion in GDP of Shanghai would continue to grow steadily from 2018 to 2025. The forecast results
             showed that the total health expenditure and its proportion in GDP of Shanghai would reach 476.519 billion
             yuan,597.659 billion yuan,8.53% and 10.21% respectively in 2025. The average relative errors of the
             established ARIMA model and the grey GM(1,1)model were both less than 10%,and the fitting degree was
             good and the prediction accuracy was high,but the grey GM(1,1)model was better than the ARIMA model.
             The paper puts forward that Shanghai should control the reasonable increase of the total health expenditure on
             the basis of keeping the investment,maintain proper matching between health expenditure and the level of
             economic development,improve health efficiency,and provide people with higher quality,more inclusive and
             more efficient health services.
                 Key words:total health expenditure;ARIMA model;grey GM(1,1)model;Shanghai
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