近年來，國內壽險市場成長快速，因此正確的找出預測變數與預測模式來進行對壽險需求的估計十分重要。本研究檢測台灣有關經濟發展與壽險產業成長間的關係，藉由自我迴歸整合移動平均模式(ARIMA Model)與自我迴歸整合移動平均轉移函數模式(ARIMA Transfer Function Model)，對台灣地區1964年至2000年間，有關實質國民所得與實質壽險保費收入之年資料進行分析。研究發現經濟發展之預測能力非常顯著，且自我迴歸整合移動平均轉移模式之預測誤差較ARIMA模式小，因此在加入外生變數進行預測之考量下，經濟成長被證實為重要的同期預測變數。由其較小之AIC和SBC值，以及近乎1之調整後決定係數，可證實其為一簡約且具有良好預測能力之模式。

Since the life insurance market in Taiwan grows rapidly in recent years, it's very important to find the proper predicting variables and construct well-fitted forecast model. This article examines the relationship between economic development and the life insurance industry growth in Taiwan, which is achieved by analyzing the ARIMA Model and the ARIMA Transfer Function Model on annual data for real GDP and real life insurance premium from 1964 to 2000. When incorporated as an exogenous variable in the ARIMA Transfer Function Model, the economic development was tested significant, and the model has better goodness of fit compared to the univariate ARIMA model. In the situation where the inclusion of the exogenous variables in the forecast model is considered, the economic development is proved to be an important variable to predict the demand. With smaller AIC and SBC as well as adjusted R^2 value close to 1, the ARIMA Transfer Function Model is shown to be parsimonious with good prediction power.