人壽保險業在台灣的金融環境一直扮演著重要的角色，國內外文獻對於影響保險需求的因素亦有諸多探討，包含人口統計變數及經濟財務變數等，但受限於資料取得，對於個體變數的討論較少。本研究使用國內人壽保險公司去識別化之承保資料，建立保險需求之橫斷面資料多重線性迴歸模型。以人壽保險之總保額除以費率，即單位保額，作為模型之被解釋變數。解釋變數方面，個體面使用：性別、年齡、職業風險等級、繳別、客戶等級等變數。總體面使用：經濟成長率、通貨膨脹率、利率、房價指數、壽險業資本額與國人平均餘命等變數。實證結果發現：年齡、職業風險等級、繳別、客戶等級、利率、房價指數等因素會影響消費者購買人壽保險，進一步分析，45~70歲、職業風險等級越低、客戶等級為VIP及準VIP的消費者，在利率越低、房市越壞的情況下，不論選擇何種繳別，都會增加對人壽保險的需求。本研究結果，除了學術上對壽險需求的決定因素更為瞭解，尋找顯著的壽險需求解釋變數，實務面也可以尋找保險缺口，來提升保險公司行銷能力與銷售策略。

Life Insurance companies play a very important role in our financial industry; many domestic and foreign studies have discussed factors that influence demand for life insurance, including demographic and macroeconomic variables. However, there’s little discussion about the micro variables due to limited resources. This study applies de-identification life insurance data to build a cross-sectional regression model on the demand for life insurance. We use total life coverage divided by premium rate, as the explained variables for the model. The explanatory variables including both micro and macro variables, such as gender, age, occupational risk level, payment kind, client level, GDP growth rate, interest rate, inflation rate, house price index, total capital for life insurers and life expectancy. The result shows in lower interest rate, higher house price economic conditions, consumers from 45to 70 years old, with lower occupational risk level, higher client level are more likely to purchase more life insurance. This study not only helps us understand the determinants of demand for insurance, but improve efficiency for insurance companies on developing their marketing strategy.

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