老齡化率變動如何影響股市風險溢酬—以中國、香港、日本、韓國、新加坡、臺灣及泰國為例

Abstract

往昔的國內海外相關文獻中，針對風險偏好議題，囊括人口結構、收入狀況、資產配置，以及最終財富等，進行眾多的研究和探討。而其中聚焦年齡傾向的風險偏好，多數的實證結果分析得出，雖然早年成長會降低風險趨避，勇於接受風險；然而，一旦年齡達到65歲以上之際，則個人風險趨避將隨年歲增長，越顯抗拒且厭惡。如此論述符合現實邏輯，當年輕之時，預期的收入狀況和資金積累，皆能給予較多時間，忍受個人風險損失與錯誤標的投資，並隨著經驗學習和市場脈動，成就最終財富。然而，進入65歲退休階段，面對收入為零，穩定性資產成為核心生存資源，其大幅增加的重視，來自於心理層面上的保障與掌握，如此訴求將改變個人資產配置，從風險投資轉移至固定收益，達到頤養天年的終極目標。 本篇論文借重65歲老齡族群的風險趨避之實證觀點，進一步探究老齡化率，65歲老齡族群占總體人口比率的具體影響，更為精確專注在，當其佔比程度從老齡化社會(7～14%)成長至老齡社會(14～21%)，並進一步遽增到超老齡社會(21%以上)，如此持續的老化現象，針對股市市場中，年輕族群的風險接受和老齡族群的風險趨避之偏好傾向，將如何影響股市風險溢酬？根據上述問題，本文鎖定亞太地區經歷老齡化率影響的中國、香港、日本、韓國、新加坡、臺灣，以及泰國為例，佐以老齡化率變動、扶養比率變動、平減指數變動，以及消費支出變動，為獨立的預測變數，並以時間序列分析1960～2016年間，此七大亞洲重要市場，進行實證本文所欲關注的老齡化率變動，將會如何影響股市風險溢酬之核心議題。 由實證結果進行深入剖析，老齡化率變動與扶養比率變動皆與風險溢酬為負向關聯，推論老齡人口結構被迫接納資本市場的風險與波動，顛覆過往撤出市場的觀點和思維。唯有重視老齡的議題、老齡族群的權益，以及老齡化率飆漲的壓力，並有更為大膽的擘劃和精心的規劃，方能強化一地未來的國際經貿和投資誘因。

Focusing on age issue, the empirical results have found that the early growth will reduce the risk aversion and embrace the risk, aggressively. Once the age reaches 65, the personal risk aversion will increase with this age issue, accordingly. It is reasonable that in the working-age, the expected income and capital investment will give time to tolerate personal risk losses, accumulate profits, and will eventually achieve the level of wealth. However, in the retirement-age of 65, along with zero income, stable assets dominate one’s living standard, and this mental safeguard will change the allocation of personal assets from risk capital to fixed Income to reach the ultimate goal of elderly life. This essay, based on the empirical evidence of risk aversion for age 65, emphasizes the impact of ageing population ratio degree of three stages from elementary 7～14%, intermediate 14～21%, and to superior 21% above, trying to figure out that how ageing population rate change along with risk tendency between working-age and retirement-age affects equity risk premium? It investigates China, Hong Kong, Japan, Korea, Singapore, Taiwan and Thailand, affected by the aging issues in the Asia Pacific region as examples, combines changes of ageing ratio, dependency ratio, GDP deflator, and consumption expenditure as predictor variables, and analyzes these markets in time series from 1960 to 2016 for how ageing population rate change affects equity risk premium? By the empirical results in-depth analysis, changes of ageing ratio and dependency ratio have negative coefficient with risk premium. This ageing population structure forces retirement group to take risk and burden volatility from stock markets, which shows a different perspective in our previous studies. Only by facing the music of ageing issues can we seize the opportunity to build a bold strategy for a place’s promising future.