Please wait a minute...
金融研究  2020, Vol. 480 Issue (6): 96-113    
  论文 本期目录 | 过刊浏览 | 高级检索 |
人口学特征与利率期限结构:老年社会平缓的收益率曲线
李雪, 朱超, 易祯
首都经济贸易大学金融学院, 北京 100070
Demographics and the Term Structure of Interest Rates: The Flat Yield Curve of an Elderly Society
LI Xue, ZHU Chao, YI Zhen
School of Finance, Capital University of Economics and Business
下载:  PDF (1043KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 本文将刻画人口结构的生命周期模型引入消费-资本资产定价模型,考察人口结构对利率期限结构的影响。模型表明,人口结构及其家庭生命周期特征不仅决定利率水平,而且将通过人对债券期限的不同偏好,影响利率期限结构。少年人口占比对利率期限结构的影响为正,中年和老年人口占比的影响为负。相比少年人口,中老年人口更偏好长期债券,使长期收益率下降,期限结构的斜率更为平缓。基于全球数据的经验研究验证了这一结论。少年人口占比增加期限利差,中老年人口占比则起反向作用。因此,在年长的经济体中,期限利差更小,呈现更平缓的收益率曲线特征。在更换人口结构变量、期限利差变量、估计方法、赋权样本和处理遗漏变量后,结果表现稳健。本文从人口学视角拓宽了利率期限结构的决定因素,揭示了老年经济体可能面临一个平缓的收益率曲线,而这说明老龄化还可能通过抑制短期投机和促进长期投资来提高长期经济发展质量。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
李雪
朱超
易祯
关键词:  利率期限结构  生命周期理论  人口结构    
Summary:  The slope of the yield curve is an important predictor of future economic activity. A flatter or inverted term spread often predicts low future output growth and a high probability of a recession. As an important economic signal and pricing benchmark for financial markets, the term structure of interest rates also affects investment decisions. We use demographics to study the dynamics of the yield curve. First, we discuss theoretically the channel of influence of the demographic structure. Next, we build a life-cycle model by introducing the consumption-capital asset pricing model (C-CAPM) to capture the dynamics of the yield curve. The life-cycle model allows us to capture the demographic structure and provides a general equilibrium basis for our analysis.
Our model reveals that the population structure affects the term structure of interest rates because of changes in savings over the life cycle, making demographics an important determinant of the yield curve. By influencing bond yields, the population structure has an impact on the yield curve. A young population prefers short-term bonds, which has a positive impact on the term structure of interest rates. Both middle-aged and elderly populations prefer long-term bonds, pushing down the long-term yields. Consequently, the slope of the term structure flattens with the age of the population.
The empirical evidence supports the predictions of our model. We obtain demographic data from the Health Nutrition and Population Statistics database of the World Bank and yield rate data from the International Financial Statistics database of the International Monetary Fund and the Wind database. Data on GDP, inflation and other economic variables come from the World Development Indicators dataset of the World Bank. Our sample includes 58 years of annual data from 194 countries or regions. We find that the term spread increases with the proportion of youth in an economy and that the proportions of middle-aged and elderly individuals have the opposite effect. The term spread is smaller and the yield curve is flatter in an older economy. These findings are robust to alternative population structure variables, term spread variables, estimation methods and sample weights.
The contributions of this paper are as follows. First, our theoretical model combines the life-cycle model and C-CAPM to examine how demographics relate to interest rates. Numerous studies focus on the impact of macroeconomic variables such as output and prices on the term structure of interest rates. We extend the literature by focusing on demographics as the driving force of the yield curve. In addition, we provide empirical evidence of the relationship between the population structure and the yield curve using various age structure variables, multi-dimensional yield curves (level and slope) and empirical models.
The second contribution is an interesting finding regarding the relationship between demographics and the yield curve. The theoretical and empirical evidence suggests that older economies may have higher short-term interest rates and lower long-term interest rates, leading to a relatively flat yield curve. A common concern is that an inverted yield curve might forecast an economic recession. However, a flat yield curve can stimulate long-term investment. In this sense, an increase in the age of the population can have a positive effect on long-term economic development.
The world's population is aging. Financial markets will respond to this change accordingly. Understanding the dynamic relationship between the yield curve and macroeconomic variables is of great importance. Our study provides investors with advice on how to judge market price distortions in the future. China's central bank, the People's Bank of China (PBOC), has recently lowered thereserve ratio. The new loan prime rate (LPR) is linked to interest rates set during open market operations, namely the PBOC’s medium-term lending facility. This change is meant to improve financial support and reduce the capital cost of the real economy. To further reduce interest rates, especially the long-term interest rate, the LPR interest rate mechanism should be used to increase the difference in interest rate policies, crack down on short-term speculation, encourage long-term investment and guide the development of the financial sector to coordinate with economic and social development. The population is always an important factor in economic development. Increasing the fertility rate and reducing the average age can revert the term structure of interest rates to a normal shape in the long run, improve the vitality of the economy and reduce the probability of an economic recession.
Keywords:  Term Structure of Interest Rate    Life-Cycle Theory    Demographic Structure
JEL分类号:  E43   E44   J11  
基金资助: * 本文感谢国家社会科学基金青年项目“供给侧价格粘性与货币政策传导机制阻滞研究”(16CJL016)资助。
作者简介:  李 雪,经济学博士,副教授,首都经济贸易大学金融学院,E-mail:lix@cueb.edu.cn.
易 祯,经济学博士,讲师,首都经济贸易大学金融学院,E-mail:yizhen@cueb.edu.cn.
朱超(通讯作者),经济学博士,教授,首都经济贸易大学金融学院,E-mail:zhuchao@cueb.edu.cn.
引用本文:    
李雪, 朱超, 易祯. 人口学特征与利率期限结构:老年社会平缓的收益率曲线[J]. 金融研究, 2020, 480(6): 96-113.
LI Xue, ZHU Chao, YI Zhen. Demographics and the Term Structure of Interest Rates: The Flat Yield Curve of an Elderly Society. Journal of Financial Research, 2020, 480(6): 96-113.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2020/V480/I6/96
[1] 陈国进和李威,2013,《人口结构与利率水平研究》,《中国人口科学》第5期,第68~77页。
[2] 丁志国、徐德财和陈浪南,2014,《利率期限结构的动态机制:由实证检验到理论猜想》,《管理世界》第5期,第36~51页。
[3] 尚玉皇、郑挺国和夏凯,2015,《宏观因子与利率期限结构:基于混频Nelson-Siegel模型》,《金融研究》第6期,第14~29页。
[4] 易祯和朱超,2017,《人口结构与金融市场风险结构:风险厌恶的生命周期特征》,《经济研究》第9期,第150~164页。
[5] 张强和胡荣尚,2014,《中央银行沟通对利率期限结构的影响研究》,《国际金融研究》第6期,第10~20页。
[6] Aksoy, Y., H.S. Basso, T. Grasl, and R.P. Smith. 2019. “Demographic Structure and Macroeconomic Trend”, American Economic Journal: Macroeconomics, 11(1):193~222.
[7] Ang, A. and M. Piazzesi. 2003. “No-arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables” ,Journal of Monetary Economics, 50(4):745~787.
[8] Ang, A., M. Piazzesi, and M. Wei. 2006. “What does the Yield Curve Tell us about GDP Growth?” ,Journal of Econometrics, 131(1-2):359~403.
[9] Buncic, D. and P. Lentner. 2016. “The Term Structure of Interest Rates in an Estimated New Keynesian Policy Model”,Journal of Macroeconomics, 50:126~150.
[10] Campbell, J.Y. and R.J. Shiller. 1991. “Yield Spreads and Interest Rate Movements: A Bird's Eye View” ,The Review of Economic Studies, 58(3):495~514.
[11] Campbell, J.Y. and L. Viceira. 2001. “Who Should Buy Long-term Bonds?” ,The American Economic Review, 91(1):99~127.
[12] Carvalho, C., A. Ferrero, and F. Nechio. 2016. “Demographics and Real Interest Rates: Inspecting the Mechanism” ,European Economic Review, 88:208~226.
[13] Davis, E.P. and C. Li. 2003. “Demographics and Financial Asset Prices in the Major Industrial Economies”, Brunel University Working Paper NO.03-07.
[14] Diebold, F.X. and C. Li. 2006. “Forecasting the Term Structure of Government Bond Yields” ,Journal of Econometrics, 130(2):337~364.
[15] Diebold, F.X., G.D. Rudebusch, and S.B. Aruoba. 2006. “The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach”, Journal of Econometrics, 131(1-2):309~338.
[16] Doh, T. 2011. “Yield Curve in an Estimated Nonlinear Macro Model” ,Journal of Economic Dynamics and Control, 35(8):1229~1244.
[17] Estrella, A. and F.S. Mishkin. 1997. “The Predictive Power of the Term Structure of Interest Rates in Europe and the United States: Implications for the European Central Bank” ,European Economic Review, 41(7):1375~1401.
[18] Favero, C.A., A.E. Gozluklu, and H. Yang. 2016. “Demographics and the Behavior of Interest Rates” ,IMF Economic Review, 64(4):732~776.
[19] Fair, R. C. and K.M. Dominguez. 1991. “Effects of the Changing US Age Distribution on Macroeconomic Equations” ,The American Economic Review, 81(5):1276~1294.
[20] Geanakoplos, J., M. Magill, and M. Quinzii. 2004. “Demography and the Long-run Predictability of the Stock Market”, Brookings Papers on Economic Activity, 1:241~325.
[21] Guibaud, S., Y. Nosbusch and D.Vayanos. 2013. “Bond Market Clienteles, the Yield Curve, and the Optimal Maturity Structure of Government Debt”, The Review of Financial Studies, 26(8):1914~1961.
[22] Hanson, S.G. and J.C. Stein. 2015. “Monetary Policy and Long-term Real Rates” ,Journal of Financial Economics, 115(3):429~448.
[23] Hvozdenska, J. 2015. “The Yield Curve as a Predictor of Gross Domestic Product Growth in Nordic Countries” ,Procedia Economics and Finance, 26:438~445.
[24] Nelson, C. and A. Siegel, 1987, “Parsimonious Modelling of Yield Curves” ,Journal of Business, 60:473~489.
[25] Rudebusch, G.D. and T.A. Wu. 2008. “Macro‐finance Model of the Term Structure, Monetary Policy and the Economy” ,The Economic Journal, 118(530):906~926.
[26] Taylor, J.B. 1993. “Discretion versus Policy Rules in Practice”, Canergie-Rochester Conference Series on Public Policy, 39(1):195~214.
[27] Vasicek, O. 1977. “An Equilibrium Characterization of the Term Structure” ,Journal of Financial Economics, 5(2):177~188.
[28] Zhang, H., H. Zhang, and J. Zhang. 2015. “Demographic Age Structure and Economic Development: Evidence from Chinese Provinces” ,Journal of Comparative Economics, 43(1):170~185.
[1] 牛霖琳, 林木材. 中国超长期国债的相对流动性溢价与收益率曲线的结构性建模[J]. 金融研究, 2017, 442(4): 17-31.
[2] 樊纲治, 王宏扬. 家庭人口结构与家庭商业人身保险需求——基于中国家庭金融调查(CHFS)数据的实证研究[J]. 金融研究, 2015, 421(7): 170-189.
[3] 邹瑾, 于焘华, 王大波. 人口老龄化与房价的区域差异研究——基于面板协整模型的实证分析[J]. 金融研究, 2015, 425(11): 64-79.
[1] 王曦, 朱立挺, 王凯立. 我国货币政策是否关注资产价格?——基于马尔科夫区制转换BEKK多元GARCH模型[J]. 金融研究, 2017, 449(11): 1 -17 .
[2] 刘勇政, 李岩. 中国的高速铁路建设与城市经济增长[J]. 金融研究, 2017, 449(11): 18 -33 .
[3] 况伟大, 王琪琳. 房价波动、房贷规模与银行资本充足率[J]. 金融研究, 2017, 449(11): 34 -48 .
[4] 祝树金, 赵玉龙. 资源错配与企业的出口行为——基于中国工业企业数据的经验研究[J]. 金融研究, 2017, 449(11): 49 -64 .
[5] 陈德球, 陈运森, 董志勇. 政策不确定性、市场竞争与资本配置[J]. 金融研究, 2017, 449(11): 65 -80 .
[6] 牟敦果, 王沛英. 中国能源价格内生性研究及货币政策选择分析[J]. 金融研究, 2017, 449(11): 81 -95 .
[7] 高铭, 江嘉骏, 陈佳, 刘玉珍. 谁说女子不如儿郎?——P2P投资行为与过度自信[J]. 金融研究, 2017, 449(11): 96 -111 .
[8] 吕若思, 刘青, 黄灿, 胡海燕, 卢进勇. 外资在华并购是否改善目标企业经营绩效?——基于企业层面的实证研究[J]. 金融研究, 2017, 449(11): 112 -127 .
[9] 姜军, 申丹琳, 江轩宇, 伊志宏. 债权人保护与企业创新[J]. 金融研究, 2017, 449(11): 128 -142 .
[10] 刘莎莎, 孔高文. 信息搜寻、个人投资者交易与股价联动异象——基于股票送转的研究[J]. 金融研究, 2017, 449(11): 143 -157 .
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 《金融研究》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持:support@magtech.com.cn
京ICP备11029882号-1