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金融研究  2019, Vol. 467 Issue (5): 1-16    
  本期目录 | 过刊浏览 | 高级检索 |
耐用品、投资专有冲击与货币政策福利
石峰, 王忏
北京大学光华管理学院, 北京 100871;
中央财经大学金融学院, 北京 100081
Durable Goods, Investment-specific Shocks and Welfare Consequences of Monetary Policy Rules
SHI Feng, WANG Chan
Guanghua School of Management, Peking University;
Financial School, Central University of Finance and Economics
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摘要 本文构建蕴含耐用品与非耐用品的两部门DSGE模型,研究投资专有冲击对货币政策及社会福利的影响。投资专有技术进步改进了投资转化为生产资本的效率,放大边际成本波动,增加了厂商调价动机和价格水平变动。即使耐用品价格完全灵活,最优货币政策也无法同时稳定价格和实际GDP。研究发现:(1)耐用品相对价格缺口波动率的上升虽然增加了实际GDP波动,但能够有效地降低投资专有技术对边际成本的冲击,减少价格变动的福利损失。所以两部门投资专有冲击时,央行倾向于稳定价格水平。与其相反,在单部门投资专有冲击和两部门生产技术冲击时,最优货币政策应降低耐用品相对价格缺口波动,稳定实际GDP。(2)对比三种泰勒规则:钉住非耐用品PPI、钉住加权平均PPI及钉住CPI,福利分析发现钉住非耐用品PPI最优,钉住CPI次之,钉住加权平均PPI的福利损失最大。就损失程度而言,投资专有冲击的福利损失是生产技术冲击的2倍,表明投资专有冲击加剧了最优货币政策在稳定价格与实际GDP间的权衡。
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石峰
王忏
关键词:  投资专有冲击  耐用品相对价格  泰勒法则  福利分析    
Summary:  The major purpose of monetary policy is to stabilize the fluctuations in economic variables and smooth the development of the macro-economy. Obviously, different exogenous shocks yield significant heterogeneous effects on the transmission mechanism and monetary policy choices. Hence, identifying the sources and characteristics of the crucial driving forces of economic dynamics is the prime task of the monetary authority. In the literature on real business cycles, including research on monetary policy in the New Keynesian framework, neutral technology shocks are treated as the main driving forces of economic variations.
However, empirical evidence from structural vector auto-regressions shows that economic fluctuations probably result from other exogenous shocks, such as investment-specific, labor supply, real interest rate, consumption, and housing demand shocks. The role of investment-specific shocks on the real business cycle is gradually attracting research interest. Several studies show that investment-specific shocks explain only about 30% of the volatility in aggregate output since World War Two. Yet some investigations of investment-specific shocks on economic cycles in China find that these shocks account for 90%, 62%, and 66% fluctuations of GDP, investment, and capital accumulation, respectively.
Inspired by these findings, we first construct a two-sector DSGE economy featuring durable and non-durable goods. The non-durable goods can only be used for consumption, whereas the durable goods can be used either for consumption by entering the household utility function, or as investment and capital goods entering firm production in both sectors.
Based on the DSGE model mentioned above, we analyze the implications of investment-specific shocks for optimal monetary policy design and the welfare consequences of alternative monetary policy rules. Our findings are as follows. First, the optimal monetary policy is unable to stabilize price inflation and output simultaneously. It is optimal to increase the variation in the price of durables relative to non-durable goods, which in turn reduces the impact of investment-specific shocks on the real marginal cost and the incentive for firms in non-durable sectors to adjust prices, thus improving social welfare. Meanwhile, the rise in fluctuation of the relative price of durables amplifies the variation in output in non-durable and durable sectors, household consumption, and aggregate investment.
Second, we compare the welfare results of three different monetary policy targeting regimes, targeting non-durable PPI inflation, weighted average PPI inflation, and CPI inflation. Under all exogenous shocks, targeting non-durable PPI inflation is always able to increase social welfare, targeting weighted average PPI inflation has the worst effect on social welfare, and targeting CPI inflation has an effect somewhere between those of the other two. When monetary authorities choose to target non-durable PPI inflation, the welfare performance under investment-specific shocks is about twice that under a neutral technology shock. The comparison illustrates that the monetary policy trade-offs between stabilizing price inflation and stabilizing output are tensioned by investment-specific shocks. A sensitivity analysis shows that the results are robust when key structural parameters are changed, such as the steady-state weight of durable consumption goods in aggregate consumption, the Frisch labor supply elasticity, and the depreciation rate of durable goods.
The conclusions of this study lead to the following suggestions for monetary policy by the People's Bank of China. First, in a dynamic stochastic general equilibrium featuring multi-sector, the central bank should consider the variations in relative prices in different sectors, and pay attention to their role in stabilizing price levels and real GDP. The operation space for monetary policy could be improved by reasonable movements in relative price. Second, the central bank should take into account the properties of different exogenous shocks. Taking our benchmark model for example, the monetary bias or stance under an investment-specific shock is obviously different from that under a neutral technology shock.
Keywords:  Investment-Specific Shocks    Relative Price of Durable Goods    Taylor Rules    Welfare Analysis
JEL分类号:  C11   E12   E32   E52  
基金资助: 本文感谢中央财经大学青年教师发展基金(QJJ1707)和中央财经大学金融学院新进教师科研启动基金项目的资助。
作者简介:  石 峰(通讯作者),经济学博士,助理研究员,北京大学光华管理学院,E-mail:feng_shi@pku.edu.cn.
王 忏,经济学博士,讲师,中央财经大学金融学院,E-mail:wangchanist@126.com.
引用本文:    
石峰, 王忏. 耐用品、投资专有冲击与货币政策福利[J]. 金融研究, 2019, 467(5): 1-16.
SHI Feng, WANG Chan. Durable Goods, Investment-specific Shocks and Welfare Consequences of Monetary Policy Rules. Journal of Financial Research, 2019, 467(5): 1-16.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2019/V467/I5/1
[1]陈师和赵磊,2009,《中国的实际经济周期与投资专有技术变迁》,《管理世界》第4期,第5~16页。
[2]黄志刚和许伟,2017,《住房市场波动与宏观经济政策的有效性》,《经济研究》第5期,第103~116页。
[3]侯成琪和龚六堂,2014,《货币政策应该对住房价格波动作出反应吗——基于两部门动态随机一般均衡模型的分析》,《金融研究》第10期,第15~33页。
[4]康立和龚六堂,2014,《金融摩擦、银行净资产与国际经济危机传导——基于多部门DSGE模型分析》,《经济研究》第5期,第147~159页。
[5]尚玉皇和郑挺国,2018,《中国金融形势指数混频测度及其预警行为研究》,《金融研究》第3期,第21~35页。
[6]仝冰,2017,《混频数据、投资冲击与中国宏观经济波动》,《经济研究》第6期,第60~76页。
[7]Aoki, K. 2001. “Optimal Monetary Policy Responses to Relative-price Changes”, Journal of Monetary Economics, 48(1): 55~80.
[8]Barsky, R.B., C.L. House, and M.S. Kimball. 2007. “Sticky Price Models and Durable Goods”, American Economic Review, 97(3): 984~998.
[9]Bouakeze, H., E. Cardia, and F. Ruge-Murcia, 2011, “Durable Goods, Inter-sectoral Linkages and Monetary Policy”, Journal of Economic Dynamics and Control, 35(5): 730~745.
[10]Cantelmo, A., and G. Melina. 2018. “Monetary Policy and the Relative Price of Durable Goods”, Journal of Economic Dynamics and Control, 86: 1~48.
[11]Chang, C., J. Chen, D. Waggoner, and T. Zha. 2016. “Trends and Cycles in China's Macroeconomy”, in NBER Macroeconomics Annual, Eds. By Eichenbaum and Parker, 30(1): 1~84.
[12]Chen, B.L., and S.Y. Liao. 2018. “Durable Goods, Investment Shocks and the Comovement Problem”, Journal of Money Credit and Banking, 50: 377~406.
[13]Cochrane, J.H. 1994. “Shocks”, Carnegie-Rochester Conference Series on Public Policy, 41: 295~364.
[14]De Paoli, B., and M. Paustian. 2017. “Coordinating Monetary and Macroprudential Policies”, Journal of Money, Credit and Banking, 49: 319~349.
[15]Erceg, C., and A. Levin. 2006. “Optimal Monetary Policy with Durable Consumption Goods”, Journal of Monetary Economics, 53(7):1341~1359.
[16]Fisher, D., 2006. “The Dynamic Effects of Neutral and Investment-Specific Technology Shocks”, Journal of Political Economy, 114(3):413~451.
[17]Gali, J., and T. Monacelli. 2005. “Monetary Policy and Exchange Rate Volatility in a Small Open Economy”, Review of Economic Studies, 72(3): 707~734.
[18]Greenwood, J., Z. Hercowit, and P. Krusell. 2000. “The Role of Investment-specific Technology Change in the Business Cycle”,. European Economic Review, 44(1): 91~115.
[19]Justiniano, A., G. Primiceri and A. Tambalotti. 2010. “Investment Shocks and Business Cycles”, Journal of Monetary Economics, 57(2): 132~145.
[20]King, R.G., C.I. Plossor, J.H. Stock, and M.W. Watson. 1991. “Stochastic Trends and Economic Fluctuations”, American Economic Review, 81(4): 819~840.
[21]Kydland, F., and E. Prescott. 1982. “Time to Build and Aggregate Fluctuations”, Econometrica,50(6):1345~1370.
[22]Liu, Z., P.F. Wang, and T. Zha. 2013. “Land Price and Macroeconomic Dynamics”, Econometrica, 81(3):1147~1184.
[23]Petrella, I., Rossi R., and E. Santoro, 2019, “Monetary Policy with Sectoral Trade-Offs”, Scandinavian Journal of Economics, 121(1): 55~88.
[24]Rotemberg, J.J. 1982. “Sticky Prices in the United States”, Journal of Political Economy, 90(6): 1182~1121.
[25]Schmitt-Grohe, S., and M. Uribe. 2004. “Solving Dynamic General Equilibrium Models Using a Second Order Approximation to the Policy Function”, Journal of Economic Dynamics and Control, 28∶755~775.
[26]Shapiro, M.D., and M. Watson. 1988. “Sources of Business Cycle Fluctuations”. In NBER Macroeconomics Annual, Eds. By Fisher Stanley, 111 ~148.
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