Summary:
How monetary policy affects output and inflation is a fundamental question in macroeconomics. Consumption and investment are the two main components of the gross domestic product (GDP). Although a large body of literature has examined the inflation of consumption goods, few studies have focused on the inflation of investment goods. The inflation of these two sectors in China moved in a highly correlated manner before 2011, and then diverged after that year. Therefore, the relative price gap has increased since 2011, which suggests a different mechanism of inflation dynamics. This raises the question of how the monetary policy on output and inflation has affected these two sectors, how the monetary transmission mechanism differs between the two sectors, and what factors determine the inflation dynamics of the two sectors. By studying these problems, we can better understand the different behaviors of consumption and investment in relation to macroeconomic fluctuations. We also examine the impact of monetary policy on the economy and provide helpful suggestions for policy making in business cycles. To provide empirical evidence, we use Bayesian VAR to evaluate the effects of monetary shocks on the output and inflation of the consumption and investment sectors. Following Litterman (1986), we estimate the BVAR and obtain the impulse response functions. Our impulse response analysis shows that when monetary policy is expansive, the output and inflation of both sectors increase. However, the increase in the output and inflation of the investment sector is greater than that in the consumption sector. This paper establishes a two-sector new Keynesian DSGE model of consumption and investment goods production, and incorporates a financial accelerator to study the effects of a monetary shock on consumption and investment inflation. By incorporating the financial accelerator, our model can better characterize a firm's investment behavior. China's quarterly macroeconomic data are used to estimate the model using a Bayesian approach. The estimation results show that the degree of the nominal price rigidities of the consumption and investment sectors are high and very close. However, the external finance premium has different effects on firms' investment behavior, with the financial accelerator effect being stronger in the investment sector. The impulse response of the model under a monetary shock is consistent with the empirical evidence based on the BVAR analysis. We further show that the demand structure heterogeneity of the two sectors is the key to explaining the effects of a monetary shock. Although firms are on the demand side of investment goods, they are also subject to financial friction when borrowing from financial intermediaries. The financial accelerator thus amplifies a firm's investment demand when the monetary policy is expansive. However, the demand for consumption goods has a smaller response to monetary shock, because households prefer consumption smoothing. Therefore, the heterogeneous demand effects result in different output and inflation dynamics. Our numerical simulation shows that the financial accelerator is the main factor influencing the effects of monetary shocks on investment output and inflation, and that it has minor effects on the consumption sector. A variance decomposition shows that aggregate technology, investment marginal efficiency, and monetary shocks are important determinants of business cycles. This paper contributes to the literature by constructing a complete two-sector model characterizing the demand and supply sides of the consumption and investment sectors. Using a Bayesian estimation, we show that demand structure heterogeneity rather than nominal price rigidity is the key factor explaining the different responses of the two sectors to monetary shocks. Although our analysis of the investment sector is more generalized than in previous studies, our estimation results show that investment shocks are the main driving force of business cycles. Overall, our results suggest that the central bank should take the structure and characteristics of different sectors into consideration when implementing monetary policy. The central bank should also pay attention to the financial condition of firms because it can change the transmission mechanism of monetary policy in different sectors.
[1]陈彦斌,2008,《中国新凯恩斯菲利普斯曲线研究》,《经济研究》第12期,第50-64页。 [2]贺力平、樊纲和胡嘉妮,2008,《消费者价格指数与生产者价格指数:谁带动谁?》,《经济研究》第11期,第16-26页。 [3]侯成琪和龚六堂,2013,《食品价格、核心通货膨胀与货币政策目标》,《经济研究》第11期,第27-42页。 [4]侯成琪和龚六堂,2014,《部门价格粘性的异质性与货币政策的传导》,《世界经济》第07期,第23-44页。 [5]黄赜琳,2005,《中国经济周期特征与财政政策效应——一个基于三部门rbc模型的实证分析》,《经济研究》第06期,第27-39页。 [6]陆军和钟丹,2003,《泰勒规则在中国的协整检验》,《经济研究》第08期,第76-85页。 [7]吕捷和王高望,2015,《Cpi与ppi“背离”的结构性解释》,《经济研究》第04期,第136-149页。 [8]伍戈和曹红钢,2014,《中国的结构性通货膨胀研究——基于cpi与ppi的相对变化》,《金融研究》第06期,第1-16页。 [9]谢平和罗雄,2002,《泰勒规则及其在中国货币政策中的检验》,《经济研究》第03期,第3-12页。 [10]张屹山和张代强,2007,《前瞻性货币政策反应函数在我国货币政策中的检验》,《经济研究》第03期,第20-32页。 [11]庄子罐、崔小勇和赵晓军,2016,《不确定性、宏观经济波动与中国货币政策规则选择——基于贝叶斯DSGE模型的数量分析》,《管理世界》第11期,第20-31页。 [12]Bernanke, B. S., M. Gertler and S. Gilchrist, 1999, “The Financial Accelerator in a Quantitative Business Cycle Framework,” Handbook of Macroeconomics, 1, pp. 1341-1393. [13]Bouakez, H., E. Cardia and F. J. Ruge-Murcia, 2009, “The Transmission of Monetary Policy in a Multisector Economy,” International Economic Review, 50(4), pp. 1243-1266. [14]Calvo, G. A., 1983, “Staggered Prices in a Utility-Maximizing Framework,” Journal of Monetary Economics, 12(3), pp. 383-398. [15]Chang, C., K. Chen, D. F. Waggoner and T. Zha, 2016, “Trends and Cycles in China’s Macroeconomy,” NBER Macroeconomics Annual, 30(1), pp. 1-84. [16]Christiano, L., R. Motto and M. Rostagno, 2003, “The Great Depression and the Friedman-Schwartz Hypothesis,” Journal of Money Credit and Banking, 35(6), pp. 1119-1197. [17]Christiano, L. J., M. Eichenbaum and C. L. Evans, 1999, “Monetary Policy Shocks: What Have We Learned and to What End?,” Handbook of Macroeconomics, 1, pp. 65-148. [18]Christiano, L. J., M. Eichenbaum and C. L. Evans, 2005, “Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy,” Journal of Political Economy, 113(1), pp. 1-45. [19]Christiano, L. J., R. Motto and M. Rostagno, 2014, “Risk Shocks,” American Economic Review, 104(1), pp. 27-65. [20]De Graeve, F., 2008, “The External Finance Premium and the Macroeconomy: Us Post-Wwii Evidence,” Journal of Economic Dynamics & Control, 32(11), pp. 3415-3440. [21]Del Negro, M., M. P. Giannoni and F. Schorfheide, 2015, “Inflation in the Great Recession and New Keynesian Models,” American Economic Journal-Macroeconomics, 7(1), pp. 168-196. [22]Doan, T. 1992, Rats: User's Manual, Version 4, Published by Estima. [23]Fisher, J. D. M., 2006, “The Dynamic Effects of Neutral and Investment-Specific Technology Shocks,” Journal of Political Economy, 114(3), pp. 413-451. [24]Gali, J. and M. Gertler, 1999, “Inflation Dynamics: A Structural Econometric Analysis,” Journal of Monetary Economics, 44(2), pp. 195-222. [25]Greenwood, J., Z. Hercowitz and P. Krusell, 2000, “The Role of Investment-Specific Technological Change in the Business Cycle,” European Economic Review, 44(1), pp. 91-115. [26]Higgins, P. C. and T. Zha, 2015, “China’s Macroeconomic Time Series: Methods and Implications,” Unpublished Manuscript, Federal Reserve Bank of Atlanta [27]Justiniano, A., G. E. Primiceri and A. Tambalotti, 2010, “Investment Shocks and Business Cycles,” Journal of Monetary Economics, 57(2), pp. 132-145. [28]Justiniano, A., G. E. Primiceri and A. Tambalotti, 2011, “Investment Shocks and the Relative Price of Investment,” Review of Economic Dynamics, 14(1), pp. 102-121. [29]Litterman, R. B., 1986, “Forecasting with Bayesian Vector Autoregressions - 5 Years of Experience,” Journal of Business & Economic Statistics, 4(1), pp. 25-38. [30]Nakamura, E. and J. Steinsson, 2010, “Monetary Non-Neutrality in a Multisector Menu Cost Model,” Quarterly Journal of Economics, 125(3), pp. 961-1013. [31]Sbordone, A. M., 2002, “Prices and Unit Labor Costs: A New Test of Price Stickiness,” Journal of Monetary Economics, 49(2), pp. 265-292. [32]Smets, F. and R. Wouters, 2003, “An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area,” Journal of the European Economic Association, 1(5), pp. 1123-1175. [33]Smets, F. and R. Wouters, 2007, “Shocks and Frictions in Us Business Cycles: A Bayesian Dsge Approach,” American Economic Review, 97(3), pp. 586-606. [34]Taylor, J. B., 1993, “Discretion Versus Policy Rules in Practice,” Carnegie-Rochester conference series on public policy, 39, pp. 195-214.
