Macroeconomic effects of China's Western Development Program: Analysis of co-movements among different regions based on the Bayesian dynamic latent factor model
LIU Chun1, ZHANG Jian2
1. School of Economics and Management, Tsinghua University, Beijing 100084, China; 2. State Administration of Foreign Exchange, Beijing 100048, China
Abstract：The influence of state-level and regional economic fluctuations on regional economic growth was analyzed using a Bayesian dynamic latent factor model based on the different economic development rates in different regions of China. This method decomposes the fluctuations of the macroeconomic aggregates in China into the state factor, the regional factors and the idiosyncratic errors specific to each aggregate variable. The dynamics of the macroeconomic variables were analyzed from 1980 to 2015 to show that the regional output and investment are mainly influenced by the state factor, while regional consumption is mainly influenced by the regional factor. Furthermore, the study finds that after implementation of China's Western Development Program, the state factor has more significant influence on the fluctuations of all the economic variables in the western region with the greatest influence on investment.
刘淳, 张健. 西部大开发政策对中国经济的影响——基于Bayes动态隐变量模型的中国地区经济联动性研究[J]. 清华大学学报（自然科学版）, 2019, 59(11): 934-939.
LIU Chun, ZHANG Jian. Macroeconomic effects of China's Western Development Program: Analysis of co-movements among different regions based on the Bayesian dynamic latent factor model. Journal of Tsinghua University(Science and Technology), 2019, 59(11): 934-939.
[1] CARSTENSEN K, SALZMANN L. The G7 business cycle in a globalized world[R]. Munich, Germany:Leibniz Institute for Economic Research at the University of Munich, 2016. [2] DOYLE B M, FAUST J, HALKET J R. An investigation of co-movements among the growth rates of the G7 countries[J]. Federal Reserve Bulletin, 2002, 88(10):427-437. [3] KALEMLI-OZCAN S, SØRENSEN B E, YOSHA O. Risk sharing and industrial specialization:Regional and international evidence[J]. American Economic Review, 2003, 93(3):903-918. [4] IMBS J. The real effects of financial integration[J]. Journal of International Economics, 2006, 68(2):296-324. [5] BAXTER M, KOUPARITSAS M A. Determinants of business cycle comovement:A robust analysis[J]. Journal of Monetary Economics, 2005, 52(1):113-157. [6] KOSE M A, PRASAD E S, TERRONES M E. How does globalization affect the synchronization of business cycles?[J]. American Economic Review, 2003, 93(2):57-62. [7] HOLLY S, PETRELLA I. Factor demand linkages, technology shocks, and the business cycle[J]. The Review of Economics and Statistics, 2012, 94(4):948-963. [8] 林毅夫, 蔡昉, 李周. 中国经济转型时期的地区差距分析[J]. 经济研究, 1998(6):3-10. LIN Y F, CAI F, LI Z. Analysis of China's regional disparities in the period of economy transition[J]. Economic Research Journal, 1998(6):3-10. (in Chinese) [9] 蔡昉, 都阳. 中国地区经济增长的趋同与差异——对西部开发战略的启示[J]. 经济研究, 2000(10):30-37. CAI F, DU Y. Convergence and divergence of regional economic growth in China[J]. Economic Research Journal, 2000(10):30-37. (in Chinese) [10] YAO S J, ZHANG Z Y. On regional inequality and diverging clubs:A case study of contemporary China[J]. Journal of Comparative Economics, 2001, 29(3):466-484. [11] 梁经伟, 文淑惠, 杜洪燕. "一带一路"战略下中国与周边国家经济联动关系研究[J]. 地域研究与开发, 2016, 35(3):5-10, 63. LIANG J W, WEN S H, DU H Y. Economic co-movement between china and neighboring countries under the belt and road initiative[J]. Areal Research and Development, 2016, 35(3):5-10, 63. (in Chinese) [12] 徐世腾, 陈有志. "一带一路"国家经济联动效应研究[J]. 浙江工商大学学报, 2018, 32(2):99-108. XU S T, CHEN Y Z. Economic co-movement effects of macroeconomic policies among countries of "One Belt One Road"[J]. Journal of Zhejiang Gongshang University, 2018, 32(2):99-108. (in Chinese) [13] OTROK C, WHITEMAN C H. Bayesian leading indicators:Measuring and predicting economic conditions in Iowa[J]. International Economic Review, 1998, 39(4):997-1014. [14] STRICKLAND C M, TURNER I W, DENHAM R, et al. Efficient Bayesian estimation of multivariate state space models[J]. Computational Statistics & Data Analysis, 2009, 53(12):4116-4125. [15] DURBIN J, KOOPMAN S J. A simple and efficient simulation smoother for state space time series analysis[J]. Biometrika, 2002, 89(3):603-616. [16] CHRISTODOULAKIS N, DIMELIS S P, KOLLINTZAS T. Comparisons of business cycles in the EC:Idiosyncracies and regularities[J]. Economica, 1995, 62(245):1-27.
2019, Vol. 59 
