经济政策不确定性对宏观经济的影响——基于实证与理论的动态分析
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摘要
"新常态"下的经济政策不确定性在加大,但针对该不确定性的宏观效应及其机制的探讨,学界并未展开。为此,本文从实证与理论两个角度研究政策不确定性对宏观经济的影响。基于Max-share方法的结构向量自回归识别技术,本文发现政策不确定性上升会导致产出和物价水平显著下降,从而表现为负的需求冲击。随后,本文将政策不确定性引入新凯恩斯动态一般均衡模型中。定量分析显示:(1)模型很好地解释了实证发现,政策不确定性显著增加了产出和价格波动分别约10%和15%;(2)公众对政策的预期会显著增强不确定性冲击对经济波动的影响;(3)随着经济结构转型期的劳动收入份额下降以及劳动供给弹性变小(刘易斯拐点之后),政策不确定性对中国宏观经济的不利影响将不断增强。
The disturbance from policy uncertainty has been overlooked by the Chinese business cycle literature. We aim to empirically and quantitatively document the aggregate effects of policy uncertainty on the Chinese economy. Using a structural vector auto-regression model with a novel identification scheme, we recover the Chinese policy uncertainty shocks, and find that this type of shock resembles a negative demand shock, leading to declines in output and price level. We then construct a New-Keynesian dynamic general equilibrium model with Chinese characteristics and policy uncertainties. The quantitative exercises show that:(1) The simulation results closely match the empirical findings;(2) The adverse effects of policy uncertainty are exacerbated by introducing expectations about future policy;(3) The adverse effects of policy uncertainty becomes more severe when labor income share and elasticity of labor supply decline.
The disturbance from policy uncertainty has been overlooked by the Chinese business cycle literature. We aim to empirically and quantitatively document the aggregate effects of policy uncertainty on the Chinese economy. Using a structural vector auto-regression model with a novel identification scheme, we recover the Chinese policy uncertainty shocks, and find that this type of shock resembles a negative demand shock, leading to declines in output and price level. We then construct a New-Keynesian dynamic general equilibrium model with Chinese characteristics and policy uncertainties. The quantitative exercises show that:(1) The simulation results closely match the empirical findings;(2) The adverse effects of policy uncertainty are exacerbated by introducing expectations about future policy;(3) The adverse effects of policy uncertainty becomes more severe when labor income share and elasticity of labor supply decline.
引文
[1]Alessandria, G., H. Choi, J. Kaboshi, and V. Midrigan,“Microeconomic Uncertainty, International Trade, and Aggregate Fluctuations”,Journal of Monetary Economics,2015,69,20—38.
[2]Alm,J.,“Uncertain Tax Policies, Individual Behavior, and Welfare”,American Economic Review, 1988,78(1), 237—245.
[3]Andreasen, M., J. Fernández-Villaverde, and J. Rubio-Ramirez, “The Pruned State-Space System for Non-linear DSGE Models: Theory and Empirical Applications”, NBER Working Paper,No.18983, 2013.
[4]Arellano, C., Y. Bai, and P. Kehoe, “Financial Frictions and Fluctuations in Volatility”, NBER Working Paper,No.22990, 2016.
[5]Bachmann R., and C. Bayer,“Investment Dispersion and the Business Cycle”, The American Economic Review, 2014, 104(4),1392—1416.
[6]Bachmann R., and C. Bayer, “‘Wait-and-See’ Business Cycles?”, Journal of Monetary Economics, 2013, 60(6), 704—719.
[7]Baker S.,N. Bloom, and S.Davis,“Measuring Economic Policy Uncertainty”, The Quarterly Journal of Economics, 2016, 131(4),1593—1636.
[8]Barsky R., and E. Sims,“News Shocks and Business Cycles”, Journal of Monetary Economics, 2011, 58(3),273—289.
[9]Basu S., and B. Bundick,“Uncertainty Shocks in a Model of Effective Demand”, Econometrica, 2017, 85(3),937—958.
[10]Bi, H.,E.Leeper, and C. Leith, “Uncertain Fiscal Consolidations”,The Economic Journal, 2013,123(566),F31—F63.
[11]Bizer D., and K.Judd, “Taxation and Uncertainty”,The American Economic Review, 1989, 79(2), 331—336.
[12]Bloom, N.,“Fluctuations in Uncertainty”,The Journal of Economic Perspectives, 2014, 28(2), 153—175.
[13]Bloom, N., M. Floetotto, N. Jaimovich, I.Saporta-Eksten, and S.Terry, “Really Uncertain Business Cycles”,NBER Working Paper,2015,NO.18245.
[14]Bloom, N.,“The Impact of Uncertainty Shocks”, Econometrica, 2009, 77(3),623—685.
[15]Born, B., and J. Pfeifer, “Policy Risk and the Business Cycle”, Journal of Monetary Economics, 2014, 68, 68—85.
[16]Calvo, Guillermo A., “Staggered Prices in a Utility-Maximizing Framework”, Journal of Monetary Economics 1983,12(3), 383—398.
[17]Chang, C., K. Chen, D. Waggoner, and T. Zha, “Trends and Cycles in China's Macroeconomy”, In NBER Macroeconomics Annual 2015, Volume 30.University of Chicago Press, 2015.
[18]Chari, V., P. Kehoe, and E. McGrattan,“Are Structural VARs with Long-Run Restrictions Useful in Developing Business Cycle Theory?”,Journal of Monetary Economics, 2008, 55(8), 1337—1352.
[19]Chen, K., P.Higgins, D.Waggoner, and T. Zha,“China Pro-Growth Monetary Policy and Its Asymmetric Transmission”,National Bureau of Economic Research, No.22650, 2016.
[20]Christiano, L., M.Eichenbaum, and C.Evans,“Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy”,Journal of political Economy, 2005, 113(1),1—45.
[21]Christianom, L., R. Motto, and M.Rostagno,“Risk Shocks”,The American Economic Review, 2014, 104(1),27—65.
[22]陈守东、杨东亮,“我国财政支出不确定性对居民消费影响的实证研究”,《数量经济技术经济研究》,2009年第9期,第119—133页。
[23]Fernandez, R., and D. Rodrik. “Resistance to Reform: Status Quo Bias in The Presence of Individual-Specific Uncertainty”, The American Economic Review, 1991, 1146—1155.
[24]Fernández-Villaverde, J., P. Guerrón-Quintana, and J.Rubio-Ramírez,“Risk Matters: The Real Effects of Volatility Shocks”,The American Economic Review, 2011, 101(6),2530—2561.
[25]Fernández-Villaverde, J., P. Guerrón-Quintana, K. Kuester, and J.Rubio-Ramírez,“Fiscal Volatility Shocks and Economic Activity”,The American Economic Review, 2015, 105(11),3352—3384.
[26]Francis, N., M. Owyang, J. Roush, and R. DiCecio,“A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks”,Review of Economics and Statistics, 2014, 96(4), 638—647.
[27]Funke, M.,“Inflation in China: Modelling a Roller Coaster Ride”,Pacific Economic Review, 2006, 11(4), 413—429.
[28]Gali, J., J. Lopez-Salido, and J. Valles,“Understanding the Effects of Government Spending on Consumption”,Journal of the European Economic Association, 2007, 5(1), 227—270.
[29]Gilchrist, S., J. Sim, and E. Zakraj?ek,“Uncertainty, Financial Frictions, and Investment Dynamics”,NBER Working Paper No.20038, 2014.
[30]Greenwood, J., Z. Hercowitz, and G. Huffman,“Investment, Capacity Utilization, and the Real Business Cycle”,The American Economic Review, 1988, 78(3),402—417.
[31]Hassett, K., and G. Metcalf, “Investment with Uncertain Tax Policy: Does Random Tax Policy Discourage Investment?”, NBER Working Paper No.4780, 1994.
[32]韩立岩、牟晖、王哲兵,“市政债券的风险识别与控制策略”,《管理世界》,2005年第2期,第58—66页。
[33]贾倩、孔祥、孙铮,“政策不确定性与企业投资行为——基于省级地方官员变更的实证检验”,《财经研究》,2013年第2期,第81—91页。
[34]金雪军、钟意、王义中,“政策不确定性的宏观经济后果”,《经济理论与经济管理》,2014年第2期,第17—26页。
[35]King, R., C. Plosser, and S.Rebelo,“Production, Growth and Business Cycles: I. The Basic Neoclassical Model”,Journal of monetary Economics, 1988, 21(2—3), 195—232.
[36]Ladner, P., and S. Rebelo,“Can News about the Future Drive the Business Cycle?”,The American Economic Review, 2009, 99(4), 1097—1118.
[37]Leduc, S., and Z.Liu,“Uncertainty Shocks are Aggregate Demand Shocks”,Journal of Monetary Economics, 2016, 82, 20—35.
[38]Li, B., and Q.Liu,“On the Choice of Monetary Policy Rules for China: A Bayesian DSGE Approach”,China Economic Review, 2017, 44,166—185.
[39]刘尚希,“财政风险: 从经济总量角度的分析”,《管理世界》,2005年第7期,第31—39页。
[40]刘尚希,“财政风险:一个分析框架”,《经济研究》,2003年第5期,第23—31页。
[41]Melitz, M.,“The Impact of Trade on Intra-industry Reallocations and Aggregate Industry Productivity”,Econometrica, 2003, 71(6), 1695—1725.
[42]Pastor, L., and P.Veronesi,“Uncertainty about Government Policy and Stock Prices”,The Journal of Finance, 2012, 67(4),1219—1264.
[43]Ramey, V.,“Identifying Government Spending Shocks:It's All in the Timing”,The Quarterly Journal of Economics, 2011, 126(1),1—50.
[44]Rodrik, D.,“Policy Uncertainty and Private Investment in Developing Countries”, Journal of Development Economics, 1991, 36(2),229—242.
[45]Song, Z., K. Storesletten, and F.Zilibotti,“Growing Like China”,The American Economic Review, 2011, 101(1),196—233.
[46]Uhlig, H.,“Do Technology Shocks Lead to a Fall in Total Hours Worked?”,Journal of the European Economic Association, 2004, 2(2—3), 361—371.
[47]Wang P, and Y.Wen,“Another Look at Sticky Prices and Output Persistence”,Journal of Economic Dynamics and Control, 2006, 30(12). 2533—2552.
[48]王必达、张忠杰,“中国刘易斯拐点及阶段研究——基于31个省际面板数据”,《经济学家》,2014年第7期。
[49]王伟同,“中国人口红利的经济增长‘尾效’研究——兼论刘易斯拐点后的中国经济”,《财贸经济》,2012年第11期,第14—20页。
[50]吴化斌、许志伟、胡永刚、鄢萍,“消息冲击下的财政政策及其宏观影响”,《管理世界》,2011年第9期,第26—39页。
[51]吴敬琏,《中国增长模式抉择》。上海:上海远东出版社,2006年。
[52]许志伟、薛鹤翔、罗大庆,“融资约束与中国经济波动——新凯恩斯主义框架内的动态分析”,《经济学》(季刊),2010年第3期。
[53]朱军、许志伟,“财政分权、地区间竞争与中国经济波动——多级政府框架下的动态一般均衡分析”,《经济研究》。2018年第1期。
[54]Zhang, W.,“China's Monetary Policy: Quantity versus Price Rules”,Journal of Macroeconomics, 2009, 31(3), 473—484.
(1)1http://news.xinhuanet.com/politics/2014-02/22/c_126175088.htm
(2)2在实证部分,本文将详细讨论该方法较之传统意义上的短期约束(Choleski分解)和长期约束(Blanchard-Quah分解)的主要优势。
(3)3以上结果对于货币数量规则仍然稳健。
(4)4关于异质性模型中的extensive-margin effect,可参考异质性厂商经典文章Melitz(2003)中的讨论。
(5)5需要注意的是,Basu and Bundick(2017)在一个标准的新凯恩斯DSGE模型中讨论了生产率的不确定性冲击,而非宏观政策的不确定性。
(6)6具体见网站:https://www.frbatlanta.org/cqer/research/china-macroeconomy.aspx。
(7)7数据可以从网站http://www.policyuncertainty.com/下载。
(8)8该政策不确定性主要反映了公众对经济形势判断偏差性、政府承诺不一致、官员更替、增税减支改革的落实、税制改革的落地时间、财政货币政策搭配模式的难以识别等。
(9)9我们用4种标准来选择滞后阶数。其中,Hannan-Quinn Criterion和Schwarz Criterion为滞后2阶,Akaike Info Criterion和Final Prediction Error建议为5阶。由于中国时间序列并不是很长,我们选择滞后阶数较少的2阶。基本结果对滞后5阶非常稳健。为讨论一致,我们在随后的VAR估计中,均选择滞后2阶。
(10)10我们所用的产出数据为去除价格因素的季度工业增加值,总消费是去除消费价格指数的季度家庭消费,总投资是去除投资价格指数的季度商业投资[见Chang et al.(2015)的详细讨论]。
(11)11为节省篇幅,这里我们并没有报告具体结果,有兴趣的读者可向作者索取。
(12)12为表述方便,本文模型中关于实际货币余额的决策时间点采用了Wang and Wen(2006)中的设置,即当期的货币可以用于支付当期的消费。而许志伟等(2010)中的设置假设当期货币仅能用于下期消费的支付。两者虽然在时间上有差异,但定量上具有非常类似的动态。
(13)13在基准模型中,流动性约束会使得投资在不确定性增大时,反而下降更少。这是由于该约束使得家庭无法通过资本配置渠道有效地对不确定性做出应对。因而,在面临外部冲击时,投资动态较之标准的CIA约束模型更为平滑。同理,当政府降低不确定性时,流动性约束也阻碍了宏观经济通过增加投资的渠道进行复苏。结果显示,本文结果对流动性约束稳健。感谢匿名审稿人关于该点的讨论。
(14)14根据1992第一季度至2013年第三季度的CPI季度数据显示,CPI季度增长率为1%,因此,结合名义利率,家庭主观贴现率应为0.99左右。
(15)15以上脉冲反应结果对于关键参数的设定均较为稳健,为节省篇幅,我们将相关分析全部放入附录,有兴趣的读者可向作者索取。
(16)16由于缺乏更细致的产业季度数据,笔者根据Chang et al.(2015)利用第二产业来代表资本密集型,第三产业代表劳动密集型。
(17)17事实上,一个更为可行的做法是利用财政政策时间序列(例如政府的公共投资、公共消费支出等)识别财政政策不确定性(财政政策冲击二阶矩的冲击)。然而,由于统计口径等问题,中国财政政策时间序列的质量并不理想。
[2]Alm,J.,“Uncertain Tax Policies, Individual Behavior, and Welfare”,American Economic Review, 1988,78(1), 237—245.
[3]Andreasen, M., J. Fernández-Villaverde, and J. Rubio-Ramirez, “The Pruned State-Space System for Non-linear DSGE Models: Theory and Empirical Applications”, NBER Working Paper,No.18983, 2013.
[4]Arellano, C., Y. Bai, and P. Kehoe, “Financial Frictions and Fluctuations in Volatility”, NBER Working Paper,No.22990, 2016.
[5]Bachmann R., and C. Bayer,“Investment Dispersion and the Business Cycle”, The American Economic Review, 2014, 104(4),1392—1416.
[6]Bachmann R., and C. Bayer, “‘Wait-and-See’ Business Cycles?”, Journal of Monetary Economics, 2013, 60(6), 704—719.
[7]Baker S.,N. Bloom, and S.Davis,“Measuring Economic Policy Uncertainty”, The Quarterly Journal of Economics, 2016, 131(4),1593—1636.
[8]Barsky R., and E. Sims,“News Shocks and Business Cycles”, Journal of Monetary Economics, 2011, 58(3),273—289.
[9]Basu S., and B. Bundick,“Uncertainty Shocks in a Model of Effective Demand”, Econometrica, 2017, 85(3),937—958.
[10]Bi, H.,E.Leeper, and C. Leith, “Uncertain Fiscal Consolidations”,The Economic Journal, 2013,123(566),F31—F63.
[11]Bizer D., and K.Judd, “Taxation and Uncertainty”,The American Economic Review, 1989, 79(2), 331—336.
[12]Bloom, N.,“Fluctuations in Uncertainty”,The Journal of Economic Perspectives, 2014, 28(2), 153—175.
[13]Bloom, N., M. Floetotto, N. Jaimovich, I.Saporta-Eksten, and S.Terry, “Really Uncertain Business Cycles”,NBER Working Paper,2015,NO.18245.
[14]Bloom, N.,“The Impact of Uncertainty Shocks”, Econometrica, 2009, 77(3),623—685.
[15]Born, B., and J. Pfeifer, “Policy Risk and the Business Cycle”, Journal of Monetary Economics, 2014, 68, 68—85.
[16]Calvo, Guillermo A., “Staggered Prices in a Utility-Maximizing Framework”, Journal of Monetary Economics 1983,12(3), 383—398.
[17]Chang, C., K. Chen, D. Waggoner, and T. Zha, “Trends and Cycles in China's Macroeconomy”, In NBER Macroeconomics Annual 2015, Volume 30.University of Chicago Press, 2015.
[18]Chari, V., P. Kehoe, and E. McGrattan,“Are Structural VARs with Long-Run Restrictions Useful in Developing Business Cycle Theory?”,Journal of Monetary Economics, 2008, 55(8), 1337—1352.
[19]Chen, K., P.Higgins, D.Waggoner, and T. Zha,“China Pro-Growth Monetary Policy and Its Asymmetric Transmission”,National Bureau of Economic Research, No.22650, 2016.
[20]Christiano, L., M.Eichenbaum, and C.Evans,“Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy”,Journal of political Economy, 2005, 113(1),1—45.
[21]Christianom, L., R. Motto, and M.Rostagno,“Risk Shocks”,The American Economic Review, 2014, 104(1),27—65.
[22]陈守东、杨东亮,“我国财政支出不确定性对居民消费影响的实证研究”,《数量经济技术经济研究》,2009年第9期,第119—133页。
[23]Fernandez, R., and D. Rodrik. “Resistance to Reform: Status Quo Bias in The Presence of Individual-Specific Uncertainty”, The American Economic Review, 1991, 1146—1155.
[24]Fernández-Villaverde, J., P. Guerrón-Quintana, and J.Rubio-Ramírez,“Risk Matters: The Real Effects of Volatility Shocks”,The American Economic Review, 2011, 101(6),2530—2561.
[25]Fernández-Villaverde, J., P. Guerrón-Quintana, K. Kuester, and J.Rubio-Ramírez,“Fiscal Volatility Shocks and Economic Activity”,The American Economic Review, 2015, 105(11),3352—3384.
[26]Francis, N., M. Owyang, J. Roush, and R. DiCecio,“A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks”,Review of Economics and Statistics, 2014, 96(4), 638—647.
[27]Funke, M.,“Inflation in China: Modelling a Roller Coaster Ride”,Pacific Economic Review, 2006, 11(4), 413—429.
[28]Gali, J., J. Lopez-Salido, and J. Valles,“Understanding the Effects of Government Spending on Consumption”,Journal of the European Economic Association, 2007, 5(1), 227—270.
[29]Gilchrist, S., J. Sim, and E. Zakraj?ek,“Uncertainty, Financial Frictions, and Investment Dynamics”,NBER Working Paper No.20038, 2014.
[30]Greenwood, J., Z. Hercowitz, and G. Huffman,“Investment, Capacity Utilization, and the Real Business Cycle”,The American Economic Review, 1988, 78(3),402—417.
[31]Hassett, K., and G. Metcalf, “Investment with Uncertain Tax Policy: Does Random Tax Policy Discourage Investment?”, NBER Working Paper No.4780, 1994.
[32]韩立岩、牟晖、王哲兵,“市政债券的风险识别与控制策略”,《管理世界》,2005年第2期,第58—66页。
[33]贾倩、孔祥、孙铮,“政策不确定性与企业投资行为——基于省级地方官员变更的实证检验”,《财经研究》,2013年第2期,第81—91页。
[34]金雪军、钟意、王义中,“政策不确定性的宏观经济后果”,《经济理论与经济管理》,2014年第2期,第17—26页。
[35]King, R., C. Plosser, and S.Rebelo,“Production, Growth and Business Cycles: I. The Basic Neoclassical Model”,Journal of monetary Economics, 1988, 21(2—3), 195—232.
[36]Ladner, P., and S. Rebelo,“Can News about the Future Drive the Business Cycle?”,The American Economic Review, 2009, 99(4), 1097—1118.
[37]Leduc, S., and Z.Liu,“Uncertainty Shocks are Aggregate Demand Shocks”,Journal of Monetary Economics, 2016, 82, 20—35.
[38]Li, B., and Q.Liu,“On the Choice of Monetary Policy Rules for China: A Bayesian DSGE Approach”,China Economic Review, 2017, 44,166—185.
[39]刘尚希,“财政风险: 从经济总量角度的分析”,《管理世界》,2005年第7期,第31—39页。
[40]刘尚希,“财政风险:一个分析框架”,《经济研究》,2003年第5期,第23—31页。
[41]Melitz, M.,“The Impact of Trade on Intra-industry Reallocations and Aggregate Industry Productivity”,Econometrica, 2003, 71(6), 1695—1725.
[42]Pastor, L., and P.Veronesi,“Uncertainty about Government Policy and Stock Prices”,The Journal of Finance, 2012, 67(4),1219—1264.
[43]Ramey, V.,“Identifying Government Spending Shocks:It's All in the Timing”,The Quarterly Journal of Economics, 2011, 126(1),1—50.
[44]Rodrik, D.,“Policy Uncertainty and Private Investment in Developing Countries”, Journal of Development Economics, 1991, 36(2),229—242.
[45]Song, Z., K. Storesletten, and F.Zilibotti,“Growing Like China”,The American Economic Review, 2011, 101(1),196—233.
[46]Uhlig, H.,“Do Technology Shocks Lead to a Fall in Total Hours Worked?”,Journal of the European Economic Association, 2004, 2(2—3), 361—371.
[47]Wang P, and Y.Wen,“Another Look at Sticky Prices and Output Persistence”,Journal of Economic Dynamics and Control, 2006, 30(12). 2533—2552.
[48]王必达、张忠杰,“中国刘易斯拐点及阶段研究——基于31个省际面板数据”,《经济学家》,2014年第7期。
[49]王伟同,“中国人口红利的经济增长‘尾效’研究——兼论刘易斯拐点后的中国经济”,《财贸经济》,2012年第11期,第14—20页。
[50]吴化斌、许志伟、胡永刚、鄢萍,“消息冲击下的财政政策及其宏观影响”,《管理世界》,2011年第9期,第26—39页。
[51]吴敬琏,《中国增长模式抉择》。上海:上海远东出版社,2006年。
[52]许志伟、薛鹤翔、罗大庆,“融资约束与中国经济波动——新凯恩斯主义框架内的动态分析”,《经济学》(季刊),2010年第3期。
[53]朱军、许志伟,“财政分权、地区间竞争与中国经济波动——多级政府框架下的动态一般均衡分析”,《经济研究》。2018年第1期。
[54]Zhang, W.,“China's Monetary Policy: Quantity versus Price Rules”,Journal of Macroeconomics, 2009, 31(3), 473—484.
(1)1http://news.xinhuanet.com/politics/2014-02/22/c_126175088.htm
(2)2在实证部分,本文将详细讨论该方法较之传统意义上的短期约束(Choleski分解)和长期约束(Blanchard-Quah分解)的主要优势。
(3)3以上结果对于货币数量规则仍然稳健。
(4)4关于异质性模型中的extensive-margin effect,可参考异质性厂商经典文章Melitz(2003)中的讨论。
(5)5需要注意的是,Basu and Bundick(2017)在一个标准的新凯恩斯DSGE模型中讨论了生产率的不确定性冲击,而非宏观政策的不确定性。
(6)6具体见网站:https://www.frbatlanta.org/cqer/research/china-macroeconomy.aspx。
(7)7数据可以从网站http://www.policyuncertainty.com/下载。
(8)8该政策不确定性主要反映了公众对经济形势判断偏差性、政府承诺不一致、官员更替、增税减支改革的落实、税制改革的落地时间、财政货币政策搭配模式的难以识别等。
(9)9我们用4种标准来选择滞后阶数。其中,Hannan-Quinn Criterion和Schwarz Criterion为滞后2阶,Akaike Info Criterion和Final Prediction Error建议为5阶。由于中国时间序列并不是很长,我们选择滞后阶数较少的2阶。基本结果对滞后5阶非常稳健。为讨论一致,我们在随后的VAR估计中,均选择滞后2阶。
(10)10我们所用的产出数据为去除价格因素的季度工业增加值,总消费是去除消费价格指数的季度家庭消费,总投资是去除投资价格指数的季度商业投资[见Chang et al.(2015)的详细讨论]。
(11)11为节省篇幅,这里我们并没有报告具体结果,有兴趣的读者可向作者索取。
(12)12为表述方便,本文模型中关于实际货币余额的决策时间点采用了Wang and Wen(2006)中的设置,即当期的货币可以用于支付当期的消费。而许志伟等(2010)中的设置假设当期货币仅能用于下期消费的支付。两者虽然在时间上有差异,但定量上具有非常类似的动态。
(13)13在基准模型中,流动性约束会使得投资在不确定性增大时,反而下降更少。这是由于该约束使得家庭无法通过资本配置渠道有效地对不确定性做出应对。因而,在面临外部冲击时,投资动态较之标准的CIA约束模型更为平滑。同理,当政府降低不确定性时,流动性约束也阻碍了宏观经济通过增加投资的渠道进行复苏。结果显示,本文结果对流动性约束稳健。感谢匿名审稿人关于该点的讨论。
(14)14根据1992第一季度至2013年第三季度的CPI季度数据显示,CPI季度增长率为1%,因此,结合名义利率,家庭主观贴现率应为0.99左右。
(15)15以上脉冲反应结果对于关键参数的设定均较为稳健,为节省篇幅,我们将相关分析全部放入附录,有兴趣的读者可向作者索取。
(16)16由于缺乏更细致的产业季度数据,笔者根据Chang et al.(2015)利用第二产业来代表资本密集型,第三产业代表劳动密集型。
(17)17事实上,一个更为可行的做法是利用财政政策时间序列(例如政府的公共投资、公共消费支出等)识别财政政策不确定性(财政政策冲击二阶矩的冲击)。然而,由于统计口径等问题,中国财政政策时间序列的质量并不理想。
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