Uncertainty Shocks, Transmission Mechanisms and Synergistic Policy Responses in the Context of Major Crises

Deng Chuang, Wu Chao, Zhao Ke

Studies of International Finance ›› 2022, Vol. 0 ›› Issue (2) : 22-33.

Studies of International Finance ›› 2022, Vol. 0 ›› Issue (2) : 22-33.

Uncertainty Shocks, Transmission Mechanisms and Synergistic Policy Responses in the Context of Major Crises

  • Deng Chuang1, Wu Chao2, Zhao Ke2
Author information +
History +

Abstract

As one of the frontier issues in current economics research, behavioral decision making under uncertainty shocks is an important basis for understanding a series of issues ranging from individual behavior to economic cycle fluctuations, and is also a key factor that cannot be ignored in the construction of economic-financial theory models. The world today is undergoing a major change unprecedented in a century, and the domestic and international environment is becoming increasingly complex, with economic and financial crises occurring from time to time. The uncertainty unique to major crisis events poses a huge challenge to the stable development of the global economy. It is true that clarifying the impact mechanism of uncertainty and policy synergy under major crisis events has become the key to enhancing the ability to deal with systemic risk prevention and control and to relieving economic downward pressure.
Against this background, in terms of empirical evidence and based on high-dimensional economic and financial monthly data for the period 2002—2020, this paper adopts a high-dimensional factor model to achieve the separation of economic (supply and demand) and financial uncertainty identification. Following that, on the basis of in-depth analysis of the occurrence and linkage mechanisms of uncertainty shocks under different crisis events, the paper further uses a TVP-VAR model to systematically examine the impact dynamics of uncertainty shocks on China's macroeconomy under major crisis events and obtain relevant empirical facts. On the theoretical side, a nonlinear DSGE model consistent with the above empirical facts is constructed and used as a basis to simulate the transmission mechanism of uncertainty shocks and effective policy response options.
It is found that, uncertainty shocks under major crisis events are characterized by multidimensionality and heterogeneity. Demand uncertainty(financial uncertainty) tends to play a dominant role in economic (financial) crisis events, but secondary uncertainty is equally alarming. Economic and financial uncertainties will have completely different impacts due to the differ-ences in their transmission mechanisms, and demand and supply uncertainties are mainly manifested as cost-driven shocks, while financial uncertainties appear as contractionary shocks in the short term. In dealing with multidimensional uncertainty shocks, the coordination of monetary and fiscal policies can create space for fiscal policy and enhance policy sustainability, especially the combination of increased fiscal spending, debt management and mixed monetary policy has outstanding effect-tiveness in regulating the economy, stabilizing finance and controlling debt. These research results can provide a powerful grip for economic stabilization and risk prevention and control on the one hand, and have important theoretical and practical signif- icance for improving and optimizing the macro policy regulation system on the other hand. These research results can provide a powerful starting point for stabilizing the economy and risk prevention on the one hand, and on the other hand have important theoretical and practical significance for improving and optimizing the macro-policy control system.

Key words

Demand Uncertainty / Supply Uncertainty / Financial Uncertainty / Non-Linear DSGE Model / Policy Coordination

Cite this article

Download Citations
Deng Chuang, Wu Chao, Zhao Ke. Uncertainty Shocks, Transmission Mechanisms and Synergistic Policy Responses in the Context of Major Crises[J]. Studies of International Finance, 2022, 0(2): 22-33

References

[1] 邓创,吴超. 中国经济、金融不确定性的交互影响动态与宏观经济效应分析[J]. 系统工程理论与实践,2021(7):1625-1639
[2] 蒋海,吴文洋,韦施威. 新冠肺炎疫情对全球股市风险的影响研究——基于 ESA 方法的跨市场检验[J]. 国际金融研究,2021 (3):3-13
[3] 李卓,包益红. 新冠疫情下经济不确定性之不确定研究[J]. 经济评论,2020 (4):46-54
[4] 刘金全,隋建利,庞春阳. 我国货币政策有效性测度——基于太阳黑子与 (不) 确定性因素视角的思考[J].数量经济研究,2010 (1):8-29
[5] 刘喜和,李良健,高明宽. 不确定条件下我国货币政策工具规则稳健性比较研究[J]. 国际金融研究,2014 (7):7-17
[6] 赵文佳,梁燚焱. 我国经济不确定性度量及其非线性经济效应[J]. 经济科学,2020(4):5-18
[7] 朱军,李建强,张淑翠. 财政整顿、“双支柱”政策与最优政策选择[J]. 中国工业经济,2018 (8):24-41
[8] 庄子罐,崔小勇,赵晓军. 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[J]. 管理世界,2016 (11):20-31+187
[9] Antonakakis N,Gabauer D. Refined Measures of Dynamic Connectedness Based on TVP-VAR[R]. MPRA Paper,2017,No. 78282
[10] Basu S,Bundick B.Uncertainty Shocks in a Model of Effective Demand[J]. Econometrica,2017,85(3):937-958
[11] Bianchi F,Kung H,Tirskikh M. The Origins and Effects of Macroeconomic Uncertainty[R]. NBER Working Papers,2018,No.25386
[12] Bloom N,Floetotto M,Jaimovich N.Really Uncertain Business Cycles[J]. Econometrica,2018,86(3):1031-1065
[13] Caldara D,Fernández-Villaverde J,Rubio-Ramirez J F,et al. Computing DSGE Models with Recursive Prefer-ences and Stochastic Volatility[J]. Review of Economic Dynamics,2012,15(2):188-206
[14] Cho D,Han Y,Oh J,et al. Optimal Monetary Policy and Uncertainty Shocks[R]. Dynare Working Papers,2020, No. 61
[15] Choi S,Shim M.Financial vs. Policy Uncertainty in Emerging Market Economies[J]. Open Economies Review, 2019,30(2):297-318
[16] Diks C,Panchenko V.A New Statistic and Practical Guidelines for Nonparametric Granger Causality Testing[J]. Journal of Economic Dynamics and Control,2006,30(9):1647-1669
[17] Fernández-Villaverde J. Guerrón-Quintana P A. Uncertainty Shocks and Business Cycle Research[J]. Review of Economic Dynamics,2020,37(1):118-146
[18] Gertler M,Karadi P.A Model of Unconventional Monetary Policy[J]. Journal of Monetary Economics,2011,58(1):17-34
[19] Huang Z,Tong C,Qiu H,et al.The Spillover of Macroeconomic Uncertainty between the US and China[J]. Economics Letters,2018,171:123-127
[20] Jurado K,Ludvigson S C,Ng S.Measuring Uncertainty[J]. American Economic Review,2015,105(3):1177-1216
[21] Lan H,Meyer-Gohde A.Solving DSGE Models with a Nonlinear Moving Average[J]. Journal of Economic Dynamics and Control,2013,37(12):2643-2667
[22] Leduc S,Liu Z.Uncertainty Shocks Are Aggregate Demand Shocks[J]. Journal of Monetary Economics,2016,82(9):20-35
[23] Ludvigson S C,Ma S,Ng S. Uncertainty and Business Cycles:Exogenous Impulse or Endogenous Response?[R].NBER Working Paper,2016,No. 21803
[24] Nakajima J,Kasuya M,Watanabe T.Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model
for the Japanese Economy and Monetary Policy[J]. Journal of the Japanese and International Economies,2011,25(3):225-245
[25] Oh J,Rogantini P A. Macro Uncertainty and Unemployment Risk[R]. Economics Working Papers,2019, No.2

63

Accesses

0

Citation

Detail

Sections
Recommended

/