Reconstruction and dynamic dependence analysis of global economic policy uncertainty

Yue Liu; Yuhang Zheng; Benjamin M Drakeford; Yue Liu; Yuhang Zheng; Benjamin M Drakeford

doi:10.3934/QFE.2019.3.550

Quantitative Finance and Economics

2019, Volume 3, Issue 3: 550-561. doi: 10.3934/QFE.2019.3.550

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Research article

Reconstruction and dynamic dependence analysis of global economic policy uncertainty

1.
School of Economics and Management, Hunan Institute of Technology, 421001, Hengyang, P. R. China
2.
School of Finance, Guangdong University of Finance & Economics, Guangzhou 510320, China
3.
Collaborative Innovation Development Center of Pearl River Delta Science & Technology Finance Industry, Guangdong University of Finance & Economics, Guangzhou 510320, China
4.
Portsmouth Business School, University of Portsmouth, Portsmouth, PO13DE, United Kingdom

Received: 11 August 2019 Accepted: 09 September 2019 Published: 12 September 2019
JEL Codes: D81, E02

In this paper,we use a generalized dynamic factor model to reconstruct the global economic policy uncertainty index developed by Davis (2016),and we investigate the dynamic dependence structure between global and national economic policy uncertainty using the time-varying copula approach. Based on this novel index,we find that global economic policy uncertainty has overall experienced a "Low-High-Low" trend during the period April 2003 to November 2018, and there are spikes in connection with notable political events and developments around the world. The results also suggest that there generally exists positive dependence between global and national economic policy uncertainty,and the magnitude of dependency in developed countries is much higher than that in developing countries. In addition,the degree of international economic policy incoordination has increased significantly after the 2008–2009 global financial crisis.
- global economic policy uncertainty,
- generalized dynamic factor model,
- time-varying copula,
- reconstruction,
- dynamic dependence
Citation: Yue Liu, Yuhang Zheng, Benjamin M Drakeford. Reconstruction and dynamic dependence analysis of global economic policy uncertainty[J]. Quantitative Finance and Economics, 2019, 3(3): 550-561. doi: 10.3934/QFE.2019.3.550

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Abstract

In this paper,we use a generalized dynamic factor model to reconstruct the global economic policy uncertainty index developed by Davis (2016),and we investigate the dynamic dependence structure between global and national economic policy uncertainty using the time-varying copula approach. Based on this novel index,we find that global economic policy uncertainty has overall experienced a "Low-High-Low" trend during the period April 2003 to November 2018, and there are spikes in connection with notable political events and developments around the world. The results also suggest that there generally exists positive dependence between global and national economic policy uncertainty,and the magnitude of dependency in developed countries is much higher than that in developing countries. In addition,the degree of international economic policy incoordination has increased significantly after the 2008–2009 global financial crisis.

References

[1]	Aloui R, Aïssa MSB, Nguyen DK (2013) Conditional dependence structure between oil prices and exchange rates: a copula-GARCH approach. J Int Money Financ 32: 719–738. doi: 10.1016/j.jimonfin.2012.06.006
[2]	Anderson BDO, Braumann A, Derstler M (2018) Identification of generalized dynamic factor models from mixed-frequency data. IFAC-PapersOnline 51: 1008–1013. doi: 10.1016/j.ifacol.2018.09.062
[3]	Baker SR, Bloom N, Davis SJ (2016) Measuring economic policy uncertainty. Q J Econ131: 1593–1636.
[4]	Balli F, Uddin GS, Mudassar H, et al. (2017) Cross-country determinants of economic policy uncertainty spillovers. Econ Lett 156: 179–183. doi: 10.1016/j.econlet.2017.05.016
[5]	Barigozzi M, Hallin M (2016) Generalized dynamic factor models and volatilities: recovering the market volatility shocks. Econ J 19: C33–C60.
[6]	Basnet HC, Sharma SC, Vatsa P (2015) Monetary policy synchronization in the asean-5 region: an exchange rate perspective. Appl Econ 47: 100–112. doi: 10.1080/00036846.2014.962228
[7]	Bildirici ME, Badur MM (2018) The effects of oil prices on confidence and stock return in china, India and Russia. Quant Financ Econ 2: 884–903. doi: 10.3934/QFE.2018.4.884
[8]	Bloom N, Bond S, Van Reenen J (2007) Uncertainty and investment dynamics. Rev Econ Stud 74: 391–415. doi: 10.1111/j.1467-937X.2007.00426.x
[9]	Boero G, Silvapulle P, Tursunalieva A (2011) Modelling the bivariate dependence structure of exchange rates before and after the introduction of the euro: a semi‐parametric approach. Int J Financ Econ 16: 357–374. doi: 10.1002/ijfe.434
[10]	Bomberger WA (1996) Disagreement as a measure of uncertainty. J Money Credit Bank 28: 381–392. doi: 10.2307/2077981
[11]	Brogaard J, Detzel A (2015) The asset-pricing implications of government economic policy uncertainty. Soc Sci Electronic Publishing 61: 3–18.
[12]	Caggiano G, Castelnuovo E, Figueres JM (2017) Economic policy uncertainty and unemployment in the United States: A nonlinear approach. Econ Lett 151: 31–34. doi: 10.1016/j.econlet.2016.12.002
[13]	Castelnuovo E, Lim G (2017) Pellegrino G.A short review of the recent literature on uncertainty. Aust Econ Rev 50: 68–78.
[14]	Cekin SE, Pradhan AK, Tiwari AK, et al. (2019) Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas. Q Rev Econ Financ.
[15]	Christou C, Gupta R (2019) Forecasting Equity Premium in a Panel of OECD Countries: The Role of Economic Policy Uncertainty. Q Rev Econ Financ.
[16]	Dai PF, Xiong X, Zhou WX (2019) Visibility graph analysis of economy policy uncertainty indices. Phys A 531: 121748. doi: 10.1016/j.physa.2019.121748
[17]	Davis SJ (2016) An index of global economic policy uncertainty. NBER Working paper, No. w22740.
[18]	Engel J, Wahl M, Zagst R (2017) Forecasting turbulence in the Asian and European stock market using regime-switching models. Quant Financ Econ 2: 388–406.
[19]	Fang L, Chen B, Yu H, et al. (2018) The importance of global economic policy uncertainty in predicting gold futures market volatility: A GARCH‐MIDAS approach. J Futures Mark 38: 413–422. doi: 10.1002/fut.21897
[20]	Fang LB, Yu HH, Li L (2017) The effect of economic policy uncertainty on the long-term correlation between U.S. stock and bond markets. Econ Model 66: 139–145.
[21]	Fontaine I, Didier L, Razafindravaosolonirina J (2017) Foreign policy uncertainty shocks and US macroeconomic activity: evidence from China. Econ Lett 155: 121–125. doi: 10.1016/j.econlet.2017.03.034
[22]	Forni M, Hallin M, Lippi M, et al. (2017) Dynamic factor models with infinite-dimensional factor space: Asymptotic analysis. J Econometrics 199: 74–92. doi: 10.1016/j.jeconom.2017.04.002
[23]	Forni M, Hallin M, Lippi M, et al. (2000) The Generalized Dynamic Factor Model: Identification and Estimation. Rev Econ Stat 82: 540–554. doi: 10.1162/003465300559037
[24]	Forni M, Lippi M (2001) The generalized dynamic factor model: representation theory. Econometric Theory 17: 1113–1141. doi: 10.1017/S0266466601176048
[25]	Ghirelli C, Gil M, Pérez JJ, et al. (2019) Measuring economic and economic policy uncertainty, and their macroeconomic effects: the case of Spain. Working Paper, No.1905, Bank of Spain.
[26]	Granville B, Mallick S, Ning Z (2011) Chinese exchange rate and price effects on g3 import prices. J Asian Econ 22: 427–440. doi: 10.1016/j.asieco.2011.07.002
[27]	Gulen H, Ion M (2016) Policy uncertainty and corporate investment. Rev Financ Stud 29: 523–564.
[28]	Guo P, Zhu HM, You WH (2018) Asymmetric dependence between economic policy uncertainty and stock market returns in G7 and BRIC: A quantile regression approach. Financ Res Lett 25: 251–258. doi: 10.1016/j.frl.2017.11.001
[29]	Huang WL, Lin WY, Ning SL (2018) The effect of economic policy uncertainty on China's housing marke. North Am J Econ Financ.
[30]	Ji Q, Liu BY, Nehler H, et al. (2018) Uncertainties and extreme risk spillover in the energy markets: A time-varying copula-based CoVaR approach. Energy Econ 76: 115–126. doi: 10.1016/j.eneco.2018.10.010
[31]	Jin X (2018) Downside and upside risk spillovers from China to Asian stock markets: A CoVaR-copula approach. Financ Res Lett 25: 202–212. doi: 10.1016/j.frl.2017.10.027
[32]	Junttila J, Vataja J (2018) Economic policy uncertainty effects for forecasting future real economic activity. Econ Syst 42: 569–583. doi: 10.1016/j.ecosys.2018.03.002
[33]	Kayalar DE, Küçüközmen CC, Selcuk-Kestel AS (2017) The impact of crude oil prices on financial market indicators: copula approach. Energy Econ 61: 162–173. doi: 10.1016/j.eneco.2016.11.016
[34]	Kim W (2019) Government spending policy uncertainty and economic activity: US time series evidence. J Macroecon 61: 103124. doi: 10.1016/j.jmacro.2019.103124
[35]	Liow KH, Huang YT, Song J (2019) Relationship between the United States housing and stock markets: some evidence from wavelet analysis. North Am J Econ Financ 50: 101033. doi: 10.1016/j.najef.2019.101033
[36]	Mallick SK, Sousa RM (2013) The real effects of financial stress in the eurozone. Int Rev Financ Anal 30: 1–17. doi: 10.1016/j.irfa.2013.05.003
[37]	Meinen P, Roehe O (2017) On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area. Eur Econ Rev 92: 161–179. doi: 10.1016/j.euroecorev.2016.12.002
[38]	Mertzanis C (2018) Complexity, big data and financial stability. Quant Financ Econ 2: 637–660. doi: 10.3934/QFE.2018.3.637
[39]	Min A, Czado C (2010) Bayesian inference for multivariate copulas using pair-copula constructions. J Financ Econometrics 8: 511–546. doi: 10.1093/jjfinec/nbp031
[40]	Oh DH, Patton AJ (2018) Time-varying systemic risk: Evidence from a dynamic copula model of cds spreads. J Bus Econ Stat 36: 181–195. doi: 10.1080/07350015.2016.1177535
[41]	Olbrys J, Majewska E (2017) Asymmetry effects in volatility on the major European stock markets: the EGARCH based approach. Quant Financ Econ 1: 422–427.
[42]	Oscar Bernal O, Jean-Yves Gnabo JY, Grégory Guilmin G (2016) Economic policy uncertainty and risk spillovers in the Eurozone. J Int Money Financ 65: 24–45. doi: 10.1016/j.jimonfin.2016.02.017
[43]	Ostry JH, Ghosh AR (2016) On the obstacles to international policy coordination. J Int Money Financ 67: 25–40. doi: 10.1016/j.jimonfin.2015.06.008
[44]	Patton AJ (2012) A review of copula models for economic time series. J Multivar Anal 110: 4–18. doi: 10.1016/j.jmva.2012.02.021
[45]	Patton AJ (2006) Modelling asymmetric exchange rate dependence. Int Econ Rev 47: 527–556. doi: 10.1111/j.1468-2354.2006.00387.x
[46]	Rehman UM (2018) Do oil shocks predict economic policy uncertainty? Phys A 498: 123–136. doi: 10.1016/j.physa.2017.12.133
[47]	Stock JH, Watson MW (2002) Forecasting Using Principal Components From a Large Number of Predictors. J Am Stat Assoc 97: 1167–1179. doi: 10.1198/016214502388618960
[48]	Yu H, Fang L, Sun W (2018) Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market. Phys A 505: 931–940. doi: 10.1016/j.physa.2018.03.083
[49]	Yu M, Song J (2018) Volatility forecasting: global economic policy uncertainty and regime switching. Phys A 511: 316–323. doi: 10.1016/j.physa.2018.07.056
[50]	Zhou ZB, Fu ZY, Jiang Y, et al. (2019) Can economic policy uncertainty predict exchange rate volatility? New evidence from the GARCH-MIDAS model. Financ Res Lett.

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