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The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model

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Abstract

We estimate a quantile structural vector autoregressive model for the Euro area to assess the real effects of uncertainty shocks in expansions and recessions using monthly data covering the period of 1999:02–2016:05. Domestic and foreign (US) uncertainty shocks hitting during recessions are found to produce a relatively overall stronger negative impact on output growth than in expansions, with US shocks having more pronounced effects. Inflation, in general, is unaffected from a statistical perspective. Our results tend to suggest that policymakers need to implement state-dependent policies, with stimulus policies being more aggressive during recessions—something we see from our results in terms of stronger declines in the interest rate during bad times.

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Notes

  1. In this regard the reader is referred to the theoretical works of Bloom (2009), Fernández-Villaverde et al. (2011, 2015), Gourio (2012), Leduc and Liu (2013), Johannsen (2013), Mumtaz and Zanetti (2013), Nakata (2013), Basu and Bundick (2014), Bloom et al. (2014), Christiano et al. (2014), Floetotto et al. (2014), and Carriero et al. (2015). While the size of the impact of uncertainty on macroeconomic variables have been analysed empirically in Alexopoulos and Cohen (2009), Bachmann and Bayer (2011), Knotek II and Khan (2011), Stock and Watson (2012), Bachmann et al. (2013), Colombo (2013), Benati (2013), Jones and Olson (2013, 2015), Born and Pfeifer (2014), Alessandri and Mumtaz (2014), Caggiano et al. (2014a, b, 2016), Foerster (2014), Furlanetto et al. (2014), Gilchrist et al. (2013), Kang et al. (2014), Karnizova and Li (2014), Nodari (2014), Pellegrino (2018), Schüler (2014), Bali et al. (2015), Carriero et al. (2015), Castelnuovo et al. (2015), Gupta and Jooste (2017), Istrefi and Piloiu (2015), Jurado et al. (2015), Ludvigson et al. (2015), Mecikovsky and Meier (2015), Rossi and Sekhposyan (2015), Baker et al. (2016), Balcilar et al. (2017, 2016a, b), Caldara et al. (2016), Cheng et al. (2016), Jones and Enders (2016), Mumtaz et al. (2016), Rossi et al. (2016), Scotti (2016), Segnon et al. (2016), Shin and Zhong (2016), and Creal and Wu (2017).

  2. Studies by Aastveit et al. (2017) and Balcilar et al. (2017) are also somewhat related in this regard. While these studies did not directly look at the spillover effect of the uncertainty of the US economy on other major economies, they were more concerned about the domestic effectiveness of monetary policy in the wake of low and high levels of US uncertainty.

  3. Sin (2015) depicted significant impact of Chinese uncertainty on Taiwan and Hong Kong.

  4. In this regard, it must be mentioned that Cheng et al. (2016) analysed the impact of US partisan conflict, besides US uncertainty, on the Euro area macroeconomic variables, and showed that partisan conflict has a relatively stronger effect than economic uncertainty. In addition, Jones and Olson (2015) were concerned more with the impact of financial market uncertainty of the US economy on Japan and the UK, and not necessarily the spillover of aggregate macroeconomic uncertainty like what we do in this paper (see below in the data segment for details on our measure of uncertainty), or what Colombo (2013), Caggiano et al. (2016), Cheng et al. (2016), and Stockhammar and Österholm (2016) did.

  5. While here we concentrate only on the Euro area, our results based on QSVAR models for the US and UK confirm the findings of the earlier studies on the asymmetric effect of uncertainty; i.e., domestic uncertainty has a relatively stronger influence during recessions than expansions. For the UK, US uncertainty also shows an asymmetric impact. Complete details of these results are available upon request from the authors.

  6. Note that shadow interest rate data is also available for Japan based on the work of Krippner (2012, 2013), who in turn derives these rates based on a two-factor model for also the Euro area, UK and US. However, Wu and Xia (2016) indicate that the three-factor term structure model fits the data better than the corresponding model with two factors. Hence, we decided to leave Japan out, as Wu and Xia (2016) does not provide estimates for the shadow rate of Japan. So in this paper, we concentrate formally on the Euro area, and also the UK and US, with results of the latter two countries not reported explicitly in the paper, but available upon request from the authors.

  7. Though it does not hold in our case, since we only have one economic activity variable, namely output, quantiles of which we condition our analysis on; but in a QSVAR, in the presence of more than one variable capturing economic activity, multiple variables can be simultaneously used as a measure of business cycle indicators. This, however, is not a possibility in other parametric nonlinear models, where we need to specify a particular variable as an indicator of business cycle.

  8. Chuliá et al. (2017) used bivariate QSVAR models to analyze the impact of domestic and US uncertainty on equity markets of both mature and emerging countries.

  9. Azzimonti (2015), Caldara and Iacoviello (2016), and Manela and Moreira (2017) use similar news-based approach to come up with measures on partisan conflict, geopolitical risks and news implied volatility (NVIX).

  10. Further details on the EPU measure for the US can be found here: http://www.policyuncertainty.com/us_monthly.html, while that of the Euro area is available here: http://www.policyuncertainty.com/europe_monthly.html.

  11. Based on the suggestion of an anonymous referee, we also ordered the Euro area EPU after the US EPU. Given this ordering of the variables, our results were both qualitatively and quantitatively similar (barring the first period for inflation, industrial production growth and interest rate) to those reported below following a shock to the domestic EPU. Complete details of these results are available upon request from the authors.

  12. When we looked at confidence bands, we observed that the impacts are statistically significant only for output and interest rates, but not the inflation, following a statistically significant increase in the domestic EPU.

  13. When we looked at the confidence bands, this effect was statistically significant.

  14. Spillovers of EPU across countries have been studied by various papers in detail [see, Gupta et al. (2016) for a detailed literature review in this regard].

  15. A variance decomposition analysis showed that the cumulative effect (over horizons 0 to 10-month-ahead) of US EPU on output growth at τ = 0.25, 0.50 and 0.75 is 14.65, 13.40, and 13.63% respectively, which were consistently higher (especially at τ = 0.25) when we compared to the corresponding values of 3.20, 13.07 and 9.87% respectively following a shock to the domestic EPU. These results, complete details of which are available upon request from the authors, basically confirm the finding from the impulse response analyses.

  16. Our results are qualitatively similar if we use τ = 0.1 and 0.9 to characterize the recessionary and expansionary regimes respectively. Complete details of these results are available upon request from the authors.

  17. Based on the suggestions of an anonymous referee, we conducted two additional robustness checks: (a) first, we included the shadow rate of the US [derived from Wu and Xia (2016)] and ordered it before the US EPU, and; (b) second, we included changes in net exports (as it was non-stationary in levels) of the Euro area (derived from the OECD’s MEIs database) and ordered it before the domestic EPU. Under (b), results were qualitatively and quantitatively the same, as a shock to US EPU failed to have a statistically significant impact on changes in net exports (though it was positive), while under (a), our results were qualitatively similar, but the severity of the effects were marginally reduced, since an increase in US EPU, resulted in a statistically significant decline in the US shadow rate, thus nullifying to some extent the negative influence of the US EPU shock on the Euro area variables. Complete details of these results are available upon request from the authors.

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Acknowledgements

We would like to thank an anonymous referee for many helpful comments. However, any remaining errors are solely ours.

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Authors and Affiliations

  1. Department of Economics, University of Pretoria, Pretoria, South Africa

    Rangan Gupta

  2. Department of Accountancy, Finance and Economics, Huddersfield Business School, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK

    Chi Keung Marco Lau

  3. College of Business Administration, University of Nebraska at Omaha, 6708 Pine Street, Omaha, NE, 68182, USA

    Mark E. Wohar

  4. School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK

    Mark E. Wohar

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  1. Rangan Gupta
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Gupta, R., Lau, C.K.M. & Wohar, M.E. The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model. Empirica 46, 353–368 (2019). https://doi.org/10.1007/s10663-018-9400-3

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