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The Impact of US Uncertainty Shocks on Small Open Economies

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Abstract

In this paper, we investigate the impact of US uncertainty shocks on GDP growth in nine small open economies: Australia, Canada, Denmark, Finland, Iceland, New Zealand, Norway, Sweden and the United Kingdom. We compare the impact of two types of shocks: i) stock market volatility shocks and ii) policy uncertainty shocks. Using quarterly data from 1986Q1 to 2016Q1, this issue is analysed using Bayesian VAR models. Our results suggest that policy uncertainty seems to matter more than stock market volatility. Stock market volatility shocks appear to robustly have significant effects on Danish GDP growth. Policy uncertainty shocks, on the other hand, reliably lowers GDP growth in all five Nordic countries in a statistically significant manner. Statistically significant effects of policy uncertainty shocks on the Anglo-Saxon countries in our sample are harder to establish and are, in our preferred specification, only found for the United Kingdom.

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Notes

  1. See, for example, Leland (1968), Bernanke (1983), Ferderer (1993), Bloom (2009) and Gilchrist et al. (2014).

  2. See, for example, Leahy and Whited (1996), Bloom et al. (2007), Bloom (2009) and Adler et al. (2016).

  3. For empirical applications relying on policy uncertainty, see, for example, Aastveit et al. (2013), Colombo (2013), Klößner and Sekkel (2014) and Stockhammar and Österholm (2016a).

  4. Additional examples of various spillover effects include Österholm and Zettelmeyer (2008), Bagliano and Morana (2010), Erten (2012) and Hájek and Horváth (2016).

  5. This has shown to be useful from a forecasting perspective; see, for example, Beechey and Österholm (2010).

  6. See, for example, Doan (1992) and Villani (2009) for details.

  7. See, for example, Cogley and Sargent (2001), Ribba (2006) and Österholm (2012).

  8. The reason for this is that the VXO is available starting 1986Q1 and the VIX is only available from 1990Q1. We argue that the longer time series is to be preferred. It can be noted that the correlation between the VXO and the VIX for the common sample is 0.99 (at the quarterly frequency).

  9. Data on the unemployment rate, CPI and Fed funds rate were supplied by the National Institute of Economic Research. GDP data were supplied by the OECD. Data on the VXO were sourced from the FRED database at the Federal Reserve Bank of St. Loius. Policy uncertainty data were downloaded from http://www.policyuncertainty.com/.

  10. These values were suggested already by Taylor (1993) in his groundbreaking paper on monetary policy rules.

  11. This stands in contrast to studies where the shocks are given a structural interpretation, such as aggregate demand shocks, aggregate supply shocks, wage setting shocks and monetary policy shocks. See Blanchard (1989) for an example and Amisano and Giannini (1997) for a more general discussion of identification in VAR models.

  12. This is based on a fairly commonly employed principle where slow-moving variables appear before fast-moving ones. The recursive structure for identification was also used in Sims (1980) original article on VARs.

  13. The standard deviation of the VXO shock is 5.1 units.

  14. The standard deviation of the policy uncertainty shock is 15.2 units.

  15. This parameter of exogenity tightness is set to 0.001.

  16. These data were supplied by the OECD.

  17. Results are not reported but are available from the authors upon request.

  18. Having moved to year-on-year growth rates, we have to change the steady state priors for the variables concerned. We set the 95% prior interval to (2, 3) in all countries. For US CPI inflation the corresponding interval is given by (0.5, 3.5).

  19. The irreversibility of investments and precautionary saving are two standard explanations; see, for example, Leland (1968) and Bernanke (1983).

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Authors and Affiliations

  1. National Institute of Economic Research, Box 3116, 103 62, Stockholm, Sweden

    Pär Stockhammar

  2. School of Business, Örebro University, 701 82, Örebro, Sweden

    Pär Österholm

Authors
  1. Pär Stockhammar
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  2. Pär Österholm
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Corresponding author

Correspondence to Pär Stockhammar.

Additional information

We are grateful to two anonymous referees for comments on this paper.

Appendix

Appendix

Table 1 Steady-state priors for the Bayesian VARs
Full size table
Fig. 5
figure 5

Impulse response functions of BVAR model with variables given by Eqs. (1) and (2). Note: Shocks in columns, responses in rows. Black line is the median and the coloured band is the 90% confidence band. Quarters are given on the horizontal axis

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Fig. 6
figure 6

Impulse response functions of BVAR model with variables given by Eqs. (1) and (3). Note: Shocks in columns, responses in rows. Black line is the median and the coloured band is the 90% confidence band. Quarters are given on the horizontal axis

Full size image
Fig. 7
figure 7

Impulse response functions of BVAR model with variables given by Eqs. (1) and (7). Note: Shocks in columns, responses in rows. Black line is the median and the coloured band is the 90% confidence band. Quarters are given on the horizontal axis

Full size image
Fig. 8
figure 8

Impulse response functions of BVAR model with variables given by Eqs. (1) and (8). Note: Shocks in columns, responses in rows. Black line is the median and the coloured band is the 90% confidence band. Quarters are given on the horizontal axis

Full size image
Fig. 9
figure 9

Impulse response functions of BVAR model with variables given by Eqs. (1) and (7)/(8). Estimated effects on GDP growth in the Nordic countries. Note: Percentage points on the vertical axis and quarters on the horizontal axis. Black line is the median and the coloured band is the 90% confidence band

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Fig. 10
figure 10

Impulse response functions of BVAR model with variables given by Eqs. (1) and (7)/(8). Estimated effects on GDP growth in the Anglo-Saxon countries. Note: Percentage points on the vertical axis and quarters on the horizontal axis. Black line is the median and the coloured band is the 90% confidence band

Full size image
Fig. 11
figure 11

Impulse response functions. Estimated effects on GDP growth in the Nordic countries of BVAR model using year-on-year growth rates for GDP and CPI. Note: Percentage points on the vertical axis and quarters on the horizontal axis. Black line is the median and the coloured band is the 90% confidence band

Full size image
Fig. 12
figure 12

Impulse response functions. Estimated effects on GDP growth in the Anglo-Saxon countries of BVAR model using year-on-year growth rates for GDP and CPI. Note: Percentage points on the vertical axis and quarters on the horizontal axis. Black line is the median and the coloured band is the 90% confidence band

Full size image

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Stockhammar, P., Österholm, P. The Impact of US Uncertainty Shocks on Small Open Economies. Open Econ Rev 28, 347–368 (2017). https://doi.org/10.1007/s11079-016-9424-x

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