Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund

VI. References

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  • Driscoll, John, and Aart Kraay. 1998. “Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data”, The Review of Economics and Statistics, 1998, Vol. 80, issue 4, 549560.

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1

We are grateful to Tim Callen, Bertrand Gruss, Bikas Joshi, Stephane Roudet, and participants at the IMF MCD Discussion Forum for insightful comments. We are also thankful to Brian Hiland and Erik Roos for excellent research assistance. Alexandra Panagiotakopoulou provided excellent editorial support.

2

John C. Williams (President and CEO, Federal Reserve Bank of San Francisco). Remarks at the 2017 Asia Economic Policy Conference: Monetary Policy Challenges in a Changing Global Environment, November 2017 (https://www.frbsf.org/our-district/press/presidents-speeches/williams-speeches/2017/november/when-the-united-states-sneezes/).

3

GCC comprises of the following countries: Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates (UAE).

4

In 2016, oil and gas production constituted on average about 42 percent of total real GDP in GCC countries.

5

As a robustness check, a linear time effect is included as an additional control variable as in IMF, 2013. We find its coefficient to be insignificant, and other results continue to hold.

6

A quadratic time trend is assumed. The key findings are robust to using alternative measures of Saudi Arabia’s non-oil real GDP growth shock, including the HP filtered and Baxter-King filtered logged non-oil real GDP. In fact, these computed alternative measures are highly correlated with our baseline measure. The oil price is the only significant explanatory variable of Saudi Arabia’s non-oil real GDP growth.

7

The endogeneity problem between Saudi non-oil real GDP growth shock and the dependent variable could arise from omitted variable bias. Specifically, there could be other factors that drive the comovements in the non-oil real GDP growth rates across the GCC, but not included in the specification. Lagging Saudi Arabia’s non-oil real GDP growth shock does not entirely solve this endogneity problem, as the growth shocks could be correlated over time. As an additional robustness check, lagged dependent variable is included as an aditional control to capture potential lagged GCC common shocks, and the findings continue to hold.

8

To control for both cross-country and cross-time correlations in the error terms, Driscoll-Kraay (1998) standard errors are computed. The error structure is assumed to be heteroskedastic, autocorrelated, and possibly correlated between panels. Driscoll-Kraay standard errors are robust to very general forms of cross-sectional and temporal dependence, especially when the time dimension becomes large.

9

If government spending is countercyclical to the oil price—governments spend more when oil price is lower—oil price could have ambiguous impact on non-oil output. As a robutness check, we include the lagged real government spending growth rate as an additional control. The key findings remain the same and the coefficient on real government spending is positive and insignificant. β2 is found to be insigificant (Table 2), one reason could be oil prices are correlated with US real interest rate and real growth. When we regress real non-oil growth on only oil prices, the coefficient on oil prices becomes significant.

10

Quarterly GDP data is only available for Bahrain, Qatar, and Saudi Arabia. The time coverage is limited by the starting point of the Saudi quarterly GDP data—2011 Q1—and hence the year-on-year growth rate, which could be used for the regression, only starts in 2012Q2.

11

Prior to 1998, a different methodology was used to measures Oman’s non-oil GDP—it was computed as a residual term of the GDP.

12

As a robustness check for the individual country regression results, the interactions of Saudi Arabia’s non-oil real growth shock and Kuwait, Oman, Qatar, and UAE country dummies are included as additional controls in the panel regression, and we continue to find only a significant Saudi spillover in Bahrain.

13

US variables are lagged to account for the time differences. Additionally, to account for the difference in weekends (weekends are on Friday and Saturday in the GCC), US Friday data is used as RHS variable for the GCC Sunday and Monday LHS variable.

14

In line with Section III, Driscoll-Kraay standard errors are computed to control for both cross-country and cross-time correlations in the error terms for both regressions (2) and (3).

15

In line with Section III, Driscoll-Kraay standard errors are computed to control for both cross-country and cross-time correlations in the error terms for both regressions (2) and (3).

16

There were structural changes in the construction of VIX at end-2003 and the Bahrain stock index in 2005.

17

We also find significant spillover from Dubai stock market—a regional financial center—to the stock markets in the rest of the GCC, and the size of the spillover is half of that from the Saudi stock market. We find no significant spillovers from any other GCC stock market—an evidence that the spillovers from Saudi and Dubai stock markets are not capturing omitted GCC-specific factors.

18

The key findings continue to hold when we use change in bond spreads as the dependent variable.

Saudi’s Growth and Financial Spillovers to Other GCC Countries: An Empirical Analysis
Author: Mr. Olumuyiwa S Adedeji, Mr. Sohaib Shahid, and Ling Zhu