Oil shocks and the volatility of BRICS and G7 markets: SVAR analysis

Figures & data

Table 1. Descriptive statistics and preliminary tests of the data and oil market structural shocks

	Mean	Median	Maximum	Minimum	Std. Dev.	Skewness	Kurtosis	Jarque Bera	ADF	PP
Brazil	0.000331	0.000000	0.134409	−0.157659	0.016630	−0.416494	11.95012	18,448.98***	−10.26184***	−9.157282***
Russia	0.000336	0.000615	0.239504	−0.252787	0.020824	−0.525757	19.38189	61,529.45***	−8.190367***	−7.980448***
India	0.000331	0.000364	0.164225	−0.137404	0.014559	−0.434800	13.01505	23,074.77***	−10.32040***	−10.03677***
China	0.000273	8.06E-05	0.140361	−0.128323	0.016959	−0.052750	9.104952	8512.624***	−6.947999***	−6.705186***
South Africa	0.000323	0.000104	0.072291	−0.094763	0.012707	−0.356266	7.462783	4663.510***	−10.35302***	−9.572099***
France	6.28E-06	0.000176	0.103625	−0.131500	0.013949	−0.236319	9.609720	10,026.52***	−9.669959***	−9.582293***
Germany	4.85E-06	0.000345	0.111255	−0.133411	0.014393	−0.200368	9.190132	8785.883***	−8.950103***	−9.250681***
Italy	−0.000132	6.10E-05	0.109855	−0.187908	0.014878	−0.635019	13.31758	24,674.96***	−11.04385***	−10.04553***
UK	1.06E-05	4.03E-05	0.092649	−0.115034	0.011706	−0.343696	11.27768	15,753.30***	−9.434477***	−9.272733***
USA	0.000191	0.000331	0.110426	−0.129220	0.012317	−0.426207	14.59363	30,856.71***	−10.07889***	−9.653221***
Canada	0.000123	0.000381	0.118016	−0.133340	0.011662	−0.869141	20.21643	68,369.16***	−9.179663***	−8.576040***
Japan	2.52E-05	0.000000	0.130618	−0.104351	0.013338	−0.315867	9.694070	10,322.87***	−9.426080***	−9.757095***
Oil supply shock	60.88783	57.20364	133.8800	16.55000	25.75300	0.431506	2.306126	280.0446***	−0.144303	0.187991
Aggregate demand shock	10.22367	−1.079380	191.3788	−158.6990	71.10985	0.507702	2.698947	256.1628***	−3.84837***	−2.55759
Oil specific demand shock	7197.129	5840.333	12,860.00	3974.000	2336.489	0.891032	2.457341	792.5146***	−3.211809**	−2.231554

Note: This table reports the descriptive statistics and preliminary tests for the used data. *** Indicates statistical significance at the 1% level. ADF, and PP denote the statistics of Augmented David et al. (1981), and Peter et al. (1988) unit root test, respectively. ^{***, **,*,} indicate respectively the stationary level at 1%, 5% and 10%.

Table 2. GJR-GARCH model estimates

GJR-GARCH ${\sigma }_{\mathbf{t}}^2=\omega +\left(\alpha +\gamma {\mathbf{I}}_{\left[{\epsilon }_{\mathbf{t}-1<0}\right]}\right){\epsilon }_{\mathbf{t}-1}^2+{\beta \sigma }_{\mathbf{t}-1}^2$
	Coefficients
	$\omega$	$\alpha$	$\gamma$	$\beta$
Brazil	6.63E-06***	0.019312**	0.078182	0.902433***
Russia	3.68E-06***	0.074505***	−0.018346	0.891279***
India	3.40E-06***	0.031059***	0.098276	0.882820***
China	2.80E-06***	0.032032***	0.032034	0.924471***
South Africa	3.37E-06***	0.016464**	0.102296	0.899507***
France	1.98E-06***	−0.017613***	0.209375	0.909095***
Germany	2.08E-06***	−0.014439**	0.184838	0.915450***
Italy	1.61E-06***	−0.003284	0.143515	0.922331***
UK	1.60E-06***	−0.008902	0.184676	0.904874***
USA	1.55E-06***	−0.013803*	0.224569	0.895168***
Canada	1.01E-06***	0.021468**	0.098848	0.904236***
Japan	3.84E-06 ***	0.020019**	0.124941	0.884225***

Note: Table 2 presents the estimates of GJR-GARCH model (Glosten et al., 1993) that is presented as follows: ${\sigma }_{\mathrm{t}}^2=\omega +\left(\alpha +\gamma {\mathrm{I}}_{\left[{\epsilon }_{\mathrm{t}-1<0}\right]}\right){\epsilon }_{\mathrm{t}-1}^2+{\beta \sigma }_{\mathrm{t}-1}^2$. *,**,*** indicate respectively the significance level at 1%, 5% and 10%.

Figure 1. The impulse response of global oil price to structural oil shocks (11 February 2000 to 12 February 2021).Note: Figure 1 shows the impulse response of global oil price to structural oil shocks for 20 periods.

Figure 2. Responses of returns volatility to structural shocks (11 February 2000 to 12 February 2021).Notes: Figure 2 shows the estimated response of the daily conditional volatility of BRICS and G7 markets returns to daily structural shocks between 11 February 2000 and 12 February 2021. They are based on a recursive-design wild bootstrap with 2000 replications (Gonc¸ & Kilian, 2004).

Table 3. Variance decomposition- returns volatility

Groups	Markets	Oil supply shock	Aggregate demand shock	Oil-specific demand shock	Volatility
BRICS group	Brazil	0.006	0.015	0.314	36.293
	Russia	0.145	0.278	0.252	66.027
	India	0.026	0.001	0.207	67.775
	China	0.156	0.148	0.092	47.573
	South Africa	0.028	0.002	0.491	31.004
G7 group	France	0.056	0.018	0.492	42.724
	Germany	0.041	0.011	0.313	60.230
	Italy	0.069	0.010	0.203	59.938
	UK	0.012	0.020	0.296	77.948
	USA	0.005	0.017	0.403	27.033
	Canada	0.004	0.017	0.382	34.008
	Japan	0.026	0.052	0.057	34.446

Note: Table 3 shows the percentage contribution of a shock to the variability of stock market volatility for BRICS and G7 markets. The table compares the variance decomposition of the structural VAR model applied to each BRICS and G7 countries.

Table 4. Variance decomposition- returns volatility for different lags

Groups	Markets	L =1				L =5				L =10				L =15
		OSS	ADS	SDS	Vol	OSS	ADS	SDS	Vol	OSS	ADS	SDS	Vol	OSS	ADS	SDS	Vol
BRICS group	Brazil	0.006	0.015	0.314	36.293	0.423	0.010	1.534	42.797	1.027	0.011	1.248	42.517	0.681	0.019	0.983	40.410
	Russia	0.145	0.278	0.252	66.027	0.880	0.922	1.712	67.912	0.747	0.945	1.106	60.184	1.445	0.719	1.471	65.370
	India	0.026	0.001	0.207	67.775	0.036	0.056	0.324	66.377	0.511	0.036	0.285	47.062	0.606	0.056	0.352	48.628
	China	0.156	0.148	0.092	47.573	0.555	0.494	0.306	54.632	0.234	0.508	0.227	37.190	0.532	0.237	0.449	37.868
	South Africa	0.028	0.002	0.491	31.003	0.221	0.097	1.768	37.904	1.030	0.058	1.413	37.659	0.924	0.114	1.122	35.648
G7 group	France	0.056	0.018	0.492	42.724	0.958	0.079	2.402	54.658	1.421	0.052	1.781	59.998	0.841	0.067	1.503	53.069
	Germany	0.041	0.011	0.313	60.230	0.767	0.104	1.734	65.382	1.114	0.085	1.508	65.758	0.565	0.070	1.211	64.164
	Italy	0.069	0.010	0.203	59.938	0.920	0.067	1.308	64.962	1.689	0.066	1.224	63.517	1.009	0.048	0.837	60.231
	UK	0.012	0.020	0.296	77.948	0.261	0.023	1.230	72.904	0.626	0.021	0.931	68.190	0.350	0.030	0.744	72.525
	USA	0.005	0.017	0.403	27.033	0.396	0.060	2.264	28.672	0.893	0.048	1.945	33.647	0.469	0.052	1.226	33.299
	Canada	0.004	0.016	0.382	34.008	0.609	0.029	1.913	44.582	1.386	0.057	1.354	46.034	1.038	0.097	0.829	42.923
	Japan	0.026	0.052	0.057	34.446	0.148	0.088	0.122	45.457	0.069	0.164	0.109	38.172	0.078	0.119	0.125	41.641

Note: Table 4 shows the percentage contribution of a shock (OSS: Oil Supply Shock; ADS: Aggregate Demand Shock; SDS: Specific Demand Shock) to the variability of stock market returns volatility for BRICS and G7 markets. The table compares the variance decomposition of the structural VAR model applied to each BRICS and G7 countries for different lags.Conclusions and implications

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