Each _(i, j)_ element of As measures the respective effect of an one-unit increase of εm,j on Xj,m+s , where i, j ε{1, 2} in this case. For example, assuming there is a shock to εm,1 (the first element of εm), the effect on the j<sup>th</sup> variable is given by the first column and j<sup>th</sup> element of I2, A1, A2, etc. An impulse response function hence plots the dynamic response of Xj,m+s to an impulse in X1,m. Crucially, here these can be interpreted as orthogonalized impulse response functions, since the covariance matrices Σ for all countries have zero offdiagonals, i.e. error terms are contemporaneously uncorrelated. Thus any given shock to an error term εm,j does not have a simultaneous effect on other error terms. In the context of this study, the impulse response functions plot the dynamic response of industrial production to a one-unit realized volatility shock (Figure 5). Following Enders (2010), for clarity of interpretation the impulse response functions are displayed for levels<sup>9</sup> .

Strikingly, in all countries industrial production responds negatively to an unexpected positive volatility shock (ceteris paribus). Notably, this includes both net oil importers and exporters. The negative effects on economic activity are the strongest in the second month after the shock – with the exception of Malaysia (first month). These impulse responses are found to be statistically significant. However, positive rebound effects (third month) in Germany, S.Korea and India are associated with low t-ratios. Overall it is confirmed that effects on economic activity do not persist: the system absorbs a realized volatility shock within twelve months. This also implies that the VAR-processes meet the stability condition.

|-0.0006<br>-0.0004<br>-0.0002<br>0.0000<br>0.0002<br>0.0004|USA|-0.002<br>-0.001<br>0.000<br>0.001<br>0.002<br>0.003|Germany<br>-0.001<br>0.000<br>0.001<br>0.002|Japan|
|---|---|---|---|---|
|-00012<br>-0.0010<br>-0.0008||-0005<br>-0.004<br>-0.003|-0003<br>-0.002||
|.|1 2 3 4 5 6 7 8 9 101112|.|1 2 3 4 5 6 7 8 9 101112<br>.|1 2 3 4 5 6 7 8 9 101112|
|0006<br>-0.005<br>-0.004<br>-0.003<br>-0.002<br>-0.001<br>0.000<br>0.001<br>0.002<br>0.003<br>0.004|S.Korea|0006<br>-0.005<br>-0.004<br>-0.003<br>-0.002<br>-0.001<br>0.000<br>0.001<br>0.002|Malaysia<br>0007<br>-0.006<br>-0.005<br>-0.004<br>-0.003<br>-0.002<br>-0.001<br>0.000<br>0.001<br>0.002<br>0.003<br>0.004<br>0.005|India|
|-.|1 2 3 4 5 6 7 8 9 101112|-.|1 2 3 4 5 6 7 8 9 101112<br>-.|1 2 3 4 5 6 7 8 9 101112|

**Figure 5.** Impulse Response Functions for IP. An ‘Impulse’ is defined as Cholesky one S.D. innovation in RV of domestic oil prices. Dotted lines indicate the ±2 S.E. interval, based on standard errors of the estimated model.

Following Lee et al. (1995) and Jones et al. (2004), it is possible to approximate the total impulse response of industrial production to a realized volatility shock, with the accumulated impulse response over twelve months (cf. Table 6.). As Awerbuch and Sauter (2005) summarize, standard literature estimates the US economy to contract by approximately 0.5% following a 10% oil price increase. The accumulated IRF however suggests a mere 0.021% contraction following a 10% increase in oil price volatility. This discrepancy is best understood by considering a specific example: From 2008m01 to 2008m7 the US real oil price increased by 30.1% from $86.3 to $123.5. This corresponds to a 1.5% GDP contraction according to standard literature. However, in the same period the realized volatility measure increased by a factor 15, which would be associated with a 3.2% contraction of US Industrial Production according to the accumulated impulse response functions. In Malaysia realized volatility increased by a factor 12.5 in the same period – implying a 10.1% contraction of industrial production. In light of this drastic contraction, it is important to bear in mind that national output in Malaysia depends strongly on oil revenues: the state owned oil and gas company _Petronas_ accounted for 40% of government revue in 2008 (CIA, 2011).

> 9 Furthermore, all series are normalized by dividing them through their respective standard errors.

10