For the purposes of this study, economic activity constitutes the dependent variable and oil price volatility the key regressor. While the overwhelming majority of literature in this field uses quarterly data, this study uses monthly data, in order to capture intra-quarter volatility. Monthly industrial production (IP) is used as a proxy for economic activity, as it is particularly sensitive to changes in input prices (such as oil). Industrial production series and consumer price indices are obtained from the IMF Intl. Finance Statistics database and seasonally adjusted<sup>4</sup> . A ‘global oil price’ is obtained by deflating an average of the WTI and Brent spot market prices (in USD/barrel) using a price index for non-fuel primary commodities. To obtain a more accurate measure of the domestically ‘perceived’ oil price, the global oil price is adjusted for the respective country’s daily $-exchange rate and inflation. Hence, for each country a time series of continuous daily oil prices πd is obtained, with d ε Td, where Td = [June, 1. ,1983; June, 2. ,1983; . . . , ; Jan. ,31. ,2011]; i.e. 7017 observations. It should be noted that adjusting global oil prices for domestic exchange rate and inflation effects is common practice in this literature (see for instance Mork et al., 1994 and Abeysinghe, 2001) – however it should also be pointed out that such domestic oil prices reflect the perceived prices _before_ any kind of policy intervention. In practice oil prices tend to be distorted further through fiscal policies, such as taxes or subsidies (for a detailed discussion of fuel pricing see Kojima, 2013).

<!-- Start of picture text --> 80 Germany 180 160 USA 180 18000 Japan 180<br>7060 (EUR/BBL) 160 140120 (USD/BBL) 160 1600014000 (JPY/BBL) 160<br>50 140 100 140 12000 140<br>4030 120 8060 120 100008000 120<br>20 100 40 100 6000 100<br>4000<br>10 80 20 80 2000 80<br>-100 60 -200 60 -20000 60<br>-20 40 -40 40 -4000 40<br>-30 -60 -6000<br>20 20 20<br>-40 -80 -8000<br>-50 0 -100 0 -10000 0<br>'83 '86 '89 '92 '95 '98 '01 '04 '07 '10 '83 '86 '89 '92 '95 '98 '01 '04 '07 '10 '83 '86 '89 '92 '95 '98 '01 '04 '07 '10<br>160000140000120000 (KRW/BBL) S.Korea 180160 60005000 (INR/BBL) India 180160 450400350 Malaysia (MYR/BBL) 180160<br>100000 140 4000 140 300 140<br>80000 120 120 250 120<br>3000 200<br>60000 100 100 150 100<br>40000 2000<br>20000 80 80 100 80<br>1000 50<br>0 60 60 0 60<br>-20000 40 0 40 -50 40<br>-40000-60000 20 -1000 20 -100-150 20<br>-80000 0 -2000 0 -200 0<br>'83 '86 '89 '92 '95 '98 '01 '04 '07 '10 '83 '86 '89 '92 '95 '98 '01 '04 '07 '10 '83 '86 '89 '92 '95 '98 '01 '04 '07 '10<br><!-- End of picture text -->

**Figure 1.** Domestic real oil prices (left axis) in domestic currency per barrel (e.g. EUR/BBL) and global real oil price (right axis, in USD/BBL).

Figure 1 illustrates that oil prices have undergone considerable fluctuations in the period 1983-2011, with the global nominal oil price varying between US$ 145.7 (03/07/2008) and US$ 8.7 (25/07/1986) with a standard deviation of US$ 25.7<sup>5</sup> . Evidently, there exists a strong correlation between all six domestic pre-tax oil prices, as well as between domestic and global oil prices (cf. Table 1.). This confirms that most of the variation in ‘perceived’ oil prices is indeed due to global oil price shocks, even though domestic effects can play a significant role. The correlation between post-tax oil prices is likely to differ, particularly for countries such as Malaysia with significant fuel subsidy schemes in place.

> 4 Seasonal adjustment using the X-12 method.

> 5 In real terms: max. US$ 86.3 (03/07/2008), min. US$ 11.1 (25/07/1986), S.D. US$ 14.6

4