share of exports of each commodity in the total commodity export basket during the period 20072014.<sup>9</sup> Commodity exports are defined in terms of SITC 4th revision at 4 digits from the World Integrated Trade Solution (WITS) database.

While estimating the model, some of the data are transformed to yield stationary series. Real GDP, oil and commodity prices, and real effective exchange rates, originally in levels, are converted into quarter-on-quarter growth rates. Any residual linear trends in those growth rates are removed. During the sample period used in this paper, the U.S. interest rate and the EMBI exhibit a downward trend. We use first differences of these two series. The aggregate model uses aggregate GDP growth rates for various country groups. Those are calculated as the GDP weighted growth rates of all the countries in a given group. The GDP weights are calculated using the annual current GDP (in US$) series from the IMF’s World Economic Outlook (October 2016) database.

# 3 Results

We present two main sets of results. First, we discuss growth spillovers from aggregate EM7 and compare those with spillovers originating from the G7. Second, we analyze spillovers from each of the individual EM7 to gauge the relative importance of these economies as a source of spillovers.

## 3.1 Spillovers from EM7

We begin by presenting growth spillovers from EM7 using the aggregate model that features aggregate EM7 as the spillover source. Spillovers are analyzed in two different dimensions. First, we show how an exogenous growth shock in EM7 spills over to other economies using impulse responses. We also calculate impulse responses due to a growth shock in G7 to assess the relative size of spillovers from EM7. Second, we perform variance decompositions that show the relative contributions of growth shocks in EM7 vis-à-vis other shocks in the VAR system in explaining business cycle fluctuations in spillover destinations.

Figure 2 presents the impulse responses of model variables to an exogenous growth shock in EM7 that increases its growth by 1 percentage point on impact.<sup>10</sup> These are highly persistent shocks as they translate into an increase of about 2.7 percentage points in cumulative terms in EM7 growth at the end of three years. Their effect on growth in other EFM is sizeable on impact and they gain momentum over time, with maximum cumulative effect towards the end of three years. On impact, growth in other EFM rises by about 0.3 percentage point in response to the shock, while the cumulative impact at the end of three years is about 0.9 percentage point. These effects are statistically significant at the 2 standard deviation significance level (corresponding to the 16-84 percent confidence bands) which is often used in the literature.

In contrast, the estimated impact on G7 growth is, on average, modest and statistically insignificant. This is partly by construction since G7 growth, ordered first in the VAR, is assumed to be relatively exogenous to EM7 growth. The weak spillover effect on G7 growth may also reflect their net oil-importing status. As net oil importers, G7 economies tend to suffer from the higher oil prices associated with a rise in EM7 growth (Figure 2E). On balance, global growth —calculated as

> 9 The trade weights are based on 2007-14 averages rather than the full sample period (2000-2015) because the number of missing observations rises considerably before 2007 and after 2014.

> 10 Throughout this paper, we present impulse responses due to positive growth shocks. Since the VAR model used in the paper is linear, the distinction between positive and negative growth shocks is, however, trivial.

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