demand, respectively, as in the benchmark specification. Our identification strategy remains the same as in the benchmark estimation.

Unfortunately, quarterly data for the terms of trade are not available for a large subset of countries in our sample, which somewhat limits our analysis. Nevertheless, we are able to estimate the SVARs for a set of 21 countries, of which 6 are developing economies and 15 developed countries. The set of developing countries includes Brazil, Colombia, Philippines, Thailand, Turkey, and South Africa, while the subsample of developed countries contains Australia, Canada, Germany, Denmark, Finland, France, UK, Hungary, Israel, Italy, Netherlands, Norway, Poland, Sweden, and the US. Of these 21 countries, based on the median cross-country population in our full sample, 5 are classified as small economies and 16 are classified as large economies. There are also just 4 countries without fiscal rule(s) in this subsample, and 17 with the fiscal rule(s). So, clearly, the set of countries with terms of trade data under-represents developing and small economies, as well as economies without the fiscal rule(s).

We re-estimate the individual country SVARs for this subset of countries and summarize the results from the variance decompositions for the overall set of 21 countries, and separately for small vs large countries. Table 7 presents the results for the overall sub-sample.

|**Table 7. Varian**|**ce Decom**|**position of G**|**DP Volatility**<br>|**(with term**|**s of trade)**|**: All countries**|
|---|---|---|---|---|---|---|
||**N**|**mean**|**median**|**p25**|**p75**|**stdev mean**|
|**(log) tot**|21|0.094|0.036|0.018|0.124|0.032|
|**rrate_us**|21|0.113|0.086|0.021|0.168|0.023|
|**(log) gdp_us**|21|0.132|0.083|0.041|0.100|0.037|
|**(log) govexp**|21|0.091|0.084|0.046|0.103|0.018|
|**tby**|21|0.048|0.033|0.010|0.073|0.010|
|**rrate**|21|0.039|0.030|0.009|0.044|0.009|
|**(log) gdp**|21|0.431|0.437|0.330|0.537|0.041|
|**(log) reer**|21|0.051|0.021|0.004|0.075|0.016|

Adding terms of trade to the SVAR regressions raises the contribution of external factors to the overall GDP volatility in our set of countries to 34%. Of these, terms of trade account for about 9% of GDP volatility. Interestingly, the contribution of the two external factors we had in the benchmark specification – the world interest rate and foreign demand – does not change much relative to the benchmark, as each is still responsible for close to 11% of the overall GDP volatility. The remaining 66% is attributable to domestic shocks. The contribution of domestic factors to GDP volatility also did not change much relative to the results for the benchmark sample, with the exception of trade balance, the shocks to which are now contributing 4.8% to the overall GDP volatility (relative to 6.6% in the benchmark specification). The main culprit for the decline in the effects of domestic factors are the shocks to GDP itself, whose effects are now lower at 43%.

Next, we report the variance decomposition results separately for small and large economies and test whether the differences in the role played by different shocks in the two groups are statistically significant. Table 8 reports the results.

25