This paper derives a structural import demand equation and estimates it for a large number of countries, using recent time series techniques that address the problem of nonstationarity. Because the statistical properties of the different estimators have been derived only asymptotically, econometric theory does not offer any guidance when it comes to comparing different estimators in small samples. Consequently, the paper derives the small-sample properties of both the ordinary-least-squares (OLS) and the fully-modified (FM) estimators using Monte Carlo methods. It is shown that FM dominates OLS for both the short- and long-run elasticities.
After skyrocketing over the past decade, commodity prices have remained stable or eased somewhat since mid-2011—and most projections suggest they are not likely to resume the upward trend observed in the last decade. This paper analyzes what this turn in the commodity price cycle may imply for output growth in Latin America and the Caribbean. The analysis suggests that growth in the years ahead for the average commodity exporter in the region could be significantly lower than during the commodity boom, even if commodity prices were to remain stable at their current still-high levels. Slower-than-expected growth in China represents a key downside risk. The results caution against trying to offset the current economic slowdown with demand-side stimulus and underscore the need for ambitious structural reforms to secure strong growth over the medium term.
A Structural import demand equation is derived and estimated for a large number of countries, using recent time-series techniques that address the problem of nonstationarity. The average price elasticity is close to zero in the short run hut is slightly higher than one in the long run. A similar pattern holds for income elasticities: the short-run income elasticities are on average less than 0.5, while the long-run income elasticities are close to 1.5. The paper also analyses the small-sample properties of both the ordinary-least-squares (OLS) and the fully modified (FM) estimators of the short- and long-run elasticities, using Monte Carlo methods.