country. We also find that the estimated series of the potential GDP growth rate suggests
that the country's growth potential has changed significantly over time, to a significant
extent in association with the underlying rate of growth of real oil prices.4
Finally, we try to establish how important are key economic and policy variables,
other than the real price oil, in the determination of potential GDP growth. We carry out
significance tests for key domestic and foreign variables, such as the public sector deficit
as a proportion of GDP in Venezuela, the real exchange rate, interest rate differentials
vis-a-vis U.S. Treasury bond yields, and real GDP growth in the U.S. From the sample
of economic variables that we have tested, only the interest rate differential was
statistically significant. We find that inclusion of interest rate differentials as an
exogenous variable in the GDP model leads to a moderate improvement in goodness of
fit measures. However, the salient features of the estimated trend and cycle components
remain essentially unchanged, regardless of whether or not interest rate differentials are
included in the GDP model. This leads us to reassert the primacy of real oil prices as the
single most important determinant of potential real GDP in Venezuela.
Stochastic Trend-Cycle Models of GDP and Oil Prices
To implement the proposed structural time series (unobserved components)
modeling framework, we represent real GDP (Yt) as
Y, = YY + ,Ity + ytY + g,
where pY represents a stochastic trend (unit root) component of real GDP, yV[ represents
a stochastic (trigonometric) cycle, and e, is an innovation. Similarly, we represent the
real price of oil as
Pi = ,Pi + P fi p¢,p + 17,
where u,P represents the stochastic trend (unit root) component of the real oil price,
V/ Prepresents a stochastic (trigonometric) cycle, and q, is an innovation. 5 In addition,
we specify these models such that the drift elements of both y,[ and pfP are themselves