Resource abundance: A curse or blessings?

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It seems that a country endowed with larger quantities of natural resources has an advantage and (other conditions being similar) has to grow faster than resource poor countries. This is not exactly the case, however, Between 1960 and 1990 the per capita incomes of resource poor countries grew two to three times faster than the per capita income of resource abundant countries, and the gap in the growth rates appears to widen with time (Sachs and Warner, 1999; Auty, 2001). This surprising phenomenon became a subject of intensive research, both empirical and theoretical. A large number of papers have been published in recent years supporting the “resource curse” thesis and effects that may inhibit growth in resource rich economies. Several recent papers, however (Alexeev and Conrad, 2005; Stijns, 2005; Brunnschweiler, 2006), question the mere existence of the “resource curse” and make it necessary to reconsider the hypotheses about the impact of resource abundance on economic growth.

Even without rigorous calculations, it is obvious that not all resource rich countries failed. “Thirty years ago, Indonesia and Nigeria both dependent on oil had comparable per capita incomes. Today, Indonesia’s per capita income is four times that of Nigeria. A similar pattern holds true in Sierra Leone and Botswana. Both are rich in diamonds. While Botswana averaged 8.7% annual economic growth over the past thirty years, Sierra Leone plunged into civil strife.” (Stiglitz, 2004). Norway, where large oil deposits were detected in the seventies, was able to avoid Dutch Disease consequences (Gylfason, 2001). Moreover, Norway increased its PPP GDP per capita very significantly, leaving behind its neighbours, and almost catching up with the USA.

Thus, the relationship between resource abundance and economic growth is not clear-cut; it could be either positive or negative. It is also possible that resource abundance has no significant impact on economic growth, in the absence of other complementary factors. As a matter of fact, searching for growth promoting factors remains largely illusive.

Information obtained from empirical investigation shows that resource abundant countries have on average:

• lower budget deficits;

• Lower inflation;

• higher foreign exchange reserves;

• higher inflows of FDI;

• lower domestic fuel prices;

• higher investment/GDP ratio;

• lower income inequality.

However, resource abundance is also associated with

• higher RER;

• distortions of domestic prices;

• high energy intensity;

• weaker institutions, if they were poor to begin with;

• slower accumulation of human capital.

Thus, there seem to be both growth enhancing and growth retarding factors that can make resource abundance a blessing or a curse. The next section provides a brief review of literature on the role of natural resources in economic growth. Explanations of the tendency for natural resource abundance to immiserise growth and development (the “resource curse”) have traditionally followed four approaches: the “Dutch disease” thesis, the “volatility effect”, the “rent-seeking” effect, and the “false security” or “overconfidence effect”.

Serious methodological concerns are raised regarding the specifications used for estimating the growth effects of one or another growth enhancing variable, in both the cross country and country specific studies. Although most of the studies claim that they are estimating the permanent long run growth effects, there is no distinction between the permanent long run and the transitory short run growth effects of variables. The dependent variable is usually the annual growth rate of GDP (or per capita GDP) in the country specific time series studies or its 5-year average in the cross country studies. Neither of the annual or 5-yearly average growth rates can said to be a good proxy for the unobservable long run growth rate in the steady state. When perturbed, a time span of 5 years is too short for an economy to attain the steady state. Simulations with the closed form solutions show that an economy takes a few decades to converge anywhere close to its steady state. This transition period may be more than 50 years even for small perturbations; see Sato (1963) and Rao (2006). The short run growth rates are also important for the policy makers especially of the developing countries because they persist for more than 5-years and will have permanent level effects (Rao and Cooray, 2009). Many studies also claim that their specifications are based on one or another endogenous growth model, but it is hard to understand how their specifications are derived from the claimed endogenous growth model. Commenting on the unsatisfactory nature of specifications in many such empirical works, Easterly, Levine and Roodman (2004) have noted that “This literature has the usual limitations of choosing a specification without clear guidance from theory, which often means there are more plausible specifications than there are data points in the sample.” Consequently, as found by Durlauf, Johnson, and Temple (2005), the number of potential growth improving variables used in various empirical works is as many as 145. Given these reservations it is hard to select a few uncontroversial control variables to estimate the growth effects of any particular variables such as aid or institutions.



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