unpredictability of aid flows is likely to be reflected in the macroeconomic and fiscal environment of the country. Hence, we take the ratio of ODA net disbursements to GDP. Likewise, the relief obtained under the Heavily Indebted Poor Countries (HIPC) initiative could push governments to allocate more resources from the debt service to public investment. Hence, a dummy variable to control for such allocation changes is introduced. This takes the value one if the country is in the period between the decision point and the completion point of the original or enhanced HIPC initiative, zero otherwise.

Along the same reasoning, the ratio of central government total revenues and grants as a percentage of GDP is introduced. Increased revenues are likely to affect positively the levels of public investment (Tanzi and Davoodi, 1997) and, at the same time, increase the volatility of public investment if the government tends to spend the new money. However, if the government is conservative and builds up a buffer to implement counter-cyclical fiscal policy, the effect on the volatility could turn out to be negative.

On the one hand, natural resources rich countries are likely to foster the investment activity both by building up infrastructure to further exploit and generate profits from such richness, and by diversifying the productive structure. On the other hand, the price fluctuations affect quantities sold and may eventually be reflected in the volatility of public investment. Unfortunately, data restrictions do not allow controlling for the overall natural resource endowments and the ratio of oil exports to GDP is typically used to proxy it to some extent. Nonetheless, oil is just one albeit important of the resources a country may be endowed with and there are cases of countries that are resource rich but do not export the commodity. In order to take into account these considerations, we employ the sum of the rent from energy depletion (crude oil, natural gas, hard coal, and lignite) and rent from oil and minerals (bauxite, copper, gold, iron, lead, nickel, phosphate, silver, tin, zinc). Each rent is computed as production volume multiplied by the difference between international market price and average unit production cost.<sup>18</sup>

# **4.2. Empirical Strategy**

While Knack and Keefer (2007) use an averaged cross-section to investigate the impact of institutional quality on public investment, we employ the system GMM estimator developed by Arellano and Bover (1995) and Blundell and Bond (1998).

Our methodology can be considered superior as it exploits the longitudinal dimension and, as specified by Roodman (2006), jointly addresses several potential econometric problems since it is specifically designed for situations with (1) few time periods and many individuals; (2) a linear functional relationship; (3) a single left hand side variable that is dynamic, depending on its own past realizations; (4) independent variables that are not strictly exogenous (possibly correlated with past and current realizations of the error); (5) unobserved heterogeneity at country level; (6) and heteroskedasticity and autocorrelation within individuals, but not across them.

Given our dataset spanning 144 countries over 25 years, a typical persistence in the investment variable, some of the explanatory variables (income and price in particular) that may be endogenous with public investment, a likely presence of specific country fixed effects, and idiosyncratic errors that are heteroskedastic and correlated within but not across individuals, the system GMM is instrumental in addressing all these issues.

To test hypothesis (i) we adopt the same specification as in Keefer and Knack (2007):

> 18 Oil exports have been used as a robustness check.

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