expenditures that have the most statistically significant positive effect on growth. The results using this criterion are shown in Tables 5, 6, and 7.

Table 5 (OLS with annual data) reinforce the results found with Criterion (1) regarding the budget surplus and macroeconomic stability (inflation), and also shows positive and statistically significant coefficients for both categories of expenditures, productive and unproductive (lower values), with the highest significance level of 1 percent for productive expenditure and 10 percent for unproductive expenditure.

Table 6 (OLS and SURE with 3-year averages) shows, however, that unproductive expenditures do not have any impact on growth anymore, which could indicate that the effects observed in Table 5 are just transitional and do not affect the medium-term path of growth. But productive expenditures are still statistically significant at the highest 1 percent level.

Table 7 (GMM) confirms that **in a dynamic panel, only productive expenditures have a positive effect on growth** that is statistically relevant at 1 percent level. Unproductive expenditures also have a positive coefficient, but the results are not statistically significant.

The results obtained using this criterion, using the OLS methodology and three-year average data, are also presented in Table 8 in comparison with the results found by the same authors who defined the productive-unproductive _a priori_ expenditure classification (Bleaney, Kneller, and Glemmell in 2001)<sup>63</sup> using also OLS but with five-year average data. We find some similar findings, notably **the statistical relevance of the productive expenditures ratio** with a positive coefficient<sup>64</sup> .

Finally, the results reported above seem to present a strong linear relationship between economic growth and productive expenditures. Given this information, we could still ask whether or not this relationship has any nonlinear components. To answer this question, we add a square term of productive expenditures in our regression specification<sup>65</sup> . While the coefficient of the linear term captures the direction of the link between economic growth and productive expenditures, the square term explains whether the link is concave or convex.

The results are presented in Table 9. When we add the nonlinear term in our regression equation, the linear term of productive expenditures still has a positive coefficient and it is statistically significant at 10 percent (down from 1 percent without the nonlinear term).

> 63 Their data set covers twenty-two “developed” countries during 1970-1995.

> 64 Unlike the work done by Bleaney et al., in this paper fiscal revenues are introduced as the sum of tax plus non-tax revenues in the function specification.  No differentiation is made between distortionary and nondistortionary taxation. The main reason is that the focus of this paper is strictly the impact of public spending on growth, and not on how the structure of the tax system affects growth.

> 65 If the coefficient of the square term is positive, it indicates a convex relationship between two variables. It means an increasing slope of the function.  The negative coefficient of the square term indicates a concave relationship between variables, meaning a decreasing slope of the function.

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