per capita growth at the country level and compare the results with previous econometric work based on a similar sectoral classification.

# _Econometric Methods_

Three econometric methods are used (OLS, SURE, and GMM) and their results are then compared<sup>54</sup> . For the selected country sample, the short and medium-term growth impacts of public spending on GDP per capita growth (dependant variable) are analyzed. First, using annual data, the focus is on the short-term effect. Second, the same regressions are run using three-year average data to “smooth out” cyclical effects<sup>55</sup> and the results of both exercises are compared using OLS and SURE methods. Finally, a dynamic panel technique (GMM) is used and the results are compared with those obtained with the static panel regressions (OLS and SURE).

The SURE methodology is a type of ordinary least squares (OLS) specification which can be used to account for various patterns of correlation among the residuals. There are four basic variance structures: period specific heteroskedasticity, contemporaneous covariances, between period covariances, and cross-section specific heteroskedasticity (SURE), which is the one used in this paper. This methodology is used to check whether or not our results with ordinary least square change when we introduced cross-section specific heteroskedasticity, given that in the data set we include countries that are quite different from each other.

Regarding the endogeneity of public spending with respect to growth, first of all we observe that in none of the sample countries (except for Botswana) the size of total government spending as ratio of GDP grew more than the rate of GDP growth during the period of analysis, which may indicate that public spending has contributed to growth more than growth has contributed to increased public spending.

Nevertheless, in the econometric analysis the possible endogeneity of public spending with respect to growth is taken into account when using the three econometric methods. Initially<sup>56</sup> , the lagged values (year t-1) of GDP per capita growth and public spending to GDP ratios are introduced as regressors, in order to isolate the effects of public spending on GDP per capita growth.

Since, as recognized in the literature, this is an imperfect technique, our third econometric method, the GMM dynamic panel method, is used to allow for a more rigorous treatment of the endogeneity of public spending with respect to growth and leads to consistent estimates. GMM is, with no doubt, the best methodology to estimate the empirical

> 54 See Appendix II for a detailed description of the three methods.

> 55 Given the lack of degrees of freedom, it was not feasible to use five-year averages, as is commonly done in cross-country growth regressions.  It should be noted, however, that the use of five-year averages has been criticized as being somewhat arbitrary; there is no strong reason to believe, a priori, that applying a common moving average filter is the correct procedure for extracting the cyclical component of all variables. There is also a potential loss of information that is hard to quantify.

> 56 When using OLS and SURE techniques.

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