8 assets are utilized and combined and include both institutional as well as economic factors. In this study, we consider the following institutional indicators, which capture the efficiency with which production can take place; as well as economic indicators, which also capture the efficiency of economic organization:

- a. _institutional development indicators_ - indices on: voice and accountability (VA); political instability and violence (PIV); government effectiveness (GE); regulatory burden (RB); rule of law (RL) and control of corruption (CC). An increase in a given index measures an improvement in the relevant indicator. Hence, they are expected to have a positive impact on income and possibly growth.  These indicators were estimated by Kaufmann, et al, 2005.<sup>7</sup>

- b. _economic indicators_ - trade openness (TOPEN) is calculated as the ratio of exports and imports to GDP (World Bank, 2005b); and the country’s domestic credit to the private sector as proportion of GDP (PCREDIT), which represents private sector investments (Beck, _et al._ , 1999)<sup>8</sup> .

Two methods of incorporating the impact of these institutional and economic indicators were investigated. The first method involved the derivation of residuals from the regression of a nested CES production function. The residuals are the part of income not explained by the wealth components – physical capital, human capital, land resources and energy resources, and are regressed on the identified institutional and economic indicators. By using this method, however, a statistically significant correlation between the residuals and any indicator would imply that relevant variables have been omitted in the estimation of the nested CES production function. Thus, the estimated coefficients of the nested CES production function earlier derived will be biased and inefficient (Greene, 2000). Hence, another method is considered to be more appropriate. The influences of the institutional and economic indicators on income will be incorporated into the efficiency parameter of the production function, _A_ (see Annex).

Depending on the available data for the variables of the nested CES production function, the number of countries drops in the range of 67 to 93 countries. For a given nested CES approach, the reduction is caused by considering only those countries that have non-missing observations for their corresponding dependent and explanatory variables (i.e., _complete case method_ ).<sup>9</sup>

> 7 Data can be obtained from the website: _http://www.worldbank.org/wbi/governance/pubs/govmatters4.html_ . 8 Hnatkovska and Loayza (2004) use openness and credit as a measure of financial depth, which they find to have a positive impact on growth. Data for this indicator can be obtained from the following website: _http://www.worldbank.org/research/projects/finstructure/database.htm_ .

> 9 An “imputation method” was tried to fill the missing values for some of the countries to keep all 208 countries in the estimation. Most of the results, however, were not found to be reasonable.  For example, the imputed value of physical capital for a low income country turned out to be too high compared to the average value of physical capital of its income group.  Hence, the imputation method was not used since it poses more problems in the estimates than using the _complete case method_ .