firms report easier access to finance in systems with larger foreign bank penetration (as is shown by Clarke et al. 2001, using the 400-firm database mentioned above).

# _Numerical implications_

Drawing from these studies, we may propose an extended set of measures of financial development, combining not only scale and competitive efficiency, but also the presence of these major infastructural preconditions. Unfortunately, a metastudy of the existing literature based on the framework outlined in (1) and (2) above is not altogether straightforward.

For one thing, there does not seem to be any existing discussion in the literature on the policy weights to be assigned to the different components of outturns (the _Wk_ ). Much of the literature seems to proceed as if growth were the only objective, but this surely cannot be so. Aggregate national fluctuations cannot easily be insured, so the second moment must be of some relevance. Likewise the poverty dimension may be important if, as has been suggested by the empirical evidence provided above, some policy approaches are more effective in reducing poverty than others, conditional on growth. Finally, it is likely that growth at the production frontier (attained in advanced economies) has somewhat different determinants than growth that is mainly a convergence to that frontier. If they embody new technology, access by new firms to finance may be even more important for growth at the frontier than away from it. For the present then, the literature does not tell us much about how to value these different components, which we need to do according to equation (2) above.

The second difficulty is a more practical one, namely that the various empirical studies have not all been set up to closely conform with equation (1). Different variables are used on both sides of the equation and so forth. So arriving at an acceptable summary is a task which, though not insurmountable, has not yet been accomplished.

But we can already begin to see whether the composite indicator has the potential to be substantially different from the size-based measures. Could it, for example, result in a considerable re-ordering of the international league table of financial development?

As an initial illustration along these lines, we took the developing countries already examined in the poverty exercise above and assembled data on (i) governance and legal institutions (KKZ and LLSV data) and (ii) regulatory approach (BCL data) and ownership (also from BCL). The same indicators are not always available for all countries, indeed, for only 17 of the poverty countries are they all available. Table 8 (panel A) shows that pairwise the indicators are not highly correlated among themselves or with the size and activity measures (Table 8 shows the correlations on the basis of the common sample, those based on the much larger maximal samples are broadly similar). Even when aggregated in an ad hoc manner<sup>26</sup> to three sub-aggregates the correlations are all moderate (panel B). This suggests that re-ranking is quite possible depending on the weights used.

> 26 Essentially by normalizing and adding together, with algebraic sign corresponding to the literature’s consensus on the direction of impact on growth.

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