percentage of banked adults for a total of 154 countries. We use their predictions for those countries for which data on explanatory variables in equation (1) were not available, and end up with 154 countries for which there are predictions or actual data on the percentage of formally banked households. The results indicate that, on average, half the world is unbanked. The regional breakdown of these predictions shows that Sub-Saharan Africa (SSA) and South Asia (SA) are the two regions with the lowest percentage of banked individuals, with medians of 12 and 22 percent, respectively. Latin America and the Caribbean (LAC), East Asia and Pacific (EAP), and Middle East and North Africa (MENA) follow with medians of 40, 42 and 42 percent, respectively. In the developing world, Europe and Central Asia (ECA) is the region with the highest percentage of banked households on average, with a median of 50 percent. Highincome OECD and non-OECD countries have 91 percent of households banked on average.<sup>3</sup> The next step is to calculate the number of unbanked adults in the world. Kendall _et al._ (2010) predict that approximately 2.7 billion adults in the developing world and 160 million adults in the developed countries are unbanked using data from _Financial Access 2009_ as well as other sources. As their methodology differs, the predictions based on the methodology presented above are not comparable to their numbers. Hence, we then redo the prediction exercise with the methodology of Kendall _et al._ using updated data from _Financial Access 2010_ to understand if there is a major change in the number of unbanked adults. In doing so, we also update the predictions of Kendall _et al._ by expanding their coverage. In the end, using the methodology of Kendall _et al._ , we arrive at two sets of predictions: one for 2008, and the other for 2009, both complemented with additional data from a variety of sources (see Table 3) and for the same sample of 191 countries.

Kendall _et al_ . (2010) use a variety of econometric models to predict the number of commercial bank deposit accounts around the world. Table 4 provides the estimation results for the two sets of predictions mentioned above, which are almost identical to the results reported by Kendall _et al._ using _Financial Access 2009_ data. We then use these models to predict the number of commercial bank deposit accounts for those countries for which data are unavailable. For the rest of the non-bank financial institution types, no estimation was made as the number of comparable observations at the country level is not sufficient. In addition, not all countries have different types of non-bank financial institutions. Instead, _Financial Access_ data for both years are complemented by other data sources (see Table 3), and the number of deposit accounts for each institution type for each reporting country is counted. The total number of deposit accounts across all institutional types within each country is then calculated by adding up the numbers for each institutional type. This prediction exercise yields the total number of deposit accounts in each country. However, the indicator of interest is the total number of banked (or unbanked) adults (see Table 3). Hence, following Kendall _et al._ , we convert the number of deposit accounts

> 3 See Map 1.1 in CGAP and World Bank (2010), pp.4.

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