2.5 points on the 1-7 scale) is associated with an increase in the probability of graduating of about 2 percentage points. Results on _Institutional Capacity_ and other variables are affected very little by this substitution of Polity indicators for Freedom House.

It could be argued that “institutions” should be limited to a narrower set most directly relevant for economic development, and that political institutions may influence graduation decisions only indirectly, if at all.<sup>20</sup> Accordingly, in regression (iii) we exclude the Polity indicators as well as _Political Freedoms_ . The main results from Table 3 still hold. In particular, the coefficients on income and institutional ratings (ICRG) remain statistically significant and of a similar magnitude. In fact, the ICRG coefficient rises somewhat, presumably because of the substantial correlation between the ICRG and political ratings.

Regression (iv) of Table 5 includes tax revenue as a share of GDP. This measure is often called “tax effort” and interpreted as an indicator of administrative capacity (see for example Brautigam, Fjelstad, and Moore 2008). Greater tax effort may encourage graduation through a second channel, separate from this “institutional” interpretation: governments with access to higher tax revenues have a greater potential to reduce poverty through progressive expenditure and transfer programs.<sup>21</sup> We do not include tax effort in most of our regressions because it is available in a comparable series only beginning in 1990, and its inclusion cuts the sample size by nearly half. Despite the relatively small sample, its coefficient in regression (iv) is positive and significant. A standard deviation increase in tax effort – about 8 percentage points – is associated with an increase in the probability of graduating of about 1 percentage point. Results for tax effort are robust to inclusion in the regression of the Polity democracy index, in column (v) of Table 5.

Regression (vi) includes a standard indicator of financial development, M2 (a measure of money supply) as a share of GDP, which is computed using data from the IMF’s International Financial Statistics database. Because missing data on M2/GDP reduces our sample size by more than one-third, we do not include this indicator of institutional development in our main tests in Table 3. Its coefficient is positive and significant in Table 5, however, suggesting that financial institutions are among the social and economic institutions taken into account in graduation decisions.<sup>22</sup> 20 According to the World Bank’s Articles of Agreement (Article IV, section 10): “The Bank and its officers shall not interfere in the political affairs of any member; nor shall they be influenced in their decisions by the political character of the member or members concerned. Only economic considerations shall be relevant to their decisions...” Of course, political considerations may influence a member government’s own decisions with respect to graduating from the IBRD.

21 Ravallion (2009) constructs an indicator of countries’ capacity to eliminate extreme poverty through income redistribution, measured in terms of the marginal income tax rates on the non-poor that would be required. This indicator is available for only a very few countries with incomes exceeding the IBRD threshold, so we are unable to use it in our tests.

22 A final variation on the credit rating and ICRG measures (not shown here) is to make use of lags. One commenter on this paper suggested that the credit ratings and ICRG scores could reflect reverse causality: a country’s graduation could cause raters to increase scores in the year of graduation. For countries as developed and integrated into global markets as the typical new graduate, it seems unlikely that IBRD graduation is taken as providing much new information on the level of institutional development and creditworthiness. Nevertheless, we tested the possibility by using lagged score rather than contemporaneous score. In the case of both variables, lagging the variable one year made the coefficient both larger and more statistically significant, which may allay concerns about reverse causality.

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