Debt (TOD), taken from the Global Development Finance dataset, which tracks the face value of the stock of external debt, and a Present Value measure (PV), computed as the discounted sum of future external debt payments. The former is standard in the empirical literature on debt, whereas the latter is more recent and relies on specific assumptions regarding the discount rates and amortization profiles. PPR use both and so do we. We do however use two PV measures, one constructed by Easterly (2001) (PVE) and the second by Dikhanov (2004), PVY.

The two measures differ in three ways. PVE builds from aggregate country-level data on the terms of borrowing, whereas PVY is based on loan-by-loan data that are aggregated up to the country level. In addition, PVY allows for currency-specific and time-varying discount rates. Unlike PVE, it is however restricted to public and publicly guaranteed debt. While this is a narrower measure than PVE, it will also provide some robustness checks on the importance of debt ownership. Both measures assume a linear amortization schedule.

We follow PPR and construct two ratios for each debt measure, expressed relative to GDP or to exports. The ratio of debt to exports captures the external resources effectively available to cover external debt liabilities, and is often used by practitioners, but it is also more sensitive to term of trade shocks, and thus more volatile, than ratios to GDP The rest of our data are standard, but offer relatively broad coverage. We construct a panel of observations for 87 developing economies over the period 1969-2002, which we use in two empirical exercises. First in standard growth regressions, based on three- or five-year averages; second in an event study where we use all the available time variation. Our control variables in the growth analysis are classic and inspired from the robust sets proposed in Levine and Renelt (1992).<sup>10</sup> They include initial income, openness to trade, population growth, secondary schooling and the growth rate of the terms of trade. We also experimented with the fiscal balance, with no changes in conclusions. Construction of these variables is standard; the sources used are the World Development Indicators, the World Economic Outlook and the International Financial Statistics.

In the event study, we track the response over time of investment, macroeconomic policy, and the terms of borrowing. Of these, only investment is readily available and its measure relatively uncontroversial. We choose to investigate the dynamic response of two policy related variables: inflation and government expenditures. If the conduct of economic policy does indeed deteriorate at high levels of debt, we conjecture that at least one of these measures will show a systematic response. We also include an index computed by the World Bank, the Country Performance International Assessment, or CPIA, meant to summarize in one number an assessment of the overall quality of policy stance.<sup>11</sup> Because we are interested in the terms under which debt is contracted, we finally bring in additional information from Global Development Finance publications, with a view to isolating changes in the rate of interest for different countries and debt levels. In particular, we collect the value of new

> 10 Doppelhofer, Miller and Sala-i-Martin (2004) recently used Bayesian techniques to isolate an alternative, updated set of control variables. The approach is however purely cross-sectional, and its results cannot be used in the present context where within-country growth determinants are of the essence. For instance, the most robust correlates of economic growth include the extents of confucianistic or protestant religions, or geographic binary variables, none of which lend themselves to a panel estimation.

> 11 These data are

8