Highly favorable external conditions have helped Latin America strengthen its economic fundamentals over the last decade. But, has the region built enough buffers to guard itself from a weakening of the external environment? This paper addresses this question by developing a simple framework that integrates econometric estimates of the effect of global factors on key domestic variables that determine public and external debt dynamics, with the IMF‘s standard debt sustainability framework. Results suggest that, while some countries in the region are well placed to withstand moderate or even large shocks, many would benefit from having stronger buffers to be in a position to deploy countercyclical policies, especially under tail events. External sustainability, on the other hand, does not appear to be a source of concern for most countries.
I. I ntroduction
This study proposes a stochastic debt forecasting framework that identifies and estimates the impact of feedback between fiscal policy and macroeconomic projections – effects which are largely absent from current debt forecasting algorithms. In such algorithms, a distribution of fiscal and debt forecasts is projected by combining simulated macroeconomic scenarios, a fiscal policy reaction function, and a debtmotionequation. In the proposed framework, fiscal projections reflect contemporaneous macroeconomic shocks through automatic
A stochastic debt forecasting framework is presented where projected debt distributions reflect both the joint realization of the fiscal policy reaction to contemporaneous stochastic macroeconomic projections, and also the second-round effects of fiscal policy on macroeconomic projections. The forecasting framework thus reflects the impact of the primary balance on the forecast of macro aggregates. Previously-developed forecasting algorithms that do not incorporate these second-round effects are shown to have systematic forecast errors. Evidence suggests that the second-round effects have statistically and economically significant impacts on the direction and dispersion of the debt-to-GDP forecasts. For example, a positive structural primary balance shock lowers the domestic real interest rate, in turn raising GDP and lowering the median debt-to-GDP projection by an additional 10 percent of GDP in the medium term relative to prior forecasting algorithms. In addition, the framework employs a new long-term (five decade) data base and accounts for parameter uncertainty, and for potentially non-normally distributed shocks.
International Monetary Fund. Western Hemisphere Dept.
-American Development Bank (2008) ; Izquierdo and others (2008) ; and Osterholm and Zettelmeyer (2008) .
As in standard debt sustainability analysis, the focus of our analysis is the dynamics of gross debt and primary balance. Risks related to financing needs as well as the composition of creditors are beyond the scope of our work.
The VAR model (together with the spread equation) and the debtmotionequations capture the key linkages between domestic and external variables. To fully determine the dynamics of debt ratios, however, a few assumptions are
function to produce first a projection of the primary surplus, and then a debt-to-GDP ratio from the debtmotionequation. Frequency distributions for public debt, as well as for all the other forecasted variables are obtained by simulating 1,000 stochastic paths.
Figure 5 shows three fan charts with five-year debt forecasts for Uruguay under endogenous fiscal policy. The median projection is represented by the bold line. The first four shaded surfaces at each side of the median represent an interval of 10 percent of the distribution of the debt ratio, and the last
Reported gap vis-à-vis baseline is reached by 2013-Q2. Prices recover gradually afterward to reach new path by end-2014.
Global Variables under Alternative Scenarios
Sources: IMF, International Financial Statistics; and authors’ estimations.
The VAR model (together with the spread equation) and the debtmotionequations capture the key linkages between domestic and external variables. To fully determine the dynamics of debt ratios, however, a few assumptions on domestic policy are also necessary. These include (1) the
The VAR model (together with the spread equation) and the debtmotionequations capture the key linkages between domestic and external variables. To fully determine the dynamics of debt ratios, however, a few assumptions on domestic policy are also necessary, as noted in section III . These include: (i) the output elasticity of non-commodity fiscal revenue; (ii) real public expenditure policy; and (iii) the extent of reserve accumulation 31 . Table 2 details these key assumptions under each of the four alternative scenarios.
Mr. Paolo Mauro, Rafael Romeu, Mr. Ariel J Binder, and Mr. Asad Zaman
ratio—we label this the policymakers’ criterion . 13 From the well known debtmotionequation, the debt-stabilizing primary surplus is s t = d t –1 ( r t – g t /1+ g t ). Note the close correspondence between the policymakers’ criterion and Bohn’s criterion for stationarity of the debt ratio, as a stable debt ratio is a special case of a stationary debt ratio. 14 15
B. Methods to Gauge Variation in Prudence/Profligacy Over Time
Although Bohn’s original application of his test considered the longest available time series, in principle the response of
Mr. Paolo Mauro, Rafael Romeu, Mr. Ariel J Binder, and Mr. Asad Zaman
We draw on a newly collected historical dataset of fiscal variables for a large panel of countries—to our knowledge, the most comprehensive database currently available—to gauge the degree of fiscal prudence or profligacy for each country over the past several decades. Specifically, our dataset consists of fiscal revenues, primary expenditures, the interest bill (and thus both the primary and the overall fiscal deficit), the government debt, and gross domestic product, for 55 countries for up to two hundred years. For the first time, a large cross country historical data set covers both fiscal stocks and flows. Using Bohn’s (1998) approach and other tests for fiscal sustainability, we document how the degree of prudence or profligacy varies significantly over time within individual countries. We find that such variation is driven in part by unexpected changes in potential economic growth and sovereign borrowing costs.
Do highly indebted countries suffer from a debt overhang? Can debt relief foster their growth rates? To answer these important questions, this article looks at how the debt-growth relation varies with indebtedness levels, as well as with the quality of policies and institutions, in a panel of developing countries. The main findings are that, in countries with good policies and institutions, there is evidence of debt overhang when the net present value of debt rises above 20–25 percent of GDP; however, debt becomes irrelevant above 70–80 percent. In countries with bad policies and institutions, thresholds appear to be lower, but the evidence of debt overhang is weaker and we cannot rule out that debt is always irrelevant. Indeed, in such countries, as well as in countries with high indebtedness levels, investment does not depend on debt levels. The analysis suggests that not all countries are likely to profit from debt relief, and thus that a one-size-fits-all debt relief approach might not be the most appropriate one.