Back Matter

Back Matter

International Monetary Fund. European Dept.
Published Date:
September 2009
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Note: The main author of this chapter is Srobona Mitra.

High spreads and high volatility in interest rates are often observed together (Fernandez-Villaverde and others, 2009). The association works through investors seeking higher expected returns in case of higher risk. In turbulent times, news also arrives fast and frequently, inducing high volumes of trade in foreign debt and raising volatility when spreads are also higher.

Blanchard (2009) warns that the “higher risk perception may well be an enduring legacy of the crisis,” citing evidence from the Great Depression that led to a lasting increase in the risk premium on stocks.

For links between fiscal policy, financial sector risks, and interest spreads, see, for instance, Blanchard (1984); IMF (2009d); Ardagna, Caselli, and Lane (2004); Debrun and Joshi (2008); and Horton, Kumar, and Mauro (2009).

The structural deficit for Hungary was considerably tightened in 2009Q2, which helped lower spreads.

This is further amplified by the contingent costs of government guarantees for the financial sector. See Horton, Kumar, and Mauro (2009) and Chapter 3 for a discussion of the impact of the crisis on fiscal sustainability.

Downward revisions in the fiscal balance for the year and time-varying volatility of the exchange rate are highly correlated for some countries. For the countries shown in Figure 23, especially since the fall of Lehman Brothers, the coefficient of correlation is on average about 0.4.

IMF programs in some countries have led to letters of commitment from parent banks to the country authorities, committing to stand by their subsidiaries. The letter for Hungary can be found at; for Romania, at; for Bosnia and Herzegovina, at; and for Serbia, at

If firms have to commit to their technology in advance, then volatility can lead to lower mean output because firms find themselves producing at suboptimal levels ex post. If lower current output affects resource accumulation, then growth is adversely affected (Ramey and Ramey, 1995).

This section and the next are written by Ioan Carabenciov, Roberto Garcia-Saltos, Michel Juillard, Douglas Laxton, Troy Matheson, Srobona Mitra, Susanna Mursula, and Kadir Tanyeri.

The analytical details are elaborated in Carabenciov and others (forthcoming). The model is estimated with data from 2001:Q3 to 2009Q1, and the standard deviation of the residuals are computed for the precrisis (2001:Q3–2007:Q2) and the crisis (2007:Q3–2009:Q1) periods.

Monetary policy shocks also tended to be more volatile in EM precrisis (not shown). In the GPM, the exchange rate shock is the shock to the uncovered interest parity equation. The expected change in the real exchange rate one quarter ahead equals the real interest rate difference between EM and the United States minus the difference between the equilibrium real interest rates (or the equilibrium risk premium) adjusted for changes in the equilibrium real exchange rate plus the exchange rate shock.

Policymakers could be thought of as wanting to maximize society’s welfare by lowering variability in inflation and output changes, given existing trade-offs. Given their preference and shock volatilities, the lowest preferred combinations of output and inflation variability can be plotted in the “efficiency frontier.” The estimates from the GPM and the various shock variances are used to draw the frontier. To do so, a social loss function denoted by the weighted sum of variances of inflation, output gap, and changes in the real interest rate is minimized subject to the estimated equations and their shock variances. Because there can be infinite combinations of weights depending on social preferences, the weight on the output gap is varied, and the optimal interest rate rule is estimated for each weight. The standard deviation of inflation and the output gap resulting from applying the newly optimized rule is then computed, forming a point in the efficiency frontier for the EM. Other points are obtained by varying the degree of dislike for output variability compared to inflation variability and following the same procedure.

For instance, if policymakers in both countries paid twice as much attention to the smoothness of inflation compared to output (for example, if the weight on the variance of the output gap in the loss function was 0.5 and that of inflation 1), then the best preferred lowest standard deviation of output would be 0.79 for the euro area, whereas the EM’s best achievement would be 1.62.

By construction, the efficiency frontier assumes that the EM’s central bank’s policy rule is optimally adjusted to the more volatile environment.

See Clarida, Gali, and Gertler (1999), footnote 11, for an interpretation of the aggregate demand shock and its relation to government spending.

For instance, Honjo and Hunt (2006) show how fiscal policy rules designed to ensure a consistently countercyclical fiscal stance along with a public debt target can shift Iceland’s efficiency frontiers to the southwest.

Sizable improvements in primary balances will be required in several emerging economies to halt or reverse the increase in debt-to-GDP ratios through 2014 (Horton, Kumar, and Mauro, 2009). Anchoring expectations about the fiscal policy path could be done by setting medium-term fiscal targets that are credibly set and supported by appropriate institutional frameworks. An example is a medium-term expenditure framework that sets multiyear limits at the aggregate, ministerial, or program level, to translate overall objectives into budget decisions. Also, see Horton, Kumar, and Mauro (2009) for a table on strategies to ensure fiscal sustainability announced or discussed by G-20 country authorities.

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