This Selected Issues paper focuses on the adoption of new technology and globalization in the United States of America, and assesses the change in the productivity growth and revised estimates, the developments in the labor market, equity prices, and the technology boom. The paper analyzes how the monetary policy influences economic conditions in emergency markets; reviews the developments in financial consolidation; discusses the key provisions contained in the Gramm-Leach-Bliley (GLB) Act, the implications of the GLB Act for financial consolidation, and regulatory and supervisory practices.

Abstract

This Selected Issues paper focuses on the adoption of new technology and globalization in the United States of America, and assesses the change in the productivity growth and revised estimates, the developments in the labor market, equity prices, and the technology boom. The paper analyzes how the monetary policy influences economic conditions in emergency markets; reviews the developments in financial consolidation; discusses the key provisions contained in the Gramm-Leach-Bliley (GLB) Act, the implications of the GLB Act for financial consolidation, and regulatory and supervisory practices.

V. How Does U.S. Monetary Policy Influence Economic Conditions in Emerging Markets?1

1. Given the integration of global capital markets, changes in U.S. monetary policy are felt almost immediately by developing countries through effects on the cost and availability of funds. In addition to the direct impact of changes in U.S. interest rates on rates in developing countries, interest rate spreads (the differences between yields on sovereign bonds of developing countries and U.S. Treasury securities of comparable maturities, which are a proxy for country risk) move in the same direction as the changes in U.S. interest rates. This effect on developing country spreads was seen clearly in 1994 when a tightening of U.S. monetary policy was reflected in a substantial widening of spreads, and in 1998 when an easing of U.S. monetary policy in response to the flight to quality following the Russian default reduced spreads somewhat.

2. The empirical evidence on interest rate spreads presented here suggests that country-specific fundamentals are important in explaining fluctuations in developing country interest rates spreads, but also important is the stance and predictability of U.S. monetary policy. To the extent that monetary policy actions can be anticipated by market participants, market turbulence would likely be reduced, and therefore one conclusion that can be drawn from the analysis is that an approach to monetary policy that provides financial markets with clear indications of the U.S. authorities’ intentions is likely to reduce the impact of a U.S. rate increase on developing countries. The direct effects of a change in U.S. monetary policy on income and domestic demand of developing countries as a group also was simulated using Multimod. The simulations indicate that a 100 basis point increase in U.S. interest rates will reduce developing countries’ GNP and domestic demand by ½ percent per year.

A. Long-Run Determinants of Sovereign Spreads in Emerging Markets

3. The existing empirical literature is far from conclusive on how U.S. monetary policy affects emerging market sovereign spreads. Most of the specifications adopted so far have been somewhat simplistic, proxying U.S. monetary policy by the level of the three-month U.S. Treasury bill yield.2 Eichengreen and Mody (1998) found, for a sample of Latin American and East Asian countries during 1991-95, that a rise in U.S. Treasury interest rates tended to reduce spreads, perhaps because it deterred less-creditworthy borrowers from issuing bonds. They found that while the level of sovereign spreads was determined largely by fundamentals, changes in sovereign spreads were also driven significantly by market sentiment. Cline and Barnes (1997) found a positive but statistically insignificant effect of U.S. Treasury yields on sovereign spreads in selected emerging markets during the mid-1990s, a finding shared by Kamin and Kleist (1997).

4. An econometric model for sovereign bond spreads was estimated individually for a group of emerging market countries.3 The model explains fluctuations in spreads as a function of country-specific macroeconomic variables, the level of the U.S. federal funds target rate, and a proxy for market volatility. The proxy for market volatility is intended to capture changes in investor sentiment which may be related to expected changes in U.S. monetary policy. It may also pick up the effects of other market-related events, such as the so-called “flight to quality” effects.4 The results show that the level of the U.S. federal funds target rate has significant positive effects on emerging market spreads, with the estimated elasticity ranging from about ½ to 1 (Table 1).5 The model also supports the view that increased market volatility related to heightened uncertainty about the expected path of U.S. monetary policy has significant positive effects on spreads across countries and regions.6 However, a significant proportion of fluctuations in emerging market spreads is driven by country-specific fundamentals. In particular, the results suggest that improved macroeconomic fundamentals, such as higher net foreign assets (in terms of GDP or imports), lower fiscal deficits, and lower ratios of debt service to exports and debt to GDP, help to lower sovereign spreads.

Table 1.

Determinants of Sovereign Bond Spreads for Selected Emerging Markets

article image
Source: Staff estimates.Probability values, for the null hypothesis of a coefficient equal to zero, are reported in parentheses.

Based on the fitted conditional standard error from an ARCH model for the spread between the three-month T-bill and the federal funds rate.

Refers to net debt.

A dummy was included to allow for the effects associated with the introduction of a currency board in Bulgaria.

Hamilton (1994) reports critical values at the 90 and 95 percent confidence level of about -2.59 and -2.912 for a sample size of 50-100 observations, respectively. One and two asterisks imply rejection of the null hypothesis of no cointegration at the 90 and 95 percent level of significance.

5. The model presented in Table 1 explains fluctuations in emerging market sovereign spreads relatively well for most countries (Figure 1). In particular, the model explains roughly between half and three-quarters of the fluctuations in spreads for most countries. However, the model is subject to a structural break in late 1995 in several countries (Figure 2). Specifically, in the cases of Argentina, Brazil, Mexico, Philippines, Bulgaria, and Poland, the model fails to fully account for the sharp narrowing of spreads that took place during the period leading up to the Asian crisis. The narrowing of sovereign spreads between the first half of 1996 and mid-1997 was particularly pronounced in these countries, and may have been associated more with changes in market access and with global portfolio shifts by institutional investors than with country-specific fundamentals.7

Figure 1.
Figure 1.
Figure 1.

Sovereign Spreads in Selected Emerging Markets Actual vs. Fitted Values

(in logarithm)

Citation: IMF Staff Country Reports 2000, 112; 10.5089/9781451960297.002.A005

Sources: Merrill Lynch; and staff estimates.
Figure 2.
Figure 2.
Figure 2.

Stability Tests 1/

Argentina

Citation: IMF Staff Country Reports 2000, 112; 10.5089/9781451960297.002.A005

1/ Based on the cumulative sum of squared residuals statistic. Confidence bands for a 95 percent level of significance.

B. Macroeconomic Effects of U.S. Monetary Policy on Developing Countries

6. The macroeconomic effects on developing countries of a tightening in U.S. monetary policy were explored using the IMF’s multi-country model (Multimod).8 A scenario that examined the macroeconomic impact on developing countries of an increase in the U.S. federal funds rate of 100 basis points relative to the baseline was simulated over a ten-year period starting in 2000 (Table 2).9 The baseline was represented by the central forecast in the May 2000 World Economic Outlook exercise. In order to focus on the effects of a U.S. monetary policy tightening, the interest rate increase was assumed to be exogenous (rather than, for example, a response to rapid U.S. demand growth). The simulation shows that for developing countries as a whole the rise in U.S. interest rates would lead to a reduction in real GNP and domestic demand relative to the baseline of nearly ½ percent annually over the medium term. Because interest rates are assumed in Multimod to affect real activity and debt service with a lag, the effects of higher interest rates are larger over the medium term than immediately upon impact.

Table 2.

Developing Countries: Macroeconomic Effects of a 100 Basis Point Increase in the U.S. Federal Funds Interest Rate

(Deviation from baseline, in percent unless otherwise noted)

article image
Source: Staff calculations, based on WEO projections and Multimod.

Deviation from baseline in percentage points.

7. Among developing countries, there is a substantial difference between the macroeconomic impact on debtor and on creditor countries, with debtor countries experiencing a much larger negative impact. Debtor countries would face a rise in debt-service costs (of nearly 2 percentage points in the first few years) and a tightening in their financing constraint, and the rise in debt service would require a rise in the net exports of these countries.10 Higher interest payments, together with the tightening of the financing constraint, would in turn contribute to a sharp reduction in domestic demand, with both consumption and investment falling relative to the baseline. The overall impact would be to reduce GNP and domestic demand by ½ percent annually. This is roughly the same as the total impact on developing countries because debtor countries account for an overwhelming proportion (around 90 percent) of the GNP of developing countries. The creditor countries, in contrast, would experience a positive wealth effect arising from higher returns on their net foreign assets. The higher returns would allow domestic demand and GNP to rise relative to the baseline by ¼ percent and ½ percent, respectively, annually over the medium term. A reduction in the trade balance of these countries would be partly offset by higher interest receipts, allowing the current account balance to improve slightly over the medium term.

List of References

  • Cantor, R. and Packer F., 1996, ’Determinants and Impact of Sovereign Credit Ratings,” Federal Reserve Bank of New York Economic Policy Review, October, pp. 3753.

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  • Cline, W. and Barnes K, 1997, “Spreads and Risk in Emerging Markets Lending,” Institute of International Finance, Working Paper No. 97-1, December.

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  • Eichengreen, B. and Mody A., 1998, “What Explains Changing Spreads on Emerging-Market Debt: Fundamentals or Market Sentiment?,” National Bureau of Economic Research Working Paper No. 6408, February.

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  • Hamilton, J., 1994, Time Series Analysis, Princeton University Press.

  • Hsieh, D. and Miller, M., 1990, “Margin Regulation and Stock Market Volatility,” Journal of Finance, Vol. XLV, No.l, March.

  • International Monetary Fund, 1995 and 1996, “International Capital Markets Report.”

  • Kamin, S. and von Kleist, K., 1997, “The Evolution and Determinants of Emerging Market Credit Spreads in the 1990s,” unpublished manuscript, Federal Reserve Board and Bank for International Settlements.

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  • Laxton D., Isard P., Faruqee P., Prasad E., and Turtelboom B., 1998, ”MULTIMOD Mark III: The Core Dynamic and Steady State Models,” International Monetary Fund, Occasional Paper No. 164, Washington, DC.

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  • Laxton, D. and Prasad, E., 2000, “International Spillovers of Macroeconomic Shocks: A Quantitative Exploration,” IMF Working Paper (forthcoming).

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1

Prepared by Vivek Arora, Martin Cerisola, and Victor Culiuc.

2

Shocks to the three-month Treasury bill rate do not always imply changes in U.S. monetary policy. The so-called “flight to quality” experienced during the Asian crisis has been quite revealing in terms of fluctuations in U.S. Treasury bill yields in the absence of changes in U.S. monetary policy, as well as how changes in U.S. short-term rates affect sovereign spreads in emerging markets.

3

The model was estimated for Argentina, Brazil, Bulgaria, Colombia, Indonesia, Korea, Mexico, Panama, Philippines, Poland, and Thailand.

4

Market volatility was proxied by the fitted values for the conditional standard error from an Autoregressive Conditional Heteroskedasticity model (ARCH) for the spread between the three-month yield on the U.S. Treasury bill and the federal funds target rate. ARCH models are useful in analyzing financial data because they capture the persistence that is observed in many financial time series. In particular, large shocks tend to be followed by large shocks of unpredictable sign, suggesting that there is persistence in market volatility, a notion that the ARCH methodology aims at capturing.

5

The rise in the level of emerging market interest rates will, however, not necessarily be as large as the sum of the rise in spreads and the rise in the U.S. federal funds rate. In the United States, the yield curve tends to flatten as monetary policy is tightened, so that a rise in short-term interest rates is not fully passed through to longer-term rates.

6

Several proxies for market volatility were used for estimating the model, and the results are somewhat sensitive to the chosen proxy. The results based on a six-month moving average of standard deviations for the spread between the three-month yield on the Treasury bill and the federal funds target rate was highly statistically significant across countries. However, the validity of this proxy for volatility has been questioned in the empirical literature by Hsieh and Miller (1990) on the basis of inducing a spurious correlation between variables due to its high serial correlation. An alternative proxy, the standard deviation of the daily spread within a month, was not statistically significant, except for Argentina, Bulgaria, and Indonesia.

7

Several countries, like Argentina and Mexico, became very active in issuing yen-denominated bonds in the Japanese market. Access was eased by regulatory changes in this market, which eliminated restrictions on the sale of sovereign yen-denominated Eurobond issues to Japanese investors in 1994 and reduced the minimum credit rating requirement for Samurai bonds in 1996. The model was extended to capture these events by including the Hodrick-Prescott cyclical component of the number of yen-denominated sovereign bond issues during this period. A significant (but very small) negative effect was found for some of those countries, particularly Argentina and Mexico. In addition, the results for Asian countries (except the Philippines) should be interpreted with some caution given the relatively small sample size.

8

See Laxton et al. (1998) for a discussion of Multimod, and Laxton and Prasad (2000) for a Multimod-based analysis of the effects of macroeconomic shocks in the United States on major industrial countries. A tightening of U.S. monetary policy would in general be expected to reduce the availability of, and raise the interest rate on, credit for developing countries. In Multimod, the reduction in credit to developing countries is modeled by a tightening of the financing constraint faced by debtor countries that depends (inversely) on the ratio of expected debt service to exports. An increase in U.S. interest rates, by raising the debt-service ratio, reduces the availability of financing. The spread (risk premium) on developing country credit is not explicitly modeled in Multimod.

9

The ten-year period was chosen so as to allow an assessment of the medium-term effects. Multimod does not have any significant nonlinearities regarding the effects of U.S. interest rate increases on developing countries. Alternative simulations with interest rate increases of 200 and 300 basis points suggest that the effects on output, domestic demand, and other macroeconomic variables in developing countries are roughly two and three times as large, respectively, as in the 100 basis point case.

10

The increase in the trade balance for these countries relative to the baseline would be offset by higher interest payments, leaving the current account balance roughly unchanged.

United States: Selected Issues
Author: International Monetary Fund