Appendix: Policy Reaction Functions
This appendix reports the results obtained from policy reaction functions estimated across a number of different countries. The main focus of this work is to examine the degree to which government policy has reacted to the current account, in order to investigate the hypothesis of Summers (1988), among others, that the observed cross-country correlations between saving and investment are due to government policy. Since there has been a fall in the observed correlation between the 1970s and the 1980s, this work also investigates whether there has been a fall in the importance of the current account as a policy target over the last twenty years.
Monetary and fiscal policy reaction functions are estimated directly, using reduced form equations with a policy instrument as the dependent variable and (lagged) targets as the independent variables. While there are other, more structural, methods of estimating reactions functions (Pissarides, 1977), the reduced form approach has been widely used in the literature (Joyce, 1986). Since they have rather different problems and complications, the monetary and fiscal reaction functions will be discussed separately.
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Michael Artis is Professor at the University of Manchester. He contributed to this study as a consultant to the Research Department. The authors would like to thank Jeff Frankel, Lars Svensson, Jim Boughton, Graham Hacche, and participants at an IMF seminar for useful suggestions and comments. They would also like to thank Flemming Larsen for suggesting the topic.
For the convenience of exposition transfers are omitted.
These definitions follow convention in assuming that all of G is a “consumption good”. In effect, of course, governments typically perform a large amount of investment and this should be recognized in empirical analysis of the problem (as in the work reported on below—see Section 4).
As saving is simply the addition to wealth, another way to think about the saving process is as an adjustment toward a desired wealth/income position (which itself may be an evolving target). This in turn indicates that current account surpluses (and deficits) are not unbounded; verification of the nature of these processes over long periods is an important objective for future research though one that is somewhat hampered by lack of data availability.
Frankel (1989) provides a comprehensive review of the process of liberalization and computes various associated measures of financial integration.
Offshore CIP (i.e., covered parity of returns in Euromarkets) does not imply that arbitrage can operate freely across national boundaries: since the same institutions set both the forward rate for a currency and the Euro-interest rate in that currency by reference to CIP (Johnston 1979), observed deviations from offshore CIP are invariably due to no more than the employment of imprecise (perhaps averaged or inexactly date-matched) data.
We are grateful to Jeffrey Frankel for permission to reproduce this diagram.
Frankel (1989, Table 6) shows that, prior to 1986 violations of offshore/onshore parity were much more marked for these two countries than for the United States, Germany, the United Kingdom, and Japan, in the 1980s.
Note however that there is no incentive to arbitrage real rates of return. Real return equalization is predicted only where expected depreciation is (correctly) given by relative expected inflation, i.e., where PPP governs the determination of exchange rates.
The fact that markets react to current account announcements does not necessarily indicate that capital mobility is low. If markets look to governments as a source of information and governments act as if financial constraints require current account balance, then the market will continue to react to deviations from balance since they imply changes in policy stance, and governments will feel justified in continuing to target the current account.
This case was elaborated by Schmitt (1979); the subsequent findings of Krugman and others in regard to the nature of international trade underline the relevance of this model (see Vines and Stephenson, 1989).
Both gross and net saving and investment have been used in the literature. The data are generally averaged over several years in order to avoid bias caused by the correlation of saving and investment over the business cycle.
Similar regressions for developing countries also show a significant correlation over time, although the coefficients are somewhat lower than that for industrial countries (Dooley, Frankel and Mathieson, 1986).
These estimates use ordinary least squares. Typically researchers have found instrumental variables results to be similar to OLS.
Frankel (1989) reports that for the United States regressions, the inclusion of the period 1984-1987 significantly reduces the estimated correlations. However, Bayoumi (1989) does not find such an effect.
Feldstein and Bacchetta (1989) argue that Obstfeld’s model cannot explain the correlations when “realistic” parameter values are used.
Feldstein and Bacchetta (1989) disaggregate the data in the Summers study further and argue that they support the hypothesis that capital mobility is low.
Issues of data reliability suggest that cross-section correlations are more reliable for the gold standard period than correlations performed on the time series. However, it should be noted that Obstfeld (1986), using a different data source to Bayoumi’s, reports quite a high coefficient for a Gold Standard time series equation for the United Kingdom.
This model has been tested extensively on data for the United States. The overall conclusion is that the model works reasonably well as a first approximation, but that a significant proportion of consumption emanates from households that are liquidity constrained. These households consume out of current, rather than permanent, income. Tests for other countries have tended to reject the model more readily than for the United States (Hall, 1988).
For example, if a variable is projected using a first order autoregressive process, the first lag will contain all the information needed to project its future values.
Full data sets were not available for other countries. The interest rates are end quarter data, while the other variables are quarterly averages. For each country the change in the interest rate was regressed on the current value and first lag of growth, inflation and the current account ratio. Since the interest rate data are end-period, the use of current period data on targets is justified, although it does assume a short lag between changes in targets and changes in instruments.
Using a simple sign test, the probability of four coefficients all turning up negative is 6.25 percent, close to conventional significance levels.
However, these results are not robust to the inclusion of lags.
This length of time was chosen because it is long enough to produce reasonable coefficient estimates, but short enough to allow genuine changes in coefficients to become apparent.
Concepts such as the full employment deficit, which aim to take out these endogenous factors, depend upon the model used; furthermore, using such concepts in a reaction function assumes that governments disregard endogenous effects when choosing their fiscal stance.
General government data were used because central government data were only available for a few countries.
When contemporaneous growth and inflation are included in the regression, the coefficient on lagged growth falls to near zero, while the coefficient on inflation becomes significantly negative.
These results are not simply a product of Ricardian effects. Using similar data, Bayoumi (1989) finds a negative correlation between government and private saving, but the effect is not as powerful as the one documented here.
Using a simple one-tailed sign test this result is significant at the 10 percent level, but not at the 5 percent level.