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University of California, Santa Cruz, and NBER; and Research Department, International Monetary Fund, respectively. We are grateful to Tamim Bayoumi, Hamid Faruqee, Peter Isard, Russell Kincaid, Lori Kletzer, Philip Lane, Gian Maria Milesi-Ferretti, Assaf Razin and numerous other colleagues and seminar participants for comments and helpful discussions and to Sarma Jayanthi for research assistance.
Glick and Rogoff (1995), Lee and Chinn (1998) and Prasad (1999) show how the sources of shocks and their persistence can affect the dynamics of trade and current account balances. Calderon, Chong and Loayza (1999) try to differentiate between the effects of permanent and transitory shocks on annual current account variation in developing countries.
As a robustness check, we tried replacing the NFA variable with the measure of net external debt taken from the World Bank saving database. In principle, these variables should be similar. However, the correlation between these two variables turned out be quite small and, perhaps because of greater measurement error in the debt variable, the coefficient on the external debt to GDP ratio was not significant in some specifications (the sample sizes were smaller since the latter variable was available only for a subset of the countries in our full sample). An effort is underway by a consortium of international organizations (BIS, OECD, IMF, World Bank) to improve the quality and consistency of cross-country external debt data but these improved data are currently available only for a very limited period.
An interesting issue that arises here is whether the relative income level is the appropriate measure to capture a country’s stage of development. As noted below, we also control for growth rates of output, which, however, could also proxy for other factors. This issue is discussed in more detail in the next section.
Debelle and Faruqee (1996) report similar cross-section results for a sample including industrial and a few developing countries. They, too, note the instability of these coefficient estimates across specifications. We experimented with the inclusion of higher order polynomials of relative income in the regressions, but their coefficients were not statistically significant and did not change any of the results.
The level of the terms of trade would also be expected to influence the evolution of the trade balance and the current account over time. However, since the terms of trade variable is available only as in index, we were unable to use this variable in cross-country analysis.
Consistent with this result, Lane (1997) reports a positive association between trade openness and the level of external debt among developing countries.
Wald tests confirmed that the hypothesis of homogeneity of coefficients across the different groupings of countries shown in the table could be rejected.
When we replaced the initial NFA/GDP ratio variable used here (based on the value of this variable in the first year of the five years averaged for a particular observation) with the NFA/GDP ratio used in the cross-section regressions (the average of the NFA/GDP ratio in the first five years of the full sample for each country), the results were similar to those discussed here, but only when the African countries were excluded. For the full developing country sample, the other coefficients did not change much but the coefficient on the initial NFA to GDP ratio, although still positive, was less strongly significant.
An alternative explanation is that the perception among international investors of implicit guarantees of bailouts for certain countries could induce a moral hazard problem. This would be reflected in perverse feedback effects, whereby countries with high external debt get further access to international capital. Lane (1998) documents a strong positive relationship between the levels of external debt and output among developing economies and notes that this finding is consistent with models of international credit rationing.
Kraay and Ventura (2000) argue that the sign of the current account response to transitory income shocks depends on the share of foreign assets in a country’s total assets. However, since our use of 5-year averaged data would be expected to smooth out transitory income shocks, this explanation might be less relevant for our medium-term results.
Although their relationship to current accounts is not obvious, we also tried including other macroeconomic variables such as average inflation rates but they did not enter significantly into any of these regressions.
To check if any of the other variables in the regressions could be picking up the effects of the capital controls, we tried a variety of specifications that excluded various combinations of the openness indicators, financial deepening variables etc. None of these specifications yielded a statistically significant coefficient on either of the indicators of capital controls.
Bosworth and Collins (1999) find that a large proportion of capital inflows into developing countries is indeed used to finance current account deficits. Countries could also finance current account deficits by running down their reserve positions. This approach is likely to be sustainable only for short periods of time. Since our focus is on current account determination at relatively low frequencies, we ignore the role of fluctuations in reserves in our analysis.
The flip side to this endogeneity is the notion that domestic saving could be influenced by capital inflows. Reinhart and Talvi (1998) argue that, in their sample of Asian and Latin American countries, long-run saving behavior has little do with capital inflows and appears instead to be driven by the sorts of structural determinants analyzed in this paper.
The turnaround in the aggregate current account position for Africa between the first and second halves of the 1980s is largely attributable to developments in Nigeria and South Africa.
A similar point, in the context of cross-country growth and convergence regressions, is made forcefully by Quah (1996, p. 38) and is echoed by Lane (1998) in his work on the determinants of external debt.
The last row of Table 4 reports Hausman test statistics for the validity of random effects (RE) versus fixed effects specifications. For the industrial countries and the full sample of developing countries, we could not reject the null hypothesis that the RE specification is appropriate. We estimated RE models for these two sub-samples but few of the results were affected. Hence, to maintain consistency, we report only FE results in this table.
To check if the East Asian countries in our sample could be driving the OLS and FE coefficients on the relative income terms in columns 4 and 5, we re-estimated the equations excluding them. The coefficient on the squared relative income term fell slightly in both cases but little else changed.
We thank Sergio Rebelo for this suggestion. Jones (1994) finds that the relative price of machinery is more important in cross-country growth regressions than the relative prices of the other components of investment. The relative prices of the components did not in general enter significantly into any of our regressions either independently or once we had controlled for the relative price of total investment.
These results are not that surprising since one would expect relative price effects to be more systematically related to variations in the trade balance rather than the current account. When we included the contemporaneous rather than lagged change in the real exchange rate in the regressions and instrumented this variable with its lags, the coefficients were negative and slightly larger, but were still not statistically significant.