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When constructing hedged interest rate arbitrage portfolios for basket currencies, two issues arise: first, how are the unknown future basket weights optimally forecasted from past exchange rate data? And, second, how is risk—in terms of the conditional variance of expected profits from the interest rate arbitrage portfolio—appropriately measured when the basket weights are time-varying? Answers to these questions are provided within a time-varying parameter modeling framework estimated through the Kalman filter. An empirical application is devoted to the experience of the Thai baht currency basket (January 1992–February 1997).

Imposing cointegration on a forecasting system, if cointegration is present, is believed to improve long-horizon forecasts. Contrary to this belief, at long horizons nothing is lost by ignoring cointegration when the forecasts are evaluated using standard multivariate forecast accuracy measures. In fact, simple univariate Box-Jenkins forecasts are just as accurate. Our results highlight a potentially important deficiency of standard forecast accuracy measures—they fail to value the maintenance of cointegrating relationships among variables—and we suggest alternatives that explicitly do so.

This paper reexamines growth in transition using panel data to 1997. It suggests that output has been strongly affected by export market growth; that inflation has been associated with weaker output only above a threshold inflation rate; that structural reform has been associated with weaker output initially, but that it stimulates higher growth thereafter; and that rapid disinflation has been associated with output losses only in the presence of pegged exchange rates.

Monetary policymakers in advanced transition economies such as Poland are increasingly interested in how inflation responds to changes in policy instruments and other economic forces. In this paper, measures of underlying CPI inflation based upon optimal trimming concepts are developed. The sensitivity of these CPI measures to changes in a set of 25 policy and economic variables is then studied via Granger causality tests and impulse responses and a multivariate model of CPI inflation developed. The results show that a core set of variables characterize one-period-ahead underlying inflation moderately well but that statistical linkages are not yet robust.