January 1998. I am grateful for research assistance from Qiming Chen,

During the past few years, many countries have suffered severe currency and banking crises, producing a staggering toll on their economies, particularly in emerging-market countries. In many cases, the cost of restructuring the banking sector has been in excess of 20 per cent of GDP, and output declines in the wake of crisis have been as large as 14 per cent. An increasingly popular view blames fixed exchange rates, specifically “soft pegs, ” for these financial meltdowns. Not surprisingly, adherents to that view advise emerging markets to join the ranks of the United States and other industrial countries that have chosen to allow their currency to float freely. (See, for example, Goldstein 1999.) At first glance, the world—with the notable exception of Europe—does seem to be marching steadily towards floating exchange rate arrangements. According to the International Monetary Fund (IMF), 97 per cent of its member countries in 1970 were classified as having a pegged exchange rate; by 1980, that share had declined to 39 per cent, and in 1999, it was down to only 11 per cent. 1 Yet, this much-used IMF classification takes at face value that countries actually do what they say they do. Even a cursory perusal of the Asian crisis countries ’ exchange rates prior to the 1997 crisis would suggest that their exchange rates looked very much like pegs to the U.S. dollar for extended periods of time. Only Thailand, however, was explicitly classified as a peg; the Philippines was listed as having a freely floating

to stimulate discussion and critical comment. References in publications to International Finance Discussion Papers (other than an acknowledgment that the writer has Some recent studies have suggested constructing a Monetary Conditions Index (or MCI) to serve as an indicator of monetary policy stance. The central banks of Canada, Sweden, and Norway all construct an MCI and (to varying degrees) use it in conducting monetary policy. Empirically, an MCI is calculated as the weighted sum of changes in a short-term interest rate and the exchange rate relative to values in a baseline year. The weights aim to re°ect these variables ' e®ects on longer-term focuses of policy | economic activity and in°ation. This paper derives analytical and empirical properties of MCIs in an attempt to ascertain their usefulness in monetary policy. An MCI assumes an underlying model relating economic activity and in°ation to the variables in the MCI. Several issues arise for that model, including its empirical constancy, cointegration, exogeneity, dynamics, and potential omitted variables. Because of its structure, the model is unlikely to be constant or to have strongly exogenous variables; and we show that constancy and exogeneity are critical for the usefulness of an MCI. Empirical analyses of Canadian, Swedish, and Norwegian MCIs con¯rm such di±culties. Thus, the value of an MCI for conduct of economic policy is in doubt.

The views expressed in this paper are those of the author. No responsibility for them should be attributed to the Bank of Canada. The methods proposed in this study are part of the ongoing research at the Bank on potential output and do not represent official measures of this concept. Contents Acknowledgements........................................................................................................................ iv Abstract............................................................................................................................................v

The main purpose of this paper is to review and interpret the use of a Monetary Conditions Index (or MCI) by central banks in the conduct of monetary policy. Numerous central banks, governmental organizations, and businesses now calculate an MCI as an indicator of the stance of monetary policy. Two central banks, those for Canada and New Zealand, use their MCIs as operational targets. This paper describes and defines the concept of an MCI, summarizes how central banks implement MCIs in practice, reviews some of the operational and conceptual issues involved, and evaluates the sensitivity of MCIs to an inherent source of uncertainty in their calculation. Empirically, this uncertainty typically results in MCIs that are uninformative as indicators of monetary conditions, so some possible alternatives are briefly considered. 1 A Monetary Conditions Index in practice Several central banks calculate a Monetary Conditions Index for use in monetary policy. Empirically, an MCI is a weighted average of changes in an interest rate and an exchange rate relative to their values in a base period. The weights on the

† Also affiliated with the Centre for Research on Economic Fluctuations and Employment, Université du

In this paper we examine the relative merits of simple monetary policy rules in the context of a small open economy. Rules considered are ones that target: the exchange rate, price level, nominal income or a monetary aggregate. The standard framework that has been employed for previous comparisons of these rules fails to take account of important features of small open economies. In particular, the standard framework fails to consider the effects on aggregate supply of exchange rate adjustments that result from adherence to policy rules. Incorporating such effects is shown to weaken the case for targeting nominal income and, more Recognition of possible time inconsistency problems when monetary policy is conducted in a discretionary setting has led to increased interest in simple policy rules. Suggested simple rules include ones to target: the exchange rate, the price level (or inflation rate), nominal income or a monetary aggregate. A rule to target

Comments welcome.

Bank of Canada working papers are theoretical or empirical works-in-progress on subjects in economics and finance. The views expressed in this paper are those of the author. No responsibility for them should be attributed to the Bank of Canada.

This paper presents a quarterly structural model of the Israeli economy which delineates the transmission mechanism of the monetary policy during the years 1989-1999 and allows to evaluate the short run consequences of various exogenous shocks on both the nominal and the real sectors of the economy. The main endogenous variables of the model are the business sector output gap, the real exchange rate, the inflation rate, the Bank of Israel (BoI) short-term nominal interest rate and the rate of change of the business sector nominal wages. The estimated model is stable and exhibits to a large extent the expected properties in response to supply and demand shocks. The model specification and the estimation results give rise to a nominal transmission channel and a real activity transmission channel of the monetary policy to prices. Unlike large and relatively closed