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I -- Introduction -- 1.1 Purpose and Outline of the Study -- 1.2 Review of the Literature on Regression Models with Random and Fixed Coefficients -- 1.3 Conclusions -- II -- Efficient Methods of Estimating a Regression Equation with Equicorrelated Disturbances -- 2.1 Introduction -- 2.2 Some Useful Lemmas -- 2.3 A Regression Model with Equicorrelated Disturbances -- 2.4 Analysis of Time Series of Cross-Sections -- 2.5 Estimation When the Variance-Covariance Matrix of Disturbances is Singular -- 2.6 Estimation When the Remaining Effects are Heteroskedastic -- 2.7 Conclusions -- III -- Efficient Methods of Estimating the Error Components Regression Models -- 3.1 Introduction -- 3.2 Some Matrix Results -- 3.3 Covariance Estimators -- 3.4 Estimation of Error Components Models -- 3.5 A Class of Asymptotically Efficient Estimators -- 3.6 Small Sample Properties of the Pooled Estimator -- 3.7 A Comparison of the Efficiencies of Pooled and OLS Estimators -- 3.8 A Comparison of the Efficiency of Pooled Estimator with Those of its Components -- 3.9 Alternative Estimators of Slope Coefficients and the Regression on Lagged Values of the Dependent Variables -- 3.10 Analysis of an Error Components Model Under Alternative Assumptions -- 3.11 Maximum Likelihood Method of Estimating Error Components Model -- 3.12 Departures from the Basic Assumptions Underlying the Error Components Model -- 3.13 Conclusions -- IV -- Statistical Inference in Random Coefficient Regression Models Using Panel Data -- 4.1 Introduction -- 4.2 Setting the Problem -- 4.3 Efficient Methods of Estimating the Parameters of RCR Models -- 4.4 Estimation of Parameters in RCR Models when Disturbances are Serially Correlated -- 4.5 Problems Associated with the Estimation of RCR Models Using Aggregate Data -- 4.6 Forecasting with RCR Models -- 4.7 Relaxation of Assumptions Underlying RCR Models -- 4.8 Similarities Between RCR and Bayesian Assumptions -- 4.9 Empirical CES Production Function Free of Management Bias -- 4.10 Analysis of Mixed Models -- 4.11 Conclusions -- V -- A Random Coefficient Investment Model -- 5.1 Introduction -- 5.2 Grunfeld's Hypothesis of Micro Investment Behavior -- 5.3 Estimation and Testing of Random Coefficient Investment Model -- 5.4 Aggregate Investment Function -- 5.5 Comparison of Random Coefficient Model with Fixed Coefficient Macro Model -- 5.6 Comparison of Random Coefficient Model with Fixed Coefficient Micro Model -- 5.7 Conclusions -- VI -- Aggregate Consumption Function with Coefficients Random Across Countries -- 6.1 Introduction -- 6.2 Aggregate Consumption Model -- 6.3 Source and Nature of Data -- 6.4 Fixed Coefficient Approach -- 6.5 Random Coefficient Approach -- 6.6 Conclusions -- VII -- Miscellaneous Topics -- 7.1 Introduction -- 7.2 Identification -- 7.3 Incorporation of Prior Information in the Estimation of RCR Models -- 7.4 Conclusions.

All pegged exchange rate arrangements are subject to predicaments that cast doubt on the ability of the policy makers to maintain the peg. This article organizes the literature dealing with the fragility of exchange rate nominal-anchor regimes around six fundamental & interrelated problems that can undermine the ability of policy makers to maintain their commitment to an exchange rate peg. It describes the regime-specific characteristics of an international monetary system comprising both floating rates & pegged rates -- the operating domain of a nominal-anchor peg -- that produce externalities relative to a pure float or a fixed-rate regime. Those externalities can lead to instability for small countries that peg to the currency of a large country, magnify the effects of asymmetric shocks on exchange rates against third currencies, & provide an escape mechanism that may help absolve the policy makers of the disciplinary constraint of a pure peg. 50 References. [Copyright 2002 Sage Publications, Inc.]

A recent contribution to the literature argues that the present international monetary system operates like the Bretton‐Woods system. Asia is the new periphery of the system and pursues an export‐led development strategy based on undervalued exchange rates and accumulated foreign reserves. The USA remains the centre country, pursuing a monetary‐policy strategy that does not take external factors into account in conducting monetary policy. We test this hypothesis and also present a new method for decomposition of a time series using a time‐varying business coefficient technique that allows us to test the relationship between the cycle and macroeconomic policies under both regimes.