Jerome L. Stein

Equilibrium exchange rates

List of Contributors. 1. Introduction: Equilibrium Exchange Rates R. MacDonald, J.L. Stein. 2. What Do We Really Know about Real Exchange Rates? R. MacDonald. 3. The Evolution of the Real Value of the US Dollar Relative to the G7 Currencies J.L. Stein. 4. A Macroeconomic Balance Framework for Estimating Equilibrium Exchange Rates H. Faruqee, et al. 5. Feers: A Sensitivity Analysis R. Driver, S. Wren-Lewis. 6. Productivity, Government Spending and the Real Exchange Rate: Evidence for OECD Countries M.D. Chinn. 7. Fundamentals of the Real Dollar-Pound Rate: 1871-1994 N.C. Mark. 8. Nominal Equilibrium Exchange Rate Models: A Panel Perspective S. Husted, R. MacDonald. 9. What Determines Real Exchange Rates: The Long and Short Of It R. MacDonald. 10. Exchange Rates and Economic Fundamentals: A Methodological Comparison of Beers and Feers P.B. Clark, R. MacDonald. 11. Japanese Effective Exchange Rates and Determinants: A Long-Run Perspective J. Nagayasu. Index.

Fundamental Determinants of Exchange Rates

Existing models fail to explain the large fluctuations in the real exchange rates of most currencies over the past twenty years. The Natural Real Exchange Rate approach (NATREX) taken here offers an alternative paradigm to those which focus on short-run movements of nominal eschange rates, purchasing power parity of the representative agent intertemporal optimization models. Yet it is also neo-classical in its stress upon the accepted fundamentals driving a real economy. It concentrates on the real exchange rate, and explains medium- tolong-run movements in equilibrium real exchange rates in terms of fundamental variables: the productivity of capital and social (public plus private) thrift at home and abroad. The NATREX approach is a family of growth models, each tailored to the characteristics of the countries considered. The authors explain the real international value of the US dollar relativ to the G10 countries, and the US current account. These are two large economies. The model is also applied to small economies, where it explains the real value of the Australian dollar and the Latin American currencies relative to the US dollar. The model is relevant for developing countries where the foreign debt is a concern. Finally, it is applied to two medium-sized economies to explain the bilateral exchange rate between the French franc and the Deutsche Mark. The authors demonstrate both the promise of the NATREX model and its applicability to economies large and small. Alongside the analysis, econometrics, and technical details of these case studies, the introductory chapter explains in accessible terms the rationale behind the approach. The mix of theory and empirical evidence makes this book relevant to academics and advanced graduate students, and to central banks, ministries of finance, and those concerned with the foreign debt of developing countries.

The real exchange rate

Abstract This essay concerns the real value of the

A Tale of Two Debt Crises: A Stochastic Optimal Control Analysis

U.S. relative to the G-10. (i) What are the dynamics of the fundamental determinants of the real exchange rate and its steady state value? (ii) To what extent are the observed movements in the exchange rate from 1973 to 1988 due to the fundamentals? (iii) How integrated are international capital markets? (iv) How does the real exchange rate respond to (a) changes in the cyclically adjusted government budget deficit, and to (b) changes in the marginal efficiency of investment?

Stochastic Optimal Control, International Finance and Debt

Banks should evaluate whether a borrower is likely to default. The author applies several techniques in the extensive mathematical literature of stochastic optimal control/dynamic programming to derive an optimal debt in an environment where there are risks on both the asset and liabilities sides. The vulnerability of the borrowing firm to shocks from either the return to capital, the interest rate or capital gain, increases in proportion to the difference between the Actual and Optimal debt ratio, called the excess debt. As the debt ratio exceeds the optimum, default becomes ever more likely. This paper is A Tale of Two Crises because the analysis is applied to the agricultural debt crisis of the 1980s and to the sub-prime mortgage crisis of 2007. A measure of excess debt is derived, and the author shows that it is an early warning signal of a crisis.

APPLICATION OF STOCHASTIC OPTIMAL CONTROL TO FINANCIAL MARKET DEBT CRISES

We use stochastic optimal control-dynamic programming (DP) to derive the optimal foreign debt/net worth, consumption/net worth, current account/net worth, and endogenous growth rate in an open economy. Unlike the literature that uses an Intertemporal Budget Constraint (IBC) or the Maximum Principle, the DP approach does not require perfect foresight or certainty equivalence. Errors of measurement and the effects of unanticipated shocks are corrected in an optimal manner. We contrast the DP and IBC approaches, show how the results of the dynamic programming approach can be interpreted in a traditional simple mean-variance/Tobin-Markowitz context, and explain why our results are generalizations of the Merton model.

A Critique of the Literature on the US Financial Debt Crisis

This interdisciplinary paper explains how mathematical techniques of stochastic optimal control can be applied to the recent subprime mortgage crisis. Why did the financial markets fail to anticipate the recent debt crisis, despite the large literature in mathematical finance concerning optimal portfolio allocation and stopping rules? The uncertainty concerns the capital gain, the return on capital and the interest rate. An optimal debt ratio is derived where the drift is probabilistic but subject to economic constraints. The crises occurred because the market neglected to consider pertinent economic constraints in the dynamic stochastic optimization. The first constraint is that the firm should not be viewed in isolation. The optimizer should be the entire industry. The second economic constraint concerns the modeling of the drift of the price of the asset. The vulnerability of the borrowing firm to shocks from the capital gain, the return to capital or the interest rate, does not depend upon the actual debt/net worth per se. Instead it increases in proportion to the difference between the Actual and Optimal debt ratio, called the excess debt. A general measure of excess debt is derived and I show that it is an early warning signal of the recent crisis.

Methodological issues in asset pricing: Random walk or chaotic dynamics

A healthy financial system encourages the efficient allocation of capital and risk. The collapse of the house price bubble led to the financial crisis that started in 2007. There is a large empirical literature concerning the relation between asset price bubbles and financial crises. I evaluate the key studies with the respect to the following questions. To what extent do the empirical relations in the existing literature help to identify asset price bubbles ex-ante or ex-post? Do the empirical studies have theoretical foundations? On the basis of that critique, I explain why the application of stochastic optimal control (SOC)/dynamic risk management is a much more effective approach to determine the optimal degree of leverage, the optimum and excessive risk and the probability of a debt crisis. The theoretically founded early warning signals of a crisis are shown to be superior, in general, to those empirical relations in the literature. Moreover the SOC analysis provides a theoretical explanation of the extent that the empirical measures in the literature can be useful.

The Evolution of the Real Value of the US Dollar Relative to the G7 Currencies

Abstract We analyze the theoretical foundations of the efficient market hypothesis by stressing the efficient use of information and its effect upon price volatility. The “random walk” hypothesis assumes that price volatility is exogenous and unexplained. Randomness means that a knowledge of the past cannot help to predict the future. We accept the view that randomness appears because information is incomplete. The larger the subset of information available and known, the less emphasis one must place upon the generic term randomness. We construct a general and well accepted intertemporal price determination model, and show that price volatility reflects the output of a higher order dynamic system with an underlying stochastic foundation. Our analysis is used to explain the learning process and the efficient use of information in our archetype model. We estimate a general unrestricted system for financial and agricultural markets to see which specifications we can reject. What emerges is that a system very close to our archetype model is consistent with the evidence. We obtain an equation for price volatility which looks a lot like the GARCH equation. The price variability is a serially correlated variable which is affected by the Bayesian error, and the Bayesian error is a serially correlated variable which is affected by the noisiness of the system. In this manner we have explained some of the determinants of what has been called the “randomness” of price changes.

Recent developments in international finance: A guide to research

When exchange rates were floated in the early 1970s, economists had certain expectations about the consequences. Nominal exchange rates would be as stable as the macroeconomic “fundamentals” and speculation would be based upon rational expectations. The real exchange rate would be stationary, and the nominal exchange rate would move proportionately with relative prices, which are determined by relative money stocks/GDP. This is referred to as the Monetary Model-PPP hypothesis. By the mid 1980s, economists concluded that these expectations were belied.