Posted Content•
The role and nature of market sentiment in the 1992 ERM crisis.
TL;DR: In this article, the authors explain the role of speculators in determining the 1992 ERM crisis and the effects that the policy of maintaining external parity had on internal growth, focusing on a different way through which expectations are formed about the macroeconomic fundamentals independently of the behaviour of the monetary policy.
Abstract: This paper attempts to explain the importance of the role of the speculators in determining the 1992 ERM crisis, and the effects that the policy of maintaining external parity had on internal growth. We focus on a different way through which expectations are formed about the macroeconomic fundamentals independently of the behaviour of the monetary policy. In the present model, agents’ rational beliefs do not emerge from arbitrary circumstances but only when the value of the exchange rate, kept under control by the central bank, did not correspond to the expected value and to the current wide-spread beliefs in the market.
References
More filters
TL;DR: In this paper, it was shown that discretionary policy does not result in the social objective function being maximized, and that there is no way control theory can be made applicable to economic planning when expectations are rational.
Abstract: Even if there is an agreed-upon, fixed social objective function and policymakers know the timing and magnitude of the effects of their actions, discretionary policy, namely, the selection of that decision which is best, given the current situation and a correct evaluation of the end-of-period position, does not result in the social objective function being maximized. The reason for this apparent paradox is that economic planning is not a game against nature but, rather, a game against rational economic agents. We conclude that there is no way control theory can be made applicable to economic planning when expectations are rational.
7,652 citations
Book•
21 Nov 1994
TL;DR: In this article, the authors present an alternative solution method for Deterministic Processes by iteratively solving homogeneous difference equation and finding particular solutions for deterministic processes, and conclude that the proposed solution is the best solution.
Abstract: PREFACE. ABOUT THE AUTHOR. Chapter DIFFERENCE EQUATIONS . 1 Time-Series Models. 2 Difference Equations and Their Solutions. 3 Solution by Iteration. 4 An Alternative Solution Methodology. 5 The Cobweb Model. 6 Solving Homogeneous Difference Equations. 7 Finding Particular Solutions for Deterministic Processes. 8 The Method of Undetermined Coefficients. 9 Lag Operators. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Imaginary Roots and de Moivre's Theorem. Appendix 2 Characteristic Roots in Higher-Order Equations. Chapter 2 STATIONARY TIME-SERIES MODELS . 1 Stochastic Difference Equation Models. 2 ARMA Models. 3 Stationarity. 4 Stationarity Restrictions for an ARMA(p, q) Model. 5 The Autocorrelation Function. 6 The Partial Autocorrelation Function. 7 Sample Autocorrelations of Stationary Series. 8 Box-Jenkins Model Selection. 9 Properties of Forecasts. 10 A Model of the Interest Rate Spread. 11 Seasonality. 12 Parameter Instability and Structural Change. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Estimation of an MA(1) Process. Appendix 2 Model Selection Criteria. Chapter 3 MODELING VOLATILITY . 1 Economic Time Series The Stylized Facts. 2 ARCH Processes. 3 ARCH and GARCH Estimates of Inflation. 4 Two Examples of GARCH Models. 5 A GARCH Model of Risk. 6 The ARCH-M Model. 7 Additional Properties of GARCH Processes. 8 Maximum Likelihood Estimation of GARCH Models. 9 Other Models of Conditional Variance. 10 Estimating the NYSE International 100 Index. 11 Multivariate GARCH. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Multivariate GARCH Models. Chapter 4 MODELS WITH TREND . 1 Deterministic and Stochastic Trends. 2 Removing the Trend. 3 Unit Roots and Regression Residuals. 4 The Monte Carlo Method. 5 Dickey-Fuller Tests. 6 Examples of the ADF Test. 7 Extensions of the Dickey-Fuller Test. 8 Structural Change. 9 Power and the Deterministic Regressors. 10 Tests with More Power. 11 Panel Unit Root Tests. 12 Trends and Univariate Decompositions. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 The Bootstrap. Chapter 5 MULTIEQUATION TIME-SERIES MODELS . 1 Intervention Analysis. 2 Transfer Function Models. 3 Estimating a Transfer Function. 4 Limits to Structural Multivariate Estimation. 5 Introduction to VAR Analysis. 6 Estimation and Identification. 7 The Impulse Response Function. 8 Testing Hypothesis. 9 Example of a Simple VAR Terrorism and Tourism in Spain. 10 Structural VARs. 11 Examples of Structural Decompositions. 12 The Blanchard and Quah Decomposition. 13 Decomposing Real and Nominal Exchange Rate Movements An Example. Summary and Conclusions. Questions and Exercises. Endnotes. Chapter 6 COINTEGRATION AND ERROR-CORRECTION MODELS . 1 Linear Combinations of Integrated Variables. 2 Cointegration and Common Trends. 3 Cointegration and Error Correction. 4 Testing for Cointegration The Engle-Granger Methodology. 5 Illustrating the Engle-Granger Methodology. 6 Cointegration and Purchasing-Power Parity. 7 Characteristic Roots, Rank, and Cointegration. 8 Hypothesis Testing. 9 Illustrating the Johansen Methodology. 10 Error-Correction and ADL Tests. 11 Comparing the Three Methods. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Characteristic Roots Stability and Rank. Appendix 2 Inference on a Cointegrating Vector. Chapter 7 NONLINEAR TIME-SERIES MODELS . 1 Linear Versus Nonlinear Adjustment. 2 Simple Extensions of the ARMA Model. 3 Regime Switching Models. 4 Testing For Nonlinearity. 5 Estimates of Regime Switching Models. 6 Generalized Impulse Responses and Forecasting. 7 Unit Roots and Nonlinearity. Summary and Conclusions. Questions and Exercises. Endnotes. STATISTICAL TABLES. A. Empirical Cumulative Distributions of the tau. B. Empirical Distribution of PHI . C. Critical Values for the Engle-Granger Cointegration Test. D. Residual Based Cointegration Test with I (1) and I (2) Variables. E. Empirical Distributions of the lambda max and lambda trace Statistics. F. Critical Values for beta 1 = 0 in the Error-correction Model. G. Critical Values for Threshold Unit Roots. REFERENCES. SUBJECT INDEX.
6,373 citations
TL;DR: The authors presented a parsimonious model of investor sentiment, or of how investors form beliefs, based on psychological evidence and produces both underreaction and overreaction for a wide range of parameter values.
3,336 citations
Posted Content•
TL;DR: In this article, the authors develop an example of a reputational equilibrium where the out-comes turn out to be weighted averages of those from discretion and those from the ideal rule.
Abstract: In a discretionary regime the monetary authority can print more money and create more inflation than people expect. But, although these inflation surprises can have some benefits, they cannot arise systematically in equilibrium when people understand the policymaker's incentives and form their expectations accordingly. Because the policymaker has the power to create inflation shocks ex post, the equilibrium growth rates of money and prices turn out to be higher than otherwise. Therefore, enforced commitments (rules) for monetary behavior can improve matters. Given the repeated interaction between the policymaker and the private agents, it is possible that reputational forces can substitute for formal rules.Here, we develop an example of a reputational equilibrium where the out-comes turn out to be weighted averages of those from discretion and those from the ideal rule. In particular, the rates of inflation and monetary growth look more like those under discretion when the discount rate is high.
3,265 citations
TL;DR: In this paper, the authors develop an example of a reputational equilibrium where the outcomes turn out to be weighted averages of those from discretion and those from the ideal rule, when the discount rate is high.
2,935 citations