An arbitrage free trilateral target zone model

This paper analyzes credibility in the Colombian exchange rate target zone. A model of imperfect credibility, in the spirit of Bertola and Svensson (1993) is derived, and is used to explain why the exchange rate in Colombia has remained for prolonged periods near the borders of the zone. The main feature of the model is that central parity depreciation expectations are endogenous with respect to the position of the exchange rate inside the target zone. The krugman(1991) perfectly credible setup turns out to be a particular case of this general model. One of the main implications of the model is that depreciation expectations increase rather than decrease as the exchange rate approaches the upper band. Hence a model as the one presented in this paper, is useful to explain the recent dynamics of interest rates in Colombia. It is also shown, that this model shares empirical features with the basic target zone model. Hence, policy makers might be misled when trying to recognize their credibility stance. A estructural estimation of the underlying parameters of the model, using McFadden's (1989) method of simulated moments, is suggested to identify the presence of non credibility issues. Econometric evidence suggest that Colombia's exchange rate target zone is properly described by a model of this nature.

Estimating Nonlinear DSGE Models by the Simulated Method of Moments

This article considers the estimation of the parameters of a copula via a simulated method of moments (MM) type approach. This approach is attractive when the likelihood of the copula model is not known in closed form, or when the researcher has a set of dependence measures or other functionals of the copula that are of particular interest. The proposed approach naturally also nests MM and generalized method of moments estimators. Drawing on results for simulation-based estimation and on recent work in empirical copula process theory, we show the consistency and asymptotic normality of the proposed estimator, and obtain a simple test of overidentifying restrictions as a specification test. The results apply to both iid and time series data. We analyze the finite-sample behavior of these estimators in an extensive simulation study. We apply the model to a group of seven financial stock returns and find evidence of statistically significant tail dependence, and mild evidence that the dependence between these assets is stronger in crashes than booms. Supplementary materials for this article are available online.

Part 1 International policy co-ordination and exchange rate management: the European monetary system, exchange rate expectations and the reputation of authorities, P.Artus would US protectionism be a threat to economic stability?, A.J.Hughes Hallett and G.J.Huston international adjustment and the dollar - a game theoretic approach, J.C.Martinez Oliva exchange rates and policy co-ordination in an asymmetric model, P.Kennen international policy co-ordination, imperfect information and target zones, A.Bisin and P.Tedeschi target zones, currency options and the dollar, P.Weller. Part 2 Strategic aspects of international policy co-ordination: time inconsistency, discounting and the returns to co-operation, M.Miller, et al policy co-operation among benevolent governments may be undesirable - an extension, P.J.Kehoe can international policy co-ordination really be counterproductive?, C.Carraro and F.Giavazzi profit shifting motives and international trade union co-ordination, D.Laussel and A.Soubeyran. Part 3 Information and uncertainty: robust lyapunov games under bounded uncertainty, C.Diessenberg asymmetric information and policy co-ordination, M.Cripps international policy co-ordination in a world with model uncertainty, A.R.Ghosh and P.R.Masson.

We propose an importance-sampling procedure to improve the computational performance of the simulated method of moments (SMM) for the estimation of structural models with fixed parameter heterogeneity. The main advantage of the procedure is that it does not require to simulate observations every time that the structural parameters change during the minimization of the SMM criterion function. We illustrate the use of our method by estimating a neoclassical model of investment for a sample of US manufacturing companies, allowing the technological parameters to vary across firms.

Utility-Based Pricing of the Weather Derivatives

In this chapter, we briefly review two other methods for exploiting moment conditions in estimation. Section 10.1 describes simulation based estimators known as Simulated Method of Moments, Indirect Inference and Efficient Method of Moments. Section 10.2 describes the method of Empirical Likelihood. The purpose of this discussion is to provide the intuition behind the methods in question and to explain their connections to GMM. References are provided for those readers interested in a rigourous analysis of the statistical properties of these estimators.

Methods to estimate dynamic stochastic general equilibrium models

Estimation of endogenously sampled time series: The case of commodity price speculation in the steel market

The Credibility of the European Monetary System: A Review

The paper considers two rival models referring to the new macroeconomic consensus: a standard three-equation model of the New-Keynesian variety versus dynamic adjustments of a business and an inflation climate in an ‘Old-Keynesian’ tradition. Over the two subperiods of the Great Inflation and Great Moderation, both of them are estimated by the method of simulated moments. An innovative feature is here that the moments do not only include the autocovariances up to eight lags of quarterly output, inflation and the interest rate, but optionally also a measure of the raggedness of the three variables. In short, the performance of the Old-Keynesian model is very satisfactory and similar to the New-Keynesian model, or even better. In particular, the Old-Keynesian model is better suited to match the new moments without deteriorating the original second moments too much.

Exchange rate fluctuations, plant turnover and productivity

We use simulation methods to impute missing data. First we suggest how one can iteratively estimate a large number of parameters associated with a joint normal distribution function fof latent variable associated with the data. We suggest a way to test the joint normality assumption next. Finally, we propose a method to use draws from the estimated distribution efficiently in a method of simulated moments or simulated maximum likelihood procedure. In the second half of the paper, we apply the proposed methods ot two data sets from Jamaica with significant missing data problems. We find that the procedure provides better parameter estimates in simple models than present popular methods

For multivariate datasets with missing values, we present a procedure of statistical inference and state its “optimal” properties. Two main assumptions are needed: 1 data are missing at random (MAR); 2 the data generating process is a multivariate normal linear regression. Disentangling the problem of convergence of the iterative estimation/imputation procedure, we show that the estimator is a “method of simulated scores” (a particular case of McFadden’s “method of simulated moments”); thus the estimator is equivalent to maximum likelihood if the number of replications is conveniently large, and the whole procedure can be considered an optimal parametric technique for imputation of missing data.

This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated as closely as one pleases by a MMNL model. Practical estimation of a parametric mixing family can be carried out by Maximum Simulated Likelihood Estimation or Method of Simulated Moments, and easily computed instruments are provided that make the latter procedure fairly efficient. The adequacy of a mixing specification can be tested simply as an omitted variable test with appropriately defined artificial variables. An application to a problem of demand for alternative vehicles shows that MMNL provides a flexible and computationally practical approach to discrete response analysis. Copyright © 2000 John Wiley & Sons, Ltd.