Risk related non linearities in exchange rates: A comparison of parametric and semiparametric estimates
نویسندگان
چکیده
This paper uses semiparametric techniques to estimate a model of exchange rate determination and compare it to a parametric LSTAR specification. In both cases the nonlinearities are modeled as part of the conditional mean of the process, rather than of its variance. Using a panel dataset for five East European countries for years 1993 2001, it results that the non parametric data-driven estimates perform a little better but actually support the LSTAR specification. The dependence of current on lagged exchange rates is confirmed to be non linear, with marginal effects that become very significant and negative for abnormal values of the lagged variable. The PPP hypothesis, is not rejected by the data.
منابع مشابه
Generalized Ridge Regression Estimator in Semiparametric Regression Models
In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...
متن کاملExtended Geometric Processes: Semiparametric Estimation and Application to ReliabilityImperfect repair, Markov renewal equation, replacement policy
Lam (2007) introduces a generalization of renewal processes named Geometric processes, where inter-arrival times are independent and identically distributed up to a multiplicative scale parameter, in a geometric fashion. We here envision a more general scaling, not necessar- ily geometric. The corresponding counting process is named Extended Geometric Process (EGP). Semiparametric estimates are...
متن کاملRegression Modeling for Spherical Data via Non-parametric and Least Square Methods
Introduction Statistical analysis of the data on the Earth's surface was a favorite subject among many researchers. Such data can be related to animal's migration from a region to another position. Then, statistical modeling of their paths helps biological researchers to predict their movements and estimate the areas that are most likely to constitute the presence of the animals. From a geome...
متن کاملModeling Probabilities of Patent Oppositions in a Bayesian Semiparametric Regression Framework
Most econometric analyses of patent data rely on regression methods using a parametric form of the predictor for modeling the dependence of the response given certain covariates. These methods often lack the capability of identifying non-linear relationships between dependent and independent variables. We present an approach based on a generalized additive model in order to avoid these shortcom...
متن کاملSemiparametric Estimation of Risk-return Relationships
This article proposes semiparametric least squares estimation of parametric risk-return relationships, i.e. parametric restrictions between the conditional mean and the conditional variance of excess returns given a set of unobservable parametric factors. A distinctive feature of our estimator is that it does not require a parametric model for the conditional mean and variance. We establish con...
متن کامل