We propose a two-step local polynomial and a weighted bootstrapped estimator for the parameter functions of a time varying GARCH(p,q) model. We also suggest a test statistic for testing the constancy of parameter functions of the model. Asymptotic distributions of the estimators and a test...

We provide methods for inference on a finite dimensional parameter of interest, theta in Re^{d_theta}, in a semiparametric probability model when an infinite dimensional nuisance parameter, g, is present. We depart from the semiparametric literature in that we do not require that the pair...

Motivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density...

Purpose – This paper aims to test the finite sample properties of the automatic variance ratio (AVR) test and suggest suitable measure to improve its small sample properties under conditional heteroskedasticity and apply it to test the martingale hypothesis in the stock prices of the Portugal,...

This article discusses the general problem of generating representative point sets from a distribution known up to a multiplicative constant. The sampling/importance resampling (SIR) algorithm is known to be useful in this context. Moreover, the quasi-random sampling/importance resampling (QSIR)...

Counterfactual distributions are important ingredients for policy analysis and de-composition analysis in empirical economics. In this article we develop modelling and inference tools for counterfactual distributions based on regression methods. The counterfactual scenarios that we consider...

Purpose – This paper aims to test the finite sample properties of the automatic variance ratio (AVR) test and suggest suitable measure to improve its small sample properties under conditional heteroskedasticity and apply it to test the martingale hypothesis in the stock prices of the Portugal,...

A multiplier bootstrap procedure for construction of likelihood-based condence sets is considered for nite samples and a possible model misspecication. Theoretical results justify the bootstrap consistency for a small or moderate sample size and allow to control the impact of the parameter...

We revisit the twofold identification problem discussed by Cho, Ishida, and White (Neural Computation, 2011), which arises when testing for neglected nonlinearity by artificial neural networks. We do not use the so-called ¡°no-zero¡± condition and employ a sixth-order expansion to obtain the...

Motivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density...