Similar Search Results

Unit roots : identification and testing in micro panels

Bond, Stephen (contributor); Nauges, Céline (contributor); … - 2005

Persistent link: https://www.econbiz.de/10002996750

Non-parametric transformation regression with non-stationary data

Linton, Oliver; Wang, Qiying - 2013

proposed by Xiao et al. (2008). We show that this method continues to improve estimation in the case where the regressor is a …

Persistent link: https://www.econbiz.de/10009734305

Nonparametric estimation of a periodic sequence in the presence of a smooth trend

Vogt, Michael; Linton, Oliver - 2012

In this paper, we study a nonparametric regression model including a periodic component, a smooth trend function, and a stochastic error term. We propose a procedure to estimate the unknown period and the function values of the periodic component as well as the nonparametric trend function. The...

Persistent link: https://www.econbiz.de/10009614392

Estimation of stochastic volatility models by nonparametric filtering

Kanaya, Shin; Kristensen, Dennis - 2015

A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically … estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed … estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps …

Persistent link: https://www.econbiz.de/10010487528

Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction

Cheng, Tingting; Gao, Jiti; Linton, Oliver - 2018

nonstationary. We also establish the estimation theory and asymptotic properties for these models in the short horizon and long …

Persistent link: https://www.econbiz.de/10011775136

Perceived shocks and impulse responses

Giacomini, Raffaella; Lu, Jason; Smetanina, Katja - 2024

This paper develops a novel approach that leverages the information contained in expectations datasets to derive empirical measures of beliefs regarding economic shocks and their dynamic effects. Utilizing a panel of expectation revisions for a single variable across multiple horizons, we...

Persistent link: https://www.econbiz.de/10015123512

Let's get LADE : robust estimation of semiparametric multiplicative volatility models

Koo, Bonsoo; Linton, Oliver - 2013

robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility … propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long … run volatility function. Our estimation is based on a two-step LAD procedure. We establish the relevant asymptotic theory …

Persistent link: https://www.econbiz.de/10009719116

Additive nonparametric models with time variable and both stationary and nonstationary regressions

Dong, Chaohua; Linton, Oliver - 2017

include a linear form of the integrated variable. Heteroscedasticity is allowed for in all models. We propose an estimation …

Persistent link: https://www.econbiz.de/10011775349

Policy choice in time series by empirical welfare maximization

Kitagawa, Toru; Wang, Weining; Xu, Mengshan - 2024

This paper develops a novel method for policy choice in a dynamic setting where the available data is a multi-variate time series. Building on the statistical treatment choice framework, we propose Time-series Empirical Welfare Maximization (T-EWM) methods to estimate an optimal policy rule by...

Persistent link: https://www.econbiz.de/10015168545

Sieve inference on semi-nonparametric time series models

Chen, Xiaohong; Liao, Zhipeng; Sun, Yixiao - 2012

The method of sieves has been widely used in estimating semiparametric and nonparametric models. In this paper, we first provide a general theory on the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi/nonparametric time series models. Next, we...

Persistent link: https://www.econbiz.de/10009504597