Next Article in Journal
Selection Criteria in Regime Switching Conditional Volatility Models
Previous Article in Journal
Detecting Location Shifts during Model Selection by Step-Indicator Saturation
Previous Article in Special Issue
Finding Starting-Values for the Estimation of Vector STAR Models
Article Menu

Export Article

Open AccessArticle
Econometrics 2015, 3(2), 265-288; doi:10.3390/econometrics3020265

Nonparametric Regression Estimation for Multivariate Null Recurrent Processes

Department of Mathematics, University of Bergen, 5020 Bergen, Norway
*
Author to whom correspondence should be addressed.
Academic Editor: Timo Teräsvirta
Received: 26 November 2014 / Revised: 27 March 2015 / Accepted: 2 April 2015 / Published: 14 April 2015
(This article belongs to the Special Issue Non-Linear Regression Modeling)
View Full-Text   |   Download PDF [532 KB, uploaded 14 April 2015]   |  

Abstract

This paper discusses nonparametric kernel regression with the regressor being a \(d\)-dimensional \(\beta\)-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate \(\sqrt{n(T)h^{d}}\), where \(n(T)\) is the number of regenerations for a \(\beta\)-null recurrent process and the limiting distribution (with proper normalization) is normal. Furthermore, we show that the two-step estimator for the volatility function is consistent. The finite sample performance of the estimate is quite reasonable when the leave-one-out cross validation method is used for bandwidth selection. We apply the proposed method to study the relationship of Federal funds rate with 3-month and 5-year T-bill rates and discover the existence of nonlinearity of the relationship. Furthermore, the in-sample and out-of-sample performance of the nonparametric model is far better than the linear model. View Full-Text
Keywords: β-null recurrent; cointegration; conditional heteroscedasticity; Markov chain; nonparametric regression β-null recurrent; cointegration; conditional heteroscedasticity; Markov chain; nonparametric regression
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Cai, B.; Tjøstheim, D. Nonparametric Regression Estimation for Multivariate Null Recurrent Processes. Econometrics 2015, 3, 265-288.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Econometrics EISSN 2225-1146 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top