Skip to main content
padlock icon - secure page this page is secure

Expectile and Quantile Kink Regressions with Unknown Threshold

Buy Article:

$106.51 + tax (Refund Policy)

In this study, we propose two non-linear models for explaining the relationship between the response and the predictor variables beyond the conditional mean. We extend the kink approach to quantile and expcetile regressions thus the models provide a more complete picture of the conditional distribution of the response variable in the non-linear context. The proposed models allow us to identify and explore the reputation effect and its heterogeneity in data. The simulation and application studies are also proposed to examine the performance of our models. We find that neither of the approaches is uniformly superior nor both of them have their advantages over each other and it is not clear which model provides the best fit results. However, the application of our models on a service output data shows that expectile kink regression is more conservative than the quantile kink regression.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Expectile and Qunatile Regressions; Kink Effect; Service Sector Output

Document Type: Research Article

Affiliations: Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

Publication date: November 1, 2017

More about this publication?
  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more