This paper aims to propose an innovative approach to identify group effects in a quantile regression model. Quantile regression is a quite recent regression technique that allows to focus on the effects that a set of explanatory variables have on the entire conditional distribution of the dependent variable. The proposal concerns the use of a stratification variable in order to detect effects attributable to different group membership. An empirical analysis is also provided to measure the changes on job satisfaction owing to modification of the evaluation of different job features and taking into account the type of job (self-employed, private employee or public employee). This latter variable is used to estimate the group effects.
Quantile regression for group effect analysis
VISTOCCO, Domenico
2010-01-01
Abstract
This paper aims to propose an innovative approach to identify group effects in a quantile regression model. Quantile regression is a quite recent regression technique that allows to focus on the effects that a set of explanatory variables have on the entire conditional distribution of the dependent variable. The proposal concerns the use of a stratification variable in order to detect effects attributable to different group membership. An empirical analysis is also provided to measure the changes on job satisfaction owing to modification of the evaluation of different job features and taking into account the type of job (self-employed, private employee or public employee). This latter variable is used to estimate the group effects.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
