scholarly journals Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure

Econometrica ◽  
2006 ◽  
Vol 74 (2) ◽  
pp. 539-563 ◽  
Author(s):  
Joshua Angrist ◽  
Victor Chernozhukov ◽  
Ivan Fernandez-Val
2004 ◽  
Author(s):  
Joshua D. Angrist ◽  
Victor Chernozhukov ◽  
Ivan Fernandez-Val

2004 ◽  
Author(s):  
Joshua Angrist ◽  
Victor Chernozhukov ◽  
Ivan Fernandez-Val

Author(s):  
Pujan Adhikari ◽  
Kishor KC ◽  
Siddha Raj Bhatta

 Labor market returns depend on the level of education as well as experience of the labors. Though education is argued to be the key determinant of wage rate, other factors such as the sector of employment, gender of the employee, marital status and work industry also matter. This paper investigates the returns from years of schooling and experience by examining the wage structure in formal, informal and agriculture sectors of Nepal. The Mincerion wage equation and quantile regression technique has been used to analyze such impact by utilizing the recent labor force survey data of Nepal. Our results show that wage returns are positively associated with schooling in all the three sectors. However, return to experience has negative association in case of agriculture sector. Furthermore, return to schooling has higher impact at higher quantile along with the distribution of wages in formal sector and informal sector. The maximum effect of education is 4 percent at 0.90 quantile in formal sector. An additional year of experience has high impact at lower-wage group in case of informal and formal sector. The effect varies from 9.2 percent at 0.1 quantile and 4.9 percent at 0.9 quantile in formal sector. The experience effect is higher at median (4.06 percent) in case of informal sector.


1995 ◽  
Vol 19 (2) ◽  
pp. 125-146
Author(s):  
Mark D. Partridge

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