This paper estimates an earnings function where the dependent variable is a mix of point and interval data using an interval regression model based on a pseudo-maximum likelihood estimation procedure. The analysis uses the 1999 OHS, and takes into account point and interval income observations, as well as design features of the survey including stratification, clustering and weights. In developing and applying the methodology, it is shown that researchers interested in analysing the determinants of income in a meaningful way need not be hampered by the presence of both point and interval observations, and can in fact account for these simultaneously using a generalised Tobit model. By incorporating survey design features into the analysis of the variance, some changes were needed to the estimation procedure and this is where the pseudo-likelihood becomes useful. However, this then affects how the coefficients of the model are interpreted, and researchers are encouraged to focus attention on the confluence of these factors.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by University of Cape Town, Development Policy Research Unit in its series Working Papers with number
9632.
Length: 19 pages Date of creation: Feb 2005 Date of revision: Publication status: Published in Working Paper Series by the Development Policy Research Unit, February 2005, pages 1-19 Handle: RePEc:ctw:wpaper:9632
Find related papers by JEL classification: C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)