We adopt a quantile regression framework, which then uses different quantile spreads to analyse the conditional inequality using the data drawn from the Labour Force Surveys over the 1990 to 2003 time--period.
Before analysing changes over time, the paper describes the overall conditional inequality using six different models.
As seen from the figure, the highest conditional inequality is in quantile 90-10 for the education group having post-graduate degree, while lowest is found in education group who has done Matriculation but less than Intermediate.
As depicted in table, Punjab has the highest conditional inequality across all the quantiles while Balochistan has the lowest conditional inequality in all quantiles spread compare to other provinces.
Figure 4 shows the conditional inequality at different level of education for male and female as well as for urban and rural area.
Having degree in Agriculture, Medicine or Engineering found to lave lowest conditional inequality for all the industries except for the Service sector.
The overall figure shows that conditional inequality increasing in the upper half as well as lower half of the distribution.
The conditional inequality estimates for different provinces is depicted in Figure 7 where Punjab and Balochistan found to have highest increase in conditional inequality over the year, from 1.
For female, the conditional inequality increase is slightly more compare to increase for male but the inequality remain higher for female compare to male.
Financial Institutions and Trade and Hotels found to have minimal increase in conditional inequality as drawn in Figure 9.