Personal Traits, Familial Characteristics and Success in the Labor Market: A Survey Study of Christian Labor Force in Pakistan

Sehrish Haroon, Faiza Azhar Khan and Naheed Zia Khan



Christian workforce, Logistic regression, Study instrument, Socioeconomic status of parents


In Pakistan, state of minorities still remains largely unexplored in a number of dimensions. Specifically, their social status and economic contribution. This study is first of its kind in that it analyzes the determinants of labour market positioning and earnings of Christian workforce of the country. The analysis is carried out by developing a study instrument, which focuses on socioeconomic characteristics of the parental family and personal characteristics of a worker. A purposive sample of 246 Christian members of labour force employed in upper and middle rungs of job hierarchies is taken from twin cities, Rawalpindi/Islamabad. Determinants of job market positioning have been examined by applying logistic regression analysis, while OLS regression has been used to investigate the determinants of income. Results of logistic regression suggest that socioeconomic status of parents is a major factor in determining occupational success of the children of Christian families in Pakistan, as 4 of the 9 respective variables are found significant in statistical estimation. On the other hand, estimates of OLS regression show that asset ownership of their parents along with personal educational achievement significantly determine higher earnings of Christian workforce in Pakistan. The study leads to the conclusion that further research warrants to be carried out on social and economic issues of Christian citizens of Pakistan, specifically targeting the vast numbers lying on the margins of social hierarchy. This essentially requires development of a comprehensive national database on demographic and economic characteristics of all religious minorities of the country. Such an initiative will help assess their state of assimilation in mainstream society which in turn will help devise most efficient and effective interventions.