The problem of sample selection complicates the process of drawing inference about populations. Selective sampling arises in many real world situations when agents such as doctors and customs officials search for targets with high values of a characteristic. We propose a new method for estimating population characteristics from these types of selected samples. We develop a model that captures key features of the agent's sampling decision.
This paper quantifies the impact of health on labour force participation, using South Africa as a case study. This is important given the essential role the labour market plays in economic growth and the potential for poor health to adversely affect labour market outcomes. South Africa has experienced significant disease burden especially due to communicable diseases like HIV/AIDS and tuberculosis. Moreover, conditions like obesity remain a public health concern. Furthermore, the country has witnessed declining labour force participation in recent years.