This research aims to investigate the incentive structure for public sector employees. The main question that this study attempts to answer is whether public sector workers with a greater number of, or more central, network connections end up with superior outcomes in terms of more desirable job allocations. This research then aims to investigate whether network based allocations have an effect on on-the-job performance.
Ex-ante the overall effect of network-based job allocation on public servant effort choice is ambiguous and is, thus, an empirical matter. If network-based job allocations aid in overcoming adverse selection problems then referred officers should have better performance. On the other hand if network-based allocation only works through distribution of network rents, with no efficiency gains, then we should not expect to see above average performance of a referred officer. The aim of this study is to move beyond testing for the presence of network effects and investigate how networks distort allocation of resources and impact outcomes.
This study is based within the context of officers of the Pakistan Administrative Service (PAS) and Punjab Civil Service (PCS) who have served/are serving in the Punjab province of Pakistan. This study compiles a novel dataset on careers and tax performance of these civil servants. More specifically, I will use career charts of all Punjab Civil Service (PCS) and Pakistan Administrative Service (PAS) officers to create a work network of officers. All other kinds of networks will be abstracted away. As detailed data is available on which officers served in which area/department, when and with whom, it will be possible to define an officer's network with some objectivity and precision. This helps in overcoming measurement error and subjectivity bias which generally results from using self-reported network data (Jackson (2013)). The performance measure will be compiled from historical records of the Board of Revenue on Land Revenue/Agriculture Income Tax (AIT) collected by various tiers of the tax machinery across the tehsils of Punjab as a percentage of the yearly target set by the Board of Revenue.