Semi-autonomous revenue authorities (ARAs) have been established all over the world as a distinctive institutional model outside the traditional public service aimed at enhancing tax administration, and thereby raising tax revenues. In order to boost the robustness of their operations, substantial expenditures have gone towards modernising ARAs. Expenditures have been guided by medium-term corporate-wide plans, and the results monitored, assessed and reported using performance measures. Performance measurement has proved challenging for ARAs to implement and sustain in practice. Some of the challenges evolve around weak capacity, implementation costs, issues to do with quantification, competing demands from a wide range of constituents, the inappropriate selection of measures and a bias towards performance measures that focus on finances. As a means for enhancing performance measurement, there are practices, lessons and theoretical perspectives that can be discerned from the broadspectrum of literature on performance measurement in the public sector and ARAs from around the world. This thesis explores how performance measurement in African ARAs can be more strategic, efficient and effective by ascertaining which key factors shape its adoption. The research focuses on the in depth study of three ARAs in Sub Saharan Africa, involving a combination of structured interviews with internal and external stakeholders, the administration of a survey instrument and review of ARA documents. The final chapters of the thesis deploy fuzzy set logic techniques to identify and test the significance of various causal conditions in the adoption of performance measurement in ARAs, as a plausible answer to the research question.

Semi-autonomous revenue authorities (ARAs) have been established all over the world as a distinctive institutional model outside the traditional public service aimed at enhancing tax administration, and thereby raising tax revenues. In order to boost the robustness of their operations, substantial expenditures have gone towards modernising ARAs. Expenditures have been guided by medium-term corporate-wide plans, and the results monitored, assessed and reported using performance measures. Performance measurement has proved challenging for ARAs to implement and sustain in practice. Some of the challenges evolve around weak capacity, implementation costs, issues to do with quantification, competing demands from a wide range of constituents, the inappropriate selection of measures and a bias towards performance measures that focus on finances. As a means for enhancing performance measurement, there are practices, lessons and theoretical perspectives that can be discerned from the broadspectrum of literature on performance measurement in the public sector and ARAs from around the world. This thesis explores how performance measurement in African ARAs can be more strategic, efficient and effective by ascertaining which key factors shape its adoption. The research focuses on the in depth study of three ARAs in Sub Saharan Africa, involving a combination of structured interviews with internal and external stakeholders, the administration of a survey instrument and review of ARA documents. The final chapters of the thesis deploy fuzzy set logic techniques to identify and test the significance of various causal conditions in the adoption of performance measurement in ARAs, as a plausible answer to the research question.

SARAs have been established to achieve dual objectives of improving efficiency and controlling corruption in tax administrations. Key question for this research include: why some SARAs have failed to effectively control opportunities for corruption and what should be done about it? To explore these questions, this thesis has set out an Anti-Corruption SARA Framework. The novel contribution of this thesis lies in developing the new lens (analytical framework) which causes us to see the topic of SARAs against corruption quite differently (due to differentiating between motivations and opportunities for corruption). In order to analyze the validity of the framework, a two-staged analysis of SARAs, labelled as the macro and micro analysis, was conducted for SARAs and Federal Board of Revenue (FBR) in Pakistan. In the macro level of analysis (through secondary literature analysis), it was found that SARAs made partial progress to control corruption by focusing more on controlling motivations for corruption (through personnel autonomy) and lesser focus on controlling opportunities for corruption (through effective accountability). In the micro analysis (through semi-structured interviews and secondary literature), it was found that FBR remained ineffective in controlling both motivations and opportunities for corruption despite focusing more on controlling motivations for corruption (through personnel autonomy) and lesser focus on controlling opportunities for corruption (through effective accountability). In both macro and micro analyses, continued interference from Ministries of Finance (MoF) was found to undermine not only effective accountability for SARAs and FBR, but also undermining control of opportunities for corruption. Findings of both macro and macro level of analysis resulted in three main recommendations. These findings pointed towards a recommendation of reforming SARAs into an organizational form which is far more disaggregated from the parent ministry, such that SARAs have no accountability link with MoFs in the presence of other effective oversight bodies. It is recommended that SARA countries should develop this understanding about importance of balancing both autonomy and accountability mechanisms to be fully effective against corruption for controlling both motivations and opportunities for corruption. Thirdly, research findings point towards a case of converting FBR into a SARA in the form of Pakistan Revenue Authority, such that it is free from any direct oversight by the MoF, and in contrast should be subjected to effective oversight by other oversight bodies, such as already existing Cabinet Committee for Federal Revenue.