Project Brief:

This research aims to investigate the relationship between judicial independence, effectiveness, and governance in Pakistan. The study will assess judicial impartiality through psychometric tests administered to judges in collaboration with judicial academies. The primary objective is to evaluate judges’ capabilities in legal aptitude, economic reasoning, and ethical judgment. The 3-Parameter Logistic IRT Model will measure the relevant underlying traits by analyzing judges’ responses to specific test items. This will help us understand how well judges align with the demands of their roles and the impact this alignment may have on judicial independence and the quality of governance. Based on the data collected and analyzed from these tests, targeted training for judges will be conducted.

Public Policy Relevance:

The research will highlight critical vulnerabilities within Pakistan’s lower judiciary, including local political interference and inadequate resources. The study will advocate for policies that safeguard judicial independence, particularly in higher courts and areas with high public interaction. Additionally, the findings will emphasize the need for specialized judicial training in economic principles, especially for judges who frequently handle commercial law or economic governance cases. The policies developed from this research will enhance judicial effectiveness and reduce errors in economically sensitive cases, contributing to improved governance and economic stability. Moreover, by introducing psychometric tools to assess judges’ competencies, this research will propose a novel policy initiative for the capacity building of judges. Incorporating such assessments into judicial selection and promotion processes will ensure that judges are well-equipped to address the economic implications of their rulings. This change will lead to a more effective and independent judiciary capable of fostering better governance.

Team Details:
Principal Investigator
Uzair Jamil Kayani
Associate Professor
LUMS

Co-PI
Sikander Ahmad Shah
Associate Professor
LUMS

Research Associate
Maryam Khalid
Research Associate
LUMS