Abstract:
Purpose: The purpose of this study was to evaluate the determinants of technical inefficiency of Saccos in Kenya. Methodology: The study adopted a descriptive research design. This study collected secondary data analyzed from the audited reports of the licensed deposit taking Saccos and macro-economic indicators sources over the research period. It focuses on environmental and specific Saccos’ predictors affecting inefficiency of Saccos and measured the pure technical inefficiencies of Saccos during a period of pre-regulation and regulation. The explanatory research design was used.
The financial reports data collected from a census of 46 Saccos was analyzed at two levels. First involves estimation of technical inefficiency by employing non-parametric DEA method and second concerned determination of inefficiency using parametric SFA. The log truncated panel data was used for a period of 8 years (2007-2014). The study was designed to address general
objective of establishing the technical inefficiency, the macro-economic and specific Saccos variables determining the technical inefficiency of Saccos.
Findings: The study concludes that all predictors jointly influence inefficiency and that are significant given loan to members’ output slack (LM) or loan output inefficiency. Further, LM slack regression reflects significant random normal error as indicated by Gamma (1.45E-32), and DEA result indicated 0.024 mean inefficiency. Contribution to theory, policy and practice: The regulators or board may not utilize the output loan slack regression to specifically measure the management inefficiency impact on Saccos’
operation while the Saccos predictor variables have significant influence on inefficiency. In addition, the random normal error indicates the influence of agency theory in Saccos is insignificant as the role of management influence given loan slack is minimal. The introduction of variables such as NPTA, MP, FLIB, CA, FI and LP in the financial reports of Saccos and inefficiency benchmarking using DEA and stochastic mechanism are important in regulation.