Exploration of variables with ridge regression in data envelopment analysis Kaur Reshampal*, Dr. Bhatti H.S.**, Dr. Aggarwal Monika*** *Research Scholar, Panjab Technical University, Jalandhar, India **HOD & Professor, BBSB Engineering College, Fatehgarh Sahib, India ***Associate Professor, UIAMS, Panjab University, Chandigarh, India Online published on 24 October, 2019. Abstract Tomeasure the efficiency levels, literature has been advocating the use of Data envelopment analysis as a powerful service management and benchmarking technique. DEA measures the relative efficiency amongst decision making units (DMUs), considering all input and output resources used by them and identifies the most efficient units. Although DEA calculates sources of inefficiency for less efficient units, but it does not provide information related to determinants of efficiency. Particularly, in a multiperiod environment, DEA has to be applied in combination with other techniques for better interpretation of results. This paper attempts to estimate efficiency using DEA in a multiperiod environment in combination with Ridge Regression, using R software with the objective of identifying determinants of efficiency, using database of Indian public sector banks (PSBs) from the year 1998 till 2013. It was found that only 51% of the PSBs were efficient, ‘Borrowings’ and ‘Deposits’ were found to be main source of inefficiency. ‘Wage bills’ were found to be the main determinant of efficiency. It was concluded that to deal with multiperiod and further multicollinearity in data, the use of DEA in association with Ridge Regression provides better interpretation of results. Top Keywords Efficiency, Data Envelopment Analysis (DEA), Public Sector Banks (PSBs), Decision Making Units (DMUs), Ridge Regression. Top |