Abstract
This paper focuses on the Data Envelopment Analysis (DEA) based efficiency evaluation to find the impact of two-step categorical impact on the enrollment efficiency of colleges in Bihar, one of the largest states of India. The objective of the study is to find the impact of factors, other than college-specific, on the efficiency of the colleges. The proposed research includes colleges funded and managed through seven state public universities. To follow the homogeneity condition of DEA, colleges providing courses of Arts (languages and humanities only), Science, and Commerce only, have been selected. The numbers of students enrolled in undergraduate and postgraduate courses are considered as two outputs. Numbers of teaching and non-teaching staff are considered as inputs. Colleges have been classified into two categories based on their presence in the rural or urban areas. The efficiency of a college due to any categorical value is calculated as the ratio of overall efficiency and efficiency calculated with similar categorical Decision-Making Units (DMUs) only. The impact of both the categorical variables, affiliation to university and geographical presence, has been analyzed through the hypothesis testing with the null hypothesis that there is no impact of category on the efficiency of DMUs due to a categorical variable.
Highlights
Based on the idea of productive efficiency of Farrell (1957), Charnes et al (1978) introduced the methodology of Data Envelopment Analysis (DEA) to evaluate the efficiency of decision-making units (DMUs) having multiple inputs and outputs
This paper applies the works of Johnes (2006b) and Kao (1998, 2000) to find the impact of the second-level category on the efficiency of higher education institutions
Location was divided into three categories and arranged in order. These categories are not considered as an input or output but affected the selection of peer DMUs for efficiency evaluation
Summary
Based on the idea of productive efficiency of Farrell (1957), Charnes et al (1978) introduced the methodology of Data Envelopment Analysis (DEA) to evaluate the efficiency of decision-making units (DMUs) having multiple inputs and outputs. CCR models (Charnes et al, 1978) considered the production technology as a constant return to scale, and the efficiency measured was radial. This paper applies the works of Johnes (2006b) and Kao (1998, 2000) to find the impact of the second-level category on the efficiency of higher education institutions. The extended models are applied to evaluate the efficiency of colleges of Bihar, a state in India, and the impact of two categories 'affiliation to university and 'location' on the efficiency obtained
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