Elementary education outcome efficiency of Indian state governments: a generalized stochastic frontier approach

Jyotsna Rosario and K.R. Shanmugam

Journal of Economic Studies, 2024, vol. 52, issue 4, 728-741

Abstract: Purpose - This paper aims to analyze the technical efficiency of Indian State governments in providing elementary education (EE) and to identify the determinants of their technical inefficiency. Design/methodology/approach - The Generalized Stochastic Frontier Approach (GSFA) is used in the context of the Inefficiency Effects Model to simultaneously estimate the frontier production function and the technical inefficiency model. Panel data of 28 Indian States from 2009–10 to 2018–19 is used. Findings - The mean efficiency of States stands at 86%. Efficiency varied between 67 and 97%. 96% of the inter-state disparity in EE outcomes can be explained by inefficiency. Arunachal Pradesh is the least efficient State, followed by Sikkim and Tripura. Efficiency estimates were observed to change across States over the study period. Proportion of government schools, rural population, and proportion of Schedule Caste and Schedule Tribe children are the major determinants of inefficiency. Practical implications - This study emphasizes that efficient resource management is as important as adequate resource allocation for achieving positive EE outcomes. It distinguishes resource-poor States from inefficient ones, providing insights to enhance States’ efficiency, and aiding policymakers in formulating strategies for ensuring equitable and quality EE. Originality/value - This is the first paper to apply GSFA (for Indian States), providing a more robust estimation of efficiency. The Inefficiency Effects Model is employed that address the limitations inherent in the two-stage approach.

Keywords: Technical efficiency; Public expenditure; Elementary education outcomes; Generalized stochastic frontier approach; I21; I22; I28; H52; D24 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jespps:jes-11-2023-0649

DOI: 10.1108/JES-11-2023-0649

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