This book presents a comprehensive study that conducts a data-driven performance benchmarking exercise for regional school education systems in India, with a clear focus on highlighting disparities and challenges within these systems, as well as providing targeted policy recommendations for potential improvements. The book conducts an in-depth examination of the educational environment, current status, policies, and interventions across schools. It explores why, despite various national initiatives aimed at improving access to and quality of school education, significant gaps persist across Indian states, particularly in the two most populous states, Uttar Pradesh and Bihar, which face a range of economic challenges.

The book evaluates rankings and efficiency variations in school education development and develops a novel nonparametric efficiency-effectiveness framework to analyze the performance of the school education system. In addition to employing a state-of-the-art meta-BoD-RDM framework for constructing a school education development index, the empirical analysis employs a two-stage network Data Envelopment Analysis (NDEA) model using survey-based data from schools in India to compute school-wise efficiency and effectiveness scores. These scores are then integrated with a machine learning-based Random Forest algorithm to identify the key factors behind the observed inter-school variations in school efficiency and school effectiveness.

The book also discusses progress in school education development during the COVID-19 pandemic. It identifies several key areas that require policy intervention and urgent attention from educationists and governments. This data-enabled benchmarking and analytical study not only contributes to understanding the current landscape but also supports the formulation of future educational policies aimed at effectively addressing the evolving needs of the school education system in India.

Rachita Gulati is Research Economist at the Asian Development Bank Institute (ADBI), Tokyo, Japan. She is also a faculty at the Department of Humanities and Social Sciences, Indian Institute of Technology (IIT), Roorkee. Previously, she held the prestigious Subir Chowdhury Visiting Fellowship (2017–2018) at the London School of Economics and Political Science. She has also served as a faculty member at the Indian Institute of Management (IIM) Kashipur. She specializes in banking and financial institutions, regulation, stability, governance, digitalization, applied econometrics, and efficiency and productivity analysis. Her work involves development of nonparametric models for performance benchmarking across sectors. She has led and coordinated policy-oriented research projects in collaboration with central banks, ministries, and prominent think tanks across Asia. Her research has been published in journals like Omega, Empirical Economics, Computational Economics, Quarterly Review of Economics and Finance, Asia-Pacific Journal of Management, Economic Modelling, Research in International Business and Finance, and The North American Journal of Finance and Accounting.

Sunil Kumar is Professor, Faculty of Economics, South Asian University, New Delhi, India. His research specialization includes data envelopment analysis, stochastic frontier analysis, banking efficiency, and industrial productivity analysis, with a particular focus on performance evaluation of financial institutions, public sector undertakings, and educational institutions. Prof. Kumar has authored two books in 2001 and 2014 and edited two in 2024 and 2025. His collaborative research includes a comprehensive Development Research Group (DRG) study in 2022 for the Reserve Bank of India. He publishes in journals like Omega, Expert Systems with Applications, Wiley Interdisciplinary Reviews (WIREs) Climate Change, Computational Economics, Economic Modelling, Socio-Economic Planning Sciences, Pacific-Basin Finance Journal, Applied Economics Letters, Economic Change and Restructuring, Economic Systems, and the International Journal of Productivity and Performance Management.

Anup Kumar Bhandari is Professor at the Indian Institute of Technology (IIT) Madras. His research areas include production economics (with special reference to efficiency and productivity analysis), industrial economics, and issues related to Indian banking and its overall financial markets. He has published in these areas in journals like Journal of Productivity Analysis, Review of Development Economics, Economic Modelling, Research in International Business and Finance, Journal of Economic Asymmetries, to name a few.

V Charles is Programme Director (MSc AI in Business), Queen’s Business School, as well as Programme Director (Beyond GenAI EdX), William J Clinton Leadership Institute, at Queen’s University Belfast, UK. He is an AWS Accredited Educator and Vice Chair of the British Computer Society (BCS) Northern Ireland. He has been recognised as Fellow of the BCS and the Royal Statistical Society (RSS), Senior Member of INFORMS, Senior Fellow of the UK Higher Education Academy, and Senior Member of The Society for the Study of Artificial Intelligence and Simulation of Behaviour (UK). His research lies at the intersection of AI and Management Science, with a particular emphasis on boosting business productivity, fostering regional competitiveness, enhancing societal welfare, and informing policy, all underpinned by a strong commitment to delivering positive, multidimensional impact. He publishes his research in top-tier journals and holds various editorial positions as a special issue editor and Associate Editor. He is a Six Sigma Black Belt and holds EdX certificates from MIT, Harvard, IE Business School, and the RSS.