Biography

Dr. Richa Singh is Assistant Professor at the Jindal School of Banking & Finance (JSBF), O.P. Jindal Global University, Haryana, India. She holds a Ph.D. in Economics from the Indian Institute of Management, Ranchi, where her doctoral dissertation, Essays on Decentralization and Development Outcomes in India, investigated the relationship between decentralized governance structures and development outcomes across Indian states. She completed her M.Sc. in Economics at the Madras School of Economics, Chennai, and her B.A. in Economics at St. Xavier's College, Mumbai.

Her scholarly contributions examine whether regional decentralization sustains the principles of federal polity in India, and how the sequencing and continuity of fiscal decentralization affect health and education delivery. This research has appeared in Regional Studies (ABDC A* ) and the Journal of Policy Modeling (ABDC A) , and been presented at international forums, including the Economics & Finance Conference of the International Institute of Social and Economic Sciences, London.

Prior to her doctoral studies, Dr. Singh spent about nine years at the intersection of analytics and applied economics across corporate and policy research settings. Her professional experience spans risk management and model validation within the BASEL regulatory framework, predictive analytics in the travel sector, and credit risk modeling for consumer financial services. She has also worked as a policy researcher, analyzing state-level economic surveys and studying the socio-economic determinants of human trafficking, advising international and multilateral organizations on public-private intervention strategies.

Her broader research interests lie in fiscal federalism, decentralized governance, public finance, and the political economy of development, with a focus on institutional and policy design in shaping welfare outcomes in emerging economies. Methodologically, she works with panel and time-series econometrics, structural equation modeling, difference-in-differences and synthetic control methods, and causal inference techniques for observational and quasi-experimental data.