Kritika Soni is a Research Associate in the Centre for Gender and Macroeconomy at NCAER. She holds a Master’s in Economics from the Barcelona School of Economics and a Bachelor’s in Economics from the University of London, with academic direction from the London School of Economics and Political Science (LSE).
Her research interests lie at the intersection of international trade, macroeconomic policy, development economics, and applied econometrics. Her past work includes a cross-country SVAR-based study of financialisation and government spending in OECD economies, and policy evaluation of housing, mutual fund performance, and trade vulnerability using diverse empirical approaches.
She has experience in working with public datasets such as UN COMTRADE, Trade Map, and national economic databases, and has applied econometric techniques including SVAR, RDD, and index construction in her academic and research work.
Prior to NCAER, she worked as an Assistant Professor of Economics at the Indian School of Business and Finance (ISBF), where she taught advanced undergraduate courses in macroeconomics and mathematical methods. She also led the institution’s Research Cell, curating academic competitions and mentoring undergraduate students for their theses.
Nitesh Khandelwal is a Research Associate in the Agriculture, Industry, Trade, Technology, and Skills vertical at NCAER. He earned his Master’s degree in Economics from Mumbai School of Economics and Public Policy, and his Bachelor’s degree in Economics from GLA University. His academic interests lie in development economics, health economics, and international trade. Prior to joining NCAER, he was involved in primary research for the Aspirational Cities Program, a project being implemented by the Government of Uttar Pradesh.
His master’s dissertation focused on analysing public health expenditure in India, while his undergraduate studies entailed research on India’s agricultural trade potential. He is proficient in the use of R and Excel software as well as econometric techniques such as time series analysis.