Rajeswari Sengupta

Rajeswari SenguptaRajeswari Sengupta is an Assistant Professor of Economics at the Indira Gandhi Institute of Development Research (IGIDR) in Mumbai, India. In the past she has held research positions at the Institute for Financial Management and Research (IFMR) in Chennai, India, the International Monetary Fund (IMF) and the World Bank in Washington D.C. She was a member of the research secretariat for the Bankruptcy Law Reforms Committee (BLRC) that recommended the Insolvency and Bankruptcy Code for India in 2016. Her research interests lie in the fields of international finance, open economy macroeconomics, monetary policy, corporate finance and national accounts statistics. Her current work focuses on topics such as monetary policy transmission, exchange rate regimes, GDP measurement issues, and firm financing. She has published in reputed international journals such as Economic Policy, The Journal of International Money and Finance, The World Economy, Emerging Markets Review, Pacific Economic Review, Open Economies Review and International Review of Economics and Finance. Dr. Sengupta completed her M.A. and Ph.D. in Economics from the University of California, Santa Cruz (UCSC). She holds two previous degrees in Economics from India, a Bachelors degree from Presidency College, Calcutta and a Masters from Delhi School of Economics.

Papers Published in World Economics:

Analysis of Revisions in Indian GDP Data

This paper studies constant price growth estimates of India’s annual GDP data in order to understand the revision policy adopted by the Central Statistics Office. The use of high-frequency indicators to prepare initial estimates overstates the growth of the economy, although at the aggregate level the difference between initial estimates and final revisions is low. At the sectoral level the extent of revision for almost all sectors is large and the magnitude and direction of the revision is unpredictable. The Central Statistical Office must address issues in data quality and revisions by (i) adopting a comprehensive revision policy, (ii) supplying information and data on high frequency indicators and (iii) adopting revision metrics to assess the quality of estimates.

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