Analysis of Revisions in Indian GDP Data

Amey Sapre & Rajeswari Sengupta
World Economics, Volume 18, Issue 4, 2017

The compilation of Gross Domestic Product (GDP) estimates in India is perhaps among the most complex processes in the world, going by the sheer volume and spread of data used. In India the  Central Statistics Office (CSO) under the Ministry of Statistics and Programme Implementation has been releasing annual estimates of GDP, among other macroeconomic aggregates in the National Accounts, since 1956 (see CSO (1993), Kolli (2007), CSO (2012), among others). Compilation of GDP requires a combination of inputs such as appropriate methods of computation and vast amounts of data across multiple sectors. Since the collection of sectoral data is time-consuming, the GDP numbers for any given year are released in a sequence of revised estimates based on different levels of data availability.

Initial estimates of Indian GDP for a particular financial year are available roughly one quarter after the start of the financial year. Thereafter, five rounds of revisions take place between the time the CSO publishes its initial and final estimates. The revision cycle gives an indication of the direction in which the economy is headed. In the literature on GDP revisions, several scholars have argued that data revisions contain both ‘news’ and ‘noise’ about the economy’s growth performance (see for instance Mankiw and Shapiro (1986), McKenzie et al. (2008)). This view is based on the fact that as initial estimates are typically compiled with incomplete data or proxies based on high-frequency indicators, there is likely to be more noise in these estimates. Gradually over the revision cycle, as more data become available, the extent of noise is expected to diminish, and the revised estimates start reflecting ‘news’ about the state of the economy.

From a stakeholder’s perspective, GDP data revisions pose several challenges as growth rates are used to infer the direction and momentum in the economy. A major challeng


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