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Journal of Income & Wealth (The)
Year : 2021, Volume : 43, Issue : 1and2
First page : ( 123) Last page : ( 137)
Print ISSN : 0974-0309. Online ISSN : 0974-0295.

Minimising the GAP between first revised and final estimates of GVO of agriculture and allied sectors

Sinha Dilip Kumar1,*, Honey C.H.2, Bindal Manish1

1Deputy Director, Ministry of Statistics and Programme Implementation, India

2Director, General in National Accounts Division of the Ministry of Statistics and Programme Implementation, India

*Corresponding author email id: ddg4.nad@mospi.gov.in

JEL Classification: E20, E30, E31

Online published on 17 May, 2022.

Abstract

In the Agriculture and Allied sectors, GVO are computed by multiplying Statewise, item-wise estimates of production/quantity/volume by the respective basic prices (farm gate prices). While doing so, at the time of First Revised Estimates, item-wise All India WPIs are applied on last year's prices to impute current year prices since the prices are not available by that time. Using All India WPI, for all the States, is not appropriate since price dynamics are different in different States. As a result, when actual prices become available, at the time of second/third (final) revision, significant changes in the estimates are registered. In this article, an attempt has been made (using iterative procedure) to find suitable State-wise, item-wise indicators to move their respective prices, if the actual data are not received, keeping all India Item WPIs as control indicators. Effort has also been made to use Agmarknet data to establish a relationship between wholesale prices available on that dataset and those supplied by the States. State-Time-Dummy Regression model has been applied to estimate the prices or indices of different items, State-wise, for the reference year. These exercises have been carried out for two items: Paddy and Wheat. Experiment with respect to other items has been left for future study. Results of these alternative approaches have been compared and suitable recommendations made to make necessary changes in the existing method of GVO estimation, in the absence of price data.

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Keywords

GVA estimation, Agriculture and allied sector.

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