Context: Three years after the shift to the new base year of 2011-12, the CSO and NITI Aayog jointly released the back series GDP data detailing growth numbers for 2004-05 to 2011-12.
GDP calculation process and Central Statistical Office
Introduction of GVA at basic prices in India
- In India, GDP is estimated by Central Statistical Office (CSO).
- Under the Fiscal Responsibility and Budget Management Act 2003 and Rules thereunder, Ministry of Finance uses the GDP numbers (at current prices) to peg the fiscal targets.
- For this purpose, Ministry of Finance makes their own projections about GDP for the coming two years while specifying future fiscal targets.
- In the revision of National Accounts statistics done by Central Statistical Organization (CSO) in January 2015, it was decided that sector-wise wise estimates of Gross Value Added (GVA) will now be given at basic prices instead of factor cost.
- In simple terms, for any commodity the basic price is the amount receivable by the producer from the purchaser for a unit of a product minus any tax on the product plus any subsidy on the product.
- However, GVA at basic prices will include production taxes and exclude production subsidies available on the commodity.
- On the other hand, GVA at factor cost includes no taxes and excludes no subsidies and GDP at market prices include both production and product taxes and excludes both production and product subsidies.
GVA at factor cost + (Production taxes less Production subsidies) = GVA at basic prices
GDP at market prices = GVA at basic prices + Product taxes- Product subsidies
|Nominal GDP||Real GDP|
|● It is the value of all goods taking price changes into account.||● It is the value of all goods produced in a given year.|
|● It is evaluated at current market price.||● It is evaluated at the market prices of some base year.|
|● Nominal value changes due to shifts in quantity and price||● Real value is not influenced by changes in price, it is only impacted by changes in quantity.|
Difference between GDP and GVA
|● It is the monetary value of all the finished goods and services produced within a country's borders in a specific time period.||● It is measure of total output and income in the economy.|
|● It is the sum of private consumption, gross investment in the economy, government investment, government spending and net foreign trade.||It provides the rupee value for the amount of goods and services produced in an economy after deducting the cost of inputs and raw materials that have gone into the production of those goods and services.|
|● GDP gives the picture from the consumers’ side or demand perspective.||● It also gives sector-specific picture like what is the growth in an area, industry or sector of an economy.|
|● GDP is a key measure when it comes to making cross-country analysis and comparing the incomes of different countries.||● It is the sum of a country’s GDPand net of subsidies and taxes in the economy.|
|● A sector-wise breakdown helps policymakers decide which sectors need incentives/stimulus and accordingly formulate sector specific policies.|
Why back series data and its important?
- The back series provides historical data for GDP from 2004-05 to 2010-11 using 2011-12 as the base year.
- The purpose for such a back series is to ensure the old GDP data and the new are comparable.
Base year and its significance
- The base year of the national accounts is the year chosen to enable inter-year comparisons.
- It is changed periodically to factor in structural changes in the economy and present a more realistic picture of macroeconomic aggregates.
- The new series changes the base to 2011-12 from 2004-05.
- The base year is important in GDP calculation as factors such as purchasing power and enables calculation of inflation-adjusted growth estimates.
- To depict a better picture of the economy through macroeconomic aggregates like Gross Domestic Product (GDP), National Income, consumption expenditure and other related aggregates and indicators.
What is the issue?
The GDP back series data released jointly by CSO and NITI Aayog contradicts the earlier findings of a committee set up by National Statistical Commission to develop a methodology for deriving back data by linking the old series with the new base year of 2011-12.
|Sudipto Mundle Committee data||GDP back series data released by CSO and NITI Aayog|
|● The National Statistical Commission (NSC) constituted a Committee on Real Sector Statistics under Dr. Sudipto Mundle in April, 2017.||● Since 2015, to gauge the long-term growth trends of the Indian economy there was a need for an official estimate of the older GDP series – the one recalibrated to the new base and the new methods.|
|● It discusses alternative approaches for converting the old GDP series to the new base year 2011-12.||● As per the CSO numbers, India’s GDP grew 8.5 percent in the financial year 2010-11 as compared to the earlier estimated figure of 10.3 percent.|
|● The committee uses production shift approach- uses sectors for which data is available.||● With the shift to the new base year 2011-12 from 2004-05, the MCA-21 database got used in addition to the volume index of Index of Industrial Production (IIP) and establishment-based dataset of Annual Survey of Industries (ASI).|
|● The committee’s report produced new back series data, which showed that the Indian economy grew at a faster clip in two terms of the UPA, between 2004-05 and 2013-14, when compared with average growth recorded in the first four years (2014-15 to 2017-18) of the NDA-II government.||● MCA-21, an e-governance initiative of the Ministry of Company Affairs was launched in 2006, to allow firms to electronically file their financial results.|
|● In 2006-07, GDP at factor cost touched double digit growth rate at 10.08 per cent.||● In certain cases, owing to the limitations of the availability of data, splicing method has been used.|
|● Mundle’s committee submitted the report to the National Statistical Commission.||● Splicing is a statistical technique of converting two, or more series of index numbers of different bases into a continuous series with a common base.|
|● But the findings of the report prompted the Ministry of Statistics and Programme Implementation to issue a statement on August 19 that “the estimates in the report are not official estimates and are meant only to facilitate taking a decision on the appropriate approach”.||● The new series shows that value addition in tradewas significantly lower than what was being projected in the old series, which used extrapolated data from a survey conducted in 1999.|
Back series data released by CSO and NITI aayog
|Why back series adjustment needed?||● Get a better assessment of growth trend|
● Allow better comparison and forecasts
● Adjust for better methodology and data
|How is the new series better?||● Follows globally accepted methods|
● Better coverage of economic growth
|What the new data shows?||● Growth trend does not change much|
● Global financial meltdown impacted economy more than anticipated
● Large decline in investment rate stands out
|Use of latest data sources||● Use of MCA-21 database|
● New series of WPI and CPI in lieu of CPI-AL/IW
|Improvement in coverage||● Inclusion of stock brokers, stock exchanges, asset management companies, addition of mutual funds and pension funds, regulatory bodies like SEBI, PFRDA, IRDA included in financial sector|
● Use of sector specific CPIs used (health, education, transport and communication)
|Implementation of International Guidelines||● Estimation by different institutional sectors- Non-financial and financial corporations, general government and households, Distinction between general government and public corporations|
● Valuation of GVA at basic prices
● R&D expenses treated as part of capital formation
What is the controversy?
- No explanation for using new datasets- There is not enough explanation for the choice of datasets and proxies, especially those datasets that didn’t exist before 2011-12.
- MCA data not available before– For instance, for years preceding 2006, when the MCA-21 database did not exist, the CSO has used ASI data for estimating manufacturing growth whereas economists say there could have been other indicators for the same metric.
- Criticism over the role of NITI Aayog- The role of the NITI Aayog in the release of the statistical exercise of CSO, which comes under Ministry of Statistics and Programme Implementation (MoSPI), has also been questioned.
- Volume index approach v/s financial data approach (GVA based approach)- The System of National Accounts prefers to go with volume indices. The big difference between the volume index approach and the financial data approach is that the financial data captures changes in quality(as it is balance sheet based) which the volume approach does not.
- Timing of data release- With ongoing assembly elections and general elections due in 6 months timing of such exercise is not taken well.
- Sustainable Investment- The GDP data controversy runs the risk of denting the market’s trust and conviction in official data released by government agencies. This can affect incoming investment in the country.
- Institutional autonomy- Organisations such as CSO, must not be politicized for institutional damage have prolong adverse ramifications.
- Political overtones- During phase of elections in specific and otherwise in general, politicians must be mindful of such exercises and its consequences. As it is well known that “If you torturethe data long enough, it will confess to anything”.
- Subjectivity should be reduced – Since there is a debate among experts over data/indicators used, there must be thus framed set of measures through effective deliberations to reduce the subjectivity involved.
- External Scrutiny:The CSO should be open to submit the methodology used and giving data to a review of independent experts to prove the credibility of the exercise.
- GDP is only one of the methods to measure economic growth– Being a demographic dividend nation, the country needs to look at other data like creation of jobs in the economy, how growth translated into inclusive growth, human development, care economy and happiness levels among others.