The GDP numbers that were released for Q2 of the year were quite significant because of the interpretation. For the first time we have had comparisons made between Q2 and Q1 which showed that the economy had improved. In fact the explanation was carried forward to vindicate the view that neither demonetisation nor GST have actually affected the economy and that things were up and about. And as this news came on the back of a Moody’s upgrade and a pat for reforms from S&P besides the improved Doing Business rank of the World Bank, the impression gathered was that the country is out of the docks.

But will this mean that we are back to the 8 per cent growth path? Here everyone is hedging between 6.5 per cent and 7 per cent, and few are going beyond. The issue is actually one of interpretation of data which can lead to considerable obfuscation depending on how it is read.

Gauging performance

Normally performance in Q2- FY18 should be juxtaposed against Q2- FY17 because the seasonal impact is removed as the periods are similar. The economy traverses various seasonal factors which by their nature make it difficult to compare with other quarters. Q1 for instance has the rabi crop while it is also the pre-monsoon time when infra projects are sped up. Industrial production slows down as this is the slack season when there is only residual spending from the rabi harvest, and marriage expenses in April-May.

In Q2, typically there is no major crop harvest except horticulture and animal husbandry which are a year-round phenomenon. Construction comes to a standstill due to the rains, while companies step up output to prepare for the festival season towards September. Q3 and Q4 are vibrant quarters as momentum picks up during harvest as well as festival time combined with accelerated production towards the end of the year.

The 6.3 per cent growth number in GDP in Q2-FY18 was well below the 7.5 per cent number of Q2-FY17 and 8 per cent in Q2-FY16 (16 per cent lower in terms of change in growth rate). A critic would say that the downslide continues and there are few signs of a recovery. However, the 6.3 per cent growth rate has been interpreted differently this time by juxtaposing the same with 5.7 per cent growth in Q1-FY18 (which is 11 per cent higher in terms of change in growth rate), which was also sensationalised to be the lowest growth rate in the preceding 12 quarters. With hype being built on the all-time low number, the 6.3 per cent growth rate gives the impression of a grand turnaround.

Hence even if one goes beyond the cynicism maintained when viewing new methodologies when economic variables are calculated where things look different, interpreting numbers could be made convenient depending on the outcome that has to be projected. In fact, the figure of 6.3 per cent growth would also be the lowest ever Q2 growth rate witnessed in the new base year methodology being followed with 7.3 per cent being the lowest in September 2013.

One can further dampen the mood by looking at gross fixed capital formation which came in at a low of 26.3 per cent in Q2-FY18 which marks a continuous decline in the second quarter for all the preceding years from a high of 34.4 per cent in 2012. Now the GDP growth number does not look as impressive when this trend is also juxtaposed.

Clearer perception

It is, therefore, necessary to be discreet when interpreting statistical data. A similar conundrum emerges when one looks at the core sector data numbers. There has been much ado about how the infra industries have really turned around with the October growth number of 4.7 per cent being extrapolated as a measure of sustainability for the rest of the year. But all production in the economy is cumulative in nature. Monthly data are susceptible to accounting issues when the date of reporting becomes important. Often at the end of the month large orders especially for capital goods could cause a spike which gets corrected subsequently leading to alternating phases of low and high growth rates. Cumulative numbers even out this anomaly.

A better way is to see overall performance is hence in cumulative terms. For the current year, growth has been 3.5 per cent compared with 5.6 per cent last year, which does not give the same sense of satisfaction as growth is still low. In fact a comparison with earlier years show an alternating picture of high and low growth rates with no discernible trend. Even in October, growth was lower than 7.1 per cent last year. This is where the ‘base year’ effect comes in when a higher number for the last year leads to lower number this year. This is a clumsy but valid explanation as statistically it is low. A similar picture is observed when we look at the IIP growth rates where it should be reckoned on a cumulative basis as monthly numbers would be misleading.

Confusing interpretation

When it comes to inflation, the interpretation of numbers seems more confusing. Households have a problem as prices of tomatoes and onions could blur the overall picture as spending on clothes and footwear happens only periodically. They are moved more by month on month changes because any comparison with what it was a year back would be less relevant as the shopping basket is compared with the immediate past. But this is never highlighted.

The RBI looks at the trend in growth rate in the last few months and then takes a call on interest rates. Since June 2017 the figure has been moving upwards from 1.46 per cent and would look at it as inflationary pressures building up notwithstanding some deviations in the period under consideration. But on an average basis for the year, the inflation rate for the first seven months till October was just 2.7 per cent while the last number remembered would be 3.58 per cent. But this may not matter as policies are coming in every two months and the monthly numbers matter more as interest rates are subject to fine-tuning.

Indian statistical data has several challenges including the presence of a dominant informal sector where data is not easily available. Further, given that even organised sector data is not free-flowing, several imputations are used for calculating numbers. This is one reason why often one cannot relate these numbers to the ground level situation. The 7 per cent growth in manufacturing GDP is hard to reconcile with corporate performance which shows a struggle, and low IIP growth for the period.

Further, the judgment used to interpret such data can result in differential interpretation. This is why we must read between the numbers.

The writer is the chief economist at CARE Ratings. The views are personal

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