India’s Central Statistics Office (CSO) has been churning out some very counter-intuitive data over the past two years. For example, according to the CSO, GDP growth ‘accelerated’ in FY16 vs FY15. However, this makes little sense as the majority of real economy indicators (including non-oil exports, core WPI, non-oil bank credit and rural wages) decelerated in FY16.

In a bid to deal with the increasingly counter-intuitive nature of national accounts data published by the government, the macro economics team at Ambit launched India’s own ‘Keqiang Index’ last year.

The index is named after Chinese Premier Li Keqiang who famously, as the Party Committee Secretary of the Chinese province of Liaoning, told a US ambassador that the GDP figures in Liaoning were unreliable and that he himself used three other indicators, namely railway cargo volume, electricity consumption and loans disbursed by banks to track the real economic health of his district (incidentally, Liaoning, last month, reported negative GDP growth for the first time in a decade.)

The Indian Keqiang Index (IKI) that my colleagues have created comprises metrics such as cars and trucks sold, power demand, bank credit and the dollar value of India’s capital goods imports. The IKI suggests that the Indian economy has been losing momentum since mid FY15. In fact, it is worth noting that if the new GDP series did not exist and if we use IKI to estimate the pace of growth in the real economy as per the old GDP series, our GDP estimate for Q2FY16 would be 6.2 per cent y-o-y (vs 7.7 per cent on the new GDP series) and for Q3FY16 it would be 5.4 per cent y-o-y.

What GDP says Even as the challenges around India’s national accounts aggregates are becoming well-known, the statistical accuracy of State-level GDP data (called GSDP) is even more suspect. For instance, the real GSDP growth estimates for a range of States have now been altered by more than 500bps.

In specific, as per the new GSDP series, Gujarat’s GDP growth for FY-13 was revised upwards by about 500bps and that of Bihar was scaled down by about 700bps for FY-13, thereby drastically altering the GDP growth trajectories of these States.

Even if one were to overlook the dodgy nature of the GSDP data with respect to individual States, this data seems to suggest that South India (i.e. Kerala, Tamil Nadu, Karnataka and combined Andhra Pradesh) grew at a slower pace than India’s Northern Belt (INB -- which includes Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Punjab, Haryana, Uttar Pradesh, Rajasthan, Bihar and Madhya Pradesh).

Our travels in the interiors of both these regions over the course of the past five years suggest that the South is clearly more prosperous than the North (and becoming ever more prosperous at a faster rate than the North).

In specific, according to both the old GDP series (over FY06-14) and the new GDP series (FY13-15), South India grew at a slower or same pace as INB. Given South India’s materially superior standing on social indicators, it is difficult to believe that this region grew at a slower pace than North India over the noughties. The task of understanding the pulse of these regional economies on a real-time basis is further complicated as State level GSDP data is not published on a quarterly basis and the annual data is published with a lag of 1-2 years.

Contra indicators Against the backdrop of India’s state-level GSDP data becoming increasingly unreliable and given the absence of a high-frequency gauge to track regional dynamics, we replicate the IKI exercise for India’s regions and launch a Regional Keqiang Index (RKI). We created the RKI for the two economically important regions of the country, namely India’s Northern Belt and South India. The RKI comprises four variables, namely rural wages, power demand, bank credit and number of cellular subscribers.

An analysis of the RKI suggests that South India has been outperforming North India in terms of economic growth over a sustained period. More importantly, the aggregate of the regional RKI indices suggests that the Indian economy lost steam in FY-16 as compared to FY-15.

Going forward, as India’s Northern Belt continues to grapple with its socio-economic problems, resulting in low economic growth and high social unrest, companies which have either operations in INB or depend on demand from the region are likely to see stunted growth opportunities. The underdeveloped state of human capital (due to lack of proper education/training and poor health facilities) and the frequency with which industrial production is disrupted will become a binding constraint on growth for INB. This will result in fewer job opportunities for people in INB and, hence, reduced demand in the region. Already, 64 people out of every 100 in INB are unemployed (the corresponding number for South India is 36). Math suggests that over two-thirds of India’s destitute people live in INB.

In contrast, the South is already almost like a middle-income country with superior performance (and improving) on a range of socio-economic parameters. For example, per capita income in South India is $2,000 versus $1,200 for INB; the gender ratio in the South is 995 women for every 1,000 men whereas in INB there are only 901 women for every 1,000 men. Ambit’s RKI’s now offers concrete evidence that South India, with its improved social environment and better human capital, is further pulling away from the North on the economic front.

The writer is CEO (Institutional Equities) at Ambit Capital. Ritika Mankar Mukherjee, Senior Economist, also contributed to the article

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