What we know and don’t about the true price of dal

If you look at only the official account (left), the price of dal has been comfortable, but the consumer experience (right) tells a quite different story.

How urgently our national food price measuring methods need a complete overhaul is best shown with the example of a staple everyone is familiar with: arhar or tur dal.

Price indexes or indices are useful because they help us view the change in the price of a particular food staple over time, not the price itself, but change in price when taken from a base year or month. Price records are useful because they log the price (per kilo for retail consumption) of a food staple in a week or month.

The three ministries concerned with food prices update their indices or actual price reports every month or week. These are: the Department of Consumer Affairs of the Ministry of Food and Consumer Affairs, the Directorate of Economics and Statistics of the Department of Agriculture and Cooperation of the Ministry of Agriculture, and the Labour Bureau of the Ministry of Labour. In addition, there is the wholesale price index prepared by the Office of the Economic Adviser, Ministry of Commerce.

Usually, movements and trends in these indices and price logs are examined by themselves, and conclusions are drawn about whether the price of a food staple has been held steady or is rising steadily or is rising seasonally and also annually (we never see prices and trends going downwards).

But this is not enough. We need also to examine whether these indices and price logs are describing what they are designed to in the same manner and – very much more important – whether their descriptions are reasonable or not.

In the two chart panels, I have plotted the descriptions for arhar/tur dal from several sources together. The left chart has solid coloured price lines from the Department of Consumer Affairs and from the Directorate of Economics and Statistics. Each has two lines, the higher at the 90th percentile and the lower at the 10th percentile of all monthly prices logged from 2009 January until 2014 June. The two dashed lines are indices – the wholesale price index for arhar/tur and the Labour Bureau’s retail price index for arhar/tur over the same period. The price logs are plotted against the left index and the price indices are plotted against the right index.

Between the two indices the WPI for arhar appears lower than the Labour Bureau index, but that has only to do with a difference base period. The overall pattern they describe is the same. The two sets of price logs shows the two different levels for the 90th and 10th percentiles – in both cases the prices recorded by the Directorate of Economics and Statistics are higher than those recorded by the Department of Consumer Affairs. However they all follow a similar pattern over the 66 months illustrated here.

And so to the question: how true is what these indices and price logs are describing?

The answer is in the right chart. Here, two more lines are seen. These are both ascending relatively evenly over the 66 months, one at a slightly steeper rate. These I have called the ‘real retail’ price lines, one low and the other high. They describe the prices paid by urban consumers for a kilogram of arhar/tur dal based on what has been charged by ordinary retail outlets in towns and cities, with the price readings collected informally. They have also been ‘straightened’ by applying a 12%-14% true inflation that has been experienced by urban food consumers over these 66 months.

The effect, as you can see, is startling. The ‘real retail’ price lines explain why the consumption of pulses has been dropping and continues to drop especially amongst urban households whose livelihoods depend on multiple informal jobs. At Rs 90 to Rs 110 per kilogram, this dal (like other pulses) is almost beyond reach. At Rs 120 to Rs 130 per kilogram – these are levels that began to be recorded by consumers, but not consistently by the government price monitoring agencies, even two years ago – the dal can be consumed only by the upper strata of the urban middle class.

The question that immediately arises is: why is the real food price inflation being experienced by consumers not reflected in the official food price logs and indices? I will take up this question in the next posting.

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How ADB cooks the climate pot

The Asian Development Bank has, amongst the world’s multilateral development banks, been a bit of a latecomer to the area of climate financing with the help of modelling. Its senior peers – the World Bank and the European Bank for Reconstruction and Development – have been at it for a while, with the World Bank being rather in its own league if one was to judge by the tonnage of reports it has printed. The ADB probably holds its own on the matter against the Inter-American Development Bank and the African Development Bank, but this latest effort, I think, pushes it ahead of the last two.

Not for any reason that would gladden a farmer or a municipal worker, for that is not the audience intended for ‘Assessing the costs of climate change and adaptation in South Asia’ (Asian Development Bank, 2014), which was released to the Asian world a few days ago. But the volume should immensely help the modelling crews from a dozen and more international agencies that specialise in this arcane craft. Providing the scientific basis around which a multilateral lending bank can plan its climate financing strategies will help the craft find a future. Rather less sunny is the outlook for states and districts, cities and panchayats, who may find an over-zealous administrator or two quoting blithely from such a report while in search of elusive ‘mitigation’.

Many reassuringly complex diagrams must only mean we need bigger loans?

In my view, this volume is useless. It is so because it is based on a variety of modelling computations which have their origin in the methods used for the IPCC’s Fourth Assessment Report (that was released in 2007). The permanent problem with all such ‘earth science’ modelling approaches is that it uses global data sets which must be ‘downscaled’ to local regions. No matter how sophisticated they are claimed to be by their inventors and sponsors, such models can only work with regular and large sets of well-scrubbed data that have been collected the same way over a long period of time and recorded reliably. This may serve a ‘global’ model (which is irrelevant to us in the districts) but in almost every single case of ‘downscaling’, a scaling down may make a smattering of sense if there is some comparable data relating to the region for which the scaling is taking place. And this correlation, I can assure you, is not possible 99 times out of 100.

But that doesn’t bother the ADB, because it is a bank, it must find a way for Asian countries to agree to taking loans that help them mitigate the effects of rampaging climate change, as this report tries to convince us about from 2030 to 2050 and 2080 (by which time those who have cashed in their climate technology transfer stock options will have passed on). Which is why the ADB has said its unimpeachable analysis is based on “a three-step modeling approach” and this is “(i) regional climate modeling (ii) physical impact assessment, and (iii) economic assessment”, the last aspect being what they’re betting the thermometer on.

The numbers that have emerged from the ADB’s computable general equilibrium model must be satisfyingly enormous to the bank’s thematic project directors and country directors. For the scenario modellers have provided the ammunition for the bank to say: “The region requires funding with the magnitude of 1.3% of GDP on average per annum between 2010 and 2050 under the business-as-usual-1 scenario. The cost could rise to up to 2.3% (upper range) of GDP per annum taking into account climate uncertainties. To avoid climate change impact under the business-as-usual-2 scenario, adaptation cost of around $73 billion per annum on the average is required between now and 2050.”

I could not, in this needlessly dense and poorly written volume, find a mention of which rice strains have been measured for their yields in the example given for India, when the ADB report makes some dire forecasts about how yields will be lowered or will plunge under several forecast conditions. Perhaps they were buried in some footnote I have overlooked, but considering that the International Rice Research Institute (one of the more dangerous CGIAR monster institutes) has in its genebank more than 40,000 varieties from India, and considering that rice conservationist Debal Deb cultivates 920 varieties himself, the ADB (and its modelling troupe) talking about rice ‘yield’ means nothing without telling us which variety in which region. And that sort of negligence naturally leads me to ask what sort of thermometers they consulted while assembling these models. [This is also posted at India Climate Portal.]

A 68th Independence Day in our Bharat

On 15 August 2014 it is the 24,473rd day that Bharat and India has been an independent country. During that time we have had 15 Lok Sabha and the 16th now sits in Parliament, having been placed there by 814,500,000 electors who cast their votes in 543 Parliamentary constituencies in a general election that has long been the largest and most complex in the world. We’re good at elections. We’re also good at reading newspapers – we have 10,908 daily newspapers – and 26,552 monthly magazines (far too many about films, far too few about farmers). Many of these get delivered thanks to the efforts of the dedicated staff of 154,822 post offices who deliver some 6,371,800,000 pieces of mail (including money orders and greeting cards). Schoolchildren like seeing postmen on their rounds and we have some 243,360,000 who learn from our heroic teachers in 1,314,633 schools.

Many of those schools (some under mango trees) are in our villages, of which there are 640,930 and these are run (quite well, on the whole) by 232,855 panchayats which noisily elect 2,645,880 panchayat members (a good number of them women, who care about how many children go to school). Our panchayats have lots on their weekly agenda, and between them manage 100,293,000 hectares of land that are planted with cereals that help feed Bharat (rotis and kheer, idlis and bicuits). All our villages keep a great number of animals – for ‘kisan’ households they are extended family – and our fields and festivals are attended by 199,075,000 cattle (whose horns are gaily painted) and 105,343,000 buffaloes (who enjoy a good scrubbing). When they’re at work, our cows and buffaloes are tramping around 138,348,461 farm holdings spread over 159,591,854 hectares – of which 117,605,129 are small and marginal holdings on 71,152,325 hectares, but cows and buffaloes aren’t choosy about farm size.

Our rice and wheat (and pulses) is moved carefully around Bharat by rail and by road. When it is moved by rail, this valuable foodgrain enters a system that is 65,436 kilometres long, rail tracks over which 9,956 locomotives (electric, diesel and still a few steam) smoothly pull 48,037 passenger bogies and 244,731 goods wagons past 7,172 stations (and their ‘chai’ stall), for which our farmers (and postmen) thank 1,307,000 railway employees (who are also some of our best sports persons). From Kaniyakumari to Leh, and from Bhuj to Kohima, our 1,325,000 jawans and 1,155,000 reservists rely on our trains (most are humbler than the well-appointed Shatabdis) to take them home to family. Usually outnumbering the jawans in railway bogies are managers and salesmen, accountants and technicians who work in our 738,331 companies and 211,660 factories.

They keep the wheels of industry and commerce turning  (they are usually small and nimble, 23,447,361 in cities and towns and 35,022,735 in rural districts). Their enterprise gives the jawan his sturdy trunk and the schoolgirl her satchel, stationery for the teacher and toolkits for the panchayat plumber. Somewhere between Ratlam junction and Nagpur, the engineer may proudly mention the 12,694,853 people (most of them workers) employed in our factories, at which the accountant will murmur that Rs 501,560 crore is the paid-up capital of Bharat’s many companies. Jawan or kisan, factory worker or manager, all must deposit their wages and salaries in a bank, and we have 109,811 bank branches (39,439 are rural and 41,681 are in cities and towns) in which savings are happily collected (Rs 56,380 per head) and against which credit is dispensed (as happily, we hope, at Rs 44,028 per head). Our bank branches are also the staging posts for the 11,756 billion currency notes in circulation (no more staples and the new series will come printed with braille) but with 933 million quick-fingered mobile phone subscribers (549 million in cities and towns) we may see fewer real notes and more ‘mobile’ payments.

Village and factory, trains and cattle, and 1,250,000,000 of us. This is our Bharat on our 68th day of Independence.

Of seeds and swadeshi

India has reached food security without GM crops. Portrayed by GM advocates as an ‘attack on science’, the movement to keep this technology out is firmly grounded in the national interest. In this article published in full by The Asian Age, I have refuted three common arguments that are advanced to the citizens of India as justifying the need for genetically modified crops.

None of these owe their intellectual genesis to the present NDA government (which is employing them nonetheless), and can be found as theses in both UPA2 and UPA1. They are: that genetically engineered seed and crop are necessary in order that India find lasting food security; that good science and particularly good crop science in India can only be fostered – in the public interest – by our immediate adoption of agricultural biotechnology; that India’s agricultural exports (and their contribution to GDP growth and farmers’ livelihoods) require the adoption of such technology.

The article has attracted a number of comments, including one which is pro-GM (and which in turn has been attacked). Here is a file of the support and exchanges till now.

Examining these uncovers a skein of untruths and imputations which have been seized upon by the advocates and proponents of GM technology and broadcast through media and industry channels. First, the food security meme, which has assumed an oracular gravity but which has not been supported by serious enquiry. On this aspect, the facts are as follows. Our country grows about 241 million tons of cereals (rice, wheat and coarse cereals), just under 20 million tons of pulses and between 160 and 170 million tons of vegetables (leafy and others together). This has been the trend of the last triennium.

Concerning current and future need, based on the recommendations of the Indian Council of Medical Research and the National Institute of Nutrition, an adult’s annual consumption of these staples ought to be 15 kg of pulses, 37 kg of vegetables and 168 kg of cereals. Using Census 2011 population data and the projections based on current population growth rates, we find that the current 2014 level of production of cereals will supply our population in 2028, that the current level of production of vegetables will be more than three times the basic demand in 2030, and that the current level of production of pulses will fall short of the basic demand in 2020.

In short, India has been comfortably supplied with food staples for the last decade (witness the embarrassingly large buffer stocks) and will continue to be so for the next 15 years at least. Why then are the GM advocates and proponents (including unfortunately the Minister of Environment, Prakash Javadekar) in a cyclonic hurry to bring the technology and its manifold risks to India by citing food security as a reason? Read the rest of this article on The Asian Age website, or find a pdf of the original full text here.

The level of public awareness about the dangers of GM food and seed needs independent and credible science as a partner. Here, anti-GM protesters in Bangalore, Karnataka, India

This blog has carried a number of posts about GM and agri-biotech in India. Consult these links for more on the subject:

It’s time to confront the BJP on GM
Lured by dirty GM, Europe’s politicians betray public
Of Elsevier, Monsanto and the surge for Seralini
Scientists’ statement deflates the bogus idea of ‘safe’ GM
India marches against Monsanto, hauls it back into court
Monsanto drops GM crop plans in Europe
The year the GM machine can be derailed
Of GM food crops, Bt cotton and an honest committee in India

Why IMD’s rain math doesn’t add up

Each blue bar represents the actual rainfall recorded by a district as a percentage of its normal. There are 614 district recordings in this chart.. The red dotted line is the 100% mark, and many of the bars end below, or way below, this mark. This is the district-level view of cumulative rainfall over eight rain weeks using the IMD’s own data.

Over eight weeks of recorded monsoon rain, the district-level data available with the India Meteorological Department (IMD) portrays a picture that is very different from its ‘national’ and ‘regional’ advice about the strength and consistency of rainfall.

In its first weekly briefing on the monsoon of August 2014, IMD said: “For the country as a whole, cumulative rainfall during this year’s monsoon (01 June to 30 July 2014) has so far upto 30 July been 23% below the Long Period Average.” Out of 36 meteorological sub-divisions, said the IMD, the rainfall has been normal over 15 and deficient over 21 sub-divisions.

The four regional readings that make IMD’s data look less worrisome than it actually is.

However, here is a far more realistic reading of the monsoon season so far, from the IMD’s own data. For the 614 individual readings from districts that have regular rainfall readings, we have the following: 86 districts have registered scanty rainfall (-99% to -60%); 281 districts have registered deficient rainfall (-59% to -20%); 200 districts have registered normal rainfall (-19% to +19%); and 47 districts have registered excess rainfall (+20% and more).

What this means, and the chart I have provided to illustrate the 614 individual values leaves us in no doubt, is that 367 out of 614 districts have had meagre rain for eight weeks. This also means that over eight weeks where there should have been rainfall that – as the IMD predicted in early June – would be around 95% of the ‘long period average’, instead three out of five districts have had less than 80% of their usual quota.