Farmer agitation in Madhya Pradesh (MP) and Maharashtra
has been in the news recently.[i] [ii] Tragically, there have been deaths in the current agitation[iii] and large number of
suicides by farmers (especially in MP) in the months leading up to the
agitation and since.[iv]
Ironically, these suicides have taken place even as MP boasted of a 20% rate of
growth in agriculture in recent years.[v] The situation is no better
in Maharashtra where also a large number of farmer suicides have taken place.[vi]
The government of Maharashtra has announced loan waivers
to farmers in order to end the agitation which had rocked the state.[vii] However, it has been
pointed out that this cannot be a solution to the problem in other states since
only Maharashtra has the fiscal capacity to bear the burden of loan waivers.[viii] In Madhya Pradesh there
has been no loan waiver, reducing the Chief Minister to symbolic gestures such as
fasting for peace.[ix]
The Central government has distanced itself from loan waivers, with the Finance
Minister leaving the states to fend for themselves.[x]
Causes for the Farmer
Agitation
In this note, I want to examine one issue that has
cropped in numerous discussions, namely, the steep decline in the prices of
agricultural products. This has been implicated especially in the context of
prices of pulses.[xiii] As far back as September 2016, a panel
headed by the
Chief Economic Advisor Arvind Subramanian had recommended higher Minimum
Support Prices (MSP) for pulses. Specifically, it was recommended that the MSP
of gram (Please see glossary at the
end of this note for English names of pulses) should be raised
to Rs 4,000 a quintal and Rs 6,000 a quintal for both urad and tur.[xiv] The
committee also recommended subsidies to farmers for growing pulses and called
for the elimination of ad hoc measures like export ban on pulses.
However, the government disregarded the recommendations of
the Subramanian committee and did not put in place an appropriate MSP
mechanism. As it turned out, 2016-17 witnessed a bumper crop in pulses. It is
well-known that agriculture production follows what is known as the cobweb
model: high price for an agricultural product in a year is signal to farmers
that demand is not being met and, hence, the next year they increase the supply
of the product. Further, with adaptive expectations, farmers estimate prices in
the current time period to be related to prices they estimated in the previous time period
adjusted for any errors that they might have made in their predictions in the previous time period.[xv] The
behavior of pulses farmers in MP followed the tenets of the cobweb model
perfectly: “Higher prices of crops like pulses and wheat in the previous years
led to higher plantings. Farmers planted a record area under pulses in 2016-17
responding to price signals from the previous year…”.[xvi] The
consequence of this was a 37% increase in pulses production in 2016-17 leading
to market prices dipping below the MSP.[xvii] It is
important to note that the collapse of prices has not been confined to pulses
but has spread to other products such as tomatoes, potatoes and onions.[xviii] In
addition, it has been suggested that the shock of demonetisation in November
2016 also had a role to play.[xix] With
86% of cash being sucked out of the economy and remonetisation proceeding at
glacial pace, there was a collapse of demand. Two reasons could be adduced for
this fall in demand: one, demonetisation led to a slowdown of the informal economy
with many losing their source of livelihood and hence without the ability to
buy products in the market; two, much of the rural economy is cash economy and,
with the absence of cash, buyers were unable to buy their requirements as per
their usual demand.
What is the Evidence?
I now try to look at what the data tell us about the prices
of pulses and some other products. The data that I use – monthly Wholesale
Price Index (WPI) of a variety of products – is sourced from the Office of the
Economic Advisor, Ministry of Commerce and Industry.[xx] The
monthly data that is used ranges from April 2012 till April 2017. Usually,
monthly data have a lot of seasonal variations which need to be eliminated so
that meaningful changes in the data can be isolated. Seasonal variations recur
year after year. For example, prices of agricultural products may be low
immediately after harvesting and this pattern will repeat itself year after
year. If we wish to find out if any other factors are affecting prices, we
should remove the effect of seasonality on prices i.e. we should deseasonalise
the data. This will allow us to identify and estimate the effect of other
factors on prices. I have deseasonlised the data using the X12 method.[xxi] This method is used by many countries - USA, UK, countries in Europe - to deseasonalise quarterly or monthly data. As a
final step, using the deseasonalised data, I have computed the annualized
monthly rate of growth of prices of products that are included in this
analysis. To compute such a rate of growth (or rate of inflation), one uses the
percentage increase in the WPI value in, say, April 2017 over the WPI value in
April 2016. I have done this for all the agricultural products analysed here.
Consider first the rate of inflation for all pulses (Fig. 1):
In Figure 1, the year 2015-16 shows a very high rate of
inflation of prices of pulses which moderated substantially from October to
January of 2016-17. In fact, the rate turns negative from February to April
2017, which are the months leading up to the agitation of May 2017. The
moderation of the rate of inflation of pulses
over October to January 2016-17 is not surprising given the high level
of prices that prevailed in the corresponding months in the previous year. What
is surprising, however, is the negative rate of inflation in the subsequent
months.
Among all the pulses depicted in Figure 1, gram and rajma are the only pulses that do not show any collapse of prices
in 2016-17. Figure 2 shows the situation for gram. We do not show the rate of inflation for rajma, though it looks similar to Figure 2.
Prices of arhar have fallen dramatically in 2016-17. It is one thing for the rate of inflation to
be moderated on the back of high price rise the previous year but it is
shocking to see the massive negative rate of inflation in 2016-17. Is it only
the base effect of 2015-16 at work or is there something else that has
driven prices down?
The story of arhar
is repeated for moong (Fig. 4), masur (Fig. 5) and urad (Fig.6).
There has also been mention of the collapse of prices of
vegetables in some of the analyses that are available.[xxii] Figures
7, 8 and 9 show the rates of inflation for onions, potatoes and tomatoes.
All
the three vegetables show negative rates of inflation as in the case of some of
the pulses.
Additional Effect of Demonetisation
The
various figures presented in the previous section show substantial negative rates
of inflation for some pulses and the three vegetables, onion, potatoes and
tomatoes. Was that negative rate of inflation due to the base effect, i.e.
exceptionally high price rise, in 2015-16 or was there an additional effect of demonetisation?
It is very likely demonetisation reduced demand for these agricultural products
which, combined with high levels of production, led to the huge negative rate
of inflation in the prices of pulses and vegetables.
I
try to examine this effect of demonetisation by first proposing a model which
relates price inflation in a particular month to price inflation in the same
month, one year (i.e. 12 months) earlier. That is,
INFLATION(%)t
= f(INFLATION(%)t-12) …(1)
I
estimate the simple model depicted in equation (1) (with a slight modification
discussed below) for price inflation data for gram, arhar, moong, masur, urad, chawli, rajma, onions, potatoes and tomatoes for the years 2013-14 to
2016-17. The data used to estimate model (1) above looks like the scatter
diagram in Figure 10.
Figure
10 shows that current rate of inflation (i.e. INFLATIONt), measured
on the horizontal axis, is high if past rate of inflation (i.e. INFLATIONt-12),
measured on the vertical axis, was low and vice versa. The general shape of the
scatter diagram shows that values are high towards the left of the diagram and
low towards the right. This is depicted in Figure 10 by a free-hand black line drawn
through the scatter diagram. This line shows the directionality of the scatter
of points and has a negative slope. A negative slope is exactly what would be
expected: if the rate of inflation of, say, gram was high last year, then
famers see that as a signal that supply was unable to keep pace with demand;
hence, for the current year, they seek to expand the area for the cultivation
of gram which results in much greater production leading to softening of prices
in the current year (i.e. a lower rate of inflation) or even an actual fall in
prices (i.e. negative rate of inflation). This behavior of farmers has
reference to the cobweb model discussed earlier in this note.
The
task before me was to use the data to estimate the black line in Figure 10. However, a
modification is necessary in order to also study the effect of demonetisation.
This is done by employing a dummy variable (Note: a dummy variable takes on only two values: 1 if some condition is satisfied; 0, if the condition is not satisfied) to introduce demonetisation into
model (1) shown above. This dummy variable takes a value of zero for every
month before November 2016 (i.e. the pre-demonetisation time period) and value
of 1 from November 2016 till April 2017 to identify the post-demonetisation
time period. In Figure 10, this effect of demonetisation will be seen as
leftward movement of the black line. This displacement of the black line is
shown by the red line.
The
estimated model that is used in the analysis is available in the appendix for
those who are interested. In Figure 11, I depict the estimated black and red
lines of Figure 10.
It
may be noted that the points that lie along the two straight lines in Figure 11 are not the
same as the free-hand drawn straight lines in Figure 10. The points along the two lines in Figure 11 emerge from estimating, on the basis of data, the black and red lines of Figure 10. The
upper sequence of points in Figure 11 corresponds to the black line in Figure
10 while the lower sequence of points corresponds to the red line in Figure 10.
To illustrate the effect of demonetization, consider the following: a 50% rate
of inflation twelve months ago (measured on the vertical axis), and shown by the
horizontal black line in Figure 11, would have led to a value of -20% for the current year’s
rate of inflation i.e. where the vertical black line meets the horizontal axis
However, during the period of demonetisation this would have led to a further
fall i.e. -40%, as shown by the red lines. This additional fall of 20 percentage points is the
effect of demonetisation over and above the fall in prices due to much higher
production in the current year.
Summing up
Instability in
agricultural prices is a well-studied phenomenon and, hence, it is not
surprising that farmers in Madhya Pradesh and other states have faced problems
with fluctuating prices. It was precisely for this reason that the Chief
Economic Advisor had cautioned the government in September 2016 that the MSP for pulses would
have to be raised. Of course, at that time, CEA would not have anticipated the
nasty shock of demonetisation that awaited the economy just a couple of month
down the line. That shock has made worse the usual instability in agricultural
prices that farmers face. What does this portend for this year? If the models
of agricultural prices have validity, it is very likely that, given the
experience of November 2016 to April 2017, farmers might move away from
production of pulses which would reduce supply substantially in the months
ahead. This is likely to create shortages and push up prices substantially. The
government would need to stand ready to meet this eventuality.
Technical Appendix
We report below the estimated fixed effects
model that underlies Figure 11. Numbers in brackets below the coefficients are
p-values.
Number of observations: 370
R-squared (within) = 0.3646
F-stat = 102.71 (0.00)
where,
INFLATION(%)it = Rate of inflation of
agricultural product i in month t
INFLATION(%)i,t-12 = Rate of inflation
of agricultural product i in month t-12
DEMON = Dummy variable for demonetisation
defined as:
= 1 for months November 2016 onwards
= 0 for months prior to November 2016
It may be noted that the above equation was also
estimated as random effects model which yielded coefficient values very similar
to those reported above. The Hausman test indicated that either model could be
used. See below:
Hausman test for Fixed Effects versus Random
Effects model: 1.56 (0.21)
Glossary
Arhar: also called tur or toovar, refers to Pigeon Pea or Red Gram
Chawli: black-eyed beans
Gram: Generally refers to chana
dal which is Split Bengal gram
Masur: Red lentils
Moong: Green gram
Rajma: Kidney beans
Urad: Black gram (whole) or white gram (when de-husked)
Source: http://www.shreyasbharadwaj.com/my-life/indian-names-for-food-products
ENDNOTES:
[i] http://www.hindustantimes.com/india-news/why-farmers-in-madhya-pradesh-are-on-warpath-against-shivraj-singh-chouhan-govt/story-7bCbncNPio1fPbxGTZ7n4M.html
[ii] http://www.hindustantimes.com/mumbai-news/farmers-agitation-across-maharashtra-and-the-politics-of-it/story-rL6SZDzZoI1bDtyuT7o0VP.html
[iii] http://indianexpress.com/article/india/why-farmers-in-madhya-pradesh-and-maharashtra-are-protesting-4691485/
[iv] http://www.hindustantimes.com/bhopal/three-farmers-ended-life-every-day-in-mp-ncrb/story-wyP4FZHJHqMpbXMeZlInHM.html
[v] http://timesofindia.indiatimes.com/city/bhopal/madhya-pradesh-11000-farmer-suicides-reported-in-9-years/articleshow/59109031.cms
[vi] http://timesofindia.indiatimes.com/city/mumbai/maharashtra-farmer-suicides-rise-15-per-cent-to-235-in-march/articleshow/58251835.cms
[vii] http://www.livemint.com/Politics/1bfn7TaLTIVbvKOqdkhCzM/Maharashtra-govt-announces-farm-loan-waiver.html
[viii]
http://www.livemint.com/Politics/3xGYAPQjK0RQKfBGrRuOjJ/Only-Maharashtra-has-fiscal-capacity-to-pay-for-farm-loan-wa.html
[ix] http://www.hindustantimes.com/india-news/mp-farmers-agitation-cm-shivraj-chouhan-to-sit-on-indefinite-fast-till-peace-is-restored/story-0C1HwEV1iT6lcL1LsjIbEO.html
[x] http://indianexpress.com/article/business/economy/states-keen-on-farm-loan-waiver-must-generate-funds-from-own-resources-fm-arun-jaitley-4699965/
[xi] http://s3.amazonaws.com/academia.edu.documents/36854521/Agrarian_Crisis_and_Agrarian_Questions_in_India.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1497774668&Signature=IR43LNtXOLsXKlPKSXCQ2JOwBiU%3D&response-content-disposition=inline%3B%20filename%3DAgrarian_Crisis_and_Agrarian_Questions_i.pdf
[xii] http://eands.dacnet.nic.in/PDF/State_of_Indian_Agriculture,2015-16.pdf
[xiii]
http://economictimes.indiatimes.com/news/politics-and-nation/why-loan-waivers-wont-fix-indias-agriculture-woes/articleshow/59086914.cms
[xiv] http://economictimes.indiatimes.com/news/economy/policy/announce-higher-msp-for-pulses-speed-up-procurement-cea-panel/articleshow/54365763.cms
[xv]
See Christophe Gouel (2012) Agricultural Price Instability: A Survey of
Competing Explanations and Remedies, Journal of Economic Surveys, Vol. 26, No.
1, pp. 129–156
[xvi] http://www.livemint.com/Politics/2B9xur0n85S5Nl2HRnSzuM/The-story-behind-Indias-bumper-crop-year.html
[xvii]
http://www.livemint.com/Politics/2B9xur0n85S5Nl2HRnSzuM/The-story-behind-Indias-bumper-crop-year.html
[xviii]
http://indianexpress.com/article/opinion/columns/the-crops-of-wrath-demonetisation-4699598/
[xix] http://www.hindustantimes.com/india-news/mandsaur-agitation-how-demonetisation-brought-mp-farmers-onto-streets/story-fD9hc9HkXhHEmFPgZqXduK.html
[xx] http://eaindustry.nic.in/download_data_0405.asp
[xxi] https://www.ons.gov.uk/ons/guide-method/method-quality/general-methodology/time-series-analysis/guide-to-seasonal-adjustment.pdf
[xxii]
http://timesofindia.indiatimes.com/business/india-business/price-fall-centre-to-procure-2-lt-onions-from-mp/articleshow/59201733.cms
