Saturday 21 October 2017

DEMONETISATION AND EMPLOYMENT


Introduction

It has been almost a year since Prime Minister Modi surprised the country with the announcement of demonetisation. Numerous commentators had criticized the move for a variety of reasons, the most prominent among these being:

(1) Demonetisation was the wrong instrument for the intended objective of eliminating black money from the Indian economy.

(2) The economy would suffer a severe adverse shock as a result of the draining of 86% of the currency from the system.

This blog had written about these criticisms and added some of its own.[1] At that time, much of the criticism was on conceptual grounds, given the importance of cash in the Indian economy. The government itself realized that the original objective of eradicating black was unlikely to succeed and kept changing the narrative. After mentioning “black money” eighteen times in his fateful November 8 2016 speech, the Prime Minister and his colleagues gradually changed the narrative to include the objectives of cashless economy, curbing of terrorism, long term growth and so on. In a revealing content analysis of the Prime Minister’s speeches, IndiaSpend.com reported that, by the end of November 2016, references to black money had fallen substantially, references to fake currency had all but disappeared and cashless economy, which was not mentioned at all in his November 8 speech, had risen high enough to become the primary objective of demonetisation.[2]

As time has passed since the withdrawal of currency from the Indian economy, evaluation of the move is no more based on only a theoretical understanding of the Indian economy; this is now being supplemented by hard data. I had written about this in June 2017 as I tried to explain the agitation of farmers.[3] Much of the recent analyses have validated the fears that had been expressed in the immediate aftermath of demonetisation. It is important to bear in mind that reports from even respectable Indian institutions have started to point towards the adverse consequences of demonetisation. A recent RBI report pointed out that almost all the currency notes that had been extinguished, had made their way back to the banks. Of the currency worth Rs. 15.45 trillion withdrawn from the economy, “the estimated value of SBNs [specified bank notes i.e. currency notes] received as on June 30, 2017 is Rs. 15.28 trillion”.[4] This has belied the expectation that almost 30% of the banned notes would not be returned[5] and would, in effect, represent black money that had been “burned” by holders of such monies.

Among the commentators who have strenuously defended demonetisation Bhagwati, Dehejia and Krishna are the most high profile with rather exalted academic standing. Bhagwati et al have been at pains to point out that demonetisation did have some beneficial effects on the Indian economy although their list of benefits seems to depend on a number of assumptions, most notably, how much may be collected in the form of taxes from the monies deposited into bank account.[6] As an aside, I must mention that the title of their paper (“It’s premature to argue if demonetisation was a success or failure”) reminds me of the interesting but, possibly, apocryphal story of Zhou Enlai, the Chinese Premier from 1949-1976.[7] When asked about the impact of the French Revolution, Zhou apparently said “It’s too early to tell”.[8]

The most specious claim made in aforementioned article of Bhagwati et al is in its last sentence. Referring to the apparent boost to digital banking and digital transactions due to demonetisation, they write: “We would note that while this was not the original intended goal of demonetisation, it may yet prove the most important long-lasting benefit”. If something was not intended, then its occurrence is serendipitous and serendipity cannot be used to bolster one’s support for a policy. Also, if unintended benefits are to be claimed as positives for demonetisation, then unintended costs should also be included on the negative side: who had, for instance, anticipated that 40 persons would die while standing in the long queues that had formed for the purpose of depositing defunct notes into the banks? This was a tragic occurrence in the aftermath of demonetisation which needs to be taken into account unless, of course, such deaths are seen as minor collateral damage. And there is no estimate of how much productive time was lost by employed individuals while standing in these queues.[9] The sheer one-sided evaluation of demonetisation by Bhagwati et al is neatly exposed by Shruti Rajgopalan and Lawrence White[10] in their comments on an earlier article by the trio.[11] Rajgopalan and Lawrence point out that Bhagwati et al, instead of carrying out a cost-benefit analysis of demonetisation, carry out only a simplistic benefit analysis of it.

Employment and Demonetisation

It has been pointed out that demonetisation has resulted in the extinguishing of jobs, especially in the informal sector.[12] The CMIE has estimated that 1.5 million jobs were lost during the period January-April 2017.[13] Alongside this reported loss of jobs there has been a decline in the labour force participation rate (LPR).[14] However, the unemployment rate (UR)[15] and the LPR show divergent trends in the post-demonetisation time period. Mahesh Vyas of CMIE does try to explain this but his explanation does not seem convincing to me.[16] Figure 1 shows the trends in Total (All India) UR and Total LPR.[17]



The reported job losses are not reflected in the unemployment rate but the declining LPR shows that persons are dropping out of the labour force. This is a phenomenon that was witnessed in the USA also during the recent recession: the dismal jobs situation led many to drop out of the labour force i.e. they stopped searching for jobs. As per the FRED database, LPR in the USA fell from 66% in September 2008 to a low of 62.4% in September 2015 before beginning to recover.[18] A mere visual examination of the data for India does not seem to suggest that LPR began to fall only after demonetisation in November 2016 since it shows a fall in October 2016 as well. Could the fall have accelerated after demonetisation? I examine this in a later section.

Figures 2 and 3 show LPR and UR for Urban and Rural sectors. The trends in LPR and UR for urban and rural areas are no different from those for Total LPR and Total UR.





LPR and Demonetisation

It has often been stated that India has a young population. Many countries in Asia seem to be moving in the other direction i.e. their population is aging but, in India, approximately half the population is under the age of 26, “and by 2020, it is forecast to be the youngest country in the world, with a median age of 29”.[19]  IndiaSpend.com reports that 64.4% of India’s population is in the 15-59 years age group. This number is 67.7% for urban India and 62.9% for rural India.[20] With this distribution of population it seems inconceivable that LPR can show a declining trend unless something dramatically unusual is happening in the Indian economy. World Bank data tells us that from 2012 to 2016, the Indian labour force has increased by 34.5 million, that is, an average yearly increase of 8.6 million[21] and yet, unexpectedly, the LPR ratio shows a sudden fall.

For the USA, which has also faced the problem of declining LPR, FRED (Federal Reserve Bank of St. Louis)[22] has put forward two reasons for this phenomenon (See also James Bullard[23] and Maria A. Arias and Paulina Restrepo-Echavarria[24])

(1) The “demographics” view, which states that the changes in the rate are a reflection of changes in the demographics of the labor force

(2) The “bad omen” view, which says that the declines in the LPR rate are due to people leaving the labor force because of the poor state of the economy

Bullard, after evaluating all the evidence, comes to the conclusion that the demographics view best explains the declining LPR in the USA: “The nation’s workforce had a younger profile as the Baby Boom generation came of age, and it will have an older profile as the Baby Boom generation continues to retire. Since different age groups have different propensities to participate, this suggests a promising avenue to explain the labor force participation data”.

Clearly, India’s demographic history is completely different from that of the USA. India does not have the equivalent of the baby-boomers generation which might be retiring now. In fact, as stated above, India’s demographic profile suggests that more and more individuals should be entering the job market. That apart, the LPR in the USA has declined over a few years which is to be expected since demographic variables change slowly. In India, the LPR has declined within a span of a couple of months thereby rejecting the demographic explanation of a declining LPR. Consequently, the only explanation that holds some credibility is the “bad omen” view. The state of the economy, already fragile before the shock of demonetisation, nosedived after November 2016 causing the unexpected decline in LPR.

Declining LPR: Empirical Verification

I carry out some exercises to show the link between LPR and demonetisation. A simplistic exercise would be to run a regression of Total LPR on a binary variable representing demonetisation. The results of such as an exercise would reveal a picture like Figure 4.


The vertical line at November 2016 divides the plot area into two segments: before and after demonetisation. Even though I don’t show it here, but similar graphs for Urban LPR and Rural LPR can be created.

I extend the above analysis by linking LPR to the amount of currency with the public (CURR) which in turn was affected by demonetisation. In the language of econometrics, I endogenise CURR and use demonetisation (which I believe to be an exogenous, unanticipated event) as an instrument. My reasoning for linking LPR to CURR is that almost the entire informal sector depends on cash for its transactions. The withdrawal of 86% of the currency from the economy dealt a blow to production of this sector rendering millions jobless. The "bad omen" effect of loss of jobs led to an adverse effect on LPR. Nakamura and Steinsson have cautioned that exogenous monetary policy shocks should be identified carefully since many apparent shocks seem to have been triggered for identifiable economic events and are, hence, not truly exogenous.[25] There is reason to believe that demonetisation was not triggered by any prior identifiable economic events.[26]

I now report the results of my empirical exercises. For those interested, the Appendix gives details of the econometrics. Using the results of the equation reported in the Appendix, I chart out the estimated path of LPR and compare it with a counter-factual path, namely, a path that LPR would have taken if demonetisation had not taken place (Figure 5). I show this only for Total LPR since the charts for Urban LPR and Rural LPR are almost identical.


The blue line shows what did happen in the Indian economy with Total LPR collapsing after November 2016. In contrast, the maroon counterfactual line shows the path LPR would have taken had demonetisation not taken place. The contrast between the two lines clearly shows that demonetisation was responsible for the sudden fall in Total LPR.

Summing Up

The decline in the LPR should be matter of deep concern for the Indian economy. Persons may drop out of the labour force due to discouragement, the inability to find a job.[27] They may not permanently stay out of the labour force and would possibly return when job prospects improve. In the meantime, they may take up part-time jobs to make ends meet or maybe compelled to start a small business as a desperate move for their very survival. A remedy for this dismal state of affairs will not be forthcoming until the government recognizes the reasons behind this phenomenon. Unfortunately, there seems to be little hope of that with the government and its ministers continuing to aggressively defend demonetisation and denying that the economy is in deep trouble. An indication of how poor the government’s understanding of the economic situation is can be gleaned from the callous comment of Railway Minister Piyush Goyal who said that loss of jobs is a good sign since the youth of today would like to be entrepreneurs.[28] Goyal, obviously, does not recognize the difference between the “forced entrepreneurship” of the jobless and those who voluntarily choose to be entrepreneurs.


APPENDIX

I use 2SLS estimation to model Total LPR as a function of Currency with the Public (CURR). However, there are strong reasons to believe that CURR is not truly exogenous and I use a dummy variable (DEMON) to represent pre- and post-Demonetisation periods as an instrument for CURR. The estimated main equation and the first stage regression are given below. The numbers in brackets are p-values.



The endogeneity test confirms that CURR is, indeed, endogenous. The RMSPE tells us that the prediction performance of this equation is very good.

The first-stage regression shows the importance of demonetisation for CURR.



Even though I do not report it here, I get very similar results for Urban LPR and Rural LPR using the same methodology as for Total LPR.



[1] http://ajitkarnik.blogspot.ae/2016/12/demonetisation-thunderbolt-in-search-of.html
[2] http://www.indiaspend.com/cover-story/how-modi-changed-and-changed-the-demonetisation-narrative-54391
[3] http://ajitkarnik.blogspot.ae/2017/06/what-is-agitating-farmers.html
[4] RBI Annual Report, 2016-17, p. 195; https://rbidocs.rbi.org.in/rdocs/AnnualReport/PDFs/RBIAR201617_FE1DA2F97D61249B1B21C4EA66250841F.PDF
[5] https://www.bloomberg.com/news/articles/2017-08-30/india-central-bank-spends-record-amount-to-replace-void-notes
[6] https://theprint.in/2017/09/05/premature-argue-demonetisation-success-failure/
[7] http://www.historytoday.com/blog/news-blog/dean-nicholas/zhou-enlais-famous-saying-debunked
[8] This perfectly good story has been debunked by spoilsports who claim that Zhou was actually referring to the 1968 protests in France. See: https://mediamythalert.wordpress.com/2011/06/14/too-early-to-say-zhou-was-speaking-about-1968-not-1789/
[9] My back-of-the-envelope calculation suggests the following: India’s population is 1.2 billion. Assume that average household size is 5. Hence, there are 240 million households in the country. Assume that only one member for only half of these households had to stand in a queue to exchange defunct bank notes (the remaining household, being better off could get someone to stand in the queues for them). Hence, 120 million individuals stood in queues. Further, assume that each person stood in the queue for only 2 hours (possibly a gross under-estimate): 240 million hours were spent in queues. Assuming a working day of 10 hours, I get an estimate of 24 million person-days were lost in queues.
[10] http://www.livemint.com/Opinion/0RUMX1LvfO8VtMdC4Acd5L/Demonetisation-and-welfare.html
[11] http://www.livemint.com/Opinion/niFH9uM377oUSHEQcRuUWP/Demonetisation-fallacies-and-demonetisation-math.html
[12] https://economictimes.indiatimes.com/markets/stocks/news/deep-impact-of-demonetisation-analysts-count-cost-in-terms-of-job-business-losses/articleshow/56370617.cms
[13] https://www.cmie.com/kommon/bin/sr.php?kall=warticle&dt=2017-07-11%2011:07:31&msec=463
[14] LPR is defined as the ratio of the labour force to the population greater than 15 years of age. Please see: https://unemploymentinindia.cmie.com/kommon/bin/sr.php?kall=wtabnav&tab=4000&sectcode=200150000000000000000000000000000000000000000
[15] Unemployment rate is defined as those who are willing to work and are actively looking for a job expressed as a per cent of the labour force. The source for this is CMIE in the previous endnote.
[16] https://www.cmie.com/kommon/bin/sr.php?kall=warticle&dt=2017-07-11%2011:07:31&msec=463
[17] The source for my data is: (1) https://unemploymentinindia.cmie.com/kommon/bin/sr.php?kall=wtabnav&tab=4020 and (2) CMIE’s Unemployment in India: A Statistical Profile (various issues) (https://unemploymentinindia.cmie.com/)
[18] https://fred.stlouisfed.org/series/CIVPART
[19] https://blogs.thomsonreuters.com/answerson/indias-demographic-dividend/
[20] http://www.indiaspend.com/viznomics/indias-demographic-dividend-64-4-youth-27-3-children-in-2015-2015
[21] https://data.worldbank.org/indicator/SL.TLF.TOTL.IN
[22] https://www.stlouisfed.org/on-the-economy/2017/january/dissecting-falling-labor-force-participation-rate
[23] https://research.stlouisfed.org/publications/review/2014/03/13/the-rise-and-fall-of-labor-force-participation-in-the-united-states/
[24] https://www.stlouisfed.org/publications/regional-economist/october-2016/demographics-help-explain-the-fall-in-the-labor-force-participation-rate
[25] http://www.columbia.edu/~js3204/papers/macroempirics.pdf  I would like to thank Jeremy Edwards for drawing my attention to this article to me though I am not sure if he will agree with my claim that demonetisation was genuinely exogenous.
[26] This can, of course, be contested if one accepts the Prime Minister’s contention that demonetisation was designed to remove black money from the economy. Given how inappropriate the instrument was to curb black money, I find it difficult to accept the Prime Minister’s contention.
[27] https://www.federalreserve.gov/newsevents/speech/yellen20140822a.htm
[28] http://indiatoday.intoday.in/video/piyush-goyal-job-loss-congress-rahul-gandhi/1/1063788.html

Friday 23 June 2017

What is Agitating the Farmers?

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
Agrarian crisis in India is a deep and complex problem and it is impossible to tackle it in a blogpost. Numerous studies on the issue are available and I draw the attention of the reader to this review of some of these books.[xi] See also State of Indian Agriculture 2015-16.[xii]
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):


 Figure 1 and, indeed all other figures in this section, focus only on the months from October to April for the years 2013-14, 2014-15, 2015-16 and 2016-17. There are two reasons for these months only: one, this makes the diagrams less cluttered but, more importantly, I wanted to especially cover the time period that includes demonetisation and the months leading up to the farmer agitation.
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.


 However, the next few figures show a dramatic collapse of prices of other pulses.



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