Sources of Agrarian Distress and Farmers' Suicides in Southern India

28 Pages·2013·1.6 MB·English

Sources of Agrarian Distress and Farmers’ Suicides in
Southern India: An Econometric Investigation
Sarah Hebous (University of Heidelberg)
and
Stefan Klonner (University of Heidelberg)∗
June 2013
This paper analyzes sources of extreme agrarian distress in semi-arid India. We collect district-
leveldataonfarmers’suicidesfortheyears1998to2004in62districtsinSouthernIndia.Using
panel techniques, we estimate the effects of transitory rainfall shocks and structural changes in
agriculture on the incidence of suicides of adult males whose primary occupation is agriculture.
We find that rainfall shocks are a major stress factor. A year with moderate drought increases
the incidence of suicide by 10 percent. On the other hand, providing irrigation decreases the
suicide mortality rate. We estimate that the expansion of irrigated land of 4 percentage points
in the state of Karnataka implied a reduction of 7 percent of farmers’ suicides. Finally, our
estimation results indicate that the shift from subsitance crops to cash crops, especially cotton,
is not increasing suicide rates, as has been claimed in the popular press. On the contrary, an
increase of one percentage point in the area under cotton is associated with a decrease in the
suicide mortality rate of up to 3 percent, holding all other factors fixed.
Keywords: Agrarian Distress, Farmers’ Suicides
JEL Classification: O130, Q100
∗ [email protected];[email protected]
versity of Heidelberg, the Goethe University Frankfurt and the Third Doctoral Research Seminar in
Development Economics at the DIW Berlin. The usual disclaimer applies.
1
1. Introduction
There are increasing concerns among policy makers, social scientists, and the media about
recent reported high numbers of suicides in rural areas in some developing countries, most
notably India1. In fact, since the late 1990s, there has been a marked increase in the
number of suicides among farmers in southern Indian states. In response, a number of
articles in the popular press blame various economic stress factors for this phenonemon,
most notably weather conditions, crop failure, the dependency on volatile prices, missing
or inappropriate irrigation facilities, and failure of agricultural policy. From an academic
viewpoint, these stress factors are risks of income shortfalls and asset depletion that are
common in low-income agriculture.
This is the first study that quantitatively addresses the relationship between economic
stress factors and suicides in low-income agriculture. Focusing on India is of a particu-
lar interest since the lack of systems of social security and formal insurances exacerbates
economic risks. We use novel data on suicides from 62 districts in two states, Karnataka
and Maharashtra, from the years 1998 to 2004. We merge those data with district-level
information on rainfall, cropping patterns and irrigation. The academic literature on de-
terminants of welfare of rural low-income households, media reports on farmers suicides,
and scientific case studies on this issue point out various economic stress factors that may
contribute to the recent surge in suicides in semi-arid India. Based on these literatures,
in our empirical analysis, we focus on three major predictors of farmers’ suicides, weather
conditions, irrigation, and the importance of cash crops.
Ourresultsareasfollows.First,rainfallshocksareasignificantpredictorofthenumber
of suicides in semi-arid India. Second, our results suggest that irrigation decreases the
suicide rate. Third, in contrast to what has been hypothesized in the popular press as
well as in case studies, we find that cash crops, especially cotton, are not driving up
suicide rates. All of these findings are broadly in line with existing academic literature in
development economics that investigates the effects of risk and structural transformation
in agricultural on household welfare. However, typically, that literature assesses household
welfareintermsofhouseholdincomeorconsumption.Incontrast,ourresultsprovidenovel
insights into welfare implications of agricultural risks by viewing the suicide of a farmer
as an extreme expression of self-perceived welfare loss.
1 Other examples include Ghana and Kenya in Africa.
2
The remainder of this paper is structured as follows. Section 2 reviews relevant strands
of the academic literature. Section 3 provides background information on the Indian wave
of farmer suicides especially in the areas of our sample. Section 4 describes our data.
Section 5 presents our estimation strategy and empirical results, and Section 6 concludes.
2. Welfare, Happiness and Suicide
Our study is located at the intersection of two general strands of the literature: Studies
on suicide, with or without the involvement of the happiness literature, and studies on
the determinants of household welfare for farming households in developing countries.
We provide background information about the specific case of farmer suicides in India in
section 3.
2.1. Studies on Suicide
Thusfar,committingsuicideismainlystudiedwithintheambitofthemedicalandpsycho-
logical literature. There are, however, a few exceptions that view this issue from economic
perspectives. The first economic model of suicide was developed by Hamermesh and Soss
(1974). They consider a lifecycle model with deterministic income, where an agent ta-
kes his life once the remaining lifetime utility given permanent income becomes negative.
They derive a negative theoretical relationship between income and suicide and provide
empirical results in support of this hypothesis. Suzuki (2008) develops this model further
by including a risky income process. He shows that the higher the income uncertainty of
an individual the more likely is this individual to commit suicide.
The above mentioned theoretical models view suicide as a function of income-based
utility. In a more holistic way of thinking we might regard committing suicide as an ex-
pression of particularly low individual well-being. Individual well-being has been a prime
interest for economic development, as e.g. expressed by Sen (1988): “..., the focus of de-
velopment analysis has to include the nature of life that people succeed in living”. Still,
the focus in most traditional empirical analyses of welfare in economics has been on mo-
netary measures such as the mean income and poverty indices (Ravallion and Datt, 2002,
and Besley and Burgess, 2000). Other, less prominent, examples of monetary measures
of welfare in development economics include the HDI and the multi-dimensional poverty
index (MPI) as well as vulnerability and risk.
3
Recently, however, there is an emerging more subjective approach to individual well-
being that has increasingly gained the attention of economists. The happiness literature
considers peoples’ own assessment of their individual situation rather than looking at
monetary measurements of welfare. Committing suicide is, after all, a decision people
take based on a personal evaluation of their lives and not an automatic event that occurs
once we cross a certain (lower) threshold. In this way we might think of the decision to
commit suicide as a function of happiness (or unhappiness) rather than purely economic
circumstances.2
But then, what makes people commit suicide? Empirically, it has been shown that
economic factors such as income, debt and unemployment affect happiness (Becchetti
et al., 2011, Brown et al. 2005, Knabe and Raetzel, 2011, and Clark, 2003). Moreover,
there is evidence that the professional situation affects happiness over and above its pure
monetary aspect (Winkelmann and Winkelmann, 1998). Finally, it is not purely one’s own
economic situation that influences happiness but also one’s economic situation compared
to that of one’s surrounding (Luttmer, 2004). The effect of happiness on suicide has
been studied inter alia by Helliwell (2007), Daly et al. (2011), and Daly et al. (2008)
using macro-economic data and yielding mixed results. Again, it seems it is not only
one’s own happiness but also the happiness in one’s surrounding that plays a role in
the decision to commit suicide. Using micro-data on self-reported happiness in a finnish
sample, Koivumaa-Honkanen et al. (2003) conclude that “self-reported unhappiness is
strongly associated with subsequent suicide in a long follow-up."
Alternatively, we might consider suicide not as a consequence of unhappiness, but
more as a measurement of extreme unhappiness.3 How well do suicide rates capture well-
being (as compared to self-reported happiness)? Daly and Wilson (2009) execute a cross-
validation exercise on micro data from the US and conclude that suicide data are indeed
usefulindicatorsofwell-being.JungeilgesandKirchgässner(2002)alsoproposethesuicide
rate as a “more objective, observable indicator[...] to measure ’general welfare’ or ’quality
of life’."
Finally, Chen et al. (2012) provide a recent survey on socio-economic predictors of
suicide. According to their evaluation, empirical studies provide a rather mixed picture of
2 The interconnection between (un)happiness and poverty has been studied by Kingdon and Knight
(2006).
3 Conceptually, this way of thinking of suicide is analogous to poverty measures in the traditional
study of welfare in economics.
4
the effect of economic variables such as unemployment or female labour force participation
on the suicide rate. The authors find support for a positive effect of income inequality on
the suicide rate and no effect of income. The above mentioned studies focus exclusively
on advanced economies.4 What distinguishes our study from existing ones on high income
countriesistheroleofindividualeconomicrisk.InallOECDcountries,therearesystemsof
social security and formal insurance markets. While the effect of a deteriorating economic
situation on suicides has received some attention (Pierce, 1971), we focus on economic risk
factors and not the general state of development and societal institutions, which is at the
center of attention in most of the existing empirical cross-country literature on suicides.
2.2. Determinants of Household Welfare
Themedicalliteraturehasrecognizedfarmersasoneofthegroupswiththehighestsuicides
rates across the globe (Malmberg and Hawton, 1999; Fraser et al., 2005). Explanations
include the high levels of economic risk resulting in large income fluctuations and the
exposure to pesticides (Malmberg and Hawton, 1999; Pickett et al., 1998). Nevertheless,
there are no formal attempts to economically investigate the determinants of suicides
of farmers and in particular farmers in developing countries. However, there is a well
established literature on the determinants of household welfare focusing on farmers in
low-income countries. As has been mentioned before, studies that identify these welfare
effects typically use household income or expenditure as measures of welfare.
Oneofthemostimmediatesourcesofriskforfarminghouseholdsarerainfallandother
weather shocks. These shocks are especially hard to mutually insure against because of the
covariate nature of this type of risk. While the importance of such shocks for the welfare
of rural households is indisputable, existing evidence suggests that it is crucial how one
measures rainfall shocks (Rosenzweig and Binswanger, 1993). Prevalent measures are,
for example, the level of rainfall (Dercon and Krishnan, 2000; Christiaensen et al., 2007),
drought indicators (Dercon et al., 2005; Thomas et al., 2010), and the monsoon onset date
(Rosenzweig and Binswanger, 1993). Accordingly, the results on welfare effects vary. Some
authors do not find effects of rain quantity on household welfare (Thomas et al., 2010).
Others find substantial negative implications of low rainfall levels on welfare (Dercon
4 One exception that also focuses on a non-advanced economy is Mitra and Shroff (2006). They use
state-level data on suicides in India and find that per capita income is a positive determinant of
the suicide rate. However, they use aggregate suicide data and do not consider different age or
professional groups.
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and Krishnan, 2000; Dercon et al., 2005). Furthermore, there is evidence suggesting that
these negative implications are not only short-term effects but also long-term effects.
Dercon et al. (2005) find negative welfare effects of drought up to 5 years after the event.
Christiaensen et al. (2007) conclude that households cope well with droughts in the short-
run but there are long-term implications on welfare.
For low-income rural households, one important instrument to mitigate income risk
is crop diversification. In this context, many researchers have documented the important
role of cash crops. Those crops are produced for profit; in contrast to subsistence crops.
Cash crops have been criticized for various reasons. First, they require expensive inputs.
Second, they are more prone to crop failure. Additionally, their prices depend on volatile
world market prices. Therefore, cash crops are often regarded as high-risk and high-profit
crops. A crop-wise overview of risk in area, yield and production in India is presented in
Raju and Chand (2008).
Although much of the literature has been concerned with the determinants of cash
crop adoption (de Janvry et al., 1991; Dercon, 1996), there is surprisingly little evidence
on the welfare effects of planting commercial crops. Some authors have highlighted the
beneficial role of cash crop adoption in theoretical models (Fafchamps, 1992). However,
the empirical evidence provides a mixed picture. Balat and Porto (2005) and Ashraf et al.
(2008) find positive effects of cotton-growing on household income in Zambia and Kenya.
However,Christiaensenetal.(2007)findnegativeorpositiveeffectsofcoffeeplantationon
consumption in Tanzania depending on the size of farmland devoted to coffee plantation.
Finally, Grootaert (1997) and Bozzoli and Brück (2009) find negative effects of cash crop
adoption on household outcomes.
The adoption of genetically modified (GM) crops is a special case in the debate of
welfare effects of cash crops. In India, several reports have associated the adoption of Bt
cotton (a genetically modified cotton variety that is resistant to bollworm infestation)
with farmer suicides. Despite the stark criticism in the media, available studies show no
evidenceofnegativewelfareeffectsofBtcotton(SubranmanianandQaim,2009).Further,
the econometric results of Gruère et al. (2008) contradict the interconnection between Bt
cotton and farmer suicides in India5.
5 ThefirstBtcottonseedswereapprovedforcommercialuseinIndiain2002.However,adoptionlevel
tookoffonlyin2004inMaharashtraandin2006inKarnataka(Gruèreetal.,2008).Therefore,their
relevance for our study is negligible.
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3. Farmer Suicides in India
In the late 1990s, there has been a sharp increase in the number of suicides among farmers
inIndia.MorethanhalfofallofficiallydocumentedsuicidescommittedbyfarmersinIndia
occurred in the three Southern states of Andhra Pradesh, Karnataka, and Maharashtra.
Figure 1 shows the geographical locations of these states within India. In this section we
present trends, patterns and reasons of farmer suicides in India.
Starting as a local phenomenon, news about farmers committing suicide soon beca-
me subject of immense national and international interest. The increase in suicides has
triggered a heated debate in media and in politics. For instance, in 2006, the New York
Times published an article entitled “Despair takes toll on Indian farmers”. Subsequently,
local authorities have taken several relief measures such as ex gratia payments to affected
families and waivers on loans and interest6. These measures have been taken on the basis
of the recommendations of the Johl Committee. In their report they state that agrarian
distress is manifested through economic factors, mainly indebtedness.
The typically cited story is about a middle aged farmer owning a small piece of land
where he grows a cash crop. Cash crops require expensive inpusts while the prices of
output depend on volatile world market prices that have been falling since the mid 1990s.
Additionally, India has embraced various cuts of subsidies. Moreover, timing and quantity
of monsoon rains in semi-arid India are unreliable and a farmer might be exposed to
more than one year of severe drought. This problem is more severe in the absence of
appropriateirrigationtechnology.However,somesourcesofirrigationhavebeenassociated
with suicide cases in the popular press. For instance, sinking a bore well is associated
with high costs and at the same time a high probability of being unsuccessful. On the
top of the above mentioned challenges, it should be mentioned that many farmers are
highly indebted. Investments in better seeds or fertilizer and adopting a better irrigation
technology have led to high levels of debt. In many cases, farmers pledge their lands as
collateral to obtain credit. All these factors constitute agrarian distress reaching the level
of committing suicide.
Available studies on this issue provide anecdotic evidence based on cases studies or ex-
post analysis with a small number of observations (Deshpande, 2002; Mohanty and Shroff,
2004;Mishra,2006;MohanakumarandSharme2006).Oneexplanationofagrariandistress
6 Thevastmajorityofthesemeasureshavebeentakenafter2004.Therefore,theywillnotbeanissue
in our subsequent analysis.
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which all researchers, politicians and journalists strongly agree upon, are crop losses due
to drought conditions. Crop failure and the associated income shortfall tpyically result in
economic stress. If profits of a cropping season are far below expectations and additional
sources of income are absent, then farmers might have to rely on credit in order to smooth
consumption and/or purchase inputs for the next cropping season. The following harvest
will be crucial for their economic situation. If subsequent periods of drought years hit then
farmers may fall in debt traps.
A further issue that has been mentioned in connection to farmer suicides is the availa-
bility of irrigation facilities. While irrigation can be beneficial in increasing yield and thus
lead to positive economic outcomes, private irrigation is on the other hand costly and
according to some authors (Posani, 2009; Sangalad and Huddar, 2011) associated with
high debt burden. In his field study, Deshpande (2002) finds no correlation between sui-
cides and farming under rain fed conditions. Moreover, crop losses due to lack of rainfall
are expected to be worse under rain fed conditions. A close look at different sources of
irrigation might be of greater insight.
The growing area under cash crops, compared to that under food crops, is often viewed
as a cause of agrarian distress. As mentioned above, cash crops generally require higher
and more costly inputs and output prices are driven by global price decline. In addition,
as suggested by Mohanty and Shroff (2004) and Rao and Suri (2006), there is the danger
of monoculture. That is, less diversification leads to higher financial risk when facing
productivity and/or price shocks.
Finally, various field studies undertaken in the suicide prone states of Maharashtra,
Andhra Pradesh, and Karnataka consider other socio-economic characteristics of the vic-
tims. For example, Mohanty (2005) describes a correlation between belonging to a lower
caste and incidence of suicide. This correlation might be the result of discrimination by
higher castes, lack of skills, and the size of landholdings.
4. Data
For this study, we collect data at the district level for the southwestern Indian states of
Karnataka and Maharashtra for the years 1998 to 2004. Within this period, the state
of Karnataka comprised 27 districts whereas the state of Maharashtra consisted of 35
districts. Table 1 displays a list of our variables with their definitions, and summary
8
statistics including means and standard deviations.
The source of the data on incidence of suicides are the State Crime Records Bureaus
(SCRB) of Karnataka and Maharashtra. They are given for the period of one calendar
year.AllotherdatathatweuseinouranalysesrefertotheIndianfinancialyearthatstarts
in April. Figure 2 summarizes the timing of important events for agriculture in Southern
India.Thisisanimportantissuesinceasmentionedbeforethesuccessofacroppingseason,
and hence the economic status of farmers, largely depends on the previous monsoon and
the weather conditions during the harvest period. In the districts considered here, the
major crops are sown in July and harvested in November. Therefore, we match suicide
data for a given calendar year with data from the financial year starting in April of the
same year. This approach is supported by findings in Mohanty and Shroff (2004) stating
that almost all suicides by small farmers occurred during harvest season.
The data on incidences of suicides that are provided by the SCRB are disaggregated by
gender and age groups as well as professions.7 For the purpose of our analysis, we restrict
our attention to those households working in farming/agriculture. Figure 3 shows the
distribution of suicides and confirms what has been suggested by popular media and field
studies. Namely, suicides are committed mainly by male farmers. Notably, among male
farmers, those between the age of 30 and 44 constitute about 39 percent of all committed
suicides. This is the age where a male is typically the main provider of the household and
is responsible for taking economic decisions.
Regarding the dependent variable in our subsequent analyses, we consider the suicide
mortality rate (SMR) defined as the number of suicides in 1,000,000 people. Figure 4
shows that there is substantial variation in SMRs across districts and time, especially in
Karnataka.
In line with the preceding discussion, we focus on three economic predictors of suicide,
one are weather shocks. There are various definitions of drought.8 We follow the meteo-
rological approach. For our study, we compute the percentage deviation of annual rainfall
from the long-term average (Rainshock).9 Accordingly, we define drought as a rain deficit
7 Although there are always concerns about data quality when dealing with suicide data – even in
developed economies - we are confident regarding the data quality in India due to strict legal re-
gulations. There is no reason to expect systematic differences in reporting across states or districts
(Mayer, 2011).
8 The National Commission on Agriculture in India has categorized drought into three types: hydro-
logical, meteorological and agricultural drought.
9 A similar approach is used in Duflo and Pande (2007)
9
of at least 20 percent. The mean of Rainshock is negative indicating that our sample
period is characterized by rainfall levels below average. Our calculation reveals that the
driest year in our sample is 2002. In this year 60 percent of all districts in Karnataka and
Maharashtra experienced drought conditions. Karnataka was hit especially hard with over
80 percent of districts suffering from drought and 2003 bringing no relief with another 70
percent of districts being hit by dry conditions. Districts experienced on average two years
of drought between 1998 and 2004 with some districts suffering from drought every second
year.
The second economic predictor of interest is the change in cropping patterns. As de-
scribed above, biased allocation towards cash crops (solely produced for sale on markets
in contrast to food crops that are also used for private consumption) might increase agra-
rian stress. In Maharashtra, typical cash crops include cotton, oilseeds and sugarcane. In
Karnataka, the same crops are popular in addition to tobacco. The most important cash
crop in both states was oilseeds followed by cotton. In Karnataka, cotton makes up only a
minor share of all crops with relative area devoted to cotton being more than 10 percent
only in very few districts. In Maharashtra, regional disparities are large. Cotton plantati-
on covers about 16 percent of total area cropped. However, a rather substantial fraction,
about 47 percent of total area in the North Eastern region of Vidarbha10 is devoted to
cotton cultivation. Figure 5 shows that the cropping pattern in Maharashtra has been
rather constant in our sample period. In Karnataka, there has been slight variation in the
area under both types of crops. Most notably, the area under food grains went down from
74 percent 2000 to 68 percent in 2004. There have also been fluctuations in area under
cotton. The most important food crops are food grains, including paddy and wheat. In
our sample period, food grains, on average, constitute more than half of the cropped area.
The third predictor of interest is the share of area under irrigation to the total crop-
ped area. Unfortunately, the data for Maharashtra only cover the period from 1998 to
2002. In Karnataka, about 35 percent of the total cropped area is irrigated whereas in
Maharashtra it is only 15 percent. The growth in area under irrigation is also unevenly
distributed between the two states. Between 1998 and 2004, the area under irrigation has
increased by roughly four percentage points in Karnataka, whereas it has almost been
constant in Maharashtra in our sample period. Furthermore, we consider the share of area
under different sources of irrigation. For the state of Karnataka we have data on area
10 Vidarbhacomprises11ofthe35districtsofMaharashtra.Fromthebeginningofreportingoffarmer
suicides, the cotton growing region of Vidarbha was in the spotlight of media attention.
10