Farmer Suicide Crisis In India - Truth Or Myth?
A scientific analysis of the data on suicides contradicts the popularly held belief that farmers in India face a suicide crisis. The data shows that other than a few states like Kerala and Punjab, farmers face relatively lower rates of suicide.
It is the completely overlooked population of non-farm workers including vendors, small businessmen, daily wagers, etc., that faces far more vulnerability to suicides than farmers.
For many years now, the claim that India faces a 'farmer suicide crisis' has become almost axiomatic. Media articles, reports, and even academic papers have routinely used imagery such as " and ".”
Often, alongside such claims are numbers of suicides of farmers that are picked from the annual reports of the National Crime Records Bureau (NCRB) and presented as corroborations. But a closer look at the data and the inferences drawn from it brings forth major fallacies and errors including the usage of absolute numbers, wrong population sizes, and the lack of proper scientific controls.
The data of the past 25 years when analysed scientifically, paints a more nuanced picture.
It shows that other than Kerala, Punjab, and a few other states for a couple of years, farmers in India face relatively lower rates of suicides.
It also indicates that the non-farmer working population that includes the vendors, small businessmen, daily wagers etc, faces much higher rates of suicides compared to the farmers.
This section of the population has been completely invisible to the discussions on suicide vulnerability in media, academia, and among policymakers.
What data do we have on farmer suicides?
Most data on farmer suicides that is quoted in studies and articles is sourced from the ‘Accidental Deaths and Suicides in India’ (ADSI) reports published by the National Crime Records Bureau (NCRB).
NCRB collates data on accidents and suicides for different demographics collected from all the states in India and publishes yearly reports aggregating them.
Since farmers were thought of as particularly vulnerable to suicides, the NCRB, since 2014, has been publishing a whole section on farmer suicides with additional details.
The data published in ADSI reports has not been without problems.
For example, some states like West Bengal have consistently not reported any farmer suicides for many years now. Nevertheless, this data with all its imperfections has been used in studies, not unreasonably, because that is the best that is available to get a picture at the national and state levels.
But more than the problems with the data itself, it is the interpretation of the data that has been marred by serious errors and fallacies.
The Fallacy Of Absolute Numbers
The numbers of suicides of farmers from the ADSI reports, for example, are routinely used in media as indications of a suicide problem among farmers. We are told, for instance, that , or that , or that to give us a sense of the severity.
Every suicide is indeed a tragedy. But do these numbers really indicate a farmer suicide problem?
Absolute numbers like these can only indicate the existence of suicides within a population. But suicides exist in all human populations across the world. So these numbers in themselves tell us precious little about whether the level of suicides is high or low. There is no reference associated with them to make that judgment.
And yet, these numbers generate an impression of largeness when quoted. I call this the ‘Fallacy of Absolute Numbers’: it is a heuristic or a cognitive shortcut that mistakes the 'numeric' for the 'categorical'.
These numbers can convey meaningful information only when they can be compared to those of a reference population. Since populations vary in size, the first step towards an accurate comparison is to normalise the number of suicides for population or to convert them into suicide rates.
The measure that is generally used in studies is the Suicide Mortality Rate (SMR) which is ‘suicides per a hundred thousand individuals’ of the population being considered.
When we normalise the suicide numbers used in the above-mentioned claims, using the population sizes (from the 1991, 2001, and 2011 Census of India reports, calculated for other years through interpolation and extrapolation) we get Suicide Mortality Rates for farmers that are significantly lower when compared to all workers and the overall population in India.
Figure 1 shows the SMRs for these three populations for the past 25 years. And clearly, they do not indicate a farmer suicide problem at an all-India level.
But suicide rates vary significantly across states and are also strongly dependent on variables such as gender (men, for example, show significantly higher rates of suicide than women the world over).
Many studies on farmer suicides have hence rightly suggested that state and gender-specific data on farmer suicides be looked into separately albeit higher rates of suicides among them are subsumed within averages at the national level.
Some studies have specifically drawn attention to male farmers in certain populous states as being the most vulnerable. In the next sections let us examine this data and the claims in detail.
Errors In Previous Studies
Many studies in the past have tried to get a picture of the phenomenon of suicides among farmers by calculating their suicide rates using gender-specific suicide data at the state and national levels and comparing them against those of the non-farmers who are taken as the reference populations.
Two papers, for instance, of the Madras Institute of Development Studies in 2008 and of the London School of Economics in 2014 had separately analysed this data and concluded that farmers in India, especially male farmers, face very high rates of suicide.
This not only set the alarm bells ringing but also helped set off the narrative of a farmer suicide crisis in India. But their calculations had a simple error that would become apparent only later.
Until 2014, the NCRB’s reports had been publishing the number of suicides of all farmers under a single tag called ‘Farming/Agriculture’. It was not readily apparent whether this tag referred to the ‘Cultivators’ alone or also included ‘Agricultural Laborers’ (cultivators are farmers who own or rent the farmland as against the agricultural labourers who are employed as workers in the farms).
The two studies had assumed that the numbers of suicides published under this tag were only of the cultivators and had based their calculations on it. But later it turned out that the tag included all farmers i.e both cultivators and agricultural labourers.
The assumption had led the two studies to choose the wrong population sizes in their calculations, leading to inflated rates of suicides for farmers.
The error became evident after the NCRB’s yearly reports, starting 2014, began publishing the data explicitly for both the categories of farmers separately, along with their aggregate.
A 2016 , pointed out this error and used the corrected population sizes in its own calculations. Based on these calculations, the study analysed the suicide rate ratios of farmers and non-farmers for the period between 1995 and 2011, nationally and for 19 major states that accounted for 97 per cent of the farmer suicides in India.
The study found that the problem of suicides was largely non-existent among female farmers who showed significantly lower rates of suicides compared to female non-farmers. Male farmers also showed lower rates nationally and in most states, but with some important exceptions: most significantly, Kerala showed higher rates for all of the years studied, Maharashtra for all but two years, and Chattisgarh, Karnataka, Uttar Pradesh, Madhya Pradesh, and Uttarakhand for few of the years studied.
These higher rates of suicide among male farmers in these states, the paper claimed, was an indication of the ‘severity’ of farmer suicides in these states.
This paper revised the earlier suicide rates which were based on wrong population sizes and painted a more nuanced picture. But, as we shall see, the results of this study too, have some inaccuracies due to the artifacts introduced by the choice of the reference group.
Using Better Scientific Control
The accuracy of the results of a study depend on how close or similar the reference population being used in the study is to the population that is being studied. If, for example, a study is analysing the effectiveness of a drug and if the ‘control group’ used as the reference is predominantly that of children while the ‘experimental group’ or the group being treated has people of all ages, it would be difficult to say how much of the recovery is due to the drug itself and how much could be due to the factor of age.
Hence, it is imperative for studies, to try and control for all variables other than the one being studied.
Suicides like other mortalities are “strongly age-dependent”. Figure 2 shows the distribution of suicides by age for the overall population. Hence it is important to control for age to get accurate results.
But the studies on farmer suicides that we have considered above do not control for age.
Figure 3 shows the age distribution of the farmers and the non-farmers who are used as the reference in these studies. It can be seen that the two populations differ significantly in their age distribution.
‘Non-farmers’ consist of all age groups, even infants, and children among which there are very few suicides.
Farmers, on the other hand, consist mostly of the working-age population where the bulk of the suicides are witnessed (compare with Figure 2). This difference makes the non-farmers unsuitable as a reference for comparison with farmers in studying suicides because such a comparison would have distortions due to age.
Let us consider an alternative. Figure 4 shows the age distribution of farmers and another group - the 'non-farm workers'.
'Non-farm workers' are all workers minus the farmers. Farmers constitute about 55 per cent of all workers in India, so the non-farm workers are the other 45 per cent of the workforce.
We can see from figure 4 that the age profile of farmers is similar to that of the non-farm workers. So, if we use ‘non-farm workers’ in place of ‘non-farmers’ as the reference, it can help minimise the distortions due to the variable of age.
It can help us understand if farmers, who are predominantly in the working age population, are more prone to suicides when compared to other groups with a similar age profile.
Analysis of data on farmer suicides
Based on the above findings, I chose other workers or ‘non-farm workers’ as the reference and analysed the suicide rates of farmers for the period between 1995 and 2019, nationally and for 21 most populous states (with more than 1 million farmers each) that together account for 98.5 per cent of India’s farmers.
Tables 1 and 2 (at the end of the article) tabulate the ratios of suicide rates for male and female farmers respectively.
The results concur to some extent with the 2016 study by Deepankar Basu et al., in that the rates of suicides among female and male farmers are considerably lower than those of the respective reference populations in most instances.
However, the important departure with that study is in what it had detected as the “severity” of farmer suicides among male farmers in many states. With the change to a more accurate reference population, fewer states now show the farmer suicide problem.
Kerala is one state that continues to show consistently higher rates of suicide for male farmers for most of the period. But Maharashtra now shows such a result only for four out of the 25 years.
All other states, namely, Chhattisgarh, Karnataka, Uttar Pradesh, Madhya Pradesh, and Uttarakhand that were listed as “severely affected” in that study no longer make it to the list for any of the considered years.
Two other states, namely erstwhile Jammu and Kashmir and Punjab show up on the list especially when the data from the period between 2012 to 2019 which was not analysed in the earlier study was also considered. Kerala, Jammu and Kashmir and Punjab also show relatively higher rates of suicide among female farmers for five, three, and one years respectively out of the 25 years studied.
So, the analysis tells us that a lot of what was detected as the problem of farmer suicide and its ‘severity’ in earlier studies was in fact distortion introduced because the variable of age was not controlled for.
Newer data on farmers suicides
The NCRB, from 2014 onwards, has started publishing additional data including the breakdown of the number of suicides committed by ‘cultivators’ and ‘agricultural laborers’. This provides an opportunity to get a better understanding of the suicides in these two sections of farmers.
I calculated the suicide rates of these sections for the period between 2014-2019 (the six years for which the data is available) and analysed them in comparison to the suicide rates of non-farm workers. The ratios of the suicide rates are tabulated in Tables 3 and 4 (at the end of the article).
The results show that agricultural labourers have significantly lower rates of suicides compared to cultivators in most states. Also, both cultivators and agricultural labourers show lower rates of suicides compared to the respective non-farm worker reference populations, nationally and in most states. But there are a few important exceptions.
Three populous states, namely Punjab for three years, Maharashtra for two years, and Karnataka for one year, show suicide rates of male cultivators to be more than those of the reference populations.
Punjab also shows higher rates of suicides among female cultivators for five out of the six years, pointing to the phenomenon of farmer suicide problem among women which was considered largely non-existent.
Three populous states show higher rates of suicides among agricultural labourers, namely erstwhile Jammu and Kashmir for five years, Himachal Pradesh for three years, and Kerala for two years among male agricultural labourers and Jammu and Kashmir and Kerala for one year each for female agricultural labourers.
It is possible that there are smaller sections within farmers like cultivators of particular crops or farmers belonging to smaller geographies (including states like the North Eastern States, Union territories, Delhi, and Goa which have not been included in this high-level analysis) who may have higher rates of suicides and this may be hidden from the data because of the averaging at the higher levels. They need to be considered in more detail through better and more granular data and empirical studies.
It is important to also note that for most data-points that were considered in this study, the rates of suicides of farmers are relatively low compared to that of the non-farm workers. In other words, the rates of suicides of non-farm workers are higher in most cases.
Who are these non-farm workers who the data indicates face higher rates of suicide?
The NCRB’s reports tell us that they include vendors, small businessmen, workers in private companies, daily wage workers, tradesmen, and many others. Most of these workers are in the informal economy.
We do not have additional information about them to calculate their individual rates of suicides. But we know from the data that this group as a whole faces far greater vulnerability to suicides, nationally, and in most states, and even in those states that have sometimes shown higher rates of suicides among farmers.
But this section of the population has been completely invisible to the discussions on suicide vulnerability and to policy interventions.
In conclusion, the available data on suicides for the past 25 years presents no evidence to the claims of a farmer suicide crisis in India.
The data shows that farmers, at the national level and in most states, face significantly lower rates of suicides compared to other workers.
The few populous states that do show higher rates of suicides for farmers, or a section of them, for a certain number of years include Kerala which shows most severity, followed by Punjab and Jammu and Kashmir which show some severity, followed by Maharashtra, Karnataka and Himachal Pradesh which are affected to a much lesser degree.
This pinpoints the extent of the farmer suicide problem in India based on the currently available data.
The data also shows that the completely overlooked population of non-farm workers or workers other than those in farming, face far greater rates of suicide than the farmers.
Notes for tables 1 to table 4
1. Calculated based on NCRB’s ADSI reports for 1995-2019 and Census of India reports for 1991,2001,2011.
2. States with more than 1 million farmers have been included and arranged based on the size of the overall farmer population.
3. The values are rounded off to two decimal places.
4. A value of more than 1.0 (marked in red) indicates that the farmer’s group considered in the table has higher rates of suicide than the reference population.
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