ISSN (Print) - 0012-9976 | ISSN (Online) - 2349-8846
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The Politics of Farm Loan Waivers

A Comparative Study

Ajit Phadnis ( is with Humanities and Social Sciences Area, Indian Institute of Management Indore, Indore. Aishwarya Gupta ( studies at the Indian Institute of Management Indore, Indore.

Loan waiver policies are ostensibly political decisions, but surprisingly there have been no political analyses of the policy. The paper presents a political study on the policy through a descriptive analysis of a comprehensive primary data set that comprises all loan waiver announcements in India over the last three decades. The findings bring into light the political, economic and environmental factors that have had a bearing on the politicians’ choice to introduce waivers. Further, it highlights that politicians choose from a variety of waiver policy designs, and this choice has substantive implications for the size of the waiver programme.

The authors thank the participants at the XIIIth International Conference on Public Policy and Management hosted by IIM Bangalore for their comments. They would particularly like to thank Gopal Naik,
N Ravi, Suhas Palshikar, Trilochan Sastry, Aparna Krishna, Gursewak Singh and Ravish Tiwari for their comments on an earlier draft/presentation of the paper.

Loan waivers have emerged as the prominent policy choice for addressing the issue of agricultural distress. Over the last one year waivers of farm loans were announced by a number of state governments such as Uttar Pradesh (UP), Maharashtra, Rajasthan, Punjab and Karnataka and the policy is under serious consideration by the state governments of Madhya Pradesh and perhaps even by the central government. This expansion of the loan waiver policy has prompted many studies and commentaries by scholars that have presented a variety of perspectives on the issue.

The extant discourse on the policy may be divided into three broad categories. The first category constitutes commentaries that are supportive of the policy and argue for the need for waivers to relieve the persistent debt stress faced by farmers following years of rural stagnancy. Commentators holding this view argue that if waivers have been granted to industrialists, why should they not be extended to farmers that are in dire straits and are committing suicide (Sainath 2008)? Alongside this is also the rational argument of the debt overhang theory (Patel 2017: 6) that hypothesises that loan waivers would help distressed farmers overcome the debt baggage and enable them to make productive investments.

The second category of papers reflect a critical view of waivers. Martin Kanz (2016) demonstrates empirical evidence that is inconsistent with the debt overhang theory. His study of the 2008 loan waiver granted by the central government shows that loan waiver beneficiaries tend to make lower investments and have less productive farms than similar non-beneficiaries. A negative view is also reflected in H S Shylendra’s (1995) study of the national loan waiver of 1990. His empirical evidence demonstrates that loan waivers primarily benefit the better-off households and waivers adversely impact the repayment
behaviour of borrowers. Further, Shamika Ravi (2015) argues that it is poor mental and physical health and not indebtedness that is the leading cause of suicides among farmers in India. Loan waivers are, in her opinion, a reactionary policy emerging from a simplistic diagnosis of the causes for farmer suicide.

The third category of work presents a more nuanced view. Saptarshi Mukherjee et al (2014) differentiate the impact of loan waivers on distressed and non-distressed borrowers. Their research shows that waivers have had a positive effect on the loan performance of distressed beneficiaries but have had no effect on non-distressed beneficiaries. Further, they find that loan waivers also lead to rationing of future credit1 by banks to the non-distressed borrowers. A Vaidyanathan (2008) and Nilkanth Rath (2008) analyse that the policy works as a temporary palliative to the debt stress faced by farmers but will not have a long-term impact on improving their living conditions.

The above studies make it clear that the existing empirical evidence does not portend an encouraging picture of the loan waiver policy. Loan waivers tend to disproportionately benefit the better-off farmers, lead to lower future investments and productivity, and also result in selective credit rationing by banks. The overarching thrust reflected in many of the studies is that the long-term investments in agriculture and the rural economy may result in higher and sustained dividends to farmers rather than the instinctive payouts in the form of waivers. This inconsistency between the intellectual discourse and the observed proliferation of loan waivers impels an answer to the question on why policymakers in India have increasingly resorted to short-term reprieves when there is opportunity to make more sustained interventions in the rural economy.

We believe this is an important and complex question that needs careful reflection and analyses. The evidence cited above suggests that the rationale for loan waivers does not lie so much in the economic benefits that it delivers to distressed farmers but it is more likely a product of the peculiarities of the policymaking process in India. Loan waivers are ostensibly political decisions taken by political actors with a view to appropriate concrete political gains. Therefore, in order to understand why politicians choose waivers as their pre-eminent policy choice for addressing the distress of the rural sector, we need to analyse the incentives and disincentives that drive their political decisions.

To our surprise we were not able to locate any study that exercises a political lens to analyse the loan waiver policy. Loan waivers have been around in India for over three decades but barring a few passing references (Chandra et al 2008: 471; Jaffrelot 2010: 469; Ruparelia 2015: 117) there has been no systematic attempt to uncover the politics behind the policy. The knowledge gap that has developed over the years is therefore immense and presents an opportunity for a plethora of political studies on the subject using a variety of research approaches.

The mandate for this paper is fairly limited. We wish to stimulate a conversation around the politics of loan waivers. As a plausible anchor for this conversation we present a comparative study of loan waivers introduced in India over a 30-year time span since the first loan waiver was announced way back in 1987. This is a descriptive study so the findings are intended to be only suggestive. We hope that the framework outlined here would motivate in-depth studies into some or all of the dimensions identified here.

Brief History of Loan Waivers

Loan waivers are a fairly recent phenomenon when viewed in the context of India’s 70-year democratic history. The first loan waiver was announced about three decades ago in 1987 by the then Chief Minister of Haryana, Chaudhary Devi Lal. When viewed in the context of the political environment during that era the policy does not seem entirely misplaced. The 1980s was a period that witnessed the emergence of new social groups on the national political stage following the success of the green revolution in the 1970s. The resulting economic ascendance of the middle peasants coalesced with the political ascendance of the Other Backward Classes (OBCs) to deliver a new level of political mobilisation to this hitherto under-represented group. Alongside the strengthening of the political organisation of the farmer community came a number of demands ranging from subsidies for inputs such as fertilisers, farm equipment and power to minimum support price (MSP) for farm produce and more recently the calls for loan waiver.

It is instructive to see that shortly after the loan waiver announcement in his state, Devi Lal went on to become the Deputy Prime Minister under the V P Singh government in 1989. Here as well, the central government of the day declared the first agricultural loan waiver at the national level. Post these early announcements there have been 16 waivers as listed in Table 1.

Table 1 shows that after the initial thrust there was virtually a moratorium on waivers for more than a decade until mid-2000. The next half-decade from 2005 to 2010 witnessed four waivers: Two in the southern states of Kerala and Tamil Nadu, one in Maharashtra and the one large central waiver in 2008. The following five years between 2010 and 2015 witnessed a significant ramp-up with five loan waivers, all from state governments such as Karnataka, Chhattisgarh, >UP, Andhra Pradesh and Telangana. We are still in the middle of the last five year period and already there have been seven loan waiver announcements from the state governments of Tamil Nadu, >UP, Punjab, Maharashtra, Rajasthan and two waivers in Karnataka alone. This broad trend suggests a steady acceleration in the number of loan waivers after 2005.

Another interesting insight that emerges from the table is that loan waivers seem to be more popular among state governments as compared to the central government. Sixteen of the 18 waivers listed above came from state governments while only two came from the central government. In fact post 2008 all the waivers announced were by different state governments and none came from the centre. This
suggests that waivers are largely a matter of state policy. We will focus on this state-centric feature of loan waivers to reveal comparative insights on how the policy has varied in its context and design.

Before we set out on the descriptive analyses of the data a few qualifications pertaining to the data set are necessary. First, the data set is constituted only of loan waivers that cover the entire expanse of the state or nation. We do not include waivers that are limited in scope to particular districts or regions within a state. This differentiation is necessary as the financial implications of small-scale waivers are not comparable to state or nationwide efforts. Second, we only include waivers that entail partial or complete moratorium of the capital value of the loan. Plain interest waivers are excluded since they are of limited financial consequence.2

Having set the initial foundation for discussion, we will now pick up some prominent arguments pertaining to loan waivers and evaluate them using the exhaustive cross-state data that we have collated.

Ideological Motivation

Some commentators have imputed a certain ideological motivation for loan waivers. For instance, R S Kapoor (2018) believes that waivers reflect the persisting socialist baggage of Indian policy-makers even after the clear transition to a capitalist thinking since economic liberalisation in 1991. We gather that if there was an ideological leaning behind the policy then we would expect waivers to be more proliferated among parties that espouse one particular ideology as compared to others. More specifically, we would regard that waivers would be more agreeable to parties that are ideologically positioned to the left or the left of centre. Figure 1 illustrates the party-wise distribution of waivers announced since 1987.

We find that quite remarkably the data defies our expectation. Out of the 18 loan waivers, only one waiver can be traced to a left-leaning party (Communist Party of India [Marxist]—CPI[M] in Kerala) and four to the centre-left Congress party. Many loan waivers (eight out of 18) were introduced by state governments ruled by right-leaning parties. Five of these came from Bharatiya Janata Party (BJP)-ruled states and three from regimes governed by right-leaning regional parties Telugu Desam Party (TDP), Telangana Rashtra Samithi (TRS) and All India Anna Dravida Munnetra Kazhagam). The rest five waivers are from other regional parties.

The evidence on the ideological types of waiver announcing parties appears so dispersed that it is difficult to narrow down to a single ideological motivation that drives the policy. Waivers have been announced multiple times by the Congress, the BJP and a number of other regional parties. This observation suggests that loan waivers have no clear relation with a particular political ideology.

Electoral Exigency

If not ideology then politicians are known to work for either elections or office. The second test is therefore to check whether waiver policies are linked to their electoral interest. We analyse this by investigating the timing of waiver announcements within the electoral cycle as shown in Figure 2.

The evidence in favour of a connection between waivers and elections is striking. In the case of seven waivers, the policy was announced about a year or a year and half prior to the impending election. This timing seems propitious as it gives the ruling incumbent sufficient time to implement the scheme and distribute benefits before it faces the electoral test. In 10 other cases, loan waivers were implemented by ruling parties within a year of coming to power. The latter are cases of political challengers who had promised loan waivers in their election manifestos. On successfully coming to power, waivers appear to be one of the first policy promises that politicians are keen to fulfil.

The above discussion shows overwhelming evidence (17 of 18 waivers) in favour of the conjecture that waivers are timed to match the electoral cycle. The case of Maharashtra in 2017 seems to be the only exception where a waiver was announced in the middle of an electoral cycle. The overall evidence suggests that the electoral incentive is a strong motive for politicians to announce waivers.

Relief from Drought

It is no surprise that politicians are motivated by electoral considerations for planning the policy. This is quite expected and the data only reinforces the existing belief. The more interesting question is, how do politicians project a rational basis for the policy? We delve into this aspect by analysing the policy rationale reflected in the speeches3 made by politicians while announcing their intent for waiving loans.

We find a common thread running across the speeches. Politicians tend to rationalise the need for a waiver by focusing public attention on a drought situation faced by the state. Loan waivers are thereafter justified as a means to alleviate the debt stress faced by farmers in the face of severe drought. Instances of such rationalisations are many but for the sake of illustration we will cite only a few. In June 2017, Maharashtra chief minister announced a farm loan waiver that is likely to cost the state exchequer a sum of ₹ 34,000 crore. The rationale behind the policy as stated by him was: “There had been a demand for loan waiver for farmers who have been severely affected due to continuous drought since 2012” (Telegraph 2017).Quite strikingly in the same month, the Karnataka chief minister cited two years of drought in the state as the cause for farmer distress which he hoped to alleviate through waivers (Hindu Business Line 2017). Further, in May 2018, the chief minister of Punjab wrote a letter to the Prime Minister requesting him to announce a debt waiver in order to help farmers tide over losses incurred from adverse climatic conditions such as drought (Chauhan 2018).

This anecdotal evidence establishes the centrality of drought within the arguments made by politicians to rationalise loan waivers. But, what about the application of this argument? Do policymakers apply the logic of drought to decide on when to announce waivers? This is the next question that we turn to.

We evaluated the efficacy of the drought argument by converging two data sets: one on rainfall data published by the Indian Meteorological Department (IMD)4 and the second on the timing of loan waiver data that has been described earlier. For the former we used fine-grained district-level data on rainfall to collate a statewise measure of the percentage of districts in the state that received deficient5 rainfall during the year. We use this measure to make a judgment on whether the state should or should not be designated as drought-affected. Table 2 illustrates the drought scenario for each state for a period of three years prior to the announcement of the waiver.

As mentioned in Table 2, we used two measures of drought for the analysis. The first measure is a relatively lenient one where states are designated drought-hit when at least one-third of their districts have received deficient rainfall. The second measure is more stringent where statewide drought is declared only when at least half the districts have received deficient rainfall.

The findings are revealing. While we cited earlier that policy-makers rationalise loan waivers by exercising the argument of drought, the evidence does not seem to tally with the rhetoric. Surprisingly, we found that in four cases (Rajasthan 2017, Andhra Pradesh 2014, Karnataka 2012 and Maharashtra 2009) there was no condition of drought in the three years prior to the announcement of the policy. In seven other cases (using the lenient measure), the state was drought affected in one of the three previous years. However, three cases (Punjab 2017, >UP 2017 and >UP 2012) were particularly severe where the state experienced drought in all the three years.

The evidence suggests an uneven pattern between loan waivers and droughts. In some cases the relationship is clear with waivers having been preceded by multiple years of drought. But in other cases we find no evidence to suggest that there was a drought prior to the announcement of the waiver.

Fiscal Viability

Concerns regarding the fiscal viability of loan waivers are rife in the literature. Waivers have been criticised for posing an additional burden on the limited financial resources of the state (EPW 2017). However, to our knowledge, this conjecture has so far not been supported with evidence. We evaluate the arguments surrounding fiscal viability in three parts. In the first part we estimate the allocation for loan waivers in the budget year in which they were announced. In the second part we estimate the opportunity costs associated with loan waiver proposals. Finally, we analyse whether state governments appear to be conscious of their fiscal position while taking decisions regarding waivers.

Figure 3 (p 54) gives an illustration of the resource-intensiveness of all loan waivers. We find that waivers are, in general, fairly resource-intensive efforts. If we take a simple state average of the loan waiver allocation as a percentage of the state budget, it works out to a high of 9.1%. This high average of course masks the wide variation in waiver policies across states and even across time. For instance, the loan waiver announced by the Andhra Pradesh government in 2014 was the biggest when viewed as a percentage of the budget. As opposed to this, the loan waiver announced in Kerala in 2006 was the least resource-intensive (0.3% of budget). It is also interesting to see that two or more loan waivers announced in the same state may differ in their allocations. For instance, the >UP loan waiver announced in 2006 accounted for less than 1% of state budget as the scheme was limited to waiver of farm loans only from cooperative banks. The same state in 2017 announced a much larger programme constituting 9.5% of the state budget that encompassed cooperative as well as commercial banks.

Our next effort was to arrive at an estimate for the opportunity cost of the waiver policy. What if the resources committed to waivers were instead allocated towards longer-term investments in agriculture? What would have been the likely accretion in investment? This measure would reveal the extent of trade-off that a loan waiver programme entails for long-term investments. In line with this premise we chose to compare the one-time allocation for loan waivers with the annual allocation for agriculture in a year just prior to or after the waiver.6Table 3 (p 53) displays the data for waiver announcements post 2012.

The table reveals a substantive opportunity cost associated with waivers. In place of a waiver if the same amount is transferred to the agricultural budget we would find between 22% to 670% increase in the annual agricultural budget. This, we believe, could entail a substantive jump in the resources available for agricultural investment, which could open up new possibilities for transforming the existing approach towards agriculture and rural development.

The third concern relates to the fiscal viability of waivers in the face of the financial debt incurred by the states. Here we feel it is instructive to throw light on the macro-picture before we set sights on the individual state waiver data. The broad picture can be gauged from Figure 4.

We see an interesting trend reflected in the data. Average debt/gross state domestic product (GSDP) ratio showed a steady rise over the period 2000 to 2005 but post 2006 the average debt levels of states has shown a consistent decline. By 2015 average state debt/GSDP reached an all-time low of 21.7%. It is interesting to see that the “second wave” of loan waivers started in 2006 and went right up to 2014 coinciding with the period that witnessed a steady decline in state debt.

The macro-picture reveals an interesting broad trend that the propensity for state governments to announce waivers tends to rise as they gain more control over their state debts. Prior to 2006 when state debts were high no loan waivers were announced. This pattern suggests that state governments have been fairly conscious of their fiscal position. When debts tended to rise, the propensity to announce waivers dropped. Unfortunately, the pattern visible for the second wave of waivers is no longer in practice during the third wave of waivers beginning from 2016. After 2015 average state debt has seen a rise and alongside this we also see a rise in the number of waivers. The imminent trend suggests that state governments seem less bothered now about their debt position than they were earlier.

This shifting trend in the fiscal consciousness of states is more evident when we look at the data on individual loan waiver announcements. Table 4 posits the debt position of states alongside the all-India average debt among states in the year the waiver was announced.

We find two striking patterns. Out of the nine loan waivers that were announced prior to 2016, seven of them were introduced by states that had lower debt/GSDP ratios than the all-India state average. The only two states (>UP in 2012 and Kerala in 2006) that had higher debt ratios, presented waivers of small size (less than 1% of state budget). The trend seems to have changed post 2016. First, a higher proportion of the seven states that announced waivers fell in the higher debt category (three out of seven). Second, the three states with high debt have introduced large waivers ranging from 8.5% to 12% of the state budget. This evidence further reinforces the fact that we are now seeing a lower degree of fiscal consciousness among policymakers.

Electoral Impact

Earlier we showed evidence that elections are an important influence for loan waivers. Now we will use the comprehensive data set to get a sense of how electorally consequential these loan waivers have been for the political actors. Have incumbent governments that implemented loan waivers come back to power? The evidence connecting the policy of loan waivers with re-election prospects is expectedly weak since there are many other factors such as the anti-incumbency element pervasive in Indian elections that are likely to have a bearing on electoral results. Also the data set is not complete since a few incumbent governments that introduced waivers after 2014 are yet to face elections. But to the extent that the data may reveal a pattern we thought it may be interesting to analyse it. Table 5 tabulates the data as currently available.

First, we find some indication of a “recency” effect applying to voter reactions to loan waiver policies. Loan waiver policies that were implemented early in the incumbent’s tenure (such as Tamil Nadu 2006, Kerala 2006 and UP 2012) show poorer electoral prospects than policies that are implemented closer to the time of elections. In the former case all three states lost the elections and showed reduced vote share, while in the latter case two out of four states that implemented waiver just before the election showed slightly enhanced vote share.

Second, it seems plausible that large loan waivers implemented just before elections receive more electoral support than small loan waivers. For instance, Karnataka in 2017 implemented a moderately large loan waiver programme (4.4%) and received some benefit for it in the 2018 elections. On the other hand, >UP in 2012 and Karnataka in 2012 implemented much smaller waiver programmes (0.8% and 2.9% of GSDP) and seem to have paid dearly in the ensuing election.

Policy Design and Implementation

So far we have brought light to the vagaries in the context and size of loan waivers that have been implemented across states and also across time. Alongside this there is also an interesting variation in the design of waiver policies and the manner in which waivers have been implemented across states. In this section, we would bring light to some of these differences, which we believe also deserve attention.

Broadly there appear to be four key elements to the policy design of loan waivers: (i) coverage of farmers; (ii) waiver limit; (iii) coverage of banks; and (iv) repayment incentive. We argue that policymakers carve out distinctive waiver programmes by making strategic choices with regard to each of these elements. The end result of these choices is substantive, as it has implications for the size of the waiver.

We see some interesting patterns. First, we find that with regard to coverage of farmers, a majority (12 of 17) of waiver programmes did not set any formal eligibility criterion. This means that all types (marginal, small and large) of farmers were eligible to avail waivers. There were only five occasions where some sort of eligibility criterion was formalised: on four occasions eligibility was limited to small and marginal farmers while on one occasion only marginal farmers were included.

Second, there is variation in the maximum amount of waiver that an individual farmer is eligible for. As shown in the table, in almost all cases some limit was exercised barring Tamil Nadu in 2006, where the waiver policy mentioned no formal limit to the waiver that could be availed by a farmer.

Third, the types of financial institutions covered under the programme also matter. In seven cases the programme was limited to only cooperative institutional loans. Eight other cases had wider coverage that included both cooperative institutions and commercial banks. A recent programme by Maharashtra in 2017 further widens the ambit by also incorporating loans from licensed moneylenders.

Last, some policymakers have incorporated some variant of a repayment incentive that attempts to partially mitigate the moral hazard issues associated with loan moratoriums. The evidence, however, shows that they were in minority as only seven out of the 17 waivers analysed had instituted a repayment incentive policy.

Further, it is instructive to see how these design choices have an impact on the size of the waiver. We illustrate this by analysing two different policy designs implemented by the same state government at different points in time. Consider the two waivers introduced by Tamil Nadu in 2006 and 2016. Both broadly shared the same design barring a difference in the farmer eligibility criterion. The 2006 waiver policy had no formal eligibility criterion while the 2016 policy was limited to only small and marginal farmers. However, this design difference seems to have substantively influenced the size of the programme. While the 2006 waiver accounted for 14% of the Tamil Nadu budget, the waiver in 2016 was much smaller, accounting for only 3% of the state budget thereby marking a 78% cut in the waiver allocation.

A similar phenomenon can be seen in the two waiver policies introduced by Karnataka in 2017 and 2018, which were separated in time only by a year. The 2017 waiver was limited to cooperative institutions and the waiver was capped at ₹ 50,000 per farmer. As opposed to this the 2018 policy offered a wider coverage of all banks and cooperative institutions as well as a higher individual waiver limit of ₹ 2 lakh. The cumulative effect of these two policy differences dramatically enhanced the allocation for the 2018 waiver. The Karnataka waiver in 2017 claimed only 4% of state budget while the 2018 waiver accounted for 16% of the budgetary resources demonstrating a fourfold hike. Both these cases suggest that the choice of policy design can have substantive implications for the size and scope of loan waivers.

With regard to implementation of the waiver programme the data is sparse as implementation plans are rarely reported by the media and detailed policy documents are not easily accessible. However, there are two innovations that have received wide attention. The first is the initiative taken by the Maharashtra and >UP governments in 2017 to link the disbursal of waiver benefits with the Aadhaar accounts of the beneficiaries. While the jury is still out on whether the transition to Aadhaar has been smooth but the initiative does appear to be one way to curb ghost beneficiaries and reduce duplicity in the allocation of benefits.

Another innovation is the model followed by Kerala since 2006 where a Farmer’s Debt Relief Commission has been in place for over a decade. As a permanent body, the mandate of the commission is to consider individual applications from farmers requesting for debt waiver or restructuring. Members of the commission, comprising agricultural experts, farmer representatives and former judges, travel across the state to receive applications and conduct hearings with applicants. One of the advantages of such a commission is that it helps dissociate the state’s debt support from the vagaries of the electoral process. Ironically, this may be the very reason why politicians in other states have not been forthcoming in considering the model.


The motivation for this paper stems from an accumulating pile of evidence from the economic stream that suggests that farm loan waivers have not been particularly beneficial even to the intended beneficiaries of the scheme. This leads to an intriguing puzzle as to why policymakers continue to announce loan waivers, and why the programme has expanded over the last decade? We argue that in order to find an answer to this question we need to conduct a political analysis of loan waiver policies but so far there has been no research in this regard. Through this paper we attempt to make a beginning towards unravelling the political roots of the policy.

We present descriptive evidence by analysing a comprehensive primary data set that collates all loan waiver announcements since the first waiver was announced three decades ago. The evidence is revealing. First, we observe that loan waiver policies are driven more by electoral exigencies rather than a deeply held ideological conviction. This is important to note because it suggests that it is difficult to connect the policy of loan waivers with any particular development philosophy, either to the left end or the right end of economic ideological spectrum.

Second, while the policy rationale given by politicians is to help farmers meet the adverse conditions emerging from drought, the data that we collated suggests that the application of the policy does not reflect a serious consideration of drought. Waivers have been announced in states that faced acute drought as well as states where drought was not widespread.

Third and contrary to the general impression, the data suggests that politicians have been fairly conscious of the state’s fiscal condition when they make decisions regarding loan waivers. Until recently the bulk of loan waiver announcements coincided with the period when states were making active efforts at restraining their public debt. Unfortunately, this trend seems to have been broken since 2016 where high debt states have also begun announcing large loan waiver packages.

The overall findings do give empirical ground for a critique of loan waiver policies. This conclusion should, however, not be incorrectly conflated to suggest, in any way, that the current crisis faced by the agricultural sector is not real and should not be addressed with vigour. As earlier studies by experts on agriculture have highlighted the roots of the agricultural crisis are structural (Nadkarni 2018) and so the solutions need to be far-sighted. The evidence so far suggests that waivers have not even worked as an effective palliative, which means there should be more creativity even while designing immediate relief measures. While the search is on for an alternate policy, the best that can perhaps be done right now is to work on the design and implementation of waivers so as to better target the benefits towards vulnerable farmers.


1 As per the CAG (2013) audit report, one of the objectives of the central loan waiver scheme announced in 2008 was to enable indebted farmers to avail fresh agricultural credit. However, the report stated that no effort was made by the government to monitor the extent to which this objective was fulfilled. Mukherjee et al (2014) is the only work so far that gives us some measure of the extent of credit rationing that accompanied the 2008 loan waiver.

2 For instance, in 1996 the Tamil Nadu government announced an interest waiver of 3%, which costed the exchequer a relatively small amount of ₹ 20 crore.

3 We studied the media extracts from the speeches made by the politicians.

4 IMD publishes district-wise rainfall data for the period of 1901–2010. For data after 2010 we referred on annual “Rainfall Statistics of India” also published by IMD.

5 We use IMD defined criteria to determine if a district has “deficient” rainfall. As per the metric a district is designated to have received deficient rainfall if actual rainfall in a year is 20% less than the long-term average.

6 We did not compare the allocation for agriculture in the same year as the waiver was announced since we expected that states would reduce their agricultural allocation in the year of the waiver.


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Updated On : 10th Jun, 2019


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