Empirical studies show its impact is limited. Farm GDP is driven more by output prices, irrigated area & public spending.

Recently, there has been an intense discussion on the strategies needed for addressing farmer distress in India. Among others, assured and greater access to institutional credit has been proposed as a way forward.

In line with this view, the Congress party in its manifesto for the 2019 Lok Sabha elections promised to supply adequate institutional credit to the farm sector and waive the outstanding farm loans if voted to power. The manifesto of Bharatiya Janata Party (BJP), on the other hand, promised to “provide short-term new agriculture loans up to ₹1 lakh at a 0 percent interest rate for 1-5 years on the condition of prompt repayment of the principal amount.”

Thus, the two major political parties believe that the removal of credit constraints is necessary to improve farmer welfare and support agricultural growth. Agricultural credit policies of successive governments have resulted in burgeoning institutional lending to agriculture over the years. The direct institutional credit for agricultural and allied activities increased from ₹1,053 billion in 2004-05 to ₹7,301 billion in 2013-14 to ₹10,911 billion in 2017-18.

However, very little attention has been given to a key policy question: whether institutional credit to the agriculture sector of such size contributes commensurately to agricultural growth.

Credit intensity

A crude way to assess the productivity of institutional credit to the agriculture sector is to measure credit intensity of agriculture, which is defined as the ratio of agricultural credit to agricultural gross domestic product (GDP). Chart 1 shows that the total direct institutional credit for agriculture and allied activities increased almost consistently from 18.55 percent of agricultural gross value added (GVA) at current prices (new 2011-12 series) in 2004-05 to 26.57 percent in 2008-09 to 37.90 percent in 2013-14 to 40.86 percent in 2017-18.

On average, agricultural credit to GVA ratio increased from 23.58 percent in UPA-I regime to 32.20 percent in UPA-II to 41.26 percent in the first four years of NDA-II regime.

The striking increase witnessed in the ratio of agricultural credit to agricultural GVA from UPA-I to UPA-II to NDA-II reveals that the ‘credit intensity’ of agriculture has increased tremendously over the years. This implies that, over the years, India has required more credit to achieve the same unit of agricultural GVA.

In other words, agricultural credit has become less efficient in delivering agricultural growth. An analysis of yearly movements in the growth of agricultural credit and agricultural GVA in nominal terms from 2005-06 to 2017-18 supports this result (Chart 2). Only in five out of twelve years, a positive relationship between agricultural credit growth and agricultural GVA growth was established.

Empirical evidence

In this context, it is important to note that serious academic studies examining the relationship between the flow of institutional credit to the agriculture sector and agricultural growth in the Indian context found that the correlation between the two is weak at best. For instance, a Reserve Bank of India study covering the period from 1988-89 to 2010-11 found that there is no statistically significant causal relationship between agricultural growth and credit cycles in India.

Another seminal study using State-level data for the period 1995-2012 reveals that though agricultural credit plays a role in influencing the purchase of agricultural inputs by farmers, its impact on agricultural GDP is weak. Instead, the performance of agricultural GDP is determined by sectoral composition, output prices, the area under irrigation and public expenditure.

The above results suggest that the ability of credit to induce agricultural GDP growth is limited. Hence, adequate attention should be given to building other capabilities required to promote agricultural growth. They include productivity increases, expansion of infrastructure, higher public expenditure on agriculture and allied services, effective extension services, sound institutions, and export competitiveness.

The impact of credit on agricultural growth would be more effective in the presence of these non-credit growth ingredients. The weak contribution of credit to agricultural growth also emphasizes the need for proper targeting of agricultural credit to achieve the desired impact on agricultural growth.

Monitoring is key

Available evidence points out that agricultural credit might not entirely benefit the actual Indian farmer due to several reasons. A substantial part of subsidized agricultural loans has been diverted for non-agricultural purposes such as investing the borrowed money in fixed deposits; deploying tractors bought on farm loan for construction activity; and using the bank credit to repay the loans from moneylenders and to meet consumption expenditure.

Also, categorization of gold loans as farm credit by banks adds to the problem. It is estimated that around 30 percent of the farm credit is extended against gold jewellery and about 50 percent of such loans are used for consumption purposes.

What is needed, therefore, is strict monitoring of agricultural credit utilization at the ground level. The RBI and commercial banks are aware of the ground reality. A few years ago, the RBI investigated the diversion of farm loans for non-agricultural uses. Yet, concrete actions to ensure proper use of agricultural credit are not forthcoming.

A notification issued by the RBI in this regard to public sector banks had advised the latter to ensure that all farm loans meet certain criteria. They mainly include limiting the disbursement of farm loans only to an agriculturist, ensuring that the loan is used for the stated purpose, and verifying that disbursal and recovery of farm loans follow seasonality pattern. To a larger extent, these tasks could be carried out using technology such as analytic software, which is made possible today as all major banks in India follow the Core Banking Solution system.

The writer is Associate Professor of Economics at IIM Kozhikode

Courtesy: The Hindu Business Line