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Taxing agricultural income has been an emotive subject in the Indian context. However, taxing agricultural income at minimal rates of about 5% can help rather than hurt our poor farmers.

Given the importance of access to finance, the policy in India has been to compel banks to lend to the underserved. The fact that access to formal finance remains a challenge even after decades of implementation of such policies demonstrates that such coercive policies have borne little fruit. The burgeoning problem of farmer distress in India despite the existence of the priority sector lending programme for more than three decades is a case in point.

Given that a large portion of Indian farmers are illiterate or semi-literate and they do not maintain systematic books of accounts regarding their production and income, assessing their true income or income-earning potential becomes an onerous task for the bank loan officers. Research has shown that bank loan officers in India rely mostly on informal networks created by social affiliations in order to elicit information about the borrowers. Thus, only those borrowers who are “connected" to the loan officers obtain optimal credit. The fact that loan officers are rotated every three years makes matters worse from a borrower’s point of view. Our own research in this area has shown that a new loan officer entering a branch after job rotation restricts credit to borrowers who borrowed from the previous loan officer.

A more sustainable approach to financial inclusion involves enabling people to borrow from the formal system. We argue that taxing agricultural income can improve access to finance to a large section of farmers because verified income tax returns can provide a credible signal of the earnings potential of a farmer. Such verifiable information can help to separate conscientious and productive farmers from the unscrupulous or unproductive farmers. Such separation can be very useful in not only enabling access to finance but also entered using the cost of credit borne by farmers.

Consider a simple illustration to understand this point. Suppose a loan officer has 100 to lend. Suppose there is a good farmer whose expected revenue for a 100 investment is 125. Also consider that in the same village, there is a bad farmer whose expected revenue for the same investment is 75. Clearly, the bad farmer is better off doing something else other than farming, such as working as a security guard or a factory worker. Such differences in farmer productivity could be because of differences in talent, motivation, quality of land, cultivation methods used, training received, etc. The bad farmer could also be a strategic defaulter intending to exploit the lax enforcement standards prevalent in the country. In an ideal world, the loan officer would possess the ability to distinguish the good farmer from the bad one. In this ideal scenario, the loan officer can lend 100 to the good farmer and none to the bad farmer. Given the higher productivity of the farmer, in this case, well-directed agricultural loans would not only enhance agricultural productivity, but also hasten the movement of unproductive agricultural workers to the manufacturing sector.

But, in the context of Indian agriculture, it is extremely difficult for the loan officers to differentiate between the good and the bad farmers. The loan officer ends up lending 50 to both the borrowers. Here we have a situation where a genuine farmer with profit opportunities is being starved of funds, and at the same time a bad farmer or a strategic defaulter is obtaining credit. The end result is easy to guess: low agricultural productivity, high default rates on agricultural loans leading to farmer distress, and lack of mobility from agriculture to other sectors.

Now, suppose both farmers file income tax returns every year. In this case, the good farmer can present his income tax return to the loan officer in order to demonstrate his earning potential. In the case of small farmers, income tax returns can provide a reasonably credible measure of earnings potential because they would neither have the high income nor the incentives to hide such high levels of income. This signal of earnings potential is credible because declaring higher income results in payment of higher taxes and hence is costly to the farmer. Now, the loan officer has a credible basis to distinguish between the borrowers. More importantly, the borrower need not depend on a particular loan officer or a particular bank. This improves the bargaining power of the borrowers by enabling them to tap multiple sources for financing. If the income tax rate is set at about 5%, even though the farmer pays 5 for every 100 of earnings, the benefits he can reap from being able to borrow 100 at cheap rates can be substantially more than 5.

There could be a concern that the imposition of tax could lead to credit flowing only to big farmers as they have higher income to show. We believe otherwise. Research has shown that loan officers can easily infer the “true income" of large borrowers even when tax records do not present a true picture. Hence, large farmers are less credit constrained. However, in case of small farmers, the loan officer cannot assess true income without carefully analysing credible evidence. Income tax return can be one such evidence.

Thus, rather than listening to the powerful lobby of rich farmers, the government should seize the opportunity to benefit the small farmers by taxing agricultural income at minimal rates of about 5%.

Krishnamurthy Subramanian is associate professor of finance and Prasanna Tantri is senior associate director at the Indian School of Business, Hyderabad.

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