Let’s not overstate the case of MSP: Financial Express 17th July 2018

MSP is an indicative price that works when the government steps in to buy the product. It does not necessarily lead to farmers being better off all the time, as the final price is still driven by the market.

A fascinating thing about all economic issues is that there are two sides to them, which is why the concept of a one-handed economist is still a mystery. Look at MSP, or minimum support prices. This is widely used as a weapon for increasing the income of farmers and hence is something to watch for. The announcement of these prices for the kharif and rabi seasons, however, raises enough controversy. At present, the clarion call is to reach out to farmers, and after the Union Budget spoke of providing a 50% margin over costs, the focus seems to be on ensuring that farmers get a good deal. This sounds good, especially in a pre-election year.

On the other side is the inflation story. MSP, when used to increase the income of farmers, would also mean that someone has to pay for it—either the government or the buyer in the market, which is ultimately the consumer. Hence, the argument goes that when prices are divorced from economic fundamentals but driven by a formula, inflation should result when MSP is increased. Put in a rudimentary manner; in case all crops have MSPs that are 10% higher and applied across the board, then prices have to rise by 10% to ensure that the farmer benefits. If the government procures the crop, then the income is transferred through the taxpayer’s taxes in the Budget. If there is no procurement and prices still rise to ensure that farmers get higher incomes, then the individual has to pay for it. This is so because it is a zero-sum game.

However, in reality, things are not so simple, and mere announcements do not guarantee that prices increase by the amount and the farmer benefits. Or, for that matter, higher MSPs do not mean that inflation will necessarily rise. There are two factors which are pertinent. The first is the strength of MSP in terms of efficacy even when there is direct procurement. Even procurement is restricted to only some states as the government machinery is not present everywhere. The second is when there is no procurement; here, the government cannot force companies to pay more for soybean especially when the supply is in excess. Therefore, MSP ceases to matter in these cases. The only psychological effect could be if benchmarks move up when MSP is increased. But this is not sustainable and prices tend to move back to fundamentals.

One way to see how this has worked is to do a rudimentary statistical exercise that links the changes in MSP to the changes in WPI for the same product. This will give an idea of whether or not MSPs have had an impact on the final prices, which can then be interpreted either as a benefit for the farmer in case prices have gone up or conversely as an additional cost for the consumer in terms of higher price inflation. In fact, curiously, when all MSPs are increased and the final prices move up, farmers may end up being in a neutral position as a farmer who grows rice would be consuming pulses and edible oils where prices would also have gone up. This is the strange paradox of MSP increases where real income may not increase in net terms for the targeted beneficiary!

A simple regression has been carried out which maps percentage changes in the two variables for all the kharif crops for the last 30 years. The first is the coefficient of determination, which shows what proportion of the changes in WPI that can be explained by the change in MSP. The second is the coefficient of the relevant MSP, which will indicate how much does 1% change in MSP lead to change in WPI. The other factors that influence WPI have been excluded, which is theoretically reflected in the intercept term. Alongside, it is also mentioned whether or not the coefficient is significant at the 5% confidence level. The WPI changes have been taken as per the respective base years of 2005-05 till 2011-12 and 2011-12 subsequently (see table).

The table highlights some very interesting observations. First, for products such as rice and cotton where there is procurement by the Food Corporation of India (FCI) and state agencies for the former and the Cotton Corporation of India (CCI) for the latter, MSPs are effective in influencing the final price. The impact of MSPs is above 0.5% for both, which means that 10% change in MSP increases prices by above 5%.

Second, for other products especially pulses, MSPs do not matter and the relation is a negative one. This means that market forces linked to supply conditions influence prices and not MSP, mainly because backend procurement does not exist.
Third, in case of soybean, the coefficient of MSP is significant, which means that the price policy tends to be effective and the relation is good at close to 1. The explanation here is that since the procurement is by oil mills there would be a tendency for MSP to become a benchmark unlike other products where buyers are well-dispersed wholesalers.

This raises the question on whether or not MSP really works when there is no procurement. In case of rice, the coefficient is around 0.6 and hence the increase of, say, 10% would not give a commensurate return to the farmer as the non-procurement quantity, which would be of higher grades, would not be linked with this factor and is between 60-65% of total production. Therefore, raising MSPs will not necessarily lead to higher incomes for farmers. As a corollary, the fear of higher inflation would also be misplaced, as if prices are driven by market factors, in the absence of intervention, prices would decline in case output increases sharply.

It needs to be appreciated that MSP is an indicative price that works when the government steps in to buy the product. It does not necessarily lead to farmers being better off all the time as the final price is still driven by the market. To overplay the role of MSP in delivering benefits to farmers may be an exaggeration, just as overstating the inflationary impact.