Widely Shared Crop Forecasts Can Actually Harm Farmers

Nov 15, 2019

By Michael Totty

One key to fighting rural poverty in developing countries is simply better information: the best time to plant, the best time to sell and the crops that will get the best prices at market. And thanks to the widespread use of mobile phones, governments, non-governmental organizations and private companies can now put all sorts of up-to-date information into the hands of producers.

Still, such market information services have had a mixed record of success. Many have ceased operating, and those that remain include market forecasts as merely part of an entire suite of offerings that include digital payments and systems that directly match farmers and buyers.

One problem with providing market information, a  working paper suggests, may lie in trying to make it widely available to everyone. The research — by National University of Singapore’s Junjie Zhou, Hong Kong University of Science and Technology’s Xiaoshuai Fan and Ying-Ju Chen, and UCLA Anderson’s Christopher S. Tang — concludes that all producers would get higher prices for their crops if planners restricted market forecasts to only a subset of farmers, for instance, those who are willing to pay for the information.

The reason is simple supply and demand. If all farmers get the same price forecasts, they’re likelier to grow the same crop that promises the highest future payout. But that would result in a glut, causing prices to fall. To lessen this “herd effect,” it’s better for planners to limit who gets the information so that those with the information will grow crop A, while those without it will grow crop B. Market prices would then be higher for both crops than if everyone grew the same thing.

“Sharing market information to some farmers is good, but sharing info with too many farmers is bad for them,” Tang said in an interview.

Using a game theory model, the authors examine the benefits of providing “public” forecasts of future prices to farmers who also possess different degrees of “private” information about the market. (For instance, a farmer might know how much fertilizer will produce the highest yield, or how much he intends to plant, but not the intention of his neighbors.)

The researchers first analyzed what might happen in a market operating under the following conditions: Forecasts are provided free of charge; planners are interested in promoting the welfare of all farmers; crop yields are predictable; and farmers can determine how much to send to market but can’t set the price.

In this case, the model suggests, the greatest benefits occurred when market forecasts were made available to exactly one farmer. “Clearly, disseminating to only one farmer would not be practical or politically correct,” the authors write. Instead, the conclusion should be treated “metaphorically” and their research indicates that “a wide dissemination of public signals will not improve farmers’ total welfare.”

The paper then considers other market situations with different starting conditions. In these cases, the best outcomes occurred when the information was limited in some way.

For instance, some market information services are provided for free to all farmers and the cost is covered by governments or NGOs. Others charge a subscription fee, sometimes nominal, to deliver the information. With a fee, some farmers will opt out of the program, which limits the herd effect on future prices. How much to charge is a balancing act, though. Prices have to be high enough to limit access and to recover costs for the provider, but enough farmers have to participate to hold down fees and make the service affordable.

A market information service also can help farmers get higher crop prices if the provider of the service only cares about certain producers, such as an agriculture cooperative that assists only its members. For instance, Walmart’s direct farm program provides market information and other assistance to small farmers around the world that supply its produce.

Source : ucla.edu
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