The term ‘auctions’ is used often in business and finance, as this is a process used for price discovery in the primary market. When there are myriads of players in the stock markets, the ‘bids and asks’ are based on the previous traded price and this resembles an auction when we place our orders. Though commonly associated more with the sale of art, auctions in the bond market where the Reserve Bank of India (RBI) conducts them when selling government paper are well established. This is the most efficient way of discovering the price.
But in auctions there is always a problem of paying a higher price, especially if the object being sold is not as common as, say, a bond. For a 10-year government bond, the prevailing yield is known at, say, 6%, and hence the bids will be around this number. For example, when bidding on a web portal for a product one has a fair idea as to what would be the true value. This would hold even for second-hand cars where the cost price would be known, and one could take an informed guess on the rundown value. Even when there are M&As, there are defined ways of reckoning the right price for the acquisition, and the chartered accountant or management consultant can give the right number.
But when it comes to radio spectrum or airport landing slots, one may end up bidding at a higher price and then realising that it is too much (the winner’s curse), or bidding at a lower price and not being considered. Solving such conundrums is the focus of the work done by Paul Milgrom and Robert Wilson, which has won them the Nobel Prize in Economics for 2020. In fact, in 1994, the US used one of their formats to sell bands of radio spectrum, which was largely successful and set a norm for future sales. This helped in ensuring that the taxpayers gained from the sale of frequencies owned by the government and was of value to the operators who paid for these rights.
By some coincidence, all winners of various prizes this year are from the US, and the two economists have a background from Stanford. Their work is something that we all would identify with as the auction has been the best way for price discovery. Almost all prices are discovered through an auction-like process, and this holds even when there are no benchmarks. One may recollect that the controversies around the irregularities in sale of coal blocks or spectrum in India had moved the needle to having more transparent auctions.
Milgrom’s work has focused on creating bidding strategies that determine how the format of an auction can give the seller higher expected revenue as bidders try and figure out the ‘private value’ others place on the item on sale. So, it is a case of guessing what others feel is the intrinsic value of the product under the hammer. Wilson’s writings have been on the theory of a ‘common value’, which is the best estimate of what an item is worth that bidders then try to set their offers below to avoid overpaying. The games that are played must finally make the private and common value get closer to one another, which benefits the bidder and the seller.
The major challenge is to eschew the winner’s curse, and here the laureates argue that the best way out is to place bids below their estimate of the common value. In all these exercises, we need to distinguish between a private value and a common value. Art, normally, has a private value, which we can be right about as the importance placed while viewing the painting on the wall every day is personal and cannot be contested. When it has a snob effect, the private value can be higher than the common value and does not matter as the buyer has the ability and willingness to pay a higher price as it improves the self-image in the eyes of others (the Veblen effect). But when one wants to sell the same, what matters more is the common value or what others think are the best possible prices. Private value ceases to matter. This is where the matching of private and common value matters. The rational way out is hence to place a bid below this perceived common value.
According to Milgrom and Wilson, there are different motivations behind winning at an auction. Maximising revenue could be the main goal, but often it could also be a way of managing liquidity or emissions that have become important in today’s world. In the early days when auctions came in the fishing space, there was always a doubt on what the ‘catch’ would be, and hence there was a risk in bidding for these rights. The same holds when bidding for minerals, where the outcome may not be known—while the bidder has some sense of what could be the quantity that could be fished or mined, the certainty is never there.
This is where their work adds sheen, because the goods being dealt with are complex and there is no certainty on the outcome. When one bids for spectrum, it is unclear as to how would the demand work out or, for that matter, even regulation as seen in India. This can make it hard to place bids, unlike in the financial markets where there is a vanilla product that must be priced.
Mind theory has become more important of late when analysing markets and price determination. Getting successful in auctions is very much a part of game theory, where each player must analyse what the other really thinks of the product and, accordingly, place a bid. While this does not matter when it is a commonly traded good like a financial instrument, it becomes progressively complex as one gauges the reactions or behaviour of other bidders. Progressively, governments would be selling more of their assets—natural resources, which can range from spectrum and minerals, to spaces (docks and airports), and getting it right can impact the financials of bidding companies. From the point of view of the government, too, this works well, as it makes systems transparent and free of controversy. The idea, however, is to get the best possible price for both the sides and create a Pareto optimal solution.
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