Auctions
Paper Session
Friday, Jan. 6, 2017 7:30 PM – 9:30 PM
Hyatt Regency Chicago, Grand Suite 5
- Chair: Rafael Tenorio, DePaul University
Selling to Advised Buyers
Abstract
In many cases, agents that make purchase decisions are uninformed and rely on the advice of biased experts. For example, when contemplating an acquisition, the board of the bidder relies on the advice of the managerial team when deciding what offer to make for the target. We study how to sell assets to such “advised buyers” if the goal is (i) to maximize revenues; (ii) to maximize allocative efficiency. In static mechanisms, such as first- and second-price auctions, advisors communicate a coarsening of information and a version of the revenue equivalence theorem holds. In contrast, dynamic mechanisms, such as multiple-round auctions, result in more informative communication between buyers and their advisors, which leads to more efficient allocations. Whether this leads to higher revenues depends on the direction of the bias. When advisors are biased for overbidding, an ascending-price auction dominates static formats in both efficiency and expected revenues. When advisors are biased for underbidding, a descending-price auction dominates static mechanisms efficiency but often results in lower revenues.Electricity Markets: Designing Auctions Where Suppliers Have Uncertain Costs
Abstract
We analyze how market design influences the bidding behavior in multi-unit procurement auctions where suppliers have uncertain costs and are uncertain about the availability of production units, as in wholesale electricity markets. We find that the competitiveness of market outcomes improves with increased market transparency. We identify circumstances where the auctioneer prefers uniform to discriminatory pricing, and vice versa. We also identify circumstances where it should be market efficiency enhancing to restrict the number of steps in the bid-schedules.How Auctions Amplify House-Price Fluctuations
Abstract
I develop a tractable dynamic model of the housing market where the prices are determined in auctions rather than by Nash bargaining as in the standard housing search model. Markets that use auctions mimic actual housing markets, in that the model can portray a ``hot" market where numerous buyers flock to each new house on the market and a ``cold" market, where numerous houses are on the market and a buyer has a wide choice without competing directly with other buyers. In the auction model prices are higher, the market is bigger and waiting times are longer in the steady state compared to the standard model. In particular, the house prices are thirty percent higher in the auction model than in the bargaining model. There are four times more buyers and sellers and it takes four times longer to buy or sell a house in steady state. The dynamic response of prices to shocks is larger in the auction model than in the bargaining model. Auctions amplify the response of house prices to shocks because prices respond more to changes in the present value of the housing services, and the option value to sell is more sensitive to the state of the housing market. The equilibrium allocations of the auction and Nash bargaining model are not socially efficient, so the government interventions are desirable.Underpricing Regimes in Housing Markets
Abstract
I study a staggered policy change intended to reduce bidding wars for homes by increasing their list price and eliminating underpricing. Using a novel and large micro data set and a difference-in-difference methodology, I find that increasing the list price reduces the buyer arrival rates in all stages of the search process -- online, at the open houses, and during bidding -- and increases the probability of a failed sale. I find a strong null effect on the sales price which can be bounded to a tight interval around zero. I find no effect on the sales effort exerted by real estate agents, nor on time-on-market. To explain these findings, I develop a search model where a non-committing list price is set optimally by real estate agents and where the list price directs buyers' search. The model is consistent with my empirical findings, and can explain why the policy did not last in the long run.JEL Classifications
- D4 - Market Structure, Pricing, and Design