Accepting Late Bids?

 

Spirit Airlines’ bankruptcy has produced an unusual auction: Google agreed to pay $10 million for a trove of Spirit’s internal corporate data, including roughly 100 million emails and 500 million Microsoft Teams messages, beating a $7.5 million bid from AI firm Mercor. But after the auction closed, AI startup Micro1 offered $12.5 million, a sizable bump from Google’s bid. The bankruptcy court must now decide whether to consider the late offer. At first glance, the answer seems obvious. Spirit’s creditors want as much money as possible, so why not accept the higher bid?

Because changing the rules after an auction can affect bidding before the auction. A well-designed auction gives bidders confidence that deadlines and procedures are credible. If firms expect a losing bidder to get another chance after seeing the winning price, they have an incentive to hold back during the formal auction and wait to top the winner afterward. That can reduce competition and lower expected revenue in future auctions. Bidders on potential auctions for additional Spirit assets may adjust their bids downward. Conversely, rigidly rejecting a substantially higher late offer leaves money on the table today. There is an auction design tension because maximizing the highest observed bid is not necessarily the same as maximizing the seller’s expected revenue. Sometimes committing not to accept a better offer later can induce bidders to make better offers now.

Specrtum Auctions Address Economies of Scope

The Federal Communications Commission (FCC) auction can demonstrate economies of scope. The FCC periodically auctions off additional spectrum licenses for advanced services. It recently raised $3.5 billion from recent AWS-3 (Advanced Wireless Services) auctions and expects to raise $30-$6 billion from upcoming Upper C-Band auctions. In telecom, these frequencies are not independent assets; their value is multiplicative. This additional spectrum will allow for greater capacity to handle the exponentially growing demand for wireless data transmission.

Spectrum auctions are usually run as Simultaneous Multiple-Round Auctions (SMRAs). US coverage is divided into many distinct geographic areas that are auctioned simultaneously across many rounds. An aggregation problem arises when a bidder risks winning fragmented licenses that are less valuable without their complementary counterparts. Since transmission has origin and a destination, it is more valuable to win a license in, say, Chicago if the operator can also secure one for Dallas. SMRAs allow bidders to cobble together desired regional capacity by aggregating multiple licenses.

The cell towers, base stations, and cables that link them are huge fixed costs. The ability to defray these costs over more volume reduces average costs. Economies of scale in these fixed costs generate economies of scope across these fixed costs in different regions.

What Set-Asides Cost: A Lesson from Timber Auctions.

California's Public Utilities Commission is pressuring utilities to steer about 1.5% of procurement toward state-certified "LGBT-owned" firms.  Setting aside the certification debate, what will this cost the state? 

In every auction, the winner has to outbid the second-best bidder, so the second-best bidder sets the price. Weaken the field and you weaken that price-setter. But which way the price moves depends on whether the government is buying or selling.

When the government buys, it runs a procurement auction: bidders compete to sell to the government, and the lowest-cost bidder wins, while second-lowest-cost bidder sets the price. Restrict who can bid and the price the government pays goes up.

When the government sells, bidders compete to buy, and the highest-value bidder wins, while the second-highest-value bidder sets the price. Restrict who can bid and the price the government receives goes down.

A set-aside moves price through two separate channels, and they push the same direction. 

• First, it shrinks the number of bidders, so the second-lowest cost is higher (or the second-highest value is lower). 
• Second, the set-aside bidders themselves may be higher-cost or lower-value than the bidders they replace. 

Both channels move price against the government.  An article by a pair of middling economists shows by how much.  Prices in Forest Service small-business set-aside auctions—where only small businesses may bid—run about 15% lower than in open auctions. 

The lesson applies to California. Fewer, weaker bidders mean a worse deal for the government. 

Winners' curse in real estate auctions

Fortune:

The real-estate 'winner's curse': Study of nearly 14 million home sales over 20 years shows you don't want to win that bidding war

In today’s hot housing market, winning a bidding war can feel like a triumph. But my research shows it often comes with a catch: Homebuyers who win bidding wars tend to experience a “winner’s curse,” systematically overpaying for their new homes.

Note: the winners' curse is a form of adverse seleccton (ch19) HT: Justin

Would eliminating DEI improve government procurement?

Yes, by 15%.  From a paper by some middling economists,

Mergers, Cartels, Set-Asides, and Bidding Preferences in Asymmetric Oral Auctions, The Review of Economics and Statistics, 2000, vol. 82, issue 2, 283-290.  

The SBA [Small Business Administration] set-aside program limits auction participation to "small" firms... The set-aside program has numerous analogies in other areas of government contracting in which, for example, bidding is restricted to minority-owned firms (Froeb and McAfee (1988)).

The costs of the SBA program can be simulated by assuming that small, high-cost firms evolve into large, more efficient firms. The expected price change under this hypothetical scenario is computed over all 51 [Forest Service] auctions... . On average, [timber] price [revenue to the govt] would increase by 14.8%. 

Using procurement for political ends gives you worse prices.

Over 20 years ago, some middling economists (cite) estimated that the Small Business Set-Aside program reduced Forest Service Timber prices by 15%.  By limiting the potential pool of available bidders to only smaller lumber mills, you get less competition and worse prices.

Now San Francisco is re-learning that lesson.  In 2016, it refused to do business with companies headquartered in states that don't share San Francisco's values. As a result, project costs increased 20 percent. 

Two forces are at work:  

• Short-run reduction in competition:  just as mergers which eliminate competition raise price, so too does limiting the number of bidders.  

NOTE:  a reduction in competition in a selling auction (high bid wins, e.g., timber), price goes down; in a procurement auction (low bid wins, e.g., city services) price goes up.  

• Long-run decline in bidder quality:  winning bidders must outbid the losers, so if losing bidders from states that share San Francisco's values--like unionization--have higher costs, they are easier to outbid, so price goes up.

REASON, "Great Moments in Unintended Consequences"

Prosecutorial Discretion: Attorney General Edition

In the late 1980's, I went with a friend to help her work the Ambassador's Ball at the French Embassy, a pay party and charity auction to support MS research.  I bought my first tuxedo and showed up early to sign people in and help set up.  After an hour or so, our job was done and we went inside to join the party.  

We grabbed a drink at the open bar, and into a big room containing the items being auctioned off: cases of rare wine, catered dinners, and vacation homes in exotic locales.  My favorite, or at least the one I might have bid on but for the money, was a week at a Chamonix chalet.  In front of each item was a lined piece of paper where people wrote down their bids.  

As the night wore on, I noticed two couples actively bidding for the chalet.  One couple would watch the other write down a bid, wait a while, and then walk over and bid again.  This went on for three or four bids, until I noticed the two couples talking to one another.  

At the time, I worked as a staff economist at the Antitrust Division of the US Dept. of Justice whose mission is to protect competition by challenging anti-competitive mergers and prosecuting price-fixing conspiracies.  Even talking about prices is viewed a criminal conspiracy subject to a prison term of up to ten years.  

I had worked on and written about a number of bid-rigging conspiracies--dealers at antique auctions, loggers at Forest Service timber auctions, and frozen perch sellers at Navy Procurement auctions--and I was excited to actually witness one. 

The event was chaired by Ursula Meese, whose husband Ed was my big boss, the Attorney General.   I saw him standing by himself in the center of the room, so I walked over, showed him my badge--that's what I liked to call my work ID--and told him what was going on. 

"Do you want me to take 'em down?" I asked.  

He smiled and said "Book 'em Danno."  [reference for those too young for the allusion]

========

NOTES: The Economist has reported on my articles on bid rigging albeit with a small mistake.  

Middle panel of my first-day class slide shows Attorney General Meese and me in the Reagan Justice Dept.  

Should the Federal Govt "spread" its cloud computing contracts around?

WSJ Reports:  

Amazon dominates the cloud-infrastructure industry with a 39% share of the 2021 global market ahead of Microsoft at No. 2 with a 21% share, according to research firm Gartner Inc. ... 

Microsoft has grown frustrated about its lack of progress selling its Azure cloud services to the U.S. federal government with its rival’s Amazon Web Services continuing to win most of those contracts, said some of the people familiar with its efforts.  ...   

Microsoft Corp. is rallying other big name cloud-computing providers such as Alphabet Inc.’s Google and Oracle Corp. to press the U.S. government into spreading its spending on such services more widely, taking aim at Amazon.com Inc.’s dominance in such contracts. 

So what would be the effects of this?  Some middling economists have estimated that similar efforts by the Small Business Administration to "spread its spending around" (by "setting aside" auctions for small firms) raises prices by 15%.   

The reason is simple, losing bidders set the price.  If you limit the pool of available bidders, you make it easier for the winner to outbid the losing bidders, so price goes up in a procurement auction (where bidders compete to sell).

Historical Knockout Auctions

The Journal of Political Economy, one of the more prestigious economics journals, gets submissions of interesting economics related anecdotes for its back cover. The most recent issue contained this:

Collusive Bidding and Intermediary Profits in Congo a Hundred Years Ago

Five traders, who have hurried up in their cars, were waiting for the market to open. The region here has not been conceded; the market is free and the bidding began at once. We were surprised to see it stop almost immediately. But soon we understood that these five gentlemen were making a ring. The first carried off the whole crop for seven francs fifty a kilo, which probably seems a very fair price to the native, who only recently was selling his rubber at three francs; but at Kinshassa, where the traders resell it, it has fetched for some time past between thirty and forty francs, which leaves a very respectable margin. What about our gentlemen? As soon as the business is concluded with the native, they meet together privately in a little room, where another auction begins and they divide the spoil among them. The administrator is powerless against this secret auction, which, with every appearance of being illicit, does not, I am told, come within the power of the law.

[Andre Gide, Travels in the Congo (1927), translated by Dorothy Bussy (Hopewell, NJ: Ecco, 1994), p. 45. See also Daniel Graham and Robert Marshall, “Collusive Bidder Behavior at Single-Object Second-Price and English Auctions,” J.P.E., vol. 95, no. 6 (December 1987), 1217–39]

(Suggested by Laurent Lamy)

Clorox is outbidding Vanderbilt for ad space

Following up on an earlier post showing Facebook, Instagram, Google, and Twitter show 20% fewer STEM ads to women than men:  as  Scientific America explains

Women are pricier to reach because they generally make more household purchasing decisions than men do. ...

...on Instagram it cost $1.74 to get a woman’s eyeballs on the ad but only 95 cents to get a man’s.

In other words, Clorox is outbidding Vanderbilt for ad space likely to be seen by women because Clorox places a higher value on the ad.  However, auctions are efficient, so both men and women end up seeing the highest-value ads.  

 OK, so there is no "disparate treatment" of men and women, but isn't it illegal to adopt practices that have a "disparate impact?" My understanding (I am NOT an attorney) is that Federal law prohibits both "disparate treatment" and "disparate impact" discrimination, even though adhering to one would violate the other. 

 For example, if you give a bidding advantage to STEM educational institutions when they bid for ad space likely to be seen by women, the algorithm is treating women differently than men.  This kind of disparate treatment is what the article recommends.

The same kind of tradeoff shows up in the current debate about equality (equal treatment) and equity (equal outcomes). If we want equity, we have to give up on equality.  

How does Google auction ads?

Note the analogy to second price auctions--the highest rejected bid determines the price.  Because advertisers do not pay what they bid, they are willing to bid their values.

Is competition among colleges becoming fiercer?

The NY Times Magazine outlines the tradeoffs that make it difficult for college admissions departments to admit deserving students and pay the bills:  the high costs of college and the link between income and test scores.  Indeed when Trinity made standardized testing optional, it fell six places in the rankings.

But I think the article may have missed a bigger issue:  the intensifying competition among colleges for students driven individualized pricing, i.e., price discrimination.  If you set a single price, competition is limited to consumers whose reservation values are near the price.  But when you offer individualized pricing, which is a by-product of financial aid, you start competing for every single student.  In essence you turn relatively mild price competition into an auction--for every single consumer!

See Cooper et al. (2007), Does price discrimination intensify competition?  Antitrust Law Journal,  (also available on SSRN).

If colleges could figure out how to quit offering individualized financial aid--without colluding to do so--I suspect it would soften competition to the point where they could stop losing money.

Why do women bid less for gigs?

They offer 4% lower prices, win jobs more frequently, and earn higher expected revenue (prob[win]*price) than men:  New working paper:

...we provide empirical evidence for a statistically significant 4% gender wage gap among workers, at the project level. We also find that female workers propose lower wage bills and are more likely to win the competition for contracts.

This raises the obvious question, whether women bid more aggressively than men because they think that the opportunity cost of their time is lower, or because they are bidding optimally, and men are not.

Competition among states for businesses

In the 1980's, when I began teaching, little or no attention was paid to customers (students).  That changed with the national rankings of colleges.  The rankings drove demand, which began a competition, especially among private business schools, to rise in the rankings.

Now a similar ranking of the best states in which to start a business may start a similar competition, like the "bidding" for a new Amazon Headquarters.  Here are the losers and winners:

The results are hardly surprising: High-tax, Democrat-controlled states in the northeast offer some of the worst conditions for businesses, while low-tax states, Republican-controlled states in the Sun Belt have some of the best conditions.

Algorithmic Gender Bias?

Last week I got to attend the always enlightening annual ZEW ICT Economics Conference. One of the Keynotes was from the always insightful, Catherine Tucker. In one part of her talk she related that her team conducted an experiment to place a generic ad for a STEM educational program on social media only to find out it was shown much more often to men/boys than women/girls. Algorithmic bias, right!?

Digging a little deeper, they discovered that their bid lost out on the ad auction for females more often because others would bid higher. Ads are placed based on the results of real time auctions for "eyeballs." It turns out that men are cheap (pun intended). That is, women control so much more discretionary spending that they are more heavily courted by advertisers with higher auction bids. The STEM ad bid was the same for men and women and so lost out more often when it had to compete with stronger bids for female "eyeballs."

Bidding advice from an unlikely source

In a first-price auction where the low bid wins, bidders face a tradeoff: a lower bid increases the probability of winning, but reduces profit if they win. In Rising Strong (p. 187), Brene Brown, a professor of social work, identifies five psychological traps that distort how bidders view the tradeoff, which can lead to suboptimal bidding.

1. Emotional blinders:  when bidders become "so emotionally invested in working with a client" that they bid too aggressively (too low). 


2. The loss leader:  an aggressive (low) bid on this project "will lead to future work that ... will eventually offset the loss."


3.  Uncharted territory: If bidding on a project in a new area, you don't know what you don't know, and will likely win only if you under-estimate costs and bid too low. 


4. Win at any cost:  when a bidder becomes addicted to the thrill of winning rather than maximizing profit, the bidder will bid too aggressively (too low). 


5. Defensive pricing:  a bidder may bid too low in order to protect a relationship with an existing client by making it difficult for others to win.

The main point of Brown's book is to present her "rising strong" algorithm on how to grow from conflict.    The bidding advice was lagniappe (Louisiana slang), at least to me.