Thursday, September 30, 2021

Should we ban private label brands?

Democrat Rep. Cicilline thinks so:  

Rep. Cicilline says, “you can be one or the other. You can't set all the rules, control the marketplace, and also sell on it.” What he forgets is that vertical integration benefits consumers and businesses alike. If America followed Cicilline’s way, this new law would drive up the prices of everyday goods. In fact, it would be illegal for CVS to sell generic over-the-counter medications, leaving low-income Americans with fewer options and higher prices.

And don't forget the beneficial effect that private brands have on competition within a store:

And most consumers like having these generic brands as options because they’re cheaper, force prices down of name brands, and can even push companies to improve their quality.

So who benefits from this?  Rival brands.  

BOTTOM LINE:  Antitrust laws protect competition, not competitors.

TRUTH IN BLOGGING DISCLOSURE:  I wear only Kirkland.     

Monday, September 27, 2021

Danish Criminals respond to incentives

The Effects of DNA Databases on the Deterrence and Detection of Offenders
Anne Sofie Tegner Anker, Jennifer L. Doleac and Rasmus LandersĂž
This paper studies the effects of adding criminal offenders to a DNA database. Using a large expansion of Denmark's DNA database, we find that DNA registration reduces recidivism within the following year by up to 42 percent. It also increases the probability that offenders are identified if they recidivate, which we use to estimate the elasticity of crime with respect to the detection probability and find that a 1 percent higher detection probability reduces crime by more than 2 percent. We also find that DNA registration increases the likelihood that offenders find employment, enroll in education, and live in a more stable family environment. 
Full-Text Access | Supplementary Materials

Here is the mechanism:  Higher probability of detection ==> lower expected profits from criminal activity ==> less crime

Saturday, September 25, 2021

Why is Bezos such an extraordinary manager?

Reading Amazon Unbound by Brad Stone, his second bio of Jeff Bezos and Amazon, which picks up where The Everything Store left off.  In the book, Bezos punishes managers for wasting time on small incremental--and successful--projects. 

It is as if Bezos recognizes the perverse incentives created by ordinary managers, who punish employees for making the more-visible Type I errors (doing something that they shouldn't), rather than the less-visible Type II errors (failing to do something they should).  Typically this kind of reward asymmetry leads to fewer Type I errors but more Type II ones. 

But in an innovative environment, Type II errors typically have bigger costs, so it is incumbent on managers to find a way to avoid them.  So Bezos rewards managers who fail spectacularly in pursuit of something big and punishes those who succeed at timid, incremental change.   

Thursday, September 23, 2021

Less of other peoples' money is funding insurance

Health insurance costs about $20,000, 3/4 of which is paid by your employer.  One way to keep costs down is to raise deductibles.  This reduces costs is two ways:

  1. By reducing consumption of low value care (moral hazard); and
  2. By giving consumers an incentive to shop for lower price and higher quality care


Why is auto insurance more expensive if you pay monthly instead of every six months?

Because insurance companies use monthly payments as a screen.  By offering a big discount if you pay for six months, you screen out bad drivers, who cannot afford to do that.  

This screen works for the same reason that screening on credit scores works, there is a positive correlation between credit scores and expected costs of insuring a driver.   

Using credit history to price car insurance

In 2007, the FTC's Bureau of Economics just relased their FACTA study, which concludes that:
  1. Credit scores effectively predict ... the total cost of [auto insurance] claims.
  2. Credit scores permit insurers to evaluate risk with greater accuracy, which may make them more willing to offer insurance to higher-risk consumers ... . [note: this is why you can call up GEICO, let them look at your credit report, and get an auto insurance quote over the phone].
  3. a group, African-Americans and Hispanics tend to have lower scores than non-Hispanic whites and Asians.
  4. ...scores effectively predict risk of claims within racial and ethnic groups.
  5. The Commission could not develop an alternative scoring model that would continue to predict risk effectively, yet decrease the differences in scores among racial and ethnic groups.
So even though credit scores help insurance companies price insurance more accurately, point 3 implies that some groups pay more, on average, than others. The policy issue behind the study is whether the government ought to ban the use of credit history for anything but making loans. As point 4 implies, banning the use of credit scores would result in higher prices for good drivers, regardless of their race or ethnicity.

Theory tells us that in states which ban the use of credit scores to price insurance (California and Massassachusetts) insurance companies would find it more costly to distinguish high from low risks, so they may lump them together (called "pooling"), and price insurance at the average risk. Or they may be concerned that only high risks would be willing to buy high-priced insurance (what economists call "adverse selection") and price high or, if price controls prevent high prices, exit the market.

I would be curious if any of our readers know of novel uses of credit scores as a screening mechanism, or if they have developed better predictors (point 5) in a particular application, like pricing insurance or screening job applicants.

Big data and the curse of dimensionality

I just finished a fabulous book, Everybody Lies, written by Seth Stephens-Davidowitz.  From the Amazon description of the book:
Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women?

I particularly liked the metaphors that Stephens-Davidowitz uses to describe his results.  For example,  in describing why it is easy to come up with variables that correlate with the stock market, but hard to find ones that can make accurate predictions, he uses the metaphor of coin flipping:

Suppose your strategy for predicting the stock market is to find a lucky coin -- but one that will be found through careful testing. Here's your methodology: You label one thousand coins - 1 to 1,000. Every morning, for two years, you flip each coin, record whether it came up heads or tails, and then note whether the Standard & Poor's Index went up or down that day. You pore through all your data. And voila! You've found something. It turns out that 70.3 percent of the time when Coin 391 came up heads the S&P Index rose. The relationship is statistically significant! Highly so! You have found your lucky coin! 
Just flip Coin 391 every morning and buy stocks whenever it comes up heads. Your days of Target T-shirts and ramen noodle dinners are over. Coin 391 is your ticket to the good life!

Every statistics user should know that when running 1000 hypothesis tests, on average 50 of them will show statistically significant results, even when there is no relationship.  This is the size of Type I error (5%) in classical hypothesis testing.

Instead, split your sample in two and use half the data to "find" (estimate) one lucky coin; and the other half to test it.

BOTTOM LINE:  the more tests you run, the more likely it is that at least one of them will show a statistically significant relationship, even if there is none.  This is likely behind what has become known as the replication crisis, that has hit the field of psychology particularly hard as only one third of the results from the most cited articles could be replicated.  It is likely that academics are testing lots of hypotheses and publishing the few that turn out to be statistically significant.  This is analogous to finding a lucky coin, as it only appears to be lucky.  Once you test it outside the sample, the luck disappears.

TRUTH IN BLOGGING:  the field of economics has its own replication crisis, only two thirds of top results could be replicated.

Wednesday, September 22, 2021

Density is green!: California housing supply to increase.

Restrictive zoning laws have decreased supply and driven up housing prices in almost every state, especially in California. This has led states to build "affordable housing" to combat the problem that their own restrictive zoning laws created. But now, the California Governor is trying to attack the zoning problem directly.
Newsom previously had shaken up single-family zoning by signing legislation that allowed more homeowners to build in-law units on their properties. SB 9 takes that further, allowing property owners to build up to two duplexes on what was once a single-family lot.
However, the usual suspects [we hypocrites] are opposing density that reduces sprawl, pollution, and traffic:
Slow-growth group Livable California, which has pushed back against SB 9, called it a “radical density experiment” and worried developers would use it to remake neighborhoods without community input.
In case I have to translate, "community input" means "no new supply" which raises the price of housing which benefits older, richer homeowners who are likely to vote; and hurts younger, poorer would-be homeowners who are less likely to vote.

Is it time to adapt by buying land in Alaska?

People are concerned about climate change:
...a recent 10-country study showing the fears of young people about climate change. Four in 10 are afraid to have children. Almost half said that fears about climate change caused them stress and anxiety in their daily lives.

 Its estimated effects will be different for different regions:

...the hottest regions in South America, Africa, India and Australia experience welfare losses of 15% and the coldest regions in Alaska, Northern Canada, and Siberia undergo welfare gains as high as 14%. On average, the world is expected to lose 6% in terms of welfare...

The net estimated effect is negative but very uncertain:

One recent estimate suggests that climate change is likely to destroy about 10% of global welfare ... by the year 2200. To the economist, that is a truly significant quantity of resources. Furthermore, the distribution of those losses may [will] be unfair ...

But the future belongs not to the strong, but rather to the adaptable.  


Tuesday, September 21, 2021

Good metaphor for tradeoffs associated with a bigger safety net

To communicate ideas, we need metaphors.  Greg Mankiw has a good one in this mornings NY Times, Can America Afford to Become a Major Welfare State?

Providing a social safety net is like using a leaky bucket to redistribute water among people with different amounts. While bringing water to the thirstiest may be noble, it is also costly as some water is lost in transit.

In the real world, this leakage occurs because higher taxes distort incentives and impede economic growth. And those taxes aren’t just the explicit ones that finance benefits such as public education or health care. They also include implicit taxes baked into the benefits themselves. If these benefits decline when your income rises, people are discouraged from working. This implicit tax distorts incentives just as explicit taxes do. That doesn’t mean there is no point in trying to help those in need, but it does require being mindful of the downsides of doing so. ...  

most European nations use that leaky bucket more than the United States does and experience greater leakage, resulting in lower incomes. By aiming for more compassionate economies, they have created less prosperous ones. Americans should be careful to avoid that fate.

Wednesday, September 15, 2021

Hidden Costs of Software Migration

Like many universities, some researchers at mine have sensitive data. Since a data breach would be calamitous, all university computers, laptops and desktops, must be encrypted. We just changed vendors for our encryption software. The new vendor requires a new version of the operating system. This requires backing up all of the data on a computer, installing the new OS and encryption functionality, and then reinstalling the backed up data (more on this in a later post). The process requires each computer user to bring their computer to our IT department and be present to provide log in credentials multiple times. If all goes smoothly (more on this in a later post), the process takes 2-3 hours of both the user's time and the techie's time. They estimate that this must be done for 7,000 university computers.

It will take 14,000 to 21,000 hours of just techie time, or 7 to 10.5 person-years at 2,000 hours per work-year to accomplish this task. I think this means that about half of the IT department's staff will be working on just this task full-time for a year. Suppose the average of techie's and staff/faculty salary is $80,000 to $100,000. This means that for a 2,000 hour work year, each hour is worth $40-$50 not counting benefits. The total value of lost time could easily be in the $1.1 million to $2.1 million range. I strongly suspect these costs were not fully taken into account when selecting the new vendor. I strongly suspect that this is greater than the marginal benefits from the new vendor.

Monday, September 6, 2021

The paradox of ESG investing

ESG definition:

  • Environment. What kind of impact does a company have on the environment? 
  • Social. How does the company improve its social impact?
  • Governance. How does the company’s board and management drive positive change? 
The point of ESG investing is to lower the stock price and raise the cost of capital of disfavored industries, and therefore slow down their investment.
If it works, it raises the cost of capital to non-ESG firms, which lowers the Net Present Value (NPV) of their investments (because they have higher discount rates). As a consequence, non-ESG firms get very picky, and invest only in projects with higher rates of return. 

On the other side of the coin, NPV investing lowers the cost of capital to ESG firms, which raises the NPV of their investments (because they have lower discount rates). As a consequence, ESG firms get less picky and invest in more projects with lower rates of return. 

The paradox: "if you don't lose money on ESG investing [relative to non-ESG investing], ESG investing doesn't work. Take your pick." 

from those who cite studies showing that ESG firms do better on average than non-ESG firms.

If this were the case, I would guess that the causality runs in the opposite direction, i.e., from successful firms who invest in ESG projects because they can afford it.  Cynically, this could be a form of virtue signaling to attract consumers who identify with ESG causes.  

As the Financial Times warns:
investors should be more discriminating in how they assess corporate capabilities rather than swallowing hook, line and sinker evaluations from investment houses desperately inflating their so-called ESG portfolios to meet the huge surge in investor demand.

Saturday, September 4, 2021

Price discriminating against brides seems profitable

The wedding industry is notorious for sticking it to brides.   But whether this is due to price discrimination or higher costs (brides can be demanding) is still a matter of debate.  But here is an example that seems clear:

As I wrote in the column, part of the reason that retailers can get away with charging higher prices for wedding-related services is that spouses-to-be probably have stronger preferences for their “special day” than consumers shopping for other kinds of events do. That means they’re less price-sensitive. In the case of gowns, for example, brides probably have much more specific requirements for their own dresses than for the dresses that their bridesmaids will wear, allowing retailers to charge different prices for each, regardless of what material or labor costs go into the respective frocks.

I classify this as direct price discrimination because retailers identify the bride, set separate prices, and prevent arbitrage.  


Thursday, September 2, 2021

Jeff Bezos does HR

Reading Amazon Unbound by Brad Stone, his second bio of Jeff Bezos and Amazon, which picks up where The Everything Store leaves off.  

It is amazing how much Bezos involves himself in the details of running the company.  For the many of problems that Amazon faced--Kindle, Alexa, expansion into India, Mexico, and Brazil, or even HR--Bezos would form a team, give them an insane deadline, and dive into the details himself.  

Most significantly, Bezos is not afraid to make mistakes.  He initially tried detailed performance reviews, but then moved to a something simpler, and easier for employees to digest.  Explaining the change to his board of directors, he said of the old way "its like telling your wife how great she is, and then adding, `but you are a little overweight.'  She won't remember anything else."