Tuesday, February 19, 2019
Don't they teach academics anything anymore?
From Parenthood contributes to gender imbalance in STEM employment, but it's not just an issue for mother by Erin A. Cech.
Reporting on what is already well-known. Given the requisite training, inclination, and capabilities, if you want maximum productivity, you find those people who are willing to work full-time for long durations, with the flexibility to expand their schedule to accommodate unanticipated circumstances. Doesn't matter what race or gender or religion or other circumstance. Extended work for lengthy periods with the necessary capabilities gives you the maximum achievable productivity.
There is no gender discrimination. Claudia Goldin among many others have demonstrated that repeatedly. The issue which creates income disparities are any of those factors which preclude focused, extended work over long periods. And that usually circles around two factors - health and family.
If health precludes such work effort, your productivity falls. If family obligations preclude such work effort, your productivity falls. Men and women. Childless men and childless women, with otherwise the same backgrounds, earn exactly the same amount.
And the productivity drop from full-time, sustained, accommodating dedication to more limited time commitments is non-linear. A 10% reduction in time might lead to a 30% reduction in productivity. Cech reports:
They follow up with some appeals which are presumably heart-felt but ungrounded in reality.
More to the point, their study supports none of their conclusions. Their study highlights the income penalty (arising from the productivity penalty) associated with less than full-time commitment to a task.
I went through this in the 1980s and 1990s, trying to find equitable alternative work arrangements, particularly for young mothers. My industry is management consulting and there is, like medicine, and law, a huge premium on deep continued experience, with long hours and long time frames and a capability and willingness to fit one's personal schedule to the demands of the business. That sort of dedication is what drives such high compensations.
Provided below is a single simplistic example of the productivity impact, this being an amalgamation of multiple trials.
One early model which was popular in the business press was job-sharing. Two women both have young children at home and both want to continue their career in consulting but need additional time flexibility. OK - why not split one job between the two of them, they both work half-time, they both stay involved, they both continue on their career track (albeit more slowly), and they both continue to earn compensation. Sounds equitable all around. Win, win, win.
Until you look at the practical and measured impact on productivity. Such high pressure demanding jobs are not easily susceptible to division. Think about the impacts. Employees come with a high fixed cost in terms of office space, equipment, insurance, etc. Say they both earn $100,000 and there is a fixed cost of $25,000 for each employee for all the overheads.
So now you have two employees for the price of one. Each is now only earning $50,000 and your salary cost remains $100,000 plus $25,000. But of course that is not right. Your salary cost indeed remains $100,000 but your overhead cost is now $50,000 since you have two head count. You have gone from a cost structure of $250,000 for two full time people to $150,000 for two part-time people. Your costs have not halved.
In addition, you have increased your supervisory time, i.e. your leadership talent, your scarcest resource. It is another fixed cost. People are regrettably not self-managing. If you had to spend two hours a week per person supervising full time jobs, you now have to spend four hours a week for two people doing one job.
They are both now working 20 hours a week, one in the mornings and one in the afternoon. You really need extra productivity from both of them now.
But that is not what you are going to get. Switching from the cost side, to productivity, it is easy to see what happens. Even with two great employees, you have doubled your risk factor. Two commutes to work instead of one and there are twice as many no-shows. Unexpected developments come during the day so the person with second shift often ends up with a disproportionate part of schedule impacts. An additional handoff during the day introduces further variance into the system. More people per job means more time keeping one another up to speed - increasing transactional coordination costs without increasing productivity. Two personalities means more interpersonal conflicts.
The list goes on and on.
You used to have two full-time employees doing two jobs full time and producing $250,000 in value each. Your income statement looked like:
2 X $100,000 = $200,000
Overhead @ $25,000 per = $50,000
Plus Supervision/person X 2 = $30,000
Total Operating Cost $280,000
Total Revenue 2 X $250,000 = $500,000
Net Income = $220,000
Now, with job sharing, your income statement looks like this:
2 X $50,000 = $100,000
1 X $100,000 = $100,000
Overhead @ $25,000 per = $75,000
Plus Supervision/person X 3 = $45,000
Total Operating Cost $320,000
Total Revenue 2 X $250,000 = $500,000
Net Income = $180,000
By going to job share, you have reduced you profits by 20% or so, theoretically doing exactly the same work.
For Cech and Blair-Loy pursuing an ideological goal where everyone has to want the same thing to the same degree and we need to see the same outcomes, it is obvious we do indeed need a revolution.
Then you look at productivity and you begin to see just how daunting the issue is. What is it that you can do to increase the productivity of individuals when you are at the same time making their jobs much more complex and with much more risk? Not a lot. Everyone is always chasing that goal, but all the easy fruit has been picked.
Cech and Clair-Loy would be far better off exploring how to make people more productive given their personal life and career choices rather than waving magical wands hoping for cultural revolutions that cannot happen with desirable outcomes.
Reporting on what is already well-known. Given the requisite training, inclination, and capabilities, if you want maximum productivity, you find those people who are willing to work full-time for long durations, with the flexibility to expand their schedule to accommodate unanticipated circumstances. Doesn't matter what race or gender or religion or other circumstance. Extended work for lengthy periods with the necessary capabilities gives you the maximum achievable productivity.
There is no gender discrimination. Claudia Goldin among many others have demonstrated that repeatedly. The issue which creates income disparities are any of those factors which preclude focused, extended work over long periods. And that usually circles around two factors - health and family.
If health precludes such work effort, your productivity falls. If family obligations preclude such work effort, your productivity falls. Men and women. Childless men and childless women, with otherwise the same backgrounds, earn exactly the same amount.
And the productivity drop from full-time, sustained, accommodating dedication to more limited time commitments is non-linear. A 10% reduction in time might lead to a 30% reduction in productivity. Cech reports:
Nearly half of new moms and a quarter of new dads leave their full-time STEM jobs after they have their first child, according to a new study.But notice that Cech and Blair-Loy never focus on productivity. This is a huge issue in these kinds of studies.
Researchers found that 43 percent of women and 23 percent of men leave their careers in science, technology, engineering and math within four to seven years of the birth or adoption of their first child.
Women have been underrepresented in the male-dominated STEM fields for decades, especially as they moved further up the career trajectory. Parenthood may contribute to the gender gap, in part, due to gender-related cultural expectations and workplace obstacles, the researchers say.
"Not only is parenthood an important driver of gender imbalance in STEM employment, both mothers and fathers appear to encounter difficulties reconciling caregiving with STEM careers," said the study's lead author Erin Cech, assistant professor of sociology at the University of Michigan.
Cech and Mary Blair-Loy, professor of sociology at the University of California-San Diego, analyzed nationally representative longitudinal survey data from U.S. STEM professionals collected between 2003 and 2010 by the National Science Foundation.
They say that new moms are more likely than new dads to switch to part-time work or leave the workforce.
Some new mothers—about 1 in 10—continue working in STEM on a part-time basis, but that situation isn't without setbacks: businesses and universities typically pay part-time work substantially less per hour than full-time work; is less likely to be accompanied by benefits, like health care; and is less likely to provide advancement opportunities.
They follow up with some appeals which are presumably heart-felt but ungrounded in reality.
"Our results indicate the need for employers to establish highly valued and well-paid part-time options as well as ramp-up policies that allow part-time STEM professionals to transition back into full-time work without long-term career penalties," Blair-Loy said.Tosh. It is pretty astonishing that we are producing academics with such monomaniacal focus on ideology and such ignorance of history that they seem unaware of the alarm bells which go off when an academic calls for a cultural revolution. That they don't know that the most recent and most infamous call for a Cultural Revolution had a butchers bill of 3-10 million is alarming.
If parents leave the STEM workforce, they are unlikely to return by the time their children are old enough to attend school, the researchers say.
"These findings point to the importance of cultural shifts within STEM to value the contributions of STEM professionals with children and the need for creative organizational solutions to help these skilled STEM professionals navigate new caregiving responsibilities alongside their STEM work," Cech said.
Blair-Loy says profound change is needed.
"We need a cultural revolution within many fields to recognize and reward the full value of professionals who also care for children," said Blair-Loy, who also directs the Center for Research on Gender in Science, Technology, Engineering, Mathematics, and Medicine at UC-San Diego.
More to the point, their study supports none of their conclusions. Their study highlights the income penalty (arising from the productivity penalty) associated with less than full-time commitment to a task.
I went through this in the 1980s and 1990s, trying to find equitable alternative work arrangements, particularly for young mothers. My industry is management consulting and there is, like medicine, and law, a huge premium on deep continued experience, with long hours and long time frames and a capability and willingness to fit one's personal schedule to the demands of the business. That sort of dedication is what drives such high compensations.
Provided below is a single simplistic example of the productivity impact, this being an amalgamation of multiple trials.
One early model which was popular in the business press was job-sharing. Two women both have young children at home and both want to continue their career in consulting but need additional time flexibility. OK - why not split one job between the two of them, they both work half-time, they both stay involved, they both continue on their career track (albeit more slowly), and they both continue to earn compensation. Sounds equitable all around. Win, win, win.
Until you look at the practical and measured impact on productivity. Such high pressure demanding jobs are not easily susceptible to division. Think about the impacts. Employees come with a high fixed cost in terms of office space, equipment, insurance, etc. Say they both earn $100,000 and there is a fixed cost of $25,000 for each employee for all the overheads.
So now you have two employees for the price of one. Each is now only earning $50,000 and your salary cost remains $100,000 plus $25,000. But of course that is not right. Your salary cost indeed remains $100,000 but your overhead cost is now $50,000 since you have two head count. You have gone from a cost structure of $250,000 for two full time people to $150,000 for two part-time people. Your costs have not halved.
In addition, you have increased your supervisory time, i.e. your leadership talent, your scarcest resource. It is another fixed cost. People are regrettably not self-managing. If you had to spend two hours a week per person supervising full time jobs, you now have to spend four hours a week for two people doing one job.
They are both now working 20 hours a week, one in the mornings and one in the afternoon. You really need extra productivity from both of them now.
But that is not what you are going to get. Switching from the cost side, to productivity, it is easy to see what happens. Even with two great employees, you have doubled your risk factor. Two commutes to work instead of one and there are twice as many no-shows. Unexpected developments come during the day so the person with second shift often ends up with a disproportionate part of schedule impacts. An additional handoff during the day introduces further variance into the system. More people per job means more time keeping one another up to speed - increasing transactional coordination costs without increasing productivity. Two personalities means more interpersonal conflicts.
The list goes on and on.
You used to have two full-time employees doing two jobs full time and producing $250,000 in value each. Your income statement looked like:
2 X $100,000 = $200,000
Overhead @ $25,000 per = $50,000
Plus Supervision/person X 2 = $30,000
Total Operating Cost $280,000
Total Revenue 2 X $250,000 = $500,000
Net Income = $220,000
Now, with job sharing, your income statement looks like this:
2 X $50,000 = $100,000
1 X $100,000 = $100,000
Overhead @ $25,000 per = $75,000
Plus Supervision/person X 3 = $45,000
Total Operating Cost $320,000
Total Revenue 2 X $250,000 = $500,000
Net Income = $180,000
By going to job share, you have reduced you profits by 20% or so, theoretically doing exactly the same work.
For Cech and Blair-Loy pursuing an ideological goal where everyone has to want the same thing to the same degree and we need to see the same outcomes, it is obvious we do indeed need a revolution.
Then you look at productivity and you begin to see just how daunting the issue is. What is it that you can do to increase the productivity of individuals when you are at the same time making their jobs much more complex and with much more risk? Not a lot. Everyone is always chasing that goal, but all the easy fruit has been picked.
Cech and Clair-Loy would be far better off exploring how to make people more productive given their personal life and career choices rather than waving magical wands hoping for cultural revolutions that cannot happen with desirable outcomes.
Epistemic violence - A refusal of an audience to acknowledge and accept my self-assessed superior position.
From The Boy Who Inflated the Concept of ‘Wolf’ by Spencer Case.
It requires powerful self-control not to shout. The profound anti-intellectualism on display beggars belief. And in particular the self-centeredness that dictates that the free speech and opinions of others must be subordinated to some callow know-nothing's delicate self-regard is almost beyond belief. What are our universities doing. Or more critically, not doing. They clearly are not educating these people.
A variant of Dotson position might be:
One of Aesop’s fables is about a shepherd boy who, out of boredom, repeatedly cries “Wolf!” when no wolf is present. As a result, the villagers lose faith in his testimony, and no one listens to his warnings when a real wolf shows up to devour his flock. The story shows why it’s bad to lie and why it’s in our interest to be honest. But lying is not the only manipulation of language that degrades trust. Consider a slightly different story.It is an interesting article but this opening grabbed me. I am shocked again and again as I hear students at universities and people in general equating the existence of contrary facts, different goals, alternate opinions, and different interpretations as the equivalent of violent of violence, oppression and genocide.
Suppose that instead of one shepherd boy, there are a few dozen. They are tired of the villagers dismissing their complaints about less threatening creatures like stray dogs and coyotes. One of them proposes a plan: they will start using the word “wolf” to refer to all menacing animals. They agree and the new usage catches on. For a while, the villagers are indeed more responsive to their complaints. The plan backfires, however, when a real wolf arrives and cries of “Wolf!” fail to trigger the alarm they once did.
What the boys in the story do with the word “wolf,” modern intellectuals do with words like “violence.” When ordinary people think of violence, they think of things like bombs exploding, gunfire, and brawls. Most dictionary definitions of “violence” mention physical harm or force. Academics, ignoring common usage, speak of “administrative violence,” “data violence,” “epistemic violence” and other heretofore unknown forms of violence. Philosopher Kristie Dotson defines the last of these as follows: “Epistemic violence in testimony is a refusal, intentional or unintentional, of an audience to communicatively reciprocate a linguistic exchange owing to pernicious ignorance.”
It requires powerful self-control not to shout. The profound anti-intellectualism on display beggars belief. And in particular the self-centeredness that dictates that the free speech and opinions of others must be subordinated to some callow know-nothing's delicate self-regard is almost beyond belief. What are our universities doing. Or more critically, not doing. They clearly are not educating these people.
A variant of Dotson position might be:
Epistemic violence in testimony is a refusal of an audience to acknowledge and accept my self-assessed superior position.Its all about demanding power over others.
Tears, Idle Tears
Tears, Idle Tears
by Alfred, Lord Tennyson
Tears, idle tears, I know not what they mean,
Tears from the depth of some divine despair
Rise in the heart, and gather to the eyes,
In looking on the happy autumn fields,
And thinking of the days that are no more.
Fresh as the first beam glittering on a sail,
That brings our friends up from the underworld,
Sad as the last which reddens over one
That sinks with all we love below the verge;
So sad, so fresh, the days that are no more.
Ah, sad and strange as in dark summer dawns
The earliest pipe of half-awakened birds
To dying ears, when unto dying eyes
The casement slowly grows a glimmering square;
So sad, so strange, the days that are no more.
Dear as remembered kisses after death,
And sweet as those by hopeless fancy feigned
On lips that are for others; deep as love,
Deep as first love, and wild with all regret;
O Death in Life, the days that are no more!
Monday, February 18, 2019
Confound their politics Frustrate their knavish tricks
God Save the QueenIn grade school in England in the sixties at school assemblies, and, I think, at the beginning of the Saturday morning cinema matinee for children, I used to sing the British national anthem. I am not sure we ever got past the first stanza, perhaps did not even know that a second and more existed.
God save our gracious Queen
Long live our noble Queen
God save the Queen
Send her victorious
Happy and glorious
Long to reign over us
God save the Queen
O Lord our God arise
Scatter her enemies
And make them fall
Confound their politics
Frustrate their knavish tricks
On Thee our hopes we fix
God save us all
Thy choicest gifts in store
On her be pleased to pour
Long may she reign
May she defend our laws
And ever give us cause
To sing with heart and voice
God save the Queen
Not in this land alone
But be God's mercies known
From shore to shore
Lord make the nations see
That men should brothers be
And form one family
The wide world over
From every latent foe,
From the assassins blow,
God save the Queen!
O'er her thine arm extend,
For Britain's sake defend,
Our mother, prince, and friend,
God save the Queen!
Which is pretty much par for the course in most countries in which I have lived. Most can stumble, more or less, through the first stanza only. But now that I look at the entire anthem, I love that second stanza.
O Lord our God ariseThe British anthem is a rousing tribal song but I think it pales to the American anthem which is really a ballad and a paean to freedom and the choice of freedom. Sure, we usually have trouble with the notes, but most people can get through the first stanza, and often with a racing pulse.
Scatter her enemies
And make them fall
Confound their politics
Frustrate their knavish tricks
On Thee our hopes we fix
God save us all
The Star-Spangled Banner
by Francis Scott Key
O say can you see, by the dawn's early light,
What so proudly we hailed at the twilight's last gleaming,
Whose broad stripes and bright stars through the perilous fight,
O'er the ramparts we watched, were so gallantly streaming?
And the rockets' red glare, the bombs bursting in air,
Gave proof through the night that our flag was still there;
O say does that star-spangled banner yet wave
O'er the land of the free and the home of the brave?
On the shore dimly seen through the mists of the deep,
Where the foe's haughty host in dread silence reposes,
What is that which the breeze, o'er the towering steep,
As it fitfully blows, half conceals, half discloses?
Now it catches the gleam of the morning's first beam,
In full glory reflected now shines in the stream:
'Tis the star-spangled banner, O long may it wave
O'er the land of the free and the home of the brave.
And where is that band who so vauntingly swore
That the havoc of war and the battle's confusion,
A home and a country, should leave us no more?
Their blood has washed out their foul footsteps' pollution.
No refuge could save the hireling and slave
From the terror of flight, or the gloom of the grave:
And the star-spangled banner in triumph doth wave,
O'er the land of the free and the home of the brave.
O thus be it ever, when freemen shall stand
Between their loved homes and the war's desolation.
Blest with vict'ry and peace, may the Heav'n rescued land
Praise the Power that hath made and preserved us a nation!
Then conquer we must, when our cause it is just,
And this be our motto: 'In God is our trust.'
And the star-spangled banner in triumph shall wave
O'er the land of the free and the home of the brave!
In the absence of specific information, taste based discrimination is weak but statistical discrimination is common.
Interesting work from Reducing Discrimination with Reviews in the Sharing Economy: Evidence from Field Experiments on Airbnb by Ruomeng Cui, Jun Li, Dennis Zhang.
Interesting in part because it reinforces my priors. From the Abstract (emphasis added):
Most academics in these studies seem to come across as highly prejudiced in that they seem to believe that all white Americans are biased against all black Americans, that pursuit of business profitability is not worthy of attention, ignore that everyone responds to incentives, ignore that race is a proxy of group average information, and fail to take into account that race and class are intertwined categories of information.
The scenario we are looking at is a low information high consequence transaction. The hospitality industry in many times and places is a fiercely competitive and low margin business. One bad guest can put the landlord into the financial red for the next several guests. Landlords are well rewarded financially for accurately assessing whether a guest will likely steal, destroy, or skip out without paying.
In a world where landlords are precluded from viewing accurate actual information related to the specific guest, they use less than desirable proxies. They are indeed attempting to discriminate but not necessarily for invidious reasons.
Attributes which might usually be seen as carrying positive or negative information might include race, gender, age, family status, profession, religion, education attainment, criminal history, credit score, etc. Virtually all landlords would rent in an unstinting fashion to 55 year-old, female, black, physicians, affiliated with a mainline protestant church, and with good credit scores and would not rent to 18 year-old, unemployed, white males without a high school diploma, with bad credit scores, and a criminal record. If they could do so knowingly. Race is not the critical factor for the landlord except to the extent that it provides information about the probability of being payed and not having any issues or damages.
If all we know is the race of an individual, there is inherently an associated and inferred income, crime, wealth, class, profile that goes with that race. But so there is also with age, gender, religion, etc.
For an individual, as long as there is no specifically individual information which can be shared, landlords will use what limited proxies they have in order to make the best income maximizing decision they can with statistical average proxies.
One solution is to provide a richer palate of individual specific information about the renter in order to allow landlords to make more targeted and informed decisions. I believe that to be the better approach. It benefits the well-intentioned landlord and the well-behaving renter. It disadvantages the ill-behaved renter.
For the past three decades or so we have gone a different route. Instead of making accurate and specific information available to the renter/decision-maker, we have instead attempted to preclude them from knowing much at all about the renter. What has been documented time and again is that landlords will use whatever proxies they can that usefully advances their goal of being paid and not having to deal with issues and damages.
It is hard on landlords and is even harder on well-behaved and reliable individuals within groups that have negative average group attributes.
We see this most clearly in labor force studies. There is a widespread, and well intentioned, movement to "ban the box" when it comes to labor force hiring. Many states preclude employers from asking about criminal history on the theory that it carries no useful information and that such information disproportionately harms some racial groups over others.
What most studies find is that black hiring rates go up when employers are able to ask about criminal history and go down when employers cannot. What appears to be happening is that employers want reliable trustworthy employees and that is poorly correlated with past criminal behavior.
For the same candidate, if the employer is able to ask about criminal history they can discover things like the fact that even though you are black and with a criminal record, the criminal conviction was for stealing a car at 17 but that you then turned your life around, served in the marines, attend church, etc. With that information, the employer can make a better informed decision about the probability of your being a reliable trustworthy employee and extends an offer of employment.
In contrast, the employer precluded from asking about criminal history can rely on only two pieces of information - you are black and group average conviction rates are much higher for blacks. If they can get away with it, they will extend job offers at a higher rate to groups with better group averages rather than to individuals.
I like Alex Tabarrok's summary of this study:
Interesting in part because it reinforces my priors. From the Abstract (emphasis added):
Recent research has found widespread discrimination by hosts against guests of certain races in online marketplaces. In this paper, we explore ways to reduce such discrimination using online reputation systems. We conduct four randomized field experiments among 1,801 hosts on Airbnb by creating fictitious guest accounts and sending accommodation requests to them. We find that requests from guests with African American-sounding names are 19.2 percentage points less likely to be accepted than those with white-sounding names. However, a positive review posted on a guest's page significantly reduces discrimination: When guest accounts receive a positive review, the acceptance rates of guest accounts with white-sounding and African American-sounding names are statistically indistinguishable. We further show that a non-positive review and a blank review without any content can also help attenuate discrimination, but self-claimed information on tidiness and friendliness cannot reduce discrimination, which indicates the importance of encouraging credible peer-generated reviews. Our results offer direct and clear guidance for sharing-economy platforms to reduce discrimination.I have long argued three key elements - 1) much of academic research on name type reflects underlying negative stereotypes by academics of their fellow Americans; 2) most does not take into account incentive structures, costs and risks; and 3) most the academic research is structurally flawed because they fail to distinguish race from class.
Most academics in these studies seem to come across as highly prejudiced in that they seem to believe that all white Americans are biased against all black Americans, that pursuit of business profitability is not worthy of attention, ignore that everyone responds to incentives, ignore that race is a proxy of group average information, and fail to take into account that race and class are intertwined categories of information.
The scenario we are looking at is a low information high consequence transaction. The hospitality industry in many times and places is a fiercely competitive and low margin business. One bad guest can put the landlord into the financial red for the next several guests. Landlords are well rewarded financially for accurately assessing whether a guest will likely steal, destroy, or skip out without paying.
In a world where landlords are precluded from viewing accurate actual information related to the specific guest, they use less than desirable proxies. They are indeed attempting to discriminate but not necessarily for invidious reasons.
Attributes which might usually be seen as carrying positive or negative information might include race, gender, age, family status, profession, religion, education attainment, criminal history, credit score, etc. Virtually all landlords would rent in an unstinting fashion to 55 year-old, female, black, physicians, affiliated with a mainline protestant church, and with good credit scores and would not rent to 18 year-old, unemployed, white males without a high school diploma, with bad credit scores, and a criminal record. If they could do so knowingly. Race is not the critical factor for the landlord except to the extent that it provides information about the probability of being payed and not having any issues or damages.
If all we know is the race of an individual, there is inherently an associated and inferred income, crime, wealth, class, profile that goes with that race. But so there is also with age, gender, religion, etc.
For an individual, as long as there is no specifically individual information which can be shared, landlords will use what limited proxies they have in order to make the best income maximizing decision they can with statistical average proxies.
One solution is to provide a richer palate of individual specific information about the renter in order to allow landlords to make more targeted and informed decisions. I believe that to be the better approach. It benefits the well-intentioned landlord and the well-behaving renter. It disadvantages the ill-behaved renter.
For the past three decades or so we have gone a different route. Instead of making accurate and specific information available to the renter/decision-maker, we have instead attempted to preclude them from knowing much at all about the renter. What has been documented time and again is that landlords will use whatever proxies they can that usefully advances their goal of being paid and not having to deal with issues and damages.
It is hard on landlords and is even harder on well-behaved and reliable individuals within groups that have negative average group attributes.
We see this most clearly in labor force studies. There is a widespread, and well intentioned, movement to "ban the box" when it comes to labor force hiring. Many states preclude employers from asking about criminal history on the theory that it carries no useful information and that such information disproportionately harms some racial groups over others.
What most studies find is that black hiring rates go up when employers are able to ask about criminal history and go down when employers cannot. What appears to be happening is that employers want reliable trustworthy employees and that is poorly correlated with past criminal behavior.
For the same candidate, if the employer is able to ask about criminal history they can discover things like the fact that even though you are black and with a criminal record, the criminal conviction was for stealing a car at 17 but that you then turned your life around, served in the marines, attend church, etc. With that information, the employer can make a better informed decision about the probability of your being a reliable trustworthy employee and extends an offer of employment.
In contrast, the employer precluded from asking about criminal history can rely on only two pieces of information - you are black and group average conviction rates are much higher for blacks. If they can get away with it, they will extend job offers at a higher rate to groups with better group averages rather than to individuals.
I like Alex Tabarrok's summary of this study:
In other words, taste based discrimination is weak but statistical discrimination is common. Statistical discrimination happens when legitimate demands for trust are frustrated by too little information. Statistical discrimination is a second-best solution to a problem of trust that both owners/sellers/employers and renters/buyers/workers want to solve. Unfortunately, many people try to solve statistical discrimination problems as if they were problems of invidious prejudice.The comments on Tabarrok's post are worth reading for a robust discussion.
If you think the problem is invidious prejudice, it’s natural to try to punish and prevent with penalties and bans. Information bans and penalties, however, often have negative and unintended consequences. Airbnb, for example, chose to hide guest photos until after the booking. But this doesn’t address the real demands of owners for trust. As a result, owners may start to discriminate based on other cues such as names. Instead market designers and regulators should approach issues of discrimination by looking for ways to increase mutually profitable exchanges. From this perspective, providing more information is often the better approach.
The shortness of life prevents us from entertaining far-off hopes
They Are Not LongThe Latin is "The shortness of life prevents us from entertaining far-off hopes" from Horace, in the Odes (Odes 1.4.15).
by Ernest Dowson
Vitae summa brevis spem nos vetat incohare longam.
They are not long, the weeping and the laughter,
Love and desire and hate;
I think they have no portion in us after
We pass the gate.
They are not long, the days of wine and roses,
Out of a misty dream
Our path emerges for a while, then closes
Within a dream.
Sunday, February 17, 2019
What happens when we can't know what we are talking about?
From What does it mean to speculate that growth is faster than we think? by Scott Sumner. There are plenty of complex system issues of which we are aware but have insufficient information to make effective decisions.
Climate change is the one I harp on with frequency - no ideological dog in this fight, just observing that climate is an extremely complex amalgamation of multiple complex dynamic, interactive, log-sensitive systems of which we have too little knowledge and radically too little information. We have very little accurate, unadjusted, consistent climate measurements before thirty years ago. A way shorter time period than the normal system cycles we know are involved in climate. And what we do have is primarily in a small handful of locations around the globe. Most the surface area is unmeasured. We are shooting in the dark.
Made worse by skewed incentive schemes and an over-reliance on system modeling which we know is prone to produce outcomes built into them through unstated assumptions. There likely is reason to be concerned but we cannot state that concern with great confidence. Instead, we skip that step and move straight towards emotional advocacy.
Sumner is talking about a similarly complex issue and possibly as consequential but with a far smaller audience of self-designated experts or interested parties - in Tyler Cowen's words:
The answer to all three questions is almost certainly NO! but we don't have good ideas for putting ourselves into a better position to know.
Sumner adds a fourth concept that makes the questions even harder to answer.
Sumner elaborates his argument, straying, in my opinion, into some fundamentally unsound positions. But the whole piece, including the comments attached, go to the heart of a pertinent challenge. We can conceptualize more than we can effectively, consistently and reliably measure.
We get growth, innovation, and prosperity wrong and concerns about climate a century and a millennia from now become somewhat moot.
What do we do about public dialogues around issues whose dynamism and complexity outstrip our capacity to reliably know through measurement?
Climate change is the one I harp on with frequency - no ideological dog in this fight, just observing that climate is an extremely complex amalgamation of multiple complex dynamic, interactive, log-sensitive systems of which we have too little knowledge and radically too little information. We have very little accurate, unadjusted, consistent climate measurements before thirty years ago. A way shorter time period than the normal system cycles we know are involved in climate. And what we do have is primarily in a small handful of locations around the globe. Most the surface area is unmeasured. We are shooting in the dark.
Made worse by skewed incentive schemes and an over-reliance on system modeling which we know is prone to produce outcomes built into them through unstated assumptions. There likely is reason to be concerned but we cannot state that concern with great confidence. Instead, we skip that step and move straight towards emotional advocacy.
Sumner is talking about a similarly complex issue and possibly as consequential but with a far smaller audience of self-designated experts or interested parties - in Tyler Cowen's words:
Many people suggest that we are under-measuring the benefits of innovation, and thus real rates of economic growth are much higher than we think. That in turn means the gdp deflator is off and real rates of interest are considerably higher than we think. Someday we will all realize the truth and asset prices will adjust.It is actually a little more complex than that - are we measuring economic growth accurately, are we measuring innovation accurately, and are we measuring well-being accurately?
Let’s say that view is correct (not my view, by the way), how should that change your investment decisions?
[snip]
More generally, if real rates of return are high, but not perceived as high by most investors (who are still victims of fallacious “great stagnation” arguments and the like), at some point those investors will learn. With more rapid growth enriching the future, and with the realization of such, there will be a sudden demand to shift funds into the present, so as to equalize marginal utilities. So bond prices will fall and that means you should short bonds and buy puts on bonds.
The answer to all three questions is almost certainly NO! but we don't have good ideas for putting ourselves into a better position to know.
Sumner adds a fourth concept that makes the questions even harder to answer.
Growth is getting increasingly hard to measure as we move from an economy of stuff (commodities) to an economy of intangibles. If we can no longer measure growth in terms of quantity of “widgets” being produced, we need some measure of the value provided by economic output. You could use money, but the value of money itself changes over time. So that won’t work.Happiness? What the hell thing is that to measure?
Economists typical speak in terms of “utility”. But as far as I know there is not a shred of evidence that we have more utility than we had 60 years ago. When I look around, it doesn’t seem like people are happier than when I was a child. Maybe they are happier (I’m agnostic on the question), it just doesn’t seem that way to me. Of course utility and happiness are not necessarily the same thing, but I’d make the same argument for each. It’s not clear we are getting happier, and it’s equally unclear that we are accumulating more utility.
Now you might argue that this is because real wages have stagnated for 60 years. I don’t agree, but that argument cannot account for China, where polls show no aggregate increase in happiness since the 1990s. No one disputes that real wages in China (as conventionally measured) have soared much higher. Unlike Americans, the Chinese really do have lots more stuff; it’s not just quality change. So economic growth is a slippery concept, which is hard to measure.
Sumner elaborates his argument, straying, in my opinion, into some fundamentally unsound positions. But the whole piece, including the comments attached, go to the heart of a pertinent challenge. We can conceptualize more than we can effectively, consistently and reliably measure.
We get growth, innovation, and prosperity wrong and concerns about climate a century and a millennia from now become somewhat moot.
What do we do about public dialogues around issues whose dynamism and complexity outstrip our capacity to reliably know through measurement?
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