Some social and political analysts regard private help as a bad thing. They speak of the “problem” of food banks, and of America’s “miserly” support for poorer countries. In fact food banks are a solution, not a problem. Private generosity has leapt into the breach to help tide people over temporary problems. The great majority of food bank users do so only once.
Similarly with US aid to poorer countries. The United States is regularly berated for being very low on the list of aid givers, but this only applies to government-to-government aid. Once the private contributions made by Americans to people in poorer countries are counted in, the US rises to the top. In fact US private help is better spent, usually going to people to spend in towns and villages in the local economy, rather than on gold palaces and white elephant steel mills in the desert.
Part of this mismatch arises from the fact that these analysts seem to wear spectacles that admit only light of a political wavelength and ignore private generosity. The latest victim of this myopia is the “bank of mom and dad.” It is assumed to be a bad thing that young people should turn to mom and dad to help out with deposits and mortgages.
“Richard”, “Is Private Help a Bad Thing? – Political Spectacles of the Left”, Continental Telegraph, 2018-04-02.
July 15, 2020
QotD: State and private charity
June 19, 2020
The economy isn’t all huge corporations and government
Paul Sellers reminds us that the economy is far more than just the big names that get mentioned in the financial pages:
An example of the kind of one-man businesses Paul is talking about.
Independents in micro-businesses are few and far between and often hard to discover, despite the internet’s ever-increasing web of enterprises. The backbone of British industry is made up of small, independent people striving to retain a measure of individualism, independence and entrepreneurialism in their lives. Statistics from 2019 show that in Britain there were 5.82 million small businesses responsible for 99.3% of the total business output in the UK.
Small businesses here comprise those with 0-49 employees and digging deeper still into what might at first seem more irrelevant than relevant is that the niche that small businesses fill in the real world of enterprise. Over 76% of businesses are operated by one-man bands; single-person enterprises who operate alone comprise almost 4.5 million men and women. With an additional 1.15 million micro-business (1-9 employees) around 95% of businesses here operate on a strength of under just 10 people. So over 99% of small to medium business enterprises, that’s zero to 249 employees, but only 0.6% have a workforce of 50-249 employees. Less than 4% are small businesses with 10-49 staff members and get this, over 95% operate as micro-businesses with 0-9 employees. What does this tell you about businesses output? What it tells me is how little of this is newsworthy by the mass media manufacturing companies (Like BBC News and ITV, Sky and so on) who constantly tell us about how many this massive company or that massive company is laying off and how little this really affects our economy because the little guys still get out into their little micro-shops and make what cannot work work.
June 2, 2020
QotD: Economic inequality
Steven Pinker, “Twenty Questions with Steven Pinker”, Times Literary Supplement, 2018-02-18.
May 31, 2020
QotD: Measuring what can be measured
Jerry Z. Muller, The Tyranny of Metrics, 2018.
May 24, 2020
QotD: The “balance of trade”
The first thing to observe about this concept [of the balance of trade] is that it is in fact an analytic tool. The balance of trade is not a concrete thing like a price or a load of merchandise.
Yes (although it is even more accurate to describe the balance of trade as an accounting convention). If, for example, it had been decided to record purchases and sales of real estate on the current account rather than on the capital account, the size of each country’s current-account deficit or surplus would be different even though absolutely nothing real in the national or global economy would be changed. And yet to hear any of the many protectionists bemoan their country’s trade- or current-account deficit is to hear people who typically mistake this accounting convention for a concrete thing. Such complaints almost always reflect utter misunderstanding of so-called “trade balances.”
Don Boudreaux, “Bonus Quotation of the Day…”, Café Hayek, 2018-01-21.
May 9, 2020
Lies, damned lies, and even-more-damned statistics
David Warren does not trust “the numbers” (and I think he’s quite right to doubt):
At some point — but it is seldom a discrete moment in space or time — the weight of the anecdotal in science, or that of the circumstantial in law, becomes overwhelming. This is the opposite of a statistical fact, in part because there are no statistical facts. I am reminded of this whenever the “scientific” control freaks of statistics lay down some law, indifferent to the Law in nature. The difference between 999,999 and one million is, in any imaginable situation, not a difference at all. Where it is made the basis for a decision, that decision is arbitrary, and not infrequently, cruel. By contrast, such differences as those between pregnant and not pregnant, dead and not dead, are unchallengeably significant. They are in the realm of meaning.
I am reminded of this hourly or better, these days, when consulting the news. All readers of the mass media (accurately described by Trump as “fake news”) are being covered, constantly, by the vomit of statistics — few with any context, and many knowingly false. They “look scientific,” which is to say, they answer to the moron’s conception of science. In “disciplines” like economics, today, and throughout the other social sciences, the participants sleepwalk. Nobel prizes are given out for numerical sludge, presented to the purpose of selling one destructive “policy” or another, that will be imposed on real, live, particular human beings. The same is true of the “mathematical biology” that has disinformed all our public health “professionals.”
The Red Chinese Batflu, now transforming our world, is a spectacular case in point. Not only the epidemiological projections, but even the counts of dead and wounded, are taken on faith — from people who are characteristically faithless. Information on prevention and cures is hostage to the work of statisticians. “Double blind tests,” which would be absolutely immoral — wicked — on human subjects facing life or death — are demanded by our medical apes.
May 5, 2020
The perverse incentives of the Wuhan Coronavirus outbreak
David Warren has clearly taken his cynical pills today:
The daily count of deaths from the Red Chinese Batflu is among the prized, scare-mongering features of our mass media. I am among those who consider these numbers to be significantly overstated, for a reason that Nikolai Gogol would understand. Each corpse is worth cash to some public authority, usually from a higher authority; and as always, finally from the taxpayers. Each also saves money for government programmes, that can be reallocated to the purchase of new votes. As the corpse providers from this virus are very old, and suffering from other life-threatening conditions, in almost every case, this statistical inflation is easy to perform. Death certificates are issued for any who died with “Covid-19,” whether or not they died from it, and more are then added of those who were never tested. Anything respiratory will do. It’s all judgement calls — on which side of the bread is buttered.
Compare if you will the Hong Kong Flu of 1968 and 1969. I was just reading a memoir, from down that memory hole. The death toll was actually higher then, than ours is now, and from within a smaller population; the victims included children and the young. Yet there were no interruptions in economic life; no public emergency theatricals; and at the height of the second wave of that scourge, we had events like Woodstock. (Those were the days, my friend.)
A neat way to correct for all our “judgement calls” might be to look at overall death rates, and see if they have risen or fallen. It is too early to get a clear view, but soon it may be too late, for vested interests will have tampered with them. All my life I have been learning to trust statistics, less — especially from those who dress in labcoats and affect that earnest look. Sometimes an exception must be considered, however. An unpredictable minority may be honest; some others might get numbers right by mistake.
April 12, 2020
QotD: The Gini coefficient
The redistributionist impulse has brought to the fore metrics such as the Gini coefficient, named after the ur-redistributor, Corrado Gini, an Italian social scientist who developed an early statistical measure of income distribution a century ago. A society where a single plutocrat earns all the income ranks a pure “1” on the Gini scale; one in which all earnings are perfectly equally distributed, the old Scandinavian ideal, scores a “0” by the Gini test. The Gini Index has been renamed or updated numerous times, but the principle remains the same. Income distribution and redistribution seem so crucial to progressives that French economist Thomas Piketty built an international bestseller around it, the wildly lauded Capital.
Through Gini’s lens, we now rank past eras. Decades in which policy endeavored or managed to even out and equalize earnings — the 1930s under Franklin Roosevelt, the 1960s under Lyndon Johnson — score high. Decades where policymakers focused on growth before equality, such as the 1920s, fare poorly. Decades about which social-justice advocates aren’t sure what to say — the 1970s, say — simply drop from the discussion. In the same hierarchy, federal debt moves down as a concern because austerity to reduce debt could hinder redistribution. Lately, advocates of economically progressive history have made taking any position other than theirs a dangerous practice. Academic culture longs to topple the idols of markets, just as it longs to topple statutes of Robert E. Lee.
But progressives have their metrics wrong and their story backward. The geeky Gini metric fails to capture the American economic dynamic: in our country, innovative bursts lead to great wealth, which then moves to the rest of the population. Equality campaigns don’t lead automatically to prosperity; instead, prosperity leads to a higher standard of living and, eventually, in democracies, to greater equality. The late Simon Kuznets, who posited that societies that grow economically eventually become more equal, was right: growth cannot be assumed. Prioritizing equality over markets and growth hurts markets and growth and, most important, the low earners for whom social-justice advocates claim to fight. Government debt matters as well. Those who ring the equality theme so loudly deprive their own constituents, whose goals are usually much more concrete: educational opportunity, homes, better electronics, and, most of all, jobs. Translated into policy, the equality impulse takes our future hostage.
Amity Shlaes, “Growth, Not Equality”, City Journal, 2018-01-21.
April 8, 2020
If the Wuhan Coronavirus panic feels oddly familiar … there’s a good reason for it
Warren Meyer explains why his skepticism about the dangers of the Wuhan Coronavirus epidemic kicked in quickly because it followed a very familiar pattern:
I have been skeptical about extreme global warming and climate change forecasts, but those were informed by my knowledge of physics and dynamic systems (e.g. feedback mechanics). I have been immensely skeptical of Elon Musk, but again that skepticism has been informed by domain knowledge (e.g. engineering in the case of the hyperloop and business strategy in the case of SolarCity and Tesla). But I have no domain knowledge that is at all relevant to disease transfer and pathology. So why was I immediately skeptical when, for example, the governor of Texas was told by “experts” that a million persons would die in Texas if a lock-down order was not issued?
I think the reason for my skepticism was pattern recognition — I saw a lot of elements in COVID-19 modelling and responses that appeared really similar to what I thought were the most questionable aspects of climate science. For example:
- We seem to have a sorting process of “experts” that selects for only the most extreme. We start any such question, such as forecasting disease death rates or global temperature increases, with a wide range of opinion among people with domain knowledge. When presented with a range of possible outcomes, the media’s incentives generally push it to present the most extreme. So if five folks say 100,000 might die and one person says a million, the media will feature the latter person as their “expert” and tell the public “up to a million expected to die.” After this new “expert” is repetitively featured in the media, that person becomes the go-to expert for politicians, as politicians want to be seen by the public to be using “experts” the public recognizes as “experts.”
- Computer models are converted from tools to project out the implications of a certain set of starting hypotheses and assumptions into “facts” in and of themselves. They are treated as having a reality, and a certainty, that actually exceeds that of their inputs (a scientific absurdity but a media reality I have observed so many times I gave it the name “data-washing”). Never are the key assumptions that drive the model’s behavior ever disclosed along with the model results. Rather than go on forever on this topic, I will refer you to my earlier article.
- Defenders of alarmist projections cloak themselves in a mantle of being pro-science. Their discussions of the topic tend to by science-y without being scientific. They tend to understand one aspect of the science — exponential growth in viruses or tipping points in systems dominated by positive feedback. But they don’t really understand it — for example, what is interesting about exponential growth is not the math of its growth, but what stops the growth from being infinite. Why doesn’t a bacteria culture grow to the mass of the Earth, or nuclear fission continue until all the fuel is used up? We are going to have a lot of problem with this after COVID-19. People will want to attribute the end of the exponential growth to lock-downs and distancing, but it’s hard to really make this analysis without understanding at what point — and there is a point — the virus’s growth would have turned down anyway.
- Alarmists who claim to be anti-science have a tendency to insist on “solutions” that have absolutely no basis in science, or even ones that science has proven to be utterly bankrupt. Ethanol and wind power likely do little to reduce CO2 emissions and may make them worse, yet we spend billions on them as taxpayers. And don’t get me started on plastic bag and straw bans. I am willing to cut COVID-19 responses a little more slack because we don’t have the time to do elaborate studies. But just don’t tell me lockdown orders are science — they are guesses as to the correct response. I live in Phoenix where it was sunny and 80F this weekend. We are on lockdown in our houses. I could argue that ordering everyone out into the natural disinfectant of heat and sunlight for 2 hours a day is as effective a response as forcing families into their houses (initial data, though it is sketchy, of limited transfer of the virus in summertime Australia is interesting — only a small portion of cases are from community transfer. By comparison less than a half percent of US cases from travel).
March 27, 2020
The Wuhan Coronavirus sucks, our data on it sucks … but our media suck most of all
The all-hysteria, all the time media will have much to regret once the worst of the Wuhan Coronavirus epidemic has run its course:
- The data we have sucks, and thus any conclusions we are drawing mostly suck too. The data is worse than just being incomplete or bad — if it was randomly distributed, we could live with that. But the lack of test kits and how we have deployed the few we have means that the data is severely biased. We are only testing people who are strongly symptomatic. If there is a normal distribution of outcomes from this disease, we are only testing on the right side of the distribution. We have no idea where the median is or how long the tail is to the left side of asymptomatic outcomes. The only thing we absolutely know about the disease is its not as deadly as the media is portraying as we are missing hundreds of thousands of cases in the denominator of the mortality rates. The media has also been terrible about reporting on risk factors of those who died. When a bunch of people died suddenly in Seattle, one had to read down 5 paragraphs into the story to find that they were all over 70 in an old-age home. Or when prime-of-life people die, facts such as their being type 1 diabetics — a known severe risk factor for this virus (and one that makes it different from the flu) are left out.
- The media is constantly confusing changes in measurement technique and intensity with changes in the underlying progress of the virus itself. Changes in case numbers have as much to do with testing patterns and availability than they do with the real spread of the disease.
- While COVID-19 is likely worse than the normal flu, our perceptions of how much worse are strongly affected by observer bias. Frankly, if every news broadcast every night spent 15 minutes reciting flu deaths each day, we would all be hiding in our homes away from flu. They present a healthy man in his thirties dying clearly as the tragedy it is, but the spoken or unspoken subtext is, “this is abnormal so this thing is much worse.” But it seems abnormal because we do not report on the very real stories of healthy young people who die of the flu. My nephew who was 25 years old and totally healthy with no pre-existing conditions died of the flu last month — and no one featured this tragedy on the national news.
- The data we are getting sucks worse because the media has decided, as one big group, that for our own good they are going to limit all facts about the virus to only the bad ones. There is a strong sense — you see it on Twitter both in Twitter’s policies as well as Twitter group attacks — that saying anything that might in any way reduce one’s fear of the disease should be banned for our own good. One of the more prominent examples was Medium removing an article NOT because it was proven wrong but because it took one side of a very open question and it was obviously decided it was “unsafe” to allow that side to even be aired.
March 20, 2020
QotD: Absolute and relative poverty
That the poor of our nation live better than 90 percent of anyone only 100 years ago, better than anyone at all from more than 200 years ago, shows just how fabulous an economic system it is.
Sure, it’s not perfect, it could do with some revisions here and there, but this system — the rule of law, markets, and capitalism — delivers in the one thing that truly matters: raising the living standards of the people, most especially poor people. Even more, no other economic system has managed this at all.
Tim Worstall, “Appalachia’s woes show the success of American capitalism”, Washington Examiner, 2018-01-09.
March 5, 2020
“Maybe … Trump’s victory caused an unusual number of spontaneous abortions in Ontario”
Colby Cosh on the recently published findings of a p-hacking conspiracy study on how the election of President Donald Trump was reflected in the birth ratio of liberals in Ontario:
Front view of Toronto General Hospital in 2005. The new wing, as shown in the photograph, was completed in 2002.
Photo via Wikimedia Commons.
On Monday there came a surprising piece of science news from BMJ Open, an open-access title affiliated with the British Medical Journal. It seems two researchers from Mount Sinai Hospital in Toronto, an endocrinologist and a statistician, have convinced themselves that the election of Donald Trump to the American presidency in November 2016 had a nerve-shattering effect on Ontario. The province of Ontario, that is, not the Los Angeles suburb.
Trump’s victory, according to the researchers, was so awful that, like a war or a disaster, it briefly altered the sex ratio in live births in the province. This is, I should say, a fairly well-established effect of extreme social traumas. When mothers experience physiological stress, the uterine environment becomes less hospitable, and male fetuses, more vulnerable to such changes, become less likely to survive pregnancy. (This makes sense from a Darwinian standpoint, because girls are more valuable than boys in replacing population after a calamity.)
In 2020 nobody should need me to say that a cute, counterintuitive scientific “result” like this, appearing in the newspapers on literally the day of its publication, should be greeted with extreme skepticism. The sex ratio at birth, always expressed in medical literature as a ratio of boys to girls, tends to hover around 1.06 under natural circumstances. (Even in an advanced civilization, things even out within the age cohort over the next 20 years as the lads explore dirt bikes, rock fights, and roofs.)
The Mount Sinai researchers, Ravi Retnakaran and Chang Ye, had records of the sexes of all children born in Ontario from April 2010 to October 2017. Even in a place as large as Ontario, the ratio naturally bounces around randomly between 1.1 and 1.0, and there are seasonal effects that the duo corrected for.
There is no obvious signature of a Trump effect in a scatterplot of the adjusted data, which serves as a warning that the effect being claimed may be an artifact of analysis. But when you apply “segmented regression” using the same parameters as Retnakaran and Ye, you find that the (unadjusted) ratio dipped to 1.03 in March 2017, the fifth month after Trump’s win, and then climbed to 1.08 in June and July before reverting to the long-term norm.
February 15, 2020
Theodore Dalrymple on the death penalty
From the New English Review:
“Tombstone Courthouse State Historic Park” by August Rode is licensed under CC BY-NC-SA 2.0
I happened to read a book published in 1965, the year Britain legislated to end the death penalty, titled Murder Followed by Suicide, by the distinguished criminologist, D.J. West. For forty years up to that date, about a third of homicides had been followed by the suicide of those who committed them.
Most people who committed homicide followed by suicide were highly disturbed psychologically, if not outright mad. For example, in killing their families they imagined that they were saving them from a worse fate. They were not the kind of people who would be deterred by anything, including the death penalty.
Here was a natural experiment. I hypothesized that if the death penalty acted as a deterrent, the homicide rate would increase but the proportion of homicide followed by suicide, which in absolute numbers would remain more or less the same, would decrease. My friend, the criminologist David Fraser, looked at the actual figures and found that this was indeed the case. Some sane people who might otherwise be inclined to kill managed to control themselves knowing that they might be executed if they did.
For the death penalty to deter, it was not necessary for it to be applied in every case. Although the death penalty for murder was mandatory in Britain, it was commuted in nine cases out of ten. All that was necessary for it to deter was that execution was a real possibility. We shall never know whether the death penalty would have deterred even more if it had been applied more rigorously.
Does its deterrent effect, then, establish the case for the death penalty, at least in Britain? No, for two reasons. First, effectiveness of a punishment is not a sufficient justification for it. For example, it might well be that the death penalty would deter people from parking in the wrong place, but we would not therefore advocate it. Second, the fact is that in all jurisdictions, no matter how scrupulously fair they try to be, errors are sometime made, and innocent people have been put to death. This seems to me the strongest, and perhaps decisive, argument against the death penalty.
Against this might be urged the undoubted fact that some convicted murderers who have been spared death have gone on to kill again, and this will continue to be so. Victims of those who murder a second time are probably more numerous than those executed in error. Therefore, utilitarians might argue, even if mistakes are sometimes made, that the death penalty overall would save lives. (Let us disregard the fact that those murderers who go on to murder a second time would not necessarily have been executed after their first murder, for nowhere are all murderers executed.)
The argument holds only if utilitarianism is accepted as a true ground of ethics. But few of us would accept that it is. It might be that hanging the wrong person after the commission of a terrible crime would have a better social outcome than hanging no one at all, provided only that it was never publicly known that the wrong person had been hanged: but we would still be horrified at the prospect. Moreover, in practice, the execution of the innocent, once it is known, serves disproportionately to undermine faith in the justice system. And surely it is true that for the state to kill an innocent man is peculiarly horrific.
February 13, 2020
Here’s a deceptive factoid … time for you to get angry to suit someone’s political agenda
Did you know that “Three Billionaires Have More Wealth Than Half of America”!!!???!!! Are you angry now? You’re supposed to be, because this factoid was concocted specifically to make people irrationally angry. Daniel C. Jensen explains how this sound bite was created:
Amazon’s Jeff Bezos, Microsoft’s Bill Gates, and Berkshire Hathaway’s Warren Buffet.
Fox Business.
People between 0 and 24 years of age account for about 32 percent of the United States population of 320 million. Almost all of them are going to be in the bottom half of the wealth distribution for reasons including diaper rash and puberty. That means they account for about 63 percent of the “bottom half of the wealth distribution.” Should it surprise us that some kid fresh out of college does not “hold any stocks or bonds”? Or a kid fresh out of the womb?
Then we must consider people with mental and physical disabilities. They will also tend to be in the bottom half of the wealth distribution because they face greater challenges to building wealth. “About 56.7 million people — 19 percent of the population — had a disability” at last count, according to the United States Census Bureau. But there is overlap between the disabled 19 percent and the young 32 percent of the population. If we assume disabilities are evenly distributed in the population, then young people and non-young disabled people account for 45 percent of the population. So we have now accounted for 90 percent of the “160 million Americans in the bottom half of the wealth distribution.”
Next, we must think about other groups who have had limited wealth-building opportunities. What about the 2.2 million people in jail and prison? What about people in their late twenties who pursued PhDs, law degrees, medical residencies, etc., and are just beginning their careers? Now we are close to accounting for 100 percent of the “bottom half of the wealth distribution.” But this wealth distribution is not what any sensible person would expect it to be.
Maybe the factoid is true. Maybe Jeff Bezos, Bill Gates, and Warren Buffet have more wealth than all of the infants, children, students, handicapped, prisoners, and postgrads combined. But you don’t need a PhD to figure out that’s not useful knowledge. Even if the factoid is true, it’s deceitful. Whoever created it was obviously trying to manipulate people. And we uncovered this deception with nothing but some simple knowledge of the US population.
Next time you encounter an economic factoid, remember that it might be pitting a bunch of newborns against Jeff Bezos, and that hardly seems fair. Thankfully, you can save those babies from certain defeat simply by knowing some basic statistics about your country.
February 1, 2020
Trudeau government’s unwillingness to define what they mean by “middle class”
The phrase has taken on almost an Alice in Wonderland quality for Justin Trudeau and his recently created “Minister of Middle Class Prosperity”:
“When I use a word,” Humpty Dumpty said in rather a scornful tone, “it means just what I choose it to mean — neither more nor less.”
“The question is,” said Alice, “whether you can make words mean so many different things.”
“The question is,” said Humpty Dumpty, “which is to be master — that’s all.”
It could be addressed, says Chris Selley … and really should be:
In the meantime, the Liberals have another problem. It is far less important than Iran or China, but it’s also far more embarrassing than either, because it is entirely of their own making and so easily fixed. It is as follows: Trudeau has given Ottawa MP Mona Fortier the new cabinet title of “Minister of Middle Class Prosperity,” but no one in the government has yet bothered to define “middle class.” And everyone is laughing at them.
Mona Fortier, Minister of Middle Class Prosperity and Associate Minister of Finance.
© HOC-CDC. Photo by Christian Diotte, House of Commons Photo Services, November 2019.Fortier has tried to explain herself. “We have to make sure we represent the realities in a rural, remote or even urban setting, (and) regional differences,” she told CTV upon her appointment. “The income required to attain a middle-class lifestyle can vary greatly based on Canadians’ specific situation,” she told the same network this week.
She’s right! Pack up your middle-class lifestyle in Small Town A, and you might well not recognize it when you unpack in Big City B. The thing is, though, statisticians — including scores of them in the federal government’s employ — are across this. They know very well that a Canadian dollar does not purchase the same quantity of goods and services in every part of the country, and they have all sorts of ingenious ways to compensate.
If it were true that “middle class” can’t be defined because it connotes different things in different places, then the same would go for “poverty.” But Canada has never had any problem defining poverty on a relative basis. And in 2018, this very Liberal government adopted an absolute measure of poverty as well: the Market Basket Measure, which estimates the cost of “a modest standard of living” in any given place, and calculates how many of us can’t afford it.
So the “poverty line” in Small Town A is not the same as it is in Big City B, and … sorry, this very simple concept doesn’t need to be explained to National Post readers any further. The point is, defining poverty was a good thing. Defining the middle class obviously doesn’t matter as much, but since this government seems utterly obsessed with it — and with evidence-based policy! — there is no good reason for it not to do likewise.
