Category Archives: economic growth

Rewarding Merit Is The Key To Growth

21 Monday Jun 2021

Posted by in economic growth, Meritocracy, Redistribution

≈ Leave a comment

Tags

, , , , , , , , , , , , , ,

Outward trappings of success, even at very modest levels, are seldom durable or predictive of future achievement if not backed by actual performance. That’s one reason why redistributionist policies are so unsuccessful at fostering upward mobility. They fail by focusing on outcomes rather than on addressing more fundamental causes, like skills, training, and well-functioning markets for low-skill labor. The same applies to programs that prescribe quotas on admissions, tuition aid, and hiring. The beneficiaries of these programs are often placed into situations in which they are unprepared. This makes them vulnerable to stigmatization and ultimately failure. And when poor performance is in any way ignored or forgiven, it has an impact on the psyche of the individual and their reputation, and it creates losses to the rest of society.

On the other hand, conditions and policies that lead to economic growth are likely to benefit the lower strata of society and minorities, to the extent that minorities are more concentrated in lower income quantities than non-minorities. We know incentives always matter, and incentives rely on the ability of individuals to act and succeed. Success implies gains to others who have occasion to avail themselves of the individual’s efforts. They are offering rewards for merit! Furthermore, those offers are always increasing in the value created, and thus, in levels of accomplishment. In that way, individuals always have opportunities to strive for growth.

But none of that works unless meritocracy holds sway. LittlBut none of that works unless meritocracy holds sway. Little wonder that meritocracy is so closely tied to a society’s prosperity, as documented in this article and a forthcoming book by Adrian Wooldridge. John Cochrane provides an excellent review and critique of Wooldridge’s thesis along with several lengthy quotes.

Wooldridge disputes the widely-accepted theory that democracy is a determinant of economic growth (also see here), noting that democracy can create economic pitfalls related to majoritarian excesses, whereas merit-based systems of rewards are common to almost all successful economies, including autocracies (Singapore, China) and democracies/republics (the U.S., Japan, Scandinavia), irrespective of the size of government. He offers examples of countries in which meritocratic systems are weak but nepotism or political “clientelism” are strong, with unfortunate results (Greece, Portugal, Italy). You certainly won’t get efficient outcomes when leaders prioritize family, friends, cronies, and political contributors for plum jobs and other rewards.

Of course, there is no pure meritocracy in the world. Rather, there are varying degrees of meritocracy across different societies. Traditionally, the U.S. economic system has relied on merit to a great extent; returns to merit are largely a matter of equal opportunity, though not entirely. Equally talented individuals do not always have access to the same opportunities. In fact, that is the major point of attack against the concept of meritocracy, but it does not imply that the benefits of meritocracy are a myth. There are many institutional dysfunctions that can and should be fixed to overcome the kinds of problems cited by critics, primarily public education, but the old expression “don’t throw the baby out with the bathwater” seems especially apt.

In fact, meritocracy promotes upward mobility. Here is Cochrane on the great paradox underlying the backlash against meritocracy:

“The US paternalistic/aristocratic elite is running away from meritocracy under the banner of ‘social justice’ and ‘racial equity.’ Yet meritocracy throughout history has been a great equalizer, a great leveler, the main way that excluded out-groups could get ahead.”

And on this point, Cochrane quotes Wooldridge:

“… Meritocracy is one of the great building blocks of modernity, along with democracy, capitalism and liberalism. … Is it really the case that meritocracy is a tool of White male privilege? W.E.B. Du Bois and Ruth Bader Ginsburg might have something different to say. Are lotteries or holistic assessments really better ways of distributing educational opportunities than standardized tests? Most of us would hesitate before flying with a pilot who had been chosen by lottery. Do we really want a society in which group identities trump individual abilities? “

To give the critics their due, however, a more refined version of their argument is that “meritocracy is a myth without inclusion”. Fair enough, but again, any shortfall in participation is not the fault of meritocracy per se, but of underlying conditions and policies fostering substandard education, family instability, high crime and incarceration rates, and high rates of unemployment among those with low skills.

An important strand of Wooldridge’s work is the implication that meritocracy is a redeeming feature of some autocratic regimes. Indeed, Wooldridge is not the least bit skeptical that autocratic rule is sustainable, just as long as merit drives rewards. This is a point on which Cochrane differs. An autocracy in which high echelons are populated by the meritorious will constantly grapple with temptations of the powerful to reward their pals. Lines of accountability must be all the stronger to prevent such decay. Furthermore, autocracy usually weds itself to meritocracy only in a conditional sense. For example, in China, one must support the party. These restraints undermine the benefits of meritocracy by offering less autonomy for individuals to leverage their talent.

“Pure” democracy has its own drawbacks, b“Pure” democracy has its own drawbacks, but at least leaders have autonomy while being accountable to a broader class. And as Cochrane says, the greatest dangers of democracy can be addressed under representative democracy along with other means of protecting minorities and individual rights.

The effort to banish meritocracy is madness and the product of a totalitarian mindset. To speak of the “illusion” or “myth” of meritocracy is to contend that talent, preparedness, sound decision-making, workmanship, precision, effort, and value-delivered represent trickery of some sort. Such is the viewpoint of those who take human well-being to be a zero-sum game. But it’s even worse than that. For example, placing lives in the hands of “randomly selected” pilots would invite catastrophe, and while that example is extreme, it clearly illustrates how non-meritocratic approaches are likely to produce negative sums! Putting resources into the hands of individuals with lesser qualifications is always a prescription for waste. Make no mistake: the road to serfdom is well-traveled and can be a very quick trip. Abandoning merit-based rewards would get us a fast start.

Joe’s “Boom”: Mendacity or Memory Loss?

06 Tuesday Oct 2020

Posted by in economic growth, Executive Authority

≈ Leave a comment

Tags

, , , , , , , , , , , , ,

Joe Biden has claimed that he and Barack Obama had left Donald Trump with a “booming” economy to start his term in office. Of course, if he had anything to do with economic performance during the Obama Administration, it may have been his oversight of the mismanaged and ineffective “shovel-ready” stimulus program of 2009, For his sake, one might hope (and suspect) his oversight was nominal. In any case, his characterization of the Obama economy is not really accurate, as this editorial at Issues and Insights demonstrates. I could argue with a few of their points, but the thrust of it is correct. The economy weakened in 2015 and 2016, and expectations were for continued slow growth or possibly a recession in 2017 or after. At that point, many economists thought the aging expansion might be on its last legs. But economic growth exceeded expectations after Trump took office. As for job growth, economists predicted relatively sluggish growth in 2017-2019, but actual job growth exceeded those projections by more than three times.

Finally, Biden’s assertion that “Trump caused the recession” was laughable, especially when the punchline is his willingness to “shut down the economy“! He insists “I would listen to the scientists”, presumably the same knuckleheads who don’t understand the public health tradeoffs between the pandemic itself and lockdown risks (and who don’t understand the Constitution). Biden might not understand that the President lacks constitutional powers to demand a nationwide shutdown. Trump was quite sensibly persuaded to leave non-pharmaceutical interventions in the hands of the private sector as well as state and local governments, with guidance from federal health authorities. That some state and local leaders instituted draconian policies, which were largely ineffective and often damaging. was and is a terrible misfortune. The more sensible approach is to  protect the most vulnerable and allow others to gauge their own risks, as we always have in earlier pandemics.

Coronavirus “Framing” Update #4

13 Monday Apr 2020

Posted by in economic growth, Pandemic

≈ 2 Comments

Tags

, , , , , , , , , , , ,

It’s beginning to look like we’ve turned a corner in mitigating the spread of the coronavirus. I hope I’m not speaking too soon.

It’s time to update some of the charts and thoughts about where the epidemic is trending in the U.S. Here’s the first of these “framing” posts I published on March 18th. The last update from about a week ago is here. The demand for tests seems to be tapering a little, and the percentage of tests that are positive has leveled and even dropped a bit. The number of confirmed cases continues to mount, but the daily increases are slowing, as is the growth rate of the cumulative count. Finally, the daily increase in the number of deaths is also slowing, and total deaths have risen more slowly than one prominent model predicted on the date at which I chose to “freeze” it for my own expositional purposes: April 2. The charts appear further below.

The epidemiological modelers have taken a real beating from many observers as their estimated virus growth curves have shifted downward. Their initial projections were way too high, and they have continued to overshoot in subsequent model revisions. In fairness, however, they didn’t have a lot to go on during the early stages of the pandemic, and conservatism was probably seen as a must. The variety and extent of mitigation measures was also an unknown, of course.

I build “event” models for a living, though the events I study are economic and are obviously much different kinds of risks than coronavirus infection. I seldom face situations in which so little historical data is available, so I can appreciate the modeling challenge presented by Covid-19: it was pretty close to an unwinnable situation. Nevertheless, until recently the projections were outrageously high. There comes a time when accurate, rather than conservative, projections are demanded. The confidence intervals produced by the modelers are really not worthy of the name. Partly on that basis, a very recent paper gave the model produced by the Institute for Health Metrics and Evaluation very poor marks (IMHE, which I called the Murray Model last week):

“In excess of 70% of US states had actual death rates falling outside the 95% prediction interval for that state…”

That’s nothing short of pathetic.

That brings me to the “framing” exercise I’ve been performing for nearly four weeks. It is not a modeling exercise. The “very good” and “pretty bad” scenarios I charted for the confirmed Covid-19 case count in the U.S. were not intended as confidence intervals except perhaps in spirit. The intent was to provide perspective on developments as they unfolded. Where to place those bounds? They were based on multiples of the Italian experience (pretty bad) and the South Korean experience (very good) as of March 18, normalized for U.S. population. Here’s the latest version of that chart, where Day 1 was March 4th:

The curve may be just starting to bend to the right. Let’s hope so. The daily growth rate of new cases has dropped below 5%. Below, it’s clear that the daily count of new confirmed cases plateaued in early April, and the last few days show an encouraging reduction.

I also think it’s telling that after a few weeks of “excess demand” for tests, demand seems to be falling. The chart below showed the sharp reduction in the “pending test” count about a week ago. It corresponded with the spike in daily tests, which have stabilized since then and may be trending down (lower panel).

The next chart shows that the cumulative share of tests with a positive diagnosis has flattened. The lower panel hints at a taper in the daily share of positive tests, which would be welcome. However, I do not necessarily expect that percentage to decline too much if the number of tests continues to fall. In fact, more testing will almost certainly be required in order to “restart” the economy. Then, we should see a reduction in the percentage of positive tests if all goes well.

The last chart highlights the IMHE model discussed above. The chart extends from March through June, though the unlabeled date axis is not cooperating with me. The mean model prediction of U.S. cumulative deaths attributed to Covid-19 is shown in red. The upper and lower bounds of the confidence interval are the blue and green lines. Again, I “froze” this forecast as of April 2 to serve as another “framing” device. Actual deaths are traced by the black line, which goes through April 13th. It is trending below the mean forecast, and IMHE has reduced their mean forecast of the death toll by about a third since April 2nd (to 60,000). Actual deaths may well come in below that level.

I hope my optimism based on these nascent developments is not unwarranted. But they are consistent with state-by-state reports of more positive trends in the data. It is time to start planning for a return to more normal times, but with a new eye toward mitigating risk that will probably involve isolating vulnerable groups when appropriate, more work at home, widespread testing, and a few other significant changes in social and business practices. It remains to be seen how easily certain industries can return to previous levels, such as hospitality, or how soon crowds can return to sporting events, concerts, and theaters. That might have to await greater levels of “herd immunity”, an effective vaccine, and fast testing.

The Opportunity of Skewed Coronavirus Transmission

30 Monday Mar 2020

Posted by in economic growth, Pandemic

≈ 1 Comment

Tags

, , , , , , , , , , , , , , , , , ,

People talk about the transmission rate or reproduction rate (R0) of Covid-19 as if it’s a single number that applies to the entire population. John Cochrane emphasizes the huge implications of this misperception for how best to prevent the spread of the virus, and at lower cost, and for how best to “restart” the economy.

First, however, lets dispense with the absolutist position that there can be no compromise on virus mitigation in favor of economic activity. I am not opposed to the “lockdown” we are now living, but it will have significant and unnecessary costs if it goes on too long: the lost output is a huge blow not only to our current lifestyles but to our ability to grow in the future, or even to afford better health care in the future. Beyond that, the lockdown has immediate negative impacts of its own on public health: economic stress leads to all kinds of terrible health outcomes like heart disease and even suicide. About the latter, the President is absolutely correct: if you need research to prove it, see here, here, here, and here, all respected journals (the links all courtesy of The Federalist.) Economic stress and isolation is quite likely to promote poor dietary habits, lethargy, and possibly family dysfunction as well. Don’t pretend there aren’t real tradeoffs between the economy, virus interventions, and public health. The trick is to improve those tradeoffs. A balance can and must be struck, and depending on policy actions, the tradeoff can be made better or worse.

Back to the virus reproduction rate: the R0 values we see quoted are estimates of the average number of other people infected by each infected person. A value of three means that each person infected with the virus passes it on to three others, on average. If R0 is greater than one, an epidemic grows. If R0 is less than one, a contagion recedes. It becomes a “non-epidemic” if R0 remains less than one. It does not have to be zero (and probably cannot be zero).

But not everyone is the same: my R0 is different from your R0 if only because we have different occupational exposure to others and different levels of social engagement. We also differ physiologically, which probably leads to differences in our “personal” R0 values. And an individual’s R0 will differ by time and place, depending on random circumstances like which way the wind is blowing. But here is where it gets interesting. Cochrane describes an extreme version of the skewed distribution shown at the top of this post:

“Suppose there are 100 people with a 0.5 reproduction rate, and 1 super-spreader with a 100 replication rate. The average reproduction rate is 1.5. Clearly, locking everyone down is wildly inefficient. It’s much more important to find the 1 super-spreader and lock him or her down, or change the business or behavior that’s causing the super-spreading.

This is exaggerated, but not far off the mark. I have not seen numbers on the distribution of reproduction rates across people, but it is a fair bet that it has an extremely fat tail. Most of us are washing our hands, social distancing, work in businesses that are shut down or are taking great steps to limit contact. And a few people and activities contribute to most of the spread.

This wide and fat-tailed dispersion is ignored in a lot of simulations I’ve seen. They take the average reproduction rate as the same for everyone. That’s a big mistake.

The danger: we waste a huge amount of time and money moving you and me from a 0.5 reproduction rate to an 0.4 reproduction rate. …  The opportunity: focus on the super-spreaders, and the super-spreading activities, and you bring down the reproduction rate at much lower cost. “

There are many ways to reduce R0. Cochrane gets a little more specific about this and the policy implications of the skewed R0 distribution across individuals:

“All we need is to get the transmission rate under one. Activities with possible but very low transmission rates, and high economic benefits should go on. Don’t separate to ‘essential’ and ‘non-essential.’ Separate into ‘high likelihood of transmission’ and ‘low likelihood of transmission.’

Why are we not using masks everywhere? Sure, they’re not perfect. Sure, an old hankerchief might only cut the chance of transmission by half. We’re not all surgeons. Cutting by half is enough to stop the virus. 

Conversely, why did they close the state parks? Really? Just how dangerous is it to drive the dog to a hiking trail and stay 6 feet away from other people? Parks, ski areas, golf courses, all sorts of businesses that surely can be run with a reproduction rate far less than one are just shut down. I met a realtor on our dog walk yesterday. They’re totally shut down. Just how hard is it to run a realty business with a 0.5 reproduction rate? One family in the house at a time, don’t touch anything, an hour between showings, stay 6 feet from the realtor… But instead the whole business is just shut down.”

The beginning of that last paragraph echoes a point I made in my last post about public park closures and the health benefits of getting outside generally.

Cochrane goes on to discuss several other policy options, including the potential benefits of simple kinds of testing and the overemphasis on false negatives and positives in policy discussions. Imperfect tests should not be discouraged by these concerns. If you’re worried about that, you shouldn’t use a thermometer either!

“Stay-at-home” or “shelter-in-place” orders will increasingly be tested by private parties if they remain in effect too long. That will be encouraged by the seemingly arbitrary distinctions some orders make between “essential” and “non-essential” activities. If workers or small businessmen judge themselves to be at low risk, they will take matters into their own hands to the extent they can. I believe that’s already happening where the specifics of “lockdown” orders have gone too far.  Workers at the low end of the income spectrum are especially hard hit by these orders. One can hardly blame them for trying to earn what they can if they believe, and their customers believe, their activities and interactions are of low risk.

Ultimately, the entire distribution of R0s will slide to the left. That will occur even at low levels of “herd immunity” and anything that offers at least weak prophylaxis. Broadly speaking, the latter includes maintaining distance, refusing admittance to venues with a fever, avoiding handshakes, wearing masks, and potentially chloroquine, which is already in widespread use by physicians treating coronavirus patients. Ultimately, a vaccine will slide the distribution far to the left, but the economy need not be held hostage until that time. To paraphrase Cochrane, we can get the transmission rate below one and keep it there without stopping the world permanently. There are many options, and now is the time for business and government to start planning for that.

Not Obama’s Economy

01 Sunday Mar 2020

Posted by in economic growth, Macroeconomics

≈ Leave a comment

Tags

, , , , , , , , , , , , ,

The “Trump economy” hasn’t been half bad, though one can’t attribute all of the results to the economic policies of his administration. In fact, the economy was growing when he took office, though it took several years after the Great Recession to recover under Barack Obama, and various sectors were showing strains before Trump took office. And yes, Obama inherited a very bad economy, but he went off the rails a few weeks ago in a pathetic attempt to take credit for ten-plus years of economic growth. Here is one of his tweets:

“Eleven years ago today, near the bottom of the worst recession in generations, I signed the Recovery Act, paving the way for more than a decade of economic growth and the longest streak of job creation in American history,”

The tweet was immediately ridiculed by Trump, as is his habit, but at best Obama received lukewarm support from his usually adoring media outlets. How interesting, however, that just a few days before Obama’s tweet, Chuck Jones, a regular Forbes contributor who really needn’t prove he’s an Obama hack, submitted a scorecard of economic performance covering President Trump’s first three years in office. It was an exercise in throwing shade at a series of good numbers. Then, a week later, Jones had the chutzpah to claim the Obama’s “shovel-ready” stimulus program of a decade ago, which proved anemic in its effects, was the proximate cause of healthy growth under Trump’s watch. Who gave him that idea?

Jones’ effort to diminish Trump’s economic accomplishments is music to the ears of leftists wistful for the days of Obama. They fancy Jones’ appearance in what they assume to be a right-leaning outlet as an enhancement to the credibility of his claims. Forbes, however, is certainly not the bastion of conservatism the Left would have you believe. Their model pays contributors who drive circulation, which has little to do with political alignment. To the extent that Jones is able to stroke the predilections of the Left, he probably can play well at that game.

The truth is it’s difficult to attribute variations in economic growth to different presidential administrations. This fairly well-balanced piece at NPR.org gives one very simple reason:

“Let’s stipulate that presidents of both parties often get more credit and blame for economic conditions than they deserve, given that much of what happens is outside their control.”

It is true that a new administration inherits economic conditions and policies from its predecessor. Trump inherited an economy that was growing, but there were plenty of strains, including sluggish wage growth, low labor force participation, weak business startups, and a languid housing sector, as this link makes clear. Moreover, economic expansions have lasted an average of only about five years in the post-WW2 era. The current expansion was about 90 months running at the time of Trump’s inauguration, a stage at which vulnerabilities might develop. But new policies often lead to new economic realities. In Trump’s case, that included tax cuts, and especially corporate tax cuts that spurred hiring and wage growth, and more liberalized regulation. Accommodative monetary policy by the Federal Reserve also provided an assist. As the chart at the top shows, Trump’s platform lifted small business enthusiasm considerably, which is a broad indicator of economic vibrancy. Of course, his trade initiatives have probably had negative effects thus far, but his way of negotiating new trade agreements might well end up making a positive contribution, on balance.

Now, the danger of a caronavirus pandemic is presenting major economic challenges. It’s unlikely to produce as many deaths as a bad flu season in the U.S., in part because the Trump Administration took quick action to limit domestic exposure. Nevertheless, the economic consequences of the virus and attempts to control its spread will be significant. At least the economy was strong when the shock occurred, so it is reasonable to expect a rebound if the outbreak runs its course over the next month or two.

The economic record since Trump took office has been impressive given the stage of the business cycle at which he took office. Not only that, but minority wage growth has surged, and minority unemployment has fallen substantially. Let’s face it: Obama and Joe Biden are eager to neutralize any plaudits a strong economy might earn Trump in an election year, but they shouldn’t embarrass themselves by trying to take credit for it, and Chuck Jones could do better than carrying their water.