This article is going slightly viral: Talent Effects and Inequality
It’s as if he just discovered the Matthew effect. People who are rich and successful tend to become richer and more successful. For example, Jordan Peterson and Ben Shapiro, both of whom have seen their popularity surge in 2018, even after large gains in 2017. Jordan Peterson was already pretty famous in mid-2017, making $40k a month on Patreon; now he’s up to $80k at least, plus massive book sales and other income steams.
One way people become successful by finding exploits that give them a material advantage over their competition. In the early 2000’s, when Google was popular but much less regulated than it is now, it was possible to get really good rankings very easily by purchasing links. Businesses that exploited this loophole were able to, say, spend $150 on a link to rank for a keyword that would generate potentially thousands of dollars month in sales, such as mortgages, diet pills, or credit cards. Eventually, over many years, Google made adjustments to their algorithms that made link purchasing less effective and more costly; plus there was more competition.
At the individual level, one’s position in a hierarchy of competence tends to stay fixed. Kids who are ‘slow’ in elementary school tend to be slow (relative to their peers) for the rest of their lives. It’s not like slow learners suddenly become geniuses. Those who are smart learn quickly and surpass those who can’t pick up the subtleties. In my own experience in business, I have never seen or worked with a mediocre person who later became a super-star. Usually people who start out mediocre stay that way. But I’m not saying I’m special either. Consider writing and blogging. After doing this for years, I’m still mediocre and will likely remain that way, yet when it comes to making money online through cryptocurrencies, stocks, economic forecasting, and other stuff, I really excel. People who are exceptional don’t want to waste their time with mediocre people and don’t need their help, so the result is successful people pulling further away from the pack, as the incompetent stay stuck.
As for the article, online, Arnold KLing is held up as some sort of genius and really insightful economist, but he makes a lot of unsupported proclamations and generalizations based on anecdotal evidence and hunches. Neoclassical economics makes no assurances of equality. He’s conflating economics with sociology. The proliferation of large technology companies and the winner-take all nature of capitalism is not a repudiation of neoclassical economics.
If we still lived in a primarily industrial economy, dominated by tangible factors, then capital abundance would indeed benefit the mass of workers.
He cites no evidence of this. Workers benefit in terms of rising nominal wages and increased purchasing power, as well more utility from the stuff they buy. A century ago, a much larger percentage of a worker’s paycheck went into energy and food, and it took weeks of saving to buy stuff that we can buy on a whim today (such as TVs and phones). The decline of labor share of income is also not incompatible with neoclassical economics. The decline of workers’ share of wealth relative to executive/CEO wealth during the 90’s during the tech boom is an example of how everyone benefits, even if workers have a smaller share. Workers’ total income tends to be monotonically increasing, but the wealth of the top 1% is more volatile, as was evidenced during the crash of 2000-2003 and again in 2007-2010.
I would argue however that the permanent ascendance of large technology companies, financialization, and globalization have made business cycles a thing of the past. The 20th century was characterized by boom-bust cycles, but now, since 2009, we’re in a perpetual ‘boom’, and big tech companies such as Google and Microsoft keep getting bigger and bigger, and are occupying an increasingly dominant and important role in the global economy, and this provides an economically stabilizing effect (which helps explains why the post-2009 recovery has been so enduring). In that sense, economics is changing, but the assumptions of neoclassical economics remain true. This is more of a refutation of Austrian economics, specially the Austrian business cycle theory (ABCT).
But the 21st-century economy is dominated by intangible factors, including technical skills and managerial talent. The rise of computers and the Internet dramatically increased the economic power of elites in various fields, not all of which are technical. As a result, income and wealth have become more concentrated.
Ummm..except that wealth inequality was even greater at the turn of the 20th century, long before computers and the internet, as shown below:
Most people are actually at a relative economic disadvantage compared with where they would have been 25 years ago. (They may be better off in some absolute sense, but relative to the economic elites, the masses have lost ground.)
I agree, but this is due to IQ becoming increasingly important in today’s hyper-competitive, super-productive, technological, winner-take-all economy. IQ inequality is becoming tantamount to income inequality, and by the virtue of the normal distribution of scores, most people (those with IQs below at least 115) are at a disadvantage compared to 25 years ago when IQ was not as important. Not being smart enough is like bringing a spatula to a knife fight. Even though I support Trump, the low unemployment rate belies the fact that the labor force participation rate is at multi-decade lows and a lot of people who want to work are for various reasons unable to do so, often going on disability or dropping out. For the vast majority of jobs, the number of job seekers still vastly exceeds the number of opening. The media scours for some tiny rural town in the middle of nowhere where there are more openings than job seekers and then generalizes this as being representative of the entire country and economy. If you live in an urban area there is much more competition.
In a 1970’s-era automobile plant, introducing a new worker to the assembly line was easy. Getting the worker to be productive required very little managerial oversight and only brief communication with other workers. But Brooks pointed out that computer programming is different. Each new person on the project adds significantly to the burden of management and communication.
That doesn’t even make sense. By the author’s logic, the optimal number of employees is one, yet Google has 85,000 employees.
If you are trying to get a lot accomplished, are you better off with a small, elite team or with a large collection of average workers? Well, if you are trying to build a lot of cars using 1970’s technology, the large team of average workers will out-produce any small team of elite automobile assemblers. But in software, the small elite team is more likely to win. Hence, Amazon is known for its “two-pizza rule” of trying to keep software teams limited to the number of developers who can be fed with two pizzas.
But splitting workers into small teams does not imply fewer workers. It’s no different than an auto assembly line splitting workers into smaller shifts and tasks (one person may work on the paint, another on the engine, another on the installation of electronics, etc.) even though the factory may have thousands of workers.
Another characteristic of the post-industrial economy is that the most talented individuals tend to get better. Think of the virtuous cycle of a movie star. Because of her talent and reputation, she gets offered the best roles. This in turn allows her to improve her skills and enhance her reputation further.
Hans’t this always been the case? How it is unique to our post-industrial economy? I would argue that for the high-tech sector, especially social networking and software, the barriers to entry are exceptionally high due to intellectual property and network effects. Food stores, oil rigs, and car washes are interchangeable, but there is only one Microsoft, one Google, and one Facebook. This could explain why large tech companies are so stable and profitable, but energy, apparel, and retail are much more volatile and have smaller profit margins, due to more competition, less intellectual property, and lower barriers to entry. But like all things, there are exceptions. An example that immediately comes to mind is Myspace, which in 2007 had seemingly achieved a networking hegemony and was valued between $5-10 billion, only to be nearly worthless two years later due to the rise of Facebook and other factors.