I want to congratulate Adam Morton and the folks in the Department of Political Economy at the University of Sydney for the success of their Progress in Political Economy blog.
And I’m flattered that the post on my “Utopia and the Critique of Political Economy” lecture is included in the Top 10 for 2016.
Special mention
The stock-in-trade of neoclassical economists, like Harvard’s Gregory Mankiw, is that free markets are the most efficient way of allocating scarce resources. Therefore, they spend a great deal of time celebrating free markets, and criticizing any kind of regulation of or intervention into markets.
Rent control is a good example, one that is taught to thousands of undergraduate students every semester. According to Mankiw, when governments establish price ceilings on rental housing, they cause a shortage of rental units. In the short run (as in the chart on the left above), when the supply of rental housing is fixed, the shortage may be relatively small. But in the long run (as in the chart on the right above), when both the supply of and the demand for rental housing are more “elastic” (that is, more sensitive to changes in price), the shortage grows.
When rent control creates shortages and waiting lists, landlords lose their incentive to respond to tenants’ concerns. Why should a landlord spend money to maintain and improve the property when people are waiting to get in as it is? In the end, tenants get lower rents, but they also get lower-quality housing. . .
In a free market, the price of housing adjusts to eliminate the shortages that give rise to undesirable landlord behavior.
That’s the world according to neoclassical economic theory. And in reality?
Philadelphia, the City of Brotherly Love—aka the nation’s poorest big city, and among the most racially segregated—according to Caitlin McCabe [ht: ja], “is increasingly becoming a renter’s haven.”
But what happens when too many renters, many of them higher-income, flood the market?
In cities such as Philadelphia, lower-income residents feel the squeeze. And it could be getting worse for them
A new study by the Federal Reserve Bank of Philadelphia shows that, as a result of gentrification, Philadelphia lost one-fifth of its low-cost rental-housing stock—more than 23,000 units renting for $750 a month or less—between 2000 and 2014.
Even more, the study found, the affordable housing that remains in the city is in danger, too—
since 20 percent of the city’s federally subsidized rental units will see their affordability restriction periods expire within the next five years. Of these rental units, more than 2,300 are in gentrifying neighborhoods.
The short-term result of gentrification and the loss of low-cost rental housing is that Philadelphia is now the fifteenth-most-expensive rental city in the nation, with a median rent (for a one-bedroom apartment) of $1,400. In the long run, the shrinking stock of affordable housing leaves lower-income renters saddled with higher rent burdens, greater financial distress, and insecure housing arrangements, which combine to reinforce residential patterns that are already highly segregated by income and socioeconomic status.
As the Philadelphia Fed explains,
The pockets of gentrification in Philadelphia appear to reinforce these patterns in several ways. First, gentrifying neighborhoods become less accessible to lower-income movers, limiting their housing search to more distressed and less central neighborhoods. Vulnerable residents who remain in these upgrading neighborhoods often face higher housing costs and are less likely to see improvements in their financial health. In addition, vulnerable residents in neighborhoods that are in more advanced stages of gentrification may even become more likely to move out of these neighborhoods. Each of these consequences of gentrification reflects the impact of increasingly burdensome housing costs, driven by losses of both low-cost rental units and units with subsidized affordability.
The market for rental housing in Philadelphia is increasingly becoming a neoclassical economist’s dream—but a nightmare for low-income renters in the City of Brotherly Love.
Special mention
It sure looks like a recovery: consumer confidence, corporate profits, and the stock market are all up. Way up over their Great Recession lows, as is clear from the chart above.
But the U.S. Conference of Mayors [ht: ja] is also reporting an increase in the demand for emergency food assistance. Forty-one percent of surveyed cities reported that the number of requests for emergency food assistance increased over the past year, while 71 percent of the cities reported an increase in the number of people requesting food assistance for the first time.
From the report (pdf):
Increased requests for food assistance were accompanied by more frequent visits to food pantries and emergency kitchens. Forty-one percent reported an increase in the frequency of visits to food pantries and/or emergency kitchens each month. . .
When asked to identify the three main causes of hunger in their cities, 88 percent named low wages; also 59 percent said high housing costs and poverty. Forty-one percent cited unemployment and 23 cited medical or health costs.
Since the end of the recession, wage increases (almost 23 percent, in nominal terms) have not been able to keep pace with the increase in rental rates for housing (which are up 26 percent).
And the situation is even worse for extremely low-income households, according to the National Housing Trust Fund (pdf). The more than 10 million extremely low-income households accounted for 24 percent of all renter households and 9 percent of all U.S. households—and they face a shortage of more than 7 million affordable rental units. Thus, 75 percent of extremely low-income households are severely cost-burdened, spending more than half of their income on rent and utilities. And that means they don’t have enough money left over for food.
Which is why cities across the country, from Charleston to Seattle, have had to increase the amount of food they distribute—7 years into the so-called recovery.
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When it comes to artificial intelligence and automation, the current White House seems to want to have it both ways.
On one hand, it warns about the potentially unequalizing, “winner-take-most” effects of the economic use of artificial intelligence:
Research consistently finds that the jobs that are threatened by automation are highly concentrated among lower-paid, lower-skilled, and less-educated workers. This means that automation will continue to put downward pressure on demand for this group, putting downward pressure on wages and upward pressure on inequality. In the longer-run, there may be different or larger effects. One possibility is superstar-biased technological change, where the benefits of technology accrue to an even smaller portion of society than just highly-skilled workers. The winner-take-most nature of information technology markets means that only a few may come to dominate markets. If labor productivity increases do not translate into wage increases, then the large economic gains brought about by AI could accrue to a select few. Instead of broadly shared prosperity for workers and consumers, this might push towards reduced competition and increased wealth inequality.
But then it invokes, and repeats numerous times across the report, the usual mainstream economists’ nostrums about the “strong relationship between productivity and wages”—such that “with more AI the most plausible outcome will be a combination of higher wages and more opportunities for leisure for a wide range of workers.”
Except, of course, historically that has not been the case—certainly not in the United States.
For example, from the early 1970s to the present, workers’ wages have not kept pace with increases in productivity. Not by a long shot. As is clear from the chart above, productivity since 1973 has risen much more than workers’ compensation—72.2 percent, compared to a paltry 9.2 percent.
And while over the same period hours worked have in fact fallen, the decrease in the United States (a minuscule 5.6 percent) has been far less than the increase in productivity—and much less than in other countries, such as France (24 percent) and Germany (27.3 percent).
So, yes, whether the use of artificial intelligence leads to improvements for U.S. workers—in the form of higher wages and fewer hours worked—”depends not only on the technology itself but also on the institutions and policies that are in place.”
But the experience of the past four decades suggests it will not benefit the American working-class.
And there’s nothing to suggest that trend won’t continue—unless, of course, there is a radical change in economic institutions and policies, which allow workers to have much more of a say in the technologies that are adopted and how wages and hours are set.
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