Tag Archives: economics

The Minimum Wage and the Cost of Housing

Each year the Department of Housing and Urban Development (HUD) calculates the fair market rents for apartments throughout the U.S. in order to set standards for housing assistance payments and vouchers for Section 8. Using data from the Census and the American Community Surveys, HUD figures out the average cost for various sizes of apartments. You can easily look up data for fiscal year 2012 here.

The generally-accepted standard for affordable, sustainable housing costs is that they should be about a third of a household’s income. The National Low Income Housing Coalition recently released a report on the mismatch between minimum wage — currently set at $7.25 nationally, with some states and municipalities having higher minimum wages within their boundaries — and the standard of living. The NLIHC report included this map showing the hourly wage that would be required for the HUD-calculated fair market rent to be about 30% of a full-time worker’s income:

In no state does the minimum wage pay enough to hit the 30%-of-income standard of affordable housing costs. How many hours would a minimum-wage worker need to work per week to make enough that the fair market rent would be about a third of their income? A lot, from a low of 63 hours a week in West Virginia to a high of 175 in Hawaii:

Thanks to Dmitriy T.M. for the tip!

Housing Market Blues

Cross-posted at Reports from the Economic Front.

Economic recoveries often depend on the state of the housing market.  While an April increase in housing prices has led many analysts to talk of a housing recovery, U.S. home values still remain depressed.  According to a Zillow real estate research report, they are still some 25% below their 2007 peak.

Perhaps the most telling indicator of the state of the housing market is that, as of the first quarter 2012, 31% of all owner-occupied homeowners with a mortgage were “underwater,” which means they had a mortgage greater than the market value of their home. As the table below shows, these homeowners owed, on average, $75,644 more than what their home was worth.

To this point, the high percentage of underwater homeowners represents, in the words of Zillow, only “a potential danger.”  That is because “the majority of underwater homeowners continue to make regular payments on their mortgage, with only 10% percent of the 31% nationwide being delinquent.”  The following figure highlights the percent of delinquent/underwater homeowners in the largest metropolitan areas.

At the same time, as Zillow notes:

With nearly a third of the nation’s mortgaged homeowners in negative equity and the average underwater homeowner having a home value that is 31 percent lower than their mortgage balance, negative equity will prove both to be difficult to fully eradicate near-term and to have pernicious effects longer term as some households continue to encounter short-term financial trouble even with a slowly improving broader economy. Should economic growth slow, more homeowners will not be able to make timely mortgage payments, thereby increasing delinquency rates and eventually foreclosures.

In other words, if the economy slows, or interest rates rise, two very likely possibilities, the housing market could deteriorate quickly, intensifying economic problems.  In short, we are a long way from recovery.

The Prisoner’s Dilemma

The prisoner’s dilemma is a concept used to help explain situations in which individual actors may pursue their own self-interest even in situations where they would all be better off if they cooperated and acted for the good of the group. In this short video posted at Scientific American, Michael Moyer explains the prisoner’s dilemma puzzle and how it helps explain situations such as the global nuclear arms race:

See also: Game Theory and the Prisoner’s Dilemma.

Illustrating the Gender Pay Gap

While income inequality between the sexes has decreased in recent decades, women still only make seventy-seven cents for every dollar a man is paid. Matt Separa from the Center for American Progress illustrated what could be bought with those lost wages to help us conceptualize how wide the wage gap is.

His first chart shows how the $10,784 in underpaid wages would almost cover annual housing costs or could pay the combined costs of a year’s worth of utilities, food, transportation, and internet access with a few hundred dollars to spare. The lost wages could also almost pay all the expenses for annual in-state tuition at a public university, twelve months of contributions to Social Security, and basic medical care for a year:

His second chart illustrates how across a lifetime, the lost wages ($431,360) could buy two houses, seven degrees from public universities, fourteen cars, or pay for a family of four to eat for thirty-seven years.   Many of Spera’s examples, including real estate, tuition and retirement savings, are especially powerful because they show how the lost wages could be turned into capital and wealth that would pay even more dividends on top of the lost income:

Overall, the graphs do a nice job of making the implications of the gender wage gap concrete.

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Jason Eastman is an Assistant Professor of Sociology at Coastal Carolina University who researches how culture and identity influence social inequalities.

Student Loan Debt Now Exceeds 100 Billion. Why?

You’ve probably heard someone in media or politics bemoan the ballooning student debt in the U.S.  In fact, debt has been rising.  It’s more than doubled in the last ten years (that’s a more than 100% increase):
This debt, though, can’t be attributed primarily to the rising cost of education, as Planet Money explains.  The average debt load for a student graduating from a public school, for example, has risen by 20%:
The average debt load for a student coming out of a private school has gone up a bit more, but still not enough to account for the leap in overall student debt.
The increase in debt, it turns out, is largely accounted for by an increase in the number of people going to college.  In 1970, 8,500 8,500,000 people enrolled in college in the Fall; in 2009, that number exceeded 20,000 20,000,000 (source).  A more than 100% increase.

So, the story isn’t quite as dire as we might think.  This may be little consolation, though, for my students who walked across the stage yesterday.  Congrats, Seniors! :)

Lisa Wade is a professor of sociology at Occidental College and the co-author of Gender: Ideas, Interactions, Institutions. You can follow her on Twitter and Facebook.

Fastest Growing and Declining Occupations, 1983-2002

The National Bureau of Economic Research recently released a paper by  Emin Dinlersoz and Jeremy Greenwood about unionization in the U.S.. They argue that economic shifts that changed the relative prevalence of different types of occupations partially explain decreasing union membership.

So what occupations are growing, and which are declining? Jordan Weissmann, at The Atlantic, adapted two graphs from the NBER paper that illustrate larger economic changes. Of the twenty fastest-declining occupations (in terms of % decrease), many are factory or industrial production jobs — machine operators of various types fare especially poorly (also, sorry, fellow sociologists):

The color of the graph indicates the level of unionization for each occupation; blue = less than 20%, green = 20-40%, red = over 40%. Nine of these occupations were over 40% unionized; their decline means the loss of many decently-paid jobs that provided benefits to employees without high levels of formal education.

So which occupations are growing, then? Take a look (though note this reflect % change, not overall # of employees):

Notice that top category: numerical control machine operators. Those words reflect a profound shift in manufacturing in the U.S. Numerical control machine operators program and operate computerized machinery, which requires a very different type of human operation than the classic assembly line machinery did — less input of physical labor and more technical management and troubleshooting.

Many of the other fastest-growing occupations require specialized, and often lengthy, higher education or licensing: health-diagnosing practitioners, teachers, scientists, physical therapists, and dentists, for instance. And unionization is consistently low in these types of occupations, contributing to overall declines in the prominence of unions in the U.S. over time.

Changes in Federal Spending

NPR’s Planet Money blog posted this image showing changes in major categories of federal spending over the past 50 years. Notably, though defense spending (which includes veteran benefits) is still the largest category of federal spending, it’s a much smaller proportion of the total budget than it was in the ’60s; spending on interest on our debt has also fallen quite a bit since the ’80s. On the other hand, spending on Social Security, Medicare and Medicaid (which didn’t even exist in 1962), and safety net programs (including food stamps and unemployment) have grown. The somewhat reduced “everything else” category includes everything from education to space exploration to agriculture and more:

Via The Sociological Cinema; data available at the Office of Management and Budget.

The Network Effect

Network effect is a concept from economics that explains situations in which something becomes more valuable as more people use it. The classic example is the telephone; as more people and businesses adopted telephones, they became more useful (you could call a larger number of people you might wish to contact). More usage increased the value of the product, both for existing users and potential users. Social media work much the same way — an issue Google has faced as they try to pull enough users into Google+ to make it competitive with Facebook.

Over the weekend Matthew Hurst posted a video at Data Mining that illustrates the network effect…with dancers using an open area at the Sasquatch music festival. The video starts out a little slow; one guy starts dancing in the field, and a second guy joins him. For about a minute, it’s just the two of them. At 0:54, a third dancer appears. Through all of this, the surrounding crowd mostly ignores them, showing no inclination to participate. But at 1:12, a couple more people arrive, following immediately by more, and suddenly we’ve reached a tipping point: that open area is now a highly desirable spot to dance. People start running in from all directions, and many who had been ignoring the dancers suddenly jump up and join. It’s a great illustration of instances in which use drives more and more use: