The notion that everyone should have a base level of income is something typically expressed by communists, people Bill O’Reilly hates (ultra-liberals), and progressive-minded hippy folk. This idea has seemed pretty impractical in the past, but economic analysis indicates it might not be so crazy after all.

Welfare programs in their current state can sometimes provide disincentives to work. The very nature of giving someone money is that it will change his or her incentives, even marginally. Some current programs are structured in a way to minimize these disincentives, such as the earned income tax credit (EITC). As the name implies, the EITC provides individuals additional income based on hours worked and is mostly effective, however, these rewards can’t go on forever—eventually the benefits decrease for each additional dollar earned. This decreases the actual wage the people make, discouraging them from working additional hours. So overall a good idea, but has its drawbacks. (more on the EITC another day)

Ed Dolan lays out a pretty convincing economic argument for providing a UBI. This would look like a flat payment that everyone receives, regardless of income level. The caveat to his analysis is that the UBI value must be below that of the previous welfare program. In doing so, it is ensured that:

  1. Individuals who received full welfare benefits in the past maintain an incentive to work (they need to earn more money to reach the same level of income as before)
  2. Individuals who previously would have been in the “phase-out” benefits period don’t lose their incentive to work more hours (their benefit is now constant, and they will make a consistent hourly wage by working more)
  3. Individuals who might have juuust missed the cutoff for welfare benefits in the past do not have an incentive to work less in order to qualify, and will thereby work more

The only group that might negatively be impacted by the shift to UBI is middle-to-upper class individuals who see their income go up, and thus work less. This idea is quite intriguing, as the world has always struggled to produce a welfare program that helped people while still giving them incentives to support themselves.

Another form of welfare argued to give people incentives not to work is unemployment insurance. In 2013, North Carolina decided to stop providing long-term unemployment benefits—despite the fact that the federal government was giving them money to pay them. This is unfortunate for the people in North Carolina, but creates a fascinating natural experiment. Conservatives (who opposed unemployment insurance) claimed eliminating benefits would encourage people to search for jobs and boost employment. Justin Wolfers discusses for the NYT Upshot:

Employment grew by 1.5 percent over the six months since the [benefits were eliminated]. While this growth rate is healthy, what matters here is whether it is better or worse than it would have been without such a policy shift. To shed light on that issue, we need a comparison group: an otherwise similar state that made no such change. The most obvious possibility is South Carolina, a neighbor that has a broadly similar industry mix. Over the same period, nonfarm payrolls in South Carolina grew by 1.6 percent.

It would then appear that eliminating benefits had little effect on the job market in comparison to similar states. This year (2014), the federal government eliminated long-term benefits nation-wide. Again, conservatives claimed that the positive economic growth seen this year was due to the elimination of benefits. Thankfully, we have an experiment in place to evaluate this:

“The cut in federal funding had no effect in North Carolina, because it wasn’t accepting that funding. This makes it the ideal “control group.”… If cutting benefits boosts the labor market, the policy change should have led South Carolina to outperform North Carolina in 2014. Yet over the six months since federal benefits ended, nonfarm payrolls grew by 0.6 percent in South Carolina and 0.4 percent in North Carolina.

It would appear that the data indicates eliminating benefits had a neutral overall effect.

Along the lines of evaluating unemployment via unconventional methods, a University of Michigan professor has been harnessing the power of social media to determine accurate unemployment data. Harnessing the power of the aggregated data available on social media (“big data”), Matthew Shapiro was able to more accurately predict unemployment rates than the government or other experts. Imagine the possibilities of big data from social media indicating health concerns, disease outbreaks, or even census information! People share a great deal of information via social media, so it’s up to clever people like Shapiro to harness the data.

Luckily for the social media users¹, not only are they helping us get better data, they also may make more money! As this Wall Street Journal article discusses, people can no longer rely on technical skills alone to make them a lot of money. Employers now place a high value on individuals with social skills to accompany technical skills:

“Thirty years ago, the worker who was above average on both dimensions earned about 3% more than the worker who was above average on one or the other dimension… Since the year 2000, the differential has grown to about 10%

Last but not least, I leave you with a list of the 11 Funniest Papers in the History of Economics². A personal favorite discusses the fact that “Japans Phillip’s Curve³ Looks Like Japan”:

“For ease of viewing, the left-hand panel of Figure 1 rotates the Phillips Curve around the vertical axis so that minus the unemployment rate now is on the horizontal axis. Clearly visible are the islands of Hokkaido and Honshu, though it is somewhat difficult to separately distinguish the southern islands of Kyushu and Shikoku. The Noto-Hanto Penninsula is evident to the north of the southern end of the main island of Honshu. Tokyo Bay is also visible. The data point to the far left in Figure 1 is the island of Fukue-Jima. “

 If you squint, you can totally see it! 

If you squint, you can totally see it! 


¹Assuming they have in-person skills to match their online presence, which could totally not be the case for some, but I digress.

²Is this what economic click-bait looks like? Oh boy.

³The Phillips curve details the relationship between unemployment and inflation, which is how I am justifying the insertion of this item into a labor-market themed post.  

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AuthorIsabel Munson