• A Neighborhood Education

    Apr 25 • Behavioral Economics, Demand, Supply, and Markets, Households, Thinking Economically • 573 Views

    By Mira Korber, guest blogger.

    You probably know that where you live says quite a lot about the public education you receive. However, living in a geographical zone that touts quality schooling may cost more than you realize.

    A new Brookings study shows a very large “price gap” relationship between expensive housing, low-cost housing, and education. For example, in the US’ most prominent 100 metropolitan areas, housing costs proved 2.4% greater than in other locations. (That’s $11k per year). Additionally, homes are clustered economically; when assessing high-income versus low-income housing, a disparity in standardized testing scores becomes evident.

    Quoting the study directly: “Northeastern metro areas with relatively high levels of economic segregation exhibit the highest school test-score gaps between low-income students and other students.”

    So, what does this mean for the cost of living near good public education? It actually may be cheaper to live in a low income neighborhood and send your kids to private school than moving to an expensive residential zone. Here are the numbers: in the NYC region, it costs $16k more per year to live near high-scoring schools than low-scoring ones. According to the NY Times, average private Catholic school tuition is $6k.

    The Bottom Line? High-cost homes bring us to negative externalities (undesirable impacts on a third party due to a private transaction). Just as a factory near a once-clean stream contaminates the water source, expensive housing can negatively impact the surrounding communities. High housing costs are directly related to quality education; therefore, soaring prices prevent — negatively affect — the less affluent third party from accessing better schools.

    Related sources:

    The main source material for this post can be found here. The link to the Brookings study cited above. And a very interesting NYU study about the correlation between public housing and lower standardized test scores.


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    (Bad) Decisions

    Apr 24 • Behavioral Economics, Economic Thinkers, Financial Markets, Thinking Economically • 679 Views

    By Mira Korber, guest blogger.

    Why might have most notorious fraudsters committed their crimes? The traditional answer seems obvious: severe character flaws, lack of ethics, unbridled greed. But there may be more to the picture than simply this “bad person.”

    In a recent Planet Money podcast, economist Lamar Pierce of Washington University in St. Louis set out to discuss why people make unethical decisions. The story in question refers to Toby Groves, a seemingly upstanding citizen who later committed multimillion-dollar fraud crimes. Upon discovering his mortgage company was $250,000 in debt, Groves decided to mortgage his own home. Lying to the bank, he said his income was $350,000 when it wasn’t even close to that number. Later on, Groves needed more, so he solicited the” help” of his employees and a title company to fabricate and verify “air loans” — made-up mortgages for made-up people. Every employee he asked and the title company colluded with no hesitation.

    Incentives are clearly at the heart of illegal decision making such as this; Groves needed to get his business out of debt and back on track however he could. When he sought help, it was readily available; perhaps his employees feared losing their jobs, or anticipated a bonus for “helping” to preserve the company.

    According to Pierce, and a second economist on the podcast, Francesca Gino, decisions to help Groves were made because a short-term “favor” seemed far more tangible than potential future repercussions. Additionally, Gino theorized that as human beings naturally “like” each other, they are prone to assisting even immoral behavior.

    This analysis brings me to Adam Smith’s The Theory of Moral Sentiments. Smith argues that a mutual sympathy between human beings causes us to empathize with each other, simply because “how selfish soever man may be supposed, there are evidently some principles in his nature, which interest him in the fortune of others, and render their happiness necessary to him…” Smith continues, “the greatest ruffian, the most hardened violator of the laws of society, is not altogether without it,” “it” being a sense of kindred emotion.

    Perhaps that shared feeling is what actually prompts said “ruffian” to perpetrate group fraud. We empathize through a self-centered perspective; only by imagining ourselves in equal agony can we feel sympathy for the one suffering in reality:

    As we have no immediate experience of what other men feel, we can form no idea of the manner in which they are affected, but by conceiving what we ourselves should feel in the like situation. Though our brother is upon the rack, as long as we ourselves are at our ease, our senses will never inform us of what he suffers…By the imagination we place ourselves in his situation, we conceive ourselves enduring all the same torments…and thence form some idea of his sensations, and even feel something which, though weaker in degree, is not altogether unlike them. His agonies, when they are thus brought home to ourselves, when we have thus adopted and made them our own, begin at last to affect us…

    Imagining ourselves “on the rack” might help us make a bad choice — say — fabricating mortgage papers?

    The Bottom Line: While fraud predictably leads to questioning of the perpetrator(s)’ incentives, it also relates to a basic psychological tendency: mutual sympathy among people who identify with each other, or offering “favors” expected to be returned in the future.  Therefore, favors are not altruistic, but may be motivated by a mutual financial dependency later on.

    Related Sources: Find the Planet Money podcast “Why People Do Bad Things” here. Adam Smith, here. And for a previous Econlife post on cheating, here. You also may wish to read “How We Decide” by Jonah Lehrer, which received a favorable NY Times review, and is on my future reading list.

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    Middle Class Questions

    Apr 23 • Government, Households, Labor, Macroeconomic Measurement, Regulation, Uncategorized • 1077 Views

    If you have questions about Verizon and middle class income growth,  your conclusions might depend on the questions that you ask.

    My story begins with a disastrous call to Verizon Wireless. One agent left and never returned, three said they could not help me, and the fifth person, hearing I had made no progress after 45 minutes said, “An iPhone is a luxury item; these things take time.” The sixth agent, realizing my problem had an easy solution, helped me graciously and quickly.
    Soon after, Verizon asked me to evaluate their service in an automated survey. Using numbers from 1 to 10 to quantify my satisfaction, I was supposed to assess the last person with whom I spoke in a series of questions. Only in a separate optional comment at the end could I tell about the other five people.
    I suspect Verizon’s computers will conclude they just made another customer happy because I gave agent #6 a “10” for every question. And yet otherwise, my experience was far from ideal.

    The Verizon survey reminded me of statistics about middle class income.

    Researchers disagree about how much middle class income grew from 1979-2007. Citing a 3 percent total, economists Thomas Piketty and Emmanuel Saez say there was virtually no growth. By contrast, a group of Cornell scholars says middle class income grew 36.7 percent.

    A 33.7 percent difference! How? Because the answers you get depend on what you ask.

    Piketty, Saez and the Cornell group had to decide whether they would ask questions about a tax unit, a household, or a family. The former two economists chose the tax unit while the latter selected the household.  Then, the Cornell group considered whether to ask questions solely about returns from land, labor and capital or to include government transfers. And after that, questions about household size become relevant because people sharing a household–even if unrelated–benefit from each other’s income through shared spending.

    The Botton Line: When Verizon, Piketty and Saez, and the Cornell group looked at the answers to their questions, their conclusions were totally accurate. Who is right? It all depends on which questions you think are appropriate.

    The NY Times introduced Thomas Piketty and Emanuel Saez and their ideas in a front page story. Their paper with much more detail is here. For the Cornell group’s research, an Econtalk podcast provided an excellent description and a great summary comparison chart. Gated, their NBER working paper is here.

    *The first sentence of this post was edited after it appeared.

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    Venezuela’s Price Controls

    Apr 22 • Behavioral Economics, Demand, Supply, and Markets, Households, Regulation, Thinking Economically, Uncategorized • 959 Views

    Reading that a Venezuelan retiree did not mind the food lines, I started thinking about how President Chavez’s price controls have changed incentives. The retiree, who has more time than money, now has the incentive to stand in line. Meanwhile, a business owner, seeing profits erased by price controls has the incentive to produce less.
    When a ceiling on prices increases the quantity that people demand while decreasing the quantity that producers supply, the result is Venezuelan shortages of the basics like powdered milk, beef, chicken, vegetable oil and sugar.

    The bottom line: A government established price creates distorted incentives for buyers and sellers. The long lines, pajama tops without buttons, and grouchy salespeople that characterized the former Soviet Union are perfect examples of the results of distorted incentives.

    This NY Times article tells more about price controls in Venezuela. Also, you might enjoy seeing this sign from a Venezuelan store that is posted here.

    *This entry was edited after it was first posted.

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  • Women’s Wages

    Apr 21 • Behavioral Economics, Demand, Supply, and Markets, Gender Issues, Households, Macroeconomic Measurement, Uncategorized • 621 Views

    I just learned that April 17 was Equal Pay Day. Assuming that the average woman earns 22 percent less than the average man, she would have to work until mid-April to equal his pay.

    For women’s pay statistics, I like to look at the Institute for Women’s Policy Research (IWPR). In a recent paper, they say the gap is 17.8 percent because a typical woman’s median weekly earnings are $684 while for men, $832.

    Calling it “occupational segregation,” the IWPR reports that jobs we associate with women pay less than “male occupations.” For example, female secretaries earn $651 a week and even that is $16 less than their male counterparts. Similarly, female cashiers earn $373 weekly and male cashiers, $411. You can see that in lower paying “female” jobs, still men earn more. (All amounts are for median weekly earnings.)

    For the wage gap in occupations dominated by men, the IWPR shows that although the wages are higher, again, women take home less. The median weekly earnings for female drivers/sales workers/truck drivers is $511 a week. A male in the same category? $712. Female janitors/building cleaners? $418. Male janitors/building cleaners? $514. Female CEOs? $1464. Male CEOs? $2122.

    Focusing on the wage gap for professional women, Harvard economists Clauda Goldin and Lawrence Katz cite children as the reason because women take more time off for child rearing and that time off decreases their lifetime earnings. Even women with career continuity tend to select lower paying specialties like general practitioners rather than neurosurgeons or salaried in-house council rather than a high pressure law firm. And, for working mothers with an MBA, 15 years after graduation, the gender pay gap is 25%.

    Super Freakonomics tells us that women are subject to greater pay discrimination for being obese or having bad teeth.

    The Bottom Line: Supply and demand for men and women differ in labor markets.

    If you would enjoy reading more about the gender pay gap, the occupational charts are fascinating in the IWPR report. For a lighter approach,  the Freakonomics blog quotes Goldin and Katz. But, if you prefer seeing their conclusions firsthand, you can look at one of their papers here.

    And finally, an interesting fact: It matters where you live. Washington, D.C. has the smallest wage gap while Wyoming has the largest. This Huffington Post article tells more.

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