About the author
Mark Perry Tweets
View related content: Carpe Diem
Pictured above are some color TVs from the 627-page 1964 Sears Christmas Catalog, available here at the WishbookWeb website along with many other Christmas catalogs from 1933 to 1988. The original prices are listed ($750 for the Sears Silvertone entertainment center and $800 for the more expensive one), and those prices are also shown converted to today’s 2014 dollars using the BLS Inflation Calculator: $5,700 for the basic 21-inch color TV model and $6,100 for the more expensive model.
To put that in perspective, the pictures below illustrate what about $5,700 in today’s dollars (actually only $5,600) would buy in the 2014 marketplace using current prices from the Sears and Best Buy websites:
Bottom Line: For an American consumer or household spending $750 in 1964, they would have been able to purchase the 21-inch color TV/entertainment center from the Sears Christmas catalog pictured above (includes phonograph and AM/FM radio). An American consumer or household spending that same amount of inflation-adjusted dollars today (about $5,600) would be able to furnish their entire kitchen with 5 brand-new appliances (refrigerator, gas stove and oven, washer, dryer, and freezer) and buy 7 state-of-the-art electronic items for their home (a Toshiba Satellite 14″ laptop computer, a Garmin 5 Inch GPS, a Canon EOS Rebel T5 DSLR Camera, a Sony 1,000 Watt, 5.1-Channel 3D Smart Blu-Ray Home Theater System, a Sharp 50 inch LED HDTV, an Apple iPod Touch 32GB MP3 Player, and an Apple iPhone 6). And of course, even a billionaire in 1964 wouldn’t have been able to purchase many of the items that even a teenager can afford today, e.g. laptop computer, GPS, iPhone, digital camera.
As much as we might complain about a slow economic recovery, the decline of the middle class, stagnant median household income, rising income inequality and a dysfunctional Congress, we have a lot to be thankful for, and we’ve made a lot of economic progress in the last 50 years as the example above illustrates, thanks to the “magic and miracle of the marketplace.”
Holiday shopping? Consider the most economically efficient gift of all: cash, and avoid the deadweight loss of Christmas
View related content: Carpe Diem
Although that strategy didn’t work out so well for Jerry Seinfeld….
It’s that time of year for my annual post on the “deadweight loss of Christmas gift giving.”
1. Economist Steven Landsburg writing in his book the “Armchair Economist: Economics and Everyday Experience“:
I am not sure why people give each other store-bought gifts instead of cash, which is never the wrong size or color. Some say that we give gifts because it shows that we took the time to shop. But we could accomplish the same thing by giving the cash value of our shopping time, showing that we took the time to earn the money.
2. In a 1993 American Economic Review article “The Deadweight Loss of Christmas,” Yale economist Joel Waldfogel concluded that holiday gift-giving destroys a significant portion of the retail value of the gifts given. Reason? The best outcome that gift-givers can achieve is to duplicate the choices that the gift-recipient would have made on his or her own with the cash-equivalent of the gift. In reality, it’s highly certain that many gifts given will not perfectly match the recipient’s own preferences. In those cases, the recipient will be worse off with the sub-optimal gift selected by the gift-giver than if the recipient was given cash and allowed to choose his or her own gift. Because many Christmas gifts are mismatched with the preferences of the recipients, Waldfogel concludes that holiday gift-giving generates a significant economic “deadweight loss” of between one-tenth and one-third of the retail value of the gifts purchased.
3. The National Retail Federation estimates that Americans will spend $617 billion this year during the holiday season. If the deadweight loss estimates of Professor Waldfogel are accurate, that would mean that between $62 billion and $206 billion of the spending on gifts this holiday season will be wasted.
4. In the Seinfeld episode above, Jerry thinks like an economist and tries to avoid the deadweight loss by giving his close friend Elaine a beautifully gift-wrapped package that contains $182 in cash for her birthday. Watch as Jerry’s economic thinking about giving cash backfires, suggesting that there might be a cost to giving cash as a gift that Professor Waldfogel’s model didn’t consider.
Sen. Sanders blamed speculators for the $7.50/barrel increase in oil prices from Jan-June; Do they now get credit for the $43/barrel drop in oil prices since July?
View related content: Carpe Diem
Last summer when oil prices rose by 5% during a three-week period in June partly due to instability in Iraq, Sen. Bernie Sanders once again blamed greedy energy-market traders for the rise in prices and introduced legislation in the first week of July that would allow the government to intervene in the futures markets to curb speculation on oil prices. Now that oil prices have plummeted by almost 60% since Sen. Sanders introduced his bill (see chart above), I’ll have some more editing fun below of a July news report on Sen. Sanders’s legislation (see some previous editing fun from a few months ago here):
Sen. Bernie Sanders is taking aim at energy-market traders he blames for sharply driving up down gas and oil prices by exploiting Iraqi instability, the current oversupply of oil, introducing legislation that would compel the federal Commodity Futures Trading Commission to intervene.
Sanders is part of a growing and diverse coalition of market watchers who believe speculators are partly responsible for the rising falling oil and gas prices over the last six months. The argument is a long-standing contention and of populists, feeds
inga narrative of Wall Street insiders making life more difficult for Main Street consumers hundreds of independent oil and gas companies. For example, the shares of oil and gas producer Continental Resources have fallen by 60 percent since September, and the shares of Anadarko, another independent producer, have dropped by 35 percent.
Energy speculators bet on future prices for oil and purchase contracts. The process can raise huge profits for oil companies and investment banks that can buy and sell hundreds of millions of barrels a day, leading to critics like Sanders claiming that Wall Street is unfairly taking advantage of the commodities market and cheating American consumers. independent oil and gas companies out of profits. But bankers and traders argue that speculation protects them from potential price shocks, and further regulations from the CFTC would burden legitimate hedging.
Sanders, a member of the Senate Energy and Natural Resources Committee, cites the 5 30 percent crude oil price rise drop in the last three weeks since June12 November 25 —when hostilities intensified in several Iraqi cities—as evidence for malpractice. In the longer term, Sanders notes that oil prices have increased decreased by 53 percent over the past five four years.
“I am getting tired of big oil companies and Wall Street speculators using Iraq using the glut of crude oil as an excuse to pump up drive down oil and gas prices,” Sanders said in a statement. “The fact is that high low gasoline prices have less to do with supply and demand and more to do with Wall Street speculators driving prices up down in the energy futures market.”
“We now know that speculators artificially drove up electricity prices on the West Coast in 2000; propane prices in 2004; and natural gas prices in 2006,” Sanders said. “Why would anyone believe that speculators at this very minute are not manipulating the price of oil lower when supply is high and demand is low?”
MP: Here are some questions for Sen. Sanders and the 17 fellow Democratic co-sponsors of his bill:
1. If greedy speculators were to blame for the $7.50 per barrel (and 10.6%) increase in oil prices during the first half of this year that motivated your anti-speculation bill in early July, do oil speculators now get any of the credit for the $43.60 (and 41%) drop per barrel in oil prices during the last half of 2014?
2. Is it your position that falling gas and oil prices over the last six months have less to do with supply and demand and more to do with Wall Street speculators driving prices down in the energy futures markets?
3. Is it your position that market forces are the primary reason that oil and gas prices fall, but speculation and energy market manipulation are the primary reasons that oil and gas prices rise?
4. Are energy traders now unfairly taking advantage of the commodities markets by speculating on the significant decline in oil prices?
5. Are greedy speculators unfairly cheating oil and gas companies out of the fair profits they deserve for their risky capital investments in oil and gas exploration and drilling?
6. Will you be calling for Congressional hearings to investigate the role of energy-market speculation in the significant decline in oil and gas prices?
7. Is it possible that greedy speculators are only responsible for rising oil and gas prices but blameless for falling commodity prices? Do they disappear somewhere when oil prices are falling, but suddenly reappear periodically to destabilize energy markets by causing spikes?
Bottom Line: Realistically, Sen. Sanders and his Democratic co-sponsors can’t have it both ways. If greedy speculators are to blame for rising oil prices, they have to also get some credit for falling prices. In that case, we and Congress should be celebrating and thanking the speculators for the recent drop in oil and gas prices that will save consumers collectively more than $100 billion over the next year.
View related content: Carpe Diem
1. Chart of the Day. Medallion Financial Corp. (NASDAQ: TAXI) is a NYC-based specialty finance company that originates, acquires, and services loans that finance taxicab medallions. As I’ve been reporting for the last year, the traditional NYC “taxi cartel,” which has operated for generations under a government-protected cartel regime of restricted entry through its medallion licensing system, has been under intense pressure in recent years from ride-sharing services like Uber, Sidecar, Lyft and Gett. As a result, the market price of NYC taxi medallions has been dropping steadily from the 2013 peak of more than $1 million to below $900,000 in recent months according to a recent analysis by the NY Times. Just as the sky-high taxi medallion prices have been significantly eroded due to competition from the upstart ride-sharing services, so has the value of Medallion Financial Corporation’s stock price been significantly dropping. After tracking the SP&500 Index closely for many decades, the share price of Medallion Financial has fallen by a whopping 36% from its peak last November, during a time when the S&P 500 has increased by 11% (see chart above). As one research report described it, Medallion Financial has been “Uber’d” – as have the taxi medallions – and we can expect a lot more “Uber-ing” before it’s all over.
2. Secret study on driving habits: Ridesharing vs. taxis. Driver safety analytics startup Zendrive found that taxis in San Francisco drove above the speed limit about 50% more than rideshares on average, and about 2.5 times more during rush hour.
3. Uber is a greater friend of urban women in India than the government ever was. Over the past several months, women have taken to the smartphone app with enthusiasm. They grade the drivers and convey to Uber their compliments — and their complaints about bad manners and body odor. Source: New York Times.
4. Who-d a-Thunk It I? Electric cars aren’t nearly as green as they’re hyped up to be? From the Associated Press:
People who own all-electric cars where coal generates the power may think they are helping the environment. But a new study finds their vehicles actually make the air dirtier, worsening global warming. Ethanol isn’t so green, either.
“It’s kind of hard to beat gasoline” for public and environmental health, said study co-author Julian Marshall, an engineering professor at the University of Minnesota. “A lot of the technologies that we think of as being clean … are not better than gasoline.”
5. Minimum-wage laws criminalize low-skill work. “Imagine being forbidden to work. That is the case for people with skills under $8.25 an hour. The federal hourly minimum wage is $7.25, and additional costs, such as Social Security, unemployment insurance, and workers compensation bring the cost of employment closer to $8.25, says Diana Furchtgott-Roth in her article “6 ways the government criminalizes economic activity.”
6. The Biggest Music Comeback of 2014: Vinyl Records — LPs Surge 49% as Aging Factories Struggle to Keep Pace.
7. Markets in Everything: a) Iowa plans to launch a new smartphone driver’s license in 2015 and b) you can hire now a Personal Health Assistant (PHA) who will coordinate your health care, connect you with expert medical advice, review your insurance, make sure all of your medical appointments are up-to-date for you and your family, and organize your health records.
8. Great Moments in Government Regulation. New regulations taking effect in California at the beginning of next year will force egg producers to allocate 73% more room to each egg-laying chicken. Result? Egg prices could jump by as much as 20%.
Quiz: Who will be harmed more by this regulation – rich people or poor people?
9. The Great Campus Rape Hoax: a) Glenn Reynolds: “Americans have been living through an enormously sensationalized college rape hoax, but as the evidence accumulates it’s becoming clear that the entire thing was just a bunch of media hype and political opportunism,” and b) Eric Owens easily found 8 campus rape hoaxes eerily like the UVA rape story.
10. Video of the Day. In her latest video in the Factual Feminist series, Christina Sommers explains below why Rolling Stone’s UVA rape hoax story went viral so easily.
New Justice Department study reveals that about 1 in 52 college women have been victims of rape/sexual assault
View related content: Carpe Diem
Trigger Warning: If you are upset by facts about campus sexual assault please stop reading now.
The Department of Justice (Bureau of Justice Statistics) released a report yesterday titled “Rape and Sexual Assault Victimization Among College-Age Females, 1995–2013.” The report was based on the National Crime Victimization Survey (NCVS) of women ages 18-24 for both reported and unreported cases of rape and sexual assault. Rape and sexual assault are defined by the NCVS to include: a) completed and attempted rape, b) completed and attempted sexual assault, and c) threats of rape or sexual assault, so the study provides a pretty comprehensive analysis of rape and sexual assault among young women. The report includes both: a) students (enrolled in college, university, trade school, or vocational school) and b) nonstudents for the 18 to 24 age group, which allows for a comparison of “campus rape/sexual assault” and offenses that take place for that age group among nonstudents. Here are some of the report’s findings:
1. Over the 1995-2013 period, the rate of rape and sexual assault victimization was almost 25% higher for nonstudents ages 18-24 (7.6 cases per 1,000 females) compared to students enrolled in a post-secondary institution in that age group (6.1 cases per 1,000 females), see chart above. So despite all of the media attention on campus sexual assault, women enrolled in colleges and universities are actually much safer compared to women in that age group who are not attending a post-secondary institution.
2. Over the 1995-2013 period, the rate of rape and sexual assault victimization for both students and nonstudents has been falling (see chart). For women attending college, the rate of rape/sexual assault has fallen by more than 50%, from 9.2 incidents per 1,000 women in 1997 to 4.4 cases per 1,000 in 2013. According to the media, politicians and gender activists, there is supposed to be a college “rape epidemic” when in fact, the rate of college female victimization has been trending downward for the last two decades.
3. What might be the most important statistic (and was not provided in the report and is not being reported by the media, except Ashe Schow at the Washington Examiner) is that the data provided by the NCVS show that only about 1 in 41 women were victims of rape or sexual assault (threatened, completed and attempted; and reported and unreported) while in college for four years during the entire period investigated from 1995 to 2013, based on this analysis:
6.1 women per 1,000 = “1 in 163.9 women” per year, and over four years attending college would then be = “1 in 41 women” while in college.
Because the victimization rate has been trending downward, that same analysis using data from the last four years (2010 to 2013) reveals that 1 in 52.6 women have been sexually assaulted or raped in recent years.
Bottom Line: Using Bureau of Justice survey data that includes: a) reported and unreported cases of sexual assault and rape, and b) threatened, attempted and completed cases, the rate of campus sexual assault, we can say that:
1. Women ages 18 to 24 attending college have about a 25% lower chance of being the victim of rape or sexual assault compared to their nonstudent counterparts.
2. College campuses have become safer for women in the last few decades, based on the decline in the rape/assault rate by 50% since 1997.
3. Over the last four years, about 1 in 52 college women were raped or sexually assaulted, which is different by a factor of more than ten times compared to the “1 in 5″ claim made by the White House based on the findings of one survey from students at two universities. Of course, 1 in 52 college women being the victim of a rape or sexual assault is still too high, but the controversy about campus sexual assault (and the victims) is best served by truthful and accurate data, and this new report from the Justice Department will hopefully contribute to the accuracy of the data on a very important issue.
New BLS report on women’s earnings: Most of the 17.9% gender pay gap in 2013 is explained by age, marriage, hours worked
View related content: Carpe Diem
According to a TV election ad in 2012, “President Obama knows that women being paid 77 cents on the dollar for doing the same work as men isn’t just unfair, it hurts families.” Do the data support the president’s claim? Not at all.
For example, the Bureau of Labor Statistics (BLS) releases an annual report on the “Highlights of Women’s Earnings” (since the BLS report actually looks equally at data for both men’s and women’s earnings, one might ask why the report isn’t simply titled “Highlights of Earnings in America?”, but maybe that’s a politically incorrect question). Here’s the opening paragraph from the most recent BLS report “Highlights of Women’s Earnings in 2013” that was released this week:
In 2013, women who were full-time wage and salary workers had median usual weekly earnings of $706. On average in 2013, women made 82.1 percent of the median weekly earnings of male full-time wage and salary workers ($860). In 1979, the first year for which comparable earnings data are available, women earned 62 percent of what men earned.
How do we explain the 23% gender pay gap claimed by Obama, or the fact that women working full-time earned only 82.1 cents for every dollar men earned in 2013 according to the BLS? Here’s how the National Committee on Pay Equity explains it:
The wage gap exists, in part, because many women and people of color are still segregated into a few low-paying occupations. Part of the wage gap results from differences in education, experience or time in the workforce. But a significant portion cannot be explained by any of those factors; it is attributable to discrimination. In other words, certain jobs pay less because they are held by women and people of color.
Let’s investigate the claim that the gender pay gap is a result of discrimination by looking at some of the wage data by gender in the BLS report for 2013:
1. Among full-time workers (those working 35 hours or more per week), men were more likely than women to work a greater number of hours (see Table 5). For example, 25.5% of men working full-time worked 41 or more hours per week in 2013, compared with only 14.3% of women who worked those hours, meaning that men working full-time last year were almost twice as likely as women to work 41 hours per work or more. Further, men working full-time were also more than twice as likely as women to work 60-hour weeks: 6.3% of men worked 60 hours per week in 2013 compared to only 2.7% of women working full-time who worked those hours.
Also, women were more than twice as likely as men to work shorter full-time workweeks of 35 to 39 hours per week: 12.2% of women worked those hours in 2013, compared to only 5% of men who did so. Although not reported by the BLS, I estimate using their data that the average workweek for full-time workers last year was 41.4 hours for women and 43.4 hour for men; therefore, the average man working full-time worked 2 more hours per week in 2013 compared to the average woman.
Comment: Because men work more hours on average than women, some of the raw wage gap naturally disappears just by simply controlling for the number of hours worked per week, an important factor not even mentioned by groups like the National Committee on Pay Equity. For example, women earned 82.5% of median male earnings for all workers working 35 hours per week or more, for a raw, unadjusted pay gap of 17.5% for full-time workers (Table 5). But for those workers with a 40-hour workweek, women earned 89.6% of median male earnings, for a pay gap of only 10.4%. Therefore, once we control only for one variable – hours worked – and compare men and women both working 40-hours per week in 2013, almost half of the raw 17.5% pay gap reported by the BLS disappears.
2. The BLS reports that for full-time single workers who have never married, women earned 95.2% of men’s earnings in 2013, which is a wage gap of only 4.8% (see Table 1 and chart above), compared to an overall unadjusted pay gap of 17.9% for workers in that group. When controlling for marital status and comparing the earnings of unmarried men and unmarried women, almost 75% of the unadjusted 17.9% wage gap is explained by just one variable (among many): marital status.
3. Also from Table 1 in the BLS report, we find that for married workers with a spouse present, women earned only 78.0% of what married men with a spouse present earned in 2013 (see chart). Therefore, BLS data show that marriage has a significant and negative effect on women’s earnings relative to men’s, but we can realistically assume that marriage is a voluntary lifestyle decision, and it’s that personal choice, not necessarily labor market discrimination, that contributes to much of the gender wage gap for married workers.
4. Also in Table 1, the BLS reports that for young workers ages 25-34 years, women earned 89.4% of the median earnings of male full-time workers for that age cohort in 2013. Once again, controlling for just a single important variable – age – we find that almost half of the overall unadjusted raw wage gap for all workers (17.9%) disappears for young workers.
5. In Table 7, the BLS reports that for full-time single workers with no children under 18 years old at home (single workers includes never married, divorced, separated and widowed), women’s median weekly earnings were 96.1% of their male counterparts (see chart). For this group, once you control for marital status and children, you automatically explain almost 80% of the unadjusted gender earnings gap.
6. Also in Table 7, the BLS reports that married women (spouse present) working full-time with children under 18 years at home earned 78.9% of what married men (spouse present) earned working full-time with children under 18 years (see chart). Once again, we find that marriage and motherhood have a significantly negative effect on women’s earnings; but those lower earnings don’t necessarily result from labor market discrimination, they more likely result from personal family choices about careers, workplace flexibility, child care, and hours worked, etc.
7. If we look at median hourly earnings, instead of median weekly earnings, the BLS reports in Table 8 that women earned 86.6% of what men earned in 2013, which accounts for about 25% of the raw 17.9% gender earnings gap that exists for weekly earnings. And when we look at young workers, women ages 16 to 19 years earned 96.7% of the hourly wage of their male counterparts in 2013, and for the 20-24 year old group, women earned 94.0% of what men earned per hour. Also in Table 8, we see that for never married hourly workers of all ages, women earned 92.7% of the hourly earnings of their male counterparts in 2013, which explains almost half of the unadjusted 13.4% gender difference in hourly earnings.
Bottom Line: When the BLS reports that women working full-time in 2013 earned 82.1% of what men earned working full-time, that is very much different than saying that women earned 82.1% of what men earned for doing exactly the same work while working the exact same number of hours in the same occupation, with exactly the same educational background and exactly the same years of continuous, uninterrupted work experience. As shown above, once we start controlling individually for the many relevant factors that affect earnings, e.g. hours worked, age, marital status and having children, most of the raw earnings differential disappears. In a more comprehensive study that controlled for all of the relevant variables simultaneously, we would likely find that those variables would account for almost 100% of the unadjusted, raw earnings differential of 17.9% lower earnings for women reported by the BLS. Discrimination, to the extent that it does exist, would likely account for a very small portion of the raw gender pay gap.
For example, in a 2005 NBER working paper “What Do Wage Differentials Tell Us about Labor Market Discrimination?” by June O’Neill (Professor of economics at Baruch College CUNY, and former Director of the Congressional Budget Office), she conducts an empirical investigation using Census data and concludes that:
There is no gender gap in wages among men and women with similar family roles. Comparing the wage gap between women and men ages 35-43 who have never married and never had a child, we find a small observed gap in favor of women, which becomes insignificant after accounting for differences in skills and job and workplace characteristics.
This observation is an important one because it suggests that the factors underlying the gender gap in pay primarily reflect choices made by men and women given their different societal roles, rather than labor market discrimination against women due to their sex.
To claim that a significant portion of the raw wage gap can only be explained by discrimination is intellectually dishonest and completely unsupported by the empirical evidence. And yet we hear all the time from groups like the National Committee on Pay Equity, the American Association of University Women, the Institute for Women’s Policy Research, and President Obama, President Jimmy Carter and Virginia governor Terry McAuliffe that “women are paid 77 cents on the dollar for doing the same work as men.” And in most cases when that claim is made, there is almost no attention paid to the reality that almost all of the raw, unadjusted pay differentials can be explained by everything except discrimination – hours worked, age, marital status, children, years of continuous experience, workplace conditions, etc. In other words, once you impose the important ceteris paribus condition of “all other things being equal or held constant,” the gender pay gap that we hear so much about doesn’t really exist at all.
But we know by now that logic, economic theory and empirical evidence won’t matter to gender activists, progressives, and most Democrats, and all we’ll hear about regarding the new BLS report will be that women earned only 82.1 cents for every dollar earned by men last year…. for doing the same work, and how unfair that is……
Related: The “Discriminator-in-Chief” Obama has his own gender pay gap at the White House that exposes his hypocrisy on this issue – while lecturing everybody about the unfairness of the gender pay gap nationally using aggregate salary data, an analysis of White House salaries shows that he pays his own female staffers 13.3% less on average than his male employees. Alternatively, if the 13.3% gender pay gap at the White House can be explained by factors other than discrimination (like experience, age and education), Obama should then stop using unadjusted, aggregate salary statistics to lecture the country about a gender pay gap crisis at the national level.
View related content: Carpe Diem
Below are summaries of three research papers on the negative effects of increases in the minimum wage — the first one finds empirical evidence of negative employment effects from increases in the minimum wage between 2008 and 2012 (negative demand side effects), and the other two find negative effects of the minimum wage on high school enrollment (negative supply side effects from reduced skill acquisition).
1. The first research article is a new NBER working paper (“The Minimum Wage and the Great Recession: Evidence of Effects on the Employment and Income Trajectories of Low-Skilled Workers” by UC-San Diego economists Jeffrey Clemens and Michael Wither) that’s been getting a lot of attention because it provides some new empirical evidence of the negative employment effects of the minimum wage increases in 2007, 2008 and 2009. And in addition to reducing employment opportunities for low-skilled workers, the researchers found that minimum wage increases also significantly reduced those workers’ upward, economic mobility to higher paying jobs by reducing “access to opportunities for accumulating work experience.”
Translation: If you’re not working, or your hours have been reduced, or your on-the-job training is reduced because of the 41% minimum wage hike, you’re not acquiring the job skills and experience that would allow you to move to a higher-than-minimum wage job over time. Here’s the paper’s conclusion:
We investigate the effects of recent federal minimum wage increases on the employment and income trajectories of low-skilled workers. While the wage distribution of low-skilled workers shifts as intended, the estimated effects on employment, income, and income growth are negative. We infer from our employment estimates that minimum wage increases reduced the national employment-to-population ratio by 0.7 percentage point between December 2006 and December 2012. As noted above, this accounts for 14 percent of the national decline in the employment-to-population ratio over this period.
We also present evidence of the minimum wage’s effects on low-skilled workers’ economic mobility. We find that binding minimum wage increases significantly reduced the likelihood that low-skilled workers rose to what we characterize as lower middle class earnings. This curtailment of transitions into lower middle class earnings began to emerge roughly one year following initial declines in low wage employment. Reductions in upward mobility thus appear to follow reductions in access to opportunities for accumulating work experience.
For an excellent, readable summary of the NBER paper, see this review by James Hamilton.
Most of the discussion and research on the minimum wage focuses on the negative employment effects of higher mandated wages, i.e. the negative effects on the demand for low-skilled and unskilled labor. The Law of Demand tells us that as the wage (price) of low-skilled/unskilled is artificially increased through legislation, the quantity demanded for those labor services by employers will fall. Period. Like in the NBER working paper above.
But there’s also an important supply-side effect of the minimum wage that receives much less attention, but significantly contributes to a higher jobless rate for teenagers and reduces the long-term job and career opportunities for that group of workers. The Law of Supply tells us that higher wages for unskilled and low-skilled workers will increase the quantity supplied of those labor services. One group of unskilled workers who are willing to supply more labor services following minimum wage increases are high school students who drop out of school to seek employment at the artificially mandated higher wage levels. The attraction to higher wages from minimum wage legislation reduces high school completion rates for some students with limited skills, who are then disadvantaged with lower wages and career opportunities over the long-run if they never finish high school.
Here are the conclusions from two different research papers that found empirical evidence of an upward sloping supply curve for unskilled high school workers and a positive relationship between minimum wage hikes and the number of students dropping out of high school.
2. “Minimum wages and skill acquisition: another look at schooling effects” by David Neumark and William Wascher (Economics of Education Review, 2002):
This paper takes another look at evidence on the effects of minimum wages on schooling, seeking to reconcile some of the contradictory results in recent research. We first examine evidence using CPS data from the late 1970s through the 1980s, a period that was characterized by many state-level minimum wage increases and received considerable attention from researchers studying minimum wages. In addition, we report results including data for the 1990s, in order to bring our estimates up to date. Our findings consistently point to negative effects of minimum wages on school enrollment, and indicate that these estimated effects are in general not very sensitive to how enrollment is measured in the CPS and are sometimes as strong or stronger using an enrollment measure that has been proposed in recent research. This bolsters the evidence of negative effects of minimum wages on enrollment from a number of recent studies, as well as some older ones, and counters claims that appeared to overturn at least some of this evidence.
Thus, our reading of the recent literature (including our work as well as that by Chaplin et al., 2002) is that the minimum wage reduces the proportion of teenagers in school. Moreover, our new evidence is consistent with our previous finding that increases in the minimum wage result in substitution by employers toward enrolled teenagers and in a significant increase in the proportion of non-enrolled teenagers without a job. Coupled with research on the effects of minimum wages on training, we regard the weight of the evidence as most consistent with minimum wages reducing skill acquisition among the young.
3. “Minimum wages and school enrollment of teenagers: a look at the 1990’s” by Duncan D. Chaplin, Mark D. Turner and Andreas D. Pape (Economics of Education Review, 2001):
In this paper we estimate the associations between minimum wages and high school continuation ratios over time and across states. We use data covering all public school students in the US. This provides us with much more precise estimates than could be obtained using data on samples of students. We find evidence that increasing the minimum wage lowers continuation ratios for grades 9–10 in states with drop out ages under 18. This suggests that these policies may have the unintended negative consequence of diverting some young people from continuing with their education.
The costs and benefits of changing the minimum wage through its effect on school enrollment depend in part on the benefits of working during high school. Chaplin and Hannaway (1999) show that high school employment may be beneficial in the long run, even if it increases the risk of dropping out, especially for at-risk youth. On the other hand, most students are probably much better off staying in high school even if they are working. For these reasons we believe that our results suggest that employment policies be adjusted to better ensure that teenagers remain in high school. Increasing the drop out age would be one means of accomplishing this goal. Indeed, this result is also supported by the work of Neumark and Washer (2003). Alternatively requiring parental and/or school permission for employment (as is often done for sports participation or forobtaining a GED) would be another way to ensure that teenagers are not taking too much time away from their education in order to work. Finally one could further restrict the hours that teenagers are allowed to work when school is in session. In any case, our results suggest that the trade-offs between employment and school enrollment for teenagers should be kept in mind when increases to the minimum wage are being considered.
Bottom Line: Despite what politicians and progressives might think, the laws of supply and demand, like the law of gravity, are not optional. Those basic fundamental economic laws can be ignored, but they can’t be avoided. Economic theory and empirical evidence tell us that higher mandated artificial minimum wages for unskilled workers will have predictable and unavoidable negative consequences for unskilled workers through reduced employment opportunities in the short run, and additional long-run adverse effects on long-term skill acquisition and educational outcomes, and ultimately reduced job and career opportunities. The three research papers summarized above provide empirical evidence for those negative demand and supply side effects of higher minimum wages.