Every Monday, the National Bureau of Economic Research, a nonprofit organization made up of some of North America’s most respected economists, releases its latest batch of working papers. The papers aren’t peer-reviewed, so their conclusions are preliminary (and occasionally flat-out wrong). But they offer an early peek into some of the research that will shape economic thinking in the years ahead. Here are a few of this week’s most interesting papers:
Authors: Jeffrey Clemens, Michael Wither
What they found: The rise in the minimum wage to $7.25 per hour from $5.15 per hour led to higher pay for low-skilled workers but fewer jobs for them — specifically, it reduced the share of employed adults by 0.7 percentage points between 2006 and 2012.
Why it matters: The economic research on minimum wage increases is contentious. After an increase in the minimum wage, it’s difficult to isolate the policy’s effects from pre-existing economic trends, such as whether the macroeconomy is in a recession or steadily growing. The researchers in this paper study the effects on employment and income for low-skilled workers during a period when the federal minimum wage was raised to $7.25 per hour. To simulate a controlled experiment — where of two groups, otherwise identical, one gets changed and the other does not — the authors looked at two groups of states and two groups of workers. There were states that already had a higher state-mandated minimum wage and those that did not; and there were workers paid $7.50 or more per hour (and only indirectly affected) and those earning wages under $7.50 per hour (and thus directly affected by the law). Using this quasi-experimental approach, the authors found that wages for low-skilled workers rose, but their probability of employment fell about 6 percent.
Key quote: “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. … This accounts for 14 percent of the national decline in the employment-to-population ratio over this period.”
Data they used: Survey of Income and Program Participation
Authors: Soohyung Lee, Lesley J. Turner, Seokjin Woo, Kyunghee Kim
What they found: Students at all-boys schools had better academic achievement than male students in mixed-gender classrooms at co-ed schools, who in turn had better achievement than male students in single-sex classes at co-ed schools. Girls’ academic achievement was unaffected by single-sex classrooms and schools.
Why it matters: In 2006, the U.S. Department of Education relaxed rules against single-sex teaching in public schools, opening up options for all-girls and all-boys classrooms and schools. But because the students who chose these settings did not do so randomly, it’s difficult to study the relative merits of single-sex education. The researchers of this paper, however, looked at the random assignment of South Korean middle school students into one of three settings: single-sex schools; mixed-gender classrooms at co-ed schools; and single-sex classrooms at co-ed schools. For girls, varying the gender composition in the classroom or of the whole school did not seem to have any effect on educational achievement. But for boys, those who attended all-boys schools improved 0.15 of a standard deviation compared to boys in mixed-gender classrooms at co-ed schools. The boys in mixed-gender classrooms did 0.10 of a standard deviation better than boys in single-sex classes at co-ed schools. Interestingly, the better results from all-boys schools were not due to gender composition in the classroom, but to more time studying.
Key quote: “We find that male students’ achievement is maximized by assignment to a single-sex school, and minimized by assignment to a single-sex class within a mixed-gender school. We also provide suggestive evidence that one channel through which single-sex schools affect male students’ achievement is through increasing students’ effort and time devoted to academic tasks. We can rule out differential teacher gender composition and school organization as explanations for differences in outcomes by school gender composition.”
Data they used: Random assignment of middle school students in Seoul.
Authors: Wojciech Kopczuk
What he found: The various approaches for measuring wealth inequality in the United States send conflicting signals. In particular, those methods that corroborate the results found by Thomas Piketty in his book “Capital in the Twenty-First Century” are different from the others.
Why it matters: It’s easier to statistically examine income inequality than wealth inequality because the data on incomes is better. For example, the Survey of Consumer Finances (SCF), conducted by the Federal Reserve, is just that — a survey, and some of the wealthiest people are unlikely to respond. To account for this, Piketty, the French economist whose “Capital in the Twenty-First Century” became an unexpected best-seller this year, developed innovative statistical methods for documenting wealth inequality in the U.S. His results showed high and rising wealth inequality. But in this paper, the author reassesses the methodological approaches to measuring wealth inequality in the U.S. There are three main approaches: the aforementioned survey data from the SCF; estate tax returns, which use taxes paid on inheritances to estimate wealth; and a “capitalization” method, which uses the capital income (e.g., stock dividends) reported in tax returns to estimate the individual’s stock of wealth. The first two methods show little increase in wealth inequality over the past few decades, whereas the capitalization method corroborates Piketty’s results. However, as the author explains, all three have their shortcomings.
Key quote: “The increased importance of self-made, busy, active individuals among top wealth-holders is a plausible conjecture for why there could be a trend toward non-response bias among the wealthiest in the Survey of Consumer Finance and difficulties in observing them on estate tax returns. It is also a plausible reason for why large capital incomes may be increasingly reflecting work rather than underlying assets. … Without taking a stand on which of the preceding stories is most empirically important, these changes can plausibly reconcile the differences in methods of estimating the concentration of wealth regardless of which one turns out to be closest to being right.”
Data he used: Survey of Consumer Finances; Internal Revenue Service data on estate taxes and capital income