April 27, 2015
New York Times relies on unrepresentative anecdotes and flawed study to provide slanted coverage of legal education (Michael Simkovic)
Just when you thought The New York Times was rounding the corner and starting to report responsibly about legal education based on hard data and serious labor economics studies, their reporting reverts to the unfortunate form it has taken for much of the last 5 years*—relying on unrepresentative anecdotes and citing fundamentally flawed working papers to paint legal education in a negative light.
Responsible press coverage would have put law graduate outcomes in context by noting that:
(1) law graduates continue to do better in terms of employment (both overall and full time) and earnings than similar bachelor’s degree holders, even in an economy that has generally been challenging for young workers
(2) law students, even from some of the lowest ranked and most widely criticized law schools, continue to have much lower student loan default rates than the national average across institutions according to standardized measurements reported by the Department of Education
(3) law graduate earnings and employment rates typically increase as they gain experience
(4) Data from After the JD shows that law graduates continue to pay down their student loans and approximately half of graduates from the class of 2001 paid them off completely within 12 years of graduation
Instead, The New York Times compares law graduate outcomes today to law graduate outcomes when the economy was booming. But not all law graduates. The Times focuses on law graduates who have been unusually unsuccessful in the job market or have unusually large amounts of debt. For example, The New York Times focused on a Columbia law school graduate working as an LSAT tutor** as if that were a typical outcome for graduates of elite law schools. But according to the National Law Journal, two-thirds of recent Columbia graduates were employed at NLJ 250 law firms (very high paying, very attractive jobs),*** and the overwhelming majority of recent Columbia graduates appear to work in attractive positions. (Columbia outcomes are much better than most, but the negative outcomes discussed in The New York Times are substantially below average for law graduates as a whole).
In Timing Law School, Frank McIntyre’s and I analyze long term outcomes for those who graduated into previous recessions, using nationally representative data and well-established econometric methods. Our results suggest that law graduates continue to derive substantial benefits from their law degrees even when graduating into a recession. The recent recession does not appear to be an exception. (See also here and here). This analysis is not mentioned in the recent The New York Times article, even though it was cited in The New York Times less than a month ago (and alluded to in The Washington Post even more recently).
The implication of The New York Times’ story “Burdened With Debt, Law School Graduates Struggle in Job Market” is that there is some law specific problem, when the reality is that the recession continues to negatively affect all young and inexperienced workers and law graduates continue to do better than most. Law school improves young workers’ chances of finding attractive employment opportunities and reduces the risk of defaulting on debt. The benefits of law school exceed the costs for the overwhelming majority of law school graduates.
The New York Times relies heavily on a deeply flawed working paper by Professor Deborah Merritt of Ohio State. Problems with this study were already explained by Professor Brian Galle:
“My problem is that instead DJM wants to offer us a dynamic analysis, comparing 2014 to 2011, and arguing that the resulting differential tells us that there has been a "structural shift" in the market for lawyers. It might be that the data exist somewhere to conduct that kind of analysis, but if so they aren't in the paper. Nearly all the analysis in the paper is built on the tend line between DJM's 2014 Ohio results and national-average survey results from NALP.
Let me say that again. Almost everything DJM says is built on a mathematical comparison between two different pools whose data were constructed using different methods. I would not blame you if now stopped reading."
In other words, it is difficult to tell whether any differences identified by Professor Merritt are:
(1) Due to differences between Ohio and the U.S. as a whole
(2) Due to differences in methodology between Merritt, NALP, and After the JD
(3) Actually due to differences between 2011 and 2014 for the same group
After Professor Galle’s devastating critique, journalists should have been extremely skeptical of Merritt’s methodology and her conclusions. Professor Merritt’s response to Galle’s critique, in the comments below his post, is not reassuring:
“Bottom line for me is that the comparison in law firm employment (62.1% for the Class of 2000 three years after graduation, 40.5% for the lawyers in my population) seems too stark to stem solely from different populations or different methods—particularly because other data show a more modest decline in law firm employment over time. But this is definitely an area in which we need much, much more research.”
Judging from this response and the quotes in The New York Times, Merritt appears to be doubling down on her inapposite comparisons rather than checking how much of her conclusions are due to potentially fatal methodological problems. What Professor Merritt should have done is replicate her 2014 Ohio-only methodology in 2000/2001 or 2010/2011, compared the results for Ohio only at different points in time, and limited her claims to an analysis of the Ohio legal employment market.
There are additional problems with Professor Merritt’s study (or at least the March 11 version that I reviewed).****
- Ohio is not a representative legal employment market, but rather a relatively low paying one where lawyers comprise a relatively small proportion of the workforce.
- A disproportionate share of the 8 or 9 law schools in Ohio (9 if you include Northern Kentucky) are low ranked or unranked, and this presumably is reflected in their employment outcomes.
- Merritt’s sample is subject to selection bias because of movement of the most capable law graduates out of Ohio and into higher paying legal markets. Ohio law graduates who do not take the Ohio bar after obtaining jobs in Chicago, New York, Washington D.C., or other leading markets will not show up in Merritt’s sample.
- Whereas Merritt concludes that law graduate outcomes have not improved, the data may simply reflect the fact that Ohio is a less robust employment market than the U.S. as a whole.
- Merritt’s analysis of employment categories does not take into account increases in earnings within employment categories. After the JD and follow-ups suggests that these within-category gains are substantial, as does overall increases in earnings from Census data.
- Merritt makes a biased assumption that anyone she could not reach is unemployed instead of gathering additional information about non-respondents and weighting the results to take into account response bias. Law schools may have been more aggressive in tracking down non-respondents than Professor Merritt was.
For the benefit of those who are curious, I am making my full 8 page critique of Professor Merritt's working paper available here, but please keep in mind that it was written in mid March and Professor Merritt may have addressed some of these issues in more recent versions of her paper. If that is the case, I trust that she’ll highlight any changes or improvements in a blog post response.
* A few weeks ago I asked a research assistant (a third year law student) to search for stories in The New York Times and Wall Street Journal about law school. Depending on whether the story would have made my research assistant more likely or less likely to want to go to law school when he was considering it or would have had no effect, he coded the stories as positive, negative, or neutral. According to my research assistant, The New York Times reported 7 negative stories to 1 positive story in 2011 and 5 negative stories to 1 positive story in 2012. In 2013, 2014, and 2015, The New York Times coverage was relatively balanced. In aggregate over the five-year period The New York Times reported about 2 negative stories for every 1 positive story. The Wall Street Journal’s coverage was even more slanted—about 3.75 negative stories for every positive story—and remained heavily biased toward negative stories throughout the five-year period.
** Professor Stephen Diamond notes the LSAT tutor’s relatively high hourly wage, more lucrative opportunities the tutor claims he turned down, and how the tutor describes his own work ethic.
*** For the class of 2010, the figure at Columbia was roughly 52 percent 9 months after graduation, but activity in the lateral recruitment market suggests things may be looking up.
**** The comments that follow summarize a lengthy (8 page) critique I sent to Professor Merritt privately in mid March after reviewing the March 11 draft of her paper. I have not had a chance to review Professor Merritt’s latest draft, and Professor Merritt may have responded to some of these issues in a revision.
April 27, 2015 in Advice for Academic Job Seekers, Guest Blogger: Michael Simkovic, Law in Cyberspace, Legal Profession, Of Academic Interest, Professional Advice, Science, Student Advice, Web/Tech, Weblogs | Permalink
April 21, 2015
At the faculty lounge, Professor Bernard Burk of the University of North Carolina echoes questions raised earlier by Professor Merritt of Ohio State about whether it is unethical or misleading for law schools to report employment using the international standard definition of employment. I have discussed these issues extensively before.*
Employment statistics are primarily useful for purposes of comparing alternatives. Comparison requires standard measurements. Standardization is efficient because it reduces the number of definitions that must be learned to use data. The standard definition of employment is meaningful and useful because, notwithstanding preferences for particular kinds of work, a job of some kind is generally preferable to no job at all. This does not mean that employment is the only measurement one should consider, but rather that it is a useful measurement.
Because international standards exist, it is not necessary to explain to a college graduate what a centimeter means when describing the length of an object. Similarly it is not necessary to explain to college graduates contemplating law school what employment means when using the international standard definition of employment.**
College educated individuals who are unfamiliar with standard terminology can easily look up or inquire about the relevant definitions, and once they have learned, can begin to understand a world of data. The standard definitions of employment and unemployment can be quickly discovered through intuitive internet searches. (see searches for unemployment and employment definitions) These definitions are neither obscure nor technically challenging.
In addition, many law schools disclose bar passage rates that are lower than their employment rates. It seems doubtful that many college educated adults contemplating law school—in particular, the subset basing their decisions on outcome data such as employment and bar passage rates—would assume that every law graduate who is employed shortly after graduation is working as a lawyer when many of those graduates cannot legally practice law.
Critiquing international standardized measurements as inherently immoral is not without precedent.
According to Martin Gardner, during the 1800s, a U.S. group attacked the French metric system as atheistic and immoral.
“The president of the Ohio group, a civil engineer who prided himself on having an arm exactly one cubit in length, had this to say . . . : "We believe our work to be of God; we are actuated by no selfish or mercenary motive. We depreciate personal antagonisms of every kind, but we proclaim a ceaseless antagonism to that great evil, the French Metric System. . .The jests of the ignorant and the ridicule of the prejudiced, fall harmless upon us and deserve no notice. . . It is the Battle of the Standards. May our banner be ever upheld in the cause of Truth, Freedom, and Universal Brotherhood, founded upon a just weight and a just measure, which alone are acceptable to the Lord." “
“A later issue printed the words and music of a song, the fourth verse of which ran:
Then down with every "metric" scheme
Taught by the foreign school,
We'll worship still our Father's God!
And keep our Father's "rule"!
A perfect inch, a perfect pint,
The Anglo's honest pound,
Shall hold their place upon the earth,
Till time's last trump shall sound!”
Many thoughtful people believe the U.S.’s non-standard approach to measurement undermines U.S. competitiveness in science, math, engineering, and industry. Time is wasted learning and converting to and from a redundant and inefficient measurement system. This entails opportunity cost and leads to unnecessary and avoidable errors.
Law schools, the American Bar Association, and the National Association for Law Placement would be better served by using standard definitions for labor market measurements when standard definitions are available and widely in use elsewhere, or at least labeling non-standard definitions with names that will not be readily confused with standard definitions.
The ABA currently requires law schools to describe individuals as “Unemployed” who under standard definitions would be defined as either “Not in Labor Force” or “Unemployed.” In other words, “unemployment” as reported under ABA definitions will be higher than unemployment under the standard and most widely used government definition. A number of people have been confused by this, incorrectly claiming that “unemployment” for law graduates is unusually high in comparison to everyone else. In fact, under consistent measurements, the fraction of recent law graduates who are employed is higher than the overall proportion of the population that is employed. (Law graduates also do relatively well on the percent employed full-time).
I agree with Professor Burk that additional information about occupational categories could be useful to some users of data. However, I do not agree that presenting standard summary statistics is inherently misleading or unethical, particularly for the sophisticated audience using the data —college educated, internet savvy adults.
April 11, 2015
Deborah Merritt and Kyle McEntee conflated “response rates” with nonresponse bias and response bias. After I brought this error to light, Professor Merritt explained that she and Mr. McEntee were not confused about basic statistical terminology, but rather were being intentionally vague in their critique to be more polite* to the law schools.
Professor Merritt also changed the topic of conversation from Georgetown’s employment statistics—which had been mentioned in The New York Times and discussed by me, Professor Merritt, and Kyle McEntee—to the employment statistics of the institution where I teach.**
What Professor Merritt meant to say is that law schools have not been properly weighting their data to take into account nonresponse bias. This is an interesting critique. However, proper weights and adjustments to data should take into account all forms of nonresponse bias and response bias, not just the issue of over-representation of large law firms in NALP salary data raised by Professor Merritt.
While such over-representation would have an effect on the mean, it is unclear how much impact, if any, it would have on reported medians—the measure of central tendency used by The New York Times and critiqued by Mr. McEntee.
Other biases such as systematic under-reporting of incomes by highly educated individuals,*** under-reporting of bonuses and outside income, and the like should be taken into account.**** To the extent that these biases cut in opposite directions, they can offset each other. It’s possible that in aggregate the data are unbiased, or that the bias is much smaller than examination of a single bias would suggest.
Moreover, focusing on first year salaries as indicative of the value of a lifetime investment is itself a bias. As The Economic Value of a Law Degree, showed, incomes tend to rise rapidly among law graduates. They do not appreciably decrease, either, until the fourth decade of employment.
If Professor Merritt’s view is that differences between NALP, ABA, and U.S. Census Bureau data collection and reporting conventions make law school-collected data more difficult to compare to other data sources and make law school data less useful, then I am glad to see Professor Merritt coming around to a point I have made repeatedly.
I have gone further and suggested that perhaps the Census Bureau and other government agencies should be collecting all data for graduate degree programs to ensure the accuracy and comparability of data across programs and avoid wasting resources on duplicative data collection efforts.
This could also help avoid an undue amount of focus on short-term outcomes, which can be misleading in light of the rapid growth of law graduate earnings as they gain experience. The inappropriate focus on the short term can be misleading if students are not aware of the growth trajectory and how it compares to the growth trajectory of likely earnings without a law degree.
** This tactic, bringing up the employment statistics of the institution where those whom she disagrees with teach, is something of a habit for Professor Merritt. See her response Anders Walker at St. Louis).
*** Law graduates outside of the big firms are highly educated, high-income individuals compared to most of the rest of individuals in the United States. That is the benchmark used by researchers when they identified the reporting biases in census data that lead to under-reporting of incomes.
**** The risk of under-reporting income in law may be particularly high because of opportunities for tax evasion for those who run small businesses or have income outside of their salary.
UPDATE (4/14/2015): I just confirmed with NALP that their starting salary data does not include end of year bonuses.
April 10, 2015
Did law schools behave unethically by providing employment and earnings information without simultaneously reporting survey response rates? Or is this standard practice?
The answer is that not reporting response rates is standard practice in communication with most audiences. For most users of employment and earnings data, response rates are a technical detail that is not relevant or interesting. The U.S. Government and other data providers routinely report earnings and employment figures separate from survey response rates.*
Sometimes, too much information can be distracting.** It’s often best to keep communication simple and focus only on the most important details.
Nonresponse is not the same thing as nonresponse bias. Law school critics do not seem to understand this distinction. A problem only arises if the individuals who respond are systematically different from those who do not respond along the dimensions being measured. Weighting and imputation can often alleviate these problems. The critics’ claims about the existence, direction, and magnitude of biases in the survey data are unsubstantiated.
High non-response rates to questions about income are not a sign of something amiss, but rather are normal and expected. The U.S. Census Bureau routinely finds that questions about income have lower response rates (higher allocation rates) than other questions.
Law school critics claim that law school graduates who do not respond to questions about income are likely to have lower incomes than those who do respond. This claim is not consistent with the evidence. To the contrary, high-income individuals often value privacy and are reluctant to share details about their finances.***
Another potential problem is “response bias”, in which individuals respond to survey questions in a way that is systematically different from the underlying value being measured. For example, some individuals may under report or over-report their incomes.
The best way to determine whether or not we have nonresponse bias or response bias problems is to gather additional information about non-responders and responders.
Researchers have compared income reported to Census surveys with administrative earnings data from the Social Security Administration and Internal Revenue Service. They find that highly educated, high-income individuals systematically under-report their incomes, while less educated, lower income individuals over-report. (Assuming the administrative data is more accurate than the survey data).
Part of the problem seems to be that bonuses are underreported, and bonuses can be substantial. Another problem seems to be that high-income workers sometimes report their take-home pay (after tax withholding and deductions for benefits) rather than their gross pay.
Other studies have also found that response bias and nonresponse bias lead to underestimation of earnings and employment figures.
In other words, there may indeed be biases in law school earnings data, but if there is, it is likely in the opposite direction of the one the law school critics have claimed.
Of course, the presence of such biases in law school data would not necessarily be a problem if the same biases exist in data on employment and earnings for alternatives to law school. After all, earnings and employment data is only useful when compared to a likely alternative to law school.
As with gross employment data, the critics are yet again claiming that an uncontroversial and nearly universal data reporting practice, regularly used by the United States Government, is somehow scandalous when done by law schools.
The only thing the law school critics have demonstrated is their unfamiliarity with basic statistical concepts that are central to their views.
* Reporting earnings and employment estimates without response rates in communication intended for a general audience—and even some fairly technically sophisticated audiences—is standard practice for U.S. government agencies such as the U.S. Census Bureau and the U.S. Department of Labor, Bureau of Labor Statistics. A few examples below:
- Earnings and unemployment by education level
- Unemployment rates
- Employment population ratio
- Tabular summaries from
** Information on response rates is available for researchers working with microdata to develop their own estimates, and for those who want to scour the technical and methodological documentation. But response rates aren’t of much interest to most audiences.
*** After the JD researchers noted that young law graduates working in large urban markets—presumably a relatively high-income group—were particularly reluctant to respond to the survey. From After the JD III:
“Responses . . . varied by urban and rural or regional status, law school rank, and practice setting. By Wave 2, in the adjusted sample, the significant difference between respondents and nonrespondents continued to be by geographic areas, meaning those from larger legal markets (i.e. New York City) were less likely to respond to the survey. By Wave 3, now over 12 years out into practice, nonrespondents and respondents did not seem to differ significantly in these selected characteristics.”
In the first wave of the study, non-respondents were also more likely to be male and black. All in all, it may be hard to say what the overall direction of any nonresponse bias might be with respect to incomes. A fairly reasonable assumption might be that the responders and non-responders are reasonably close with respect to income, at least within job categories.
April 08, 2015
Opportunity costs and tradeoffs are foundational principles of micro-economics. Comparison between earnings with a law degree and earnings with likely alternatives to law school is the core of The Economic Value of a Law Degree.
In her recent post, Professor Merritt raises interesting questions about whether some students who now go to law school could have had more success elsewhere if they had majored in a STEM (Science Technology Engineering & Math) field rather than humanities or social sciences.
These questions, however, don’t invalidate our analysis. A percentage of those who major in STEM fields of course go on to law school, and our data suggest that they also receive a large boost to their earnings compared to a bachelor’s degree. Some studies suggest that among those who go to law school, the STEM and economics majors earn more than the rest.
Research on college major selection reveals that many more individuals intend to major in STEM fields than ultimately complete those majors. STEM/Econ majors who persist have higher standardized test scores than humanities/social science majors at the same institution and also higher scores than those who switch from STEM/Econ to humanities or social science. Those who switch out of STEM received lower grades in their STEM classes than those who persist. Compared to Humanities and Social Science majors, the STEM majors spend more time studying, receive lower grades, and take longer to complete their majors.
In other words, many of the individuals who end up majoring in the humanities and social sciences may have attempted, unsuccessfully, to major in STEM fields. (For a review of the literature, see Risk Based Student Loans and The Knowledge Tax).
In The Economic Value of a Law Degree, Frank McIntyre and I investigated whether the subset of humanities majors who go to law school had unusually high earning potential and found no evidence suggesting this. The humanities majors who attend law school are about as much above the average humanities major in terms of earning potential as the STEM majors who attend law school are above the average STEM major.
In her recent post, Professor Merritt does not suggest alternatives to law school. Instead she selectively discusses occupations other than being a lawyer. These are generally very highly paid and desirable occupations, such as senior managerial roles, and many individuals who pursue such jobs will be unable to obtain them. In other words, these high paid jobs cited by Professor Merritt are not the likely alternative outcome for most of those who now go to law school if they chose another path. (Indeed, given the high earnings premium to law school including the 40 percent of graduates who do not practice law, a law degree probably increases the likelihood of obtaining highly paid jobs other than practicing law).
Occupations are outcomes. Education is a treatment. Students choose education programs (subject to restrictive admissions policies and challenges of completing different programs), but have more limited control over their ultimate occupation. Comparing occupations as if they were purely choices would be an error. Not every MBA who sets out to be a Human Resources Manager will land that job, just as not every law school graduate will become a lawyer at a big firm. Analysis of nationally representative data from the U.S. Census Bureau using standard statistical techniques from labor economics to consider realistic earnings opportunities--rather than selective focus on the very highest paid occupations tracked by the BLS--suggests that most of the folks who go to law school would be in much less attractive positions if they had stuck with a bachelor’s degree.
Frank McIntyre and I have previously noted the importance of additional research into how the value of a law degree varies by college major, and how the causal effect of different kinds of graduate degrees varies for different sorts of people.
We appreciate Professor Merritt’s interest in these issues and look forward to discussing them in the future when more methodologically rigorous research becomes available. Professor Merritt raises some interesting ancillary issues about response rates, but discussion of those issues will have to wait for a future post.
After my first post on employment definitions, a law school dean emailed me to suggest that perhaps the ABA felt it needed to be extra tough because it was worried it couldn’t trust some of the law schools to make close judgment calls in categorizing employment data.
The Census Bureau does a wonderful job collecting and reporting earnings and employment data using standard methods and definitions. Why not empower the Census Bureau to collect the relevant data about law schools and all programs of higher education?
There are two potential uses of employment outcome data of law school graduates.
(1) Comparing law school to alternatives to law school
(2) Comparing law schools to teach other
Census Bureau data is very well suited to the first use, and could also be useful for high level information about geography or rank even if not for comparisons of individual institutions. If the Current Population Survey and the American Community Survey—which have larger sample sizes and release data more regularly than the Survey of Income and Program Participation—were expanded to include questions on graduate education field (i.e., law, medicine, business) as well as level (B.A., PhD, Master’s, or Professional degree), and specific information about institution or caliber or geography of institution attended, that would go along way toward making law school data redundant. Census surveys will not have data on every law graduate, but as long as the sample is representative, that is not much of a problem.
The Census Bureau data would likely be superior to law school data in the most important respects because it would be comparable to data for those with other educational backgrounds. Since Census Bureau data is for a representative sample of the population, it would not encourage an unhealthy and misleading fixation on short-term outcomes.
As far as comparing individual law schools to each other, student loan default data from the Department of Education might serve this function at least as well as ABA data. To the extent we are concerned about poor outcomes at any particular law school, such poor outcomes will show up in higher student loan default rates.
Default rates will reflect outcomes not only for graduates, but also for those who fail to complete the program. This data would also not be sensitive to response bias on the low end—individuals who do not respond to their student loan bills will be counted as defaulters. Another advantage of this data is that it can be compared with other educational programs. Of course, we would still need to be mindful of the issue of selection versus causation. (Although we could quibble about how the Department of Education calculates its default rates (they publish more than one), the specifics of the definition are far less important that the fact that it is applied consistently across institutions, is used for comparative purposes, and is correlated with other validated measures).
If the Department of Education required colleges and universities to release separate default rate data for every field of graduate study (and perhaps for every college major), that would go a long way to helping inform students and increasing comparability of information about risk levels across programs. (I’ve discussed the merits of this kind of granular disclosure before).
The data won’t capture differences in the boost to earnings across law schools for students in the middle or high end of the distribution, since relatively few students default on their loans. It also won’t tell us anything about the students who don’t need to borrow. Nor will it tell us which schools have the strongest alumni networks in specific geographies or industries. That purpose might be better served by expanding longitudinal studies like After the JD, Baccalaureate and Beyond, National Longitudinal Survey of Youth, and the National Survey of College Graduates to include larger samples, better information about pre-law school differences in characteristics, and more long term information on post-graduate earnings and employment.
The Census Bureau’s ethics and incentives are unimpeachable. Putting data collection in its capable hands and into the hands of similar agencies charged with broad-based data collection would enable these agencies to do more of what they do best and free law schools from the burdens of a task they may not be well equipped to handle.
Resources that are now wasted collecting very precise but not very useful data about initial outcomes for law graduates could instead be redeployed to analyzing the higher quality data. (Or if we still think short term ABA and NALP data provide incremental value that exceeds the costs of collecting, reporting, and interpreting the data—and the costs of predictable misinterpretation and misuse—we could have that much more data to work with).
Food for thought.
April 07, 2015
Recently, The New York Times reported on law school and the legal profession based on hard data and peer reviewed research rather than anecdote and innuendo. The New York Times came to the conclusion that anyone looking honestly at the data would naturally come to—law school seems to be a pretty good investment, at least compared to a terminal bachelor’s degree.
Mr. McEntee suggests incorrectly that The New York Times reported Georgetown’s median private sector salary without providing information on what percentage of the class or of those employed were working in the private sector. (Mr. McEntee also seems to be confused about the difference between response rates—the percentage of those surveyed who respond to the survey or to a particular question—and response bias—whether those who respond to a survey are systematically different along the measured variable from those who do not).
The New York Times wrote:
Last year, 93.2 percent of the 645 students of the Georgetown Law class of 2013 were employed. Sixty percent of the 2013 graduates were in the private sector with a median starting salary of $160,000.
Deborah Merritt disputes the accuracy of these numbers, suggesting it is 60 percent of the 93.2 percent of the graduating class who were employed that were employed in the private sector. This would come to 56 percent of the class employed in the private sector and is a small enough difference that The New York Times may have simply rounded up.
In any case, it is clear that The New York Times provided information about the percent of graduates working in the private sector.
Mr. McEntee also repeats the odd claim that by reporting employment numbers that appear to be close to consistent with the standard definition of “employment” established by the U.S. Census Bureau and promulgated internationally by the International Labor Organization, The New York Times is somehow misleading its readers.
To the contrary, it is Mr. McEntee’s non-standard definitions of employment, taken out of context, that are likely to mislead those attempting to compare law school statistics to the employment statistics of the next best alternative. Mr. McEntee discusses full-time employment statistics for law schools without noting that the full-time employment rate for law graduates is higher than the full-time employment rate for bachelor’s degree holders with similar levels of experience and backgrounds under consistent definitions and survey methods. And he overlooks the evidence that those who do not practice law still benefit from their law degrees.
Mr. McEntee also inaccurately describes my research with Frank McIntyre, claiming incorrectly that we do not take into account those who graduated after 2008. Timing Law School was specifically designed to address this limitation of our earlier research.
Timing Law School includes an analysis of two proxies for law school graduates from the American Community Survey: (1) young professional degree holders excluding those working in medical professions, and (2) young lawyers. This analysis includes individuals who graduated as recently as 2013, and finds no evidence of a decline in recent law graduates’ outcomes relative to those of similar bachelor’s degree holders. (See also here for a discussion of recent data for the subset of law graduates who work as lawyers).
Timing Law School also simulates the long term effects on the earnings premium of graduating into a recession based on the experiences of those who have graduated into previous recessions. The differences between graduating into a recession and graduating into an average economy are not very large (there is a large boost for those graduating into a boom, but booms and recessions are not predictable at the time of law school matriculation).
Moreover, in Timing Law School we find that fluctuations in short-term outcomes for recent graduates are not good predictors of outcomes for those who are currently deciding whether or not to enter law school; long term historical data is a better predictor.
The Economic Value of a Law Degree did not include data on those who graduated after 2008 because such data was not available in the Survey of Income and Program Participation. However, it did include earnings data through 2013, and found no evidence of the earnings premium for law graduates declining in recent years to below its historical average.
Frank and I have noted repeatedly that our analysis compares a law degree to a terminal bachelor’s degree and that we think an important area for future research is careful comparative analysis of alternate graduate degrees, being mindful of selection effects (read The Economic Value of a Law Degree or for the most recent example, see our post from two days ago). While a casual (i.e., not causal) examination of raw data suggests that a law degree likely compares reasonably well to most alternatives other than a medical degree, we’ve noted that it’s possible that more rigorous analysis will reveal that another graduate degree is a better option for some prospective law students, especially when subjective preferences are taken into account along with financial considerations.
Mr. McEntee claims incorrectly that when it comes to other graduate degrees, “McIntyre and Simkovic don’t know and don’t care; they’re convinced that the value of a law degree as immutable as the laws of nature.”
Mr. McEntee insists that law graduates, even at the higher ranked schools, will find it challenging to repay their student loans. However, data from After the JD shows that law school graduates from the class of 2000/2001 have been paying down their loans rapidly.
What about those who entered repayment more recently, when tuition was higher and job prospects less plentiful?
Data from the U.S. Department of Education shows that law students, even at low ranked law schools, remain much less likely to default than most student borrowers. This is true even though law students typically graduate with higher debt levels.
Indeed, The Economic Value of a Law Degree suggests that law graduates generally have higher incomes after taxes and after paying additional debt service than they likely would have had with a terminal bachelor’s degree, even before taking into account debt forgiveness available under Income Based Repayment plans.
Based in part on our research, private student lenders have noticed how unlikely law graduates are to fail to repay their loans. These lenders offer refinancing at substantially lower rates than those charged by the federal government, further reducing the costs of legal education for many graduates (while earning a profit in the process).
No matter what new information becomes available, Mr. McEntee insists that law school is financially disastrous. This is curious for a public figure who claims that his goal is providing prospective law students more accurate information about law school.
April 05, 2015
The choice of whether or not to go to law school is always a choice between law school and the next best alternative. College graduates do not vanish from the face of the earth if they choose not to go to law school. They still must find work, continue their education, or find some other source of financial support.
The question everyone who decides not to go to law school, and every critic of law schools, must answer is—what else out there is better?*
To enable prospective students to compare law school to the next best alternative, we need standardized measurements that apply to both law school and alternatives to law school.
Professor Merritt objects to the standard definition of employment used by the United States government, which she believes is too loose, since it includes an individual as employed if the individual works just one hour during the week of the interview. (This is also the international standard promulgated by the International Labor Organization and widely used around the world).
Using the standard definition of employment and consistent survey and reporting methods reveals that law graduates are more likely to be employed than similar bachelor’s degree holders.
The important thing is not the measurement itself, but rather the relative (causal) differences between law school and the next best alternative. Only by using consistent measurements for law school and the alternatives to law school can we understand those differences.
A single measurement like employment status may not provide all of the information we want. (As a discrete variable, employment status will contain less information than a continuous variable like earnings or hours of work). The solution is to use several standard measurements consistently to compare two different populations. For example, in addition to employment, we might consider work hours, the percent of individuals working “full-time” (i.e., more than 35 hours per week), earnings, or wages (earnings per hour).
In The Economic Value of a Law Degree, Frank McIntyre and I find that no matter which of these measurements we use, the results always point in the same direction. Law graduates participate more actively in the work force and are much better paid than similar bachelor’s degree holders.
If what students really care about is whether law school is a good investment financially, then no isolated measurement taken 9 or 10 months after graduation will provide much insight. (Especially since other educational programs and data collection agencies are not specifically collecting data 9 or 10 months after graduation).
To answer the investment question, we need estimates of the causal effect of education on the present value of lifetime earnings—what Frank and I try to do in The Economic Value of a Law Degree.
To the extent that measurements at or shortly after graduation are useful at all, it is only for purposes of comparison, and only then while being mindful of the differences between outcomes and causation.
Using non-standard definitions means that ABA data at best can facilitate comparisons between different law schools,** but cannot readily be used to compare law school to any alternative.
Professor Merritt argues that the American Bar Association should require law schools to use a uniquely stringent system of measuring employment. To demonstrate that the legal profession holds itself to a higher standard of ethics, law schools should report lower employment rates than everyone else by using less inclusive, non-standard definitions of employment.
I disagree with the premise that different definitions lead to higher standards. Professor Merritt’s proposal would mean that law school statistics cannot be compared to any other employment statistics, and if history is any guide, will contribute greatly to student confusion and error.
The right thing to do is to report standardized measurements so that law school statistics can be readily compared to statistics of other education programs, as well as used to compare law schools to each other.
* Another graduate degree might be better than law school for a particular individual, especially when preferences for certain kinds of education or work are taken into account along with differences in financial value added. One of the frontiers of labor economics research is comparative analysis of the causal effects of different kinds of graduate education.
** I have reservations about the extent to which ABA initial outcome data should be used to compare the value added by one law school to the value added by another. There are large differences between the student bodies of different law schools along dimensions that predict earning potential—standardized test scores, GPA, college quality and college major, socioeconomic status, and demographics. The differences between students matriculating to the highest and lowest ranked law schools appear to be much larger than the differences between the average college graduate and the average law student. While law schools disclose information about their entering classes, they do not reveal information about their graduates. Entering characteristics could be different from graduating characteristics for schools that accept large numbers of transfer students or have unusually high attrition. In addition, the average growth rate of earnings at different law schools might be different and comparing only initial earnings could lead to misleading results.
April 02, 2015
Paul Campos of the University of Colorado is once again confused by my research with Frank McIntyre. This time, the source of Professor Campos’s confusion is not present value calculations, but rather grant funding.
The Economic Value of a Law Degree was not funded through grants. No disclosure of grant funding appears in that article because there was no funding to disclose.
Two follow up studies, Timing Law School and an upcoming study about differences in the law earnings premium by college major, race and gender, are funded through grants from Access Group, Inc., a non-profit that provides financial education to students and schools and aims to promote broad access to education, and the Law School Admission Council (LSAC), which is an important provider of data and research about law schools (see here and here).
The funding provided through these grants is used to buy out time so that Frank and I can spend more time on research. I do not receive the money for my teaching buyout—Seton Hall is paid so that it can find replacements to teach the classes I would have taught. The grants also provide funding for research assistants, software and equipment, summer stipends, and conferences. The payments are scheduled over a two to three year period.
Frank and I are interested in methodological rigor, not in particular results or outcomes, which in any case are unknowable until after we analyze the data. We believe in maximizing the transparency of the methods we use for our research so that it can be replicated or challenged by future empirical researchers. There has never been any effort by LSAC or Access Group to influence or censor our results.
Frank and I are proud of our success securing funding from such highly regarded organizations. We trumpet their support in the first footnote of Timing Law School, and announced it in our first blog post about Timing Law School. I also list the grants and dollar amounts of each on my CV and on my LinkedIn page.
Curiously, Professor Campos and his followers seem to think that the fact that highly regarded non-profit organizations believe our research is worthy of funding is some sort of dirty secret. We’ve practically been shouting it from the rooftops, so I suppose we should thank him for pointing it out.
April 01, 2015
Recently, two criticisms have been leveled against law schools. The first is an economic critique—law school is not worth it financially compared to a terminal bachelor’s degree. This critique is incorrect for the overwhelming majority of law school graduates.
The second is a moral critique—that law schools behaved unethically or even committed fraud (see here, here, and here) by presenting their employment statistics in a misleading way. (While at least one of the 200+ American Bar Association (ABA) approved law schools misreported LSAT scores and GPAs of incoming students, and a former career services employee at another alleges specific misreporting of unemployment data at that law school, I am focusing here not on the outliers, but on the critique against all law schools generally).
The moral critique against law schools comes down to this: The law schools used the same standard method of reporting data as the U.S. Government.
According to the critics’ line of reasoning, “employment” means only full-time permanent work as a lawyer. Anything else should count as either “unemployment” or some special category of pseudo-unemployment (i.e., underemployment) . (This is apparently based on an incorrect belief that law school only benefits the subset of graduates who practice law).
Employment and unemployment statistics are not meaningful in a vacuum. They only become useful when they can be compared across time, for different groups, or for a different set of choices. For example, prospective law students might want to know that law school graduates are generally less likely to be unemployed or disabled than similar bachelor’s degree holders. (Frank McIntyre and I combine the unemployment and disability rates whenever possible because of research showing that disability is often a mask for unemployment, although we’d generally get similar results for relative rates if we just used unemployment).
To avoid confusion and ensure that data are comparable, the standard definitions used by the U.S. Government should be used when reporting employment statistics, unless there is an indication that non-standard definitions are being used.
The standard government definitions of “employment” and “unemployment” are the way we all use these words in ordinary speech when we say things like “the unemployment rate went down this year.” These are not obscure definitions. Googling “unemployment definition” and checking the first few results—Investopedia , Wikipedia, About.com, and the U.S. Bureau of Labor Statistics (BLS) website —will get you to the right answer.
So how does the United States government define “employment”?
The most commonly reported and cited official government employment statistics include individuals as “employed” whether such individuals are employed full-time or part-time, whether in permanent or nonpermanent positions, whether in jobs that do or do not require the level of education they have obtained.*
In other words, the U.S. Government counts individuals as employed even if they are employed in part-time, temporary jobs that do not require their level of education. Indeed, individuals count as employed even if they are self-employed or worked without pay in a family-owned business.
When the government reports education-level-specific employment statistics** it uses the same definitions and does not restrict employment to those who are employed in jobs that require their education level. Employment includes any employment, whether full-time or part-time, whether temporary or permanent, whether in a job that requires a given level of education or not.
What about the standard definition of “unemployment”?
Unemployment is not the absence of employment. Instead, there are three categories—employed, not-in-labor-force, and unemployed. An individual only counts as “unemployed” if he or she “had no employment during the reference week”, was “available for work, except for temporary illness” and recently “made specific efforts to find employment.”
Those who are not working and are not actively seeking work for whatever reason—for example, caring for dependents, disability, pursuing additional education—are not counted as part of the labor force. Unemployed persons as defined by CPS are used to calculate the widely cited “unemployment rate.” The unemployment rate is defined as unemployed persons as a percent of the labor force--in other words, excluding those who are neither working nor seeking work.***
Some law school critics have claimed that anyone who fails to respond to a survey about their employment status should be assumed to be unemployed. The Census and BLS disagree, and instead weight the data to account for non-respondents.
In addition to top-level information about employment status, some data sources such as the CPS may also include fields with more detailed information about full- or part-time work-status, industry or sector, and occupation. Law schools have also historically provided a detailed breakdown of employment categories shortly after graduation in the ABA-LSAC Official Guide To ABA-Approved Law Schools. In the last few years, law schools have provided even more detail in ABA-required disclosures. (We’ve previously noted some of the problems with focusing on employment outcomes shortly after graduation rather than long-term value added; The ABA's new employment data protocols have additional problems with their definition of "unemployed" discussed below ****). The National Association for Law Placement (NALP) also provides high level data and a more detailed breakdown.
The inclusion or non-inclusion of more detailed information does not alter the meaning of top-level information about employment status: the meaning of “employed” is established and well understood by users of employment data. Commonly used and cited employment statistics have been reported by the BLS from 1948 through the present, and are widely understood by users of employment data.
Indeed, the BLS has noted for decades in its Occupational Outlook Handbook that many law school graduates do not work as lawyers. Law schools and bar examiners publish bar passage rate statistics which clearly show that many recent law school graduates cannot legally be working as lawyers (unless everyone who failed a bar exam in one state passed a bar exam in another).
Comparing apples to apples using standard definitions reveals that law school graduates are doing relatively well compared to similar bachelor’s degree holders. By contrast, critics of law schools and plaintiffs lawyers have used non-standard definitions and compared apples to oranges.
It is not surprising that the courts have dismissed the lawsuits against law schools. If only the New York Times and the Wall Street Journal were as fair and judicious.
* The primary source of labor force statistics for the population of the United States is the Current Population Survey (CPS), sponsored jointly by the United States Department of Labor, Bureau of Labor Statistics and the United States Census Bureau (Census). CPS is the source of numerous high-profile economic statistics, including the national unemployment rate. CPS defines "Employed persons"* to broadly include anyone who has done any paid work during the week when it is measured, who worked for themselves or a family member, or who was temporarily absent from work.
“Employed persons”* as defined by CPS are used to calculate the “Employment-population ratio”. The Employment Population Ratio resembles the “Percent Employed” statistics reported by law schools.
“Employed Persons” includes:
- 16 years and over
- in the
- noninstitutional population
- who, during the reference week,
- did any work at all (at least 1 hour) as paid employees;
- worked in their own business, profession, or on their own farm,
- worked 15 hours or more as unpaid workers in an enterprise operated by a member of the family;
- all those who were not working
- but who had jobs or businesses
- from which they were temporarily absent
- because of
- bad weather,
- childcare problems,
- maternity or paternity leave,
- labor-management dispute,
- job training,
- other family or personal reasons,
- whether or not they were paid for the time off or were seeking other jobs. . . . “
** The BLS also reports Employment Population Ratios for specific education levels and age groups such as bachelor’s degree holders and above ages 25 to 34. These statistics are also reported by the United States Department of Education, National Center for Education Statistics. (To the extent economists have tried to define and measure “underemployment” (see here and here ), it appears to be as or more common among bachelor’s degree holders compared to similar law degree holders).
*** The “labor force” as defined by CPS consists only of persons who are either “employed” or “unemployed” under CPS definitions.
**** The ABA’s new data protocol counts individuals as “Unemployed” who would instead be considered “Not-in-labor-force” by the U.S. government. The ABA subcategory, “Unemployed—Seeking” is probably the closest to the standard definition of unemployment. This misalignment between ABA definitions and standard government definitions of unemployment could lead individuals comparing ABA data to standard and widely used government employment data to erroneously conclude that unemployment for law school graduates is higher relative to other groups than it really is.