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.
March 31, 2015
The Absence of Evidence for Structural Change: Growth in Lawyer Employment and Earnings (Michael Simkovic)
There have been a lot of doom-and-gloom reports about layoffs and collapsing job opportunities for lawyers. As we’ve noted before, the relevant question for valuing legal education is the boost to earnings from the law degree across occupations, not the more specific question of what is happening to lawyers, or even more specifically, big law firms.
But for the sake of argument, focusing more narrowly on the under-inclusive category of lawyers only, what does the data actually show about lawyer employment? Are doom-and-gloom predictions justified for lawyers even if not for law degree holders? According to many of the proponents of the structural change hypothesis, signs of structural change were showing up as early as 2010, or perhaps even as early as 2008. We now have several years of historical data beyond that point to consider whether their predictions, thus far, have proven correct.
Lawyer employment is growing. This is true both in absolute numbers, and also relative to overall employment. In other words, lawyers are becoming a larger share of the U.S. workforce.
The data in the chart above is from the U.S. Department of Labor, Bureau of Labor Statistics (BLS), Occupation Employment Statistics (OES), which is a survey of establishments (employers). The blue columns scaled to the left axis represents the absolute number of lawyers, while the red line scaled to the right axis represents lawyers as a percentage of the total labor force. As can be seen from the above chart, both numbers are trending upward.
One limitations of BLS OES is that it focuses on employees, not owners, and therefore excludes law firm partners and solo practitioners. Another leading source of data, the U.S. Census Bureau’s Current Population Survey (CPS), is a survey of households, and includes solos and law firm partners.
CPS shows much the same trend as BLS OES. Lawyer employment is increasing, both in absolute terms and as a share of total employment. The charts below show CPS data.
The leading government data sources show the same thing—growth in employment of lawyers is faster than (or at least as fast as) overall employment growth.
The practice of law is also becoming more lucrative, at least over the long term. According to a recent draft paper by Richard Sander and E. Douglass Williams, after controlling for changes in the demographic composition of the legal profession, Sander and Williams find long-term growth in real (inflation-adjusted) lawyer earnings. (Sander and Williams use IPUMS-CPS data, and focus on white males, since historical data is not as readily available for women and minorities who have joined the legal profession in large numbers only in recent years; To understand the importance of controlling for demographic changes in the profession, consider Simpson’s Paradox).
Data from the Sander and Williams study is provided in the chart below.
After 2010, the picture for lawyer earnings is more mixed. BLS OES data suggests modest declines in real earnings of lawyers of around 6 percent by 2014. By contrast, the CPS suggests modest real growth in lawyer incomes of around 3 percent by 2014. Overall, it’s likely that real lawyer earnings have been close to flat. Flat earnings are consistent with what has been happening elsewhere in the labor market (see here and here). Given lawyers’ highly advantageous starting position relative to most other occupations, flat earnings or even modest declines suggest that lawyers have maintained a large relative advantage even as they have grown in relative numbers. (It’s possible that incomes for lawyers may have become more dispersed over time, notwithstanding the averages—indeed, it would be surprising if that were not the case, given the general trend toward widening income dispersion across the economy).
As noted previously, changes in entry level earnings and employment, though larger than those for the profession as a whole, are consistent with changes at the entry level for the rest of the labor market and established historical patterns. Young law graduates continue to earn substantially more than young bachelor’s degree holders post 2008.
Within a few years of graduation, about as large a proportion of employed young professional degree holders were working as lawyers after 2008 as before 2008.
Some critics of legal education have focused on “legal services” (mostly law firms). This is not a good measure of either the value of a law degree, or of the labor market for lawyers. Most employees in “legal services” are not lawyers, but rather support personnel such as secretaries, paralegals, and business and technology specialists. Many lawyers and law degree holders work outside law firms.
Changes taking place in “legal services” might be affecting the non-lawyers who work there rather than the lawyers. Changes in “legal services” affecting lawyers could be offset by changes affecting lawyers working in other industries. In other words, legal work could be moving out of the law firms and in house or into other professional service firms such as accounting firms.
BLS and CPS data for “lawyers” provides a much clearer picture of the legal employment market, while law earnings premiums across occupations are the most useful measure of the value of a law degree.
Growth in earnings and employment has been slower in recent years than in the past, to be sure, but that is generally true across the economy. The case for massive structural change in the legal profession eroding the value of a law degree is not well supported by the data.
March 26, 2015
Some have claimed that deteriorating outcomes for recent law school graduates are a sign of permanent structural change in the legal industry and that these changes are reducing the value of legal education.
There are two important problems with this claim. First, the same changes are taking place across the labor market, and are not a law-specific problem. Indeed, the law degree has maintained its value relative to a bachelor’s degree. Second, entry-level employment and starting salaries are known to be volatile and cyclical, so large swings aren’t a sign of much of anything other than business as usual in a recession or boom.
The Economic Value of a Law Degree lacked data on those who graduated after 2008 because of limitations of the Survey of Income and Program Participation (SIPPP). Timing Law School supplements this data with additional information from the American Community Survey (ACS). Using ACS we look at young lawyers and young professional degree holders excluding those in medical occupations—two proxies for law graduates, one under inclusive, the other over inclusive. Both of these proxies (along with SIPP data) suggest that recent law graduates have maintained a large advantage relative to similar bachelor’s degree holders. The ACS data is presented below.
(A log earnings premium is similar to a percentage difference in earnings. A 0.6 log earnings premium means that young lawyers earn about 82 percent more than young bachelor's degree holders.)
What many in the press and some law professors mistook for a law-specific crisis was in fact a widely known phenomenon in labor economics—employment and salaries for inexperienced workers are more volatile and sensitive to economic cycles than employment and salaries for those with more experience.
Predicting structural change on the basis of established cyclical patterns is analogous to drawing conclusions about permanent climate change on the basis of temperature changes between summer and winter. Occasionally, the person making the prediction might get lucky and turn out to be right, but the evidence is weak, the analysis fails to test more plausible rival hypotheses, and the conclusion of permanent change is little more than a wild guess.
Climate Scientists are more careful than this. They use a back testing approach similar to the one Frank McIntyre and I use in Timing Law School. Back testing suggests that the prediction methods used to support the structural change hypothesis are baseless, at least with respect to such changes degrading the value of legal education.
Structural change can mean different things to different people. By structural change, some people may simply mean that subjectively, the practice of law feels different than it used to, not that law graduates are getting any less value for the money. Or they may mean more generally that the kind of work law graduates do is different, even if not relatively less well compensated. This softer, humanistic view of structural change may have merit, although once again, it may also reflect broader trends in the economy rather than law-specific issues.
Over the last two weeks I’ve discussed the case for structural change—Bureau of Labor Statistics projections, entry-level outcomes, etc.—and found little support for the hypothesis that the value of a law degree has permanently declined.
Next week I’ll discuss another pillar of the structural change argument—growth rates in the “legal services” industry.
Law schools and prospective law students may be paying more attention to employment outcomes shortly after graduation than this short-term data deserves. One potential use of the aggregate data about entry level employment and salaries is to assess whether now is a good or bad time to apply to law school. But fluctuations in employment outcomes for recent graduates do not predict fluctuations in employment outcomes 3 or 4 years in the future when those currently deciding whether to enroll would graduate.
Nevertheless, law students and the press pay close attention to the short-term outcome data. Starting salary data from the National Association for Law Placement (NALP) is covered by the press and is a good predictor of the number of law school applicants two years later (We assume one year lag for data collection and dissemination; one year lag to apply to law school).
Why are students responding to this data even though it does not predict their own short-term outcomes? And does the responsiveness of enrollment to short-term outcomes mean that law students care only about the short term?
Law students likely think more long term. If law students were so impatient that they only cared about one or a few years of earnings, it is doubtful that law students would have completed college, since college also makes sense only as a long-term investment. Indeed, students who were so focused on the short term might not even have finished high school. While temporal preferences can change over time, education appears to shift people toward thinking more long term. Aging from adolescence through the age of 30 is also associated with becoming more oriented toward the future.
Perhaps students are focused on the short term because they mistakenly believe that swings in short term outcomes predict more than they do. Students would not be alone in this error.
Some widely read back-of-the-envelope analyses started with initial salaries, assumed unrealistically low earnings growth along with high discount rates or an arbitrary payback period (lack of concern for the future) and reached the erroneous conclusion that going to law school does not make sense financially. (For a discussion see here; for examples of erroneous studies, see here and here )
Students may be focused on the short term because they mistakenly believe it predicts more than it does. Or they may focus on the short term because it is the only information that is readily available to them.
Legal educators and the press can and should make greater efforts to inform students of the long term as opposed to the short-term consequences of legal education. We should also shift the discussion away from raw outcomes and toward estimates of causation and value-added relative to the next best option.
This will be a challenge. Short-term raw outcome data is embedded in American Bar Association-required disclosures, in NALP’s data collection efforts and in the U.S. News rankings. Thinking in value-added terms requires us all to understand basic principles of causal inference and labor economics. But shifting toward long-term value added is ultimately the right thing to do if we are serious about providing students with meaningful disclosure and facilitating informed decision making.
This is not meant to justify indifference to the plight of young people who have suffered the misfortune of graduating into an unfavorable economic climate over the last several years. To help alleviate youth unemployment, we must understand that the cause of this misfortune is the macro-economy, not higher education. Education is an important part of the solution. Among those who are young and inexperienced, those with more education continue to do better in the labor market than those with less, and this difference appears to be largely caused by the differences in level of education.
Insurance programs like income-based repayment of student loans and flexible and extended repayment plans can help young people manage the unpredictable and uncontrollable risk that they might happen to graduate into a bad economy. If this insurance leads to more people pursuing higher education, earning higher incomes, and paying more taxes, it will benefit not only students and educators, but also the federal government and the broader economy.
March 25, 2015
Many legal educators believe that shrinking class sizes will help the students they do admit find higher paid work more easily and boost the value of legal education. They reason that if the supply of law graduates shrinks, then the market price law graduates can command should increase.
According to another hypothesis, now popular in the press, a decline in the number of law school applicants reflects the wisdom of the crowds. Students now realize that a law degree simply isn’t worth it, and smaller class sizes reflect a consensus prediction of worse outcomes for law graduates in the future.
Frank McIntyre and I investigated whether changes in law cohort size predict earnings premiums. Historically, they have not. Not for recent graduates, and not for law graduates overall. Nor have changes in cohort size predicted much of anything about the entry-level measures used by the National Association for Law Placement (NALP)—starting salary, initial employment, initial law firm employment.
How can both of these theories be wrong? One possibility is that they are both right, but the two effects offset each other. This seems unlikely however. If neither macroeconomic data nor Bureau of Labor Statistics (BLS) employment projections can predict law employment conditions at graduation, then how likely is it that recent college graduates with less information and less expertise could make a better prediction?
A more likely possibility is that there are other factors at play that prevent any strong predictions about the relationship between cohort size and outcomes / value added. For example, law schools may become less selective as cohort size shrinks and more selective as it increases. In addition, the resources available to law schools, and therefore the quality of education and training they are able to provide, may also change with cohort size. Since physical facilities expenses are not particularly variable in the ordinary course, most budgetary adjustments at law schools presumably take place with respect to personnel.
Anecdotally, many law schools appear to be managing the recent decline in enrollments by shrinking their faculties and administrations and using remaining personnel to teach classes and perform functions outside of their areas of expertise. Reduced specialization and a lack of economies of scale could affect the quality of service provided to students, offsetting any benefits to students from less competition at graduation.
Previous research in labor economics has found that resources per student are an important predictor of value added by college education, and that the use of adjuncts can lead to worse outcomes for students. (See here for a review)
Much of this is speculative—we do not yet understand why changes in cohort size do not predict law graduate outcomes, only that they do not predict outcomes. Given the historical data, it is probably not advisable to read too much into what the decline in law school enrollment means for students who will graduate over the next few years.
Instead, we should focus on the long-term historical data and the value of a law degree across economic cycles and enrollment levels.
March 24, 2015
UPDATE: As of March 20, applicants are now down only 2.9% from last year. My guess is that we have hit bottom in terms of the applicant decline.
March 23, 2015
Labor economists have long cautioned against the misuse of Bureau of Labor Statistics (BLS) employment projections.
In 2004, Michael Horrigan at the BLS explained that the BLS projections should not be used to value education or to attempt to predict shortages or surpluses of educated labor. Instead, the value of education should be measured based on earnings premiums—the measure used in The Economic Value of a Law Degree and Timing Law School.
The general problem with addressing the question whether the U.S. labor market will have a shortage of workers in specific occupations over the next 10 years is the difficulty of projecting, for each detailed occupation, the dynamic labor market responses to shortage conditions. . . . Since the late 1970s, average premiums paid by the labor markets to those with higher levels of education have increased.
It is the growing distance, on average, between those with more education, compared with those with less, that speaks to a general preference on the part of employers to hire those with skills associated with higher levels of education.
The BLS takes the same position in its FAQ. The BLS does not project labor shortages or surpluses.
In 2006, Richard Freeman back-tested the BLS projections and found that “the projections of future demands for skills lack the reliability to guide policies on skill development.”
The BLS employment projections are not only unreliable. Comparing occupation-specific employment projections to number of graduates in related fields systematically underestimates the value of higher education.
In 2011 David Neumark, Hans Johnson, & Marisol Cuellar Mejia wrote:
If there are positive returns to education levels above those indicated as the skill requirement for an occupation in the BLS data – and especially if these wage premia are similar to those in other occupations – then relying on the BLS skill requirements likely substantially understates projected skill demands.
For nearly every occupational grouping, wage returns are higher for more highly-educated workers even if the BLS says such high levels of education are not necessary. For example . . . for management occupations, the estimated coefficients for Master’s, professional, and doctoral degrees are all above the estimated coefficient for a Bachelor’s degree, which is the BLS required level. . . ..
If the BLS numbers are correct, we might expect to see higher unemployment and greater underemployment of more highly-educated workers in the United States. As noted earlier, we do not find evidence of this kind of underemployment based on earnings data. Similarly, labor force participation rates are higher and unemployment rates are lower for more highly educated workers.
Neumark et. al. also noted that recent BLS projections appeared to be much too low for managerial and legal services occupations.
Starting around 2012 many law professors and pundits argued that the number of job openings for lawyers projected by the BLS relative to the number of expected law graduates suggested that too many students were attending law school and that they would not get much value out of their degrees.
The Bureau [of Labor Statistic]’s occupational employment projections . . . answer the very question that many law school applicants want to know: How many new lawyers will the economy be able to absorb this decade?
The Bureau currently estimates that the economy will create 218,800 job openings for lawyers and judicial law clerks during the decade stretching from 2010 through 2020. That number, unfortunately, falls far short of the number of aspiring lawyers that law schools are graduating.
The oversupply of entry-level lawyers deprives many graduates of any opportunity to practice law. At the same time, the lawyer surplus constrains entry-level salaries.
Merritt notes the possibility that law might be a versatile degree with value outside of legal practice.
Further evidence that law degrees are unlikely to become more valuable going forward can be found in the projections of the Bureau for Labor Statistics (BLS) . . . [which suggest many more law graduates than job openings].”
In 2013, Brian Tamanaha wrote:
The U.S. Bureau of Labor Statistics estimates about 22,000 lawyer openings annually through 2020 (counting departures and newly created jobs). Yet law schools yearly turn out more than 40,000 graduates. This bleak job market coexists with astronomically high tuition.
Several and journalists also started comparing BLS projections and job openings to make much the same argument.
In 2013, unaware of the problems with job openings projections, I (Simkovic) suggested that projections might be used to make adjustments to more objective historical baselines for risk-based student loan pricing.
On the chance that BLS projections that perform poorly in other contexts perform well in the legal education context, Frank McIntyre and I analyzed the extent to which BLS projections predict law graduate outcomes (earnings premiums). The answer is: no better than random chance.
As in other areas, BLS employment projections are not reliable or meaningful for predicting earnings premiums and are therefore not useful for valuing legal education.
But what about the number of job openings for lawyers? Can BLS projections at least predict that reasonably well?
It is unclear at this point if the new job opening projections method will predict earnings premiums better than the old ones. In any case, that was never their intended purpose, and it would be safer to predict earnings premiums and value education based on historical earnings premiums.
It remains likely that many law school graduates will not practice law. Such has been the case in the past, and such is the case in other fields. Many engineering, math and science graduates do not work as engineers, mathematicians or scientists in their fields of study. Most fields of study do not have a one-to-one correspondence with a particular occupation, but are more broadly useful in the labor market, and law is no exception. In spite of many individuals working outside their degree fields, higher education typically has been, and likely will remain, an investment with positive returns.
To best way to tell whether there is too much or too little investment in education is to consider relative returns that take into account risks and variability in employment. Are the returns to education higher or lower than returns that can be had elsewhere with similar levels of risk? The returns to education are generally much higher, and risk does not appear to explain this difference adequately. The high relative returns to education suggest underinvestment in education.
March 19, 2015
How can we test predictions about the future when we don’t yet have data showing what will happen in the future? One answer is hindcasting. You already believe in hindcasting if you believe in the science behind global warming (see also here and here).
“Hindcasting” (or “backtesting”) is using historical data to test prediction methods and it is widely used in finance, engineering, and climate science. The basic idea is that a prediction method can be reduced to a set of rules or mathematical formulas. Historical data from the more distant past can be fed into these rules and formulas, and the resulting predictions about the “future” (relative to the distant past that provided the data) will also be predictions about the past (relative to the period in which the researcher conducts the backtest).
Since data about the “future” is now available, predictions generated by the prediction method can be compared to what actually happened. A prediction method does not have to be correct all of the time to be useful; if a prediction method performs a bit better than random chance, it might still be useful in many contexts, especially in investment management. If it performs better than the next best prediction method, then it is still useful even if it is imperfect. But if a prediction method does not perform any better than random chance, it is discredited and discarded.
Using this hindcasting approach, Frank McIntyre and I test popular prediction methods used by various pundits and professors to try to predict whether now is a good or bad time to go to law school. (See Timing Law School) As in our previous research, our primary outcome variable of interest is law earnings premiums—the earnings of law school graduates relative to the earnings of similar bachelor’s degree holders. This is the relevant measure, because it goes to the value added by law school, and can be compared to the cost of attendance.
The peer-reviewed labor economics literature finds that a law degree has been a lucrative investment for the overwhelming majority of law school graduates compared to entering the labor market with just a bachelor’s degree. Nevertheless, questions persist about whether now is an unusually good or bad time to start law school.
According to one popular hypothesis, now is an unusually bad time to go to law school because employment outcomes for recent graduates 9 months after graduation have deteriorated. These graduates, it is argued, will not have the same career success as law school graduates in the past. Moreover, deterioration in outcomes for those who graduated last year predicts poor outcomes three or four years in the future and beyond for those who are entering law school now.
According to another popular hypothesis, now is an unusually good time to go to law school because so few people are doing it. When these small cohorts of law students eventually graduate, they will all be more likely to find a high paying job than the larger cohorts of the past. A variation on this argument is that now is still a bad time to go to law school in spite of falling enrollments because the number of law school graduates will still be greater than the number of BLS projected job openings for lawyers. (For a discussion of newer BLS projection methods showing more job openings, see here)
Our analysis includes graduates from 1964 through 2008 and earnings data from 1984 to 2013. This period captures numerous economic booms and recessions. As in The Economic Value of a Law Degree, our main source of data is the U.S. Census Bureau’s Survey of Income and Program Participation. We were able to backfill the data to include older versions of the survey and capture more years of macroeconomic variation thanks to grant funding from Access Group, Inc., and LSAC. (Because the older data has some limitations, those who are interested in the value of a law degree rather than the size of cohort effects should still consult our 2014 article).
None of the prediction methods we tested perform better than random chance. Cohort size is not predictive. Cohort size relative to BLS projections is equally useless. Although those who graduate in a boom when unemployment is low do indeed have higher earnings premiums in their first few years after graduation than those who graduate when unemployment is low or moderate, the effect fades after the first four years. More importantly, it is not possible to predict whether unemployment will be high or low four years in the future based on currently available data. Even those who are unlucky enough to graduate into a weak economy still generally benefit substantially from their law degrees.
Delaying law school to attempt to “time the market” is an imprudent strategy. It does not improve one’s chances of graduating into a favorable economic climate. It entails substantial opportunity costs in the form of fewer years of higher, post-law-school earnings. The cost of every year of delay averages tens of thousands of dollars. Popular prediction methods for market timing are not only scientifically baseless; they also appear to be financially toxic to prospective students who take them seriously.
The best guide to the future continues to be the long-term historical data. Short-term fluctuations around these averages are not readily predictable. Instead of trying to predict the unpredictable, it may be more prudent to focus on helping students manage these risks, for example through insurance programs similar to Income-Based Repayment of student loans. (See also here)
But what about more recent graduates? How much can we say about those who graduated after 2008, and is this time different? How can we explain our results in light of previous research on cohort effects focused on bachelor’s degree holders?
For answers to some of these questions, look for our next blog post.