sou · GYB388 · 2010-11-30 00:00:00 — first review studies that have examined the finan- cial returns to the timing of investments in higher education by comparing the earnings of people who enter into higher education directly after secondary school to earnings of those who enter into higher education at later stages in life. After that I review studies that analyse the effects of studying and working in parallel by examining the effects of work experience while at school. Finally, I calculate the private and social returns to late graduation using Swedish data. 4.1Financial incentives for early vs. The most natural way of analysing the effects of timing of invest- ments is to compare lifetime earnings between those who complete higher education early in life to those who graduate later. However, most existing studies only analyse the effects of graduation age at earnings in a single point in time or at a certain age. The earliest analysis on the effects of graduation age that I am aware of is reported in an article by (1925).6 The study analy- ses data on age at graduation of college graduates from Whos Who in 1922–23 and compares the age of graduation of those listed in Whos Who to the general age distribution of college 6 Apparently, the analysis was actually done by one of his students, . Empirical research on economic incentives affecting graduation age Bilaga 3 till LU2011 graduates reported by (1903). The study shows that the median age for graduation from college of 1080 people selected at random from Whos Who was 22 years and 3.3 months. In com- parison (1903) had reported that the median age of all graduates for the same age cohorts (mainly from the colleges) was 22 years and 9.3 months. concludes that there is very difference between the two groups but whatever difference there is indicates that, so far as inclusion in Whos Who is a measure of success, those who graduate from college under the median age have a somewhat greater chance of success than those who are of median age or older. (1925, p. In a somewhat more recent study, Light (1995) examines the effects of interrupted schooling on wages based on National Longitudinal Survey of Youth (in the US). She finds that men who delay their schooling receive wage boosts that are smaller than those received by their continuously schooled counterparts. She notes for example that individuals who wait two years before advancing from 12 to 16 years of school (i.e. from high school to college) receive a 20 percent wage boost upon completing their re- enrolment spell. This reward is considerably smaller than the 40 per cent wage gap in starting wages between individuals who attain these two schooling levels prior to starting their careers. However, the wages grow rapidly during the first years in the labor market. Therefore, if an individual attends years, works con- tinuously for four years and then attends more years, his starting wage is 17 percent lower than the wage of a per- son that attended years and then worked continu- ously for four years. This gap diminishes over time and virtually disappears in four years.7 A more serious attempt to evaluate the effects of college timing was performed by , and (2008) who estimate the effects of postponing higher education on life- time earnings using Swedish data. They note that over on new university entrants have a 2–4 -year gap and of entrants more 7 A related study by Monks (1997) uses an expanded version of the same data, including also women and minorities, to address the issue. He also makes an attempt to control for the differences across individuals by focusing on within-individual earnings growth instead of comparing earnings across individuals who have graduated at different ages. Unfortunately, this also wipes away all variation in age of college completion since each person in his data graduates only once. Apparently he also uses information on wages prior to graduation which effectively drops all persons who enter college directly after high school from the analysis and hence the estimates provide no information on the key issue, whether a delayed entry has an impact on earnings. Bilaga 3 till LU2011 Empirical research on economic incentives affecting graduation age than a five year (!) gap between completing high school and entry into university. They then estimate the effect of gap years on annual earnings after graduation. According to their estimates, one additional gap year is associated with lower earnings at age 35. This is actually a very large estimate given that the return to educa- tion in is comparatively low. The effect of gap years declines over time and disappears by age 40. The main reason is that earnings growth is rapid during the first years after completing a university degree. The first years of work experience is valuable and those who graduate when they still are relatively young have obtained more experience by age 35. By age 40 late starters have caught up as small differences in experience become less important after the first few years. The data used by et. al (2008) is based on Swedish administrative registers. The sample size is much larger and the information much more detailed than in the previous studies. This allows controlling for a large set of covariates including high school GPA as well as the field and duration of university education. Still their estimates could be affected by unobserved individual charac- teristics that affect earnings and the likelihood of entering univer- sity directly after high school. As an attempt to identify causal effects of gap years they also try to use variation in admission poli- cies to identify the effects but unfortunately the results are rather imprecise. Perhaps the strongest argument that the study still identifies causal effects of timing is that no effects on earnings are found after age 40. So if the delay in entry is due to some unob- served factors, these factors apparently have no permanent effects on earnings. The problems of estimating the effect of delayed entry into higher education are also discussed in a recent paper by Humlum (2007). She notes that the age of entry is likely to be cor- related with a number of individual characteristics that may have direct effects on earnings. Her proposal is to use variation in entry age due to admission requirements, student grant system, compul- sory military service or distance to schools to identify causal effects of entry age. In practice, this has proven to be rather difficult, and attempts to follow such strategies have not been very successful. to the caveats listed above, the results in et. al should be interpreted with care. However, at the moment they probably present the best available estimate regarding the effects of gap years on earnings. The study also estimates the effects of gap years separately on annual earnings at each age between 20 and 44. Empirical research on economic incentives affecting graduation age Bilaga 3 till LU2011 According to the results those who take gap years have higher earnings until age 23 (because many are working during the gap). After that the effect of gap years is negative (first reflecting later graduation and then lower experience). Using these estimates, and assuming a discount rate, they calculate that two gap years reduce the present value of lifetime earnings by 40–of annual earnings at age 40. This is also a very large effect and indicates that there are substantial social costs of delaying entry into tertiary edu- cation. 4.2Financial incentives to study and work in parallel A large fraction of students work while enrolled in a university. This raises several issues. Spending more time at work may imply that less time is spent on studying which may delay graduation. On the other hand, work experience while at university may improve chances of getting a job after graduation and potentially increase wages. Still not much research exists on the effects of working while enrolled. An article by and (1987) is probably one of the first (economic) studies on the effects of employment while in college. They use US data from the National Longitudinal Survey of Youth (NLSY) and examine the effect of hours of work during the academic year on academic achievement and post-college out- comes. According to their results weekly hours of work during college had almost no adverse effects on grade point average or post-college earnings. However, according to their results, increasing hours worked increased the dropout rates and reduced the probability of graduating on time. Light (2001) analyses the effects of in-school work experience. She notes that in the US a typical college graduate gains over 5000 hours of work experience by the time he leaves school. Light esti- mates that an individual who accumulates 2 years of experience while completing 16 years of school (typical college graduate) begins his post-school career earning about more than his counterpart who gains no in-school experience. She also finds that return to education is much lower if in-school experience is con- trolled for. , part of the return to education really is return to work experience acquired during enrolment. Bilaga 3 till LU2011 Empirical research on economic incentives affecting graduation age , Xu, Tienda and Ahituv (2002) analyze the effects of working while in school on wages after school also using the NLSY data from the US. Compared to previous papers they make a more serious effort to separate causal effects of in school work experi- ence from spurious correlations caused by unobserved factors that affect both working and later earnings. They also find that the cor- relation of working while in college (or high school) and later wages is positive, which is consistent with previous research on the topic. However, they find that men who worked while in school differed in many ways from those who did not work. For example, their scores on ability tests and their mothers educational attain- ment were both substantially higher. Therefore, the results suggest that the men who worked while is school were more advantaged than those who did not acquire work experience while in school. Controlling for this selectivity led to much smaller estimated returns to working while enrolled. They conclude that policies to increase a young mans skills via full-time schooling will have greater payoffs to subsequent wage attainment than will policies that promote employment of enrolled youth. (2004) studies the effects of work-experience on post-school outcomes using data on Finnish university students. She also finds that work-experience acquired during university studies has a positive effect on earnings after graduation. The effect is largest immediately after the graduation date, and decreases over time. Importantly however, the result only holds conditional on duration of studies (time-to-degree). Working while enrolled typi- cally increases the duration of studies and those who spend more time in school accumulate less experience after graduation. Accounting for the effect through the duration of studies leads to the conclusion that student employment has no significant effects of later earnings. All the studies that have reviewed the effects of working while at school on later incomes have analyzed the effects on gross income. However, private profitability of in-school employment also depends on the tax treatment of earnings. Earned income tax deductions and progressive taxes that are based on annual earnings increase the incentives of spreading earnings to several years by working and studying in parallel. One should note that the effective tax rates for students may also be quite high if study grants are reduced when earnings increase. In the Swedish case the students who work and study at Empirical research on economic incentives affecting graduation age Bilaga 3 till LU2011 the same time may keep the full amount of the study support if their income does not exceed the exempt amount which is cur- rently 000 per year for full-time studies. When income exceeds this amount, study support decreases by half of what the student earns over the exempt amount. In practice, this implies that the effective tax rate is low up to the exempt amount, but is plus the income tax rate for students that earn more than 107 000 per year. However, at the current level the exempt amount does not seem to matter much. As shown in Figure 3.1 below, most university students earn much less. Also, there is no bunch- ing of earnings just below the exempt amount which suggests that the students are not strategically planning their earnings to maxi- mize the amount of student aid. Figure 4.1 Annual earnings of full-time students in 2006 Source: Calculations by based on data from the IFAU database Notes: Annual earnings include labor income, income from self-employment, allowances for sickness absence and parental leave but exclude student aid. Data contains university students that were studying full-time both in the spring and fall terms of 2006 and were receiving student aid (197,769 individuals). Those with zero income in 2006 are excluded (about ). The vertical line shows the exempt amount (101,250 in 2006). Bilaga 3 till LU2011 Empirical research on economic incentives affecting graduation age private costs of late graduation To my knowledge no existing studies have compared the private and social costs of delayed graduation. , I present cross-sec- tional calculations based on Swedish data. I calculate the social costs of delaying graduation based on esti- mates of the effects of delays on gross lifetime income, which serves as a proxy for the productive contribution of the worker. The private costs of delay are calculated based on estimates of the effects delayed graduation on lifetime disposable income, which is a fairly accurate measure of the economic well being of the individ- ual. The difference between social costs and private costs are exter- nalities, i.e. costs carried by society. Thus, government intervention aiming to lower the graduation age would (only) be beneficial for society if the social costs of delayed graduation are larger than the private costs.8 My basic data includes all Swedes that have completed a univer- sity-level education by 2007 drawn from the database. I use these data to calculate lifetime gross and net incomes, and social transfers by age of graduation. I estimate lifetime earnings profiles from a cross-section data. To be able to calculate average earnings also from years before graduation, I take data from 1996 and merge to these data the age of graduation as recorded in 2008. For those who graduate after 1996, this naturally refers to a future date. I restrict the data to per- sons between 19 and 50 in 1996 and to persons who have graduated or will graduate between ages 24 and 30. To remove some observable differences across students that graduate at different ages, I regress earnings separately at each age on gender, immigration status and field of education (17 different fields) and calculate average earnings adjusted for these covariates by setting them to the sample averages.9 It would be useful to 8Due to lack of data direct costs of education are not included in these calculations. It may not cause major problems, since it is far from clear that students who graduate later use more university resources. 9I do this adjustment somewhat unconventionally with levels rather than log earnings. There are two main reasons for this. First, data includes persons with zero earnings and having no earnings is relevant information (using logs would drop these observations). Second, I need levels of earnings to calculate discounted lifetime earnings. Naturally, predicted values (i.e conditional means) from regression on log earnings can be converted to levels using the exponential function, but since logarithmic and exponential functions are nonlinear, this would create biased estimates for levels (unless one properly accounts for variances). To lessen the influence of extreme values on the estimates, I drop all observations with annual earnings or annual disposable income over one million krones. (of the data). Empirical research on economic incentives affecting graduation age Bilaga 3 till LU2011 account also for other differences across students, for example high school grades. However, since graduation years in the data range from 1970 to 2007, this would require much more intensive data work than was possible within this project. Figure 4.2 presents the results of these calculations for average annual gross wage earnings. I have plotted earnings in 1996 at each age separately for those who graduated (or will eventually gradu- ate) at ages 24, 26, 28 and 30. The pattern is expected. Those who graduate at a later age have somewhat higher earnings between ages 20 and 25, because they work more, e.g. during gap years. Earnings increase quickly after graduation and the large part of the cost of delay in graduation age is apparently related to the earnings lost during the first few years after graduation. However the gap in earnings seems to be persistent. Those who graduate earlier have higher earnings through most of their lifetimes compared to those who graduate from the same fields at an older age. This difference should naturally not be interpreted as a causal effect. Fast gradua- tion is likely to be correlated with student ability that has inde- pendent effects on earnings. Figure 4.2 Gross annual wage earnings by age and age of graduation Regression adjusted estimates for average annual gross earnings by age and eventual age of graduation based on cross-sectional micro data for 1996.Amounts in . Source: The IFAU-data base. For details see text. Bilaga 3 till LU2011 Empirical research on economic incentives affecting graduation age In Figure 4.3 I have repeated the calculation using disposable incomes as the income measure instead. This income concept accounts for income taxes and all transfers and benefits including e.g student grants. Student loans are also counted as income and re- payments of these loans after graduation are deducted from earned income. Transfers for families are individualized by Statistics . The pattern in Figure 4.3 looks similar to Figure 4.2 but the differences across persons graduating at different ages are smaller. This mainly reflects the effects of progressive taxes. Interestingly also the differences before graduation are small indicating that those graduating earlier do not suffer much in terms of forgone earnings – or that these losses are compensated by the student sup- port system. Figure 4.3 Disposable income by age and age of graduation Regression adjusted estimates for average disposable income by age and eventual age of graduation based on cross- sectional micro data for 1996. Data source: The IFAU-data base. For details se text. Finally in Figure 4.4 I have calculated average social transfers by age of graduation. This is a summary measure used by Statistics and includes student support and all other benefits that are Empirical research on economic incentives affecting graduation age Bilaga 3 till LU2011 paid during absence from the labor market (e.g unemployment benefits and benefits during sickness absences). Here the results are quite striking. The society clearly pays much larger subsidies to persons who enter the labor market later. Figure 4.4 Income transfers received by age and age of graduation Regression adjusted estimates for average combined transfer incomes by age and eventual age of graduation based on cross-sectional micro data for 1996. Data source: The IFAU-data base. For details see text. I used the earnings profiles displayed above to calculate discounted present value of lifetime earnings by age of graduation. I did this separately for gross earnings and disposable income. In these cal- culations I assumed a discount rate and calculated the present values of earnings streams between 19 and 50 discounted to age 19. As noted before my calculations were based on 1996 data. have deflated the results to the level of using the con- sumer price index10. In addition to groups displayed in the figures above I repeated these calculations for those who graduated at age 25, 27 and 29. As a result I was able to calculate an average cost of a 10 Alternatively, this could be done with wage index which would imply multiplying the 1996 values by 1.60 instead of CPI deflator that is 1.17. Bilaga 3 till LU2011 Empirical research on economic incentives affecting graduation age one year delay in the graduation age and compare the social cost and cost to the individual. I have plotted the estimated costs in Figure 4.5. According to the estimates a one-year delay in graduation may cost up to 250,000SEK in terms of lost lifetime labour earnings, Average cost of a one year delay within the age range used in calculations in 160,000. The number is close to median annual earnings of employed university graduates at the time of measurement. This estimate may be biased upwards if the students that graduate earlier are somehow more productive at work. However, even if the esti- mates for the gross cost of delaying graduation would be biased, it is instructive to compare the costs for the individual to the social costs. According to the Figure 4.5 the individual pays only about half of the cost for the delay. This implies that delay in graduation age has substantial external effects suggesting that government actions aiming at a lower average graduation age are well motivated. Figure 4.5 Social and private costs of delaying graduation by one year, in Source: Own Calculations based on cross-section data from 1996 deflated to 2009 price level. For details, see text. 4.4Summary of research on economic incentives According to the studies reviewed above delaying entry into terti- ary education is costly in terms of lifetime earnings. The costs for the society are even larger than the private costs borne by the stu- Empirical research on economic incentives affecting graduation age Bilaga 3 till LU2011 The results regarding the incentives to work and study in par- allel are more mixed. Work experience acquired while at school appears to have positive effects on earnings after graduation, but also postpones the graduation date. If one is willing to take the estimates in the existing studies as representing the causal effects of delaying entry into higher educa- tion, one has to conclude that delayed entry has substantial effects on lifetime earnings. This also implies that there already are sub- stantial financial incentives to enter higher education immediately after completing secondary education. Since the gap years are common despite of financial incentives to enter university directly after high school one has to find alter- native explanations to the observed behaviour. At least the follow- ing could be a part of the story (i)The students perceive the incentives in a different way. Pre- dicting future incomes after higher education is difficult and it may be even more difficult to understand the costs of delaying entry into higher education. Lack of informa- tion leads to decisions that are not optimal for the individ- ual. (ii)Making decisions about schooling and occupational choice is difficult, and delaying the decision may be a rational response to uncertainty about ones own schooling prefer- ences. (iii)The youth have a strong preference for leisure when young and free from family commitments. Another way of stating this is that the youth are short-sighted so that their subjec- tive discount rates are higher than the that was used in the calculations referred above. This may induce taking a gap year even if there are financial costs later in life.