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Money Does Matter After All

This is a response to “Money Matters After All?” by Eric Hanushek, published July 17, 2015 on the Ed Next blog, which was a response to “Boosting Educational Attainment and Adult Earnings,” by C. Kirabo Jackson, Rucker C. Johnson and Claudia Persico, published in the Fall 2015 issue of Education Next.  Eric Hanushek has responded to this piece in a blog entry published on July 20, 2015 on the Ed Next blog. 

We would like to thank Eric Hanushek for his comments and interest in our work.  We appreciate the opportunity to offer a brief response. Hanushek provides an accurate description of our study and is correct that the methodological details matter. His critique, however, is not an objection to any of our methodological choices; he instead disputes our results. He states “while these [questions about measurement and how spending reactions to court decision is measured…] are important methodological issues, it is more useful to focus on the substance of their findings.” We take this as clear evidence that Hanushek finds our methodology sound. When the methods are sound, the results must be taken seriously.  We appreciate that Hanushek has done so in this case. His single, important critique of our key results is the “time trend” argument. Following the summary of our findings below, we present the “time trend” argument and highlight its flaws. We then discuss how we overcome the problems of the previous studies on which Hanushek bases his opinions. Finally, we discuss how our results differ from previous literature because (a) existing studies suffered from biases, and (b) the spending increases analyzed in our analysis were spent on more productive inputs than the spending increases examined in other studies.

Overview of our findings:

In most states, prior to the 1970s, most resources spent on K–12 schooling were raised at the local level, through local property taxes (Howell and Miller 1997; Hoxby 1996). Because the local property tax base is typically higher in areas with higher home values, and there are persistently high levels of residential segregation by socioeconomic status, heavy reliance on local financing contributed to affluent districts’ ability to spend more per student. In response to large within-state differences in per-pupil spending across wealthy/high-income and poor districts, state supreme courts overturned school finance systems in 28 states between 1971 and 2010, and many states implemented legislative reforms that spawned important changes in public education funding. The goal of these school finance reforms (SFRs) was to increase spending levels in low-spending districts, and in many cases to reduce the differences in per-pupil school-spending levels across districts. By design, some districts experienced increases in per-pupil spending while others may have experienced decreases (Murray, Evans, and Schwab 1998; Card and Payne 2002; Hoxby 2001). Our key finding is that increased per-pupil spending, induced by court-ordered SFRs, increased high school graduation rates, educational attainment, earnings, and family incomes for children who attended school after these reforms were implemented in affected districts. We find larger effects for low-income children, such that these reforms narrowed adult socioeconomic attainment differences between those raised in low- vs. high-income families.

What we do not find:

There are two misunderstandings about our findings that critics appear to make. As such, we feel it is helpful to outline what we do not conclude from our study.

1. We do not find that merely increasing spending will improve student outcomes irrespective of how it is spent. Though Hanushek’s critique may lead readers to think otherwise, at no point in our paper do we make claims suggesting that “policy makers…only have to concern themselves with how much money was provided to schools and not with how money was used.” We are very careful to highlight that how money is spent matters. We find that increased spending that leads to reductions in class sizes, increased teacher salaries and more instructional school days in a year improved outcomes. As such, one of our key conclusions is that, while how much money one spends does clearly matter, how it is spent is very important. The final lines of our full paper read, “Money alone may not be sufficient, but our findings indicate that provision of adequate funding may be a necessary condition. Importantly, we find that how the money is spent may be important. As such, to be most effective it is likely that spending increases should be coupled with systems that help ensure spending is allocated toward the most productive uses.”

2. We do not find that increasing spending by 22.7 percent will eliminate all differences in outcomes by socioeconomic status. This is a common misunderstanding of our findings that is also made by Hanushek. We find that a 22.7 percent spending increase is large enough to eliminate the average outcome differences between the poor (those with family incomes below twice the poverty line) and the non-poor (those with family incomes above twice the poverty line). Because there are large differences by socioeconomic status among those in each income group (e.g., the wealthy tend to have better outcomes than the average non-poor person, and the very poor tend to have worse outcomes than those just above the poverty line) eliminating the average difference in outcomes across the two broad groups does not eliminate all differences by socioeconomic status within each group. Simply put, just because a 22.7 percent spending increase is large enough to eliminate the average outcome differences between the poor and non-poor it does not mean that a 22.7 percent spending increase is large enough to eliminate the difference in outcome between the very poor and the very wealthy or differences across other measures of socioeconomic status. Also, we do not speculate that this spending increase will eliminate differences in outcomes by other categories such as race and gender. To illustrate this logic, consider the following simple mathematical example.

Illustrative example: There are 4 people in a society of different income levels. Persons are ranked by income level so that Person 1 is the richest and person 4 is the poorest. Richer individuals tend to have better outcomes such that Person 1 has 20 years of education, Person 2 has 18 years, Person 3 has 18 years and person 4 has 16 years of education. The average educational attainment for the two richest persons is 19 years and the average educational attainment for the two poorest persons is 17. The average gap between the high income group and the low income groups is 2 years. However, the gap between the richest and poorest person is 4 years. If one could increase the level of education for both lower income persons (persons 3 and 4) by 2 years, the average gap across the two groups would be eliminated. However, the richest person would still have 2 more years of education that the poorest person. This simple example illustrates that eliminating the average difference across the two groups will only remove all differences by socioeconomic status if there are no differences in outcomes by socioeconomic status within the broad income groups. Given that there are large difference in outcomes by socioeconomic status within broad income groups in the United States, this condition clearly does not hold in reality.

The Problem with Hanushek’s “Time Trend” Critique:

Now that the reader should have a clear sense of our paper and its implications, we now describe the Hanushek “time trend” argument. Hanushek points out that school spending in the United States has increased substantially between 1970 and present day. As such, he argues that, if our results are correct and school spending really does improve student outcomes (with larger effects for low-income children), outcomes should have improved over time and achievement gaps by income should have been eliminated over this time period. He then argues that any improvements between 1970 and today have been small so that it is unlikely that our conclusion that school spending improves student outcomes is correct.

While this “time trend” argument is intuitive, it is flawed for two reasons. The first reason is that it relies on the same flawed understanding of our results outlined above (i.e., that eliminating differences across two broad income groups implies eliminating all differences by socioeconomic status). The second problem with this “time trend” argument is that it is a facile argument based on fuzzy (albeit intuitive) logic. We highlight the problems of his logic below.

To see the problems of Hanushek’s logic, consider the following true statistics: between 1960 and 2000 the rate of cigarette smoking for females decreased by more than 30 percent while the rate of deaths by lung cancer increased by more than 50 percent over the same time period.[1] An analysis of these time trends might lead one to infer that smoking reduces lung cancer. However, most informed readers can point out numerous flaws in looking at this time trend evidence and concluding that “if smoking causes lung cancer, then there should have been a large corresponding reduction in cancer rates so that there can be no link between smoking and lung cancer.” However, this is exactly the facile logic invoked by Hanushek regarding the effect of school spending on student achievement.

While there are several problems with this simplistic argument, to avoid going too deeply into the weeds we focus on the most important flaw in this “time trend” argument. Simply put, the “time series” argument will hold only if nothing else has changed between 1970 and present day. It is important to bear in mind that these spending increases occurred against the backdrop of countervailing influences, such as the rise in single-parent families, more highly concentrated poverty, deterioration of neighborhood conditions for low-income families, the exodus of the middle class to the suburbs, mass incarceration, the crack epidemic, changes in migration patterns, and others. Consider just one countervailing factor: the significant rise in segregation by income between neighborhoods over the past four decades. This increased residential segregation was driven mostly by families with school-age children (Owens 2015), a simple reflection that quality of local schooling options is a key driver of segregation. This significant increase in residential sorting by income among families with school-age children would have likely led to far greater disparities in school resources by community socioeconomic status had SFRs not been an effective leveling tool.

In short, 1970 and 2010 is not an “apples-to-apples” comparison, so there is no reason to expect that the correlation between aggregate spending and aggregate outcomes over such a long time span will yield anything resembling a “causal” relationship. In fact, the observation that using simple correlations over time is unlikely to yield the true “causal” relationship is exactly what motivated us to follow a different methodological approach. Our methodological approach allows for an “apples-to-apples” comparison and allows us to disentangle the effects of school spending from that of all these other countervailing forces. Though Hanushek has chosen not to discuss the methodological advances in our work, they are important, and methods matter.

How We Overcome These Problems to Facilitate “Apples-to-Apples” Comparisons:

We make several decisions in order to facilitate more of an apples-to-apples comparison. First, we use fine-grained data on individual students, rather than comparing the entire United States in 1970 to the entire United States in 2010. With these finer-grained data we are able to account for a variety of other factors that may have changed over time such as family structure, childhood poverty, and neighborhood factors. Using these finer grained data, our main approach is to compare the outcomes of individuals with similar background characteristics born in the same school district but who attended public schools during different years (when per-pupil spending levels may have been different) — i.e., an apples-to-apples comparison. However, this is not all that we do to ensure that our results yield real causal relationships.

In our paper, we point out that even if one can carefully account for several observable factors (as we do), correlating all actual changes in school spending with changes in student outcomes is unlikely to yield causal relationships. We point out that some spending changes are unrelated to other factors that may obscure the real effect on outcomes (i.e., clean spending changes), while other kinds of spending changes would clearly yield erroneous results (i.e., confounded spending changes). We point out that many of the spending changes analyzed in previous studies may have been of the confounded variety. To give an example of such confounded spending changes, consider the following example. The federal Elementary and Secondary Education Act allocates additional funding to school districts with a high percentage of low-income students, who are more likely to have poor educational outcomes for reasons unrelated to school spending. As such, school districts serving declining neighborhoods are also those that are most likely to receive additional per-pupil spending over time. Such compensatory policies generate a negative relationship between changes in school spending and student outcomes that obscure the true relationship between school spending and student outcomes. We avoid this kind of problem by focusing only on clean spending changes. Specifically, we focus on the relationship between external “shocks” to school spending and long-run adult outcomes. The “shocks” we use are the sudden unanticipated increases in school spending experienced by predominantly low-spending districts soon after passage of court-mandated SFR.

As discussed above, by design, very soon after a court-ordered SFR in a state, some districts experienced sudden unanticipated increases in per-pupil spending (i.e., shocks) while others may have experienced decreases. Our analytic approach compares the outcomes of individuals who attended school before these spending shocks to those of similar individuals from the school district after these spending shocks. The validity of our design relies on the idea that districts that experienced sudden increases in school spending right after the passage of a court-ordered SFR were not already improving in other ways in exactly those same years. For this reason, we spend much time in our work showing that the timing of these spending shocks has nothing to do with underlying neighborhood changes or changes in family characteristics, so that changes in outcomes due to these shocks are likely to reflect a causal relationship. We encourage interested readers to consult the full paper for further detail.

Reconciling our results with the Older Literature:

Even though we outline the faulty assumptions in Hanushek’s “time trend” argument, in the interest of good social science it is helpful for us to try to reconcile our findings with the simple time-series evidence. As we explain above, our results do not imply that a 22.7 percent increase will eliminate all differences by parental socioeconomic status. However, they do suggest the much more realistic prediction that one might observe some convergence across groups over time as school spending has increased. Indeed this has been the case. For example, Krueger (1998) uses data from the NAEP and documents test score increases over time, with large improvements for disadvantaged children from poor urban areas; the Current Population Survey shows declining dropout rates since 1975 for those from the lowest income quartile (Digest of Education Statistics, NCES 2012). Murnane (2013) finds that high school completion rates have been increasing since 1970 with larger increases for black and Hispanic students; Baum, Ma and Pavea (2013) find that postsecondary enrollment rates have been increasing since the 1980s, particularly for those from poor families. Contrary to Hanushek’s assertions, outcomes have improved. Importantly, these improvements are consistent with increase in school spending playing a key role.

Finally, Hanushek proposes three reasons why our estimates (if true) may not track the national time trends very well. His ideas are not novel — we considered, tested, and addressed them ourselves in the paper and herein.  First, he says there may be diminishing marginal returns to schools spending. Indeed we find that this is the case in our study. Areas with the lowest initial spending levels were also those for which increased spending had the most pronounced positive effect. The second reason he cites is that spending induced by the courts might have large effects while spending not related to judicial rulings have small effects. Indeed we find evidence of this also. Specifically, spending increases associated with court-mandated reform are much more strongly related to improvement in measured school inputs (e.g., student-to-teacher ratios, length of the school year) than ordinary spending increases. There are a few explanations for this that we explore in our study. Finally, he proposes that our estimates are wrong. We propose an alternative: the time series evidence Hanushek relies on does not reflect a causal relationship. Indeed in our larger study, we show that simple correlations are obscured by a variety of other factors that also influence student outcomes. We also present numerous pieces of analysis in our larger study that support a causal interpretation of our results.

To be clear, we do not think that our study is the final word on the question of whether increasing school spending will improve student outcomes in all contexts. As Hanushek himself concedes “none of this discussion suggests that money never matters. Or that money cannot matter.” Here we will make a similar concession; none of what we show suggests that money always matters. We show that money did matter and that it mattered quite a lot. What our study does is dispels the notion that school spending does not matter, so that one must look only at how it is spent. We find that money does matter and how it is spent matters. Contrary to Hanushek’s claims, our findings do not let policymakers off the hook. Our findings suggest that it is extremely important that money is allocated effectively and also that it is allocated equitably so that all schools have the resources necessary to help all children succeed.

— Rucker C. Johnson, C. Kirabo Jackson and Claudia Persico

Rucker C. Johnson is associate professor of public policy at University of California, Berkeley. C. Kirabo Jackson is associate professor of human development and social policy at Northwestern University. Claudia Persico is a doctoral candidate in human development and social policy at Northwestern University. This article was originally posted on EducationNext.

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[1] http://www.geocities.ws/microecon03/sectionII.html

http://scienceblog.cancerresearchuk.org/2014/11/09/its-lung-cancer-awareness-month/

http://www.cancer.org/research/cancerfactsstatistics/cancerfactsfigures2013/cancer-statistics-2013-slide-presentation.pdf

NOTE: The lung cancer rates for males has been on the decline since 2000 and has been relatively stable for females between 2000 and 2009.

Boosting Educational Attainment and Adult Earnings

Does school spending matter after all?

Per-pupil spending can vary drastically between school districts, with affluent suburban districts often outspending their neighbors by significant margins. Such disparate school spending is frequently identified as a primary culprit in our nation’s wide achievement gaps between students of different socioeconomic and racial backgrounds. The argument makes intrinsic sense to many: if one school district spends significantly more educating its students, then of course those students will perform better academically. Existing research on the topic, however, paints a muddier picture.

In 1966, James Coleman conducted one of the largest education studies in history to analyze aspects of educational equality in the United States, including the relationship between school spending and student outcomes. Coleman found that variation in school resources (as measured by per-pupil spending and student-to-teacher ratios) wasunrelated to variation in student achievement on standardized tests. In the decades following the release of the Coleman Report, the effect of school spending on student academic performance was studied extensively, and Coleman’s conclusion was widely upheld.

Given that substantial funding is needed to hire teachers and staff, purchase instructional materials, and maintain facilities, the lack of a positive relationship between school spending and student outcomes is surprising. Two key limitations of previous studies, however, make it difficult to draw firm conclusions from their results—limitations that we address in this study.

The first limitation is that test scores are imperfect measures of learning and may be only weakly linked to important long-term outcomes such as adult earnings. Yes, many interventions that boost test scores, such as being assigned to an effective teacher, have been shown to generate substantial gains in later earnings (see “Great Teaching,” research, Summer 2012). But several recent studies have also shown that effects on adult outcomes may go undetected by test scores. We address this limitation by focusing on the effect of school spending on such long-run outcomes as educational attainment and earnings rather than on test scores.

The second limitation of previous work is that most national studies simply examine correlations between observed changes in school spending and changes in student outcomes. This is problematic because many changes in how schools are funded are designed to provide additional resources to districts at risk of low performance. For example, the federal Elementary and Secondary Education Act allocates additional funding to school districts with a high percentage of low-income students, who are more likely to have poor educational outcomes for reasons unrelated to school quality. Such compensatory policies generate a negative relationship between changes in school spending and student outcomes that would bias analyses of the effects of school spending based on correlations alone.

We overcome this second limitation by focusing on the effects of exogenous shocks to school spending, that is, shocks that should be unrelated to family and neighborhood characteristics or the characteristics of any particular district or school. The exogenous shocks we use are the passage of court-mandated school-finance reforms (SFRs). In order to remove the confounding influence of unobserved factors that have an impact on both school spending and student outcomes, we calculate how much spending in a given school district would have been predicted to change due solely to the passage of an SFR, and use that prediction, rather than the spending change the district actually experienced, as our key variable. We then see if, within districts predicted to experience larger reform-induced spending increases, “exposed” cohorts (children young enough to have been in school when or after the reforms were passed) have better outcomes than “unexposed” cohorts (children who were too old at the time of passage to be affected by the reforms).

Our findings provide compelling evidence that money does matter, and that additional school resources can meaningfully improve long-run outcomes for students. Specifically, we find that increased spending induced by SFRs positively affects educational attainment and economic outcomes for low-income children. While we find only small effects for children from nonpoor families, for low-income children, a 10 percent increase in per-pupil spending each year for all 12 years of public school is associated with roughly 0.5 additional years of completed education, 9.6 percent higher wages, and a 6.1-percentage-point reduction in the annual incidence of adult poverty.

School-Finance Reforms

To document the causal relationship between school spending and long-run outcomes, we isolate variation in spending that occurred in response to the passage of court-mandated SFRs. What do these finance reforms look like, and how do they affect school districts?

In most states, prior to the 1970s, the majority of resources spent on K–12 schooling was raised at the local level, through local property taxes. Because the local property tax base is typically higher in areas with higher home values, and there are persistently high levels of residential segregation by socioeconomic status, heavy reliance on local financing enabled affluent districts to spend more per student. In response to lawsuits that identified large within-state differences in per-pupil spending across wealthy and poor districts, state supreme courts overturned school-finance systems in 28 states between 1971 and 2010, and many state legislatures implemented reforms that led to major changes in school funding. SFRs that began in the early 1970s and accelerated in the 1980s caused some of the most dramatic changes in the structure of K–12 education spending in U.S. history.

Most SFRs changed spending formulas to reduce differences in per-pupil spending across districts within a state. To document the equalizing effect of these reforms, Figure 1 compares the changes in spending in previously low-spending and high-spending districts during the 10 years leading up to a court-mandated SFR and the two decades that followed. We classify districts as low- or high-spending based on whether their average per-pupil spending levels were in the bottom or top 25 percent of districts in their state as of 1972, before any such reforms were implemented.

We see that court-mandated reforms were in fact successful at reducing spending gaps between previously low- and high-spending districts. In states that passed SFRs, low-spending districts initially experienced greater increases in per-pupil spending than similar districts in nonreform states, while high-spending districts experienced decreases. This general pattern was sustained over time.

Having established that court-mandated reforms, on average, affected school spending differently in different kinds of districts, we use more detailed information about the specific reforms enacted in each state to “predict” reform-induced spending changes for each district nationwide. That is, we ignore what actually occurred in a given district and instead calculate what would have been expected to occur based on the experiences of all other districts with similar characteristics experiencing the same kind of reform. We can therefore be confident that these predicted spending changes are unrelated to any unobserved changes in that particular district that may have influenced both school spending and adult outcomes.

The basic idea behind this approach is as follows: if certain kinds of reforms have systematic and predictable effects on certain kinds of school districts, then one can predict district-level changes in school spending based only on factors that are unrelated to potentially confounding changes in unobserved determinants of school spending and student outcomes (e.g., local commitment to education or the state of the local economy). With this clean, predicted variation in spending, one can then test whether in those districts that are predicted (based on pre-reform characteristics) to experience larger reform-induced spending increases, cohorts exposed to the reform have better outcomes than unexposed cohorts. By correlating outcomes with only the reform-induced variation in school spending (rather than all variation in spending), one removes the confounding effect of unobserved factors that might influence both school spending and student outcomes.

Of course, this strategy is only viable to the extent that one’s predictions of spending increases are reasonably accurate. Fortunately, we are able to examine actual spending in each district to confirm that, after reforms, districts with larger predicted spending increases experienced larger actual spending increases. Figure 2a shows that exposed cohorts in reform districts predicted to experience larger per-pupil school spending increases did exactly that, while exposed cohorts in reform districts predicted to experience smaller spending increases saw little change in school spending. Importantly, as our results show, predicted increases in per-pupil spending induced by SFRs are correlated not only with actual spending increases, but with improved outcomes for students as well.

Impact on Educational Attainment

Because test scores are not necessarily the best measure of learning or of likely economic success, we examine instead the relationships between SFR-induced spending increases and several long-term outcomes: educational attainment, high school completion, adult wages, adult family income, and the incidence of adult poverty. Our data on these outcomes come from the Panel Study of Income Dynamics (PSID), a survey that has tracked a nationally representative sample of families and their offspring since 1968. In particular, we use information on the roughly 15,000 PSID sample members born between 1955 and 1985, who have been followed into adulthood through 2011.

We find that predicted school spending increases are associated with higher levels of educational attainment. Figure 2b illustrates the effects of reform-induced changes in per-pupil spending on years of schooling completed. One can see clear patterns of improvement for exposed cohorts in districts with larger predicted spending increases. Cohorts with more years of exposure to higher predicted spending increases have higher completed years of schooling than cohorts from the same district who were unexposed or had fewer years of exposure. Also, the increases associated with exposure are larger in districts with larger predicted increases in spending (the line for districts with high predicted increases is consistently above that of districts with low predicted increases for the exposed cohorts). The patterns in timing and in intensity strongly indicate that policy-induced increases in school spending were in fact responsible for the observed increases in educational attainment. Taking into account the relationship between predicted and actual spending increases, we find that increasing per-pupil spending by 10 percent in all 12 school-age years increases educational attainment by 0.3 years on average among all children.

Because prior research has shown that children from low-income families may be more sensitive to changes in school quality than children from more-advantaged backgrounds, we also separately examine the effects of spending on low-income and nonpoor children. We define children as being low-income if their family’s annual income fell below two times the federal poverty line at any point during childhood.

For children from low-income families, increasing per-pupil spending by 10 percent in all 12 school-age years increases educational attainment by 0.5 years. In contrast, for nonpoor children, a 10 percent increase in per-pupil spending throughout the school-age years increases educational attainment by less than 0.1 years, and this estimate is not statistically significant.

To put these results in perspective, the education gap between children from low-income and nonpoor families is one full year. Thus, the estimated effect of a 22 percent increase in per-pupil spending throughout all 12 school-age years for low-income children is large enough to eliminate the education gap between children from low-income and nonpoor families. In relation to current spending levels (the average for 2012 was $12,600 per pupil), this would correspond to increasing per-pupil spending permanently by roughly $2,863 per student.

Predicted spending increases are also associated with greater probabilities of high school graduation, with larger effects for low-income students than for their nonpoor peers. Specifically, increasing per-pupil spending by 10 percent in all 12 school-age years increases the probability of high school graduation by 7 percentage points for all students, by roughly 10 percentage points for low-income children, and by 2.5 percentage points for nonpoor children. Figure 3 highlights the difference in effect size for these two childhood family-income groups and illustrates the closing of the high-school-graduation-rate gap between low-income and nonpoor children as a result of reform-induced spending increases.

In short, increases in school spending caused by SFRs lead to substantial improvements in the educational attainment of affected children, with much larger impacts for children from low-income families.

Impact on Adult Economic Outcomes 

Our analyses also reveal sizable effects of increased school spending on low-income children’s labor market outcomes and their economic status as adults. For children from low-income families, increasing per-pupil spending by10 percent in all 12 school-age years boosts adult hourly wages by $2.07 in 2000 dollars, or 13 percent (see Figure 4). In contrast, the estimated effect of spending increases on wages for children from nonpoor families is small and statistically insignificant.

Increased per-pupil spending also has a positive effect on exposed students’ family income in adulthood. For children from low-income families, increasing per-pupil spending by 10 percent in all 12 school-age years increases family income by 17.1 percent. For children from nonpoor families, the estimated effect is small and not statistically significant. Effects on family income may reflect a) increases in one’s own income,
b) increases in other income due to increases in the likelihood of being married, or c) increases in the income of one’s family members (which is likely if children tend to marry individuals who were also affected by spending increases). Consistent with the effects on family income, which reflect, in part, any family composition effects, we find that, among low-income children, a 10 percent spending increase is associated with a 10-percentage-point increase in the likelihood of being married and never divorced. Spending increases have no effect on the probability of ever being married, however, suggesting that the higher marriage rates reflect higher levels of marital stability.

Our final measure of overall economic well-being is the annual incidence of adult poverty. Because this is an undesirable outcome, lower numbers are better. Our analysis finds that for children from low-income families, increasing per-pupil spending by 10 percent in all 12 school-age years reduces the annual incidence of poverty in adulthood by 6.1 percentage points. The effect for children from nonpoor families is once again small and statistically insignificant.

In summary, for children from low-income families, predicted increases in school spending are associated with increases in adult economic attainment in line with their educational improvements, and likely reflect improvements in both the quantity and quality of education received. Taken together, these analyses show that increased school spending caused by SFRs had important positive effects on adult wages, family income, and poverty status.

Methods Matter

As mentioned previously, a large literature inspired by the Coleman Report has compared outcomes of individuals exposed to different levels of school spending without accounting for the possibility that changes in spending may have resulted from factors that also directly affect the outcomes of interest. One of the benefits of our approach is that we exploit only plausibly exogenous variation in school spending that is driven by court-mandated reforms.

We confirm that our approach generates significantly different results than those that use observed increases in school spending, by comparing our results to those we would have obtained had we used actual rather than predicted increases as our measure of changes in district spending. For all outcomes, the results based simply on observed increases in school spending are orders of magnitude smaller than our estimates based on predicted SFR-induced spending increases, and most are statistically insignificant.

This stark contrast provides an explanation for why our estimates differ from those of other influential studies in the literature, including the Coleman Report itself. We suspect prior studies that relied on variation in actual spending and found only modest effects of school spending may have been influenced by unresolved biases.

Exploring Mechanisms

Another possible explanation for our findings of large school-spending effects is that how the money is spent matters a lot and that districts use the resources that come from unexpected increases in school spending more productively than they use other resources. Given that money per se will not necessarily improve student outcomes (for example, using the funds to pay for lavish faculty retreats or to shore up employee pension funds will likely not have a large positive effect on student outcomes), understanding how the increased funding was spent is key to understanding why we find large spending effects where others do not.

To shed light on the causal pathways through which education spending affects adult outcomes, we examine the effects of court-mandated spending increases on spending for school support services, physical capital, and instruction. We also estimate effects on student-to-teacher ratios, student-to-guidance-counselor ratios, teacher salaries, and the length of the school year.

We find that when a district increases per-pupil school spending by $100 due to reforms, spending on instruction increases by about $70, spending on support services increases by roughly $40, spending on capital increases by about $10, while there are reductions in other kinds of school spending, on average. While instructional spending makes up about 60 percent and support services make up about 30 percent of all total school spending, the two categories account for about 70 percent and 40 percent of the marginal increase, respectively. This suggests that exogenous increases in school spending are more likely than other forms of school spending to go to instruction and support services. The increases for instruction and for support services (which include expenditures to hire more teachers and/or increase teacher salaries along with funds to hire more guidance counselors and social workers) may help explain the large, positive effects for students from low-income families.

We also examine the effects of court-mandated spending increases on three commonly used proxies for school quality: the length of the school year, teacher salaries, and student-teacher ratios. We find that a 10 percent increase in school spending is associated with about 1.4 more school days, a 4 percent increase in base teacher salaries, and a 5.7 percent reduction in student-teacher ratios. Because class-size reduction has been shown to have larger effects for children from disadvantaged backgrounds, this provides another possible explanation for our overall results.

While there may be other mechanisms through which increased school spending improves student outcomes, these results suggest that the positive effects are driven, at least in part, by some combination of reductions in class size, having more adults per student in schools, increases in instructional time, and increases in teacher salaries that may help to attract and retain a more highly qualified teaching workforce.

Conclusion

Previous national studies have examined the relationship between school resources and student outcomes and found little association for students born after 1950. Those studies, however, suffer from major design limitations. We address those limitations and demonstrate that, in fact, when examined in the right way, it becomes clear that increased school spending is linked to improved outcomes for students, and for low-income students in particular. Investigating the causal effect of school spending increases generated by the passage of SFRs, we conclude that increasing per-pupil spending yields large improvements in educational attainment, wages, and family income, and reductions in the annual incidence of adult poverty for children from low-income families. For children from nonpoor families, we find smaller effects of increased school spending on subsequent educational attainment and family income in adulthood.

Taken together, these results highlight how improved access to school resources can profoundly shape the life outcomes of economically disadvantaged children and thereby reduce the intergenerational transmission of poverty. Money alone may not lift educational outcomes to desired levels, but our findings confirm that the provision of adequate funding may be critical. Importantly, we also find that how the money is spent matters. Therefore, to be most effective, spending increases should be coupled with systems that help ensure spending is allocated toward the most productive uses.

This article is based on the full paper “The Effects of School Spending on Educational and Economic Outcomes: Evidence from School Finance Reforms,” The Quarterly Journal of Economics (forthcoming).

Rucker C. Johnson is associate professor of public policy at University of California, Berkeley. C. Kirabo Jackson is associate professor of human development and social policy at Northwestern University. Claudia Persico is a doctoral candidate in human development and social policy at Northwestern University.

This article was originally posted on EducationNext. Read Eric A. Hanushek's response to this article titled, "Money Matters After All?" here, and the three author's counter-response in an article titled, "Money Does Matter After All" here.

The Great Recession and its aftermath: What role do structural changes play?

The last seven years have been disastrous for many workers, particularly for lower-wage workers with little education or formal training, but also for some college-educated and higher-skilled workers. One explanation is that lackluster wage growth and, until recently, high unemployment reflect cyclical conditions—a combination of a lack of demand in the U.S. economy and greater sensitivity of workers on the bottom-rungs of the job ladder to changes in the business cycle. A second explanation attributes stagnant wages and employment losses to structural changes in the labor market, including long-term industrial and demographic shifts and policy changes that reduce the incentive to work. This explanation interprets recent trends as the “new normal” and suggests that the U.S. economy will never return to pre-recession labor market conditions unless policies are changed dramatically.

My research, based on a review of extensive data on labor market outcomes since the end of the Great Recession of 2007-2009, finds no basis for concluding that the recent trend of stagnant wages and low employment is the “new normal.” Rather, the data point to continued business cycle weakness as the most important determinant of workers’ outcomes over the past several years. It is only in the past few months that we have started to see data consistent with growing labor market tightness, and even this trend is too new to be confident. The continued stagnation of wages through the end of 2014 implies that, at a minimum, a fair amount of slack remained in the labor market as of that late date. In turn, policies that would promote faster recoveries and encourage aggregate demand during and after recessions remain key policy tools.

Why is this relevant for policymakers?

Labor force participation rates are still down sharply since the onset of the Great Recession, but the unemployment rate, which spiked from 5 percent to 9.5 percent during the recession, has almost returned to its pre-recession level. If the low participation rate reflects structural economic changes then the current labor market is the “new normal” and there is not much that policymakers can do to improve short-term performance. If instead the problems are due to cyclical economic weakness, generating continued labor market slack that is hidden by the low unemployment rate, then there is much more scope for fiscal and monetary policy to improve labor market conditions. Clearly, cyclical and structural explanations imply vastly different policy responses.

A number of structural shifts have been suggested as explanations for the “new normal,” among them a reduction in workers’ willingness to take jobs (perhaps driven by changes in the incentives created by government transfer programs such as extended unemployment insurance), an aging population that creates shortages of younger workers, and rapid shifts in employers’ needs toward newer types of skills that are in short supply in the labor force. My examination of recent data finds little basis for any of these hypothesized changes. Rather, the evidence—most notably stagnant wages among those who are employed—suggests that lackluster employment growth from 2009 through at least the end of 2014 reflected a continued shortage of demand for virtually all types of workers. It is only in the most recent data—which may well be a temporary blip—that we start to see wage growth consistent with a tightening labor market. It is far too soon to conclude that structural changes will prevent a full recovery to pre-recession labor force participation rates. In the meantime, it will be important to have accommodative fiscal and monetary policies, lest we strangle the belated, still nascent recovery in its infancy. What little wage growth we have seen to date suggests little reason to worry that increases in demand for labor above the current level will trigger meaningful wage inflation.

What do the data say?

The unemployment rate has been below 6 percent since September 2014, lower than many estimates of the level consistent with “full employment.” (Even in a full-employment labor market, we would expect some unemployment as workers transition from one job to another.) Yet the employment-to-population ratio—the share of working-age adults who hold jobs—has been much slower to recover after the Great Recession, and remains lower than was seen at any point between 1984 and 2009. The difference between these measures of labor market slack reflects a sharp decline since 2007 in the share of the population that is participating in the labor market. These declines have continued throughout the recovery, and show no sign of being reversed.

Diagnoses of the situation have thus depended on which data series one chooses to emphasize. The unemployment rate data suggested a robust recovery from early 2011 onward. By 2014, the economy appeared to have little room left to improve, leading some to conclude that the still low employment rate and weak wage growth must have been the “new normal.” But the employment rate series suggested that there remained substantial slack left in the labor market throughout the period as four percent of the population who had been employed before 2007 but were not being pulled back into the labor market. Neither data series in isolation could reveal the true state of the labor market.

To distinguish between these “glass-half-full” and “glass-half-empty” views, I look to evidence regarding employment and wage growth by industry and demography, seeking indications of imbalances between labor supply and demand. If the labor market in 2013-14 was as tight as the unemployment rate alone indicated then we should have seen wage increases as employers bid against each other for workers who were in increasingly short supply. By contrast, if wage growth remained anemic throughout the period, and if employment shortfalls were spread evenly across high- and low-skill demographic groups, then that would be an indication that the unemployment rate was misleading and that the labor market remained quite slack.

Findings by industry

One potential source of structural problems is an imbalance between employers’ needs and the skills being offered by job seekers. Rapid technological changes can lead to increases in the demand for workers with specialized skills, yet slack might still remain in other parts of the labor market. There is clear evidence of this sort of imbalance in the mining and logging sector, which has grown substantially since before the recent recession and where there are clear signs that employers are having trouble finding workers to fill open jobs. But outside of this sector, there is little sign that demand growth has been disproportionately concentrated in sectors such as information and technology that typically require specialized skills.

Rather, job openings have grown most in sectors such as transportation, lodging and food services, and arts and recreation. These data generally appear consistent with the view that the increase in job openings reflects reduced recruiting efforts, lower starting wages, or higher minimum qualifications rather than shortages of qualified workers.  (See Figure 1.)

Figure 1

It also is possible that demand for labor within certain industries created shortages of some particular types of workers that are masked by weakness in other subsectors. This explanation is perhaps most plausible for the finance and information sectors, where one can easily imagine shortages of workers with industry-specific skills. The information sector, where technological changes requiring new skills are most likely to be an important component of labor demand, and thus where structural labor supply shortages are most plausible, has had only a modest increase in job openings, and total employment remains below its 2007 level.

Findings by demography

Another source of evidence about mismatches between workers skills’ and firms’ needs lies in the demographic distribution of unemployment. In the recent recession, unemployment rose much more for non-college workers than for those who had attended college, and at each education level more for men than for women. The latter likely reflects the disproportionate declines in construction and manufacturing, which are cyclically sensitive industries that were very hard hit in this cycle. The former could be consistent with a shift in favor of higher-skill workers.

But data from the subsequent economic recovery contradict this explanation. The unemployment rate fell faster in the recovery for less-skilled workers than for college-educated workers, and particularly fast for non-college men. There is no indication that the unemployment rate for college-educated workers has reached any sort of a floor since it remains—even in the most recent data—notably higher than in 2007. (See Figure 2.)

Figure 2

Findings regarding wages

Ultimately, the most decisive way to diagnose the adequacy of labor demand is by examining wages: If employers are having trouble finding suitable workers then they will compete against each other for those workers who are available, bidding up wages. Across-the-board labor shortages would mean increases in wages across the economy while shortages for workers with specialized skills would mean raises in particular sectors.

If the economy were pushing against overall limits then we would expect to see rising wages. But the data through 2014 showed no signs of upward pressure on wages. Average real wages (adjusted for inflation) were stagnant since 2009, with increases below 1 percent per year even in 2014. Workers at the very top of the wage distribution saw larger increases, but even these totaled only 2 to 3 percent between 2008 and 2014, and they were concentrated among the top 20 percent of workers. Below the 80th percentile, real wages fell by about 3 percent at the median. It is only in the most recent data (since the beginning of 2015) where there is any sign of real wage growth, at roughly a 3 percent annual rate. If this is sustained, and especially if it accelerates in the coming months, then it might indicate that the labor market has finally begun to tighten. But a few months of data are too little to support this conclusion, particularly when real wage growth has been boosted by low inflation attributable to declines in energy prices. (See Figure 3.)

Figure 3

Over the longer period, there is no sign of meaningfully larger wage increases in sectors with rising job openings, as would be expected if these sectors faced persistent labor shortages. Across industries, only the mining and finance sectors appear to have posted meaningful wage increases, and even these have averaged less than 1 percent per year real wage growth. Once again, the patterns in the data are fully consistent with continued demand weakness, and not at all consistent with growing shortages of workers in growing sectors. (See Table 1.)

Table 1

Policy implications

In the years since the Great Recession, the unemployment rate has gradually crept downward while other indicators of the health of the labor market have been stagnant. Lackluster wage growth and high unemployment rates among lower-skilled workers appear to be attributable to a continued shortage of demand in the U.S. economy, combined with greater sensitivity to cyclical conditions of workers on the bottom-rungs of the job ladder. That means the high nonemployment rate among lower-skilled workers is not the “new normal” but rather could be substantially resolved by more robust economic growth and better fiscal and monetary demand-management policies.

Further, my research suggests that increased aggregate demand for workers, at the current level, will not create inflation. At best, we are only in the past few months seeing meaningful tightness. More likely, this is an artifact of declining oil prices, which means the current labor market still has substantial slack. Under the latter interpretation, additional labor demand would improve employment outcomes, with particular benefits for low-skilled workers and other disadvantaged groups who suffer disproportionately from cyclical downturns.

My results also counsel against many of the recommendations made by proponents of the view that the economy has settled into a “new normal.” In particular, there are two ill-advised responses to current conditions in the labor market predicated on a misdiagnosis of the economy as having escaped the cyclical downturn. First, tax cuts or reductions in unemployment insurance or means-tested government transfer programs aimed at increasing labor supply will do more to reduce wages than to increase employment.

Second, education and training programs aimed at increasing the skill of low-wage workers are unlikely to do much to help the labor market when there are demand shortages at every rung of the job ladder. So education and training programs are unlikely to help in the short term. That said, these programs alongside increased income support for low earners still make sense as a response to long-term trends—even if they cannot be expected to contribute meaningfully in the short run.

Taking ill-advised policy steps, such as failing to implement needed fiscal and monetary policies to boost demand for labor, or, worse, implementing policies aimed at tamping down an overheating economy, could extend periods of underemployment, damaging workers’ productivity for many years to come. Every month that the economy continues to underperform is making us poorer for decades into the future. Over-cautious policy could cause substantial damage. It is also crucial to put policies in place now to prepare for the next downturn, to avoid such a sustained, weak recovery.

Conclusion

Claims that the economy is nearing its growth potential, and that ongoing low employment rates are the unavoidable consequence of structural changes in the labor market, are at odds with the evidence. Neither comparisons across industries or education groups, nor analyses of wage growth offer any evidence of tight labor markets pushing up against their limits. Unemployment rates remain higher than in 2007 for all ages, education levels, genders, and industries. Sectors that have been more cyclically sensitive in the past saw larger increases in unemployment in the Great Recession, but there is remarkably little difference beyond this observation in the current data. And wages have continued to stagnate for the vast majority of workers, at least until the very most recent data. All of these patterns are consistent with an ongoing shortfall in aggregate labor demand, and less so with a gradual adjustment to technological or demand-driven shocks that created demand for new types of skills that cannot be satisfied by the current workforce.

View full pdf here.

Jesse Rothstein is an associate professor of public policy and economics and the director of the Institute for Research on Labor and Employment at the University of California, Berkeley. This featured research was originally posted on the Washington Center for Equitable Growth.

Museums Can Change - Will They?

Our great art institutions are cheating us of our artistic patrimony every day, and if they wanted to, they could stop.

I tell my students, and only somewhat flippantly, that arts policy is the most important policy arena. Seriously? Well, most people think health policy is right up there—but why live longer if life isn’t worth living? And if you don’t think government has a lot to do with whether and how you can engage with art, you just don’t understand the situation.

Think about a world in which our great paintings and sculpture are mostly on view instead of where they actually are, which is mostly locked up in the basements and warehouses of a handful of our largest museums. In which you didn’t have to go to one of a half-dozen big cities to see them, and didn’t rush through an enormous museum for a whole day because you paid so much to get in. In which you weren’t constantly afraid that you aren’t entitled to what you see, or competent to engage with it. That world is actually within reach, and the main reason we don’t have it is that the people to whom we have entrusted our visual arts patrimony have nailed each other’s feet to the floor so they can’t move toward it, and done so with the tacit approval and even collaboration of government.

Big museums have long refused to recognize their unexhibited collections of duplicates and minor works as a financial resource. As a consequence, they are wasting value by keeping these works hidden. If they were redistributed to smaller institutions, and even to private collectors and businesses, they would fund an explosion of the value for which we have museums in the first place: people looking at art and getting more out of it when they do.

The story will wind its way through accounting rules, professional ethics, and tax policy, but we can start right in a museum. This is such a conventional ritual that it requires conscious effort to realize how many things about it could be different, and maybe should be. Let’s do a field trip and look around!

A Museum Field Trip

We arrive during regular business hours or on a weekend, as the museum is open evenings only once a week. The building looks a lot like a temple, and is probably situated like one, in a park or up on a hill. We walk in past a wall of names that no one is looking at. Famous artists? No—donors. Every name on this wall records a financial transaction—but what exactly was sold in those deals? Strangely, though anywhere from a third to 90 percent of the millions of dollars acknowledged here is actually tax money, not private funds, the government and the taxpayers aren’t listed.

Usually there’s no less museum for anyone else if we go in, but this visit is going to cost some serious coin (though we didn’t pay anything when we visited the National Gallery of Art in Washington). The posted tariff offers the same thing at different prices to different people, as well as quantity-discounted admission with a newsletter subscription. This is called a “membership,” though it doesn’t entitle us to vote on anything.

We take a floor plan and perhaps an audio guide, and plunge into a maze of galleries without windows or clocks, an environment as disorienting as a Las Vegas casino. Of course, the galleries are full of art….Well, not actually full, as the paintings are spaced across the walls rather loosely. Through the rooms people (mostly women) come and go, talking occasionally in hushed tones of Michelangelo, and texting. Visitors look at each work for about six seconds, bobbing in and out to read tiny labels with an almost random selection of information. Some galleries have explanatory panels introducing the ensemble on view, with text that may be historical or biographical, may be in art-criticalese jargon or at the most elementary, introductory level, but is always laudatory and enthusiastic about the work on view: Everything here is absolutely superb.

The art is sorted by place, medium, and date of origin. At about 1900, we experience either relief or anxiety on realizing that decoding symbols (is St. Jerome the one with the lion, or the arrows?) is no longer useful, and we start to see things and images that don’t seem to be about—or of—anything, and that we would never realize are art if they weren’t in a museum. We might chat among ourselves about the art, but our engagement is quite one-way. At a concert we can at least applaud; at a restaurant we actually eat the food; at a gallery the art is for sale; and at the science museum we can touch and pick things up.

We’ve been on our feet for three hours now, though we did occasionally find a bench. Let’s go sit down and have lunch! The restaurant menu radiates educated upper-middle class: We can get a latte, but not a hot dog. What’s that—you’re tired and maxed out? We could leave and come back tomorrow, but then we’d have to pay another admission charge. So we keep going and try to see it all.

On the way out is a store selling an immense variety of things, of which not one would qualify for display in the museum, though all have something to do with art. Lots of books, and lots of tchotchkes. Art supplies, with which we could make something ourselves, are always in the children’s section.

Not everything of interest is obvious here, especially what we can’t see. We didn’t see art being made, or learn anything about how that happens. (What’s silverpoint, again? Giclée?) We didn’t see the wheels of the art world turning (dealers, auctions, collectors, artists, and critics); indeed, one would infer from a museum that what we are looking at has nothing to do with either the business of art or the process of making it. For every object on view, another 20 are in storage; almost none will ever be displayed. And, perhaps most important, we didn’t see the 80 percent of the population who didn’t go to an art museum at all in the last year.

What Are Museums For?

An art museum is a business, often a big one, but a special kind. In the United States, almost all of them are tax-exempt, educational nonprofits, with unique privileges given in return for certain kinds of social value; in other countries, they are typically government agencies, though this difference in legal form has minimal effect on their behavior. In both cases, they get to spend tax money. Either public money is appropriated directly, or, in the American system, contributions to museums are tax-deductible, and each gift carries a public subsidy. Furthermore, museums are typically exempt from state and local taxes, even though they receive the usual services of the fire and police departments, sidewalks, and the like.

They are also charged to care for the physical art objects that embody civilization and culture. Of course, science, literature, political institutions, religions, and performing arts are cultural storehouses too, but the plastic arts are unique in being at risk of loss by physical destruction. Losing the autograph score of Bach’s Mass in B minor would be a pity, but there are lots of copies adequate to perform it from; the loss of the Athena Parthenos was forever.

To think about how art museums could do their job better, we need a better idea of what that job is beyond just “owning art and showing some of it.” In his 1979 book, The Art Museum: Power, Money, Ethics, journalist Karl Meyer could write, “Since the turn of the century, museum professionals themselves have been trying to define the nature of the art museum,” and things have not been much clarified since. Museum mission statements are all over the map. The most common words (after art) in a 2011 survey of mission statements were: collect, museum, program, exhibit, cultural, educate, public, artist, and (oddly) words. The verbs here describe the behaviors of the museum, not the visitors (educate/exhibit, but not learn/see). With a very few interesting exceptions—of which my favorite is the Detroit Institute of Arts’ deliciously terse “Creating experiences that help each visitor find personal meaning in art”—these statements describe what museums undertake to do, but say almost nothing about what they expect to accomplish for their audiences. There is a lot of attention to making art accessible but little about art actually being accessed, or what happens to visitors who seize those opportunities.

What about visual cues? Well, reviewing the home and “about” pages of major American museums, I found only three showing anything other than art from the collection or the building from the outside. Detroit’s “about” illustration is distinctive and notable: It has young people looking at one of the Rivera murals (which we see only in a sidelong, partial view), guided by a docent who is not just talking but using her whole body. It is a picture of engagement with art, not just having art. In contrast are the Met’s aerial shot of people milling about in an enormous lobby, which could have been taken in Grand Central Station, and the Art Institute of Chicago’s picture of staff and the back of a large canvas.

I think the extremely abstract and passive presence of the museum’s public in these statements is an important and symptomatic failing, and I propose a different assignment: The purpose of an art museum is more, better engagement with art. Anything a museum does that can’t be connected back to this goal is peripheral and incidental.

Of course, this short version hides multiple dimensions of performance. “More” can entail more people looking at the art, looking at it for longer times, and looking at more, as well as more kinds of, art. Recently, museums have realized that “more” should also mean more kinds of people, especially across ethnic and social class categories. Half of people with graduate degrees went to art museums last year, but only 10 percent of high school graduates; 24 percent of whites went, but only 12 percent of blacks. And museums properly think about people in a very long future, most not yet born, and almost neurotically protect their collections for those future viewers from fire, flood, umbrellas, humidity changes, and finger oil.

“Better” is the more interesting part of my recipe. Perception, science has shown, is an active process. The only art engagement that matters is created inside the head of a viewer who combines a visual (in this case) stimulus from an artist’s work with a whole library of prior experiences and knowledge, ideas (not always art ideas) that “come to mind” (not always the conscious mind) when she confronts something presented as art. Better engagement results from presentation and installation, including mundane matters like lighting, air conditioning, and whether you can actually get to the work through a crowd. It also results from managing the library of experience that you open up and “see” the work with, including how today’s engagement with a painting (and its explanatory label, and its neighbors on the wall) enriches your engagement with an upcoming lifetime of art experiences.

Better engagement is what justifies the research function as well. People have a different experience of a work when they know who made it, whom he or she studied with, who commissioned and owned it, and how an engraving gets on paper. Better engagement puts the museum in the business of making a more competent and more demanding arts public. (Because this process is lifelong, it can’t merely be delegated to the schools, though the current savaging of arts education in K-12 schools is a tragedy, and a blunder, that we have to leave for another discussion.)

My simple goal statement already entails a variety of ways to make a better museum, and forces attention to ruthless trade-offs. For example, it may be easier to get a lot of people to come to the museum to see work that professional judgment thinks ephemeral or even schlocky, or for a bunch of wrong reasons (pornographic edginess, or high auction prices), but they can’t have a better experience if they don’t come at all. Works on paper have a finite lifetime of exposure to light, so every minute they are displayed is a minute they are denied to future generations. No simple formula can be confidently applied to optimize a museum’s discharge of its responsibilities, but steering by the “more, better engagement” star is useful.

Museums may have economic development benefits, attracting Richard Florida’s creative class, and they have served economic elites as indicators of status and distinction for generations. They are certainly good for curators’ children’s orthodontia, and a museum retrospective directs a Niagara of money into the pockets of an artist and her dealer. But all these are incidental and, as we will see, sometimes at odds with the point of a museum. The ball to keep our eye on, again, is arts engagement.

What Should We Want More Of?

How could museums do more and better? Well, for “more,” they could show more of the art they have. Any top-rank museum exhibits no more than a twentieth of its collection, often much less. There is some rotation in and out of storage but, as a rule of thumb, consider the least distinguished object in a gallery, and you can be sure that there are one or two just a teeny bit inferior, and a dozen nearly as good, in a warehouse or the basement. The Met, for example, shows 27 of its 41 Monets, but only three out of its 13 Eugène Boudins. When it comes to engravings and drawings, the ratios fall dramatically: For example, none of the Met’s 134 etchings, and only two of its 23 drawings, by Fragonard are on display. If it really damages the experience of a painting to see it any closer to its neighbor (recent museum practice has been to greatly increase the spacing between works, and never “sky” them one above the other), more art for the public would mean building more galleries and expanding museum buildings.

Second, for “better” engagement, museums could have educational programs that, as a nurse grad student of mine once said, “start where the patient is” and begin before the visitor leaves home. Enjoy history? Here’s how this painting explains it, and why it happened when and where it did. Basement woodworker? Here’s how they made the inlays in this chest. Religious? This painting is a theological tract, and here’s how it works. Political lefty? Let me introduce you to George Grosz. Think you might want to own original art? Here’s how to start.

Unfortunately, most museums are in very straitened financial circumstances, and all this costs a lot of money. The recession hit them hard, with charitable giving and government support cut way back and operating expenses hard to reduce. Ideas like these are pipe dreams, right?

Well, no. To understand why, we need to look at some museum financials, almost all of which are online as part of their annual reports. Take a look at the typical museum’s balance sheet asset column. There’s the building itself—worth millions, but it’s pointless to talk about selling that. Furniture and equipment? Not much there, and we’re using it. Endowment? Only a few dozen millions, and the whole point of an endowment is to grow it, earn some income, and hold it for safety, not to cash it in. Tractor to mow the lawn? Now we’re scraping the bottom of the barrel.

But wait a minute. Where’s the art? Incredibly, it’s not there. No museum known to me recognizes its art collection on its balance sheet. When it buys a painting, there’s an expense, and then it just disappears, as though they bought lunch for everyone and ate it. This might not matter if the amounts were small, but they are actually quite breathtaking. I have estimated the value of the collection of the Art Institute of Chicago (AIC) by triangulating in various ways from a couple of the rare cases in which museum collections were actually appraised (Detroit and the Berkeley Art Museum). The 280,000 objects in its collection turn out to be worth between $26 billion and $43 billion.

This finding has dilated the pupils of everyone I have ever shared it with. “How much??! Wow, what would the Met’s number be? The Louvre’s?” A common management assessment of a firm is “return on equity” (ROE). This is roughly the net value the firm creates each year, divided by the net assets it holds, comparable conceptually to the interest on a loan or the gain from an investment. We can make a coarse calculation of this kind for a museum by valuing the visitor-hours and research it provides in a year (with caution; these cost-benefit-analysis valuation techniques are always approximations). In the case of the AIC, the ROE is less than 1 percent. As the AIC is a wonderful museum in many ways (go there!), this is in no way a worst or even a bad case—but no established private firm would be allowed to stay in business, or keep its management, if that’s all it could earn with the resources investors (that’s us, citizens) entrusted to it. Private firms, when they get up and running, have to promise ROE numbers in the 5 percent range to get people to give them control of resources, and a big museum is not a startup deliberately running a high burn rate to set up big profits in the future. Of course, this kind of talk feels like rough and untrained hands being laid on the precious beating heart of immortal and ineffable art, so let’s leave it at this: Knowing the monetary value of a large museum’s collection raises very salient questions about how that resource is actually being used, and whether that use is the best it can do.

Accordingly, the most important policy reform museums need is for the Financial Accounting Standards Board (FASB), a private organization that establishes the rules accountants have to use, to require them to value their collections and report them as assets. And if the FASB doesn’t do this (an attempt to do so a couple of decades ago failed), state attorneys general, who oversee nonprofits, should do it, not to mention museum trustees, who cannot responsibly oversee their institutions without this information. The excuses for this omission are that it would be a big bother to appraise a large collection, and as the museum never intends to use the art as a financial resource by selling any or borrowing against it, there’s no point. But simply asserting that those 134 Fragonard etchings have no monetary value doesn’t make it true: If you call a dog’s tail a leg, it still has four legs, and the Detroit Institute of Arts’ collection was absolutely on the table as a financial asset in the city’s bankruptcy. What if the refusal to value collections were relaxed? How could placing a valuation on those enormous collections create more, better engagement with art?

Given that so little of it is ever exhibited or ever will be, maybe we could start at the bottom and sell some stuff out of storage that has no real prospect of being shown. What would that buy? Selling just 1 percent of the collection by value—much more than 1 percent by object count—would enable the AIC to endow free admission forever. You read that right: free admission forever, on the sale of just 1 percent—with a nice lagniappe of reduced storage expenses, to boot. Free is the right price for a nonrival good (you’re not displacing anyone else) like attending a museum that isn’t congested, and makes it much easier for people to engage with art in a sane way, a couple of hours at a time (better engagement!). As it happens, the AIC triggered a big debate recently when it raised prices to pay for its new building (adult general admission is now $23). When the British national museums went to free admission in 2001, attendance more than doubled—more engagement!

How much should museums charge for admission? As I suggested, the main reason the price should usually be zero rests on the most fundamental normative principle of economics: Everything should be sold at marginal cost. If a museum isn’t congested, the marginal cost of one more visitor is a little wear on the floor and a few cents worth of air conditioning; unlike a seat in a concert hall, it doesn’t deprive anyone else of the chance to visit. Note that this principle is technical, and is neither a moralistic assertion that art is priceless or besmirched by money, nor a political judgment. If you wake up a Chicago economist and a lefty progressive in the middle of the night, they both say, “Marginal cost pricing!”

Farebox revenue is hard to give up, but to make it easier for a low-income public to attend, some museums have adopted a “pay what you wish” approach (with very heavy-handed suggestions as to amount). Is it psychologically easier to attend if you’re made to feel like a charity case? And why ask people to estimate the value of the experience before they have it? It would be relatively easy to do experiments to let visitors decide how much to pay as they leave and see what happens. I did that once, many years ago, for a special exhibition with an extra charge, and revenues were substantially higher than when visitors were charged going in.

If the museum is so crowded that your visit interferes with someone else’s—and a few like MoMA, the Louvre, and the Uffizi are in that state—then it’s appropriate to charge admission that will ration access by price (and subsidize attendance for those who can’t afford the fee). But it would be much better to expand the museum! When a lot of new families move to town, we don’t start auctioning seats in class, we build more public schools. Going back to our AIC example, selling another percent of the museum’s collection would pay for 30 percent more exhibition space (either where it is now, or in a big satellite somewhere), to actually show us more art.

Let’s go crazy and sell another percent—that would endow $17 million a year of operating budget, a fifth of the institute’s current “instructional and academic” staff costs, which would enable it hire to something on the order of 200 more full-time researchers, educators, designers, and people studying the audience to understand what really goes on when people get up close to art. All this, and the AIC would still be sitting on 97 percent of the value of its current stockpile, but showing a third more of it, and better.

In business language, we could say that the AIC has drastically misallocated its capital resources between the assets of “building” and “art,” and also misallocated resources between production (the staff) and capital. Idling capital is a waste, just like idling labor, and if done in secret as it is here, may even justify associated charges of fraud and abuse.

If you open this discussion with museum people, as I have done, you find out very quickly that you have walked into a hornet’s nest called the “deaccessioning debate.” Deaccessioning is fancy art language for selling, and the first thing the director you have provoked will tell you about is the museum directors’ code of ethics, which forbids him to ever sell art except to buy more art. If he did, he could never lend anything to other museums or borrow any art from them. He probably couldn’t have coffee with his pals at the next convention either: outer darkness, and how appropriate for unethical behavior.

Of course, this code was not brought down a mountain by Moses; the directors themselves made it up. A code of ethics is a good thing, but it isn’t a law of God or nature. Once upon a time, the lawyers’ code of ethics forbade them to advertise. Now it doesn’t; the republic and the bar endure. The museum directors’ code says, “Gifts and bequests should be unrestricted whenever possible,” in part because a donor’s restrictions on how a work is shown, or whether future judgment finds it deserving of display at all, lets donors short-circuit professional expertise forever. But important museums like the Met and the Stanford University collection have violated this rule spectacularly and haven’t been excommunicated, so maybe these ethical principles are not quite the moral absolutes they claim to be.

A piece-by-piece appraisal of a large collection is an enormous undertaking (though it was somehow accomplished fairly quickly for the Detroit museum) and the cost of such an exercise might justify omitting it from financial reporting. But it isn’t necessary to do this to get a useful estimate of the total value—say, plus-or-minus 10 percent. Things like art values have an exponential distribution, with a large percentage of the value in relatively few items. Museums know what their masterpieces are, and these few thousand items would have to be appraised individually. But the rest can be sampled by drawing randomly from accession numbers (every object has one) and actually appraising as little as 5 percent of the other works. This process is never perfect, but completely doable: Museums appraise individual objects when they insure them for loan exhibitions and (obviously) when they are offered art for purchase. Large companies value unique assets with thin markets, like buildings and patents, well enough to inform regulators and managers.

What the no-sale provision is good for is to protect the big old museums, which have collections far larger than they can ever show, from even thinking about having to share, or about operational changes like the ones described above. It’s about managerial comfort and institutional prestige, and has nothing to do with the public interest.

My colleague Eugene Smolensky asked rhetorically on reading an early draft of this essay, “If we could reallocate all the art across museums optimally, how much of it would wind up where it is now?” Museums like those in San Francisco, which were late to start seriously collecting while those in Eastern cities already had a half-century head start, can never catch up under current rules, while lots of art that smaller markets would kill for is locked up in the vaults of the Met and the AIC and their ilk. The existing allocation is interesting; here, for example, is the distribution of some Monet paintings in U.S. museums:

Is this patrimony distributed so as to create the most art engagement value possible? Is it fair? The small Harn Museum of Art in the college town of Gainesville, Florida, is so proud of its single Monet that it issued a reassuring press release when it was lent for four months to a temporary exhibition across the state in Naples; the AIC, on the other hand, sees fit to keep almost a fifth of its Monets in storage.

Deaccessioning and Its Discontents

The debate about selling from collections has been characterized by an unusual combination of naïveté, careless and tendentious language, and posturing. Without rehashing it all, let us note here, first, that works sold from the unexhibited collection of a museum are not “lost,” especially if they are sold to another museum. Indeed, even if they go to a collector’s private home, they will be seen by more people than when they were in the vaults; the same is true if they are bought by businesses for their offices—and these sales could reserve a right to borrow the works back now and then. (People don’t buy original art and lose or mistreat it or hide it—they almost always show it and care for it.) But garage sales by our overstocked, big-city major museums would mainly put important art on the walls (not in the basements) of museums in places where art is scarce. The reason I’m so interested in simply changing the accounting rules, so we can see these assets as we see the endowment, is that I expect sunshine to provoke a conversation in which simply asserting selling to be evil will have less force, and options like the ones I floated above will be in play.

If we establish that sold art doesn’t leave the planet or go into a landfill, defenders of the dog-in-the-manger approach will claim, “These paintings were given to us with the understanding that we would never sell them! And if we sell even unrestricted items, no one would ever give us anything again!” To which we may ask, “What will they do with it instead?” (And, “How much more art that you have no space to show do you really want?”) Art usually goes to museums when collectors’ heirs don’t want it. Here is where the tax code becomes important, along with the sociology of the big-time art world. A lot of paintings in museums were received as tax-deductible gifts, and the donor’s deduction is based on the full market value of the painting, even though no tax was paid on its appreciation in his hands. So giving a painting bought for $10,000 that could now be sold for $110,000, minus the $28,000 capital gains tax a wealthy donor would pay, costs the donor $82,000 (and thank you, certainly)—but earns him back a tax break of 39.6 percent (his marginal tax rate) of $110,000, or $43,560. So the gift actually only costs him $38,440; taxpayers pony up the rest. (Calculations for bequests under the estate tax are different; in general, that tax subsidy now only benefits the wealthiest collectors with multimillion-dollar estates.)

This whole arrangement may or may not be good public policy; in my book written with Alan L. Feld and J. Mark Schuster, Patrons Despite Themselves, we examine this question extensively and of course conclude, “It’s complicated!” But the charitable-contribution deduction is certainly not necessary to have museums, as it was nonexistent or de minimis when the great U.S. museums were being established, and is unimportant outside the United States, where there are lots of nice museums full of art. The part of the scheme that’s important here is that the donor gets the same deduction regardless of whether the work is given with a restriction on sale. This makes no economic or moral sense: A painting the museum is stuck with storing and protecting forever is simply worth less than a painting that may be sold, just as unrestricted money gifts are more valuable than gifts with strings attached. A nice amendment to the tax code would require the IRS to reduce the appraised value of donated art to reflect any restrictions, including restrictions on sale. This would at least make collectors think twice about demanding them.

It would not control winks and nods, however: A collector might well shop his painting around to find a museum willing to make an unofficial agreement. We have to think about the sociological context of this deal-making, not just explicit rules, because donors gain social status by being able to say that they collected work fine enough to be accepted into “the collection of” the most prestigious museum that will take it. If museums established an ethical obligation to never assure retention, and made it clear that while gifts are welcome, restrictions really are against the rules, collectors would find it harder to play them against each other this way.

A bigger question is, why do large museums that can only show a fraction of what they already have (or even of the really good stuff), and that are increasingly besieged by visitors whose numbers in the space available seriously damage the art-engagement experience, continue to fight for acquisitions that would create much more value if dispersed to smaller “markets”? Why don’t they more effectively steer donors to give money for programs that put more people, more effectively, in front of more art? Eli and Edythe Broad, the 800-pound gorillas of the Los Angeles art scene, have a refreshingly different take here, explaining to the Los Angeles Times in 2008 why they gave the Los Angeles County Museum of Art dibs on borrowing (and ponied up for an enormous building expansion) but would not donate works:

….our job is to have our collection be seen by the broadest possible public. And with all due respect to the museums, they will only lend to their peers. LACMA will lend to the Met. They will lend to the Modern, to the Louvre, to the National Gallery. But they will not particularly make a point of lending to Knoxville, Portland, where they can’t get anything in return.

So we thought a lot about this and we said we’re gonna make this a public collection, and we’re going to favor LACMA. Whatever LACMA wants to have on their walls they can have on their walls for as long as they want to have it on their walls. But if they want to put it in the basement, we want to be able to have it shown elsewhere.

Governance and Policy

A century ago, art museums changed society’s relationship to art by spearheading the transition from private collecting by and for the rich and powerful into the modern public museum. Today, they can change that relationship again. The symphony and the opera don’t have the resources for such an enterprise, but museums do; what sort of innovations should we be demanding?

The most important opportunity is the explosive availability of art as very high-quality digital content, the revolution that has upended the worlds of music, drama, and text. Of course, original artworks will always trade in a separate market from reproductions, and seeing the “real thing” close-up is not the same as having a perfect image projected on your retina from a screen. But the second is not inferior to the first, just different and complementary, especially when it’s available on demand from a “custom-made” museum you can organize for yourself with a few clicks, out of works thousands of miles apart. The Google Cultural Institute serves up virtual walking tours of almost 500 museums around the world, with thousands of works available in very high resolution, actually higher than you can usually get standing in front of the real painting.

What hasn’t happened, but is underway, is the release of painting, print, and drawing collections from their storage vaults into the digitized cloud (sculpture is a different story). When it happens, it will be less of a problem that big museums show so little of their collections “live,” and the opportunities for creative and enriched modes of engagement will have expanded enormously. But crucially, it will be less important for a museum to actually possess (for possible research study) works it doesn’t show.

Merely invoking technology or shoveling out more information can easily miss the mark; success is also a matter of attitude and empathy. When I worked in a museum, I had some troubling epiphanies, like the time the curator of a quarter-mile of decorative arts galleries, full of chairs with ropes across them and nowhere for a visitor to sit, interrupted my staff meeting presentation about seating to say, “Mike, I don’t know why we’re spending time on this; if I want to sit down, I can go to my office. I don’t need chairs in the galleries!”

I still remember being infuriated by the label on a pair of metal devices in a vitrine, etched in my memory as “Pair of objects for striking fire, with three lines of Qu’ranic script. They are beautifully made and invite our touch.” Okay, I’m an engineer and a shade-tree mechanic. You have my interest:How do you strike fire with them—hit them together? Rub? Did they hold flints? Do you use them together, or one at a time? What is “Qu’ranic script”—a calligraphic style, like Kufic? Is it a pedantic way to write what hoi polloi call “lines from the Quran”? And I understand why they’re under glass, but why, Mr. Curator, are you rubbing it in that you can touch them and I can’t? “Education” like this may be well-meaning, but it is inept.

I also had some eye-opening moments, such as when a curator would walk me through his galleries and just talk to me about the art. It’s really breathtaking how interesting these folks can make their stuff, and no, you don’t get it by reading their published work, or from the labels they write, or from the audio guide; it only happens when they aren’t looking over their shoulders at their peers and showing off how erudite they are. Everyone can’t have that kind of personal engagement, of course, but could we give every visitor something like it? I don’t want someone talking in my ear when I’m watching a play or listening to a string quartet, but this can happen right in front of a painting—what an opportunity!

As a visitor, I keep encountering missed opportunities and misfires, usually resulting from an insouciant unconcern for what would really enrich the experience for a typical visitor—that is, a visitor a museum should want to make repeated visits. The big David Hockney exhibition at San Francisco’s de Young Museum that I saw last year was full of the artist’s experiments with synchronized videos, iPad drawing, and the like, mostly well-documented and explained. But it also included Hockney’s 30 riffs on Claude Lorrain’s “Sermon on the Mount”—with no image of the Lorrain anywhere to be seen. Not educated enough to bring it up in memory, I had to find it on the Web on my phone. No, the original of 1656 is not copyrighted. The unspoken message is, if you don’t have the Lorrain original in your head, you’re not really qualified to be here. A few months later I ran into the original at the Frick, where it would have benefited greatly from association with a couple of Hockney’s covers (as reduced-size reproductions, of course). But while Hockney hasn’t slowed down for a minute at 77, the Frick has long been frozen in aspic. Here’s a wasted opportunity to put an important work into a context of artistic borrowing and exchange, and to make a centuries-old painting speak to a modern art lover.

Audio guides and smartphone apps, more and more common but still needing work, are the beginning of an exciting new way to engage with art. “Beginning,” because there’s plenty of headroom for improvement. A stellar Kandinsky exhibition at New York’s Neue Galerie had an audio guide, but I had to start up Spotify on my phone with earphones to associate his theater set designs for a “Pictures at an Exhibition” ballet with the respective parts of the music, which could perfectly well have been available on a headset on the wall next to each piece, or on the audio tour device. I know the music pretty well, but not well enough to be sure I wasn’t remembering “The Great Gate of Kiev” when I was looking at the old castle set. Much too often, the audio commentary itself is delivered in an off-putting academic style with a stuffy accent—a lecture from someone who would rather be somewhere else. Why can’t it be conversational, and share real enthusiasm and curiosity?

Getting with the tech revolution is not the only opportunity museums could seize by starting to use their enormous idle wealth responsibly. Real research about the visitor experience, which flowered briefly (mostly in science museums) between the 1930s and ’80s and then withered, could inform presentation so it actually works better, instead of just looking good to other curators and designers. At present, museums know very little about their audience and even less about the people who don’t attend. (Where, for example, did we get the bizarre idea that six seconds is the right amount of time to spend with a painting worth looking at—and isn’t it the responsibility of art museums to fix that?)

Building more space (and endowing its maintenance and operation) is an obvious path toward “more engagement,” at least for the people who attend now. What about those who don’t? Again, we need more research, but many of my students at a big public university simply don’t feel entitled, by background or competence, to art in a museum. When I take them on a field trip, I can sense a strong defensive and insecure reaction: “If I don’t see what’s so great about this, I must be not good enough for it.” Art-historical expertise and connoisseurship are not chopped liver. But they are not everything, not even everything about art. How is it that one can go in and out of every great museum and have no idea that there is a large body of research in cognitive psychology and the brain science of perception that (as the eminent art historian E.H. Gombrich was not too blinkered to see) makes art more important, more interesting, and more relevant? Ms. Curator, you may be way up there in the art world pecking order, but you are no Gombrich: Learn from him! There is simply no reason a visitor to the de Young Museum should need his kids to take him across town to the Exploratorium to learn about this.

Would it hurt society’s relationship to art if the institutions that display it had a less religious and awestruck affective orientation to the work? A less one-dimensional scale of value—which doesn’t sort objects out on a “masterpiece” index and induce visitors to scoot past wonders in search of the most famous few pieces—would help. Indeed, why don’t museums show us some fashionable bad art and explain why it is such, and authorize us to believe that if we think this or that piece is silly or a con, we might be right? Certified excellence isn’t the only way to be interesting and considerable. Why aren’t they more willing to entertain the idea that a lot of stuff selling for big money is faddish, schlocky, or silly (but may still be interesting), rather than torturing themselves into making excuses for an embalmed shark or one more metal balloon animal? Why can’t we see the experts disagree and argue with each other?

Management failures usually start with governance failures, and museum boards are way too heavy on wealthy collectors and too light on psychologists, artists, educators, and science-museum curators. Board selection is a hermetic, self-replicating process focused on wealth and social status to the exclusion of expertise, judgment, and wisdom; Met director Thomas Hoving memorably captured this willful blindness with his immortal, “Any trustee should be able to write a check for at least $3 million and not even feel it.” Why don’t members elect a trustee or two to provide real guidance? Even members of a bowling league, not to mention citizens of a state, have governing responsibility and authority.

The director of a top-rank museum like the Met or Chicago—certainly two or three of them together—could put paid to the code-of-ethics deaccessioning roadblock as quickly as Saudi Arabia could dismantle OPEC. However, real progress in more effective and creative use of collections will most likely begin with minor or specialized museums and those constrained by smaller collections, like the San Francisco Museum of Modern Art. Unfortunately, the prestige pecking order of museums, to the extent that we assess them by size and fame of collections, makes it extremely difficult for the dinosaurs to learn from these improvisational, adaptive little creatures, and they need help from larger institutions.

One of these, of course, is government, including (in the United States) grant-giving and subsidizing agencies like the National Endowments for the Arts and Humanities and the National Science Foundation’s social science programs, and overseers like state attorneys general. Museums that have not estimated their collection value and reported it should not be eligible for NEA grants. The distinctive U.S. system delegates government-like powers to tax-exempt nonprofits, including museums and the FASB, so discussion of “arts policy” has to attend also to the governance and practices of the institutions themselves. The first task for all these parties should be accountability, both financial (valuing their collections, at the least) and operational. The second should be pressure to use museums’ enormous latent wealth to create, well, more, better engagement with art in all the dimensions of the phrase.

Museum culture is deep and ingrained. Realizing the latent value in our patrimony will, finally, require a public that asks our institutions, graciously but insistently, whether they are using the priceless resources they have been given to serve the public interest as well as possible.

This article was originally posted in Issue #36, Spring 2015 of Democracy: A Journal of Ideas.