Click here for the announcement for the Second Annual Conference on Empirical Legal Studies,
which will be held at New York University on November 9-10, 2007. The conference's official website is at: http://www.law.nyu.edu/cels/. The paper submission deadline is July 1, 2007.
I just finished reading a really terrific empirical study by Joanna Shepherd (Emory Law), Fred Tung (Emory Law), and AlbertYoon (Northwestern Law), entitled Cross-Monitoring and Corporate Governance. In a nutshell, the authors show, after controlling for a wide variety of relevant control variables (most importantly corporate governance), that companies that rely on bank loans, as opposed to equity or public debt, post higher market returns. Presumably, these results flow from the heightened monitoring and positive market signaling supplied by loan agreements. Their multiple specifications do a nice job of ruling out alternative hypotheses.
This is quite an important paper for thinking about manager and director agency costs, especially in a world where portfolio diversification has reduced the incentives for shareholders to pay attention to annual elections for directors. (It also is a excellent example of methodology for large panel data.) Here is the article abstract:
We take the view that corporate governance must involve more
than corporate law. Despite corporate scholars' nearly exclusive focus on
corporate law mechanisms for controlling managerial agency costs, shareholders
are not the only constituency concerned with such costs. Given the thick web of
firms' contractual commitments, it should not be a surprise that other
financial claimants may also attempt to control agency costs in their contracts
with the firm. We hypothesize that this cross-monitoring by other claimants has
value for shareholders.
We examine bank loans for empirical evidence of the value of
cross-monitoring. Our approach builds on prior empirical work on the value of
good corporate governance, to which we add data on the presence of bank loans
and their interactions with free cash flow, governance indices, and individual
corporate governance provisions. We find strong evidence that bank monitoring
adds value. In effect, bank monitoring can counteract somewhat the
value-decreasing effects of managerial entrenchment. Bank monitoring may
substitute for good corporate governance.
UCLA will be hosting the sixth summer institute on the Empirical Implications of Theoretical Models (EITM) from June 24 to July 21, 2007:
The Summer Institute on EITM seeks to train a new generation of
scholars who can better link theory and empirical work. It is a highly
interactive training program for advanced graduate students and junior
faculty led by political scientists from across the discipline who
employ EITM in their research. Summer institutes general[ly] accept 25
advanced graduate students and junior faculty through a competitive
selection process. In most cases, tuition, room and board, travel and
living expenses are covered for participants through a grant from the
National Science Foundation.
Graduate students who will benefit most from the program should be
committed to using both theoretical models and empirical data in their
dissertations. They should have some training in both formal
methodology and quantitative analysis -- and advanced training in at
least one of these areas. We will also accept junior faculty looking to
improve their defended dissertation in a direction that incorporates
EITM, or junior professors that are embarking on a "second EITM-like
First, I'd like to thank the editors of ELS for asking me to guest blog. I think that blogs can provide valuable points of intellectual interaction and can also be a lot of fun.
A while back, Washington University law professor Margo Schlangerblogged on ELS about trial courts and trial court judicial politics, and
I was hoping to revisit this topic. Her Civil Rights Litigation Project goes a
long way toward facilitating research on trial courts. Trial courts and access
to justice have long been research interests of mine. Between other research
projects and teaching, I have been doing some reading on the use of summary judgment by trial court judges and especially empirical examinations of summary
This week's guest blogger is Jeff Yates, Associate Professor of Political Science at the University of Georgia. Jeff received his J.D. from the University of Tennessee and his Ph.D from Florida State University. His research focuses on the study of judicial process, criminal justice and tort litigation. His recent work is available here.
A number of ELS gurus have blogged about empirical courses offered by law schools. I'd like to raise some issues about teaching ELS in law schools.
1. What are we trying to do? Is the goal to teach statistics to students with no background so that they understand empirical evidence? Or are we trying to go further than that and enable students to produce statistical evidence and/or understand academic ELS? Ideally, the answer would be both, but its hard to do this with one course, and right now one course is the high end for the number of ELS courses offered at any law school. With time, law schools may begin offering ELS sequences with more than one course, which would help solve the problem, but right now any ELS course has to decide what its goal is.
2. How do we get the right people to take the right course? If law schools are only offering one course on ELS, then it seems to make sense for the course to be introductory. One concern with this is that the course may be disproportionately taken by people with prior backgrounds in the subject-- the course will be reteaching stuff that most of the students had heard already, rather than introducing new material to those who would most benefit. Assuming law schools will be reluctant to make statistics mandatory, I 'm not sure what the solution should be.
3. How do we teach ELS? Should it be taught with an ordinary statistics book, or is there something to be said about greater integration of the law into a course. Its easy to say that law should be integrated into the course, and that is certainly the preferred option, but how do we go about doing it? Is there a textbook that does this? When its all said and done, it might be easiest to teach the skills directly.
FACULTY JOB OPENING: The Harvard School of Public Health is seeking candidates for a tenure-ladder position as assistant or associate professor of law and public health. The faculty member will work on collaborative health law research projects with a focus on empirical research. Information is available at http://www.hsph.harvard.edu/searches/hpm1.html.
Back in November, I posted an announcement for the Law Firms Working Group, which is a joint initiative of the American Bar Foundation and Indiana Law. Pursuant to a special licensing agreement with American Lawyer Media (ALM), the Working Group is soliciting proposals for research projects that will utilize a large cache of data on law firms, including information on law firm profitability, revenues, billing rates, firm size, structure, office locations, various dimensions of associate satisfaction, lawyer demographics, technology migration, recruitment of new associates, lateral partner mobility, corporate clients, big deals and big lawsuits, and much more. Most of the variables are available for multiple years.
ALM is remarkably good at collecting data, but academic researchers--i.e., ELS readers--have a comparative advantage when it comes to analyzing it. This is the core insight that produced the special licensing arrangement. In my capacity as the Working Group director, I have received numerous inquires and several proposals. If you are interested in submitting a proposal, the deadline is February 16. Note that we are limited to twelve active projects. See this announcement for details.
"Threatened and endangered species recovery programs consume increasing resources. Even so, there is increased concern about actual and projected biodiversity losses and in the success of recovery programs in reversing these trends. In this paper, we use a panel data set and ordered probit econometric methods to statistically examine the determinants of the 1990-2002 biennial U.S. Fish and Wildlife Service (FWS) recovery scores for up to 225 vertebrate species listed as threatened or endangered under the Endangered Species Act. We find that species-specific spending is a significant determinant of species' recovery scores and that increased spending reduces the probability that FWS will classify a species as extinct or declining. The evidence does not support the hypothesis that increased spending increases the probability that a species is stable or improving. Other FWS' actions have significant and substantive influences on improved recovery scores. These include progress on or completion of a recovery plan and achievement of stated recovery objectives. We find evidence that species achieve better recovery scores if FWS considers them to have high recovery potential and that species whose recovery is judged by FWS to be in conflict with economic activity are more likely to be classified as extinct. Our evidence does not support the conclusion that critical habitat designation promotes species' recoveries or prevents species' declines. We also report a new finding that recovery success varies across FWS administrative regions."
In 2005, Citizens for Tax Justice released a report on effective state corporate income tax rates entitled "Corporate Tax Avoidance in the States Even Worse Than Federal." The most prominent conclusion of the study is that:
A new analysis of the state corporate income taxes paid by 252 of America’s largest and most profitable corporations finds that by 2003, these companies on average failed to include two-thirds of their actual U.S. pretax profits on their state tax returns.
By 2003, these 252 companies had slashed their state income tax payments to an average of only 2.3 percent of their U.S. profits. Since the average statutory state corporate tax rate is about 6.8 percent (weighted by gross state product), that means that in 2003, two-thirds of their profits escaped corporate tax entirely.
This is an important study of corporate income tax rates-- a subject we know little about-- and I don't doubt the finding that two-thirds of corporate profits avoided state tax. I am less certain, however, that this is mostly because companies set out to avoid state corporate income taxes.
For companies that operate in multiple states, corporate income must be apportioned to each state. States do this through a formulary system. In 1957, the formulary was based on an equal weighting of sales, property, and payrolls. As I understand it (please correct me if I'm wrong), this means that if a company had 10% of its sales, 33% of its property, and 60% of its payroll in Alabama ,and 90% of its sales, 67% of its property, and 40% of its payroll in CA, then 36.7%=(.333*.1)+(.333*.4)+(.333*.6) of that corporation's income would be apportioned to Alabama and 63.3%=(333*.9)+(.333*.6)+(.333*.4) of its income to California. Many states have changed the formula, however to overweight sales. In a state like Alabama, this would reduce the corporation's state tax burden. For example, if Alabama placed a two thirds weight on sales, then only 23.3%=(.667*.1)+(.167*.4)+(.167*.6) of that corporation's income would be taxed in Alabama.
If every state followed the same formulary (and doubled the weight on sales), then on a national level there would be no decrease in tax. The company would pay less of its tax in Alabama, and more tax (76.7%) in California where sales are high. Every state doesn't follow the same formulary, however. For some background, see pages 14 and 15 of this article. Indeed, I think that states with high sales typically do not place added weight on sales. If California sticks with the original formula while Alabama deviates, then only 86.6%=63.3%+23.3% of corporate income will be attributed to some state.
Thus, the effective state corporate tax rate will be lower than the average state corporate tax rate, not because comapanies are deliberately avoiding corporate income taxes, but rather because the formulary inconsistencies allow some corporate income to be effectively untaxed. I don't know about the size of this effect, and it may be small, but if the formularies are highly skewed, it is easy to imagine that a lot of corporate income doesn't get taxed in any state without any deliberate avoidance by corporations. Further empirical work on this issue could easily get at the size of this effect.
Last summer I posted about Ronen Avraham's (Northwestern) database containing state tort law reforms for all fifty states (and DC) during the recent decades. Ronen recently mentioned updates to that database that make it even more user-friendly, especially as it relates to coding. Those interested in the updated database can access it (and the related paper) here.
One of my favorite articles about the costs of bankruptcy is by David Cutler and Larry Summers (yes, that Larry Summers). Here is the abstract of the article:
Since 1984, Texaco and Pennzoil have
been engaged in a legal battle over Texaco's usurpation of Pennzoil in
the takeover of the Getty Oil Company. The stakes are huge: the jury
award that has been upheld through several appeals calls for Texaco to
pay Pennzoil more than $10 billion. The Texaco-Pennzoil case presents a
unique natural experiment for studying debt burdens and bargaining
costs. Essentially continuous market assessments of the prospects of
both parties in a high stakes bargaining game are rarely as observable
as they are in the case of publicly traded companies like Texaco and
Pennzoil. Further, unlike in the Texaco case, financial distress is
usually brought on by events impinging directly on a firm's operations,
thus making the costs of distress difficult to measure.
paper uses data on the abnormal returns earned by the shareholders of
Texaco and Pennzoil to examine whether resources were "lost" in the
course of the litigation. We find that the leakage involved in the
forced transfer is enormous: each dollar of value lost by Texaco's
shareholders has been matched by only about 30 cents gain to the owners
of Pennzoil. Our estimates suggest that the Texaco-Pennzoil conflict
has reduced the combined equity value of the two companies by about $2
billion. Further losses have been suffered by Texaco's bondholders,
though these may be offset by the tax collections that would result if
Texaco made a large payment to Pennzoil. After documenting
the large joint losses that Texaco and Pennzoil have suffered, we seek
to identify their causes. Clearly one explanation is the fees that both
companies will pay to the many lawyers, investment bankers, and
advisors that have been retained. Even making generous allowance for
these costs, however, we are unable to account for a large fraction of
the loss in combined value. It appears that there have been additional
costs to Texaco's shareholders from disruptions in Texaco's operations,
difficulties in obtaining credit, incentive problems created by fears
that Texaco would cease operations, and distraction of top management.
The argument that "difficulties in obtaining credit, incentive problems created by fears
that Texaco would cease operations, and distraction of top management." hurt value is reasonable, but the paper doesn't provide much evidence of this. This has always bothered me. Today, I'll search for some evidence that fits in with a long finance literature on the impacts of the impacts of financing contstraints on investment. One way the difficulties caused by the verdict might have killed value is by limiting investment. If Texaco's managers were distracted and Texaco's access to outside credit was limited, then we'd expect its investment to go down. If Texaco is passing up good investment opportunities because of the litigation, then this is a real cost of the litigation that might explain the drop in combined value of Texaco and Pennzoil.
So did investment at Texaco go down?
To answer this, I took a look at capital expenditure rates at Texaco and other oil companies (in the same NAICS code) between 1980 and 1994. I'll use a basic differences-in-differences framework:
Inv(year i,company t)=a+b*Texaco_dummy+c*post_trial_dummy +d*Texaco_dummy*post_trial_dummy+error term
The key coefficient is d, whether or not something special happened to Texaco's investment after the post trial verdict. Note that the investment variable is scaled by the size of the company to allow for comparison.
The results are inconclusive-- not surprising when there is only one variable receiving the treatment. Texaco's investment indeed went down after 1984-1985. In 1980-1983, Texaco's capital expenditures equalled around 11% of gross PPE. In 1986-88 (the initial verdict was in late 1985), Texaco's capital expenditures went down to around 5.5% of hard assets. It sound like a big decline, confirming the Cutler-Summers speculation. The problem is that the capital expenditures of other oil companies went down even more, from around 15% of gross PPE in 80-83, to around 8% of gross PPE in 86-88.
The estimate of d is actually positive (around .01)-- Texaco's investment went down less than other company's investment after the verdict-- but the coefficient is nowhere near significant.
If the verdict had a bad effect on Texaco's capital expenditures, we can't find that effect in the midst of the heavy decline in investment for all oil companies during the period. Cutler and Summers' speculation about the cause of the value decline for Texaco remains speculation.
Those interested in a slightly more sanguine perspective on the role of IRBs (especially in the bio-medical setting) will find Jerry Menikoff's (Kansas, Medicine) recent paper helpful (forthcoming in a Northwestern L. Rev. symposium issue). An excerpted abstract follows:
"... Admittedly, the current system is
imperfect and a variety of improvements can and should be made to
eliminate those review requirements that do little to protect subjects.
But even with these problems, getting IRB approval of social and
behavioral research studies should in the great majority of cases be a
relatively non-burdensome task that is a minimal hindrance to the
conduct of the research. That burden should rarely if ever rise to the
level of triggering constitutional protections against censorship."
Defined Contribution plans have greatly expanded over the last two decades. Defined Contribution plans place the investment risk on employees. Employee investment decision making should be examined to determine whether those decisions are influenced by race, ethnicity and/or class.
Empirical data show that investor behavior is greatly influenced by race, ethnicity and/or class. Blacks and Hispanics are far less likely to invest in the stock market than whites. Low-income whites are far more likely to invest in the stock market than blacks or Hispanics regardless of income. As a result, retirement account balances are the greatest for many white households and the least for black, Hispanic, and certain white households. This article explores those issues and suggests solutions that will allow employees to overcome their built-in biases and make wiser investment choices.
I'm a big fan of regression discontinuity studies. In a regression discontinuity study, there is typically a discontinuous determination of who receives a treatment. For example, a cholesterol medication may be given to all individuals with bad cholesterol levels over x, but to no individuals with cholesterol levels below x.
In a regression discontinuity design, we exploit the discontinuity to determine the treatment effect. The idea is that some individuals randomly fall just above the treatment cutoff (in my example, they have a cholesterol level of x+epsilon) while others fall just below (have a cholesterol level of x-e). These individuals are pretty similar-- their cholesterol levels are almost identical, yet they get treated differently. Some get the treatment, but others don't. If, after receiving the treatment, a group of people with original cholesterol levels just above x have a much lower cholesterol level than a group with original cholesterol levels just below x (who do not get the medication), then we can attribute that decrease in cholesterol level to the medication.
It is, of course, true that the people who receive the medication have a higher average cholesterol level than those who do not, but the size of the effect is small and can be controlled for.
When regression discontinuity assumptions are valid, then the design is a great way to obtain valid inferences of causal effects in a non-experimental setting. For a really cool application of regression discontinuity to estimate the impact of class size on test scores, see Angrist and Lavy (1999).
The validity of the identification from regression discontinuity designs comes from the assumption (among others) that people with cholesterol levels just below x are very similar to those with a cholesterol level just above x. This assumption will be satisfied when people are unaware of the cutoff, or if the cutoff is not important enough to induce any change in behavior. When making or not making the cutoff is an important choice variable, however, then the validity of the inferences may be flawed.
For example, suppose that people know x and that this medication is highly anticipated-- some people really want to be able to take the medication. Suppose also that you can regularly check your cholesterol and affect your level by modifying behavior. If this is the case, then people with cholesterol levels just below x might be very different from people with cholesterol levels just above x. The ones with cholesterol levels just above x might be people who really wanted the medication and made sure to have just enough cholesterol, but not more than that. The ones with cholesterol levels just below x apparently didn't care about getting the medication or were "bad" at controlling their cholesterol levels. Under these assumptions, the groups are very different in their attitudes towards medication and/or their motivation levels, in spite of the fact that their cholesterol levels are very similar.
When we apply the regression discontinuity design in this case, then we do not get the valid inferences of the impact of the medication that we'd like. The difference in post-treatment cholesterol levels between those with original cholesterol levels just above vs. just below x may be due to the medication, but they also may be due to other factors, such as differences in motivation or difference in belief in the power of medication.
At the recent AFA meetings in Chicago, there was a very interesting paper by Chava and Roberts that may be subject to this critique. The paper tries to estimate the impact of violation of debt covenants on the amount of corporate investment. The paper applies a regression discontinuity design. Many covenants define minimum net worths. The paper estimates the effect of violating the covenant by comparing the investment decisions of companies that barely violated net worth covenants with the decisions of companies that barely avoided violations. The paper assumes that these companies are similar except for the fact that some violated the covenants and others didn't.
I'm not so confident that this assumption is valid. I presume that most companies want to avoid covenant violations. Once you've avoided a violation, however, then you care much less about your actual net worth and don't spend much time worrying about it. This means that companies that barely violate the covenants may be systematically different than those that don't violate the covenants. The companies that violate may less careful, more honest, or be in a much more delicate financial position than those that are just above the minimum new worth. The effect found by Chava and Roberts may be the impact of covenant violations, or it may be due to the fact that the two groups they are comparing are systematically different.
I don't want to sound too negative, however. Regression discontinuity is a great research design, and I'd love to see more of it in empirical legal studies.