The corporate governance literature has long argued that corporate boards should be comprised of a majority of independent directors. This is the result of a simple agency theory argument: Boards comprised of insiders (i.e., firm employees) will put their own interests ahead of the shareholders’. Moreover, any insider other than the CEO may have incentive to accommodate, rather than challenge, the CEO in the boardroom. Independent directors are assumed not to have such conflicts of interest and therefore to be better monitors of management on behalf of shareholders.
This argument, combined with corporate scandals in the early 2000s, has led to both regulatory requirements and shareholder activist pressure for increased board independence–to the point that many firms now have only one insider on the board, the CEO. That’s well beyond the theoretical justification for increased independence. But is it actually a good thing for the CEO to be “home alone” as the sole insider on the board? Has the push for board independence gone too far?
Corporate scandals of the previous decade have heightened attention on board independence. Indeed, boards at many large firms are now so independent that the CEO is ‘home alone’ as the lone inside member. We build upon ‘pro-insider’ research within agency theory to explain how the growing trend toward lone-insider boards affects key outcomes and how external governance forces constrain their impact. We find evidence among S&P 1500 firms that having a lone-insider board is associated with (1) excess CEO pay and a larger CEO-top management team pay gap, (2) increased likelihood of financial misconduct, and (3) decreased firm performance, but that stock analysts and institutional investors reduce these negative effects. The findings raise important questions about the efficacy of leaving the CEO ‘home alone.’
Following concerns that insider-dominated boards failed to protect shareholders, there has been a push for greater board independence. This push has been so successful that the CEO is now the only insider on the boards of more than half of S&P 1500 firms. We examine whether lone-insider boards do in fact offer strong governance or whether they enable CEOs to benefit personally. We find that lone-insider boards pay CEOs excessively, pay CEOs a disproportionately large amount relative to other top managers, have more instances of financial misconduct, and have lower performance than boards with more than one insider. Thus, it appears that lone-insider boards do not function as intended and firms should reconsider whether the push towards lone-insider boards is actually in shareholders’ best interests.
Much of the research on franchising as an organizational form relies on an agency theory explanation. In short, it assumes operators of local franchise establishments will have greater incentive to operate efficiently if they are owners of the establishment (i.e., franchisees) rather than managers employed by the franchisor-owner. However, there isn’t a lot of empirical research substantiating that assumption. Matt Sveum and my recent working paper finds that there does appear to be a franchise effect–but it depends on the nature of the business format. We use US Census data for essentially all limited- and full-service restaurants in the US and find franchising explains differences in establishment performance for full-service, but not for limited-service, restaurants. The abstract follows:
While there has been signiﬁcant research on the reasons for franchising, little work has examined the effects of franchising on establishment performance. This paper attempts to ﬁll that gap. We use restricted-access US Census Bureau microdata from the 2007 Census of Retail Trade to examine establishment-level productivity of franchisee- and franchisor-owned restaurants. We do this by employing a two-stage data envelopment analysis model where the ﬁrst stage uses DEA to measure each establishment’s eﬃciency. The DEA efficiency score is then used as the second-stage dependent variable. The results show a strong and robust effect attributed to franchisee ownership for full service restaurants, but a smaller and insigniﬁcant difference for limited service restaurants. We believe the differences in task programmability between limited and full service restaurants results in a very different role for managers/franchisees and is the driving factor behind the different results.
The current issue of Journal of Empirical Legal Studies includes an interesting data resource and survey by Bernard Black, et al., titled Medical Liability Insurance Premia: 1990–2016 Dataset, with Literature Review and Summary Information. Having just talked briefly about med mal premia and healthcare regulation last week, I was interested to read through the review and description of some of the data and trends. The authors have compiled data from the Medical Liability Monitor, “the only national, longitudinal source of data on med mal insurance rates.” But they don’t stop there.
We link the MLM data with several related datasets: county rural-urban codes (from 2013); annual county- and state-level data on population (from the Census Bureau); number of total and active, nonfederal physicians, with a breakdown by specialty (from the Area Health Resource File, originally from the American Medical Association); annual state-level data on paid med mal claims against physicians from the National Practitioner Data Bank (NPDB), available through 2015; and data on direct premiums written by med mal insurers from the National Association of Insurance Commissioners (NAIC), available through 2015. We also provide a literature review of papers using the MLM data and summary information on the association between med mal insurance premia and other relevant features of the med mal landscape.
The data appendix, public data, and STATA code book (for cleaning the dataset) are also available from SSRN here. The survey includes a summary of some research into possible explanations for and consequences of medical malpractice premia: effect of med mal risk on healthcare spending, effect of med mal reform on med mal premia, effect of med mal rates on C-section rates and physician supply, effect of med mal payouts on med mal premia.
Noticeably absent from the literature they summarize, which they claim are the principle prior studies using MLM data, is any attention to or focus on market structure issues. Doubly so since there has been a consistent drop in rates over the past 15 years that is generally unexplained in the cited literature. Now, I don’t specialize in health care industry research, but I do know that in the past 15 years there has been an ongoing trend of consolidation among both health insurance companies and medical providing companies (e.g., hospital networks, physician groups, both). I could easily hypothesize a couple potential dynamics:
Increased consolidation among insurance companies may lead to contractual incentives (by way of contract rates and performance measures) that affect the expected cost of med mal insurance.
Increased consolidation among hospital networks and physician groups leads to more consistent or standardized practices across larger populations of patients/services, thereby reducing uncertainty or volatility of medical service provision/quality and, thereby, expected cost of med mal insurance.
I suspect there are several potential channels, but it would seem a potentially fruitful area of research–and now there is a more convenient data set with which to play.
Justus Haucap and Joel Stiebale with the Düsseldorf Institute for Competition Economics (DICE) at the University of Düsseldorf have a recent paper analyzing the effects of mergers on innovation in the European pharmaceutical industry. The develop a model that suggests mergers reduce innovation not only in the merged firms, but among industry competitors as well. Their data bear this out, as explained in the abstract:
This papers analyses how horizontal mergers affect innovation activities of the merged entity and its non-merging competitors. We develop an oligopoly model with heterogeneous firms to derive empirically testable implications. Our model predicts that a merger is more likely to be profitable in an innovation intensive industry. For a high degree of firm heterogeneity, a merger reduces innovation of both the merged entity and non-merging competitors in an industry with high R&D intensity. Using data on horizontal mergers among pharmaceutical firms in Europe, we find that our empirical results are consistent with many predictions of the theoretical model. Our main result is that after a merger, patenting and R&D of the merged entity and its non-merging rivals declines substantially. The effects are concentrated in markets with high innovation intensity and a high degree of rm heterogeneity. The results are robust towards alternative specifications, using an instrumental variable strategy, and applying a propensity score matching estimator.
While I haven’t yet read the paper in detail, a cursory examination suggests they have ignored another possibility: mergers in high-intensity R&D industries could be a leading indicator of decreased innovation productivity (i.e., lower returns to investment in R&D). Consider that as research advances, the “low hanging fruit” are collected first before the more difficult (and lower return) investments are pursued. As companies in a high-intensity R&D industry exploit all of the low hanging fruit, particularly internally, one might expect mergers as a way of expanding the available set of lower-cost/higher-return R&D investment opportunities. Since firms are competing in the same science space, a slow-down in one firm is likely to be spuriously correlated with slowdowns throughout the industry.
“Affect” is a word of causation. To suggest that mergers cause a reduction in innovation is a strong statement–especially when paired with a merger policy implication. This may be something that bears more scrutiny since, as the authors note, the entire subject is one on which relatively little light has thus far been shed.
Steven Levitt of Freakonomics fame (and professor of economics at University of Chicago) has a new paper out on a not-so-new research project. In “Heads or Tails: The Impact of a Coin Toss on Major Life Decisions and Subsequent Happiness” (gated at NBER, a summary article is available here), Levitt finds that individuals who made important life decisions based on a coin flip were more likely to be happy two or six months afterward. Based on these findings, Levitt suggests that individuals may be too cautious in making major decisions. The abstract reads:
Little is known about whether people make good choices when facing important decisions. This paper reports on a large-scale randomized field experiment in which research subjects having difficulty making a decision flipped a coin to help determine their choice. For important decisions (e.g. quitting a job or ending a relationship), those who make a change (regardless of the outcome of the coin toss) report being substantially happier two months and six months later. This correlation, however, need not reflect a causal impact. To assess causality, I use the outcome of a coin toss. Individuals who are told by the coin toss to make a change are much more likely to make a change and are happier six months later than those who were told by the coin to maintain the status quo. The results of this paper suggest that people may be excessively cautious when facing life-changing choices.
So if in doubt, maybe you should reach in your pocket for a coin. Or you could do it like this guy:
The latest Journal of Economic Perspectives includes a pair of papers debating the social value of economics research funding from the National Science Foundation, featuring Robert Moffitt from Johns Hopkins and Tyler Cowen and Alex Tabarrock from George Mason. The abstracts of their respective viewpoints follow:
Robert Moffitt: “In Defense of the NSF Economics Program“ The NSF Economics program funds basic research in economics across all its disparate fields. Its budget has experienced a long period of stagnation and decline, with its real value in 2013 below that in 1980 and having declined by 50 percent as a percent of the total NSF budget. The number of grants made by the program has also declined over time, and its current budget is very small compared to that of many other funders of economic research. Over the years, NSF-supported research has supported many of the major intellectual developments in the discipline that have made important contributions to the study of public policy. The public goods argument for government support of basic economic research is strong. Neither private firms, foundations, nor private donors are likely to engage in the comprehensive support of all forms of economic research if NSF were not to exist. Select universities with large endowments are more likely to have the ability to support general economic research in the absence of NSF, but most universities do not have endowments sufficiently large to do so. Support for large-scale general purpose dataset collection is particularly unlikely to receive support from any nongovernment agency. On a priori grounds, it is likely that most NSF-funded research represents a net increase in research effort rather than displacing already-occurring effort by academic economists. Unfortunately, the empirical literature on the net aggregate impact of NSF economics funding is virtually nonexistent.
Tyler Cowen & Alex Tabarrock: “A Skeptical View of the National Science Foundation’s Role in Economic Research” We can imagine a plausible case for government support of science based on traditional economic reasons of externalities and public goods. Yet when it comes to government support of grants from the National Science Foundation (NSF) for economic research, our sense is that many economists avoid critical questions, skimp on analysis, and move straight to advocacy. In this essay, we take a more skeptical attitude toward the efforts of the NSF to subsidize economic research. We offer two main sets of arguments. First, a key question is not whether NSF funding is justified relative to laissez-faire, but rather, what is the marginal value of NSF funding given already existing government and nongovernment support for economic research? Second, we consider whether NSF funding might more productively be shifted in various directions that remain within the legal and traditional purview of the NSF. Such alternative focuses might include data availability, prizes rather than grants, broader dissemination of economic insights, and more. Given these critiques, we suggest some possible ways in which the pattern of NSF funding, and the arguments for such funding, might be improved.
11th Annual Conference on Empirical Legal Studies (CELS)
Duke Law School, Durham, North Carolina
Friday, November 18 and Saturday, November 19, 2016
Duke Law School is pleased to host the 11th Annual Conference on Empirical Legal Studies (CELS) on November 18-19, 2016. CELS is a highly regarded interdisciplinary gathering that draws scholars from across the country and internationally and is sponsored by the Society for Empirical Legal Studies. The conference brings together hundreds of scholars from law, economics, political science, psychology, policy analysis, and other fields who are interested in the empirical analysis of law and legal institutions. Papers are selected through a peer review process and discussion at the conference includes assigned commentators and audience questions.