Archives For Sykuta

Mike Sykuta and I have been blogging about our new paper responding to scholars who contend that institutional investors’ common ownership of small stakes in competing firms significantly reduces market competition and should be restricted.  (FTC Commissioner Noah Phillips cited the paper yesterday in his excellent prepared remarks on common ownership.)  Mike first described the purported competitive problem.  I then set forth some problems with the anticompetitive theory common ownership critics have asserted.

When confronted with criticisms of their theory, common ownership critics have pointed to the empirical evidence Mike mentioned. In the most high-profile study, researchers correlated changes in commercial air fares with changes in “MHHI∆”, an index designed to measure the degree to which common ownership has reduced the incentive to compete. They concluded that common ownership has increased airfares by three to seven percent. A similar study of the commercial banking industry correlated banking fees and interest on deposit accounts with “GHHI”, a metric similar to MHHI∆. That study concluded that common ownership has led to higher fees and lower interest rates for depositors.

Common ownership critics have treated these studies as a trump card. The authors of the airline study, for example, brushed off a criticism of their anticompetitive theory with the following retort: “This argument falls short of explaining why, empirically, taking into account shareholders’ economic interests does help to explain firms’ product market behavior.”

Of course, to demonstrate “empirically” that institutional investors’ “economic interests” influence their portfolio companies’ “product market behavior” (i.e., cause the companies to charge higher prices, etc.), researchers would need to (1) correctly identify institutional investors’ economic interests with respect to their portfolio firms’ product market behavior, and (2) establish that those interests cause firms to act as they do. On those crucial tasks, the airline and banking studies fall short.

In assessing institutional investors’ economic interests, the studies have assumed that if an institutional investor reports holding a similar percentage of each firm in a market—say, five percent of the stock of each major airline—then it must have an “economic interest” in maximizing industry rather than own-firm profits. Such an assumption is unwarranted. That is because each institutional investor’s reported holdings, set forth on forms it must submit under Section 13(f) of the Securities Exchange Act, aggregate its holdings across all its funds. Such aggregation paints a misleading picture of the institutional investor’s actual economic interest.

For example, while Vanguard’s Section 13(f) filing reports ownership of a similar percentage of American, Delta, Southwest, and United Airlines—suggesting an economic interest in industry profit maximization—the picture looks very different at the individual fund level:

  • Vanguard’s Value Index Fund (VIVAX) holds significant stakes in American, Delta, and United (0.46%, 0.45%, and 0.42%, respectively) but holds no Southwest stock. VIVAX does best if United, American, and Delta usurp business from Southwest.
  • Vanguard’s Growth Index Fund (VIGRX) holds a significant stake in Southwest (0.59%) but holds no stake in American, Delta, or United. Investors in VIGRX would prefer that Southwest win business from American, Delta, and United.
  • Vanguard’s Mid-Cap Index Fund (VIMSX) and Mid-Cap Value Index Fund (VMVIX) hold significant stakes in United (1.00% and 0.321%, respectively) but hold no stock in American, Delta, or Southwest. Investors in VIMSX and VMVIX would prefer that United win business from American, Delta, and Southwest.
  • Vanguard’s PRIMECAP Core Fund (VPCCX) holds stakes in all four major airlines, but its share of Southwest (1.49%) is twice its share of American (0.72%), nearly four times its share of United (0.38%), and seven-and-a-half times its share of Delta (0.198%). Investors in VPCCX would prefer that Southwest grow at the expense of American, United, and Delta. They would also prefer that American win business from United and Delta, and that United win business from Delta.

We could go on, but the point should be clear: Because returns to retail investors in the funds of Vanguard and similar institutions turn on fund performance, the competitive outcome that maximizes retail investors’ profits will differ among funds.

Proponents of restrictions on common ownership might respond that even if an institutional investor’s individual funds have conflicting preferences, the institutional investor as an entity must have some preference about whether to maximize industry profits or the profits of a particular company. Because it cannot honor all its individual funds’ conflicting preferences with respect to competitive outcomes, the institutional investor will settle on the compromise strategy that maximizes its individual funds’ aggregate returns: industry profit maximization.  Such a strategy would be the first choice of the institution’s funds holding relatively equal shares of all firms within a market.  And, while the first choice of the institution’s funds that are disproportionately invested in one firm would be to maximize that firm’s profits, those funds would do better with industry profit maximization than with the first-choice strategy of other of the institution’s funds, i.e., those that are disproportionately invested in a different firm.

But even if maximization of industry profits leads to the greatest aggregate returns for an institutional investor’s funds, such a strategy may not be the best outcome for the institutional investor itself. An institutional investor typically wants to maximize its profits, which will grow as it attracts retail investors into its funds versus those of its competitors and steers those investors toward the funds that earn it the greatest profits (fees less costs). To assess an institutional investor’s preferences with regard to the returns of its different funds, then, one must know (1) the degree to which each fund’s attractiveness vis-à-vis rivals’ similar funds turns on portfolio returns, and (2) the profit margin each fund delivers to the institutional investor.

For funds tracking popular stock indices, portfolio returns play little role in winning business from rival fund sponsors.  (For example, higher returns on the stocks in the S&P 500 are unlikely to attract investors to BlackRock’s S&P 500 index fund over Fidelity’s or Vanguard’s.) Moreover, the fees charged on such funds, and thus the institutional investor’s potential profit margins, are extraordinarily low. For actively managed funds, portfolio returns are far more significant in attracting investors, and management fees are higher. The upshot is that an institutional investor, in determining what competitive outcome it prefers, will attach little weight to the competitive preferences of passive index funds and more weight to the preferences of actively managed funds, with that weight growing as the funds provide the institutional investor with higher profit margins.

It is quite possible, then, for an intra-industry diversified institutional investor to prefer a competitive outcome other than the maximization of industry profits, even if industry profit maximization would maximize the aggregate returns of its individual funds. Consider, for example, an institutional investor that offers funds similar to the following Vanguard funds:

  • Vanguard’s 500 Index Fund (VFIAX) holds near equivalent interests in American, Delta, Southwest, and United and would thus do best with a strategy of industry profit maximization. Its expense ratio (annual fees divided by total fund amount) is 0.04 percent.
  • Vanguard’s Value Index Fund (VIVAX) holds similar stakes in American, Delta, and United but does not hold Southwest stock. Its expense ratio is 0.18 percent.
  • Vanguard’s PRIMECAP Core Fund (VPCCX) holds a much higher stake in Southwest than in the other airlines and has an expense ratio of 0.46 percent, 2.5 times as great as the no-Southwest VIVAX fund and 11.5 times as high as the fully diversified VFIAX fund.
  • Vanguard’s Capital Opportunity Fund (VHCAX) holds significantly higher shares of Southwest and United (1.74% and 1.55%, respectively) than of Delta and American (0.65% and 1.16%, respectively). Its expense ratio is 0.38, more than twice as great as the no-Southwest VIVAX fund and 9.5 times the fully diversified VFIAX fund.

This institutional investor’s Southwest-heavy funds (those resembling Vanguard’s VPCCX and VHCAX funds) charge much higher fees than its fully diversified index fund (the one resembling VFIAX, for which fund returns are unimportant) and significantly higher fees than its funds that are more heavily invested in airlines besides Southwest (those resembling VIVAX).  Thus, despite being intra-industry diversified at the institutional level, this institutional investor may do best if Southwest maximizes own-firm profits.

The point here is that discerning an institutional investor’s actual economic interest requires drilling down to the level of its individual funds, something the common ownership studies have not done. Thus, contrary to the assertion of the airline study’s authors, the common ownership studies have not shown “empirically” that “taking into account shareholders’ economic interests does help to explain firms’ product market behavior.” Indeed, they have never established what those economic interests are.

Even if institutional investors’ aggregated holdings accurately revealed their economic interests with respect to competitive outcomes, the common ownership studies would still be deficient because they fail to show that those economic interests caused portfolio firms’ “product market behavior.” As explained above, the common ownership studies employ MHHI∆ (or a similar measure) to assess institutional investors’ interests in competition-softening. They then correlate changes in that metric with changes in portfolio firms’ pricing behavior. The problem is that MHHI∆ is itself affected by factors that independently influence market prices. It is thus improper to infer that changes in MHHI∆ caused changes in portfolio firms’ pricing practices; the pricing changes could have resulted from the very factors that changed MHHI∆. In other words, MHHI∆ is an endogenous measure.

To see why this is so, consider the three-step process involved in calculating MHHI∆ (which Mike described). The first step is to assess, for every coupling of competing firms in the market (e.g., Southwest/Delta, United/American, Southwest/United, etc.), the degree to which the controlling investors in each of the firms would prefer that it avoid competing with the other. The second step considers the market shares of the two firms in the coupling to determine the competitive significance of their incentives not to compete with each other. (The idea is that reduced head-to-head competition by bit players matters less for overall market competition than does reduced competition by major players.) The final step is to aggregate the effect of common ownership-induced competition-softening throughout the overall market by summing the softened competition metrics for each coupling of competitors within the market.

Given this process for calculating MHHI∆, there are at least two sources of endogeneity in the metric. One arises because of the second step. To assess the significance to market competition of any two firms’ incentives to reduce competition between themselves, the market shares of those two firms must be incorporated into the metric. But factors that influence market shares may also influence market prices apart from any common ownership effect.

Suppose, for example, that five institutional investors hold significant and equal stakes (say, 3%) in each of the four airlines servicing a particular air route and that none of the airlines has another significant shareholder. The air route at issue is subject to seasonal demand fluctuations. In the low season, the market is divided among the four airlines so that one has 40% of the business and the other three have 20% each. The MHHI∆ for this market would be 7200. When the high season rolls around, demand for flights along the route increases, but the leading airline is capacity constrained, so additional ticket sales go to the other airlines.  The market shares of the airlines in the high season are equal: 25% each.

On these facts, the increase in demand causes MHHI∆ to rise from 7200 to 7500.  But the increase in demand is also likely to raise ticket prices. We thus see an increase in MHHI∆ that correlates with an increase in ticket prices, but the price change is not caused by the change in MHHI∆. Instead, the two changes have a common, independent cause.

Endogeneity also creeps in during the third step in calculating MHHI∆.  In that step, the “cross MHHI∆s” of all the couplings in the market—the metrics assessing for each coupling the extent to which common ownership will cause the two firms to compete less vigorously—are summed. Thus, as the number of firms participating in the market (and thus the number of couplings) increases, the MHHI∆ will tend to rise. While HHI (the market concentration measure) will decrease as the number of competing firms rises, MHHI∆ (the measure of common ownership pricing incentives) will increase.

For example, suppose again that five institutional investors hold equal stakes (say, 3%) of each airline servicing a market and that the airlines have no other significant shareholders. If there are two airlines servicing the market and their market shares are equivalent, HHI will be 5000, MHHI∆ will be 5000, and MHHI (HHI + MHHI∆) will be 10000. If a third airline enters and grows so that the three airlines have equal market shares, HHI will drop to 3333, MHHI∆ will rise to 6667, and MHHI will remain constant at 10000. If a fourth airline enters and the airlines split the market evenly, HHI will fall to 2500, MHHI∆ will rise further to 7500, and MHHI will again total 10000.

This is problematic, because the number of participants in the market is affected by consumer demand, which also affects market prices. In the market described above, for example, the third or fourth airline might enter the market in response to an increase in demand, and that increase might simultaneously cause market price to rise. We would see, then, a price increase that is correlated with, but not caused by, an increase in MHHI∆; increased demand would be the cause of both the higher prices and the increase in MHHI∆.

In the end, then, the empirical evidence of competition-softening from common ownership is not the trump card proponents of common ownership restrictions proclaim it to be.

As Thom previously posted, he and I have a new paper explaining The Case for Doing Nothing About Common Ownership of Small Stakes in Competing Firms. Our paper is a response to cries from the likes of Einer Elhauge and of Eric Posner, Fiona Scott Morton, and Glen Weyl, who have called for various types of antitrust action to reign in what they claim is an “economic blockbuster” and “the major new antitrust challenge of our time,” respectively. This is the first in a series of posts that will unpack some of the issues and arguments we raise in our paper.

At issue is the growth in the incidence of common-ownership across firms within various industries. In particular, institutional investors with broad portfolios frequently report owning small stakes in a number of firms within a given industry. Although small, these stakes may still represent large block holdings relative to other investors. This intra-industry diversification, critics claim, changes the managerial objectives of corporate executives from aggressively competing to increase their own firm’s profits to tacitly colluding to increase industry-level profits instead. The reason for this change is that competition by one firm comes at a cost of profits from other firms in the industry. If investors own shares across firms, then any competitive gains in one firm’s stock are offset by competitive losses in the stocks of other firms in the investor’s portfolio. If one assumes corporate executives aim to maximize total value for their largest shareholders, then managers would have incentive to soften competition against firms with which they share common ownership. Or so the story goes (more on that in a later post.)

Elhague and Posner, et al., draw their motivation for new antitrust offenses from a handful of papers that purport to establish an empirical link between the degree of common ownership among competing firms and various measures of softened competitive behavior, including airline prices, banking fees, executive compensation, and even corporate disclosure patterns. The paper of most note, by José Azar, Martin Schmalz, and Isabel Tecu and forthcoming in the Journal of Finance, claims to identify a causal link between the degree of common ownership among airlines competing on a given route and the fares charged for flights on that route.

Measuring common ownership with MHHI

Azar, et al.’s airline paper uses a metric of industry concentration called a Modified Herfindahl–Hirschman Index, or MHHI, to measure the degree of industry concentration taking into account the cross-ownership of investors’ stakes in competing firms. The original Herfindahl–Hirschman Index (HHI) has long been used as a measure of industry concentration, debuting in the Department of Justice’s Horizontal Merger Guidelines in 1982. The HHI is calculated by squaring the market share of each firm in the industry and summing the resulting numbers.

The MHHI is rather more complicated. MHHI is composed of two parts: the HHI measuring product market concentration and the MHHI_Delta measuring the additional concentration due to common ownership. We offer a step-by-step description of the calculations and their economic rationale in an appendix to our paper. For this post, I’ll try to distill that down. The MHHI_Delta essentially has three components, each of which is measured relative to every possible competitive pairing in the market as follows:

  1. A measure of the degree of common ownership between Company A and Company -A (Not A). This is calculated by multiplying the percentage of Company A shares owned by each Investor I with the percentage of shares Investor I owns in Company -A, then summing those values across all investors in Company A. As this value increases, MHHI_Delta goes up.
  2. A measure of the degree of ownership concentration in Company A, calculated by squaring the percentage of shares owned by each Investor I and summing those numbers across investors. As this value increases, MHHI_Delta goes down.
  3. A measure of the degree of product market power exerted by Company A and Company -A, calculated by multiplying the market shares of the two firms. As this value increases, MHHI_Delta goes up.

This process is repeated and aggregated first for every pairing of Company A and each competing Company -A, then repeated again for every other company in the market relative to its competitors (e.g., Companies B and -B, Companies C and -C, etc.). Mathematically, MHHI_Delta takes the form:

where the Ss represent the firm market shares of, and Betas represent ownership shares of Investor I in, the respective companies A and -A.

As the relative concentration of cross-owning investors to all investors in Company A increases (i.e., the ratio on the right increases), managers are assumed to be more likely to soften competition with that competitor. As those two firms control more of the market, managers’ ability to tacitly collude and increase joint profits is assumed to be higher. Consequently, the empirical research assumes that as MHHI_Delta increases, we should observe less competitive behavior.

And indeed that is the “blockbuster” evidence giving rise to Elhauge’s and Posner, et al.,’s arguments  For example, Azar, et. al., calculate HHI and MHHI_Delta for every US airline market–defined either as city-pairs or departure-destination pairs–for each quarter of the 14-year time period in their study. They then regress ticket prices for each route against the HHI and the MHHI_Delta for that route, controlling for a number of other potential factors. They find that airfare prices are 3% to 7% higher due to common ownership. Other papers using the same or similar measures of common ownership concentration have likewise identified positive correlations between MHHI_Delta and their respective measures of anti-competitive behavior.

Problems with the problem and with the measure

We argue that both the theoretical argument underlying the empirical research and the empirical research itself suffer from some serious flaws. On the theoretical side, we have two concerns. First, we argue that there is a tremendous leap of faith (if not logic) in the idea that corporate executives would forgo their own self-interest and the interests of the vast majority of shareholders and soften competition simply because a small number of small stakeholders are intra-industry diversified. Second, we argue that even if managers were so inclined, it clearly is not the case that softening competition would necessarily be desirable for institutional investors that are both intra- and inter-industry diversified, since supra-competitive pricing to increase profits in one industry would decrease profits in related industries that may also be in the investors’ portfolios.

On the empirical side, we have concerns both with the data used to calculate the MHHI_Deltas and with the nature of the MHHI_Delta itself. First, the data on institutional investors’ holdings are taken from Schedule 13 filings, which report aggregate holdings across all the institutional investor’s funds. Using these data masks the actual incentives of the institutional investors with respect to investments in any individual company or industry. Second, the construction of the MHHI_Delta suffers from serious endogeneity concerns, both in investors’ shareholdings and in market shares. Finally, the MHHI_Delta, while seemingly intuitive, is an empirical unknown. While HHI is theoretically bounded in a way that lends to interpretation of its calculated value, the same is not true for MHHI_Delta. This makes any inference or policy based on nominal values of MHHI_Delta completely arbitrary at best.

We’ll expand on each of these concerns in upcoming posts. We will then take on the problems with the policy proposals being offered in response to the common ownership ‘problem.’

 

 

 

 

 

 

One of the hottest antitrust topics of late has been institutional investors’ “common ownership” of minority stakes in competing firms.  Writing in the Harvard Law Review, Einer Elhauge proclaimed that “[a]n economic blockbuster has recently been exposed”—namely, “[a] small group of institutions has acquired large shareholdings in horizontal competitors throughout our economy, causing them to compete less vigorously with each other.”  In the Antitrust Law Journal, Eric Posner, Fiona Scott Morton, and Glen Weyl contended that “the concentration of markets through large institutional investors is the major new antitrust challenge of our time.”  Those same authors took to the pages of the New York Times to argue that “[t]he great, but mostly unknown, antitrust story of our time is the astonishing rise of the institutional investor … and the challenge that it poses to market competition.”

Not surprisingly, these scholars have gone beyond just identifying a potential problem; they have also advocated policy solutions.  Elhauge has called for allowing government enforcers and private parties to use Section 7 of the Clayton Act, the provision primarily used to prevent anticompetitive mergers, to police institutional investors’ ownership of minority positions in competing firms.  Posner et al., concerned “that private litigation or unguided public litigation could cause problems because of the interactive nature of institutional holdings on competition,” have proposed that federal antitrust enforcers adopt an enforcement policy that would encourage institutional investors either to avoid common ownership of firms in concentrated industries or to limit their influence over such firms by refraining from voting their shares.

The position of these scholars is thus (1) that common ownership by institutional investors significantly diminishes competition in concentrated industries, and (2) that additional antitrust intervention—beyond generally applicable rules on, say, hub-and-spoke conspiracies and anticompetitive information exchanges—is appropriate to prevent competitive harm.

Mike Sykuta and I have recently posted a paper taking issue with this two-pronged view.  With respect to the first prong, we contend that there are serious problems with both the theory of competitive harm stemming from institutional investors’ common ownership and the empirical evidence that has been marshalled in support of that theory.  With respect to the second, we argue that even if competition were softened by institutional investors’ common ownership of small minority interests in competing firms, the unintended negative consequences of an antitrust fix would outweigh any benefits from such intervention.

Over the next few days, we plan to unpack some of the key arguments in our paper, The Case for Doing Nothing About Institutional Investors’ Common Ownership of Small Stakes in Competing Firms.  In the meantime, we encourage readers to download the paper and send us any comments.

The paper’s abstract is below the fold. Continue Reading…

I received word today that Douglass North passed away yesterday at the age of 95 (obit here). Professor North shared the Nobel Prize in Economic with Robert Fogel in 1993 for his work in economic history on the role of institutions in shaping economic development and performance.

Doug was one of my first professors in graduate school at Washington University. Many of us in our first year crammed into Doug’s economic history class for fear that he might retire and we not get the chance to study under him. Little did we expect that he would continue teaching into his DoughNorth_color_300-doc80s. The text for our class was the pre-publication manuscript of his book, Institutions, Institutional Change and Economic Performance. Doug’s course offered an interesting juxtaposition to the traditional neoclassical microeconomics course for first-year PhD students. His work challenged the simplifying assumptions of the neoclassical system and shed a whole new light on understanding economic history, development and performance. I still remember that day in October 1993 when the department was abuzz with the announcement that Doug had received the Nobel Prize. It was affirming and inspiring.

As I started work on my dissertation, I had hoped to incorporate a historical component on the early development of crude oil futures trading in the 1930s so I could get Doug involved on my committee. Unfortunately, there was not enough information still available to provide any analysis (there was one news reference to a new crude futures exchange, but nothing more–and the historical records of the NY Mercantile Exchange had been lost in a fire).and I had to focus solely on the deregulatory period of the late 1970s and early 1980s. I remember joking at one of our economic history workshops that I wasn’t sure if it counted as economic history since it happened during Doug’s lifetime.

Doug was one of the founding conspirators for the International Society for New Institutional Economics (now the Society for Institutional & Organizational Economics) in 1997, along with Ronald Coase and Oliver Williamson. Although the three had strong differences of opinions concerning certain aspects of their respective theoretical approaches, they understood the generally complementary nature of their work and its importance not just for the economic profession, but for understanding how societies and organizations perform and evolve and the role institutions play in that process.

The opportunity to work around these individuals, particularly with North and Coase, strongly shaped and influenced my understanding not only of economics, but of why a broader perspective of economics is so important for understanding the world around us. That experience profoundly affected my own research interests and my teaching of economics. Some of Doug’s papers continue to play an important role in courses I teach on economic policy. Students, especially international students, continue to be inspired by his explanation of the roles of institutions, how they affect markets and societies, and the forces that lead to institutional change.

As we prepare to celebrate Thanksgiving in the States, Doug’s passing is a reminder of how much I have to be thankful for over my career. I’m grateful for having had the opportunity to know and to work with Doug. I’m grateful that we had an opportunity to bring him to Mizzou in 2003 for our CORI Seminar series, at which he spoke on Understanding the Process of Economic Change (the title of his next book at the time). And I’m especially thankful for the influence he had on my understanding of economics and that his ideas will continue to shape economic thinking and economic policy for years to come.

Mike Sykuta and I, both proud Missourians, recently took to the opinion section of the Kansas City Star to discuss pending state legislation that would bar automobile manufacturers from operating their own retail outlets in the Show Me state.  The immediate target of the bill is Tesla, but the bigger concern of the auto dealers, who drafted the statutory language we criticize, is that the big carmakers will bypass independent dealers and start running their own retail outlets.

The arguments in our op-ed will be familiar to TOTM readers.  We begin with three fundamental points:  (1) Distribution is an “input” for carmakers.  (2) Producers, if left to their own devices, will choose the more efficient option when deciding whether to “buy” the distribution input (i.e., to sell through independent dealers, who pay a discounted wholesale price) or “make” it (i.e., to operate their own retail outlets and charge the higher retail price).  (3) Consumers — who ultimately pay all input costs, including the cost of distribution — will benefit if the most efficient option is selected.  In short, the interests of carmakers and consumers are aligned here: both benefit from implementation of the most efficient distribution scheme.

We then rebut the arguments that a direct distribution ban is needed to break up monopoly power, to assure adequate aftermarket servicing of vehicles, or to encourage appropriate safety recalls.  (On these points, we draw heavily from International Center for Law & Economics’ letter to Gov. Chris Christie regarding New Jersey’s proposed anti-Tesla legislation.)

Go read the whole thing.

Our TOTM colleague Dan Crane has written a few posts here over the past year or so about attempts by the automobile dealers lobby (and General Motors itself) to restrict the ability of Tesla Motors to sell its vehicles directly to consumers (see here, here and here). Following New Jersey’s adoption of an anti-Tesla direct distribution ban, more than 70 lawyers and economists–including yours truly and several here at TOTM–submitted an open letter to Gov. Chris Christie explaining why the ban is bad policy.

Now it seems my own state of Missouri is getting caught up in the auto dealers’ ploy to thwart pro-consumer innovation and competition. Legislation (HB1124) that was intended to simply update statutes governing the definition, licensing and use of off-road and utility vehicles got co-opted at the last minute in the state Senate. Language was inserted to redefine the term “franchisor” to include any automobile manufacturer, regardless whether they have any franchise agreements–in direct contradiction to the definition used throughout the rest of the surrounding statues. The bill defines a “franchisor” as:

“any manufacturer of new motor vehicles which establishes any business location or facility within the state of Missouri, when such facilities are used by the manufacturer to inform, entice, or otherwise market to potential customers, or where customer orders for the manufacturer’s new motor vehicles are placed, received, or processed, whether or not any sales of such vehicles are finally consummated, and whether or not any such vehicles are actually delivered to the retail customer, at such business location or facility.”

In other words, it defines a franchisor as a company that chooses to open it’s own facility and not franchise. The bill then goes on to define any facility or business location meeting the above criteria as a “new motor vehicle dealership,” even though no sales or even distribution may actually take place there. Since “franchisors” are already forbidden from owning a “new motor vehicle dealership” in Missouri (a dubious restriction in itself), these perverted definitions effectively ban a company like Tesla from selling directly to consumers.

The bill still needs to go back to the Missouri House of Representatives, where it started out as addressing “laws regarding ‘all-terrain vehicles,’ ‘recreational off-highway vehicles,’ and ‘utility vehicles’.”

This is classic rent-seeking regulation at its finest, using contrived and contorted legislation–not to mention last-minute, underhanded legislative tactics–to prevent competition and innovation that, as General Motors itself pointed out, is based on a more economically efficient model of distribution that benefits consumers. Hopefully the State House…or the Governor…won’t be asleep at the wheel as this legislation speeds through the final days of the session.

An occasional reader brought to our attention a bill that is fast making its way through the U.S. House Committee on Financial Services. The Small Company Disclosure Simplification Act (H.R. 4167) would exempt emerging growth companies and companies with annual gross revenue less than $250 million from using the eXtensible Business Reporting Language (XBRL) structure data format currently required for SEC filings. This would effect roughly 60% of publicly listed companies in the U.S.

XBRL makes it possible to easily extract financial data from electronic SEC filings using automated computer programs. Opponents of the bill (most of whom seem to make their living using XBRL to sell information to investors or assisting filing companies comply with the XBRL requirement) argue the bill will create a caste system of filers, harm the small companies the bill is intended to help, and harm investors (for example, see here and here). On pretty much every count, the critics are wrong. Here’s a point-by-point explanation of why:

1) Small firms will be hurt because they will have reduced access to capital markets because their data will be less accessible. — FALSE
The bill doesn’t prohibit small firms from using XBRL, it merely gives them the option to use it or not. If in fact small companies believe they are (or would be) disadvantaged in the market, they can continue filing just as they have been for at least the last two years. For critics to turn around and argue that small companies may choose to not use XBRL simply points out the fallacy of their claim that companies would be disadvantaged. The bill would basically give business owners and management the freedom to decide whether it is in fact in the company’s best interest to use the XBRL format. Therefore, there’s no reason to believe small firms will be hurt as claimed.

Moreover, the information disclosed by firms is no different under the bill–only the format in which it exists. There is no less information available to investors, it just makes it little less convenient to extract–particularly for the information service companies whose computer systems rely on XBRL to gather they data they sell to investors. More on this momentarily.

2) The costs of the current requirement are not as large as the bill’s sponsors claims.–IRRELEVANT AT BEST
According to XBRL US, an XBRL industry trade group, the cost of compliance ranges from $2,000 for small firms up to $25,000–per filing (or $8K to $100K per year). XBRL US goes on to claim those costs are coming down. Regardless whether the actual costs are the “tens of thousands of dollars a year” that bill sponsor Rep. Robert Hurt (VA-5) claims, the point is there are costs that are not clearly justified by any benefits of the disclosure format.

Moreover, if costs are coming down as claimed, then small businesses will be more likely to voluntarily use XBRL. In fact, the ability of small companies to choose NOT to file using XBRL will put competitive pressure on filing compliance companies to reduce costs even further in order to attract business, rather than enjoying a captive market of companies that have no choice.

3) Investors will be harmed because they will lose access to small company data.–FALSE
As noted above,investors will have no less information under the bill–they simply won’t be able to use automated programs to extract the information from the filings. Moreover, even if there was less information available, information asymmetry has long been a part of financial markets and markets are quite capable of dealing with such information asymmetry effectively in how prices are determined by investors and market-makers.  Paul Healy and Krishna Palepu (2001) provide an overview of the literature that shows markets are not only capable, but have an established history, of dealing with differences in information disclosure among firms. If any investors stand to lose, it would be current investors in small companies whose stocks could conceivably decrease in value if the companies choose not to use XBRL. Could. Conceivably. But with no evidence to suggest they would, much less that the effects would be large. To the extent large block holders and institutional investors perceive a potential negative effect, those investors also have the ability to influence management’s decision on whether to take advantage of the proposed exemption or to keep filing with the XBRL format.

The other potential investor harm critics point to with alarm is the prospect that small companies would be more likely and better able to engage in fraudulent reporting because regulators will not be able to as easily monitor the reports. Just one problem: the bill specifically requires the SEC to assess “the benefits to the Commission in terms of improved ability to monitor securities markets” of having the XBRL requirement. That will require the SEC to actively engage in monitoring both XBRL and non-XBRL filings in order to make that determination. So the threat of rampant fraud seems a tad bit overblown…certainly not what one critic described as “a massive regulatory loophole that a fraudulent company could drive an Enron-sized truck through.”

In the end, the bill before Congress would do nothing to change the kind of information that is made available to investors. It would create a more competitive market for companies who do choose to file using the XBRL structured data format, likely reducing the costs of that information format not only for small companies, but also for the larger companies that would still be required to use XBRL. By allowing smaller companies the freedom to choose what technical format to use in disclosing their data, the cost of compliance for all companies can be reduced. And that’s good for investors, capital formation, and the global competitiveness of US-based stock exchanges.

The Securities and Exchange Commission (SEC) recently scored a significant win against a Maryland banker accused of naked short-selling. What may be good news for the SEC is bad news for the market, as the SEC will now be more likely to persecute other alleged offenders of naked short-selling restrictions.

“Naked” short selling is when a trader sells stocks the trader doesn’t actually own (and doesn’t borrow in a prescribed period of time) in the hopes of buying the stocks later (before they must be delivered) at a lower price. The trader is basically betting that the stock price will decline. If it doesn’t, the trader must purchase the stock at a higher price–or breach their original sale contract.Some critics argue that such short-selling leads to market distortions and potential market manipulation, and some even pointed to short-selling as a boogey-man in the 2008 financial crisis, hence the restrictions on short-selling giving rise to the SEC’s enforcement proceedings.

Just one problem, there’s a lot of evidence that shows restrictions on short-selling make markets less efficient, not more.

This isn’t exactly news. Thom argued against short-selling restrictions seven years ago (here) and our late colleague, Larry Ribstein, followed up a couple years ago (here).  The empirical evidence just continues to pile in. Beber and Pagano, in the Journal of Finance earlier this year examine not just US restrictions on short-selling, but global restrictions. Their abstract reads:

Most regulators around the world reacted to the 2007–09 crisis by imposing bans on short selling. These were imposed and lifted at different dates in different countries, often targeted different sets of stocks, and featured varying degrees of stringency. We exploit this variation in short-sales regimes to identify their effects on liquidity, price discovery, and stock prices. Using panel and matching techniques, we find that bans (i) were detrimental for liquidity, especially for stocks with small capitalization and no listed options; (ii) slowed price discovery, especially in bear markets, and (iii) failed to support prices, except possibly for U.S. financial stocks.

So while the SEC may celebrate their prosecution victory, investors may have reason to be less enthusiastic.

Who’s Flying The Plane?

Michael Sykuta —  12 November 2012

It’s an appropriate question, both figuratively and literally. Today’s news headlines are now warning of a looming pilot shortage. A combination of new qualification standards for new pilots and a large percentage of pilots reaching the mandatory retirement age of 65 is creating the prospect of having too few pilots for the US airline industry.

But it still begs the question of “Why?” According to the WSJ article linked above, the new regulations require newly hired pilots to have at least 1,500 hours of prior flight experience. What’s striking about that number is that it is six times the current requirement, significantly increasing the cost (and time) of training to be a pilot.

Why such a huge increase in training requirements? I don’t fly as often as some of my colleagues, but do fly often enough to be concerned that the person in the front of the plane knows what they’re doing. I appreciate the public safety concerns that must have been at the forefront of the regulatory debate. But the facts don’t support an argument that public safety is endangered by the current level of experience pilots are required to attain. Quite the contrary, the past decade has been among the safest ever for airline passengers. In fact, the WSJ reports that:

Congress’s 2010 vote to require 1,500 hours of experience in August 2013 came in the wake of several regional-airline accidents, although none had been due to pilots having fewer than 1,500 hours.

Indeed, to the extent human error has been involved in airline accidents and near misses over the past decade, federally employed air traffic controllers, not privately employed pilots, have been more to blame.

The coincidence of such a staggering increase in training requirements for new pilots and the impending mandatory retirement of a large percentage of current pilots suggests that perhaps other forces were at work behind the scenes when Congress passed the rules in 2010. Legislative proposals are often written by special interests just waiting in the wings (no pun intended) for an opportune moment. Given the downsizing and cost-reduction focus of the US airline industry over the past many years, no group has been more disadvantaged and no group stands more to gain from the new rules than current pilots and the pilots unions.

And so the question, as we face this looming shortage of newly qualified pilots: Who’s flying the plane?

 

As an economist, it’s inevitable that social friends ask my thoughts about current economic issues (at least it’s better than being asked for free legal advice). This weekend a friend commented about the “recovery that isn’t”, reflecting the public sense that the economy doesn’t seem to be doing as well as government reports (particularly unemployment reports) and some politicians make it out to be.

This morning I ran across a weekend article in the WSJ Online that reports on the broader unemployment rate by State in the U.S. In the article, Ben Casselman discusses the difference between the official unemployment rate, formally known as U3 (those who are not working but actively seeking work), and the broadest Labor Department measure, affectionately called U6, which includes people who want to work but are not actively looking and those who want full-time work but are working part-time jobs to make ends meet. Casselman shows how the difference in those measures sometimes reveals significant differences. Take Idaho, for instance, whose unemployment rate is below the national average, but whose U6 measure is above the national average, suggesting a disproportionately large number of people who want full-time work but are stuck with only part-time job opportunities or have given up looking.

This got me wondering just how the difference between U3 and U6 are behaving on a national level, so I went to the Dept of Labor’s website and downloaded both series going back to 1994, when U6 was first introduced.

US Unemployment and Underemployement, 1994-2012This figure shows U3 (seasonally adjusted, in blue) and the difference between U6 and U3 (i.e., underemployment, in red) for the past 18 years. As one would expect, the two are positively correlated. But a couple things stand out. First, while positively correlated, the degree of correlation before and after mid-2001 is very different. For the first eight years, the two track very closely; not so closely afterward.

Second, while unemployment has dropped 2% since hitting its peak of 10% in October 2009, the underemployment rate has barely moved, dropping from 7.2% in October 2009 to only 6.9% in September 2012. So, regardless of whether you buy Jack Welch’s conspiracy theory about the unemployment (U3) numbers being manipulated, it’s clear that there is a persistently large portion of the labor force–double what it had been in 2008–that is wanting full-time work and unable (or discouraged) to find it.

Which pretty well sums up, I believe, the disconnect between the numbers and the reality of the economy. Pointing to the official unemployment numbers masks the truth about the state of the labor market in the US and belies the economic malaise that persists.