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The Effect of Latent Hazards on Firm Exit in Manufacturing Industries 37
The Effect of Latent Hazards on Firm Exit in Manufacturing Industries A. TODD MEROLLA Atlanta, Georgia E-mail: [email protected]
This paper provides a theoretical and empirical examination of the impact of latent hazards on manufacturing firms. I discuss the effects of corporate structure and changes in legal regime on firm exit and derive several testable propositions. The empirical analysis tests whether a firm’s expected liability from latent hazards affects the length of time the firm remains in business. I find that firms in more hazardous industries have shorter life spans. This research is the first extensive empirical study on the exit decisions of firms in hazardous industries. © 1998 by Elsevier Science Inc. I. Introduction Firms’ reactions to large-scale, long-term hazards and the effects of liability rules pertaining to those hazards recently generated much discussion in the economics and environmental literature. Although it is presently well accepted that larger firms divested hazardous tasks to smaller firms to avoid the risks of future liability,1 this paper adds to the debate on the subject by conducting the first empirical study of the effect of latent hazards on the likelihood that a firm exits the market. Section II extends the current research on latent hazards, which began with a study by Ringleb and Wiggins (1990) on large firm reaction that finds a significant increase in the number of ‘‘small’’ firms in hazardous sectors in the 1970s.2 I describe the managerial and financial structure that may lead a firm to behave strategically to avoid future liability payments. Such a firm may simply go out of business instead of paying the full amount of damages. I also discuss various issues that affect a firm’s expected liability. I then present testable implications derived from the research. Section III reports on empirical tests of these implications. I focus on how relative hazardousness across industries affects the amount of time a firm remains in business, as well as how corporate structure affects firm life. The results show that the increased risk involved in I thank all the members of my dissertation committee who assisted me on this paper: Paul H. Rubin (chair), Joel Schrag, and Hashem Dezhbakhsh. 1 Ringleb and Wiggins (1990). 2 Ringleb and Wiggins (1990).
International Review of Law and Economics 18:13–24, 1998 © 1998 by Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010
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Latent hazards and firm exit in manufacturing
hazardous industries attributable to legal changes in the late 1960s and early 1970s exert a negative effect on firm life, particularly for firms in the more hazardous industries. As just noted, earlier research shows that small, private, independent firms dominate hazardous industries. I conclude that this phenomenon has arisen to protect large firms from the consequences of future mass tort episodes. Because they have fewer assets to lose than large firms, small firms more cheaply can bear the risks associated with the manufacture and use of hazardous substances. II. Present State of the Latent Hazard Problem The foundation of much of the latent hazards research comes from Ringleb and Wiggins (1990), in which they test the hypothesis that large firms transferred hazardous activities to smaller firms by examining the period when the courts began to apply strict liability in tort to manufacturers of asbestos and asbestos-related products, from 1967 to 1980.3 They find that small-firm4 entry into hazardous sectors, measured by worker exposure to carcinogens, greatly increased during the 1970s, and they discuss a statistically significant causal link between this phenomenon and the legal changes that held firms liable under unanticipated circumstances.5 The authors conclude that the liability system in a latent hazard setting results in an equilibrium where small corporations handle hazardous tasks. If these firms miscalculate their future liability or if the liability rule concerning carcinogens changes from negligence to strict liability, they would suffer a smaller loss than would a large firm, because by definition they have fewer assets to lose. Consequently, in a mass-tort setting a market with a small firm equilibrium will result in even more injured parties being left uncompensated. Ringleb and Wiggins (1990) further suggest that small firms will be inexperienced with hazards. These firms will compromise safety because liability does not lead to substantial incentives for safety, considering the lag between exposure and the manifestation of injury.6 However, the way a firm may react in a latent hazard setting depends on several variables, including financial and managerial structure, asset level, and the legal regime. Corporate Structure For a public firm, even if it is able to consider bankruptcy as a viable option to remedy mass tort liability, many obstacles remain to executing that option. After a mass tort has occurred, a firm first draws upon its insurance. After exhausting this resource, and after it becomes apparent that future claims are likely to exceed the firm’s assets, the shareholders, in effect, are keeping the company open for the benefit of the contingent future tort claimants. Eventually, the shareholders’ investments may be completely dissipated. To act in the best interest of its owners, the firm would consider selling its operations, paying off current creditors, and then turning whatever is left over to the shareholders.7 Internal corporate structures, market forces, and psychological factors, however, combine to reduce the chance of a possible strategic liquidation to avoid liability. 3
See, Borel v. Fibreboard Paper Products Corp., 493 F.2d 1076, at 1083 (5th Cir. 1973), cert. denied, 419 U.S. 869 (1974). A ‘‘small’’ firm is defined as one that has assets less than $250,000 in 1980 dollars (5$100,000 in 1967 dollars). 5 Ringleb and Wiggins (1990), p. 593. 6 Wiggins and Ringleb (1992), p. 211. Although this conjecture does have support in the literature, this phenomenon has admittedly not yet been observed or tested. See Schwartz (1985), p. 718, n. 42. 7 Roe (1986). 4
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At the point when expected future claims exceed the firm’s assets, the firm has three options.8 Strategic liquidation is the first, and least desirable, option for future claimants. Because thousands of people were exposed to the hazard but have not yet manifested any injury, the hazard’s latency aspect makes it difficult to determine what compensation the injured should receive (if any) and who receives it at the time of liquidation. A second option is to keep the firm in operation outside of bankruptcy, which results in a long rundown of the firm. This option most likely wipes out the shareholder’s investment. Third, the firm may opt for a mass tort bankruptcy reorganization in which the tort claimants become the major owners of the firm and the firm is finished with liability payments beyond the large stock turnover. A reorganization presents the same problems to future claimants as does the strategic liquidation option, because neither the firm nor the courts may take their interests into consideration. Of the three options just outlined, the owners of the firm (shareholders) clearly prefer a quick strategic liquidation when the firm’s liability exceeds its value. At this point the best thing for the firm is to declare bankruptcy, pay off as many creditors with whatever assets remain, and avoid any further liability payments not yet accrued. The separation of managers and shareholders in the corporate structure, however, allows managers to increase their own wealth at the expense of shareholders. Although liquidation would maximize shareholder wealth, managers may try to keep the company as a going concern to retain their jobs and salaries. In determining whether or not to liquidate, managers face two competing forces. Although liquidation maximizes shareholder wealth and enhances the manager’s reputation for profit maximization, a bankruptcy hardly benefits the manager’s reputation for running a firm profitably. In liquidating, managers not only lose their jobs, they also lose their protection from personal liability, their sources of indemnity, and their control over the main source of information concerning managerial involvement in the tort disaster.9 Firm Strategy The preceding discussion suggests that firms may not immediately opt for strategic liquidation whenever expected claims exceed firm value. To the contrary, managers will likely try to preserve the firm, as well as their jobs, regardless of shareholder interests. The early reorganization option, moreover, ironically seems to align managerial interests with those of tort claimants, which some tort observers surely would applaud. In sum, for the publicly held firm, a strategic liquidation seems difficult at this late stage (when tort claims already exceed firm value). For a privately owned firm, by contrast, the restraints just reviewed are no longer present. In this scenario, owner and manager interests are more closely aligned (perfectly aligned, if the firm is owner managed), which leads to a much quicker decision and execution of a liquidation or shut-down option if expected liabilities exceed assets. Thus, where a firm is privately owned or owner managed, it is more possible to enter a hazardous market with the expectation of exiting early to avoid damage payments attributable to suboptimal actions regarding safety.10
8
This discussion relies heavily on Roe (1986). Although there do exist corporate structures that can align manager and shareholder interests, they are especially weak in the mass tort context. For an in-depth discussion of why they are weak, see Roe (1984). 10 Rational investors, however, most likely require such a corporate structure in hazardous markets to maximize their rate of return. 9
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Latent hazards and firm exit in manufacturing
A firm’s incentive to take due care also may decline if it can shield its assets. Spin-offs of this kind do not have proper incentives to maintain an optimal safety schedule; they exist to give the parent firm a short-run payoff and do not necessarily operate assuming an infinite horizon. One drawback to such a strategy is the possibility of piercing the corporate veil if the subsidiary is undercapitalized.11 Another drawback is if a principal– agent relationship may be proven to exist; then the parent remains liable for any harm resulting from the subsidiary’s actions. Consequently, the parent firm will prefer either completely to fully spin-off the risky subsidiary to its shareholders,12 or to purchase the product or service by independent contract. But regardless of the corporate framework, the ultimate decision to exit the market in the latent hazard setting still originates from the expected liability the firm faces at the time of production. If great uncertainty exists about the probability of an accident, the expected liability for undertaking hazardous activities may not be at all accurate. Because the level of damages may be quite large in the latent hazard setting, the firm soon could face a bankruptcy or exit decision regardless of its overall assets. Thus, ceteris paribus, the more uncertain the expected liability is, the lower the amount of assets a firm would choose to hold, because it could lose everything in the event of a disaster. Moreover, if legal issues such as the evidentiary and standing requirements are constantly changing, estimating expected liability is further complicated. For example, changing the duty of care from a negligence standard to strict liability greatly contributed to the disarray in the asbestos cases. So because of the great uncertainty surrounding expected liability, large firms will not internalize hazardous production tasks because an unexpected mass tort setting will cost them large sums of money, whereas a small company can more cheaply use a bankruptcy option. Consequently, a small firm market may act as a kind of market-wide strategy for large firms that require the good or service associated with the latent hazard.13 III. Empirical Analysis Testable Implications Ringleb and Wiggins (1990) offer the conjecture that firms in hazardous industries may choose suboptimal safety levels of care and then exit from the market, leaving many people injured and uncompensated. I show, however, that such firms may have the incentives to remain in the market. No one to date has tested whether small firms are more likely, strategically, to cease operations in avoidance of liability payments, probably because it is difficult to observe strategic actions or to test for them. In this paper I identify several testable implications regarding firm decisions in hazardous industries: PROPOSITION 1: Increases in expected liability arising from latent hazards accelerate a firm’s decision to exit.
11 However, in the case of the latent hazard setting it is unlikely that the undercapitalization argument will successfully pierce the corporate veil, because by definition the latent hazard setting involves highly speculative liabilities. 12 This is done by issuing shares in the subsidiary to the shareholders of the parent corporation pro rata. Roe (1986), p. 49, n. 135. 13 Although I focus my discussion on firm size and structure, there still remains work to be done in the area of firm incentives to take care. Although many offer the conjecture that small firms will not exercise optimal levels of care, due to either lack of experience in dealing with hazards or a lack of incentive to develop knowledge over time, no formal development has yet been offered on this issue in the literature.
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PROPOSITION 2: Private firms are more likely than public firms to strategically exit because owner and manager interests are more closely aligned. PROPOSITION 3: Subsidiaries are less likely than independent firms to exercise a strategic exit because parents are responsible for their liabilities. Sampling and Data To test the preceding propositions I sample from manufacturing data, because workers are exposed to carcinogens more frequently in manufacturing compared to other industries.14 I first collect a random sample of 427 firms from the Product & Services Section of the 1977 Thomas Register. I take my sample of firms from 1977, because by then the various legal changes of interest in latent hazard industries had been in place and the ‘‘small’’ firms probably had entered the latent hazard markets.15 I then identify each firm’s industry, according to Standard Industrial Classification (SIC) by referencing Predicasts’ 1977 F & S Index of Corporations & Industries.16 I then used various sources to find out how long a firm has (had) been in existence, whether or not it is (was) publicly held, and whether or not it is (was) a subsidiary or an independent company.17 After completing this procedure, I discovered that more than 74% of the 427 firms in my sample were still in existence as of 1994 (only 112 firms had exited by 1994). Because the aim of this paper is to focus on the exiting decisions of manufacturing firms, such large right censoring of the data presented a problem. To generate a sample of completed spells with about 200 observations, I drew an additional 412 firms from the Thomas Register of Manufacturers to identify an additional 88 firms. Although the main discussion of this section relates to this sample of completed spells, I also conduct some tests on the original sample of 427 firms from the first draw, which hereinafter I refer to as the expanded sample.18 The next step is to find a measure of ‘‘dangerousness’’ of each industry and to use it as a proxy for expected liability from latent hazards that an average firm faces in that industry. I use a variation of the Hickey-Kearney (1977) index, which measures the frequency in each industry of worker exposure to carcinogens and suspected carcinogens as a proxy for expected liability costs. I construct this variation for each industry by
14 I collect data from the Thomas Register of American Manufacturers, which lists all manufacturers in existence for a given year, Predicasts’ 1977 F & S Index of Corporations & Industries, Ward’s Business Directory, Standard & Poor’s Register of Corporations, Directors and Executives; Directory of Corporate Affiliations; D&B - Dun’s Market Identifiers, and Hickey and Kearney (1977). 15 See Ringleb and Wiggins (1990). 16 Predicasts publishes an extensive list of the Standard Industrial Classification (SIC) to which certain products belong. Using the product listing under which each firm is collected, I ascertain the firm’s SIC code by cross-listing that product to the relevant Predicasts listing. 17 Ward’s Business Directory identifies firms’ dates of incorporation and whether they were publicly or privately held. The Thomas Register lists whether or not a firm is a subsidiary of a larger firm. Other sources used include Standard & Poor’s Register of Corporations, Directors and Executives, Directory of Corporate Affiliations, and D&B - Dun’s Market Identifiers, an on-line data base in Dialog. For some firms I could not find the date of entry from a print source, so I use instead the first year each firm is listed in the Thomas Register. I take a firm’s date of entry as its date of incorporation, which I found for those firms listed in Ward’s Business Directory or Standard & Poor’s Register of Corporations; if the firm was not listed in one of these sources, the date of entry is the first year the Thomas Register which dates back to 1905, lists the company. To ascertain the date of exit, I use the last year the firm was listed in the Thomas Register, the cut-off date was the 1994 issue. 18 The expanded sample also includes those firms that have not yet completed a spell; that is, have not exited from their industries.
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Latent hazards and firm exit in manufacturing
TABLE 1. Summary of data sample of completed spells
I. Low exposure II. Medium exposure III. High exposure IV. Independent firms V. Subsidiaries
VI. Firm entry before or during 1965 VII. Firm entry after 1965
Number of firms
Subsidiary/ independent
Mean duration
Standard deviation
50 60 90 164 36
9/41 10/50 17/73
21.80 23.28 19.80 20.68 24.39
14.18 16.25 14.39 14.93 14.71
Number of firms
Subsidiary/ independent
Mean exposure
Standard deviation
79
16/63
6231
5080
121
20/101
8034
5134
multiplying the number of workers exposed over a 3-year period by the carcinogenic potential of each carcinogen and then dividing by the number of sampled firms from that industry.19 The numerator of this ratio is the carcinogenic potential measure reported in the Hickey-Kearney (1977) study. Ringleb and Wiggins use a form of this index in their 1990 paper. The belief is that the known worker exposure to carcinogens in the mid 1970s will measure forecasted potential liability in the late 1980s and 1990s. Hence, as the exposure to carcinogens increases, so does the expected future liability. Hickey and Kearney constructed their study at the two-digit SIC level, and therefore I conduct the present study at that level.20 For the present study I divide the 19 different SICs into groups of high, medium, and low exposure levels.21 Descriptive Statistics Table 1 presents the characteristics of the sample of completed spells. The hypothesis is that firms in high-exposure industries (who anticipate higher expected liability costs) will be more likely to operate unsafely and then avoid damage payments through an 19 According to John Sestito, Chief of the Surveillance Branch of the National Institute for Occupational Safety and Health (NIOSH), and David Peterson, Environmental Health Specialist at NIOSH (1974), the Hickey-Kearney (1977) study is based on a random sample of 5,000 urban workplaces chosen by the Bureau of Labor Statistics (BLS). To construct an average firm index, which is relevant for the present study, I divide the industry-wide frequencies by the number of firms that NIOSH studied. 20 Ringleb and Wiggins concluded this measure of worker exposure to carcinogens to be the best among the various other methods. See Ringleb and Wiggins (1990), p. 584. Lott and Manning (1995) also recently used the HickeyKearney index. Notice that occupational and production processes change over time, and the Hickey-Kearney index is not particularly useful as a measure of hazardousness for later years. The Hickey-Kearney index remains valid for this study, however, because I take a snapshot of firms in 1977 and look at their subsequent actions. 21 I define low exposure as mean firm exposures times carcinogenic potential less than 3500; medium exposure is greater than 3500 but less than 5500; and high exposure is mean firm exposures greater than 5500. This division is proportional to the ratio of overall firms by SIC code throughout manufacturing sectors. The Thomas Register does not list those firms in SIC numbers 20 (Food and Kindered Products) and 27 (Printing and Publishing); as such, those industries were excluded from the data set. Also notice that although this stratification is somewhat arbitrary, it allows comparison of the extreme groups.
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early exit. They will either exit their respective industries through dissolution or file bankruptcy upon the manifestation of lawsuits. Only one of these firms is public, so I can do no analysis based on a distinction between public and private firms. Instead, the focus is on the duration times across exposure levels and corporate structure. At first glance we see that the mean durations across firms is lower in the high-exposure group. Subsidiaries, moreover, have a greater mean than do the independent firms. Finally, the mean exposure level for exited firms is much higher for those that entered after 1965, when the previously discussed legal changes began. To test the difference in the central tendencies of the duration and exposure for various subsamples of completed spells, I use Wilcoxon’s nonparametric, distributionfree rank sum test for the two-sample location problem.22 I compute W* using duration data (in years) to compare firms in: (1) high- versus combined low- and mediumexposure groups; (2) subsidiaries versus independent firms; and (3) public versus private firms in the expanded sample. The W* for case (1) is 1.751, suggesting that firms in the high-exposure level have significantly shorter durations (at the 10% level) than do those in the low and medium groups. For case (2) W* is 1.44 and is statistically insignificant. For case (3) W* is 5.52, suggesting that public firms have significantly longer durations than do private firms. I also compute W* using exposure level data to compare: (4) firms that enter before and after 1965. For case (4), W* is 1.477, suggesting that firms that enter after 1965 are appreciably more concentrated in the highexposure industries; however, the difference is not statistically significant.23 Estimation I use least squares to regress the duration of each individual firm in the sample of completed spells on the exposure level for its industry controlling for other independent variables. The specification for the sample of completed spells takes the form Di 5 g(H-Ki, SUBi, INDi, ei),24 where Di is the number of years an individual firm has been in existence, H-Ki is the Hickey-Kearney index for the corresponding SIC, SUBi is a binary dummy variable taking the value of 1 for subsidiaries and 0 otherwise, INDi is a proxy for each firm’s industry growth over the time period the firm exists, and ei is a random error term assumed to have 0 mean and finite variance.25 I hypothesize (Proposition 1) that the hazardousness of an industry affects duration such that the higher the expected liability, the shorter a firm’s existence, because of the theoretically possible strategic activities discussed earlier. Therefore, I expect the sign of
22 For details of this test and its advantages over the popular t-test, see Hollander et al. (1973), pp. 67–75, and Randles and Wolfe (1979), ch. 4. 23 This result supports Ringleb and Wiggins’ (1990) conclusions. 24 One obvious variable missing from the specification is a proxy for firm size. Although such a variable is highly relevant to the present discussion, it is virtually impossible to retrieve. All but one firm are privately held, such that no public disclosure of any financial data exists. Moreover, recall that this specification includes firms with completed spells; as such, they are no longer in existence and can no longer be contacted. Although this omission does not affect any results relating to the overall exit behavior attributed to expected liability, it may affect the subsidiary and public dummy variables and their coefficient interpretation insofar as they may be highly correlated with the size of the firm. Accordingly, I caution the reader to interpret the results subject to this unavoidable limitation to the specification. 25 Di and H-Ki variables are in log form, and, depending on the growth measure, INDi is either in log form or in percentages.
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Latent hazards and firm exit in manufacturing
H-Ki to be negative. With regard to the subsidiary dummy variable, I hypothesize (Proposition 3) that the coefficient will be positive, so that a firm with this characteristic will have a longer duration than will those without it.26 Finally, it is necessary to control for market conditions in each industry. If an industry is growing, an individual firm’s duration should increase because of the expanding market. I use three different measures as a proxy for industry growth: growth in the number of firms, growth in total assets, and average real net income. I collect these data at the industry level as reported in the Statistics of Income, Corporate Tax Returns. In constructing the different industry growth rates (number of firms and assets) relevant for each firm in a specific industry, I use the entry and exit dates for the firm and then compute the average annual industry growth rate over that time period.27 For real net income I use the average per-firm net income for the given industry over the relevant time period. I use the gross domestic product deflator to change the nominal income to real income before averaging across each time horizon.28 Table 2 reports a summary of the results containing the fully specified model with industry growth proxies of number of firms, total assets, and average real net income, respectively. I obtain the results by applying the least squares method with heteroskedasticity-consistent covariance estimates to the sample data.29 The estimated coefficient for the Hickey-Kearney index is negative across all specifications. These estimates are significant at the 1% level with the net income industry performance proxy [equation (2)], and at the 5% level for the other two industry performance proxies. These results are similar to the results based on descriptive statistics in that they support Proposition 1—the uncertainty of expected liability may accelerate a firm’s decision to exit because of the potential problems a liability system has in the latent hazard setting.30 The subsidiary dummy variable has consistently positive coefficient estimates, and it is significant at the 1% level with the ‘‘assets’’ industry growth variable and at the 5% level for the other two variables. This result supports Proposition 3, which states that subsidiaries will have longer durations than will independent firms. The results relating to the industry growth variables are consistently positive, as one would expect, and highly significant. I also apply least squares analysis with heteroskedasticity-consistent covariance estimates to the expanded sample. Table 2 reports the results in equation (4). I include a dummy variable for public versus private firms and delete the industry growth vari26 I planned originally to include a dummy variable for public firms to test Proposition 2. Because only one such firm is in the sample of completed spells, I do not include this variable here. I do include it, however, for regressions involving the expanded sample. 27 The average annual growth rate proxy takes different values among firms in the same industry because of different dates of entry and exit, even though the life spans may be the same. The earliest entry date used for this purpose is 1954, the earliest publication of Statistics of Income, Corporate Tax Returns. This procedure should be satisfactory for the present study, because any growth before this date precedes the recent legal changes and the earliest exit date by at least 10 years, and therefore any growth before 1954 will have a minimal effect on the firms I examine. Moreover, if a firm exits in either 1992 or 1993, I use the data from the 1991 Statistics of Income because that is the latest publication; I assume the growth rate to be constant for the remaining 2 years. 28 I add also a binary variable to capture the macroeconomic influences on the timing of the exit (recessionary versus nonrecessionary years). The estimated coefficient of this variable is insignificant in all cases, and its inclusion does not alter the sign or significance of other estimated coefficients. So, I drop the variable from all equations estimated here. 29 I use this method because in all cases heteroskedasticity of unknown form is present. See, White (1980) for details of the heteroskedasticity test and estimation procedure. 30 I also ran regressions on the three subgroups. However, due to the small variation in the Hickey-Kearney variable within each subgroup, the results, although consistent, were not robust.
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TABLE 2. Least squares results for sample of completed spells an expanded sample Equations Independent variables Intercept Hickey-Kearney index Subsidiary dummy Industry growth
(1)
(2)
(3)
(4)
3.99 (6.01)** 20.17 (22.11)* 0.32 (2.50)* 3.01 (4.62)**
3.55 (5.44)** 20.26 (22.67)** 0.31 (2.32)* 0.20 (2.76)**
4.34 (6.08)** 20.23 (22.55)* 0.31 (2.69)** 1.23 (2.46)**
3.47 (10.00)** 20.001 (20.07) 0.12 (1.67)
Public dummy R2 Adj z R2 F Sample size
0.12 0.10 8.78 200
0.07 0.05 4.64 200
0.17 0.16 13.48 200
0.64 (6. 30)** 0.06 0.06 9.40 427
Note: The dependent variable is the duration of firms. (1) Sample of Completed Spells with industry growth 5 firms (2) Sample of Completed Spells with industry growth 5 net income (3) Sample of Completed Spells with industry growth 5 assets (4) Expanded Sample t-statistics are in parentheses. * Significant at the 5% level. ** Significant at the 1% level.
able.31 Similar to earlier results, there is a negative relationship between the HickeyKearney index and duration, although it is not statistically significant. The coefficient estimates for the public dummy are positive and significant at the 1% level, much in accordance with Proposition 2. This result supports the hypothesis that public firms remain in business much longer than do private firms. The subsidiary dummy is also positive, implying that subsidiaries may remain in business longer than independent companies.32 Finally, I apply duration analysis to the sample of completed spells. Parameter estimates for the Weibull, Exponential, and Log-logistic distributions are given in Table 3.33 To give external factors a role, I include covariates in a proportional hazard specification. The model takes the form 2ln L0(t) 5 F(H-Ki, SUBi, ei)
31 Due to multicollinearity between industry growth and the public dummy variable, the growth variable is omitted. In this sample of 427 observations, only 28 were public companies, of which 20 were both founded before 1954 and still in existence as of 1994. Consequently, all 20 of these firms would take on the same value for industry growth. Because the focus of this specification concerns the relationship between length of stay and public financial structure, I exclude the industry growth variable. 32 The results based on the expanded sample must be interpreted with caution because the dependent variable is right censored for most observations. 33 For background in duration analysis, see Greene (1993), pp. 715–727.
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Latent hazards and firm exit in manufacturing
TABLE 3. Estimated duration models (estimated standard errors in parentheses) Equations Model Weibull Exponential Log-logistic
l
p
Median duration
0.04990 (0.00396) 0.05084 (0.00482) 0.06191 (0.01045)
1.10043 (0.09041) 1.00000 (0.00000) 1.10043 (0.10188)
14.36 (1.13913) 13.63 (1.29175) 16.15 (2.72797)
where L0(t) is the integrated baseline hazard of each firm, H-Ki is the Hickey-Kearney index for the corresponding SIC, SUBi is a binary dummy variable taking the value of 1 for subsidiaries and 0 otherwise, and ei is a random error term that has a fully specified (but not normal) distribution.34 A summary of the results for each of the distributions can be seen in Table 4. Although the Weibull and exponential estimations show a positive sign on the HickeyKearney index variable, there is a negative result for the Log-logistic distribution. However, the t-statistics are extremely low for all specifications, such that no conclusions may be drawn with regard to the effect of expected liability on the conditional probability of completing a spell. The subsidiary dummy variable always generated a positive sign, suggesting that spell length increases given that a firm is a subsidiary. But, once again, none of the results were statistically significant. In sum, the descriptive statistics and least squares results strongly suggest that firms in the more hazardous industries have shorter life spans, as Proposition 1 suggests, although the duration results are ambiguous. Meanwhile, all testing methodologies support Propositions 2 and 3, to the extent that public firms and subsidiaries have longer durations than do private companies and independent firms. IV. Interpretations and Conclusions Ringleb and Wiggins (1990) offer the conjecture that small firms operating at suboptimal levels of care will dominate manufacturing industries that involve long-term, latent hazards. In the event of a mass tort, this equilibrium could lead firms to own insufficient assets to compensate the injured. Although it is difficult, if not impossible, to observe directly whether firms choose suboptimal care and/or exit to avoid liability payments, the testable hypotheses developed here shed some light on firms’ actions. The empirical results generally support the hypothesis that firms in more hazardous industries exit more quickly. Moreover, the empirical results show that private and independent firms have significantly shorter life spans. It would be overreaching, of course, to infer automatically from these results that firms act strategically to avoid their liabilities arising from latent hazards. Although the empirical results are consistent with a tendency by firms to choose a strategic exit, less than 25% of the firms sampled in 1977 had exited by 1994, and there is no evidence that 34 The industry growth variables were not able to be included in the analysis because the regression was unable to locate a function minimum when they were involved.
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TABLE 4. Duration results for sample of completed spells Equations Covariates Intercept Hickey-Kearney index Subsidiary dummy Log likelihood Sample size
(1) 2.847 (21.98) 0.000002 (0.80) 0.301 (1.23) 2259.877 200
(2) 2.847 (18.33) 0.000002 (0.54) 0.301 (1.02) 2266.179 200
(3) 2.847 (9.516) 20.000003 (20.50) 0.301 (0.60) 2302.005 200
Note: (1) Weibull estimation. (2) Exponential estimation. (3) Log-logistic estimation. t-Statistics are in parentheses.
any of these exited firms did so to avoid tort claims.35 An alternative interpretation would be that these firms suffer from mismanagement unrelated to tort liability—a variable for which the empirical model does not control. After all, Ringleb and Wiggins (1990) show that there is a significant increase in firm entry in hazardous industries after 1965; some proportion of these firms are bound to fail for reasons other than tort liability. Moreover, my empirical results and the findings that small firms dominate hazardous industries support the notion that the high uncertainty about the probability of injury and the change in legal regime altered the shape of hazardous manufacturing industries over the past 20 years. The asbestos firms had severely miscalculated the legal and physical risk of their activities, and consequently they harmed many more people than ever anticipated. Tort reform in the 1970s also held these firms liable under circumstances they never had imagined would be possible. We can interpret the reaction to externalize hazardous activities and forego the economies of vertical integration as a way to avoid the risks associated with dangerous activities. Thus, many large firms should have removed themselves from hazardous markets. Meanwhile, small firms entered the market and handled the tasks that large firms with greater levels of assets wanted to avoid because the small firms did not have nearly as much to lose.36 This is precisely what Ringleb and Wiggins (1990) show. My results also suggest that firm entry into hazardous markets has accelerated since 1965 and that these are predominantly privately held, independent firms. Consequently, if present firms severely miscalculate the probability of disaster, or if 35 I ran an extensive search on these exited firms in Westlaw and Lexis/Nexus for court records or newspaper articles mentioning these firms in any way. Nothing relating to tort claims came up on any of the firms. However, I am not suggesting that firms go out of business only after litigation is initiated; it is likely that they will shut down and exit well before any suits are filed, when assets are not sunk. 36 Some argue that if the firm’s assets are small enough, the tort victims will not bother to sue. But these are manufacturing plants, so some amount of fixed assets must be present that could partially settle an award of damages. There are generally no costs to the plaintiff to sue, moreover, because the attorney most likely will be paid ex ante on a contingency basis; the size of the assets a firm holds also is usually realized ex post to the lawsuit. And, in the present litigious climate, although costs to the attorney do exist, lawyers certainly must be willing to take these kinds of cases.
24
Latent hazards and firm exit in manufacturing
liability rules once again change unexpectedly, these small firms with few assets have relatively less to lose. And because these are generally private and independent firms, a plan to liquidate is relatively easy to achieve. As such, the small firm equilibrium may indeed act as a survival strategy for the industry as a whole, given the unknown risk of future asbestos-like disasters. However, what incentives a firm may have to take socially optimal levels of care in the latent hazard setting ex ante to a disaster is a question left for further research. References Directory of Corporate Affiliations. (1994). New Providence, NJ: National Register Publishing. D & B - Dun’s Market Identifiers. (1994). Bethlehem, PA: Dialog Information Services. F & S Index of Corporations & Industries. (1977). Cleveland, OH: Predicasts. GREENE, WILLIAM H. (1993). Econometric Analysis, 2d ed. New York: Macmillan. HICKEY, J.L.S., AND J.J. KEARNEY. (1977). Engineering Control Research and Development Plan for Carcinogen Materials, Cincinnati: National Institute For Occupation and Health. HOLLANDER, MYLES, AND DOUGLAS A. WOLFE. (1973). Nonparametric Statistical Methods, New York: Wiley. LOTT, JOHN R., AND RICHARD L. MANNING. (1995). ‘‘Have Changing Liability Rules Compensated Workers Twice For Occupational Hazards?: Earnings Premiums and Cancer Risks.’’ Working paper. National Institute For Occupational Safety and Health. (1974). National Occupational Hazard Survey, Washington, D.C.: Government Printing Office. RANDLES, RONALD H., AND DOUGLAS A. WOLFE. (1979). Introduction to the Theory of Nonparametric Statistics, New York: Wiley. RINGLEB, AL H., AND STEVEN N. WIGGINS. (1990). ‘‘Liability and Large-Scale, Long-Term Hazards.’’ Journal of Political Economy 98:574. ROE, MARK J. (1984). ‘‘Bankruptcy and Mass Tort.’’ Columbia Law Review, 84:846. ROE, MARK J. (1986). ‘‘Corporate Strategic Reaction to Mass Tort.’’ Virginia Law Review 72:1. SCHWARTZ, ALAN. (1985). ‘‘Products Liability, Corporate Structure, and Bankruptcy: Toxic Substances and the Remote Risk Relationship.’’ Journal of Legal Studies 14:689. Standard & Poor’s Register of Corporations, Directors, and Executives. (1994). New York: McGraw-Hill. Thomas Register of American Manufacturers. (1905–1995). New York: Thomas Publishing Company. Ward’s Business Directory. (1993–1995). Washington, D.C.: Gale Research, Inc. WHITE, H. (1990). ‘‘A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test For Heteroskedasticity.’’ Econometrica 48:817. WIGGINS, STEVEN N., AND AL H. RINGLEB. (1992). ‘‘Adverse Selection and Long-Term Hazards: The Choice Between Contract and Mandatory Liability Rules.’’ Journal of Legal Studies, 21:189.
This paper provides a theoretical and empirical examination of the impact of latent hazards on manufacturing firms. I discuss the effects of corporate structure and changes in legal regime on firm exit and derive several testable propositions. The empirical analysis tests whether a firm’s expected liability from latent hazards affects the length of time the firm remains in business. I find that firms in more hazardous industries have shorter life spans. This research is the first extensive empirical study on the exit decisions of firms in hazardous industries. © 1998 by Elsevier Science Inc. I. Introduction Firms’ reactions to large-scale, long-term hazards and the effects of liability rules pertaining to those hazards recently generated much discussion in the economics and environmental literature. Although it is presently well accepted that larger firms divested hazardous tasks to smaller firms to avoid the risks of future liability,1 this paper adds to the debate on the subject by conducting the first empirical study of the effect of latent hazards on the likelihood that a firm exits the market. Section II extends the current research on latent hazards, which began with a study by Ringleb and Wiggins (1990) on large firm reaction that finds a significant increase in the number of ‘‘small’’ firms in hazardous sectors in the 1970s.2 I describe the managerial and financial structure that may lead a firm to behave strategically to avoid future liability payments. Such a firm may simply go out of business instead of paying the full amount of damages. I also discuss various issues that affect a firm’s expected liability. I then present testable implications derived from the research. Section III reports on empirical tests of these implications. I focus on how relative hazardousness across industries affects the amount of time a firm remains in business, as well as how corporate structure affects firm life. The results show that the increased risk involved in I thank all the members of my dissertation committee who assisted me on this paper: Paul H. Rubin (chair), Joel Schrag, and Hashem Dezhbakhsh. 1 Ringleb and Wiggins (1990). 2 Ringleb and Wiggins (1990).
International Review of Law and Economics 18:13–24, 1998 © 1998 by Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010
0144-8188/98/$19.00 PII S0144-8188(97)00054-9
14
Latent hazards and firm exit in manufacturing
hazardous industries attributable to legal changes in the late 1960s and early 1970s exert a negative effect on firm life, particularly for firms in the more hazardous industries. As just noted, earlier research shows that small, private, independent firms dominate hazardous industries. I conclude that this phenomenon has arisen to protect large firms from the consequences of future mass tort episodes. Because they have fewer assets to lose than large firms, small firms more cheaply can bear the risks associated with the manufacture and use of hazardous substances. II. Present State of the Latent Hazard Problem The foundation of much of the latent hazards research comes from Ringleb and Wiggins (1990), in which they test the hypothesis that large firms transferred hazardous activities to smaller firms by examining the period when the courts began to apply strict liability in tort to manufacturers of asbestos and asbestos-related products, from 1967 to 1980.3 They find that small-firm4 entry into hazardous sectors, measured by worker exposure to carcinogens, greatly increased during the 1970s, and they discuss a statistically significant causal link between this phenomenon and the legal changes that held firms liable under unanticipated circumstances.5 The authors conclude that the liability system in a latent hazard setting results in an equilibrium where small corporations handle hazardous tasks. If these firms miscalculate their future liability or if the liability rule concerning carcinogens changes from negligence to strict liability, they would suffer a smaller loss than would a large firm, because by definition they have fewer assets to lose. Consequently, in a mass-tort setting a market with a small firm equilibrium will result in even more injured parties being left uncompensated. Ringleb and Wiggins (1990) further suggest that small firms will be inexperienced with hazards. These firms will compromise safety because liability does not lead to substantial incentives for safety, considering the lag between exposure and the manifestation of injury.6 However, the way a firm may react in a latent hazard setting depends on several variables, including financial and managerial structure, asset level, and the legal regime. Corporate Structure For a public firm, even if it is able to consider bankruptcy as a viable option to remedy mass tort liability, many obstacles remain to executing that option. After a mass tort has occurred, a firm first draws upon its insurance. After exhausting this resource, and after it becomes apparent that future claims are likely to exceed the firm’s assets, the shareholders, in effect, are keeping the company open for the benefit of the contingent future tort claimants. Eventually, the shareholders’ investments may be completely dissipated. To act in the best interest of its owners, the firm would consider selling its operations, paying off current creditors, and then turning whatever is left over to the shareholders.7 Internal corporate structures, market forces, and psychological factors, however, combine to reduce the chance of a possible strategic liquidation to avoid liability. 3
See, Borel v. Fibreboard Paper Products Corp., 493 F.2d 1076, at 1083 (5th Cir. 1973), cert. denied, 419 U.S. 869 (1974). A ‘‘small’’ firm is defined as one that has assets less than $250,000 in 1980 dollars (5$100,000 in 1967 dollars). 5 Ringleb and Wiggins (1990), p. 593. 6 Wiggins and Ringleb (1992), p. 211. Although this conjecture does have support in the literature, this phenomenon has admittedly not yet been observed or tested. See Schwartz (1985), p. 718, n. 42. 7 Roe (1986). 4
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At the point when expected future claims exceed the firm’s assets, the firm has three options.8 Strategic liquidation is the first, and least desirable, option for future claimants. Because thousands of people were exposed to the hazard but have not yet manifested any injury, the hazard’s latency aspect makes it difficult to determine what compensation the injured should receive (if any) and who receives it at the time of liquidation. A second option is to keep the firm in operation outside of bankruptcy, which results in a long rundown of the firm. This option most likely wipes out the shareholder’s investment. Third, the firm may opt for a mass tort bankruptcy reorganization in which the tort claimants become the major owners of the firm and the firm is finished with liability payments beyond the large stock turnover. A reorganization presents the same problems to future claimants as does the strategic liquidation option, because neither the firm nor the courts may take their interests into consideration. Of the three options just outlined, the owners of the firm (shareholders) clearly prefer a quick strategic liquidation when the firm’s liability exceeds its value. At this point the best thing for the firm is to declare bankruptcy, pay off as many creditors with whatever assets remain, and avoid any further liability payments not yet accrued. The separation of managers and shareholders in the corporate structure, however, allows managers to increase their own wealth at the expense of shareholders. Although liquidation would maximize shareholder wealth, managers may try to keep the company as a going concern to retain their jobs and salaries. In determining whether or not to liquidate, managers face two competing forces. Although liquidation maximizes shareholder wealth and enhances the manager’s reputation for profit maximization, a bankruptcy hardly benefits the manager’s reputation for running a firm profitably. In liquidating, managers not only lose their jobs, they also lose their protection from personal liability, their sources of indemnity, and their control over the main source of information concerning managerial involvement in the tort disaster.9 Firm Strategy The preceding discussion suggests that firms may not immediately opt for strategic liquidation whenever expected claims exceed firm value. To the contrary, managers will likely try to preserve the firm, as well as their jobs, regardless of shareholder interests. The early reorganization option, moreover, ironically seems to align managerial interests with those of tort claimants, which some tort observers surely would applaud. In sum, for the publicly held firm, a strategic liquidation seems difficult at this late stage (when tort claims already exceed firm value). For a privately owned firm, by contrast, the restraints just reviewed are no longer present. In this scenario, owner and manager interests are more closely aligned (perfectly aligned, if the firm is owner managed), which leads to a much quicker decision and execution of a liquidation or shut-down option if expected liabilities exceed assets. Thus, where a firm is privately owned or owner managed, it is more possible to enter a hazardous market with the expectation of exiting early to avoid damage payments attributable to suboptimal actions regarding safety.10
8
This discussion relies heavily on Roe (1986). Although there do exist corporate structures that can align manager and shareholder interests, they are especially weak in the mass tort context. For an in-depth discussion of why they are weak, see Roe (1984). 10 Rational investors, however, most likely require such a corporate structure in hazardous markets to maximize their rate of return. 9
16
Latent hazards and firm exit in manufacturing
A firm’s incentive to take due care also may decline if it can shield its assets. Spin-offs of this kind do not have proper incentives to maintain an optimal safety schedule; they exist to give the parent firm a short-run payoff and do not necessarily operate assuming an infinite horizon. One drawback to such a strategy is the possibility of piercing the corporate veil if the subsidiary is undercapitalized.11 Another drawback is if a principal– agent relationship may be proven to exist; then the parent remains liable for any harm resulting from the subsidiary’s actions. Consequently, the parent firm will prefer either completely to fully spin-off the risky subsidiary to its shareholders,12 or to purchase the product or service by independent contract. But regardless of the corporate framework, the ultimate decision to exit the market in the latent hazard setting still originates from the expected liability the firm faces at the time of production. If great uncertainty exists about the probability of an accident, the expected liability for undertaking hazardous activities may not be at all accurate. Because the level of damages may be quite large in the latent hazard setting, the firm soon could face a bankruptcy or exit decision regardless of its overall assets. Thus, ceteris paribus, the more uncertain the expected liability is, the lower the amount of assets a firm would choose to hold, because it could lose everything in the event of a disaster. Moreover, if legal issues such as the evidentiary and standing requirements are constantly changing, estimating expected liability is further complicated. For example, changing the duty of care from a negligence standard to strict liability greatly contributed to the disarray in the asbestos cases. So because of the great uncertainty surrounding expected liability, large firms will not internalize hazardous production tasks because an unexpected mass tort setting will cost them large sums of money, whereas a small company can more cheaply use a bankruptcy option. Consequently, a small firm market may act as a kind of market-wide strategy for large firms that require the good or service associated with the latent hazard.13 III. Empirical Analysis Testable Implications Ringleb and Wiggins (1990) offer the conjecture that firms in hazardous industries may choose suboptimal safety levels of care and then exit from the market, leaving many people injured and uncompensated. I show, however, that such firms may have the incentives to remain in the market. No one to date has tested whether small firms are more likely, strategically, to cease operations in avoidance of liability payments, probably because it is difficult to observe strategic actions or to test for them. In this paper I identify several testable implications regarding firm decisions in hazardous industries: PROPOSITION 1: Increases in expected liability arising from latent hazards accelerate a firm’s decision to exit.
11 However, in the case of the latent hazard setting it is unlikely that the undercapitalization argument will successfully pierce the corporate veil, because by definition the latent hazard setting involves highly speculative liabilities. 12 This is done by issuing shares in the subsidiary to the shareholders of the parent corporation pro rata. Roe (1986), p. 49, n. 135. 13 Although I focus my discussion on firm size and structure, there still remains work to be done in the area of firm incentives to take care. Although many offer the conjecture that small firms will not exercise optimal levels of care, due to either lack of experience in dealing with hazards or a lack of incentive to develop knowledge over time, no formal development has yet been offered on this issue in the literature.
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PROPOSITION 2: Private firms are more likely than public firms to strategically exit because owner and manager interests are more closely aligned. PROPOSITION 3: Subsidiaries are less likely than independent firms to exercise a strategic exit because parents are responsible for their liabilities. Sampling and Data To test the preceding propositions I sample from manufacturing data, because workers are exposed to carcinogens more frequently in manufacturing compared to other industries.14 I first collect a random sample of 427 firms from the Product & Services Section of the 1977 Thomas Register. I take my sample of firms from 1977, because by then the various legal changes of interest in latent hazard industries had been in place and the ‘‘small’’ firms probably had entered the latent hazard markets.15 I then identify each firm’s industry, according to Standard Industrial Classification (SIC) by referencing Predicasts’ 1977 F & S Index of Corporations & Industries.16 I then used various sources to find out how long a firm has (had) been in existence, whether or not it is (was) publicly held, and whether or not it is (was) a subsidiary or an independent company.17 After completing this procedure, I discovered that more than 74% of the 427 firms in my sample were still in existence as of 1994 (only 112 firms had exited by 1994). Because the aim of this paper is to focus on the exiting decisions of manufacturing firms, such large right censoring of the data presented a problem. To generate a sample of completed spells with about 200 observations, I drew an additional 412 firms from the Thomas Register of Manufacturers to identify an additional 88 firms. Although the main discussion of this section relates to this sample of completed spells, I also conduct some tests on the original sample of 427 firms from the first draw, which hereinafter I refer to as the expanded sample.18 The next step is to find a measure of ‘‘dangerousness’’ of each industry and to use it as a proxy for expected liability from latent hazards that an average firm faces in that industry. I use a variation of the Hickey-Kearney (1977) index, which measures the frequency in each industry of worker exposure to carcinogens and suspected carcinogens as a proxy for expected liability costs. I construct this variation for each industry by
14 I collect data from the Thomas Register of American Manufacturers, which lists all manufacturers in existence for a given year, Predicasts’ 1977 F & S Index of Corporations & Industries, Ward’s Business Directory, Standard & Poor’s Register of Corporations, Directors and Executives; Directory of Corporate Affiliations; D&B - Dun’s Market Identifiers, and Hickey and Kearney (1977). 15 See Ringleb and Wiggins (1990). 16 Predicasts publishes an extensive list of the Standard Industrial Classification (SIC) to which certain products belong. Using the product listing under which each firm is collected, I ascertain the firm’s SIC code by cross-listing that product to the relevant Predicasts listing. 17 Ward’s Business Directory identifies firms’ dates of incorporation and whether they were publicly or privately held. The Thomas Register lists whether or not a firm is a subsidiary of a larger firm. Other sources used include Standard & Poor’s Register of Corporations, Directors and Executives, Directory of Corporate Affiliations, and D&B - Dun’s Market Identifiers, an on-line data base in Dialog. For some firms I could not find the date of entry from a print source, so I use instead the first year each firm is listed in the Thomas Register. I take a firm’s date of entry as its date of incorporation, which I found for those firms listed in Ward’s Business Directory or Standard & Poor’s Register of Corporations; if the firm was not listed in one of these sources, the date of entry is the first year the Thomas Register which dates back to 1905, lists the company. To ascertain the date of exit, I use the last year the firm was listed in the Thomas Register, the cut-off date was the 1994 issue. 18 The expanded sample also includes those firms that have not yet completed a spell; that is, have not exited from their industries.
18
Latent hazards and firm exit in manufacturing
TABLE 1. Summary of data sample of completed spells
I. Low exposure II. Medium exposure III. High exposure IV. Independent firms V. Subsidiaries
VI. Firm entry before or during 1965 VII. Firm entry after 1965
Number of firms
Subsidiary/ independent
Mean duration
Standard deviation
50 60 90 164 36
9/41 10/50 17/73
21.80 23.28 19.80 20.68 24.39
14.18 16.25 14.39 14.93 14.71
Number of firms
Subsidiary/ independent
Mean exposure
Standard deviation
79
16/63
6231
5080
121
20/101
8034
5134
multiplying the number of workers exposed over a 3-year period by the carcinogenic potential of each carcinogen and then dividing by the number of sampled firms from that industry.19 The numerator of this ratio is the carcinogenic potential measure reported in the Hickey-Kearney (1977) study. Ringleb and Wiggins use a form of this index in their 1990 paper. The belief is that the known worker exposure to carcinogens in the mid 1970s will measure forecasted potential liability in the late 1980s and 1990s. Hence, as the exposure to carcinogens increases, so does the expected future liability. Hickey and Kearney constructed their study at the two-digit SIC level, and therefore I conduct the present study at that level.20 For the present study I divide the 19 different SICs into groups of high, medium, and low exposure levels.21 Descriptive Statistics Table 1 presents the characteristics of the sample of completed spells. The hypothesis is that firms in high-exposure industries (who anticipate higher expected liability costs) will be more likely to operate unsafely and then avoid damage payments through an 19 According to John Sestito, Chief of the Surveillance Branch of the National Institute for Occupational Safety and Health (NIOSH), and David Peterson, Environmental Health Specialist at NIOSH (1974), the Hickey-Kearney (1977) study is based on a random sample of 5,000 urban workplaces chosen by the Bureau of Labor Statistics (BLS). To construct an average firm index, which is relevant for the present study, I divide the industry-wide frequencies by the number of firms that NIOSH studied. 20 Ringleb and Wiggins concluded this measure of worker exposure to carcinogens to be the best among the various other methods. See Ringleb and Wiggins (1990), p. 584. Lott and Manning (1995) also recently used the HickeyKearney index. Notice that occupational and production processes change over time, and the Hickey-Kearney index is not particularly useful as a measure of hazardousness for later years. The Hickey-Kearney index remains valid for this study, however, because I take a snapshot of firms in 1977 and look at their subsequent actions. 21 I define low exposure as mean firm exposures times carcinogenic potential less than 3500; medium exposure is greater than 3500 but less than 5500; and high exposure is mean firm exposures greater than 5500. This division is proportional to the ratio of overall firms by SIC code throughout manufacturing sectors. The Thomas Register does not list those firms in SIC numbers 20 (Food and Kindered Products) and 27 (Printing and Publishing); as such, those industries were excluded from the data set. Also notice that although this stratification is somewhat arbitrary, it allows comparison of the extreme groups.
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early exit. They will either exit their respective industries through dissolution or file bankruptcy upon the manifestation of lawsuits. Only one of these firms is public, so I can do no analysis based on a distinction between public and private firms. Instead, the focus is on the duration times across exposure levels and corporate structure. At first glance we see that the mean durations across firms is lower in the high-exposure group. Subsidiaries, moreover, have a greater mean than do the independent firms. Finally, the mean exposure level for exited firms is much higher for those that entered after 1965, when the previously discussed legal changes began. To test the difference in the central tendencies of the duration and exposure for various subsamples of completed spells, I use Wilcoxon’s nonparametric, distributionfree rank sum test for the two-sample location problem.22 I compute W* using duration data (in years) to compare firms in: (1) high- versus combined low- and mediumexposure groups; (2) subsidiaries versus independent firms; and (3) public versus private firms in the expanded sample. The W* for case (1) is 1.751, suggesting that firms in the high-exposure level have significantly shorter durations (at the 10% level) than do those in the low and medium groups. For case (2) W* is 1.44 and is statistically insignificant. For case (3) W* is 5.52, suggesting that public firms have significantly longer durations than do private firms. I also compute W* using exposure level data to compare: (4) firms that enter before and after 1965. For case (4), W* is 1.477, suggesting that firms that enter after 1965 are appreciably more concentrated in the highexposure industries; however, the difference is not statistically significant.23 Estimation I use least squares to regress the duration of each individual firm in the sample of completed spells on the exposure level for its industry controlling for other independent variables. The specification for the sample of completed spells takes the form Di 5 g(H-Ki, SUBi, INDi, ei),24 where Di is the number of years an individual firm has been in existence, H-Ki is the Hickey-Kearney index for the corresponding SIC, SUBi is a binary dummy variable taking the value of 1 for subsidiaries and 0 otherwise, INDi is a proxy for each firm’s industry growth over the time period the firm exists, and ei is a random error term assumed to have 0 mean and finite variance.25 I hypothesize (Proposition 1) that the hazardousness of an industry affects duration such that the higher the expected liability, the shorter a firm’s existence, because of the theoretically possible strategic activities discussed earlier. Therefore, I expect the sign of
22 For details of this test and its advantages over the popular t-test, see Hollander et al. (1973), pp. 67–75, and Randles and Wolfe (1979), ch. 4. 23 This result supports Ringleb and Wiggins’ (1990) conclusions. 24 One obvious variable missing from the specification is a proxy for firm size. Although such a variable is highly relevant to the present discussion, it is virtually impossible to retrieve. All but one firm are privately held, such that no public disclosure of any financial data exists. Moreover, recall that this specification includes firms with completed spells; as such, they are no longer in existence and can no longer be contacted. Although this omission does not affect any results relating to the overall exit behavior attributed to expected liability, it may affect the subsidiary and public dummy variables and their coefficient interpretation insofar as they may be highly correlated with the size of the firm. Accordingly, I caution the reader to interpret the results subject to this unavoidable limitation to the specification. 25 Di and H-Ki variables are in log form, and, depending on the growth measure, INDi is either in log form or in percentages.
20
Latent hazards and firm exit in manufacturing
H-Ki to be negative. With regard to the subsidiary dummy variable, I hypothesize (Proposition 3) that the coefficient will be positive, so that a firm with this characteristic will have a longer duration than will those without it.26 Finally, it is necessary to control for market conditions in each industry. If an industry is growing, an individual firm’s duration should increase because of the expanding market. I use three different measures as a proxy for industry growth: growth in the number of firms, growth in total assets, and average real net income. I collect these data at the industry level as reported in the Statistics of Income, Corporate Tax Returns. In constructing the different industry growth rates (number of firms and assets) relevant for each firm in a specific industry, I use the entry and exit dates for the firm and then compute the average annual industry growth rate over that time period.27 For real net income I use the average per-firm net income for the given industry over the relevant time period. I use the gross domestic product deflator to change the nominal income to real income before averaging across each time horizon.28 Table 2 reports a summary of the results containing the fully specified model with industry growth proxies of number of firms, total assets, and average real net income, respectively. I obtain the results by applying the least squares method with heteroskedasticity-consistent covariance estimates to the sample data.29 The estimated coefficient for the Hickey-Kearney index is negative across all specifications. These estimates are significant at the 1% level with the net income industry performance proxy [equation (2)], and at the 5% level for the other two industry performance proxies. These results are similar to the results based on descriptive statistics in that they support Proposition 1—the uncertainty of expected liability may accelerate a firm’s decision to exit because of the potential problems a liability system has in the latent hazard setting.30 The subsidiary dummy variable has consistently positive coefficient estimates, and it is significant at the 1% level with the ‘‘assets’’ industry growth variable and at the 5% level for the other two variables. This result supports Proposition 3, which states that subsidiaries will have longer durations than will independent firms. The results relating to the industry growth variables are consistently positive, as one would expect, and highly significant. I also apply least squares analysis with heteroskedasticity-consistent covariance estimates to the expanded sample. Table 2 reports the results in equation (4). I include a dummy variable for public versus private firms and delete the industry growth vari26 I planned originally to include a dummy variable for public firms to test Proposition 2. Because only one such firm is in the sample of completed spells, I do not include this variable here. I do include it, however, for regressions involving the expanded sample. 27 The average annual growth rate proxy takes different values among firms in the same industry because of different dates of entry and exit, even though the life spans may be the same. The earliest entry date used for this purpose is 1954, the earliest publication of Statistics of Income, Corporate Tax Returns. This procedure should be satisfactory for the present study, because any growth before this date precedes the recent legal changes and the earliest exit date by at least 10 years, and therefore any growth before 1954 will have a minimal effect on the firms I examine. Moreover, if a firm exits in either 1992 or 1993, I use the data from the 1991 Statistics of Income because that is the latest publication; I assume the growth rate to be constant for the remaining 2 years. 28 I add also a binary variable to capture the macroeconomic influences on the timing of the exit (recessionary versus nonrecessionary years). The estimated coefficient of this variable is insignificant in all cases, and its inclusion does not alter the sign or significance of other estimated coefficients. So, I drop the variable from all equations estimated here. 29 I use this method because in all cases heteroskedasticity of unknown form is present. See, White (1980) for details of the heteroskedasticity test and estimation procedure. 30 I also ran regressions on the three subgroups. However, due to the small variation in the Hickey-Kearney variable within each subgroup, the results, although consistent, were not robust.
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TABLE 2. Least squares results for sample of completed spells an expanded sample Equations Independent variables Intercept Hickey-Kearney index Subsidiary dummy Industry growth
(1)
(2)
(3)
(4)
3.99 (6.01)** 20.17 (22.11)* 0.32 (2.50)* 3.01 (4.62)**
3.55 (5.44)** 20.26 (22.67)** 0.31 (2.32)* 0.20 (2.76)**
4.34 (6.08)** 20.23 (22.55)* 0.31 (2.69)** 1.23 (2.46)**
3.47 (10.00)** 20.001 (20.07) 0.12 (1.67)
Public dummy R2 Adj z R2 F Sample size
0.12 0.10 8.78 200
0.07 0.05 4.64 200
0.17 0.16 13.48 200
0.64 (6. 30)** 0.06 0.06 9.40 427
Note: The dependent variable is the duration of firms. (1) Sample of Completed Spells with industry growth 5 firms (2) Sample of Completed Spells with industry growth 5 net income (3) Sample of Completed Spells with industry growth 5 assets (4) Expanded Sample t-statistics are in parentheses. * Significant at the 5% level. ** Significant at the 1% level.
able.31 Similar to earlier results, there is a negative relationship between the HickeyKearney index and duration, although it is not statistically significant. The coefficient estimates for the public dummy are positive and significant at the 1% level, much in accordance with Proposition 2. This result supports the hypothesis that public firms remain in business much longer than do private firms. The subsidiary dummy is also positive, implying that subsidiaries may remain in business longer than independent companies.32 Finally, I apply duration analysis to the sample of completed spells. Parameter estimates for the Weibull, Exponential, and Log-logistic distributions are given in Table 3.33 To give external factors a role, I include covariates in a proportional hazard specification. The model takes the form 2ln L0(t) 5 F(H-Ki, SUBi, ei)
31 Due to multicollinearity between industry growth and the public dummy variable, the growth variable is omitted. In this sample of 427 observations, only 28 were public companies, of which 20 were both founded before 1954 and still in existence as of 1994. Consequently, all 20 of these firms would take on the same value for industry growth. Because the focus of this specification concerns the relationship between length of stay and public financial structure, I exclude the industry growth variable. 32 The results based on the expanded sample must be interpreted with caution because the dependent variable is right censored for most observations. 33 For background in duration analysis, see Greene (1993), pp. 715–727.
22
Latent hazards and firm exit in manufacturing
TABLE 3. Estimated duration models (estimated standard errors in parentheses) Equations Model Weibull Exponential Log-logistic
l
p
Median duration
0.04990 (0.00396) 0.05084 (0.00482) 0.06191 (0.01045)
1.10043 (0.09041) 1.00000 (0.00000) 1.10043 (0.10188)
14.36 (1.13913) 13.63 (1.29175) 16.15 (2.72797)
where L0(t) is the integrated baseline hazard of each firm, H-Ki is the Hickey-Kearney index for the corresponding SIC, SUBi is a binary dummy variable taking the value of 1 for subsidiaries and 0 otherwise, and ei is a random error term that has a fully specified (but not normal) distribution.34 A summary of the results for each of the distributions can be seen in Table 4. Although the Weibull and exponential estimations show a positive sign on the HickeyKearney index variable, there is a negative result for the Log-logistic distribution. However, the t-statistics are extremely low for all specifications, such that no conclusions may be drawn with regard to the effect of expected liability on the conditional probability of completing a spell. The subsidiary dummy variable always generated a positive sign, suggesting that spell length increases given that a firm is a subsidiary. But, once again, none of the results were statistically significant. In sum, the descriptive statistics and least squares results strongly suggest that firms in the more hazardous industries have shorter life spans, as Proposition 1 suggests, although the duration results are ambiguous. Meanwhile, all testing methodologies support Propositions 2 and 3, to the extent that public firms and subsidiaries have longer durations than do private companies and independent firms. IV. Interpretations and Conclusions Ringleb and Wiggins (1990) offer the conjecture that small firms operating at suboptimal levels of care will dominate manufacturing industries that involve long-term, latent hazards. In the event of a mass tort, this equilibrium could lead firms to own insufficient assets to compensate the injured. Although it is difficult, if not impossible, to observe directly whether firms choose suboptimal care and/or exit to avoid liability payments, the testable hypotheses developed here shed some light on firms’ actions. The empirical results generally support the hypothesis that firms in more hazardous industries exit more quickly. Moreover, the empirical results show that private and independent firms have significantly shorter life spans. It would be overreaching, of course, to infer automatically from these results that firms act strategically to avoid their liabilities arising from latent hazards. Although the empirical results are consistent with a tendency by firms to choose a strategic exit, less than 25% of the firms sampled in 1977 had exited by 1994, and there is no evidence that 34 The industry growth variables were not able to be included in the analysis because the regression was unable to locate a function minimum when they were involved.
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TABLE 4. Duration results for sample of completed spells Equations Covariates Intercept Hickey-Kearney index Subsidiary dummy Log likelihood Sample size
(1) 2.847 (21.98) 0.000002 (0.80) 0.301 (1.23) 2259.877 200
(2) 2.847 (18.33) 0.000002 (0.54) 0.301 (1.02) 2266.179 200
(3) 2.847 (9.516) 20.000003 (20.50) 0.301 (0.60) 2302.005 200
Note: (1) Weibull estimation. (2) Exponential estimation. (3) Log-logistic estimation. t-Statistics are in parentheses.
any of these exited firms did so to avoid tort claims.35 An alternative interpretation would be that these firms suffer from mismanagement unrelated to tort liability—a variable for which the empirical model does not control. After all, Ringleb and Wiggins (1990) show that there is a significant increase in firm entry in hazardous industries after 1965; some proportion of these firms are bound to fail for reasons other than tort liability. Moreover, my empirical results and the findings that small firms dominate hazardous industries support the notion that the high uncertainty about the probability of injury and the change in legal regime altered the shape of hazardous manufacturing industries over the past 20 years. The asbestos firms had severely miscalculated the legal and physical risk of their activities, and consequently they harmed many more people than ever anticipated. Tort reform in the 1970s also held these firms liable under circumstances they never had imagined would be possible. We can interpret the reaction to externalize hazardous activities and forego the economies of vertical integration as a way to avoid the risks associated with dangerous activities. Thus, many large firms should have removed themselves from hazardous markets. Meanwhile, small firms entered the market and handled the tasks that large firms with greater levels of assets wanted to avoid because the small firms did not have nearly as much to lose.36 This is precisely what Ringleb and Wiggins (1990) show. My results also suggest that firm entry into hazardous markets has accelerated since 1965 and that these are predominantly privately held, independent firms. Consequently, if present firms severely miscalculate the probability of disaster, or if 35 I ran an extensive search on these exited firms in Westlaw and Lexis/Nexus for court records or newspaper articles mentioning these firms in any way. Nothing relating to tort claims came up on any of the firms. However, I am not suggesting that firms go out of business only after litigation is initiated; it is likely that they will shut down and exit well before any suits are filed, when assets are not sunk. 36 Some argue that if the firm’s assets are small enough, the tort victims will not bother to sue. But these are manufacturing plants, so some amount of fixed assets must be present that could partially settle an award of damages. There are generally no costs to the plaintiff to sue, moreover, because the attorney most likely will be paid ex ante on a contingency basis; the size of the assets a firm holds also is usually realized ex post to the lawsuit. And, in the present litigious climate, although costs to the attorney do exist, lawyers certainly must be willing to take these kinds of cases.
24
Latent hazards and firm exit in manufacturing
liability rules once again change unexpectedly, these small firms with few assets have relatively less to lose. And because these are generally private and independent firms, a plan to liquidate is relatively easy to achieve. As such, the small firm equilibrium may indeed act as a survival strategy for the industry as a whole, given the unknown risk of future asbestos-like disasters. However, what incentives a firm may have to take socially optimal levels of care in the latent hazard setting ex ante to a disaster is a question left for further research. References Directory of Corporate Affiliations. (1994). New Providence, NJ: National Register Publishing. D & B - Dun’s Market Identifiers. (1994). Bethlehem, PA: Dialog Information Services. F & S Index of Corporations & Industries. (1977). Cleveland, OH: Predicasts. GREENE, WILLIAM H. (1993). Econometric Analysis, 2d ed. New York: Macmillan. HICKEY, J.L.S., AND J.J. KEARNEY. (1977). Engineering Control Research and Development Plan for Carcinogen Materials, Cincinnati: National Institute For Occupation and Health. HOLLANDER, MYLES, AND DOUGLAS A. WOLFE. (1973). Nonparametric Statistical Methods, New York: Wiley. LOTT, JOHN R., AND RICHARD L. MANNING. (1995). ‘‘Have Changing Liability Rules Compensated Workers Twice For Occupational Hazards?: Earnings Premiums and Cancer Risks.’’ Working paper. National Institute For Occupational Safety and Health. (1974). National Occupational Hazard Survey, Washington, D.C.: Government Printing Office. RANDLES, RONALD H., AND DOUGLAS A. WOLFE. (1979). Introduction to the Theory of Nonparametric Statistics, New York: Wiley. RINGLEB, AL H., AND STEVEN N. WIGGINS. (1990). ‘‘Liability and Large-Scale, Long-Term Hazards.’’ Journal of Political Economy 98:574. ROE, MARK J. (1984). ‘‘Bankruptcy and Mass Tort.’’ Columbia Law Review, 84:846. ROE, MARK J. (1986). ‘‘Corporate Strategic Reaction to Mass Tort.’’ Virginia Law Review 72:1. SCHWARTZ, ALAN. (1985). ‘‘Products Liability, Corporate Structure, and Bankruptcy: Toxic Substances and the Remote Risk Relationship.’’ Journal of Legal Studies 14:689. Standard & Poor’s Register of Corporations, Directors, and Executives. (1994). New York: McGraw-Hill. Thomas Register of American Manufacturers. (1905–1995). New York: Thomas Publishing Company. Ward’s Business Directory. (1993–1995). Washington, D.C.: Gale Research, Inc. WHITE, H. (1990). ‘‘A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test For Heteroskedasticity.’’ Econometrica 48:817. WIGGINS, STEVEN N., AND AL H. RINGLEB. (1992). ‘‘Adverse Selection and Long-Term Hazards: The Choice Between Contract and Mandatory Liability Rules.’’ Journal of Legal Studies, 21:189.