Whose Safety Net? Home Insurance and Inequality

Whose Safety Net? Home Insurance and Inequality

Tom Baker and Karen McElrath

Drawing on jnior theoretical and empirical work that has begun to con- stitute the insurance field as a distinct sociolegal research project, this study uses quantitative and qualitative data collected following Hurricane Andrew in 1992 to explore distributional questions within that field. Survey results show that higher income, age, and education were associated with having home insurance and that Hispanics and blacks were less likely than non- Hispanic whites to have insurance. The study provides the first quantitative evidence of bias in the insurance claims process by documenting a statistically significant and substantial ethnic difference in the timing of insurance payments. The qualitative research helps to explain the difference in the timing of insurance payments as the product of unconscious bias by insurance adjusters. The study concludes by proposing market-structuring regulation to reduce the inequality encountered.

Bad things happen to good people. This is one of the more painful lessons of childhood, and it is also an important thread in the social fabric. Because bad things happen to good people-that is, to us or to people we care about-we have constructed elaborate ways of providing for the individual and collective disasters that are a constant feature of the human condition.

It is one of the distinctive characteristics of late 19th-century laissez faire capitalism that significant aspects of this caretaking function came to

~

Tom Baker is an associate professor, University of Miami School of Law. Karen McElrath is an associate professor, University of Miami Department of Sociology.

The authors wish to acknowledge research support provided by the University of Miami, research assistance provided by Les Riordan, and assistance in the design, distribution and collection of the survey provided by the University of Miami publications and mail departments. Thanks to Ian Ayres, Howard Erlanger, Michael Froomkin, Terence Halliday, Marvin Jones, Karyl Kinsey, Sheldon Messinger, David Reiss, Robert Rosen, Laurence Ross, Jonathan Simon, and anonymous reviewers for comments on an earlier draft.

0 1996 American Bar Foundation. 0897-6546/96/2 102-0229$01 .oO 229

230 LAW AND SOCIAL INQUIRY

be handled through private contracts between individuals and business en- terprises. Even with the growth of the social welfare state, privately contracted caretaking by insurance companies has remained enormously important. In 1992 in the United States, for example, insurance premiums for property and casualty insurance were over $227 billion, premiums for life insurance were over $2 15 billion, and premiums for private health insurance were over $255 billion.’

The relationship between insurance and caretaking by the state has been and continues to be one of the more explosive themes in American politics. Indeed, near the inception of the American social welfare system in 1934, President Roosevelt dumped the “radical” Townsend plan in favor of his Social Security Act, because Social Security was social “insurance” funded by “contribution,” not “public assistance.”z More recently, President Clinton promoted as his solution to the health care crisis “guaranteed private insurance,” not a “government take over.”3

Despite the material and symbolic importance of privately contracted insurance in American society, there is a dearth of serious empirical research on this private safety net. This study provides one step in that direction. Our most significant finding is that the distribution of residential insurance differs along the race/ethnicity and income fault lines of late 20th-century American society. This study also shows that insurance law- in-action has a similar effect. The first-party insurance claims process favors the advantaged, through the discretion of the private, street-level bureaucrats who administer the insurance contract. If, as we began, insurance of- fers “good people” protection against “bad things,” then we might also say that the more difficult it is for the adjuster to see the claimant as a good person, the less protection that claimant will receive. As a result, disaster increases inequality, not only between those who are and who are not insured against that disaster but also among those who are insured.

These findings will hardly surprise students of inequality.4 Still, they bear emphasizing, particularly because of the ascendance in the insurance field of neoclassical economic theory, with its emphasis on the market and its assumption that the market treats all alike.5 Like racial disparities ob-

1. See The Fact Book: 1994 Properry/Cusualtjr Insurance Facts 5 (New York: Insurance Information Institute, 1994).

2. See Franklin Delano Roosevelt, Communication from the President to Congress, 78 Cong. Rec. S.10770, 78 Cong. Rec. H.10851 (daily ed. 8 June 1934); William H. Simon, “Rights and Redistribution in the Welfare System,” 38 Stan. L. Rev. 1431 (1986).

3. “Clinton Answers Questions about Health Care Reform,” Washington Post, 12 April 1994, Health, at 28.

4. See, e.g., William Julius Wilson, The Truly Disadvantaged: The Inner City, the Under- class, and Public Policy (Chicago: University of Chicago Press, 1987).

5. See, e.g., the essays collected in Georges Dionne & Scott E. Harrington, eds., Founda- tions of Insurance Economics (Boston: Kluwer Academic Publishers, 1992). See also Kenneth Abraham, Distributing Risk: Insurance, Legal Theory and Public Policy (New Haven, Conn.: Yale University Press, 1986) (“Abraham, Distributing Risk”).

Home Insurance and Inequality 23 I

served in other markets,6 the racial and ethnic inequality we observe casts doubt on that equal treatment assumption. It is just as important to emphasize, however, that much of the inequality we observe is consistent with a vision of unbiased insurance companies competing for business. As these more banal results remind us, equal treatment by the insurance market does not produce equal results. As important a goal as equal access to that market may be, access alone will not create a private safety net that works for all.

This study joins a small but growing area of sociolegal research that is concerned with an enormous social field-insurance-that is interpene- trated with and by the legal field(s).7 As writers from diverse traditions have emphasized, “insurance” and “liability” are often two sides of the same coin.n Indeed, the insight that liability insurance is tort law-in-action produced two of the leading studies on the gap between law-on-the-books and law-in- action: Ross’s study of automobile adjusters9 and Whitford’s study of products liability.10

Other studies have emphasized that “private” and “social” insurance are, to stretch the metaphor, two halves of one side of that coin.” As Defert and O’Malley have described, social insurance grew up with, and in part out of, private insurance companies.’* Ever since, private and social insurance-“market” and “state” insurance-have existed in a complex relationship that is yet to be adequately investigated. While the contours of that relationship are not well understood, i t is clear nevertheless that the availability of market insurance strongly influences state or state-sponsored insurance and that the reverse is true as well.

It is also increasingly clear that insurance practices exercise a powerful governmental force on those who enter the insurance field. Recently,

6. See, e.g., Ian Ayres, “Fair Driving: Gender and Race Discrimination in Retail Car Negotiations,” 104 Haw. L. Rev. 817 (1991) (discussing the implications for neoclassical economics of research finding gender and racial bias in the new car market).

7. See Pierre Bourdieu & Loic J. D. Wacquant, An Invitation to Refkxive Sociology 94- 100 (Chicago: University of Chicago Press, 1992) (on the concept of a field).

8. See, e.g., Richard Abel, “A Socialist Approach to Risk,” 41 Md. L. Rev. 695, 697-98 (1982); Richard Epstein, “Products Liability as an Insurance Market,” 14 1. Jigal Stud. 645 (1985).

9. H. Laurence Ross, Settled Out of Court: The Social Process of Insurance Claims Adjust- ment (Chicago: Aldine Publishing Co., 1970) (“Ross, Settkd Out of Court”).

10. William C. Whitford, “Strict Products Liability and the Automobile Industry: Much Ado about Nothing,” 1968 Wis. L. Rev. 1983.

11. See Kenneth S. Abraham & Lance Liebman, “Private Insurance, Social Insurance and Tort Reform: Toward a New Vision of Compensation for Illness and Injury,” 93 Colum. L. Rev. 75 (1993). It should be clear that we are using the word “private” in the colloquial sense indicating that the insurance companies, in contrast to, say, the Social Security Admin- istration, are not state owned or operated.

12. Daniel Defert, “ ‘Popular Life’ and Insurance Technology,” in Graham Burchell, Colin Gordon, & Peter Miller, eds., The Foucalt Effect: Studies in Governmentality 211 (Chi- cago: University of Chicago Press, 1991) (“Burchell et d., Foucault Effect”); Pat OMalley, “The Prudential Man Cometh” (presented to 1995 Law &a Society Association Annual Meet- ing, Toronto).


O’Malley has investigated private home insurance in Australia as an example of Foucault’s concept of governmentality , describing how “private” insurance adjusters form a domestic security network with “public” policing agencies.’) Simon’s studies of actuarial practices and of risk management and campus lifeI4 and Simon’s and Ewald’s historical researchI5 reflect these same underlying theoretical concerns.

A parallel sociolegal research tradition has been concerned with the delivery of legally mandated services and the enforcement of regulation. Re- search by LipskyI6 and Handler,I7 among others,’S has explored the strategies that street-level bureaucrats use to balance the competing demands of clients and supervisors. Research by Hawkins19 and Ross and Thomas,20 among others,21 has explored the strategies that street-level regulators use to balance the competing demands of regulatory targets and supervisors. These studies have shown that the delivery of legally mandated services or regulation involves substantial discretion on the part of the state agents most directly responsible for delivering those services or regulation. The studies have also shown that moral judgments about clients or regulatory targets have a substantial impact on the exercise of that discretion.

Another strand of sociolegal research has focused on the question of who has access to the insurance market. Prompted in part by the insurance market’s retreat from the central city in the wake of civil unrest in the 1960s’ this research has examined access to insurance largely through the lens of civil rights discourse. Heimer’s study of the origins of insurance redlining,** Squire’s and Velex’s empirical research,23 and theoretical work by

13. Pat O’Malley, “Legal Networks and Domestic Security,” 11 Stud. L. B Pol. SOC. 171 (1991).

14. Jonathan Simon, “The Ideological Effects of Actuarial Practices,” 22 Law B Soc’y Rev. 771 (1988); id., “In the Place of the Parent: Risk Management and the Government of Campus Life,” 3 Soc. B Legal Stud. 15 (1994).

15. Jonathan Simon, “The Emergence of a Risk Society: Law, Insurance, and the State,” 89 Socialist Rev. 61 (1987); Francois Ewald, “Insurance and Risk,” in Burchell et al., Foucault Effect 197.

16. Michael Lipsky, Street Level Bureaucracy: Dilemmas of the Individual in Public Services (New York: Russell Sage Foundation, 1980).

17. Joel Handler, The Conditions of Discretion (New York: Russell Sage Foundation, 1986).

18. See, e.g., Roy Sainsbury, “Administrative Justice: Discretion and Procedure in Social Security Decision-making,” in K. Hawkins, ed., The Use of Legal Discretion 295 (New York: Oxford University Press, 1992) (“Hawkins, Discretion”).

19. Keith Hawkins, Environment and Enforcement: Replation and the Social Definition of Pollution (Oxford: Clarendon Press, 1984).

20. H. Laurence Ross &a John M. Thomas, “Housing Code Enforcement: A Study of Law in Action” (1995) (MS. on file with the first author) (“ROSS & Thomas, ‘Housing Code Enforcement’ ”).

21. See, e.g., Richard Lempert, “Discretion in a Behavioral Perspective: The Case of a Public Housing Eviction Board,” in Hawkins, Discretion 231.

22. Carol A. Heimer, ‘The Racial and Organizational Origins of Insurance Redlining,” 10 J. Intergroup Rel. 42 (1982).

Home Insurance and Inequality 233

Taibi and others24 have been directed at documenting and explaining racial disparities in access to the insurance market, with the goal of developing legal strategies for expanding that access. While these researchers might not use this language to describe their projects, their emphasis on access to insurance demonstrates that the insurance field acts not only on those who enter it but also on those who cannot, in large part because of the relationship between the insurance and investment fields.

Our study joins and extends these previously unconnected strands of sociolegal research. We combine Ross’s and O’Malley’s focus on the private insurance adjuster with insights from the literature on street-level discretion in the delivery of public benefits. Following Handler’s ~uggestion,~~ we in- troduce an explicitly distributional aspect to the question of discretion. And we extend the empirical investigation of access to the insurance field to the realm of insurance claims. While there have been anecdotal reports of bias in the exercise of insurance adjuster discretion, ours is the first study to use quantitative data to document differential treatment in the handling of insurance claims.26

Part I describes our research project and the basic outline of residential property insurance as it is sold in the United States. Part I1 presents the results of our investigation into who has home insurance. Based on the survey research, we conclude that home insurance disproportionately protects the relatively advantaged. Most strikingly, when we control for income, education, age, home ownership, type of home, and other factors we considered, we find substantial race/ethnicity disparities in the distribution of home insurance.

Part I11 presents the results of the investigation into the distributional effects of the insurance claims process. Drawing on interviews with adjusters, claimants, and insurance mediators, we conclude that the insurance claims process also favors the relatively advantaged, through the discretion exercised by adjusters in settling insurance claims. Using the survey, we pro-

23. See, e.g., Gregory D. Squires & William Velex, “Insurance Redlining and the Pro- cess of Discrimination,” Rev. Black Pol. Econ., Winter 1988, at 63; id., “Insurance Redlining, Agency Location, and the Process of Urban Disinvestment,” 26 Urb. Aff. Q. 567 (1991).

24. Anthony D. Taibi, “Banking, Finance, and Community Economic Empowerment: Structural Economic Theory, Procedural Civil Rights, and Substantive Racial Justice,” 107 Haw. L. Rev. 1465 (1994); Ruthanne DeWolfe, Gregory Squires, &a Alan DeWolfe, “Civil Rights Aspects of Insurance Redlining,” 29 DePaul L. Rev. 315 (1980); David I. Badain, “Insurance Redlining and the Future of the Urban Core,” 16 Colum. J.L. Gs SOC. Prob. 1 (1980).

25. Joel Handler, “Power, Quiescence and Trust,” in Hawkins, Discretion 333 (“Handler, ‘Power’ ”) (criticizing the discretion literature for insufficient attention to distributional issues).

26. In the disaster literature, Bolin and Bolton noted race/ethnicity differences in insurance coverage after natural disasters, but they did not explore whether these differences re- sulted from purchasing patterns or disparate treatment in the claims process. See Robert Bolin & Patricia Bolton, Race, Religion and Ethnicity in Disaster Recovery 16, 169 (Boulder: Univer- sity of Colorado Institute of Behavioral Science, 1986).


vide strong, objective evidence of the systematic effect of this discretion by documenting an ethnic disparity in the timing of insurance payments.

In part IV we address the implications of our findings for insurance regulation and propose limited, market-structuring intervention to address the inequality we encountered.

I. HOME INSURANCE IN THE UNITED STATES

Today’s home insurance is the direct descendant of the fire insurance developed in London in the late 17th century. First popularized in the United States in the mid- 19th century, fire insurance protected the owners of homes and other buildings from damage to the building structure caused by fire. Fire insurance for the contents of buildings became widely available in the United States later in the 19th century. As the coverage expanded to include damage from wind, hail, lightning, and other perils, “fire insurance” became “hazard insurance.” Then, in the mid-20th century, “hazard insurance” became “homeowners’ insurance,” as insurance companies combined residential property and liability insurance into a single package.

The standard homeowners’ insurance policy27 provides three distinct types of property insurance coverage: “dwelling” or “structure” coverage, which pays in the event of damage to the structure of the home; “contents” or “personal property” coverage, which pays in the event of damage to the contents of the home; and “additional living expenses” or “loss of use” coverage, which pays for additional living expenses incurred while recovering from damage to the home (e.g., lodging and restaurant meal expenses that exceed an insured’s usual living expenses). This additional expense coverage is especially important in the wake of a disaster, like Hurricane Andrew, in which the disruption of the social infrastructure prolongs the recovery process.

There are three other forms of home insurance: condominium owners’ insurance, renters’ insurance, and “dwelling protection insurance.” The standard condominium owners’ policy is like a homeowners’ policy but with less structure coverage (for the inside walls and other parts of the structure that are not the responsibility of the condominium association and for as- sessments by the condominium association). The standard residential renters’ policy is like a condominium policy but typically without any structure coverage (because the structure is typically the responsibility of the land- ~~ ~~

27. The first author has compared the homeowners insurance policies issued by the leading homeowners insurance carriers in the Florida market (Allstate and State Farm), as well as the standard Insurance Services Office, Inc., policies issued by most of the rest of the carriers. These are the same insurance policies sold in most of the United States. While there were minor differences in the homeowners policies sold by various insurers, those differences are not significant for present purposes. Similarly, while the standard Florida policies differ slightly from those sold in other states, those differences are also not significant.


lord). The basic dwelling protection insurance policy contains only a some- what less desirable form of the building structure coverage and a small amount of additional expenses coverage. Contents coverage can be added by paying an additional premium but typically is not.

The most common purchasers of dwelling protection policies include banks and mortgage holders, which purchase dwelling protection policies to protect their collateral when the owner of the home does not otherwise arrange for the purchase of insurance. Standard mortgage documents au- thorize lenders to charge their borrowers for this insurance.28 Such “forced place” insurance is more expensive than homeowners’ insurance, notwithstanding the narrower coverage provided. As a result, homeowners have a strong incentive to purchase the broader-coverage homeowners’ insurance. When they do not, the bank or mortgage company will likely have purchased dwelling protection insurance that covers at least the lender’s interest in the structure of the house. There is no corresponding institutional force in the renters’ insurance market, a lapse that we will address in our conclusions and recommendations.

Hurricane Andrew, the University of Miami, and the Hurricane Mediation Center: Windows on 636,000 Insurance Claims

On 24 August 1992, the eye of Hurricane Andrew passed just 10 miles south of Miami, leaving behind billions of dollars of property damage and an enormous insurance laboratory. Located just south of Miami and near the northernmost edge of the most heavily devastated area, the University of Miami offered a unique window on the hurricane and recovery. The university’s nearly 7,000 full-time employees live as far south as the upper Florida Keys and as far north as Palm Beach, with most concentrated in Dade County. Just under half of those lived south of Sunset Road, which roughly begins the area in which the hurricane damage became severe, the area that the insurance “storm troopers” who descended on Miami immediately dubbed the “war zone.”

In the wake of the hurricane, an interdisciplinary faculty committee proposed conducting a survey of university employees to study hurricane- related issues. Although there were serious methodological objections to this approach, there were no better ways available to respond to this opportunity. University employees, while not “representative’’ of the greater

28. This practice is authorized by state law. See, e.g., Fla. Admin. Code 8 3D-160.025 (12). It is also mandated by federal regulation. See, e.g., 12 C.F.R. 8 571.4 (1994) (requiring each savings association “to include in its loan contracts provisions which require the maintenance of such hazard insurance as will protect the savings association from loss in the event of damage to or destruction of the real estate securing the savings association loan”).


Miami p ~ p u l a t i o n , ~ ~ surely represented the range of hurricane-related experiences, at least those of households with a steady, secure job. The university is the second largest private employer in Dade County; its hospital is the largest in Florida. Respondents would include maintenance workers, secre- taries, and orderlies, as well as doctors, nurses, and university professors. The only available alternative, a random telephone survey, presented equally significant problems. Living patterns were sufficiently disrupted by the hurricane that a telephone survey could just as easily be criticized. Moreover, a telephone survey conducted even with several multiples of the resources available on such short notice would have only a fraction of the respondents as a university survey.

From the beginning, it was clear that any effort to use the Hurricane Andrew experience to study home insurance would require a mix of approaches. A survey would be an ideal way to measure who had home insurance and to test objective measures of the insurance claims process. Providing a fuller picture of that claim process, however, would require qualitative research.

We began the qualitative research with claimant interviews, first with university employees and then radiating out in a “snowball” fashion to non-university-affiliated acquaintances of the initial inf0rmants.3~ The claimant interviews taught us the basics of the insurance claim process and provided a sense of the variety af claimants’ experiences. Above all, the interviews underscored the centrality of home insurance after the hurricane, in stark contrast to the uniformly invisible nature of that insurance before the hurricane.

After some false starts, we obtained good access to insurance adjusters-the central figures in the claim process-at the Florida Department of Insurance Hurricane Mediation Center. In part because Department of In- surance regulations prohibited the use of attorneys at the mediations, the Mediation Center had a surprisingly relaxed atmosphere in which the usu- ally hard-to-reach adjusters were accessible and ready to talk. While at the Center, adjusters had time on their hands and little to do with it. The re- sulting interviews, together with observations of mediations and a later se- ries of interviews with mediators, form the core of the qualitative research. A more detailed description of the qualitative methods appears in the technical appendix.

29. For example, the race/ethnicity composition of our sample was 65% white non-His- panic, 8% black non-Hispanic, and 27% Hispanic, compared with the Dade County population of 32% white non-Hispanic, 19% black non-Hispanic, and 49% Hispanic. Dade County figures are from US. Bureau of the Census, Census of Population and Housing, 1990, Summary Tape File 3, Florida.

30. The qualitative research was conducted by and under the direction of the first author.


11. WHO HAS INSURANCE: SURVEY FINDINGS

The Hurricane Andrew Impact Survey used an attractively designed booklet that was distributed to university employees at work in April 1993 (seven months after the hurricane) and collected through the campus mail system. The survey booklet contained questions on many hurricane- and recovery-related topics, including insurance, home ownership, hurricane damage, and area of residence, along with questions about family income, race/ethnicity, and other demographic information. A description of the rel- evant areas in which we collected data and the way we measured the data appears in the technical appendix.

Summary statistics for the survey respondents are presented in table 1. We received 3,406 responses, a response rate of 51.7%. Of the respondents, 70% were insured.3’ Of those insured, an astonishing 73% filed hurricane- related insurance claims.

We first looked at all respondents to see what characteristics were associated with having insurance. The results of our logistic regression analysis are presented in summary form in table 2.32 As expected, factors associated

31. This finding is consistent with survey results using a random sample of South Florida residents contacted by telephone four months after the hurricane. See Walter GilIis Peacock, Chris Girard, & Hugh Gladwin, “A Summary of Findings from the FIU Hurricane Andrew Survey” (1994) (unpub. report on file with the authors).

32. Logistic regression differs from the more commonly used linear regression in that logistic regression can be used to analyze associations with a dependent variable that is yes/no in character, such as having insurance or not. The beta weights and odds ratios reported in our tables express the strength of the association between a particular independent variable and the dependent variable under analysis. Here, the dependent variable is having insurance and the independent variables are race/ethnicity, income, etc.

A logistic regression equation predicts the log of the odds of an observation being in one category of the dependent variable versus the other. This is the beta weight (b ) reported in the tables. An odds ratio is the antilog of the beta weight (e“”)), and it always has a positive sign (i.e., it is greater than zero). An odds ratio represents the amount by which a unit change in an independent variable multiplies the odds of an observation being in one category versus the other, holding the remaining independent variables constant. See David W. Hosmer, Jr., & Stanley Lemeshow, Applied Logistic Regression 41 (New York: Wiley, 1989). This means that the farther an odds ratio for a given independent variable is from 1.00, the more strongly associated that variable is with the dependent variable, either in a positive or negative direction. In the first equation, the highest odds ratio is the 12.44 reported for homeownership, which tells us that owning a home is very strongly associated with having insurance. The lowest odds ratio is the .17 reported for living in a trailer, which tells us that respondents who lived in trailers were quite unlikely to have insurance. We calculated the odds ratios only for the significant variables.

In comparing odds ratios among independent variables, it is important to keep in mind the difference between dummy variables (i.e., yes/no variables, such as homeownership in this study), interval variables (i.e., variables with categories composed of ranges, such as income in this study) and continuous variables (such as age in this study). Because the odds ratios pre- dict the effect of increasing or decreasing the independent variable by one unit, regardless of the kind of variable under analysis, an important dummy variable can be expected to have an odds ratio further from 1.00 than an important interval variable, just as an important interval variable can be expected to have an odds ratio further from 1.00 than an important continuous variable. See id. at 56. Among our variables, age is continuous; income, education, and


TABLE 1 Summary Statistics

Percentage of respondents with home insurance Percentage of those insured who filed a claim Percentage of claimants visited by an adjuster

within one month after the hurricane Percentage of claimants who received an insurance

payment within one month after the hurricane

Race/ethnicity of respondents: Black non-Hispanic Hispanic White non-Hispanic Other No response

Average income of respondents Average age of respondents Average education of all respondents Percentage of respondents living in female-headed

Percentage of respondents who owned their home Housing type of respondents:

households

House Apartment Townhouse Trailer Other

Area in which respondents lived at the time of the hurricane

Disaster zone Elsewhere in Dade County Broward County

70% 73%

39%

37%

8% 24% 58%

7% 4%

$50,001-$65,000 43 years

Some college-associate degrees

5% 32%

60% 23% 13% 1% 2%

41% 54%

5%

with the home were strongly associated with having insurance. Owning a home was the most strongly associated factor; living in a house, rather than an apartment or townhouse, was a close second.33

Income, age, and education also were significant; higher-income, older, and more educated respondents were more likely to be insured than other respondents. These latter, unsurprising, results are consistent with the findings of a recent study using U.S. Department of Labor survey data.34 The

damage are interval, and the remainder are dummy variables. A further description of the variables appears in the technical appendix.

33. Among renters, the percentages having insurance by home type were 25.9% for apartments, 29.5% for townhouses, and 43.8% for houses; among owners, the percentages were 69.4% for apartments, 88.7% for townhouses, and 97.0% for houses.

34. See Vince E. Showers & Joyce A. Shotick, “The Effects of Household Characteris- tics on Demand for Insurance: A Tobit Analysis,” 61 1. Risk B Ins. 492 (1994). The study did not consider education or the other independent variables used in our equations, so no comparison of those measures can be made.


TABLE 2 Logistic Regression Results for Insured/Not Insured

b Odds Ratio

Race/e thnicitya Black non-Hispanic Hispanic Other No response

Income Age Education Female-headed household Age of home Homeowner Residence typeh

Apartment Townhouse Trailer Other

Disaster zone Broward County

Area‘

Constant

-.536* -.359* -.737* -.383

.326***

.027***

.167*** -.457 -.007 2.521***

-1.422*** -.850***

-1.786** -.243

.286

.220 -5.201

.59

.70

.48

1.39 1.03 1.18

12.44

.24

.43

.17

a “White non-Hispanic” is omitted category. “Detached house” is omitted category. “Elsewhere in Dade Giunty” is omitted category.

* p < .05 ** p < .01 *** p < ,001

new, and troubling, finding is that there were also significant race/ethnicity differences in who had insurance: controlling for home ownership, income, and the other variables we examined, we found that white non-Hispanics were significantly more likely than either black non-Hispanics or Hispanics to have home insurance.

We also looked at homeowners and renters separately. Table 3 presents a summary of those results. For both homeowners and renters, higher age and income were associated with having insurance, as was living in a house. Higher education was associated only with having insurance for homeowners, not for renters.

We found significant race/ethnicity differences in the results for both homeowners and renters. Among renters, Hispanics were nearly twice as likely to be uninsured as white non-Hi~panics.3~ Black non-Hispanic renters did not differ significantly from white non-Hispanic renters in the logistic

35. Respondents who did not report their ethnic identity also differed significantly from those who reported this item. This finding suggests that missing racelethnicity data might have biased the results for this equation had we not accounted for the omission.


TABLE 3 Logistic Regression Results for Insuremot Insured for Homeowners and Renters Separately

Homeowners Renters

b Odds Ratio b Odds Ratio

Race/e thnicity” Black non-Hispanic Hispanic Other No response

Income Age Education Female-headed household Age of home Residence Typeh

Apartment Townhouse Trailer Other

Disaster zone Broward County

Areac

Constant

-.850* -.037

-1.090** .904 .185** .042*** .246**

-.493 -.013

-3.084*** -1.468*** -2.943*** -1.437**

.351

.909

.094

.43

.3 7

1.20 1.04 1.28

.05 -23 .05 .24

-.45 1 -.530* .59 -.223

-1.919* . I5 .443 * * * 1.56 .019* 1.02 .085

-.773 -.008

-.542* -.314

.714 1.250

.076 -.342

-2.819

.58

” White non-Hispanic is omitted category. ” Detached house is omitted category.

Elsewhere in Dade County is omitted category. * p < .05 ** p < .01 *** p < .001

regression analysis. This does not mean, however, that black non-Hispanic renters were as likely to have insurance as white non-Hispanic renters, but rather that the substantial difference between the two groups is “explained” in the logistic regression equation by other factors, such as income and the type of home rented (i.e., apartment vs. house).

Among homeowners, black non-Hispanics were over twice as likely as white non-Hispanics to be uninsured even when we controlled for these other factors. Hispanic homeowners, in contrast, were no more likely to be uninsured than white non-Hispanic homeowners. The disappearance of the Hispanic difference under conditions of owning a house confirmed the strong institutional force provided by the mortgage financing market.36

36. A comparison of renters and owners by race/ethnicity revealed that among white non-Hispanics, 61% of renters, 16% of condominium owners, and 2% of house owners were not insured; among black non-Hispanics, 80% of renters and 9% of house owners were not insured (there were too few condominium owners for comparison); among Hispanics, 73% of renters, 33% of condominium owners, and 3% of house owners were not insured.


Who Has Insurance: Discussion

The survey results show that the distribution of insurance is weighted toward the relatively advantaged. Respondents who were young, less educated, poor, black, or Hispanic received less protection from the private insurance market than those who were older, more educated, wealthier, and non-Hispanic whites. Although our findings must be treated with some cau- tion because all respondents were employed by the University of Miami, the differences we found even in this employed and educated community strongly suggest that in our society, as presently constructed, the private home insurance safety net does a better job of protecting the relatively advantaged than of protecting the less advantaged.

It is important to emphasize that the race/ethnicity differences we found cannot be attributed to home ownership, type of home, income, education, or age; these variables were introduced as controls in the equation. The unequal distribution of these other social characteristics on race/ ethnicity lines, however, underscores how “overdetermined” are the race/ ethnicity disparities in insurance and, as a result, how disproportionately the financial effects of disasters fall on blacks and Hispanics.

Looking separately at homeowners and renters, we found that black homeowners were less likely than Hispanic or white non-Hispanic homeowners to be insured and that Hispanic renters were less likely than white or black non-Hispanic renters to be insured. The most salient difference between the homeowners’ and renters’ insurance markets is the compulsion provided by banks and mortgage companies in the purchase of homeowners’ ins~rance.~7 Controlling for income and the other variables we examined, we found that our black and white renter respondents purchased insurance in near equal proportions. Thus, the difference between black and white respondents in the incidence of homeowners’ insurance is unlikely to be attributable to consumer preference. Instead, the difference between black and white respondents in the incidence of homeowners’ insurance must be attributable to some feature of the home financing process (which includes the purchase of insurance incident to that financing).

The survey did not collect geographic information that was fine- grained enough to determine whether this difference correlates with patterns of residential segregation. It is well recognized that insurance companies use geographic-based distinctions when setting rates and marketing

37. While there is no difference in the incidence of home insurance among white non- Hispanic and Hispanic owners of houses, there is a substantial difference in the incidence of home insurance among owners of apartments, as the text in note 36 shows. This result is consistent with the mortgage “compulsion” because in the case of an apartment-type condominium the important coverage, from the lender’s perspective, is the insurance that the condominium association maintains on the building structure, not the insurance the individual unit owners maintain on their personal property.


insurance policies. Prior research suggests that these geographic distinctions affect blacks in greater proportion than whites because blacks are more likely to live in urban areas in which insurance is more expensive and less available.38 Insurance companies have contended that this result is consistent with the insurance principle of “actuarially fair di~crimination”~~ because of the greater risks of loss in urban neighborhoods.40

The geographic information collected in the survey was intended to capture hurricane-damage-related information rather than patterns of residential segregation. Nevertheless, it was possible to identify those zones that contained substantial urban areas and to perform separate zone-by-zone regression analyses using the same variables listed in table 2. In those zones that were exclusively suburban, no race/ethnicity variables were significant predictors of having insurance, either for renters or homeowners. In each of the four zones that included urban areas, however, a race/ethnicity variable was significant. In two of the zones, Hispanic renters were significantly less likely to have home insurance than non-Hispanic renters, and in the other two zones, black non-Hispanic homeowners were significantly less likely to have home insurance than Hispanic or white non-Hispanic homeowners. Thus, it is possible that the race/ethnicity differences observed in the survey reflect what would be regarded as “fair discrimination” within the context of actuarial practice; that is, the differences may be attributable to insurance pricing and availability decisions that are based on geographic variations in loss experience, not suspect variables such as race or ethnicity.4’

Nevertheless, because the home financing process typically requires the purchase of insurance, such actuarially fair behavior by insurance companies is unlikely to be a complete explanation for the lower incidence of home insurance among black respondents. As described earlier, conventional mortgage arrangements require the homeowner to obtain home insurance and also provide for “force placing” home insurance in the event the homeowner does not. Thus, our results suggests either that non-Hispanic blacks have differential access to the conventional mortgage market4* or

~~~~~~~~~ ~ ~ ~~ ~~

38. See, e.g., Squires & Velex, 26 Urb. Ajf. Q. 567 (cited in note 23) . 39. Kimball has described “fair discrimination” as follows: “to measure as accurately as is

practicable the burden shifted to the insurance fund by the policy holder and to charge ex- actly for it, no more and no less.” Spencer L. Kimball, “Reverse Sex Discrimination: Manhmt,” 1979 A.B.F. Res. J. 83, 105 (1979). For a perceptive review of the literature and a discussion of the principle of actuarially fair discrimination in the context of gender-based life insurance and annuity premiums, see Simon, 22 Law &? Soc’y Rev. 771 (cited in note 14).

40. See, e.g., R. W. Swegle (Vice-president of Safeco), Letter to the Editor, Nat’l Under- vn‘ter, Prop. & Casualty Ed., 21 March 1994, pp. 23-24 (responding to “redlining” allegations by stating that “there are loss patterns which correlate with geography, construction, replacement cost and age of construction”).

41. Cf. Abraham, Distributing Risk 94 (cited in note 5) (“[wlhether the use of territorial variables is considered an alternative to discriminatory classification or a mere subterfuge depends on whether the purpose of the substitution is symbolic or practical”).

42. There are allegations that blacks have less access to the conventional mortgage market than non-Hispanic whites. See, e.g., Roberta Achtenburg (Assistant Secretary, United


that the conventional mortgage market is less active in policing the insurance requirement when dealing with non-Hispanic blacks. The difficulty of making such causal statements, however, is underscored by the fact that differential access to the insurance market could also be an explanation of differential access to the mortgage market. Clearly, more research is needed in this area.

For renters, there is no institutional compulsion analogous to that provided to homeowners by the mortgage financing market. Thus, consumer preference plays a larger role in the decision to purchase renters’ insurance. For that reason, one plausible explanation for the lower incidence of renters’ insurance among Hispanic respondents may be culturally influenced preferences. The fact that there was no significant difference between His- panic and non-Hispanic white respondents in the incidence of homeowners’ insurance suggests that Hispanic respondents have access to the insurance market. Nevertheless, before concluding that the non-Hispanic/ Hispanic difference in the incidence of renters’ insurance is attributable to cultural preference, more research is needed on the relationship between insurance purchasing patterns and culture4’ as well the differences between the renters’ and homeowners’ insurance markets. The fact that the His- paniclnon-Hispanic difference was observed only in geographic zones that contained urban sectors suggests that “redlining” (whether actuarially fair or not) may be an additional explanation.

Our income finding was unsurprising, confirming earlier research on total insurance demand.44 We learned from the interviews with adjusters (and from subsequent verification with insurance agents) that insurance for low-priced homes or for low-value belongings has a higher price per dollar of coverage than insurance for high-priced homes or for high-value belongings. Insurance agents and adjusters explain that this price difference is attributable to higher loss ratios on lower-value policies. Whether that explanation is accurate or not, the result is that home insurance costs more for those with lower incomes. In addition, home insurance provides less utility to those with lower incomes, because the home insurance package commonly includes both property and liability insurance. Lower-income in-

States Department of Housing and Urban Development Oftice of Fair Housing and Equal Opportunity), Prepared Statement before the House Committee on the Judiciary, Subcom- mittee on Civil and Constitutional Rights Oversight Hearings on Fair Housing, 28 Sept. 1994; Peter P. Swire, “The Persistent Problem of Lending Discrimination: A Law and Eco- nomics Analysis,’’ 73 Tex. L. Rev. 787 (1995). At least some alternative financing arrangements, such as loans from family members or religious organizations, lack the institutional mechanism for requiring insurance exercised by banks and mortgage companies. As a result, reduced access to the conventional mortgage market can be expected to result in a lower incidence of homeowners’ insurance.

43. Such research would have to take into account the fact that the label “Hispanic,” like all such labels, hides a great deal of cultural diversity. See Virginia Dominguez, “Same- nesses” (1994) (MS. on file with the author).

44. Showers & Shotick, 61 1. Risk d Ins. 492 (cited in note 34).


dividuals can be expected to derive less benefit from liability insurance, because they are unlikely targets for a liability claim (at least, unless they have insurance) .45

In sum, the pattern of insurance distribution that we observed appears largely consistent with the hypothesis that insurance purchasing patterns reflect unbiased, profit-maximizing behavior by insurance companies competing for business in a world characterized by great inequality. The exception may be racial and ethnic bias in the insurance/home financing market (and, as discussed in the next section, in the adjustment of claims). Never- theless, given the tight correlation between race/ethnicity, income, and education, eliminating whatever racial or ethnic bias is present in the insurance market will not eliminate racial and ethnic diqunties in the insurance market. That we regard eliminating such bias to be an important goal is demonstrated in the next section. Nevertheless, if the private insurance market is to become a safety net that works for more than the comparatively privileged, some intervention in that market is necessary. We propose one such intervention in part IV.

111. THE DISTRIBUTION OF INSURANCE BENEFITS

Both the survey and qualitative portions of this study examined the insurance claim process. The strength of this aspect of the study comes from the interplay between the quantitative and qualitative methods.

The survey contained two questions designed to capture objective information about respondents’ claims experiences: the timing of the respondents’ first insurance payment and the timing of the first meeting of a member of the household with an adjuster at the home.46 Timing measures have been used by other researchers as a lens on the micro exercise of power and di~cretion.4~ Nevertheless, we are sensitive to concerns about the importance of timing measures. Time is measurable and objective, but it does not present a complete picture of the insurance claims process.

Our claimant interviews made clear, however, that prompt action by an insurance company does mean a great deal to the victims of a disaster. Prompt payment of structure and contents claims allows the physical recov-

45. As Kent Syverud’s recent, provocative article suggests, all individuals without significant assets to protect might well be better off without such insurance, or at least without large amounts of such insurance, because having insurance makes one a more likely target of litigation. Kent Syverud, “On the Demand for Liability Insurance,” 72 Tex. L. Rev. 1629 (1994).

46. To screen out meetings at an insurance field office, which would not give the adjuster an opportunity to assess the damage to the home, the survey specified a meeting “at the home.”

47. See Barry Schwartz, Queuing and Waiting: Stwhes in the Social Organization of Access and Delay (Chicago: University of Chicago Press, 1975).


ery process to begin; prompt payment of additional living expenses claims softens the financial “disaster after the disaster”; and, perhaps most important, prompt payment demonstrates, concretely and materially, that social supports work and that recovery will take place.

One informant whose home was destroyed in the storm reported an experience that illustrates this last point:

INFORMANT: You know what? We got the [homeowners’ insurance] policy the same day the hurricane came . . . . When the hurricane passed and everything, we went to get the mail and when we opened the box, the insurance policy was there.

INTERVIEWER: “That’s incredible! So, did you read it?” INFORMANT: Yes, I read everything, everything, every little word it

had. . . . When I saw my house (because I saw my house before I got the policy), I was thinking “Forget it. That’s it.” The first thing that was in my mind [was] “My credit was going down.” And since I had a problem before that-I cosigned for somebody and they re- possessed the car. So I was thinking about it: “This was the way I was getting my credit clean, and I lost everything. I’m not going to be able to pay this house and pay another rent.” So as soon as I opened the policy I was looking to see what I could do, . . . and I kept on reading and looking at all this and I knew right away after I finished the policy, that everything was going to be OK.

Like many of the other claimants we interviewed, however, the informant’s wife was less optimistic:

My wife was the one that . . . didn’t know what to do and she was crying, every second, every minute of the day, but, you know, I kept on telling her what I was going to do and what I had decided to do. . . . She was worried because she saw everything like that and she thought she would never get paid.

Fortunately, this story had a happy ending (as did most of the Hurricane Andrew stories we recorded). The informant reached the insurance company within a few days of the storm, an adjuster was at the site within a week with an initial payment in hand, and the full insurance check arrived within a month:

When we went to claim the money, it was OK. The money was right. They did a good thing.

Reading the insurance policy helped some. Seeing the adjuster helped some more. Getting the money made it real. Timing measures may not be perfect,


but they provide a meaningful, objective basis for comparing claims experiences.

We used a logistic regression analysis to examine the associations between the responses to the timing questions and the demographic variables used before, plus the level of damage to the home. When examining the timing of the first check, we also considered whether the claimant had met with an adjuster at the home. Table 4 presents a summary of those results.

TABLE 4 Logistic Regression ResuIts for First Adjuster Visit and Insurance Payment

Adjuster Meeting within 1 Insurance Payment Month“ within 1 Month

b Odds Ratio b Odds Ratio

Race/Ethnicityb Black non-Hispanic .049 -.243 Hispanic -.223 -.496** .61 Other -.137 -.518* .60 No response .I67 .236

Income .017 -.001 Education .005 -.012 Female-headed household -.356 .252 Damage .097* 1.10 .252*** 1.29 Area‘

Disaster zone .I79 .789*** 2.20 Broward County .435 .373

1 month“ not applicable 1.681 *** 5.37 Met with adjuster within

Constant -.976 -2.367

a The “adjuster meeting within 1 month” variable measured whether the respondent reported that a member of the respondent’s household had met with an adjuster at the home during the first month after the hurricane.

“White non-Hispanic” is omitted category. ‘ “Elsewhere in Dade County” is omitted category. * p < .05 ** p < .01 *** p < ,001

Only one factor was associated with an early adjuster meeting and that only weakly: the more damage to the residence, the more likely that an adjuster met with a respondent during the first month after the hurricane. Surprisingly, respondents who lived in the disaster area were no more likely to have met with an adjuster in the first month than respondents who lived elsewhere in Dade County. Race/ethnicity, income, education, and head of household type also made no significant difference.

Four of the factors we considered made an important difference in the timing of the first payment. Three of these are unsurprising: (1) respondents who reported that a member of their household had met with an adjuster at


the home during the first month were five times as likely as other respondents to paid within that month; (2) a disaster zone resident was twice as likely to be paid in the first month after the hurricane as someone who lived elsewhere in Dade County; and ( 3 ) the more damage, the more likely an early payment.48 More problematically, there was also a significant ethnic difference in the timing of the first insurance payment. When we controlled for the other variables we examined, Hispanic respondents were found to be only 60% as likely to receive an insurance payment within the first month as white non-Hispanic re~pondents.4~

When we tested for interaction effects among the significant factors, we found ethnic differences associated with both the location of the home and the timing of the adjuster visit.5o Examining separately those respondents who lived in the disaster zone and those who lived outside the disaster zone, we found that ethnicity was significant only for claims outside the disaster zone. When we controlled for the other factors listed in table 4, we found that Hispanic and non-Hispanic respondents who lived inside the disaster zone were equally likely to receive an insurance payment within the first month. Outside the disaster zone, Hispanic respondents were only 56% as likely as other respondents to have been paid within the first month.

Examining separately those respondents who reported an early adjuster meeting and those who did not, we found that ethnicity was significant only among respondents who reported an early meeting. When we controlled for the other factors listed in table 4, we found that Hispanic and non-Hispanic respondents who did not report meeting with an adjuster at the home during the first month received early insurance payments in equal proportions. But among respondents who did report an adjuster meeting within the first month, Hispanics were only half as likely as other respondents to receive a payment in that month. Table 5 illustrates these interaction effects.

Using Qualititative Research to Explain the Survey Findings

The survey results, by themselves, are confusing. Why were Hispanics the apparent subject of bias in the claims process, and not non-Hispanic blacks or residents of female-headed households? And why did the level of damage and location of the home make a substantial difference in the tim-

48. The odds ratio of 1.29 for the damage variable in table 4 means that one step up the seven-point damage scale increased the likelihood of being paid within the month by nearly 30%. For a description of the damage scale, see the technical appendix. For an explanation of logistic regression and odds ratios, see note 32.

49. The percentages of claimants in each race/ethnicity group who received a payment within 1 month after the hurricane were 42% (white non-Hispanic); 39% (black non-His- panic); and 25% (Hispanic). For an explanation of why the timing measures are dichotomized, see the technical appendix.

50. There was no significant interaction effect between damage and ethnicity.


TABLE 5 Location, TIming of Adjuster Visit, and Ethnicity

Did Ethnicitv Make a Difference?

Location of damaged home: Inside the disaster zone

Outside the disaster zone

Did a member of the household meet with an adjuster at the home during the first month?

No

Yes

Ethnicity was not a significant factor in the timing of the first payment Hispanics were only 60% as likely to receive a payment within the first month

Ethnicity was not a significant factor in the timing of the first payment Hispanics were only 50% as likely to receive a payment within the first month

ing of the first insurance payment but not in the timing of the first adjuster meeting? It was only through the qualitative research that we could explain these results.

According to the adjusters we interviewed, the formal claims adjustment policy was to give priority to those in the disaster zone (which the adjusters called the “war zone”) and to those who suffered greater damage to their home. The insurance companies implemented that policy by establish- ing walk-in claims centers in the disaster zone and by sending field agents into heavily damaged neighborhoods to distribute checks for immediate repairs and living expenses in advance of the usual claim adjustment process. The survey results for the first insurance payments are consistent with this policy (with the important exception of the race/ethnicity disparity that will be addressed below): living in the disaster zone was strongly associated with an early first payment, and the more damage a home suffered, the more likely that a respondent received an early payment.

The survey results for the first adjuster visits, however, are not consistent with this formal policy, except for a weak association between the level of damage to the home and the timing of the first visit. The adjusters reported that, notwithstanding the official policy of targeting the disaster zone, in adjusting claims they often responded to claimants in the order in which the claim was received or in response to pressure from the claimant or the claimant’s insurance agent. Several adjusters reported that they gave priority service to local celebrities and to prestigious addresses.51 These ex- planations suggest that the timing of adjuster visits was affected by the con-

51. Our geographic variable was defined according to preliminary estimates of damage and could not be adapted to distinguish the relative prestige of the address.


tacts and other aspects of social capital that claimants possessed.52 In addition, the adjustment of many claims was delayed because of the difficulty of locating the insured or reaching the property (either because the roads were impassable or road signs were down).53

The adjusters did not describe an explicit claims adjustment policy that would explain the race/ethnicity differences observed in the survey results for the timing of the first insurance payments. Nevertheless, a few adjusters who were told about the survey results suggested that the difference in timing of the first insurance payment may be attributable to a language barrier between Spanish-speaking claimants and the largely non-Spanish-speaking insurance company employees. The interviews and observations suggested an additional explanation for the difference: bias in the exercise of discre tion.

Adjuster Discretion

The interviews and observations revealed that adjusters have substantial discretion in the handling of an insurance claim. While there is both an internal hierarchy and external legal process that stands behind and theo- retically checks the adjuster’s discretion, in the usual instance, that hierarchy is engaged only in the form of a first-level supervisor who (quickly) reviews the written documents in a file. I t is only in the truly extraordinary case that the external legal process is invoked at all, and in few of those instances does the matter reach a court.

In the case of Hurricane Andrew, the Florida Department of Insurance reported that the 636,000 hurricane-related insurance claims produced 17,604 (3%) administrative c0mplaints.~4 This was during a time when the Florida Department of Insurance “800” telephone number was published daily in the newspaper and almost nightly on the evening news, and filing a complaint consisted of returning a simple form obtained by calling the 800 number. Fewer than 3,000 of the complaint claims persisted to the Depart- ment of Insurance’s mediation stage, and the vast majority of those settled.55 From September 1992 (the month after the hurricane) through March 1994, the Dade County Circuit Court kept track of all hurricane-related

52. We are indebted to Terence Halliday for the observation that, by virtue of their relationship to the university and those within it, our survey respondents were comparatively advantaged with regard to social capital.

53. These factors would not have as significant an effect on the timing of the first insurance payment of the first check, because a claimant could go to a walk-in claims center to pick up a check.

54. Florida Department of Insurance Hurricane Andrew Fact Sheet (16 Dec. 1994) (on file with the first author).

55. Florida Department of Insurance Hurricane Andrew Mediation Reports (27 Dec. 1994) (on file with the first author).


lawsuits filed in that court (the primary venue for cases regarding hurricane- related insurance claims). Fewer than 200 of those cases were insurance cases; the trend of insurance cases peaked in February and March 1993 and declined steadily thereafter.s6 Thus, for the overwhelming majority of claimants, the insurance law that mattered was the law-in-action of the insurance adjuster.

As research on other street-level bureaucrats would suggest,57 adjusters exercise their discretion in a manner that favors individuals with certain defining characteristics over individuals without those characteristics or with other “negative” defining characteristics. While few adjusters said that ethnicity was such a characteristic, a set of practices that produced an ethnic bias was observed.

To understand these practices, it is first important to understand the degree to which adjusting an insurance claim is not a mechanical process. As the adjusters reported, and as was observed in the mediations, important aspects of an insurance claim subject to adjuster discretion include:

The order in which a claim is handled The speed with which a claim is handled The level of documentation required to support a claim The payment of additional living expenses, including the determination of whether a home is sufficiently damaged that alternative housing is necessary and, if so, for how long The valuation of damage, including the determination of whether a damaged item can be repaired or must be replaced, the cost of repair or replacement of a damaged item, and the amount of depreciation deducted in those situations in which depreciation is used to limit the value of a loss The degree to which “technical” insurance policy requirements are used to limit insureds’ recovery58

56. The first author reviewed the court’s list and, together with a research assistant, examined the court files of all the insurance cases. While there is some reason to believe that the court’s list of cases is incomplete, the order of magnitude is still informative. The trend line is important because it provides some confidence that a substantial number of the claims that will be litigated have already been filed, notwithstanding the applicable five-year statute of limitations. In February 1993, 21 complaints were filed; in March 1993, 20 complaints; in April 1993, 8 complaints; after that time, the trend was flat or down (data on file with the first author).

57. See, e.g., Handler, “Power” (cited in note 25). 58. Examples of such policy requirements include the requirement that the insured “mit-

igate” damages, that the damage not be the result of a failure to maintain the property, that the cost of rebuilding not include costs of improving the building to meet current building code requirements, that damaged items be replaced within 180 days of the loss, and that the home not be underinsured. There was widespread agreement that insurance adjusters often did not pursue such “technicalities.” As one adjuster put it, “If I and the other adjusters kept to the letter of the policy, the number of complaints would have been at least three times as much.”


In combination, the adjuster’s judgment on these points of discretion largely determines how much, and when, the claimant gets paid. Indeed, one of the most surprising aspects of the mediations, both to the observers and the mediators (none of whom had mediated insurance claims before the hurricane), was the manipulability of the dollar value of a claim, particularly the additional living expense portion. Some of the mediators began privately referring to additional living expense payments as a “slush fund” available to compromise almost any claim, provided the adjuster was willing.

Whether the adjuster was willing depended in significant part on the adjuster’s moral assessment of the claim. In handling claims, one of the ar- chetypal narratives guiding the insurance adjuster is what has been called the story of the immoral ins~red.~9 As one adjuster said,

I don’t want to sound too cynical, but most people, when they see money laying on the ground, will pick it up. And when Joe sees his neighbor getting a new roof or having a tile or two missing, he is going to begin to think, maybe, “You know, this is never going to happen again. I am never going to have another hurricane. I need a new roof.” So, he makes a claim.

As this example might suggest, insurance fraud was a continual theme in our interviews and observations. Three quarters of the adjusters we interviewed articulated some version of immoral insured story, and the subject of fraud surfaced in nearly a third of the mediations we observed. As the interviews and observations reflect, adjusters are continually measuring claims against their expectations about claims and claimants, on the alert for any hint of exaggeration or fraud.

Adjusters readily volunteered that they respond to a claim based, at least in part, on their sense of a claimant’s “situation.” Without prompting, over half the adjusters interviewed mentioned the importance of evaluating whether a claim fits the usual pattern within the insured’s social setting. As one adjuster said, “I look at the car they drive, the other things in the house, the way they carry themselves.” All the adjusters asked to explain how to identify potentially fraudulent claims referred to social attributes. These attributes included the character of the home, possessions, or neigh- borhood, employment status, business or professional background, immigrant status (more on this below), perceived wealth, and what another adjuster called “a life style that indicates a basic honesty.”

59. See Tom Baker, “Constructing the Insurance Relationship: Sales Stories, Claims Stories, and Insurance Contract Damages,” 72 Tex. L. Rev. 1395, 1411 (1994). This story serves much the same function as similar moral evaluations made by social workers and governmental enforcement officers. See Keith Hawkins, “The Use of Legal Discretion: Perspec- tives from Law and Social Science,” in Hawkins, Discretion (cited in note 18); Ross & Thomas, “Housing Code Enforcement” (cited in note 20) (describing how housing code in- spectors distinguish between “bad apples” and “good apples”).


As our interviews and observations reflect, the adjuster’s reaction to a claim is a complex interplay of preconceptions about the claimant’s social attributes, the nature of the claim, and what Erving Goffman would have called the “face work” of the claimant in the interaction.60 In some cases, the adjuster’s initial reaction to the claim is suspicion, and only extraordina- rily effective efforts by a claimant will avoid a reduction in the claim. In other cases, the initial reaction to the claim is supportive, and only extraor- dinarily ineffective efforts (or what some adjusters called “violating the pig rule”) will keep the claim from being paid generously. As one adjuster put it, “How you feel about someone affects how easily you can see their point of view.” How an adjuster feels about a claimant is, at least in part, a function of the preconceptions the adjuster has about people like the claimant and the way those preconceptions are managed in the claim adjustment process.

Preconception, we hardly need to say, is not everything. Claimants can and do gain and lose the trust of their adjusters. Other things being equal, insureds who persuade their adjuster that they are articulate, reasonable, informed, cooperative, and prepared have an easier time with their claim. Specific examples of effective measures observed in the mediations or recal- led by adjusters include:

Contacting the adjuster early and often, but not to the point that the adjuster becomes hostile Carefully and consistently itemizing and documenting the damaged property Obtaining objective evidence of value, such as estimates from contractors, statements from structural engineers, quotes from merchants, etc. Demonstrating a general understanding of the internal organization of an insurance claims organization, with the concomi- tant availability of “appeals” to the adjuster’s supervisor and field level headquarters, and indicating a willingness to in- voke those appeals, especially in situations in which the adjuster’s judgment can be questioned by reference to objective evidence

As with other aspects of cultural and social capital, the ability to do these things is unevenly distributed within the general population.61 Managing the adjuster relationship is not unlike managing relationships with street- level workers in public service agencies, whose partial control over the dis- pensation of benefits gives them some degree of power and whose preconceptions affect the administration of that power. Like those other

60. Erving Goffman, “On Face Work,” in Erving Goffman, Interaction R i d (Garden

61. See Handler, “Power” (cited in note 25). City, N.Y.: Anchor Books, 1967).


encounters, the insurance claims process simultaneously reflects and repro- duces a social order that is permeated by differences that matter.

Discretion, Bias, and Delayed First Checks

Our findings relating to insurance adjuster discretion offer a plausible explanation for the difference between Hispanics and non-Hispanics in the timing of the first insurance payment. In the first month after the hurricane, adjusters and other insurance company personnel at walk-in centers and in the field had discretion to write checks for additional living expenses and immediate repairs. The personnel also had the discretion to require, or not, that the insured provide supporting information as a condition of writing the check. Even in the wake of a hurricane, writing a check with little or no documentation supporting the claimed amount requires a certain amount of trust.

As observed in the mediations, it can be difficult to establish trust across the language and cultural divide that separated at least some Hispanic claimants from the largely non-Hispanic adjusters. While we observed no overt discrimination in the mediations, several adjusters mentioned in interviews a concern that recent immigrants to the United States from Cen- tral or South America were less likely to be “honest” with an insurance company.62 These adjusters said that they would respond with greater suspicion to a claim from someone thought to be a recent immigrant than from someone else.

This concern could easily explain at least part of the aggregate delay among Hispanic respondents in receiving first checks. Adjusters and other insurance company personnel brought to South Florida following the hurricane were unlikely to appreciate the diversity within what is commonly referred to in Miami as the Latin community and, therefore, could easily generalize a concern about recent immigrants well beyond the community of truly recent immigrants. Alternatively, the comments about “recent immigrants” could have been a guarded way of expressing a more general concern, much as “urban” is sometimes a code for “African American.”

Other adjusters and some mediators referred to a “language difference” that made it difficult for some adjusters to communicate with Hispanic claimants. While this did not appear to reflect a conscious bias, the “difference” was more complex than a simple facility with the English language. The survey results illustrate this point. The university employees who responded to our survey work in an environment in which English is essential,

62. We do not endorse these views; we simply report them. Like xenophobia in the political arena, concern about the fraudulent tendencies of recent immigrants has a long his- tory in the insurance field. See Tom Baker, “On the Genealogy of Moral Hazard,” 75 Tex. L. Rev. (forthcoming 1996).


as evidenced by their ability to respond to a 24-page survey that was prepared entirely in English. Yet, notwithstanding this facility with English, the Hispanic respondents received their payments later than non-Hispanic respondents.

By “language difference,” we understand the adjusters to include the cultural difference and consequent lack of ease observed even in some mediations in which Hispanic claimants were fully conversant in English. For example, our observers attended two mediations in which an impasse between a Hispanic claimant and an Anglo adjuster was broken only when the mediator gained the trust of the claimants (who spoke competent Eng- lish) by addressing them in Spanish.

As the adjusters attending the mediations acknowledged, they were the most experienced and the best at dealing with the public that their companies had to offer. For this reason, we conclude that any problems observed and reported in the mediation center were magnified in the field. Indeed, one claimant opened his mediation by compiaining that his first adjuster (not the adjuster at the mediation) told him, “You talk English like a Puerto Rican,” and then tore up his receipts and threatened to bring a fraud action against him.

Further analysis of the survey data provided additional support for our conclusion that the Hispanic difference in the timing of the first payment is attributable to a lack of trust in the handling of claims. First, when we used a logistic regression analysis to look at whether a check was received within the first three months after the hurricane (rather than the first month as reported in table 4), Hispanic ethnicity was no longer significant. This means that Hispanic respondents who made claims were paid in the same ratio as non-Hispanic respondents, only later. In other words, the Hispanic difference is in when, not if, respondents were paid. This result is consistent with our explanation that insurance company personnel required additional verification from Hispanic respondents.

Second, when we used a logistic regression analysis to look separately at respondents living in the disaster zone and at those living outside the disaster zone, there was an important difference. Outside the disaster zone, Hispanic ethnicity was significant; inside it was not. This strongly supports our conclusion that the Hispanic difference is attributable to bias in the exercise of discretion. “Trust” is much less implicated in the context of claims within the disaster zone; for such claims, the location of the insured property alone provides substantial verification that insured property was damaged.

Finally, when we used a logistic regression analysis to look separately at respondents from households who had met with an adjuster at the home during the first month and respondents from households who did not, there was also an important difference. Hispanic ethnicity was significant only if


a member of the household had met with an adjuster. Indeed, within that group, Hispanics were only half as likely as non-Hispanics to receive a payment within the first month. This finding is consistent with social-psycho- logical research showing that face-to-face contact activates stereotypes,63 and it strongly confirms our conclusion that the Hispanic “difference” is attributable to bias in the exercise of adjuster discretion.

While significant, this one relatively hard conclusion should not over- shadow the softer findings of our investigation of insurance law-in-action. The finding that adjusters have substantial discretion over how much and when individual claimants get paid confirms Ross’s pioneering efforts to identify insurance adjusters as important objects of study.64 Where we have improved on prior research is by asking, and beginning to answer, questions about the distributional consequences of insurance adjuster discretion. Tim- ing measures are only a beginning.

Discretion and Racial and Gender Bias

One “nonfinding” from the survey bears comment: the lack of signifi- cance of the black non-Hispanic and female-headed household variables in the claims-payment timing analysis. Notwithstanding this result, aspects of the qualitative research suggested that there may be racial and gender bias in the claims process. Several informants suggested that female or black claimants would be disadvantaged in the insurance claim process. One female former adjuster reported that some adjusters take advantage of women. Several female claimants suggested women would obtain smaller payments because they have less experience exercising the skills needed to obtain a good result in the insurance claim process. One mediator stated that adjusters routinely “low-balled” black claimants.65

While such suggestions are hardly conclusive proof of bias, the discretion exercised by adjusters would allow ample room for bias. The survey findings should not be interpreted as meaning that these informants were mistaken. Indeed, if the informants are right, the race and gender difference would be manifested in smaller payments, not later ones. Our survey could not measure that difference; all the survey could measure was the timing of the first payment and adjuster visit. Timing measures have the important virtues of objective measurement and easy comparison, but they certainly do

63. See Susan T. Fiske & Shelley E. Taylor, Social Cognition 119-24 & 145 (2d ed. Reading, Mass.: Addison-Wesley Pub. Co., 1991). We are grateful to Karyl Kinsey for sug- gesting the contact salience hypothesis that led us to test the interaction between ethnicity and adjuster visits.

64. Ross, Setded Out of Court (cited in note 9). 65. For additional anecdotal reports of racial, ethnic, and gender bias in the insurance

claims process, see Michelle Saadi, Claim It Yourself: The Accident Victim’s Guide to Persond Injury Claims 17-18, 50-60 (New York: Pharos Books, 1987).


not tell the whole story of the insurance claims process. The regulatory response we advocate in the next section could move us in that direction and provide a basis for testing our informants’ claims of racial and gender bias.

IV. IMPLICATIONS FOR INSURANCE REGULATION

This study examined two aspects of the distributional consequences of relying on the private home insurance market as the primary residential safety net: who has insurance and who gets the most benefit from that insurance. Our results show that the distribution of insurance is weighted toward the relatively advantaged and that, as a result, disaster increases inequality. In addition, our survey findings demonstrate that insurance adjuster discretion has systematic distributional effects. The qualitative research on the claims process suggests that these distributional effects are likely to be more far reaching than the survey could measure. Both sets of findings have important implications for the regulation of the insurance market.

The Distribution of Insurance

As the survey shows, inequality in the distribution of insurance primar- ily affects renters and condominium owners, not people who own houses. While there are inequalities in the distribution of insurance among people who own houses, homeowners overwhelmingly are insured. For example, over 91% of the black non-Hispanic respondents who owned houses were insured. In stark contrast, only 20% of black non-Hispanic renters were insured.

The reason for the difference is simple, and we did not need a survey to discover it. For most people, having insurance is not about being responsible but rather about owning a house and having a mortgage. Most people cannot buy a house without a mortgage, and conventional mortgages in effect come with homeowners’ insurance attached. We stress homeowners’ insurance for a reason. Homeowners’ insurance protects more than simply the structure of the house. It also protects the contents of the house, and it provides money for the additional living expenses that accompany a disaster. It is that coverage that most renters and a large percentage of condominium owners lack.

Given the higher average income, age, and education of the homeowner respondents as compared with the renter respondents, and given that homeowners have far more property to lose than renters, it is a near cer- tainty that, even without the mortgage compulsion, homeowners would be insured in greater proportion than renters. Nevertheless, as our survey anal-


ysis shows, the explanatory power of home ownership swamps that of income, age, education, and the other factors we examined. Further support for this (obvious) conclusion comes from our claimant interviews. When we asked why the informant purchased insurance, by far the most common response was a look that said, in effect, “What a dumb question!” and then a patient explanation that it is impossible to buy a house without buying insurance.

While it is possible to construct an explanation that this result reflects consumer preference, that “preference” undeniably is shaped by legal and institutional forces. The legal forces include the various federal regulations requiring that home mortgage documents contain covenants requiring property insurance and the legal institutions that back up mortgage holders’ enforcement of those provisions36 The institutional force is twofold: the interest of lenders in protecting their collateral and, just as important, insurance companies’ pricing practices. In combination with the federal requirement, the interest of lenders means that houses are insured. The pricing practices of insurance companies-under which the broader-coverage homeowners’ insurance is less expensive than the narrower-coverage dwelling protection insurance-means that the insurance protects not only the structure of the home but also the contents and the additional living expenses that result from damage to the home.

Because large numbers of renters and condominium owners do not purchase insurance to protect their belongings and to provide for additional living expenses, there remains a significant need for grant and loan disaster relief programs, especially for lower-income renters. While economic theory might suggest that the current availability of disaster relief may play a role in the decision not to insure,67 widely acknowledged imperfections in the insurance market, together with the social dislocation that would result if large numbers of people lacked the financial means to recover from a disaster, counsel against eliminating those programs on the basis of theory.

The more responsible course would be to develop market-based solu- tions to improve the penetration of renters’ and condominium unit owners’ insurance. The survey results suggest that the homeowners’ insurance experience presents a useful model. That experience teaches an important les- son: consumer self-interest and insurance marketing, alone, are not enough to achieve widespread insurance coverage. After all, if they were enough, the institutional and legal arrangements compelling the purchase of homeowners’ insurance would not have arisen.

There are similar institutional arrangements for renters and condominium owners that could be harnessed to obtain similar results. Banks induce

66. See supra note 28 and accompanying text. 67. See Louis Kaplow, “Incentives and Government Relief for Risk,” 4 J. Risk B Uncer-

tainty 167 (1991).


their borrowers to insure because that insurance protects the banks’ interest. If landlords and Condominium associations had a similar interest in preserv- ing their tenants’ and members’ property, similar results would follow. The most straightforward way to create that interest would be to make landlords and condominium associations liable for the destruction of their tenants’ and members’ property.68 Obviously, the nature and limits of that liability would deserve far greater attention than we can provide here, but the concept would be administratively easy to accomplish. Once a state statute created the requisite liability, insurance companies would offer standard endorsements to landlord and condominium association policies, and landlords and condominium associations would induce tenants and members to purchase insurance directly from an insurance company (perhaps by providing rent or management fee rebates upon the presentation of proof of insurance) .69 Insurance companies would then create a mechanism for adjusting the premium paid by the landlord or condominium association to reflect their success in inducing tenants or members to obtain insurance.

This market-structuring solution would reduce the race/ethnicity and income based disparities in the incidence of home insurance, with minimal regulatory apparatus.70 Admittedly, it would raise the cost of housing, perhaps more so at the lower end of the income spectrum, and, to the extent that this private safety net replaced disaster relief (which is funded by federal income tax revenues), this change could be seen as regressive. Yet, the increased cost would buy real home insurance, which provides more extensive, and more broadly applicable, benefits than federal disaster relief.’’

While some might object to the mandatory nature of this approach, we already live in a world in which there is mandatory home insurance: ( 1 ) the private, good-quality, broad-coverage home insurance that is mandated by banks and banking regulation for the relatively advantaged and (2) the public, poor-quality, narrow-coverage home insurance that is mandated for eve-

68. A more politically palatable, but slightly more complicated, approach might be to mandate that landlords and condominium associations purchase insurance of a given sort protecting their tenants’ or members’ property and to provide that the sanction for the failure to do so would be liability for the destruction of that property.

69. The institutional pressure to insure could be increased if the liability were made a lien on the property. This would induce lenders to monitor landlords and condominium associations. That lenders are capable of such monitoring is apparent in the homeowner context.

70. Because of the problem of insolvent landlords and condominium associations, however, even this solution would not eliminate the need for disaster grants and loans. The lien suggestion in note 69 would reduce this solvency concern.

71. For a theoretical analysis of why mandatory insurance is superior to government relief, see Kaplow, 4 J. Risk B Uncertainty 167. It should be noted that Kaplow addresses a situation in which the benefits provided by compulsory insurance are the same as the benefits provided by relief. Because home insurance provides more extensive benefits in a much wider range of circumstances than does federal disaster relief, mandating home insurance would, therefore, increase the total social resources devoted to protection against property loss. It would do so, however, on behalf of those who now need that protection most.


ryone else by the federal government in the form of taxpayer-financed disaster relief. Whether good-quality, broad-coverage home insurance should be mandated for renters and condominium owners requires more investigation into the costs involved and a normative judgment about such a pater- nalistic approach. Nevertheless, no voluntary approach is likely to reduce the distributional consequences of the decision to rely on the private insurance market as the primary protection against individual and collective disaster.

It is important to remember that even if our solution were adopted, there would remain the problem of bias in the insurance market, as manifested by the lower incidence of home insurance among black non-Hispanic homeowners. Our research confirms that the problem exists, but does not suggest a solution, other than the relatively weak suggestion that the difference is traceable to the home financing and insurance market rather than to consumer preference. Making a meaningful contribution to understanding that problem would require a very different research project, one that ought to be attem~ted.7~

Supervision of the Claims Process

Historically, legal regulation of the insurance claims process was the province of common law judges, who used contract law on a case-by-case basis to determine whether insurance companies had lived up to the insurance bargain.73 With the increasing size of state departments of insurance, state regulators have taken a more active In recent years, this role has been quite active in the case of natural disasters, as illustrated by the response of the Florida Department of Insurance to Hurricane Andrew and that of the California Department of Insurance to the Oakland firestorm in 1991. As the results of even our crude claims performance measures demonstrate, however, the insurance claims process has systematic distributional effects that will elude the case-by-case approach of courts and state insurance regulators. Addressing these effects would take a new approach to reg- ulating the claims end of the insurance relationship.

72. For a recent effort to address the related problem of discrimination in the lending market, see Peter P. Swire, “The Persistent Problem of Lending Discrimination,” 73 Tex. L. Rev. 787 (1995).

73. See Spencer L. Kimball, “The Role of the Court in the Development of Insurance Law,” 1957 Wis. L. Rev. 520.

74. For an early description of this aspect of insurance department activity, as well as a prediction that it would increase, see Edwin W. Patterson, The Insurance Commissioner in the United States 283-307 (Cambridge: Harvard University Press, 1927). For a more recent (and pessimistic) study, see William Whitford & Spencer Kimball, “Why Process Consumer Com- plaints? A Case Study of the Office of the Commissioner in Wisconsin,” 1974 Wir. L. Rev. 639.


The necessary first step, which is all that we advocate here, is to obtain more complete information about the distributional effects of the insurance claims process. Through the insurance companies they regulate, state insurance departments have access to more comprehensive data than we had available for our survey. For each claim, insurance companies maintain a record of the insured’s name, the policy limits, the exact address of the damaged property, a description of the damage for which the claim is made, the date and amount of all payments, the identity of the adjuster(s) who handled the claim, and the dates and contents of all communications with the insured, among other information. Much of this information exists in com- puter-readable form. With these data, a state insurance department could develop claims performance measures that could be used to map the distributional effects of the insurance claims process. Because the available data include the size as well as the timing of insurance payments, the measures could be used to investigate whether the assertions of gender and racial bias made by some of our informants can be supported.75 The measures would also permit comparison among insurance companies.76

CONCLUSION

This study has shown that the choice to rely on private home insurance as the principal disaster protection safety net has significant distributional consequences. Private home insurance disproportionately benefits the relatively advantaged, who are more likely to be insured and who fare better in the insurance claims process. This means that disaster, whether individual or collective, increases the economic inequality existing in our society.

The reforms suggested at the conclusion of our analysis represent one way to begin to address the role of home insurance institutions in reproduc-

75. At least some insurance companies maintain detailed demographic information about their policyholders. For companies that do not, the insurance department could select a sample of claimants and conduct a telephone survey to obtain the necessary information. Alternatively, the insured’s name can be used for distinguishing gender and ethnic identity, and policy limits can be used as a proxy for income. Together with census information, address can also be used to identify demographic characteristics. While such indicators would be far from perfect, they could be used for the large-scale mapping and screening purposes we envision.

76. In addition to educating regulators about systemic effects of insurance adjuster discretion, claims performance measures could serve a more general purpose. Most personal-lines insurance advertising today consists of idealized “sales stories” that provide consumers with little basis for distinguishing among insurers. See Baker, 72 Tex. L. Rev. 1395, 1403-6 (cited in note 59). Claims performance measures would permit consumers to go beyond both the sales stories and the diffuse reputational information now available from intermediaries such as insurance agents, realtors and mortgage brokers. While not a panacea, the measures would give consumers an objective basis to use, in combination with price, in deciding where to invest their premium dollars.


ing inequality. Whether these reforms are adopted or not, it is vitally important in this era of reduced expectations about the capacity of government that we focus on the insurance market. For the insurance market is the arena in which the only real safety net, other than the narrowly targeted Social Security system, is constructed. Understanding-and expanding- that safety net presents one of the more significant challenges before us.

TECHNICAL APPENDIX

A. Survey Methods

1 . The Variables

This study analyzes three dependent variables from the survey question- naire. Because the three dependent variables were dichotomous, we used logistic regression to estimate each of the equations.

Who has insurance. The first dependent variable indicated whether respondents had residential insurance prior to the hurricane. This variable was binary and coded 1 for insured, 0 for not insured. Independent variables included in this equation were race/ethnicity, income, age, female-headed household, education, home ownership, age of home, type of residence, and area of residence before the hurricane.

Race/ethnicity was measured with four dummy variables: black non-His- panic, white non-Hispanic, Hispanic, and other.77 The omitted group used for comparison was white non-Hispanic. Of the respondents, 4% did not report race/ethnicity. Rather than exclude these respondents through listwise deletion, we created a dummy variable which indicated whether respondents had not answered the race/ethnicity question (coded 1 for “no response,” 0 for “responded”). A significant coefficient for this variable would suggest that respondents who did not report race/ethnicity differed significantly, in terms of the dependent variable, from those who did respond to the question.

Income was measured with a nine-category rank-ordinal scale: “less than $10,000,’’ “$10,000-$20,000,~~ “$20,001-$35,000,’’ and from there by $15,000 increments to “more than $1 10,000.” Because of the large number of categories, we treated this variable as interval. (We did not simply ask for family income because “fill-in-the-blank” income questions present greater missing data problems than “check-off” income questions.) Education was measured by a rank-ordinal scale with eight categories. This variable was also treated as interval and ranged from “less than 12 years” to a doctorate (or equivalent) degree. The variable age was continuous (by year). Female-headed household was measured by whether the respondent was a female with at least one child in a

77. The survey asked the following race/ethnicity question: “Which best describes you? (MARK ONE ANSWER ONLY).” The options were (1) White, non-Hispanic; (2) Black, non-Hispanic; ( 3 ) Asian or Pacific Islander; (4) Other (please specify); (5) Hispanic, regardless of race.


household without any adult male; it was coded 1 for female-headed household (else = 0).

Home ownership was binary; respondents who owned their homes were coded 1 (else = 0). Age of home was an interval variable that was measured in years. Type of residence included five dummy categories: house, apartment, townhouse, trailer, and other type of residence. Each dummy variable was coded 1 for the presence of the trait (else = 0). Finally, area of residence included three dummy categories (coded 1, 0): disaster zone (the area in Dade County that experienced the most hurricane damage) , other residential areas in Dade County, and Broward County (the county lying immediately north of Dade County). The few respondents who did not live in Dade or Broward County (N = 49) were excluded from the analysis.

Insurance claims. Because of our interest in insurance claim processing, we then selected the subsample of respondents who had filed an insurance claim as a result of the hurricane to examine two dependent variables: (1) whether a member of the respondent’s household had met with an adjuster at the respondent’s home within 1 month of the hurricane, and (2) whether a claim payment had been received within 1 month of the hurricane. These dependent variables were selected because they provide an objective basis for comparing the claims treatment of the individuals surveyed and because they measure a significant aspect of the claims process. The variables were dichotomized and analyzed using a logistic regression analysis because the survey collected timing information using a 4-category interval scale that could not be used as the dependent variable in a linear regression analysis.

Both dependent variables were binary, coded 1 for the presence of the trait (else = 0). We used the same independent variables as in the first equation (race/ethnicity, income, education, female-headed household, and area of residence before the hurricane), together with one additional variable: degree of damage to the residence. This final independent variable was an interval scale consisting of 7 categories, ranging from 0 (no damage) to 6 (roof and/or some exterior walls destroyed). For the analysis of the timing of the first payment, we also used the adjuster meeting variable as an additional independent variable.

2 . Representativeness of Survey Respondents

The two variables with which we were able to compare the survey respondents with the population surveyed were age and gender. The university does not maintain other information about its employees in a manner that would permit comparison with our sample respondents. The age and gender represen- tation of the respondents was nearly identical to that of the entire population of university employees. The average age of the university employees at the time of the survey was 42 years; the average age of our respondents was 43 years. The percentage of university employees who were female was 59.9; the percentage of our respondents who were female was 59.8.


B. Qualitative Research Methods

1. Mediation Observations

During the winter following Hurricane Andrew, the Florida Department of Insurance set up a mediation center in Homestead, Florida, to handle disputed residential insurance claims. The first author and four law student research assistants observed a total of 35 mediations on 10 days during the summer of 1993. Mediations lasted from 15 minutes to 8 hours, with 1 to 1.5 hours being the norm. Field notes were taken during the mediation, and typed notes were prepared at the end of the day.

The mediations were conducted in English. There was a Spanish-language translator present for those claimants who needed one, and several of the mediators spoke Spanish. Few of the adjusters observed spoke Spanish, and those who did used English almost exclusively. Three of the observers (including the first author, who attended over half the mediations observed) spoke Spanish and were therefore able to listen to conversations conducted in Spanish.

2. Adjuster lnterviews

Twenty insurance adjusters were interviewed during 1993 and 1994, prin- cipally by the first author, with the assistance of law student research assistants. Fifteen of the interviews were conducted at the mediation center. Typically, adjusters came to the center to participate in more than one mediation. The waiting time before the first mediation and between mediations presented an opportunity for interviews. Field notes were taken during the interviews, and typed field notes were prepared later in the day. Three of the interviews were conducted in Coral Gables, Florida, one in Miami, and one was conducted by telephone. One adjuster, who was not interviewed, provided important information by e-mail.

The adjuster interviews were semistructured. Interview topics included hurricane claims the adjusters were then handling, other hurricane claims the adjuster had handled, the hurricane claim process, and differences between hurricane claims and the adjusters’ usual claims. The goal was to understand the insurance claim process from the perspective of the adjuster.

There is substantial reason to believe that the adjusters interviewed were not representative of the population of adjusters who worked on Hurricane An- drew claims. The adjusters interviewed were largely in-house adjusters, employed directly by the insurance company they represented, in contrast to the large number of contract adjusters who handled claims in the first few months after the storm. The adjusters interviewed reported that they were more experienced than the norm and that they were regarded as “successful” within their organizations. Indeed, in most of the mediated cases, less experienced adjusters had initially handled the claim. While this conclusion is admittedly impression- istic, we believe that the adjusters interviewed more closely represented their employers’ ideal rather than the norm.


3. Mediation Interviews

During five visits to the Mediation Center in June and July 1993, the first author briefly interviewed mediators present at the center, administrative personnel stationed at the center, and the State of Florida attorneys who rotated through the center to assist in the mediation process. During May and June 1994, a law student research assistant under the direction of the first author interviewed the ten mediators identified by the organization responsible for scheduling the mediations as having handled the largest number of mediations. These ten mediators reported handling anywhere from 25 to 100 mediations each, representing a total of about 450 to 500 sessions, or 25% of the about 2,000 claims mediated at the center.

As with the adjuster interviews, all mediation interviews were semistructured. The interviews addressed the mediators’ and staff’s recollections of specific mediations, their general impressions of the various approaches to insurance claims taken by adjusters and claimants, and the pattern of issues and problems that arose during the course of the mediations. The interviewers also probed for the role of claimants’ social attributes in the claims mediated. Field notes were taken during the interviews, and typed notes were prepared at the end of the day.

4. Claimant Interviews

About 40 home insurance claimants were interviewed by the first author and four law student research assistants during the spring and summer of 1993. The interviews were semistructured; they addressed the claimants’ experiences purchasing insurance, prior insurance claims, and the Hurricane Andrew claim process. All but a few of the interviews were taped and transcribed. Field notes were taken during the remainder.

5. Miscellaneous

The first author (who teaches insurance law) attended public meetings, advised consumer groups, consulted with Florida Department of Insurance offi- cials and with attorneys handling insurance claims, and, together with a research assistant, reviewed the files of all Dade County Circuit Court cases identified as Hurricane Andrew insurance cases. These aspects of the research were not the direct source of any of the findings reported in this article, but they greatly assisted in gaining the confidence of the adjusters and mediators.

Documents

Whose Safety Net? Home Insurance and Inequality