The Affordability of Homeowners Insurance: Study Proposal And Planned Preliminary Results



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The Affordability of Homeowners Insurance: Study Proposal And Planned Preliminary Results Mark V. Pauly The Wharton School, University of Pennsylvania mpauly@wharton.upenn.edu September 2009 Risk Management and Decision Processes Center The Wharton School, University of Pennsylvania 3730 Walnut Street, Jon M. Huntsman Hall, Suite 500 Philadelphia, PA 19104 USA Phone: 215-898-4589 Fax: 215-573-2130 http://opim.wharton.upenn.edu/risk/

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Introduction: THE AFFORDABILITY OF HOMEOWNERS INSURANCE: STUDY PROPOSAL AND PLANNED PRELIMINARY RESULTS One of the key policy issues is whether consumers can afford the premiums insurers wish to charge for homeowners insurance. Problems arise both about the level of the premium the premium is too high to be affordable and about changes in the premium people cannot afford to pay for an increase in their insurance premiums. Previous work at the Wharton Risk Center documented the characteristics of households that did or did not choose to have homeowners insurance (especially in the setting in which there was no mortgage on the property about 15% of all owner occupied homes), and how high premia were in different cities relative to household income and wealth. Ongoing work is extending this analysis in two directions. First, it explores what other levels of household spending accompany unusually high or low premiums relative to income. On the one hand, it would be interesting to know what households charged a high premium (with or without a mortgage) reduce in order to cover the premium (compared to households charged lower premiums). That is, we want to know what is negatively related. Does the high premium displace spending that might be regarded as discretionary (e.g., entertainment) or that is regarded as necessary (e.g., health insurance)? On the other hand, what categories of spending potentially related to homeowners insurance tend to vary positively with insurance premiums? Are high premiums often accompanied by high property taxes or high mortgage payments? If so, it would probably be more correct to say that housing is unaffordable, and not single out insurance premiums as a unique problem. In short, examining the relationship between premiums and other items of consumption spending may shed light on both the effects of high or low premiums and on public policy that might affect those premiums. This investigation is part of a larger effort to look at the issue of affordability as a whole. There is no technical definition, no convenient formula, that would define afford for any spending item of concern to public policy. (The affordability of plasma TVs is not an issue, though the affordability of PCs is.) Ultimately it is a value judgment, and primarily a social value judgment. If we say that we think that household X owning a particular home with particular income and assets cannot afford homeowners insurance, we are judging that the amount of income left over after paying such a premium is in our opinion inadequate or unfair. Thus the question of what else might be bought, and is or is not bought, as a function of variation in the premium, comes to the fore. If what is left over is regarded as inadequate, one clear and direct solution would be to provide the household with some kind of targeted credits for homeowners insurance. However, this is not the only, or necessarily the best solution, depending on exactly what society s objectives are. For example, rather than take as a given that the household should 1

stay in a house it cannot afford, a program to move it to decent but lower cost housing might be preferable. How much weight to give to consumer preferences for housing I must stay in this house that has been in the family for years even though it is not riskier and/or more costly is important. Nor are value judgments the only things that matter. Our earlier work showed that many households that chose to go without insurance would have had enough income left over for a good standard of living; affordability as judged by others may not explain actual behavior. This is the central dilemma of public policy: some people, for a variety of reasons, do not choose to protect themselves and their property against some risk. Should the risky event then occur, their adverse situation tugs at the sensibilities of their fellow citizens. But if all imprudent households are caught by a safety net, it is much less rational to be prudent. Subsidies alone are not enough; penalties are needed too, and probably some examples of risk-taking with harm as the consequence, all to avoid moral hazard generated by full social insurance or social protection. Our goal is to assemble as much information as we can on both insurance spending and other spending, propose several different standards of social affordability, simulate the kinds of credits that might be needed to meet each of those standards, and further explore alternative social policies that best balance concerns of other homeowners (about their premiums and their taxes) as they relate to social concerns about homeowners premiums. Prior work and modifications. There has been some prior work analyzing actual spending patterns that is intended to shed light on the question of affordability (though with no pretense of generating a definitive answer to a subjective question). In particular, Helen Levy and Thomas DeLiere looked at the impact of having or not having health insurance on households spending on other things. They found that spending on health insurance displaced spending on housing, transportation, and cigarettes and alcohol. The interpretation of this kind of result, it should be clear, is not immediately apparent: one would at a minimum need to know why these other categories shrunk (or why they were higher for the uninsured) and then, based partly on that information, decide whether the fall in spending was troublesome. Probably most people (including Levy and Deleire) would not have minded the fall in spending on vices (though the dollar amount was small there), but the spending on transportation might or might not be troublesome: did buying insurance mean not getting a new car, or did it mean not being able to take the job at the end of a costly commute? And they speculate that the high spending on housing comes not from lavish digs but from living in areas where the cost of housing is high, and so the high spending on this necessity is no fault of the uninsured household. In their study, they did not have a measure of the dollar cost of health insurance, so they could only compare people with and without coverage. The great bulk of homeowners have coverage, but we have measures of the dollar cost of premiums that we will be able to use. We will divide 2

households into those with high (above median or higher) levels of spending on premiums, and compare their levels and proportions of spending on other items with those with low premiums. This will describe what high premiums displace. Preliminary specifications. Most of our early work will be descriptive. In the simplest version we will look at lower income homeowners and see what effect high premiums have on other spending. In a second version we will further subdivide the data by the value of the house (since houses worth more will, for that reason, generally have higher premiums), and again examine what is displaced. For purposes of comparison, we will perform the same exercise for higher income households. Further work will control for other household characteristics, such as family size, age of homeowner, and location through the use of multiple regression. While this approach is suitable for description, it does not take into account the possible reasons for high spending on premiums (and on other categories of consumption spending). The most general economic model would hypothesize that spending should depend on income, the prices of various goods (including the premium per dollar of coverage for homeowners insurance), and measures of household characteristics and preferences (such as spending on other kinds of insurances). Such price measures should help us identify the causal relationship between high premiums and other spending. That is, we will be able to say how other spending varies when total premiums are high because the relative price of insurance is high. This more refined result may the one most relevant to policy. Using prices (rather than total spending) to control for the other spending categories may also be desirable. Implications and interpretation. In each of the analyses, we will be able to see what categories of spending people choose to reduce when their homeowners premiums are unusually high. Once this information is available, it may be possible to make a more informed though still subjective judgment about which kinds of premium increases at which household income levels cut other spending below socially acceptable norms. 3