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,_0,,", '....--' ~^") N .....1 I-'" c..o CHAl'l'Jili m MUNICIPAL DAMAGE ESTIMATES THE CALIFORNIA INVESTIGATION It has been recognized for some time that variations in the chemical constituents of water may induce differences in corrosion rates, thereby affec- ting the lifetimes of household water conveyance systems as well as household appliances using water. In this study, an attempt was made to measure economic losses associated with various salinity levels in household water (Appendix 4). Losses were measured for galvanized wastewater pipes, galva. nized water pipes, brass faucets, dishwashers, washing machines, and garbage disposals. A statisti. cal analysis was undertaken to compare estimated mean lifetimes for households in two locations in tbe Los Angeles area of California. Proeedure Two municipal locations in the Los Angeles area, San Fernando Valley and Costa Mesa- Newport Beach, were divided according to socio.economic units based on differences in median home value, mediaD contract rent, number of persons per household, age of structure, etc. A third area, Long Beach, was also included in portions of the analysis. Plumbing contractors serving each ofthese areas for at least 12 years were also contacted along with local appliance dealers. This survey was designed to provide a distribution of lifetime estimates by type of plumbing fixtures or appliances. A regression analysis exami- ning the relationship between estimated lifetime, total dissolved solids (TDS), and the socio.economic variable was conducted. A Conceptual Model There are basically two approaches to analyzing consumer or household decision-making with respect to water quality. One is to assume that sufficient low-cost information is available to home buyers such that preferred locations, those with the higher water quality, are valued more highly by consumers. Another assumption is that information costs are relatively high and water quality characteristics are considered insignificant to the home buyers when compared with other locational considerations (travel time to work, depreciation rates, socio.economic attributes of the neighborhood, etc.). Since the aggregate cost of water softening devices, bottled water, acid rinses for swimming pools, additional detergents, and other direct consu. mer expenditures for reducing the effect of poor water quality are typically less than 2.3 percent of income, it would appear more realistic to presume that information costs on water quality exceed the expected benefits of such information. It was assumed that the home buyer makes his purchase decision independent of variations in water quality except for an estimate of the corrosion of faucets and pipes. and perhaps a query on the age and condition of appliances. Once location is selected, then the consumer considers combinations of defensive expen- ditures designed to achieve a desired level of water quality. Many of these defensive expenditures might be partially or completely capitalized into property values. Defensive expenditures undertaken by the indi. vidual household would partially reflect economic losses associated with direct physical damages or loss of palatability due to poorer water quality. In consequence, it was anticipated that actual marginal damages (WLD) would exceed measured physical damages (WLW), but were either greater or less than the losses capitalized in property values. That is, WLp ;. WLD> WLW When the quality of water delivered to the household could not be altered, it was anticipated that the consumer would then make decisions designed to achieve suitable water quality through various water use activities. Tbose decisions included the purchase and use of a water softener, bottled water purchases, increased lawn and shrub watering, etc. Since the household cannot directly purchase water of varying quality, a demand function is not observable. The approach taken in this study was to estimate physical damages in terms of expected lifetimes and assume that the household would be willing to pay up to the economic value of those physical damages to avoid them. Clearly, this estimate does not consider how the household might, acting individually. avoid some or all of the consequences of poor water quality. 19