Predicting Frequency of Problems Experienced By Owners of Used Cars: a Statistical Analysis of Six Years of Consumer Reports' Survey Data For 1979 Model Cars


Monroe Friedman (1987) ,"Predicting Frequency of Problems Experienced By Owners of Used Cars: a Statistical Analysis of Six Years of Consumer Reports' Survey Data For 1979 Model Cars", in NA - Advances in Consumer Research Volume 14, eds. Melanie Wallendorf and Paul Anderson, Provo, UT : Association for Consumer Research, Pages: 571.

Advances in Consumer Research Volume 14, 1987      Page 571


Monroe Friedman, Eastern Michigan University

Every year millions of consumers find it necessary to buy used automobiles with little reliable information to help them make this important purchase decision. The one source of information which is often cited as an exception to this generalization is the monthly magazines published by consumer associations in many nations of the world, such as Consumer Reports, the American publication of the non-profit, consumer testing organization, Consumers Union. Each year in the April issue of this magazine detailed summary information is presented relating to serious problems (i.e., problems requiring major repairs) which owners of major makes and models of automobiles report they have experienced in the previous year.

The purpose of this research study is to empirically assess the usefulness of this information to consumers interested in the purchase of used automobiles. More specifically, the study attempts to determine the predictive validity of the information which consists. technically speaking, of aggregate frequency data yielded by Consumers Reports' annual surveys of problems experienced by owners of used cars.

Bivariate and multivariate correlational techniques were used to analyze the data of sis annual surveys for 62 makes and models of 1979 cars. The data reports owner problems experienced in 17 individual categories as well as an overall category.

The findings indicate that each year's reported frequencies of problems are highly predictive of next year's both for the overall and individual categories. Predictability was found to differ significantly by individual problem category and by the recency of the survey data.

Should additional research confirm the study's findings for the 1979 model cars, it would sees that consumer educators would have a strong empirical basis for recommending that prospective purchasers of used cars employ Consumer Reports' used car problem data as a positive predictor of future problems. These consumers should be cautioned, however, that a) all problem areas are not likely to be equally predictable, and b) for a car of a given model year, the more years it is owned and used, the more useful is the survey information derived from it likely to be in predicting next year's problems.

(The author would like to thank Eastern Michigan University for funds to support this study and three students (Leslie Braden, Alice Mack and Tammala Woodrum) for their assistance with the data analysis.)



Monroe Friedman, Eastern Michigan University


NA - Advances in Consumer Research Volume 14 | 1987

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