equivalences may be overestimated. Using a national sample of the United States, Goodman and Ittner (1992) explore the accuracy of owner estimates of house values relative to the sales prices of the same properties. They find that the median homeowner in the mid-1980s overvalued the home by about 6 percent. Garner and Short (2001) find that housing costs based on self-reported rental equivalence resulted in higher estimates (almost 15 percent) than those based on a hedonic model. Garner, Short, and Kogan (2006) state that the median reported rental equivalence is higher in the U.S. Consumer Expenditure Survey than in estimates based on the same data using the hedonic model, the rent-to-value model, or the payment approach. The way the information on selfassessed rental values is elicited in surveys may also matter in explaining the inaccuracy of homeowners. Phrasing the question to homeowners as “How much would you receive as a rent if you were to lend your apartment?” as opposed to “How much would you pay if you were to rent the dwelling you are currently living in?” might be one way to mitigate self-assessment bias because of misreporting. In fact, the theoretical and experimental literature on the difference between willingness to accept and willingness to pay for the same good concludes that measures of the former are usually superior to measures of the latter (Fehr, Hakimov, and Kübler 2015; Hanemann 1991; Tunçel and Hammit 2014).

Even if homeowners were able to provide accurate estimates of the rental market values of their dwellings, a comparison of average values, either unconditional or conditional on a set of observable characteristics of dwellings, might lead to incorrect inferences. In countries in which rental markets are developed and thick, and information about market rental values is available, the characteristics of the dwellings inhabited by homeowners and by tenants might nonetheless differ considerably. Attention should therefore be paid to the selection among comparison groups to avoid comparing the incomparable. This matters both in the case of national accounts and country-level CPIs where obtaining correct estimates of average housing values serves the purpose and in the case of the analysis of household living standards wherein the construction of income or consumption aggregates requires the imputation of values for each household.

Despite the existing empirical evidence on the inaccuracy of homeowner self-assessed rental values described in section 2, there is no clear methodological recommendation on how to test accuracy. In developing countries in particular, analyses are hampered by the lack of up-to-date, complete administrative data and alternative surveys on the market for dwellings. Practitioners must therefore rely on the data collected in household budget surveys to test the accuracy of homeowner self-assessed rents.

The study illustrated in this paper proposes the use of matching estimators to assess the accuracy of homeowner self-assessed rents based on information typically available in household budget surveys. Matching estimators allow the identification of groups of tenants who live in dwellings that are as similar as possible in observable characteristics to the dwellings inhabited by homeowners. Thus, the comparison between homeowner selfassessed rents and market rents paid by tenants occurs among dwellings that share similar observable characteristics.

The rest of the paper is organized as follows. Section 2 provides a short review of studies that test the accuracy of homeowner self-assessed rents. Section 3 describes recent trends in the housing market in Peru. Section 4 presents the methodology used to ascertain the accuracy of homeowner self-assessed rents. Section 5 describes the microdata used in the analysis. Section 6 presents descriptive statistics and discusses the results. Section 7 offers final remarks.

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