Housing features and rent: estimating the microstructures of rental housing

Abstract

Purpose While consumers did not previously have information on detailed housing features via traditional media, such as magazines, nowadays, due to the progress in information technology, they can access detailed information on various housing features via housing information websites. Therefore, detailed housing features may affect current rents to some extent. This paper aims to identify the effects of detailed housing features on rent and on omitted variable bias in Tokyo, Japan. Design/methodology/approach This paper applies the hedonic approach. To identify the effects of features which are not observed previously, we use a unique data set that contains various housing features and over 200,000 housing units. This data set enables to simulate the situations when the researcher cannot get some variables, and this simulation shows which variables cause omitted variable bias. Findings The analysis shows that housing features significantly influence housing rent. If significant housing feature variables are not included in the hedonic model, the estimated coefficients show omitted variable bias. Additionally, unit-specific features such auto-locking door can cause omitted variable bias on location-specific features such accessibility to downtown. Originality/values This paper shows empirical evidence that detailed housing features can cause omitted variable bias on other features including variables which are often used in previous searches. The result from our unique data set can be a guide for variable selection to reduce omitted variable bias.

Apartment selection by college students

“…A prior research study regarding rent prices of housing examined utilitarian as well as hedonic features of the house. Findings revealed that omitting hedonic attributes from the house description caused a biased perception of the utilitarian features listed (Nishi et al, 2019).…”

Supply Management of Rental Housing Facilities: Effect of Changes in the Quality of Housing Equipment in the Tokyo Housing Rental Market

“…Shimizu [11] demonstrates that the environment surrounding housing is important in the case where house prices are determined by building use conditions and the characteristics of neighboring residents and suggests that in the case such variables are not taken into consideration and the estimated statistics of the hedonic function lack robustness. Nishi et al [8] also show that there is a similar problem with estimated statistics when housing equipment is not taken into consideration. Fuerst and Shimizu [13] show that in the new condominium market in Tokyo, the offered value for highly novel functionality such as environmental performance differs greatly when taking the household's annual income into account.…”

“…As for variable selection in the estimation of hedonic functions in Tokyo's rental housing market, Nishi et al [8] have conducted an exhaustive survey of the previous research. Nishi et al [8] pointed that the housing amenities used in hedonic analyses are categorized as "location or accessibility,""housing features," and "site advantages." This paper is focused on housing features, because they can be reflected in the rent due to the technological progress in the information systems and supply management.…”

“…Since the aim of this study is to identify the effect due to the addition of new functions over time, we hypothesize that the price structure will change according to the period of construction. 8 Data were segmented into the following three stocks:…”

“…(c) Data on housing exceeding 50 years of age (built before 1967), which were exceedingly few, were deleted. 8 When the market structure changes, it is necessary to construct a model to absorb the change [16,17].…”