Separating the Age Effect from a Repeat Sales Index: Land and Structure Decomposition

Wong, SK; Chau, K. T.; Karato, Koji; Shimizu, Chihiro

doi:10.1007/s11146-017-9631-2

Cited by 11 publications

(7 citation statements)

References 17 publications

(14 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If housing amenities can be assumed not to change over time, such variables can be excluded from the model using this method (McMillen and Thorsnes, 2006). However, if housing features do change due to renovations or some other events, this method is not appropriate (Billings, 2015;McMillen and Thorsnes, 2006;Shimizu and Karato, 2015;Wong et al, 2017).…”

Section: Classification Of Housing Amenitiesmentioning

confidence: 99%

Housing features and rent: estimating the microstructures of rental housing

Nishi

Asami

Shimizu

2019

IJHMA

View full text Add to dashboard Cite

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.

show abstract

Section: Classification Of Housing Amenitiesmentioning

confidence: 99%

Housing features and rent: estimating the microstructures of rental housing

Nishi

Asami

Shimizu

2019

IJHMA

View full text Add to dashboard Cite

show abstract

“…To really compare "like with like" repeat-sales indices should also control and adjust for major renovations and for depreciation between sales. A recent paper by Wong et al (2018) proposes a repeat-sales approach to estimate an age-adjusted repeat-sales index by decomposing property value into land and structure components. As depreciation is more relevant to the structure than land, the property's depreciation rate should then depend on the relative value shares of land and structure.…”

Section: Repeat-sales Methodsmentioning

confidence: 99%

“…For CPPIs to become properly useful to the national accounts they need to provide a decomposition of property values into price and volume (quantity) components for both the structure and the land parts of the property (see chapter 11 of the Eurostat report, Wong et al, 2018;Diewert and Shimizu, 2019). This separation between land and structure is the main difference in the statistical needs for CPPIs between the national accounts community and other users.…”

Section: Cppis Play Many (Potential) Rolesmentioning

confidence: 99%

See 1 more Smart Citation

Commercial Property Price Indices and Indicators: Review and Discussion of Issues Raised in the CPPI Statistical Report of Eurostat (2017)

Hill

Steurer

2020

Review of Income and Wealth

View full text Add to dashboard Cite

show abstract

“…Wong et al (2018) exploited the structure-to-property value ratio to break the linear relationship between age and time differences between sales, making it possible to separate the age effect from a repeat-sales index. Another suggestion is to take age as a proxy of the depreciation effect in the repeat-sales model.…”

Section: Literature Reviewmentioning

confidence: 99%

A housing price index with the improvement-value adjusted repeated sales (IVARS) method

Yiu

Cheung

2021

IJHMA

View full text Add to dashboard Cite

Purpose The repeat sales house price index (HPI) has been widely used to measure house price movements on the assumption that the quality of properties does not change over time. This study aims to develop a novel improvement-value adjusted repeat sales (IVARS) HPI to remedy the bias owing to the constant-quality assumption. Design/methodology/approach This study compares the performance of the IVARS model with the traditional hedonic price model and the repeat sales model by using half a million repeated sales pairs of housing transactions in the Auckland Region of New Zealand, and by a simulation approach. Findings The results demonstrate that using the information on improvement values from mass appraisal can significantly mitigate the time-varying attribute bias. Simulation analysis further reveals that if the improvement work done is not considered, the repeat sales HPI may be overestimated by 2.7% per annum. The more quality enhancement a property has, the more likely it is that the property will be resold. Practical implications This novel index may have the potential to enable the inclusion of home condition reporting in property value assessments prior to listing open market sales. Originality/value The novel IVARS index can help gauge house price movements with housing quality changes.

show abstract

Separating the Age Effect from a Repeat Sales Index: Land and Structure Decomposition

Cited by 11 publications

References 17 publications

Housing features and rent: estimating the microstructures of rental housing

Housing features and rent: estimating the microstructures of rental housing

Commercial Property Price Indices and Indicators: Review and Discussion of Issues Raised in the CPPI Statistical Report of Eurostat (2017)

A housing price index with the improvement-value adjusted repeated sales (IVARS) method

Contact Info

Product

Resources

About