Improving Median Housing Price Indexes Through Stratification

Richards, Anthony; Prasad, Nalini

doi:10.2139/ssrn.958159

Cited by 3 publications

(12 citation statements)

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“…This can result in inaccurate indexes, susceptible to variations in the mix of houses sold from period to period in a particular region. Richards and Prasad (2008) argue that stratifying the full sample by suburb, and then taking the simple average of the median sale prices across each suburb, yields price index estimates that are not significantly different from hedonic regression. Given the effectiveness of this strategy for stratification, Richards and Prasad (2008) suggest that the marginal benefits of the more complex and data-intensive methods, such as hedonic regression and repeat-sales, are not justified.…”

Section: Central-price Tendency Methodsmentioning

confidence: 95%

“…Richards and Prasad (2008) argue that stratifying the full sample by suburb, and then taking the simple average of the median sale prices across each suburb, yields price index estimates that are not significantly different from hedonic regression. Given the effectiveness of this strategy for stratification, Richards and Prasad (2008) suggest that the marginal benefits of the more complex and data-intensive methods, such as hedonic regression and repeat-sales, are not justified. Goh et al (2012) directly compared these three different strategies and concluded that hedonic regression models give the best performance.…”

Section: Central-price Tendency Methodsmentioning

confidence: 95%

“…Because it assumes that all houses in a given location stratum are drawn from the same distribution of hedonic quantities, there is no need to identify hedonic attributes of individual houses, collect large amounts of data or carry out any esoteric statistical procedures. Goh et al's (2012) findings support Richards and Prasad's (2008) claim that, in absence of information on hedonic attributes, the mix-adjusted median is likely to be the best alternative. Our aim is to investigate whether the central tendency approach can be enhanced to the point where it can compete with, or even outperform, hedonic regression, as applied to the Irish housing market.…”

Section: Comparison Of Approachesmentioning

confidence: 90%

“…Case & Shiller, 1987;Hansen, 2009). Case and Szymanoski (1995) and Richards and Prasad (2008) developed methods for comparing various models by directly comparing goodness-of-fit statistics. However, Sommervoll (2006) argues that, due to the risk of overfitting, goodness-of-fit statistics can be misleading, especially where indexes are estimated at high levels of disaggregation or for sparse data.…”

Section: Measuring Robustnessmentioning

confidence: 99%

“…For example, if twice as many properties in Dublin are sold as usual, a region in which the value of most properties is higher than the national median, these sales will act to drag the median upwards, despite no actual change in price. Richards and Prasad (2008), for example, found that, based on a database of 3.5 million transactions in the six largest Australian cities, compositional shifts between higher and lower priced parts of cities led to much volatility in unadjusted median prices. Similarly, realtors in the US report that median house prices rise in the summer: most families with children, who typically buy more expensive homes, time their purchase based on school year considerations (Richards & Prasad, 2008).…”

Section: Stage 2: Mix-adjustment Through Proximity Votingmentioning

confidence: 99%

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A robust house price index using sparse and frugal data

Maguire

Miller

Moser

et al. 2016

Journal of Property Research

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In this article, we describe a house price index algorithm which requires only sparse and frugal data, namely house location, date of sale and sale price, as input data. We aim to show that our algorithm is as effective for predicting price changes as more complex models which require detailed or extensive data. Although various methods are employed for determining house price indexes, such as hedonic regression, mix-adjusted median or repeat sales, there is no consensus on how to determine the robustness of an index, and hence no agreement on which method is the best to use. We formalise an objective criterion for what a house price index should achieve, namely consistency between time periods. Using this criterion, we investigate whether it is possible to achieve strong robustness using frugal data covering only 66 months of transactions on the Irish property market. We develop a simple multi-stage algorithm and show that it is more robust than the complex hedonic regression model currently employed by the Irish Central Statistics Office.

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Section: Central-price Tendency Methodsmentioning

confidence: 95%

Section: Central-price Tendency Methodsmentioning

confidence: 95%

Section: Comparison Of Approachesmentioning

confidence: 90%

Section: Measuring Robustnessmentioning

confidence: 99%

Section: Stage 2: Mix-adjustment Through Proximity Votingmentioning

confidence: 99%

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A robust house price index using sparse and frugal data

Maguire

Miller

Moser

et al. 2016

Journal of Property Research

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Teoretyczne i metodyczne aspekty wyznaczania indeksów cen na rynku mieszkaniowym

Trojanek¹

2018

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In the book, an attempt was made to catalogue knowledge concerning the importance of research into the dynamics of housing prices for social and economic development. The analysis of the experience of countries with well-developed real estate markets in the aspect of building price indexes was carried out. Based on original databases of asking and transaction prices, price indexes were built, which were then subjected to numerous resistance tests. The aims of these research tasks were as follows: 1) to examine the quality of offers for sale as a source of information about changes in the real estate market, 2) to find out whether the repeat sales method can be used for building price indexes and to critically assess this method in terms of the stability of the obtained results, 3) to analyze hedonic methods and indicate the preferred one in terms of the ratio of the quality of results to how time-consuming and cost-intensive it is to build such indexes, 4) to establish the importance of methods and sources of information for building price indexes in different time horizons, 5) to identify how important it is for the fluctuation of price indexes if the cooperative property right to a flat is not taken into account. In order to perform the research tasks and accomplish the goals scopes of the work were defined. The subject followed the aim of the study and refers to prices in the secondary housing market, encompassing both the property right and cooperative property right to a flat or house. The broad scope concerns the discussion in the general part, being narrowed down to the secondary market of flats located in multi-family and single-family buildings. The time scope covers the years 2000-2015, which is connected to the range of empirical studies carried out. They focused both on actual transactions and on offers of flats for sale. On this basis, we built databases which served as the starting point for further analyses. The study involved transactions and offers in the area of Poznan.

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Using the ARDL Approach to Explore the Effect of Chinese Individual Mobility in Australian Residential Real Estate Market

Wu¹,

Tam²

2018

Proceedings of the Third International Conference on Economic and Business Management (FEBM 2018)

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To better understand whether Chinese mobility has a significant effect on the Australian residential real estate market, the relationship between Chinese individual mobility and Australian residential real estate market is explored. The Autoregressive Distributed Lag (ARDL) approach is employed to investigate the cointegration relationship of the variables, including Chinese tourism mobility, Chinese temporary migration mobility, Australian residential real estate prices and the Australian real estate construction. The primary finding is that Chinese tourism mobility and temporary migration mobility does not have a significant and positive effect on Australian residential real estate prices, but Chinese tourism mobility contributes to the development of the Australian real estate construction in the long run. In terms of the short run, Chinese tourism mobility and temporary migration mobility lead to an increase in Australian residential real estate prices and have a negative effect on the Australian real estate construction. It is believed that understanding the effect of Chinese individual mobility in the Australian residential real estate market will assist policymakers or researchers to make reasonable policies or methods to solve affordability issues caused by high residential real estate prices.

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Improving Median Housing Price Indexes Through Stratification

Cited by 3 publications

References 16 publications

A robust house price index using sparse and frugal data

A robust house price index using sparse and frugal data

Teoretyczne i metodyczne aspekty wyznaczania indeksów cen na rynku mieszkaniowym

Using the ARDL Approach to Explore the Effect of Chinese Individual Mobility in Australian Residential Real Estate Market

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