Hedonic Prices and House Numbers: The Influence of Feng Shui

In contemporary practice, feng shui incorporates a wide range of concepts considered to affect a person’s luck. These include traditional ideas about site selection and building design, as well as newer beliefs about the “luckiness” of certain numbers. Focusing on an area with a relatively high percentage of Chinese households in Auckland, New Zealand, this paper uses hedonic price analysis to investigate whether house values are affected by lucky and unlucky numbers. Sales transactions for 1989 to 1996 are used in this analysis. The results demonstrate that lucky house numbers are capitalised into house values.Feng shui, hedonic price model, lucky, New Zealand

Land value taxation & housing development for three cities in Pennsylvania

This paper reviews theories about the economic effects of land value taxation as well as research which suggests hypotheses addressing the disparate circumstances of central cities such as Pittsburgh, suburban cities such as McKeesport, and relatively isolated cities such as New Castle. In order to test those hypotheses, specified a general econometric model of the housing market is specified. The model is adjusted to fit the circumstances of each city, and then the adjusted models using time-series data for each city is estimated. The periods of study for each city cover spans of time during which there were both increases in the tax rates applicable to land and decreases in the tax rates applicable to improvements. Incentive effects of decreases in the tax rate on buildings are expected to encourage housing development in Pittsburgh and, possibly, New Castle, but not in McKeesport. Liquidity effects of increases in the tax rate on land may encourage housing development in the three cities. All three cities employ land value taxation as an economic development tool and as a means for helping to stem or reverse the loss of population. By encouraging the construction of housing, land value taxation may help to attract households that would otherwise locate in other jurisdictions. Although Pittsburgh has had land value taxation since 1913 (Williams 1962), McKeesport and New Castle did not adopt such a tax system until 1979and1982, respectively

Predicting House Prices with Spatial Dependence: A Comparison of Alternative Methods

This paper compares alternative methods for taking spatial dependence into account in house price prediction. We select hedonic methods that have been reported in the literature to perform relatively well in terms of ex-sample prediction accuracy. Because differences in performance may be due to differences in data, we compare the methods using a single data set. The estimation methods include simple OLS, a two-stage process incorporating nearest neighbors’ residuals in the second stage, geostatistical, and trend surface models. These models take into account submarkets by adding dummy variables or by estimating separate equations for each submarket. Based on data for approximately 13,000 transactions from Louisville, Kentucky, we conclude that a geostatistical model with disaggregated submarket variables performs best.

Spatial Dependence, Housing Submarkets, and House Prices

This paper compares the impacts of alternative models of spatial dependence on the accuracy of house price predictions in a mass appraisal context. Explicit modeling of spatial dependence is characterized as a more fluid approach to defining housing submarkets. This approach allows the relevant “submarket” to vary from house to house and for transactions involving other dwellings in each submarket to have varying impacts depending on distance. We compare the predictive ability of different specifications of both geostatistical and lattice models as well as a simpler model based on submarkets with fixed boundaries. We conclude that – for our data – no spatial statistics method does as well in terms of predictive ability as a simple OLS model that includes a series of dummy variables defining submarkets. However, of the spatial statistics methods, geostatistical models provide more accurate predictions than lattice models. We argue that this is due to the fact that the kriging procedure used to make predictions in a geostatistical framework directly incorporates spatial information about nearby properties. That is not possible in a lattice framework due to the reliance on a matrix of weights that incorporates relationships only for the sample of properties that transact.spatial dependence; hedonic price models; geostatistical models; lattice models; mass appraisal; housing submarkets

A Simple Alternative House Price Index Method

This paper presents the Sale Price Appraisal Ratio (SPAR) method for constructing house price indexes. The method, which uses ratios of transaction prices and previous appraised values to build up an index, has been applied since the early 1960s to produce semi-annual price indexes for regions and cities in New Zealand. We compare the official New Zealand indexes for three urban areas with repeat sales and hedonic indexes created from the same transactions data, and observe that the SPAR method produces an index very much like those produced by hedonic methods. Given the number of advantages and few disadvantages that we find for the SPAR method relative to the more traditional methods, we maintain that it should be considered by government agencies elsewhere when developing house price indexes.house price indexes

What’s in a View?

The impact of views on property values has not been the specific focus of as much research as has the impact of other externalities on property values. When the impact of views is assessed, it is usually done by adding a single dummy variable to a hedonic regression equation. This paper provides a detailed literature review as well as an empirical analysis of the impact of a view on residential property values using a very rich database of nearly 5,000 sales in Auckland, New Zealand. Several dimensions of a view are analyzed: type of view, scope of view, distance to coast, appearance of immediately surrounding improvements, average quality of landscaping in the neighborhood, and average quality of structures in the neighborhood. It is found that wide views of water add an average of 59% to the value of a waterfront property, but that this effect diminishes quite rapidly as the distance from the coast increases. Attractive buildings in a property’s neighborhood on average add 37% to value relative to properties in neighborhoods with only average quality structures. Particularly attractive improvements in the immediate surroundings of a property add another 27% to value on average. On the other hand, properties in neighborhoods with only poor quality landscaping on average experience a -51% impact on price. Our results lead to the conclusion that aesthetic externalities are multi-dimensional and can have a substantial impact on residential property values.

Do Housing Submarkets Really Matter?

We maintain that the appropriate definition of submarkets depends on the use to which they will be put. For mass appraisal purposes, submarkets should be defined so that the accuracy of hedonic predictions will be optimized. Thus we test whether out-of-sample hedonic value predictions can be improved when a large urban housing market is divided into submarkets and we explore the effects of alternative definitions of submarkets on the accuracy of predictions. We compare a set of submarkets based on small geographical areas defined by real estate appraisers with a set of statistically generated submarkets consisting of dwellings that are similar but not necessarily contiguous. The empirical analysis uses a transactions database from Auckland, New Zealand. Price predictions are found to be most accurate when based on the housing market segmentation used by appraisers. We conclude that housing submarkets matter, and location plays the major role in explaining why they matter.Housing; Submarkets; Price Predictions; Mass Appraisal; Hedonic Method

House Price Changes and Idiosyncratic Risk: The Impact of Property Characteristics

While the average change in house prices is related to changes in fundamentals or perhaps market-wide bubbles, not all houses in a market appreciate at the same rate.The primary focus of our study is to investigate the reasons for these variations in price changes among houses within a market. We draw on two theories for guidance, one related to the optimal search strategy for sellers of atypical dwellings and the other focusing on the bargaining process between a seller and potential buyers. We hypothesize that houses will appreciate at different rates depending on the characteristics of the property and the change in the strength of the housing market. These hypotheses are supported using data from three New Zealand housing markets.Atypicality; Bargaining; Housing Risk; House Price Appreciation; Search Models

Estimation and Updating Methods for Hedonic Valuation

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U.S. metropolitan house price dynamics

For helpful comments, we thank Dan McMillen and other participants at the 2017 FSU-UF Critical Issues in Real Estate Symposium, two anonymous referees, and the editor. We thank Sam Khater for providing the CoreLogic house price indexes, Albert Saiz for giving supply elasticity data, and Andrew VanValin for preparing the maps. Funding: This work was supported by the OP-Pohjola Group Research Foundation and the Academy of Finland (first author; grant number 268310)Peer reviewedPostprin