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.

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

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

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.

COMPARING THE IMPACTS OF RETIREE VERSUS WORKING-AGE FAMILIES ON A SMALL RURAL REGION: AN APPLICATION OF THE WISCONSIN ECONOMIC IMPACT MODELING SYSTEM

The Wisconsin Economic Impact Modeling System, a conjoined input-output/econometric model of Wisconsin counties, is used to simulate the economic and fiscal impact of two alternative residential development patterns. Under the first scenario, the impact of migrating retirees on a small tri-county region in northern Wisconsin is examined. Under the second scenario, the impact of the migration of younger families with children is examined. A comparison-contrast between the two scenarios demonstrates that the characteristics of the migrating household can have a significant impact on the nature of the impacts.Community/Rural/Urban Development,

THE IMPACT OF THE YOUNG-OLD AND THE OLD-OLD ON A SMALL RURAL REGION: AN APPLICATION OF THE WISCONSIN ECONOMIC IMPACT MODELING SYSTEM

The literature on the economic and fiscal impacts of in-migrating retirees on rural communities concentrates on the young, newly-retired. An issue not systematically addressed are the impacts on the communities as these retirees age. The Wisconsin Economic Impact Modeling System, a county level conjoined input-output/econometrics simulation model, is used to assess the impact of an aging rural population. Using data from the US Bureau of Labor Statistics' Consumer Expenditure Survey, profiles of two household types are constructed and used to simulate the economic impact of an additional 500 elderly households into a small rural economy. Household types vary by age and, as a result, have different income levels and expenditure patterns. As hypothesized, the magnitude and nature of impacts is in direct proportion to relative household size and income level.aging, economic impacts, development policy, Community/Rural/Urban Development,

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

THE IMPACT OF RETIREES AND WORKING-AGE FAMILIES ON A SMALL RURAL REGION: AN APPLICATION OF THE WISCONSIN ECONOMIC IMPACT MODELING SYSTEM

The Wisconsin Economic Impact Modeling System, a conjoined input-output/econometric model of Wisconsin counties, is used to simulate the economic and fiscal impact of two alternative residential development patterns. Under the first scenario, the impact of migrating retirees on a small tri-county region in northern Wisconsin is examined. Under the second scenario, the impact of the migration of younger families with children is examined. A comparison-contrast between the two scenarios demonstrates that the characteristics of the migrating household can have a significant impact on the nature of the impacts.Community/Rural/Urban Development,

Detection of benzimidazole carbamates and amino metabolites in liver by surface plasmon resonance-biosensor

This research was funded by the Irish Department of Agriculture, Fisheries and Food under the Food Institutional Research Measure as part of the National Development Plan (Project 05/R&D/TN/355)peer-reviewedTwo surface plasmon resonance (SPR) biosensor screening assays were developed and validated to detect 11 benzimidazole carbamate (BZT) and four amino-benzimidazole veterinary drug residues in liver tissue. The assays used polyclonal antibodies, raised in sheep, to detect BZTs and amino-benzimidazoles. A modified Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) extraction method was developed to isolate benzimidazole carbamate residues. Liver samples were extracted using an acetonitrile extraction method. BZTs were purified by dispersive solid phase extraction (d-SPE) using C18 sorbent. Residues of amino-benzimidazoles were effectively cleaned-up using a simple cyclohexane defatting step. The assays were validated in accordance with the performance criteria described in 2002/657/EC. The BZT assay limit of detection was calculated to be 32 μg kg−1, the detection capability (CCβ) was determined to be 50 μg kg−1 and the mean recovery of analytes was in the range 77–132%. The amino-benzimidazole assay limit of detection was determined to be 41 μg kg−1, the CCβ was determined to be 75 μg kg−1 and analyte recovery was in the range 103–116%. Biosensor assay performance was tested by analysing liver tissue from animals treated with benzimidazole drugs and comparing the results with an ultra high performance liquid chromatography tandem mass spectrometry (UHPLC–MS/MS) confirmatory method. All non-compliant samples were identified using the biosensor assays.Department of Agriculture, Food and the Marin