Residential Hedonic Models: A Rational Expectations Approach to Age Effects

This paper develops a rational expectations framework for interpreting the coefficient on age in a standard hedonic model. The model demonstrates that there are two components to the age coefficient: a pure cross-sectional depreciation component and a demand-side component that changes over time. We also show that a constant quality price index with age constant can be estimated by using any repeat sales database that contains the year of construction (or property age). When Fairfax County data are fitted to the model, the time series of age coefficients is non-stationary: they change from negative in the early 1980s to positive in the late 1980s; we infer that the demand-side component dominated in the latter period.     

A Semiparametric Method for Valuing Residential Locations: Application to Automated Valuation

This paper is motivated by automated valuation systems, which would benefit from an ability to estimate spatial variation in location value. It develops theory for the local regression model (LRM), a semiparametric approach to estimating a location value surface. There are two parts to the LRM: (1) an ordinary least square (OLS) model to hold constant for interior square footage, land area, bathrooms, and other structural characteristics; and (2) a non-parametric smoother (local polynomial regression, LPR) which calculates location value as a function of latitude and longitude. Several methods are used to consistently estimate both parts of the model. The LRM was fit to geocoded hedonic sales data for six towns in the suburbs of Boston, MA. The estimates yield substantial, significant and plausible spatial patterns in location values. Using the LRM as an exploratory tool, local peaks and valleys in location value identified by the model are close to points identified by the tax assessor, and they are shown to add to the explanatory power of an OLS model. Out-of-sample MSE shows that the LRM with a first-degree polynomial (local linear smoothing) is somewhat better than polynomials of degree zero or degree two. Future applications might use degree zero (the well-known NW estimator) because this is available in popular commercial software. The optimized LRM reduces MSE from the OLS model by between 5 percent and 11 percent while adding information on statistically significant variations in location value.     

A Methodology for Constructing Vacant Land Price Indices

Existing estimates of movements in vacant land prices are limited to a few metropolitan areas and infrequent time intervals. This paper develops a new methodology for estimating vacant land price trends for subareas within states and metropolitan areas. It utilizes data from a sales ratio study, a large database available in most states. The methodology uses assessed value to control for "hedonic characteristics" associated with the property and its location. A model is developed to correct assessed value for measurement errors. Statistical results for forty-one Connecticut towns indicate that the model provides a reasonable compromise between data availability and accuracy of price trend estimates.     

Do Laws Influence the Cost of Real Estate Brokerage Services? A State Fixed Effects Approach

A FTC‐DOJ study argues that state laws and regulations may inhibit the unbundling of real estate brokerage services in response to new technology. Our data show that 18 states have changed laws in ways that promote unbundling since 2000. We model brokerage costs as measured by number of agents in a state‐level annual panel vector autoregressive framework, a novel way of analyzing wasteful competition. Our findings support a positive relationship between brokerage costs and lagged house price and transactions. We find that change in full‐service brokers responds negatively (by well over two percentage points per year) to legal changes facilitating unbundling.     

Estimating price trends for residential property: A comparison of repeat sales and assessed value methods

The repeat sales methodology for estimating residential price indices is based on actual appreciation of individual properties. On the other hand, the repeat sales method wastes data, typically discarding a large percentage of all sales. This article explores two issues related to the subsample of repeat sales. First, are paired sales representative of the entire population of properties that sold? Second, is there evidence that sample selectivity biases the price trend estimates? Evidence from five metropolitan areas supports a negative answer to the first question and the second question. It appears that a “lemon” or “starter home” effect causes repeat residential sales to be a biased subsample of all transactions. Cumulative price trends for the repeat subsamples can differ from the full samples over periods ranging from two to ten quarters. While short-term price trends can differ widely, there are no systematic differences among the samples over long periods of time (e.g., three years or more).     

Hedonic estimation of housing demand elasticity with a markup over marginal costs

We show that recent developments in hedonic pricing theory allow modeling of the equilibrium pricing function as the marginal cost of an additional housing unit plus a markup that varies inversely with the elasticity of demand. Useful information about demand elasticity at a given point on the envelope function can be recovered from the hedonic regression and limited information on marginal costs. In particular, the elasticity of the envelope with respect to any characteristic such as interior area provides information on the elasticity of demand. Relative price elasticities (i.e., elasticities that vary from a base value in a known way with interior area, unit type or neighborhood characteristics) can be computed from the elasticity of the hedonic envelope. Like Yinger (2010), our method is based on a single hedonic equation.We test our method using sales of new high rise condominiums in two districts within Shenzhen, China: Futian and Longgang. The results strongly confirm the main hypothesis of this paper: price elasticity with respect to size is increasing for more complex types of units. Together with estimates of marginal costs of production, these results imply that relative demand elasticity is declining for larger, more complex units.     

A Semiparametric Method for Estimating Local House Price Indices

Spatial autoregressive hedonic models utilize house prices lagged in space and time to produce local house price indices, for example, the spatial and temporal autoregressive (STAR) model might be used this way. This paper complements these models with a semiparametric approach, the Local Regression Model (LRM). The greater flexibility of the LRM may allow it to identify space–time asymmetries missed by other models. The LRM is fitted to 49,511 sales from 1972Q1 to 1991Q2 in Fairfax County, Virginia. The local price indices display plausible and significant variations over space and time. The LRM price indices in selected neighborhoods are shown to differ significantly from those in some other neighborhoods. A new method for estimating standard errors addresses an overlooked problem common to all local price indices: how to evaluate the amount of noise in the estimates. Out-of-sample prediction errors demonstrate that LRM adds significant information to the hedonic model.     

Production with land and nonland factors: Which functional form?

Recent literature has investigated alternative CES and VES specifications for the production of building services with land and nonland inputs. The evidence presented here is consistent with a wide range of functional forms; the Cobb-Douglas form cannot be rejected but neither is it strongly supported. These findings are not inconsistent with previous estimates which are likely to be biased by errors-in-variables. Furthermore, the results reported here parallel findings from the literature on the substitution of labor for capital. Since data are not as readily available as in the labor-capital context, one must be pessimistic about the prospects for definitive empirical work.     

Imperfect Information and Investor Inferences From Housing Price Dynamics

We examine characteristics of housing price dynamics that may be consistent with rational learning and not simply irrational feedback trading. We find significant patterns of temporal and spatial diffusion that are more amenable to explanations that allow for rational components. First, we execute our tests not simply on housing price changes, but on town-by-town differentials from regional average price changes. Second, we find significant relationships with own and neighboring town differentials, but not with control groups of non-neighboring towns. Third, we find that population density, a proxy for scale economies in information production, accelerates the diffusion process. Test were performed on quarterly data for large samples from Connecticut and the San Francisco area, employing method of moments estimators.