Nonparametric Identification and Estimation of Nonadditive Hedonic Models

This paper studies the identification and estimation of preferences and technologies in equilibrium hedonic models. In it, we identify nonparametric structural relationships with nonadditive heterogeneity. We determine what features of hedonic models can be identified from equilibrium observations in a single market under weak assumptions about the available information. We then consider use of additional information about structural functions and heterogeneity distributions. Separability conditions facilitate identification of consumer marginal utility and firm marginal product functions. We also consider how identification is facilitated using multimarket data.hedonic models, hedonic equilibrium, nonadditive models, identification, non-parametric estimation

Identifying Individual and Group Effects in the Presence of Sorting: A Neighborhood Effects Application

Researchers have long recognized that the non-random sorting of individuals into groups generates correlation between individual and group attributes that is likely to bias naïve estimates of both individual and group effects. This paper proposes a non-parametric strategy for identifying these effects in a model that allows for both individual and group unobservables, applying this strategy to the estimation of neighborhood effects on labor market outcomes. The first part of this strategy is guided by a robust feature of the equilibrium in vertical sorting models - a monotonic relationship between neighborhood housing prices and neighborhood quality. This implies that under certain conditions a non-parametric function of neighborhood housing prices serves as a suitable control function for the neighborhood unobservable in the labor market outcome regression. This control function transforms the problem to a model with one unobservable so that traditional instrumental variables solutions may be applied. In our application, we instrument for each individual’s observed neighborhood attributes with the average neighborhood attributes of a set of observationally identical individuals. The neighborhood effects model is estimated using confidential microdata from the 1990 Decennial Census for the Boston MSA. The results imply that the direct effects of geographic proximity to jobs, neighborhood poverty rates, and average neighborhood education are substantially larger than the conditional correlations identified using OLS, although the net effect of neighborhood quality on labor market outcomes remains small. These findings are robust across a wide variety of specifications and robustness checks.

Nonparametric identification and stimation of nonadditive hedonic Models

This paper studies the identification and estimation of preferences and technologies in equilibrium hedonic models. In it, we identify nonparametric structural relationships with nonadditive heterogeneity. We determine what features of hedonic models can be identified from equilibrium observations in a single market under weak assumptions about the available information. We then consider use of additional information about structural functions and heterogeneity distributions. Separability conditions facilitate identification of consumer marginal utility and firm marginal product functions. We also consider how identification is facilitated using multimarket data

Prices, Profits, Proxies, and Production

This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent rendering standard approaches inapplicable. Instead, we require observation of profits or other optimizing-values such as costs or revenues, and either prices or price proxies of flexibly chosen variables. We extend classical duality results for price-taking firms to a setup with discrete heterogeneity, endogeneity, and limited variation in possibly latent prices. Finally, we show that convergence results for nonparametric estimators may be directly converted to convergence results for production sets.Comment: This paper was previously circulated with the title "Prices, Profits, and Production

Demand Estimation with Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach

We study the identification and estimation of Gorman-Lancaster style hedonic models of demand for differentiated products for the case when one product characteristic is not observed. Our identification and estimation strategy is a two-step approach in the spirit of Rosen (1974). Relative to Rosen's approach, we generalize the first stage estimation to allow for a single dimensional unobserved product characteristic, and also allow the hedonic pricing function to have a general, non-additive structure. In the second stage, if the product space is continuous and the functional form of utility is known then there exists an inversion between the consumer's choices and her preference parameters. This inversion can be used to recover the distribution of random coefficients nonparametrically. For the more common case when the set of products is finite, we use the revealed preference conditions from the hedonic model to develop a Gibbs sampling estimator for the distribution of random coefficients. We apply our methods to estimating personal computer demand.

Estimating firms' demand for agglomeration

The market for commercial properties is characterised by extreme heterogeneity in demand. In this paper, we aim to gain more insight in the heterogeneity in demand for employment agglomeration and size of the rental property using a two-stage hedonic approach following Bajari and Benkard (2005). We use unique micro-data of properties' attributes as well as of firm characteristics. Given assumptions on the functional form of the production function, we identify firm-specific parameters using a nonparametric control function approach that corrects for endogeneity. The results show that agglomeration benefits are capitalised in rents: a one standard deviation increase in agglomeration leads to an increase in the annual rents of about 6 percent. It is found that larger and business services firms are willing to pay (substantially) more for agglomeration. Furthermore, for office buildings a 10 percent increase in number of employees increases the marginal willingness to pay for floor space with 8 percent, which suggests that internal returns to scale are present

Evaluation of Urban Improvement on the Islands of the Venice Lagoon: A Spatially-Distributed Hedonic-Hierarchical Approach

This paper presents a model for the evaluation of environmental and urban improvements on the islands of the Venetian lagoon. The model simulates the changes in residential real estate values using a value function integrated in a geographical database which provides spatial distributions of values changes. The fairly weak market signals, fragmented demand and strong externalities, and the scarcity of market data available do not permit the use of econometric models for value appraisal. Appropriate hedonic-hierarchical value functions are calibrated on the basis of a set of indicators of the characteristics of the buildings and the location. Some applications of the model are illustrated simulating two scenarios of future interventions which are actually being discussed or realised and involving the island of Murano, Burano and S. Erasmo in the Venice Lagoon. The interventions considered are: subway beyond the lagoon connecting Murano with Venice and the mainland, and the solution of “high water” problems on Murano, Burano and S. Erasmo.Public work assessment, Property value, Hierarchical analysis

Modelling the impact of earthquake activity on real estate values: a multi-level approach

Purpose – This paper seeks to look at the impact of recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market. Design/Methodology/Approach – The paper employs a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows us to isolate the effects of earthquake risk and explore the differential impact in different submarkets in two study periods - one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey, served to alter the perceptions of risk through the wider geographic region. Findings – The analysis shows that their are variations in the size of price discounts in submarkets resulting from the differential influence of recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values. Practical implications – The methods introduced in this study can be used by real estate agents, valuers, and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments. Originality/value – The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach

Hedonic Wage Equilibrium: Theory, Evidence and Policy

We examine theoretically and empirically the properties of the equilibrium wage function and its implications for policy. Our emphasis is on how the researcher approaches economic and policy questions when there is labor market heterogeneity leading to a set of wages. We focus on the application where hedonic models have been most successful at clarifying policy relevant outcomes and policy effects, that of the wage premia for fatal injury risk. Estimates of the overall hedonic locus we discuss imply the so-called value of a statistical life (VSL) that is useful as the benefit value in a cost-effectiveness calculation of government programs to enhance personal safety. Additional econometric results described are the multiple dimensions of heterogeneity in VSL, including by age and consumption plans, the latent trait that affects wages and job safety setting choice, and family income. Simulations of hedonic market outcomes are also valuable research tools. To demonstrate the additional usefulness of giving detail to the underlying structure we not only develop the issue of welfare comparisons theoretically but also illustrate how numerical simulations of the underlying structure can also be informative. Using a reasonable set of primitives we see that job safety regulations are much more limited in their potential for improving workplace safety efficiently compared to mandatory injury insurance with experience rated premiums. The simulations reveal how regulations incent some workers to take more dangerous jobs, while workers’ compensation insurance does not (or less so).hedonic labor market equilibrium, VSL, panel data, job safety, OSHA, quantile regression, workers’ compensation insurance