Estimating Hedonic Models

Estimating Hedonic Models
Author: Helen Tauchen
Publisher:
Total Pages: 40
Release: 2001
Genre: Economics
ISBN:

In this paper we consider the conditions under which instrumental variables methods are required in estimating a hedonic price function and its accompanying demand and supply relations. We assume simple functional forms that permit an explicit solution for the equilibrium hedonic price function. The principles are the same for models in which no analytic solution exists, but having the solutions makes the issues far more transparent. The need for instrumental variables estimation is directly analogous for the classical demand and supply model with undifferentiated products and for the hedonic model with differentiated products. In estimating individual demand and supply functions, instrumental variables estimation is required if the consumer and firm unobservables, which give rise to the error terms in the demand and supply functions, are correlated across consumers/firms within a community. In estimating inverse demand/supply functions, which are referred to as bid/offer functions in the hedonic model, instrumental variables estimation is required even if the unobservables are not correlated across agents within a community. If the unobservables are not correlated across agents within a community, then community binaries or the means of observable consumer and firm characteristics can be used as instruments. If the unobservables are correlated then only the latter can be used. The error term in the hedonic price function is often assumed to be uncorrelated with the chosen attributes. This assumption may be reasonable if consumers have quasilinear preferences. If not, then the error term in the price function may affect the utility-maximizing amounts of the attributes. The feasible instruments again depend upon whether the error term is correlated for agents within a community. If not, then community binaries or observed individual characteristics may be used as instruments. If so, then the community binaries are correlated with the error terms and cannot serve as instruments.

Hedonic Methods in Housing Markets

Hedonic Methods in Housing Markets
Author: Andrea Baranzini
Publisher: Springer Science & Business Media
Total Pages: 283
Release: 2008-09-20
Genre: Business & Economics
ISBN: 0387768157

Cities are growing worldwide and their sprawl is increasingly challenged for its pressure on open spaces and environmental quality. Economic arguments can help to decide about the trade-off between preserving environmental quality and developing housing and business surfaces, provided the benefits of environmental quality are adequately quantified. To this end, this book focuses on the use and advancement of the “hedonic approach”, an economic valuation technique that analyses and quantifies the sources of rent and property price differentials. Starting from theoretical foundations, the hedonic approach is applied to the valuation of natural land use preservation and noise abatement measures, as well as to residential segregation and discrimination, extending the analysis to the role of the buyers and sellers' identity on housing market prices and to the issue of environmental justice.

Identification and Estimation of Hedonic Models

Identification and Estimation of Hedonic Models
Author: Ivar Ekeland
Publisher:
Total Pages: 0
Release: 2009
Genre:
ISBN:

This paper considers the identification and estimation of hedonic models. We establish that in an additive version of the hedonic model, technology and preferences are generically nonparametrically identified from data on demand and supply in a single hedonic market. The empirical literature that claims that hedonic models estimated on data from a single market are fundamentally underidentified is based on arbitrary linearizations that do not use all the information in the model. The exact economic model that justifies linear approximations is unappealing. Nonlinearities are generic features of equilibrium in hedonic models and a fundamental and economically motivated source of identification.

A Primer on Nonmarket Valuation

A Primer on Nonmarket Valuation
Author: Patricia A. Champ
Publisher: Springer
Total Pages: 508
Release: 2017-02-08
Genre: Business & Economics
ISBN: 9400771045

This is a practical book with clear descriptions of the most commonly used nonmarket methods. The first chapters of the book provide the context and theoretical foundation of nonmarket valuation along with a discussion of data collection procedures. The middle chapters describe the major stated- and revealed-preference valuation methods. For each method, the steps involved in implementation are laid out and carefully explained with supporting references from the published literature. The final chapters of the book examine the relevance of experimentation to economic valuation, the transfer of existing nonmarket values to new settings, and assessments of the reliability and validity of nonmarket values. The book is relevant to individuals in many professions at all career levels. Professionals in government agencies, attorneys involved with natural resource damage assessments, graduate students, and others will appreciate the thorough descriptions of how to design, implement, and analyze a nonmarket valuation study.

Estimation of Hedonic Regression Models with Missing Observations

Estimation of Hedonic Regression Models with Missing Observations
Author: Mohamed Rashed
Publisher: LAP Lambert Academic Publishing
Total Pages: 148
Release: 2014-01-01
Genre:
ISBN: 9783659502156

The use of the word "hedonic" to describe this technique stems from the word's Greek origin meaning "of or related to pleasure. In economics, hedonic regression or hedonic demand theory is a revealed preference method of estimating demand or value. In this book we present the hedonic regression and its important definitions. Also the statistical foundations and assumption of hedonic price indices are presented. A short overview of well-known functional forms of hedonic equations is given. We also discuss the missing data problem. we explore the type of missing data and the different ways of handle missing observation, the advantages and disadvantages of each method. Furthermore we discuss the chow test of parameter stability.Research on the real estate markets using hedonic models has not been undertaken previously in Egypt. The growing need for a research on the economics of the real estate property markets provided a base for the present study.

Improved Estimators of Hedonic Housing Price Models

Improved Estimators of Hedonic Housing Price Models
Author: Helen X. H. Bao
Publisher:
Total Pages: 26
Release: 2006
Genre:
ISBN:

In hedonic housing price modeling, real estate researchers and practitioners are often not completely ignorant about the parameters to be estimated. Experience and expertise usually provide them with tacit understanding of the likely values of the true parameters. Under this scenario the subjective knowledge about the parameter value can be incorporated as non-sample information in the hedonic price model. In this paper, we consider a class of Generalized Stein Variance Double k-class (GSVKK) estimators which allows real estate practitioners to introduce potentially useful information about the parameter values in the estimation of hedonic pricing models. The GSVKK estimator is a generalization of a family of shrinkage estimators introduced by Ohtani and Wan (2002, Econometric Reviews). Data from the Hong Kong real estate market are used to investigate the estimators' performance empirically. Compared with the traditional Ordinary Lease Squares approach, the GSVKK estimators have smaller predictive mean squared errors and lead to more precise parameter estimates. Some results on the theoretical properties of the GSVKK estimators are also presented.