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This study focuses on the Chicago CBD office market, an important market at the local, regional, national and international levels. The purpose of this study is to develop a hedonic regression model that explains the variation in office rent per square foot. Five functional forms (linear, reciprocal, logarithmic, semi-log and log-linear) of the model are considered. A generally log-linear model is determined to be the best model based on a series of Box-Cox/Box-Tidwell type transformations and likelihood ratio tests. The regression results reveal that the model has very high explanatory power. The methodology of this study differs substantially from that of previous studies on this topic. Perhaps most importantly, the unit of analysis is the office unit rather than the building. This choice suggested the use of specific lease terms for actual transactions and location of the unit within the building as new variables. Finally, the modeling of location of the building within the CBD was found to be a critical step. Copyright American Real Estate and Urban Economics Association.

We extend the literature on the impact of externalities using an approach based on a hybrid of hedonic and repeat-sales methods. The externality in question is groundwater contamination in Scottsdale, Arizona. The use of condominium sales allows us to assume that major physical characteristics remain unchanged, but location parameters may be altered by urban growth and development as well as contamination. We find an economically significant discount for properties located in the contaminated area. Interestingly, it does not appear until several years after the contamination becomes publicly known, and it seems to have disappeared before the end of the study period.The last three decades have seen the emergence of a voluminous literature examining the interaction between environmental factors and real estate markets, much of it concerning the extent to which negative environmental spillovers are capitalized into real estate values. These interests have given rise to two broad categories of real estate literature reviewed in Jackson (2001). The first of these is dominated by the appraisal profession and has focused on valuation concepts and methods (see, e.

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Within the market data approach to real estate appraisal, two basic types of analysis generally are used: (1) regression analysis; and (2) adjustment grid methods. The focus of this paper is on the adjustment grid methods. Three such methods are identified in the appraisal literature, but their analytical foundations are not clearly presented. The primary objective of this paper is to clarify the analytical foundations of each method. In addition, various ways to estimate the adjustment factors needed to apply the grid methods and a weighting scheme for reconciliation of indicated values are presented. Also, the possible advantage of grid-based over purely regression-based predictions is identified. Copyright American Real Estate and Urban Economics Association.