This paper analyzes the incentive properties of the standard and burden of proof for a finding of negligence, when evidence is imperfect and rests with the parties. We show that the preponderance of evidence' standard provides maximal incentives to exert care. This holds even though litigants...

The difference-in-differences (DID) approach that identifies the capitalization of amenities through changes in housing prices has been widely used in the literature of hedonic estimation in the past decade. However, concerns have been raised about how to interpret the estimated capitalization...

Using a quantitative spatial model as a data-generating process, we explore how spatial frictions affect the measurement of quality of life. We find that under a canonical parameterization, mobility frictions—generated by idiosyncratic tastes and local ties—dominate trade...

Making use of restrictions imposed by equilibrium, theoretical progress has been made on the nonparametric and semiparametric estimation and identification of scalar additive hedonic models (Ekeland, Heckman, and Nesheim, 2002) and scalar nonadditive hedonic models (Heckman, Matzkin, and...

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 identified up to affine transformations from data on demand and supply in a single hedonic market. For a very...

Changes in product characteristics on the extensive margin are an important and hitherto neglected dimension of quality change. Standard techniques for quality-adjusting price indices cannot handle such changes satisfactorily, which leads to an economically and statistically significant bias in...

We focus on the housing market and examine why nonlocal home buyers (NLBs) pay 15 percent more for houses than local home buyers (LBs). We estimate a housing demand model that returns heterogeneous willingness to pay parameters for housing attributes. Our results show that NLBs are willing to...

We develop a programming algorithm that predicts a balanced-panel mix-adjusted house price index for arbitrary spatial units from repeated cross-sections of geocoded micro data. The algorithm combines parametric and non-parametric estimation techniques to provide a tight local fit where the...