Urban Dynamics and Hedonics

Paper Session

Saturday, Jan. 7, 2017 10:15 AM – 12:15 PM

Sheraton Grand Chicago, Erie
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Gilles Duranton, University of Pennsylvania

The Value of a Healthy Home: Lead Paint Remediation and Housing Values

Stephen Billings
University of North Carolina-Charlotte
Kevin Schnepel
University of Sydney


The presence of lead paint significantly impairs cognitive and behavioral development, yet little is known about how this residence-specific environmental health risk affects property values. In this paper, we estimate the benefits of lead-paint remediation on housing prices. Using data on all homes that applied to a HUD-funded program in Charlotte, North Carolina, we adopt a difference- in-differences estimator that compares values among remediated properties with those for which an inspection does not identify a lead paint hazard. Results indicate that remediation has large benefits-a typical investment of $7,291 is associated with a capitalized benefit of $20,323 as well as a reduction in residential turnover.

Vertical Density and Agglomeration Economies

William Strange
University of Toronto
Crocker Liu
Cornell University
Stuart Rosenthal
Syracuse University


Cities are defined by density, and density is made possible by constructing tall buildings. Tall buildings are, therefore, defining features of cities. Despite this, urban economists have focused largely on the height of tall buildings, largely ignoring their internal structure. This paper will help to fill this gap in knowledge by focusing on patterns of vertical density within commercial buildings. Productivity, access, and amenities are all shown to impact density, often in conflicting ways. The vertical density gradient depends on the strength of these forces, which is an empirical issue. The paper’s empirical analysis shows that density does not change with vertical location in a simple, unambiguous way. In contrast, factors associated with productivity have a positive effect on the density of employment. In particular, vertical density patterns are consistent with agglomeration economies that attenuate with vertical distance.

Stability & Change: The Durable Hierarchy of Neighborhoods in U.S. Metropolitan Areas from 1970 to 2010

Thom Malone
University of Southern California
Christian Redfearn
University of Southern California


In urban economics change is generally examined one issue at a time – tipping, gentrifica-
tion, filtering, suburbanization, access to transportation, and others each have their own mature
literature. 1 But, there is little attention paid to the cumulative effect of all this change and how
metropolitan areas are broadly arranged and rearranged over time. In this paper, we exam-
ine patterns of stability within and across US metropolitan areas. Using Census data covering
over 300 U.S metropolitan areas from 1970 to 2010 we use several socioeconomic variables to
define a neighborhood hierarchy and ask how durable it is over time. Despite the substantial
changes that have occurred in metropolitan America over the sample period, we find remark-
able persistence in population density, income, education, and house prices, with many cities
having rank correlations of over 0.75. And while racial and ethnic variables appear to be less
persistent, all seven variables exhibit a general trend toward more stability over time. Even
in the presence of large shocks to the metropolitan economy, a majority of MSAs retain the
same basic spatial hierarchy they had decades ago. Collectively, the results suggest a durable
hierarchy of neighborhoods through which different types of residents pass through over time.
Hierarchies are disturbed by shocks that are highly spatially correlated wherein large amounts of
new development and/or immigration lead to significant reordering of neighborhoods within the
hierarchy. This pattern of stability and change has significant implications for how we analyze
and understand urban areas and their change.

Valuing Time-Varying Attributes Using the Hedonic Model: When is a Dynamic Approach Necessary?

Alvin Murphy
Arizona State University
Kelly Bishop
Arizona State University


We build on the intuitive (static) modeling framework of Rosen (1974) and specify a simple forward looking model of location choice. We use this model, along with a series of insightful graphs, to describe the potential biases associated with the static approach and relate these biases to the time-series trend of the amenity of interest. We then derive an adjustment factor that allows the biased static estimates to be converted into estimates coming from a forward-looking model. Finally, we empirically motivate the use of this adjustment factor in an application of estimating the willingness-to-pay to avoid violent crime in California.
Reed Walker
University of California-Berkeley
Daniel McMillen
University of Illinois-Urbana-Champaign
Sanghoon Lee
University of British Columbia
Rebecca Diamond
Stanford University
JEL Classifications
  • Q5 - Environmental Economics
  • R2 - Household Analysis