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Papers Containing Keywords(s): 'house'

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Viewing papers 11 through 17 of 17


  • Working Paper

    The Dynamics of House Price Capitalization and Locational Sorting: Evidence from Air Quality Changes

    September 2012

    Authors: Corey Lang

    Working Paper Number:

    CES-12-22

    Despite extensive use of housing data to reveal valuation of non-market goods, the process of house price capitalization remains vague. Using the restricted access American Housing Survey, a high-frequency panel of prices, turnover, and occupant characteristics, this paper examines the time path of capitalization and preference-based sorting in response to air quality changes caused by differential regulatory pressure from the 1990 Clean Air Act Amendments. The results demonstrate that owner-occupied units capitalize changes immediately, whereas rent capitalization lags. The delayed but sharp rent capitalization temporally coincides with evidence of sorting, suggesting a strong link between location choices and price dynamics.
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  • Working Paper

    The Effect of Power Plants on Local Housing Values and Rents: Evidence from Restricted Census Microdata

    July 2008

    Authors: Lucas Davis

    Working Paper Number:

    CES-08-19

    Current trends in electricity consumption imply that hundreds of new fossil-fuel power plants will be built in the United States over the next several decades. Power plant siting has become increasingly contentious, in part because power plants are a source of numerous negative local externalities including elevated levels of air pollution, haze, noise and traffic. Policymakers attempt to take these local disamenities into account when siting facilities, but little reliable evidence is available about their quantitative importance. This paper examines neighborhoods in the United States where power plants were opened during the 1990s using household-level data from a restricted version of the U.S. decennial census. Compared to neighborhoods farther away, housing values and rents decreased by 3-5% between 1990 and 2000 in neighborhoods near sites. Estimates of household marginal willingness-to-pay to avoid power plants are reported separately for natural gas and other types of plants, large plants and small plants, base load plants and peaker plants, and upwind and downwind households.
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  • Working Paper

    You Can Take it With You: Proposition 13 Tax Benefits, Residential Mobility, and Willingness to Pay for Housing Amenities

    June 2008

    Working Paper Number:

    CES-08-15

    The endogeneity of prices has long been recognized as the main identification problem in the estimation of marginal willingness to pay (MWTP) for the characteristics of a given product. This issue is particularly important when estimating MWTP in the housing market, since a number of housing and neighborhood features are unobserved by the econometrician. This paper proposes the use of a well defined type of transaction costs ' moving costs generated by property tax laws - to deal with this type of omitted variable bias. California's Proposition 13 property tax law is the source of variation in transaction costs used in the empirical analysis. Beyond its fiscal consequences, Proposition 13 created a lock-in effect on housing choice because of the implicit tax break enjoyed by homeowners living in the same house for a long time. First, I provide estimates of this lock-in effect using a natural experiment created by two subsequent amendments to Proposition 13 - Propositions 60 and 90. These amendments allow households headed by an individual over the age of 55 to transfer the implicit tax benefit to a new home. I show that mobility rates of 55-year old homeowners are approximately 25% higher than those of 54 year olds. Second, all these features of the tax law are then incorporated into a household sorting model. The key insight of this model is that because of the property tax law, different potential buyers have different user costs for the same house. The exogenous property tax component of this user cost then works as an instrument for prices. I find that MWTP estimates for housing characteristics are approximately 100% upward biased when the model does not account for the price endogeneity.
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  • Working Paper

    A Unified Framework for Measuring Preferences for Schools and Neighborhoods

    October 2007

    Working Paper Number:

    CES-07-27

    This paper develops a comprehensive framework for estimating household preferences for school and neighborhood attributes in the presence of sorting. It embeds a boundary discontinuity design in a heterogeneous model of residential choice to address the endogeneity of school and neighborhood attributes. The model is estimated using restricted-access Census data from a large metropolitan area, yielding a number of new results. First, households are willing to pay less than one percent more in house prices ' substantially lower than previous estimates ' when the average performance of the local school increases by five percent. Second, much of the apparent willingness to pay for more educated and wealthier neighbors is explained by the correlation of these sociodemographic measures with unobserved neighborhood quality. Third, neighborhood race is not capitalized directly into housing prices; instead, the negative correlation of neighborhood race and housing prices is due entirely to the fact that blacks live in unobservably lower quality neighborhoods. Finally, there is considerable heterogeneity in preferences for schools and neighbors: in particular, we find that households prefer to selfsegregate on the basis of both race and education.
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  • Working Paper

    Location, Location, Location: The 3L Approach to House Price Determination

    May 2004

    Working Paper Number:

    CES-04-06

    The immobility of houses means that their location affects their values. This explains the common belief that three things determine the price of a house: location, location, and location. We use this notion to develop the 3L Approach to house price determination. That is, prices are determined by the Metropolitan Statistical Area (MSA), town, and street where the house is located. This study creates a unique data set based on data from the American Housing Survey (AHS) consisting of small 'clusters' of housing units with information on their housing characteristics and resident characteristics that is merged with census tract-level attributes. We use this data to verify the 3L Approach: we find that all three levels of location are significant when estimating the house price hedonic equation. This indicates that individuals care about their local neighborhood, i.e. the general upkeep of their street and possibly their neighbors' characteristics (cluster variables), a broader area such as the school district and/or the town (tract variables) that account for school quality and crime rates, and the particular amenities found in their MSA.
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  • Working Paper

    An Equilibrium Model of Sorting in an Urban Housing Market: A Study of the Causes and Consequences of Residential Segregation

    January 2003

    Working Paper Number:

    CES-03-01

    This paper presents a new equilibrium framework for analyzing economic and policy questions related to the sorting of households within a large metropolitan area. At its heart is a model describing the residential location choices of households that makes explicit the way that individual decisions aggregate to form a housing market equilibrium. The model incorporates choice-specific unobservables, and in the presence of these, a general strategy is provided for identifying household preferences over choice characteristics, including those that depend on household sorting such as neighborhood racial composition. We estimate the model using restricted access Census data that characterize the precise residential and employment locations of a quarter of a million households in the San Francisco Bay Area, yielding accurate measures of references for a wide variety of housing and neighborhood attributes across different types of household. The main economic analysis of the paper uses these estimates in combination with the equilibrium model to explore the causes and consequences of racial segregation in the housing market. Our results indicate that, given the preference structure of households in the Bay Area, the elimination of racial differences in income and wealth would significantly increase the residential segregation of each major racial group. Given the relatively small fractions of Asian, Black, and Hispanic households in the Bay Area (each ~10%), the elimination of racial differences in income/wealth (or, education or employment geography) spreads households in these racial groups much more evenly across the income distribution, allowing more racial sorting to occur at all points in the distribution ' e.g., leading to the formation of wealthy, segregated Black and Hispanic neighborhoods. The partial equilibrium predictions of the model, which do not account for the fact that neighborhood sociodemographic compositions and prices adjust as part of moving to a new equilibrium, lead to the opposite conclusion, emphasizing the value of the general equilibrium approach developed in the paper. Our analysis also provides evidence sorting on the basis of race itself (whether driven by preferences directly or discrimination) leads to large reductions in the consumption of public safety and school quality by all Black and Hispanic households, and large reductions in the housing consumption of upper-income Black and Hispanic households.
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  • Working Paper

    Interactions, Neighborhood Selection, and Housing Demand

    August 2002

    Working Paper Number:

    CES-02-19

    This paper contributes to the growing literature that identifies and measures the impact of social context on individual economic behavior. We develop a model of housing demand with neighborhood e'ects and neighborhood choice. Modelling neighborhood choice is of fundamental importance in estimating and understanding endogenous and exogenous neighborhood effects. That is, to obtain unbiased estimates of neighborhood effects, it is necessary to control for non-random sorting into neighborhoods. Estimation of the model exploits a unique data set of household data that has been augmented with contextual information at two di'erent levels ('scales') of aggregation. One is at the neighborhood cluster level, of about ten neighbors, with the data coming from a special sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. Tract-level data are available in the Summary Tape Files of the decennial Census data. We merge these two data sets by gaining access to confidential data of the U.S. Bureau of the Census. We overcome some limitations of these data by implementing some significant methodological advances in estimating discrete choice models. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. This can perpetuate income inequality since those with the best opportunities at economic success will cluster together. The results for the housing demand equation are similar to those in our earlier work [Ioannides and Zabel (2000] where we find evidence of significant endogenous and contextual neighborhood effects.
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