Academic journal article AEI Paper & Studies

The Price of Residential Land for Counties, ZIP Codes, and Census Tracts in the United States

Academic journal article AEI Paper & Studies

The Price of Residential Land for Counties, ZIP Codes, and Census Tracts in the United States

Article excerpt

1 Introduction

Researchers have taken to describing a single-family house as a physical structure occupying some land: See Bostic, Longhofer, and Redfearn (2007), Davis and Heathcote (2007) and Davis and Palumbo (2008), for example. Because housing structures are infrequently renovated and construction costs change relatively slowly from year to year, rapid change in the value of housing typically occurs when the underlying land is appreciating or depreciating. For this reason, the housing boom and bust of 1998-2012 has been described as a land boom and bust (Davis, Oliner, Pinto, and Bokka, 2017).

Although the importance of studying and monitoring the price of land currently in residential use is now well understood, until recently few studies have produced data on land prices at a relatively fine level of geography. Broadly speaking, researchers have used one of two methods to estimate the price of land in current residential use. Both of these methods require data that have been, until recently, hard to acquire. The first method uses data from sales of vacant or near-vacant land. Three examples of the first method are Haughwout, Orr, and Bedoll (2008), Nichols, Oliner, and Mulhall (2013) and Albouy, Ehrlich, and Shin (2018). These authors all use data from the CoStar Group, Inc. Haughwout, Orr, and Bedoll (2008) estimate the price of land inside the New York metro area; Nichols, Oliner, and Mulhall (2013) produce price indexes for land for 23 metro areas; and Albouy, Ehrlich, and Shin (2018) estimate land values for all urban land in nearly all metropolitan areas in the United States.

The second method measures the price of land as the difference between house value and the replacement cost of the structure on the land. Davis and Palumbo (2008) apply this method to data from the American Housing Survey to generate the average price of land for 46 metro areas. Davis, Oliner, Pinto, and Bokka (2017) use proprietary data on house prices and construction costs from a number of sources to generate the level of land prices and changes in land prices at the ZIP code level for the Washington, DC metropolitan area. (2)

In this paper, we use a huge database of home appraisals to produce annual panel data for the price of land in single-family residential use for 964 counties, 8,344 ZIP codes, and 11,494 census tracts over the 2012 through 2017 period. Land prices are estimated for areas representing more than 85% of the U.S. population and 83% of all single-family homes homes. (3) To our knowledge, ours is the first study to produce these estimates at a fine geography for nearly the entirety of the United States. (4) Our source data are the Uniform Residential Appraisal Report submissions to the Government Sponsored Enterprises (GSEs), Fannie Mae and Freddie Mac. These reports are required by the GSEs before they guarantee a mortgage against default. These data contain more than 16 million unique appraisals submitted between 2012 and 2018.

Our raw estimates of land values in this data set are based on "cost-approach" appraisals; we set land value equal to the appraised value of the house less an estimate of depreciated replacement cost of the housing structure. (5) A common concern about this residual method of estimating land values is that it assumes that the sum of the replacement cost of the housing structure and the value of the land (if it were vacant) is equal to the value of housing. This is not true when the market value of the structure is below its replacement cost, as would be the case when a housing structure has become functionally obsolete and is due to be torn down or extensively remodeled, or when housing demand has fallen dramatically and construction activity in the area has ceased (see Glaeser and Gyourko, 2005). To address this issue, we calibrate a simple option model for tearing down and rebuilding a house. Simulations of the calibrated model suggest that the value of housing is well approximated as the sum of the replacement cost of the structure and the market value of the land if vacant for at least the first 10 years of the life of the structure. …

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