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Three Essays On Urban Economics and Housing Finance

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This dissertation consists of three essays on urban economics and housing finance. The three essays are related to the standard urban model, housing price gradient shift, urban structure changes, total return to housing, and effect of housing wealth shocks on household consumption. Chapter 1 provides direct evidence documenting shifts of the asset and rental price gradients, and develops reasons for the steepening of the house price gradient using the standard urban model. Chapter 2 discusses specific properties of the relation among the rental and asset return components of the total return to housing using the estimates of these rates across US MSAs, and empirically tests the effects of housing wealth shocks on consumption by constructing shocks to total housing return, as well as its division between capitalization and asset appreciation rates. Chapter 3 compares constant-quality inter-area housing price indices using alternative data sets to construct both asset and rental price indices for 35 MSAs over 1985-2013 using the AHS, and 2337 PUMAs over 2005-2019 using the ACS. Alonso (1964), Mills (1967) and Muth (1969) formalized the monocentric standard urban model (SUM) and demonstrated that price and density gradients characterize differences in urban structure. Subsequent literature concentrated on changes in the population density or the housing asset price gradients. The rental price gradient has been ignored. Chapter 1 adds to the literature by providing direct evidence documenting shifts of both asset and rental price gradients. The rental and asset price gradients are found to behave differently over the 1985 to 2013 period studied. Possible reasons for the steepening of house price gradient are then developed using the standard urban model (SUM) and tested empirically. Asset price gradient steepening is positively associated with the rising congestion cost and dwelling age. MSAs with larger housing units and higher income tend to have a smaller rental price gap between the center city and the suburbs.The total return to housing is properly measured as the sum of its rental and asset appreciation returns. Housing wealth shocks should be based on total return but the literature often ignores rental return. Chapter 2 discusses specific properties of the relation between the two components of total return using the estimates of these rates across US metropolitan areas. Im-Pesaran-Shin panel unit root tests and augmented Dickey-Fuller regressions demonstrate that asset appreciation returns differ by location and there is persistence in differences. Beyond demonstrating the problem with treating differences in asset appreciation return as shocks, Chapter 2 constructs measures of shocks to total housing return. Empirical tests following the Case-Quigley-Shiller framework show that the effect of housing return shocks on consumption is much larger when measured using total return rather than just appreciation. If shocks to total return to housing are the basis of consumption effects, they may be important to understanding other household responses to housing wealth. There are large differences in cost-of-living across cities due to the differences in housing prices, taxes and amenities. An accurate measurement of quality-adjusted place-to-place indices of housing prices is important. Chapter 3 reports the production of constant-quality place-to-place housing price indices based on the hedonic estimation method to construct a panel data set of asset and rental price indices for 35 MSAs over 1985-2013 using the AHS, and 2337 PUMAs over 2005-2019 using the ACS. A comparison of the information in the two data sets is made and then a statistical comparison of ability to explain housing price variation is conducted. Finally an application of the newly constructed quality-adjusted housing price indices on measuring housing market inflation is discussed. A Laspeyres index, a Paasche index, and a Fisher index are produced using the AHS and the ACS for the time period of 2005-2013 on MSA level.

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