000			01573naa a2200181uu 4500
001			0121514200537
003			OSt
005			20190211174159.0
008			101215s2010 xx ||||gr |0|| 0 eng d
100	1		_aNELSON, Ashlin Aiko _943402
245	1	0	_aCredit scores, race, and residential sorting
260			_aHoboken : _bWiley-Blackwell, _cWinter 2010
520	3		_aCredit scores have a profound impact on home purchasing power and mortgage pricing, yet little is known about how credit scores influence households' residential location decisions. This study estimates the effects of credit scores on residential sorting behavior using a novel mortgage industry data set combining household demographic, credit, and financial data with property location information and detailed community attribute data. I employ the data set to estimate a discrete-choice residential sorting model. I find that credit scores significantly predict residential sorting behavior and models that do not account for credit score provide biased estimates of housing utilities for black households in particular. Simulation results show that increases in credit score are associated with increases in the consumption of higher-priced homes in more expensive school districts, higher-quality public schools, and proximity to urban/metropolitan areas
773	0	8	_tJournal of Policy Analysis and Management _g29, 1, p. 39-68 _dHoboken : Wiley-Blackwell, Winter 2010 _xISSN 02768739 _w
942			_cS
998			_a20101215 _b1420^b _cDaiane
998			_a20110118 _b1711^b _cCarolina
999			_aConvertido do Formato PHL _bPHL2MARC21 1.1 _c37782 _d37782
041			_aeng