東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Essays on Housing Space Analysis.

Liu, Yishen.

FindBook

Google Book

Amazon

博客來

Essays on Housing Space Analysis.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Essays on Housing Space Analysis./
作者:	Liu, Yishen.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	115 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-08(E), Section: A.
Contained By:	Dissertation Abstracts International77-08A(E).
標題:	Economic theory. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10090272
ISBN:	9781339596006

Essays on Housing Space Analysis.
Liu, Yishen.

Essays on Housing Space Analysis. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 115 p.

Source: Dissertation Abstracts International, Volume: 77-08(E), Section: A.

Thesis (Ph.D.)--The George Washington University, 2016.

This dissertation demonstrates that the standard urban model (SUM) has important, previously unknown, and rather counterintuitive predictions about the determinants of housing consumption in cities. For example, the SUM predicts that, as higher wages in the CBD prompt city growth, the housing space per household falls, i.e. rising income is associated with falling housing consumption. Empirical testing using a specially constructed panel dataset of U.S. cities, confirms this prediction. When city size, income, and housing price rise, housing space per household falls.

ISBN: 9781339596006Subjects--Topical Terms:

1556984
Economic theory.

Essays on Housing Space Analysis.
LDR:02530nmm a2200301 4500 001 2117338
005 20170516070335.5
008 180830s2016 ||||||||||||||||| ||eng d
020 $a 9781339596006
035 $a (MiAaPQ)AAI10090272
035 $a AAI10090272
040 $a MiAaPQ $c MiAaPQ
100 1 $a Liu, Yishen. $3 3279110
245 1 0 $a Essays on Housing Space Analysis.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 115 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-08(E), Section: A.
500 $a Adviser: Anthony M. Yezer.
502 $a Thesis (Ph.D.)--The George Washington University, 2016.
520 $a This dissertation demonstrates that the standard urban model (SUM) has important, previously unknown, and rather counterintuitive predictions about the determinants of housing consumption in cities. For example, the SUM predicts that, as higher wages in the CBD prompt city growth, the housing space per household falls, i.e. rising income is associated with falling housing consumption. Empirical testing using a specially constructed panel dataset of U.S. cities, confirms this prediction. When city size, income, and housing price rise, housing space per household falls.
520 $a Virtually all research on urban housing supply uses the number of housing units as a measure of housing output. Supply differences among cities are based on changes in the number of units as housing price changes. Microeconomic models of the housing market treat housing units as heterogeneous combinations of attributes producing housing services. Logically the supply of housing services should be measured by aggregating housing services rather than units.
520 $a The dissertation focuses on measuring housing services as square feet of interior space and provides insights in understanding the spatial and temporal variations in housing space. It demonstrates the consequences of conducting housing market analysis based only on housing units instead of housing space. In addition, the theoretical literature has developed many propositions about the determinants of total housing units in cities but neglected propositions regarding the total supply of housing services. The theoretical component of this dissertation therefore fills the gap in the literature as well.
590 $a School code: 0075.
650 4 $a Economic theory. $3 1556984
690 $a 0511
710 2 $a The George Washington University. $b Economics. $3 1020291
773 0 $t Dissertation Abstracts International $g 77-08A(E).
790 $a 0075
791 $a Ph.D.
792 $a 2016
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10090272