Housing Prices and Housing Preferences in Israel

Borukhov, Eli; Ginsberg, Yona; Werczberger, Elia

doi:10.1080/00420987820080311

Cited by 5 publications

(5 citation statements)

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“…No reliable data are available on the proportion of government-sponsored units in the housing stock of the Tel-Aviv metropolitan area. Between 1963 and 1973, the proportion of publicly built units has fallen from 43% to 22% (Borukhov et al, 1978).…”

Section: Resultsmentioning

confidence: 99%

The Social Ecology of Tel-Aviv

Borukhov

Ginsberg²,

Werczberger³

1979

Urban Affairs Quarterly

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This article analyzes the urban ecology of the Tel Aviv metropolitan area using data from the 1972 census. The method used is factor analysis. The following factors are identified: (a) socioeconomic status: distributed along radial sectors; (b) life cycle stage: differentiated according to concentric zonal pattern; (c) religious orthodoxy: mostly concentrated in one of the suburban towns. A fourth factor whose interpretation is not clear appears to be associated with crowded housing conditions.

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Section: Resultsmentioning

confidence: 99%

The Social Ecology of Tel-Aviv

Borukhov

Ginsberg²,

Werczberger³

1979

Urban Affairs Quarterly

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“…Differences between towns would be reflected in differences in the coefficients in the regression equation: as Ball (1973: 230) says, 'There are a number of reasons why the choice of city will affect all coefficients in the house-price equation'. (Compare the way in which multiple regression has been used or recommended by Richardson et al, 1974;Grether and Mieszkowski, 1974;Mark9 1977;Borukhov et al, 1978). Two statistical methods have been used (although the results of only one of them are reported here)~ and it is important to realize that each method is applied for a different purpose.…”

Section: Some Remarks About the Methods Usedmentioning

confidence: 99%

A model of house prices in a Dutch city

1987

Neth. J. of Housing and environment Res.

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“…There has been a tremendous amount of literature on the use of hedonic price regression to analyze determinants of housing prices since then and therefore, it is impossible to mention all of them here. Some of these studies include: Lancaster (1966), Ridker and Henning (1967), Ball (1973), Borukhov et al (1978), Goodman (1978), Follain and Malpezzi (1980), Mendelsohn (1984), Bover et al (1989), Arimah (1992), Malpezzi (1998), Cheshire and Sheppard (1998), Bover and Velilla (2002), Mok et al (1995), Song and Shon (2007), Gao et al (2006), Gao and Asami (2007). These studies are conducted within multiple regression analysis frameworks and employed as many variables as possible to capture main determinants of housing prices in different countries and in different regions.…”

Section: Literature Reviewmentioning

confidence: 99%

Housing price determinants in Istanbul, Turkey

Özsoy

Şahin

2009

International Journal of Housing Markets and Analysis

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PurposeThe purpose of this paper is to analyze empirically major factors that affect housing prices in Istanbul, Turkey using the classification and regression tree (CART) approach.Design/methodology/approachThe data set was collected from various internet pages of real estate agencies during June 2007. The CART approach was then applied to derive main results and to make implications with regard to the housing market in Istanbul, Turkey.FindingsThe CART results indicate that sizes, elavators, existance of security, existance of central heating units and existance of view are the most important variables crucially affecting housing prices in Istanbul. The average price of houses in Istanbul was found to be 373,372.36 New Turkish Liras. The average size of a house was 138.37 m2. The average age of houses is 15.07 years old with the average number of rooms being 3.11. The average number of baths is 1.43 and average number of toilets is 1.22. Only 5 percent of homes have storage space, 45 percent of homes have parking space, 64 percent of homes are heated with furnace, whereas only 29 percent of homes are used central heating system. Among the 31 variables employed in this study, it was concluded size, elavator, security, central heating unit and view are the most important factors that have impact on housing prices in housing market in Istanbul.Practical implicationsFuture research and analysis of housing market in Istanbul and in Turkey can benefit from the method used in this study and findings derived from this research to come up with more general model(s) to include more houses in a wide range of regions in Turkey to analyze the determinants of housing prices in Turkey in general.Originality/valueExamining housing prices using the CART model is relatively new in the field of housing economics. Additionally, this study is the first to use the CART model to analyze housing market in Istanbul and in Turkey and derive valuable housing policies to be used by the authorities.

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Housing Prices and Housing Preferences in Israel

Cited by 5 publications

References 0 publications

The Social Ecology of Tel-Aviv

The Social Ecology of Tel-Aviv

A model of house prices in a Dutch city

Housing price determinants in Istanbul, Turkey

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