Explaining metropolitan housing price differences

Ozanne, Larry; Thibodeau, Thomas G.

doi:10.1016/0094-1190(83)90045-1

Cited by 115 publications

(67 citation statements)

References 5 publications

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“…Earlier studies show a significant positive correlation between the three major factors characterizing the residential area's socioeconomic level -income, education and employment -and the price of dwellings (Heikkila 1992;Potepan 1996;Goodman and Thibodeau 1998;Greenberg 1999;Des Rosiers et al 2002;Yates 2002). Income is considered the primary factor (Ozanne and Thibodeau 1983;Malpezzi et al 1998). Those with relatively high incomes choose their residential area in an attempt to avoid neighbors with a low socioeconomic status.…”

Section: Dwelling Price In Light Of Socioeconomic Level Characteristicsmentioning

confidence: 99%

Dwelling Price Ranking versus Socioeconomic Clustering: Possibility of Imputation

Fleishman¹,

Gubman²,

Tur‐Sinai³

2015

Journal of Official Statistics

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In order to characterize the socioeconomic profile of various geographic units, it is common practice to use aggregated indices. However, the process of calculating such indices requires a wide variety of variables from various data sources available concurrently. Using a number of administrative databases for 2001 and 2003, this study examines the question of whether dwelling prices in a given locality can serve as a proxy for its socioeconomic level. Based on statistical and geographic criteria, we developed a Dwelling Price Ranking (DPR) methodology. Our findings show that the DPR can serve as a good approximation for the socioeconomic cluster (SEC) calculated by the Israel Central Bureau of Statistics for years when the required data was available. As opposed to the SEC, the suggested DPR indicator can easily be calculated, thus ensuring a continuum of socioeconomic index series. Both parametric and nonparametric statistical analyses have been carried out in order to examine the additional social, demographic, location, crime and security effects that are exogenous to SEC. Complementary analysis on recently published SEC series for 2006 and 2008 show that our conclusions remain valid. The proposed methodology and the obtained findings may be applicable for different statistical purposes in other countries which possess dwelling transactions data.

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Section: Dwelling Price In Light Of Socioeconomic Level Characteristicsmentioning

confidence: 99%

Dwelling Price Ranking versus Socioeconomic Clustering: Possibility of Imputation

Fleishman¹,

Gubman²,

Tur‐Sinai³

2015

Journal of Official Statistics

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“…For example, Ozanne and Thibodeau [26] found positive impacts of both income and number of household on area rents (but not as substantial evidence with respect to home prices). Appelbaum [3] also reported higher home prices and rents in rapidly growing Cities.…”

Section: The Effects Of Growth Upon Local Inflation Ratesmentioning

confidence: 96%

The effects of growth upon local inflation rates

Hogan

1988

Ann Reg Sci

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This paper investigates the impact of regional growth upon the local rate of consumer inflation. To capture both the temporal and spatial aspects in the study, a pooled time-series/cross-section approach was used. The analysis is based upon 1965-82 data for the 22 metropolitan areas for which the U.S. Bureau of Labor Statistics compiled CPI series. With a model specifying local inflation to be primarily determined by national trends but also influenced by local conditions, both area population and income growth were identified as positively related to local inflation rates. Using disaggregated price series, the effects of population growth were found to work solely through impacts upon the housing sector. The econometric procedures were performed upon the A~U IBM 3090 computer system using the SAS PROC TSCS.

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“…Moreover, the constant quality, assumption is very storong as houses undergo changes in characteristics over taime and a combined index calld hybrid index which combines advantages of hedonic and repeat sale index been developed and well estabished (Case and Quigley, 1995;Case, Pollakowski, and Wachter, 1991;Quigley, 1995;Englund, Quigley and Redf earn, 1998;and Hill et al, fothcoming focussed on explanations to regional price differences was made by Ozanne and Thibodeau (1983). Price differences have an income effect.…”

Section: House Price Index Methodology Reviewmentioning

confidence: 99%

Intra-Metropolitan House Price Movements: An Analysis of Stockholm 1981-1993

Tiwari¹,

Turner²

2000

SiRS, SRS

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The present paper highlights the importance of house price index methodology and relevance of studying price indices within a metropolitan region. Two approaches based on hedonic approach have been compared. Though the results are inconclusive as to whether explicit time variable hedonic approach is superior to cross section hedonic approach or vice versa but there are evidences that would suggest that cross section approach is better. The results are compared with indices developed by other methodologies like improved repeat sales method and official methodology of SCB. The index obtained by us are very similar to others but the quarterly price increases as calculated by us lags the other two. This paper further tries to explain the intra-metropolitan price variations based on population , employ ment and tenureship trends. A ripple effect is also noticed where the prices in one zone leads the others .

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Explaining metropolitan housing price differences

Cited by 115 publications

References 5 publications

Dwelling Price Ranking versus Socioeconomic Clustering: Possibility of Imputation

Dwelling Price Ranking versus Socioeconomic Clustering: Possibility of Imputation

The effects of growth upon local inflation rates

Intra-Metropolitan House Price Movements: An Analysis of Stockholm 1981-1993

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