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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.

Housing policy, as well as academic research, are increasingly concerned with the role of bias in subjective dwelling valuations as a proximate measure of households’ house price expectations and their relationship with housing demand. This paper contributes to this area of study by exploring the possibility of simultaneous relationships between households’ price expectations and incentive to maximise the size of housing services demanded also accounting for the supply side factors and regional perspective. The empirical estimation takes the form of a system of a two simultaneous equations model applying two stage least squares estimation technique. Cross sectional estimations utilise data extracted from the Israeli Longitudinal Panel Survey (LPS) data. Applying the best available proxy for households’ price expectations, calculated as the ratio between subjective dwelling valuations (LPS) and the estimated market value of the same properties, research has identified the interrelated factors that simultaneously influence householders’ price expectations and housing demand. Results offer conceptual and empirical advantages, highlighting the imperfect nature of the housing market, as reflected by the inseparability of bias in subjective valuations and housing decisions.

This paper aims to develop and test a valid and reliable methodology to explore residents' attitudes toward religious composition of their neighborhood, by integrating traditionally used survey data with administrative data, and collaborative Geographic Information System (GIS) techniques. The main research question is whether residents perceive changes in the religious composition of their neighborhood in relation to their personal religiosity. Focusing on the Jewish population, we compared residents' subjective assessment of changes in the religious composition of their neighborhood, obtained from Israel's 2009 Social Survey, with actual changes in the percentage of residents with differing degrees of religiosity. Using a specifically designed methodology, we found that the two groups on the extreme ends of the religious spectrum (ultraorthodox and nonreligious) are the keenest observers of changes in the religious composition within their neighborhoods. Subjective perception of the dynamics of neighborhood religious composition was found to be systematically associated with neighborhood satisfaction, individual traits, dwelling, and neighborhood characteristics. Using spatially dependent analysis, we also examined mutual relationships between the religious composition, both actual and perceived, of census tracts, based on distances between those geographic areas.