|M.Sc Student||Elena Taha )Groisman(|
|Subject||Housing as a Measure of Wealth Inequality|
|Department||Department of Industrial Engineering and Management||Supervisor||Dr. Baron Mira|
|Full Thesis text - in Hebrew|
Reliable measurement of economic inequality among people is important for comparison over time or comparison between nations. A problem in measuring inequality is that in most cases we measure income inequality, though wealth inequality is a better criterion for comparing individuals and populations. Measuring total wealth is most difficult or even impossible. If we look at the components of wealth, we can see that for households with medium-low income, housing is the major component in their wealth. So, the question raised in this thesis, can the value of housing be a proxy for wealth. The following hypotheses were examined: is there connection between the apartment value and socio-economic characteristics; is there similar relationship between income and socio-economic characteristics as between value of housing and socio-economic characteristics; is it possible to examine inequality in wealth through the examination of inequality in housing. We examined the impact of socio-economic characteristics separately on income and on value of housing. The results show that there is similarity in the impact of each characteristic on the value of housing and on income. During the next stage of the work we examined which variables we will include in the model of multiple regressions in order to examine the impact on housing and income. We examined the whole population with the dependent variable income. We examine which socio-economic variables affect significantly income. We repeated the analysis and examined the socio-economic characteristics which affect homeowners’ income. Following the results of the analysis we cannot reject the hypothesis that income is affected by socio-economic characteristics .According to the analysis the conclusion is that we can use homeowners as a statistical sample. We ran a regression model with the same explanatory variables, but the dependent variable is the apartment value. We conclude that the apartment value is a function of similar socio-economic characteristics as the ones affecting income. From the analysis we conclude that there is similar relation between income and socio-economic characteristics and home value and socio-economic characteristics, and it is possible to examine inequality in wealth by examining the inequality in housing .Using this conclusion, we examined inequality by calculating Gini Index. There is a greater inequality if examination is done for the whole population than inequality in the incomes of homeowners. In addition, there is a smaller inequality if examination is done according to the value of housing. We will deduct that there is a smaller inequality in housing value than in the incomes of the general population.