Qiang Li Housing Space of Chinese People in 1993 Research question What were the factors that influenced individual s housing space in China in early 1990s Was individual income and employment status economic status individual s education human capital individual s work unit characteristics institutional characteristic or individual s administrative and political status more important in determining one s living condition such as housing space Data China Housing Survey 1993 obtained from Inter University Consortium for Political and Social Research ICPSR Models Dependent variable Space of housing Square meters Quantitative Predictors 1 Income determines housing space regress housing space on income control for number of people living in the house Nominal and Ordinal Predictors 2 Individual s education and employment status determine housing space ANOVA analysis 3 Individual s political affiliation and administrative position determine housing space ANOVA analysis 4 Work unit characteristics nature industry administrative rank and government juris determine one s house spacing 1 Qiang Li Data check 1 For regression analysis check the normality of variables especially the dependent variable The results show that housing space and earnings are highly skewed Therefore I made log transformation to make them normal 2 For ANOVA Analysis check 1 whether the dependent variable is normally distributed in every category within each predictors or 2 whether the sample size of every category is large to make the CLT applicable if the distribution is not exactly normal 3 if largest sample standard deviation is no more than twice the smallest sample The results show that in most cases log transformation of housing space is roughly normally distributed among each category of each predictor and the standard deviation of largest sample is no more than that of the smallest sample Only the variable of industry nature of present work unit has too many categories and each category has small sample size which is not always normally distributed So I exclude it from the ANOVA analysis Analysis and Results 1 Correlation Pearson correlation coefficient between log of housing space and log of earning is 0 07489 which is significant at 0008 level See output 2 Regression Model log of housing space 0 1 number of Cohabiters 2 Log of earnings Error 2 Qiang Li Regression coefficient of log of earning is 05143 and it is significant only at 0467 level R square of the model is only 0772 which means that individual s earning is not a strong predictor of one s housing space See output 3 ANOVA Except employment status the overall test of the predictors of education political affiliation nature of work unit administerial rank of work unit and government juris of work unit are significant which means that both individual s education and party affiliation and work unit related characteristics have significant influence on one s housing space Based on pairwise means comparison test the following list the significant different mean pairs among each predictor 1 Education between college degree and either no formal education or elementary school or high school degrees 2 Political Affiliation between communist party members and those without political affiliation 3 Nature of work Unit between state institutions and state enterprises 4 Administerial rank of work unit between no rank work unit and all other higher rank work units between bureau or higher rank and sector or lower rank work unit 5 Government juris of work unit between central ministries and either municipal bureau municipal company or district company between municipal government and district company between district bureau and district company Conclusion In early 1990s not long after Tian an Men Square Accident in 1989 China still allocated housing through a planned system rather than a market system Even as a fact of today the political reform is still a blurry construction in mind which lags far behind the fast development of economy People are now obviously feeling the nervousness in all kinds of anomy Even the CPC and the elites of China are struggling in 3 Qiang Li themselves on how to balance the conflicting interests of the gainers and the losers so that to maintain the main political constitutions and social well being on the other hand to steadily decrease all kinds of outdated restriction on individual freedom and civil rights In such a situation as a result of the political legacy the excessive control on social life in Mao s era is reflected on the allocation of private spaces Individual s income pure economic status does not have a strong influence on the housing space Most of individuals were still highly organized and controlled by work unit in China at that time and their housing was also allocated through their work unit Thus the characters of work unit matter a lot for one s housing space In addition at that time in China work unit was not simply an economic unit it was rather a political social and administerial unit therefore what really matters was the nature of work unit whether it was state institution or state company the administerial rank of the work unit whether it had a rank or not whether it had the highest rank or not whether it was the governmental juris of work unit or not and whether it was the most centralized or less centralized unit Since some fields then had already been facing the impact of free economy the difference inside or outside of level in or distance from the communist system were important even are no less important today one can experience in other cases work unit Dan Wei in Chinese as a unit on which political economic and all other kinds of controls and resources were centralized and to which individuals had to adhere themselves so that they could make their lives It was also excessively powerful in its functioning in Mao s era since it was the organizer of all aspects of social life 4 Qiang Li SAS Program Dependent Variable V1003 M sq present housing Descriptive Statistic check for distribution proc freq data china tables v1003 run proc univariate plot data china var v1003 run Quantitative Predictors V0618 Present estimate monthly earnings proc univariate plot data china var v0618 run Create cohab Number of people living in present house make log tranformation of housing space and earnings data newchina set china if v0140 then cohab 1 if v0147 then cohab 2 if v0203 then cohab 3 if v0210 then cohab 4 if v0217