Satisfaction Levels of Ethnic Groups in the UK - Paper Example

There is an increasing body of evidence that shows levels of household satisfaction is an important dimension of wellbeing (Battu and Zenou, 2010; Schmid et al., 2013; Hewstone and Schmid, 2014). According to Kahneman and Krueger (2006), life satisfaction is linked to immediate life experience as well as subsequent outcomes such as differences in risks of morbidity and mortality. Consequently, the monitoring and evaluation of satisfaction levels are now regarded as an important policy objective and a subject of extensive academic research (e.g., Layard, 2005). Therefore, satisfaction levels are an essential outcome and potential source of inequalities across ethnic groups. Various characteristics such as employment, income, social resources, and health are correlated with levels of satisfaction, and may as such contribute to peoples evaluations of their wellbeing (Bobowik et al., 2015). The literature suggests that even controlling for such relevant aspects of inequalities, ethnic inequalities among minority groups relative to the majority persist (Knies, Nandia, and Platt, 2016).

The aim of the present research was to find out whether satisfaction levels of households differ by ethnic groups and the potential factors contributing to levels of satisfaction. In order to achieve this aim, the following research questions were used to guide the process:

How does household satisfaction levels of white people compare with those of minorities in the UK?

How does gender, ethnicity, locality, and class affect the satisfaction levels of ethnic groups in the UK?

Based on these questions, it is hypothesized that:

Research Question 1

H0: White people would be more satisfied with their household than the other minorities

H1: White people would not be more satisfied with their household than the other minorities

H0: There is a statistical difference between the different ethnic groups and satisfaction with accommodation

H1: There is no statistical difference between the different ethnic groups and satisfaction with accommodation

Research Question 2

H0: gender, ethnicity, locality, and class positively affect the satisfaction levels of ethnic groups

H1: gender, ethnicity, locality, and class negatively affect the satisfaction levels of ethnic groups

Methods

This study uses the English Housing Survey (2012-2013), which covers a wide range of themes such as housing needs, housing moves, and vulnerable and disadvantaged groups (The United Kingdom Statistics Authority, 2014). The English Housing Survey is concerned with the people's housing circumstances in England. In this study, the dependent (outcome) variable was satisfaction with accommodation. The independent variable was ethnicity (White/ Black/ Asian/ other) while the annual gross income is used as the controlling variable. The independent variable was dummy coded into 1 (Whites) and 0 (non-Whites) to differentiate the satisfaction levels between the majority who are the Whites and the minorities (non-whites). The limitation of such dummy coding for the present study is that it does not provide the opportunity to investigate satisfaction levels among individual ethnic groups.

Descriptive statistics make it easier to understand complex data in a simpler way. The Raw English Housing Survey (2012-2013) data is hard to visualize because the data is plenty. Descriptive statistics are performed in the form of univariate analysis, which involves the estimation of the measures of central tendency, distribution, and dispersion. Measures of central tendency include the estimation of the mean, mode, and median values of the data. Measures of dispersion/ spread that include standard deviation, variance, and range describe how spread out or dispersed the scores are. Measures of dispersion help us visualize how spread out the scores of the population is. In some cases, we would want to understand the distribution of scores or skewness of the data. The descriptive analyses in this study are applied to the demographic characteristics of the sample as well as the independent variables. On the other hand, inferential statistics look beyond the immediate group of data in order to reach conclusions. The simplest inferential analysis used in this study (ANOVA) involves the measures of significance testing or hypothesis testing using the t-test analysis (comparing the average performance of two groups to determine their differences). Regression analysis is run to help observe trends and to predict satisfaction based on the independent variable (ethnicity).

Results

A total of 13,652 people participated in the survey. Out of the 13,652, 57.6% were male while 42.4% were female participant. Most of the household representatives were over 45 years of age. The majority were predominantly White (90.01%) followed by Asians (4.67%), Blacks (2.97%), and Others (2.34%). In addition, 46.76% were in full-time work, 28.98% were retired, 9.87% in part-time employment, 4.15% unemployed, 1.12% in full time education, and 9.13% were inactive. The average Household gross annual income (inc. income from all adult household members) was 32691.62 23475.06. The most common household type was couples with no dependent children (34.5%) while couples with dependent children were 21.1% (Annex Table). More than half of the respondents had 1 or 2 persons in the household (Annex Table). Overall, 89.9% of the participants said that they were either very or fairly satisfied while 6.4% mentioned they were either slightly or very dissatisfied with their accommodation. 3.7% were neither dissatisfied nor satisfied with their accommodation (Annex Figure).

Cross-tabulation between ethnicity and satisfaction scores shows that the overwhelming majority who were either very or slightly satisfied were Whites (see Figure 1). In addition, the Chi-Square tests indicate a statistically significant relationship between ethnicity and satisfaction (p<0.05). The null hypothesis that a statistical difference between the different ethnic groups and satisfaction with accommodation exist is accepted.

Chi-Square Tests

Value dfAsymp. Sig. (2-sided)

Pearson Chi-Square 3.095E2a 12 .000

Likelihood Ratio 271.334 12 .000

Linear-by-Linear Association 173.032 1 .000

N of Valid Cases 13510 a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 7.53.

An independent sample test was conducted to determine how satisfaction levels among the Whites compared with those of the non-Whites. The results show that White people are more satisfied with their household than the other minorities in the UK. The null hypothesis is thus accepted.

Table 2: Independent Samples Test

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means

F Sig. t dfSig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference

Lower Upper

Satisfaction with accommodation Equal variances assumed 34.009 .000 -15.872 13508 .000 -.417 .026 -.468 -.365

Equal variances not assumed -13.150 1.513E3 .000 -.417 .032 -.479 -.354

A multiple linear regression was performed to determine whether a variety of independent variables positively predicted the satisfaction levels of ethnic groups in the UK with regard to their accommodation. The results show that collectively gender, ethnicity, rurality classification, gross annual income, householder's view on property value, and employment status positively predicted the satisfaction levels (F(6, 6415) = 48.885, p < 0.05). However, only ethnicity (p=0.000), householder's view on property value (p=0.000), and employment status (p=0.000) were statistically significant predictors of satisfaction with accommodation (Table 3).

Table 3: Multiple regression analysis

CoefficientsaModel Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta 1 (Constant) 1.505 .043 34.677 .000

Sex of household reference person .009 .018 .007 .527 .598

Ethnic origin of HRP - 4 categories .117 .016 .091 7.442 .000

Rurality classification - morphology (COA) -.019 .011 -.021 -1.666 .096

Household gross annual income (inc. income from all adult household members) 1.552E-7 .000 .006 .368 .713

Householder's view on property value -7.006E-7 .000 -.173 -12.276 .000

Employment status (primary) of HRP -.038 .008 -.066 -4.875 .000

a. Dependent Variable: Satisfaction with accommodation Discussion

This study is in agreement with various previous work suggesting that levels of household satisfaction is linked to various factors (Kahneman and Krueger, 2006; Battu and Zenou, 2010; Schmid et al., 2013; Hewstone and Schmid, 2014). These factors which include employment, income, social resources, and health play a significant role in the immediate life experience as well as their subsequent wellbeing. Therefore, it is important to continuously measure satisfaction levels since they are an essential outcome and potential source of inequalities across ethnic groups (Bobowik et al., 2015). The limitations of this study include using outdated data (2012-2013). In addition, the outcome variable (satisfaction) may be subjective which may affect the reliability of the findings. In addition, not every external factor could be accounted for in the present study.

References

Battu, H., & Zenou Y. 2010. Oppositional identities and employment for ethnic minorities: evidence from England. Econ. J., 120, pp. F52-F71;

Bobowik et al., 2011. Personal values and well-being among Europeans, Spanish natives and immigrants to Spain: does the culture matter? J. Happiness Stud., 12 (2011), pp. 401-419

Kahneman, D& Krueger, B. (2006). Developments in the measurement of subjective well-being J. Econ. Perspect., 20 (1), pp. 3-24;

Schmid, K., Hewstone, M & Ramiah, A . 2013. Neighborhood diversity and social identity complexity implications for intergroup relations. Soc. Psychol. Personal. Sci., 4 (2), pp. 135-142;

Appendix

Sex of household reference person

Frequency Percent Valid Percent Cumulative Percent

Valid male 7868 57.6 57.6 57.6

female 5784 42.4 42.4 100.0

Total 13652 100.0 100.0

Statistics

Household gross annual income (inc. income from all adult household members)

N Valid 13652

Missing 0

Mean 3.2692E4

Median 2.6258E4

Mode 1.00E5

Std. Deviation 2.34751E4

Variance 5.511E8

Skewness1.221

Std. Error of Skewness.021

Kurtosis .978

Std. Error of Kurtosis .042

Minimum 2925.00

Maximum 1.00E5

Household type - 6 categories

Frequency Percent Valid Percent Cumulative Percent

Valid couple, no dependent child(ren) 4708 34.5 34.5 34.5

couple with dependent child(ren) 2878 21.1 21.1 55.6

lone parent with dependent child(ren) 1152 8.4 8.4 64.0

other multi-person households 1044 7.6 7.6 71.7

one person under 60 1680 12.3 12.3 84.0

one person aged 60 or over 2190 16.0 16.0 100.0

Total 13652 100.0 100.0 Number of persons in the household

Frequency Percent Valid Percent Cumulative Percent

Valid 1 3870 28.3 28.3 28.3

2 4831 35.4 35.4 63.7

3 2211 16.2 16.2 79.9

4 1827 13.4 13.4 93.3

5 645 4.7 4.7 98.0

6 185 1.4 1.4 99.4

7 56 .4 .4 99.8

8 19 .1 .1 99.9

9 6 .0 .0 100.0

10 or more 2 .0 .0 100.0

Total 13652 100.0 100.0