Well-being – Comparing Economic Variables with Survey Data

Well-being – Comparing Economic Variables with Survey Data

Prepared by Aiysha Mirza, CMR Group
 

Introduction

As part of a project to compare measures of personal well-being and economic data, we are looking to test the validity/relevance of the current topics of questioning and how extensive the current measures are. We analyse this using information on the changes and trends of the main personal and economic well-being measures often measured quarterly. The data for this report is sourced from ONS’s report “Personal and economic well-being dashboard of indicators” released in September 2020.
 

Objective

The objective of this report is to compare well-being and economic variables and find the relationship between them. The end goal is to help evaluate a wide range of topics which underlie concepts of well-being so that we can assess our current measures of well-being.
 

Method

We find the relationship of these variables by using correlations. All correlations are calculated using the function in excel with a percentage format. A score of 100% indicates a perfect positive correlation, a -100% indicates a perfect negative correlation and a value near 0% indicates no correlation.
 

Results – Personal Well-Being

First, we are comparing personal well-being. Variables that all have a very high correlation are low life satisfaction, low worthwhile and low happiness. All these variables significantly correlate with each other.

Correlation Values	Variable 1	Variable 2	Significance Level
96.3%	low life satisfaction	low worthwhile	99%
95.5%	low life satisfaction	low happiness	99%
91.1%	low worthwhile	low happiness	99%

High anxiety has the lowest correlation with all the personal well-being variables, the correlation with low happiness being the lowest. Note that it is still significant.

Correlation Values	Variable 1	Variable 2	Significance Level
59.4%	low worthwhile	high anxiety	99%
55.3%	low life satisfaction	high anxiety	99%
52.7%	low happiness	high anxiety	99%

 

Results – Introducing Economic Variables

Now we introduce economic variables in relation to the personal well-being variable of high anxiety. These seem to have quite low correlation except when we compare high anxiety and debt to income ratio.

Correlation Values	Variable 1	Variable 2	Significance Level
58.9%	debt to income ratio	high anxiety	99%
-37.9%	aggregate balance	high anxiety	95%
22.6%	unemployment rate	high anxiety	80%

Correlations between personal well-being data and economic data show the relationship between wealth and satisfaction. Low life satisfaction has significant correlations with unemployment rate, debt to income ratio, aggregate balance etc.

Correlation Values	Variable 1	Variable 2	Significance Level
91.2%	debt to income ratio	low life satisfaction	99%
-89.0%	aggregate balance	low life satisfaction	99%
88.4%	unemployment rate	low life satisfaction	99%

Comparing more well-being and economic data shows the correlation between unemployment rate and low happiness seems to be particularly high

Correlation Values	Variable 1	Variable 2	Significance Level
91.5%	unemployment rate	low happiness	99%
90.8%	debt to income ratio	low worthwhile	99%
-88.4%	aggregate balance	low happiness	99%
-87.7%	aggregate balance	low worthwhile	99%
87.4%	debt to income ratio	low happiness	99%
82.1%	unemployment rate	low worthwhile	99%

 

Results – Comparing Economic Variables

Here we compare economic data. Real Gross Household Disposable Income per head (RHDI), Real Net National Disposable Income (RNNDI) and spending per head notably correlate with each other.

Correlation Values	Variable 1	Variable 2	Significance Level
95.5%	RNNDI per head	spending per head	99%
93.7%	RHDI per head	spending per head	99%
90.5%	RHDI per head	net wealth per head	99%
88.4%	net wealth per head	spending per head	99%
87.2%	RHDI per head	RNNDI per head	99%
81.6%	RNNDI per head	net wealth per head	99%

 

Conclusion

There is very clearly high correlation between personal well-being and economic variables supporting a strong relationship between financial security, wealth, and mental health. In terms of variables with high correlation, such as low life satisfaction and low worthwhile, an argument can be made that not both variables need to be surveyed as they measure similar things.

We do have to keep in mind that these variables could have different correlations at the micro level, for example a particular demographic may have a lower correlation between low life satisfaction and low worthwhile than others. In this case it would be beneficial to keep both variables with a demographic breakdown.