Empirical Project 8 Solutions
These are not model answers. They are provided to help students, including those doing the project outside a formal class, to check their progress while working through the questions using the Excel, R, or Google Sheets walk-throughs. There are also brief notes for the more interpretive questions. Students taking courses using Doing Economics should follow the guidance of their instructors.
Part 8.1 Cleaning and summarizing the data
- No solution is provided.
- One way to rename the variables is given in Solution figure 8.1.
Variable | New name | Variable description |
---|---|---|
S002EV | EVS-wave | EVS-wave |
S003 | Country/region | Country/region |
S006 | Respondent number | Original respondent number |
S009 | Country abbreviation | Country abbreviation |
A009 | Health | State of health (subjective) |
A170 | Life satisfaction | Satisfaction with your life |
C036 | Work Q1 | To develop talents you need to have a job |
C037 | Work Q2 | Humiliating to receive money without having to work for it |
C038 | Work Q3 | People who don’t work become lazy |
C039 | Work Q4 | Work is a duty towards society |
C041 | Work Q5 | Work should come first even if it means less spare time |
X001 | Sex | Sex |
X003 | Age | Age |
X007 | Marital status | Marital status |
X011_01 | Number of children | How many children you have—deceased children not included |
X025A | Education | Educational level respondent: ISCED-code one digit |
X028 | Employment | Employment status |
X047D | Monthly household income | Monthly household income (× 1,000), corrected for ppp in euros |
Completed data dictionary.
- Examples of answers on how some of the variables were measured are provided:
-
To use reported life satisfaction in interpersonal and cross-country comparisons, we need to assume that all individuals share similar presuppositions and answer the questions in similar environments and contexts.
These assumptions are not entirely plausible. Perceived social norms, beliefs, culture, and many other characteristics vary across individuals and across countries, affecting individuals’ responses. As a result, differences in answers may reflect differences in these factors rather than the true level of satisfaction.
There are a large number of environmental factors that can influence the answers. The day of the week, the weather, and major news stories are all examples of such factors. It is impossible to control for all these factors.
Although the measure has limitations, it may be the best we can obtain.
- Employment status: Social norms, beliefs, culture, and other factors which vary across individuals and countries can affect people’s willingness to report truthfully on their employment status. Many people probably do not know accurately the technical definitions of the terms associated with employment status, resulting in misreports. Misreporting of employment status is therefore likely to be an issue.
-
An example answer is given below.
- No-opinion responding: A tendency to select the response category that is most neutral in its meaning (for example ‘neither agree nor disagree’). Some people may consider the information being asked for as private and therefore will not want to give opinions. We can check for respondents who choose neutral answers for most questions.
- Primacy effects: A tendency to select one of the first response categories presented on a list. When people want to spend minimal time on a questionnaire, they may just choose the first category given for each question. We can check for respondents who choose the first category for most questions. We can include in the questionnaire similar questions with the categories ordered differently so that if individuals select the first categories even for similar questions, we would know that they are probably not paying attention.
- Socially desirable responding: Conscious or subconscious tendency to select response options more likely to conform with social norms or present the respondent in a good light. The answers reveal the values, attitudes, and beliefs of the respondents. Respondents may engage in socially desirable responding because they are afraid of the risk that their employers or potential employers may learn about their answers and penalize them. We can identify a set of answers complying with social norms in any given region and identify respondents who chose almost the same set of answers.
- (a)–(e) No solution is provided. For Excel users: Refer to Excel walk-through 8.1 for guidance on answering Question 3(a) and (e). For R users: Refer to R walk-through 8.2. For Google Sheets users: Refer to Google Sheets walk-through 8.1.
- No solution is provided.
- No solution is provided.
- The long right tail means the mean is skewed to the right. Using deviations from the average income in this case would underestimate the living standards of many people.
- No solution is provided. For Excel users: Refer to Excel walk-through 8.3 for guidance, and for an example of naming a new variable. For R users: Refer to R walk-through 8.4. For Google Sheets users: Refer to Google sheets walk-through 8.3.
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The table in Solution figure 8.2 shows the breakdown of each country’s population according to employment status. There are many possible features to comment on, for example:
- the differences in percentages of students surveyed
- the percentages in full-time employment, part-time employment, and self-employment, making a comparison between developing and developed countries
- variations in unemployment across countries.
Country | Full-time | Housewife | Other | Part-time | Retired | Self-employed | Students | Unemployed |
---|---|---|---|---|---|---|---|---|
Albania | 29.42 | 7.42 | 1.50 | 5.50 | 9.08 | 22.08 | 7.33 | 17.67 |
Armenia | 23.86 | 20.92 | 1.14 | 8.09 | 18.38 | 5.96 | 6.70 | 14.95 |
Austria | 39.80 | 7.24 | 1.89 | 9.95 | 25.49 | 5.02 | 8.39 | 2.22 |
Belarus | 57.88 | 2.43 | 1.21 | 6.95 | 18.59 | 3.40 | 6.87 | 2.67 |
Belgium | 42.89 | 5.96 | 3.72 | 8.94 | 23.01 | 3.57 | 5.21 | 6.70 |
Bosnia Herzegovina | 34.06 | 9.33 | 0.82 | 2.90 | 14.67 | 3.08 | 8.15 | 26.99 |
Bulgaria | 46.32 | 2.62 | 0.76 | 2.79 | 31.28 | 5.58 | 2.37 | 8.28 |
Croatia | 41.58 | 3.37 | 0.93 | 2.78 | 26.01 | 2.86 | 8.75 | 13.72 |
Cyprus | 46.32 | 13.68 | 1.29 | 2.84 | 24.39 | 6.58 | 1.68 | 3.23 |
Czech Republic | 46.56 | 3.06 | 4.66 | 1.68 | 31.27 | 3.82 | 5.43 | 3.52 |
Denmark | 55.89 | 0.28 | 1.32 | 6.69 | 24.32 | 5.94 | 4.15 | 1.41 |
Estonia | 50.35 | 4.08 | 2.20 | 5.11 | 28.52 | 3.61 | 3.38 | 2.75 |
Finland | 52.34 | 1.38 | 3.94 | 5.11 | 22.77 | 6.17 | 3.72 | 4.57 |
France | 46.83 | 5.59 | 1.94 | 6.04 | 28.78 | 2.76 | 3.13 | 4.92 |
Georgia | 19.46 | 11.60 | 0.81 | 6.57 | 19.38 | 7.06 | 2.60 | 32.52 |
Germany | 38.44 | 4.58 | 3.03 | 8.44 | 28.64 | 2.97 | 2.67 | 11.23 |
Great Britain | 33.50 | 7.32 | 4.01 | 11.23 | 28.99 | 5.72 | 1.40 | 7.82 |
Greece | 28.49 | 17.42 | 0.40 | 2.97 | 26.73 | 13.72 | 6.18 | 4.09 |
Hungary | 46.39 | 1.20 | 7.21 | 2.00 | 24.04 | 3.53 | 6.57 | 9.05 |
Iceland | 54.50 | 2.25 | 6.01 | 9.91 | 7.06 | 11.41 | 4.95 | 3.90 |
Ireland | 41.87 | 19.84 | 1.59 | 9.72 | 13.89 | 4.96 | 1.59 | 6.55 |
Italy | 32.88 | 8.33 | 0.46 | 9.13 | 23.06 | 13.70 | 7.08 | 5.37 |
Kosovo | 19.57 | 11.65 | 0.52 | 5.23 | 5.83 | 9.41 | 18.00 | 29.80 |
Latvia | 52.05 | 6.18 | 2.34 | 3.76 | 23.22 | 3.26 | 4.26 | 4.93 |
Lithuania | 50.13 | 4.11 | 2.89 | 5.16 | 23.97 | 3.41 | 6.04 | 4.29 |
Luxembourg | 51.33 | 9.36 | 1.12 | 7.38 | 15.36 | 3.00 | 9.87 | 2.58 |
Macedonia | 35.74 | 4.34 | 1.24 | 1.71 | 16.74 | 3.72 | 8.53 | 27.98 |
Malta | 33.84 | 32.33 | 0.68 | 3.84 | 23.42 | 2.33 | 0.55 | 3.01 |
Moldova | 30.49 | 7.24 | 1.87 | 7.58 | 25.64 | 4.86 | 4.43 | 17.89 |
Montenegro | 39.02 | 4.63 | 0.60 | 2.14 | 16.64 | 4.97 | 4.80 | 27.19 |
Netherlands | 32.40 | 9.52 | 3.68 | 18.24 | 27.76 | 6.48 | 0.80 | 1.12 |
Northern Cyprus | 31.19 | 19.55 | 2.23 | 5.20 | 8.91 | 8.91 | 13.61 | 10.40 |
Northern Ireland | 30.10 | 10.36 | 4.53 | 8.74 | 29.45 | 3.56 | 1.29 | 11.97 |
Norway | 53.23 | 2.22 | 6.55 | 9.48 | 12.60 | 8.17 | 7.06 | 0.71 |
Poland | 41.81 | 6.00 | 0.10 | 3.14 | 28.00 | 5.81 | 7.62 | 7.52 |
Portugal | 46.20 | 5.24 | 1.57 | 3.27 | 33.51 | 1.70 | 1.05 | 7.46 |
Romania | 41.07 | 10.54 | 1.95 | 3.22 | 33.95 | 3.02 | 3.61 | 2.63 |
Russian Federation | 54.36 | 5.81 | 2.72 | 5.08 | 23.77 | 1.27 | 2.72 | 4.26 |
Serbia | 34.21 | 5.02 | 1.07 | 2.38 | 25.16 | 6.91 | 4.11 | 21.13 |
Slovakia | 40.98 | 1.73 | 4.89 | 2.21 | 39.73 | 3.55 | 1.25 | 5.66 |
Slovenia | 47.44 | 2.50 | 2.75 | 1.25 | 31.59 | 4.37 | 6.99 | 3.12 |
Spain | 41.52 | 16.30 | 0.11 | 4.63 | 19.93 | 6.28 | 3.19 | 8.04 |
Sweden | 54.82 | 0.38 | 6.60 | 7.36 | 15.36 | 7.23 | 4.06 | 4.19 |
Switzerland | 48.50 | 6.42 | 3.21 | 14.03 | 21.31 | 2.89 | 1.39 | 2.25 |
Turkey | 16.42 | 42.39 | 0.60 | 2.14 | 10.00 | 7.66 | 5.92 | 14.88 |
Ukraine | 40.92 | 6.79 | 1.02 | 4.84 | 32.09 | 4.41 | 3.23 | 6.71 |
Self-reported employment status in each country (per cent of sample).
- Solution figure 8.3 shows the summary table.
Male | Female | |||
---|---|---|---|---|
Mean | Standard deviation | Mean | Standard deviation | |
Life satisfaction | 6.98 | 2.30 | 6.98 | 2.30 |
Self-reported health | 3.68 | 0.95 | 3.68 | 0.95 |
Work ethic | 3.68 | 0.76 | 3.68 | 0.76 |
Age | 47.10 | 17.42 | 47.09 | 17.42 |
Education | 3.09 | 1.36 | 3.09 | 1.36 |
Number of children | 1.63 | 1.41 | 1.63 | 1.41 |
A summary table for the EVS data.
Part 8.2 Visualizing the data
- Germany is used as an example.
- Solution figures 8.4 and 8.5 provide frequency tables for work ethic in Germany for Wave 3 and Wave 4.
Range of work ethic score | Frequency | Percentage of individuals (%) |
---|---|---|
1.00 | 0 | 0.00 |
1.20 | 3 | 0.21 |
1.40 | 6 | 0.42 |
1.60 | 9 | 0.63 |
1.80 | 15 | 1.05 |
2.00 | 18 | 1.26 |
2.20 | 21 | 1.47 |
2.40 | 47 | 3.28 |
2.60 | 68 | 4.75 |
2.80 | 79 | 5.52 |
3.00 | 114 | 7.96 |
3.20 | 130 | 9.08 |
3.40 | 166 | 11.59 |
3.60 | 171 | 11.94 |
3.80 | 185 | 12.92 |
4.00 | 164 | 11.45 |
4.20 | 106 | 7.40 |
4.40 | 55 | 3.84 |
4.60 | 34 | 2.37 |
4.80 | 20 | 1.40 |
5.00 | 21 | 1.47 |
Frequency table for work ethic (Germany, Wave 3).
Range of work ethic score | Frequency | Percentage of individuals (%) |
---|---|---|
1.0 | 1 | 0.06 |
1.2 | 1 | 0.06 |
1.4 | 0 | 0.00 |
1.6 | 6 | 0.36 |
1.8 | 9 | 0.53 |
2.0 | 18 | 1.07 |
2.2 | 22 | 1.31 |
2.4 | 35 | 2.08 |
2.6 | 44 | 2.61 |
2.8 | 75 | 4.46 |
3.0 | 90 | 5.35 |
3.2 | 125 | 7.43 |
3.4 | 152 | 9.03 |
3.6 | 171 | 10.16 |
3.8 | 180 | 10.70 |
4.0 | 207 | 12.30 |
4.2 | 191 | 11.35 |
4.4 | 166 | 9.86 |
4.6 | 79 | 4.69 |
4.8 | 37 | 2.20 |
5.0 | 74 | 4.40 |
Frequency table for work ethic (Germany, Wave 4).
- Solution figure 8.6 shows the column chart for Germany for Waves 3 and 4.
- The work ethic scores have increased over time, as shown by the rightward shift in the distribution in Wave 4.
- Solution figure 8.7 shows the average life satisfaction in Waves 1 to 4.
Country | Wave 1 | Wave 2 | Wave 3 | Wave 4 |
---|---|---|---|---|
Belgium | 7.37 | 7.60 | 7.42 | 7.63 |
Denmark | 8.21 | 8.17 | 8.31 | 8.41 |
France | 6.71 | 6.77 | 6.98 | 7.05 |
Germany | 7.22 | 7.03 | 7.43 | 6.77 |
Iceland | 8.05 | 8.01 | 8.08 | 8.07 |
Italy | 6.65 | 7.30 | 7.18 | 7.40 |
Netherlands | 7.75 | 7.77 | 7.83 | 7.99 |
Northern Ireland | 7.66 | 7.88 | 8.07 | 7.82 |
Spain | 6.60 | 7.15 | 6.97 | 7.29 |
Sweden | 8.03 | 7.99 | 7.62 | 7.68 |
Average life satisfaction across countries and survey waves.
- Solution figure 8.8 provides the line chart of average life satisfaction across countries and survey waves. Note: When producing a chart with many lines, the key produced by Excel/R/Google Sheets is often inadequate in allowing the reader to distinguish between the series. You may need to add labels to the series.
- Average life satisfaction increased slightly over the survey periods for most countries. Also, instead of looking at averages, we could look at deciles, which would allow us to assess whether the changes in average life satisfaction are due to a shift in the entire distribution or an increase in reporting of extreme values.
- The answer depends on your chosen country/countries.
- Solution figure 8.9 shows the correlation coefficients.
Variable | life satisfaction | Work ethic |
---|---|---|
Age | –0.08 | 0.13 |
Education | 0.09 | –0.15 |
Full-time employment | 0.18 | –0.03 |
Gender (= 0 if male, = 1 if female) | –0.02 | –0.05 |
Self-reported health | 0.38 | –0.07 |
Income | 0.24 | –0.15 |
Number of children | –0.02 | 0.09 |
Relative income | 0.19 | –0.05 |
Life satisfaction | 1.00 | –0.03 |
Work ethic | –0.03 | 1.00 |
Correlation between life satisfaction, work ethic and other variables.
- The correlation coefficient, ranged between –1 and 1, measures the strength and direction of a linear relationship between two variables. A negative coefficient means the two variables are negatively linearly correlated, and a positive coefficient means the two variables are positively linearly correlated. The coefficient of 0.18 between employment status and life satisfaction, for example, means that people who are full-time employed tend to be more satisfied with their lives relative to those who are unemployed. The coefficients between life satisfaction and other variables have the expected sign. The results that work ethic is negatively linearly related to education, employment status, and relative income, however, are somewhat surprising.
-
Solution figure 8.10 shows average life satisfaction according to employment status.
Employed respondents are more satisfied with their lives compared with the unemployed. The retired, like the unemployed, do not work, but they do not suffer nearly as large a drop in life satisfaction. This suggests that social norms that discriminate against the unemployed is a plausible explanation for the relatively low life satisfaction of the unemployed.
Average life satisfaction | Employment status | ||
---|---|---|---|
Country/Region | Full-time | Retired | Unemployed |
Albania | 6.63 | 5.81 | 6.07 |
Armenia | 6.04 | 4.85 | 5.46 |
Austria | 7.44 | 7.74 | 6.07 |
Belarus | 6.10 | 5.62 | 5.61 |
Belgium | 7.72 | 7.83 | 6.37 |
Bosnia Herzegovina | 7.33 | 7.01 | 6.77 |
Bulgaria | 6.18 | 4.97 | 4.69 |
Croatia | 7.31 | 6.48 | 7.17 |
Cyprus | 7.38 | 7.03 | 6.56 |
Czech Republic | 7.30 | 6.89 | 6.07 |
Denmark | 8.54 | 8.21 | 7.20 |
Estonia | 6.93 | 6.25 | 4.97 |
Finland | 7.82 | 8.02 | 5.77 |
France | 7.20 | 6.97 | 6.24 |
Georgia | 6.12 | 4.69 | 5.42 |
Germany | 7.26 | 6.85 | 4.61 |
Great Britain | 7.53 | 7.93 | 6.03 |
Greece | 7.15 | 6.62 | 5.98 |
Hungary | 6.65 | 5.89 | 4.86 |
Iceland | 8.20 | 8.45 | 7.23 |
Ireland | 7.90 | 7.83 | 7.18 |
Italy | 7.43 | 7.44 | 6.60 |
Kosovo | 6.30 | 6.04 | 6.78 |
Latvia | 6.52 | 5.93 | 5.31 |
Lithuania | 6.59 | 5.63 | 4.53 |
Luxembourg | 7.87 | 8.24 | 5.50 |
Macedonia | 7.19 | 6.67 | 6.61 |
Malta | 7.70 | 7.76 | 5.95 |
Moldova | 7.12 | 5.98 | 6.07 |
Montenegro | 7.63 | 7.22 | 7.47 |
Netherlands | 8.04 | 7.95 | 7.00 |
Northern Cyprus | 6.74 | 6.44 | 5.64 |
Northern Ireland | 7.68 | 7.77 | 7.54 |
Norway | 8.19 | 8.26 | 8.00 |
Poland | 7.46 | 6.57 | 7.06 |
Portugal | 6.84 | 5.88 | 5.44 |
Romania | 7.14 | 6.57 | 7.41 |
Russian Federation | 6.86 | 5.70 | 6.40 |
Serbia | 7.17 | 6.67 | 6.73 |
Slovakia | 7.47 | 6.71 | 6.12 |
Slovenia | 7.83 | 7.13 | 6.76 |
Spain | 7.34 | 7.21 | 7.19 |
Sweden | 7.88 | 8.17 | 6.52 |
Switzerland | 8.04 | 8.12 | 5.76 |
Turkey | 6.50 | 6.61 | 5.76 |
Ukraine | 6.34 | 5.44 | 4.95 |
Average life satisfaction according to employment status and country.
- The calculation of the difference in average life satisfaction is provided in Solution figure 8.11.
Country/Region | Difference between full-time employed and unemployed | Difference between full-time employed and retired |
---|---|---|
Albania | 0.57 | 0.83 |
Armenia | 0.58 | 1.18 |
Austria | 1.36 | –0.31 |
Belarus | 0.49 | 0.48 |
Belgium | 1.35 | –0.12 |
Bosnia Herzegovina | 0.56 | 0.33 |
Bulgaria | 1.48 | 1.20 |
Croatia | 0.14 | 0.83 |
Cyprus | 0.82 | 0.35 |
Czech Republic | 1.24 | 0.42 |
Denmark | 1.34 | 0.34 |
Estonia | 1.95 | 0.67 |
Finland | 2.05 | –0.20 |
France | 0.96 | 0.23 |
Georgia | 0.70 | 1.43 |
Germany | 2.65 | 0.41 |
Great Britain | 1.51 | –0.40 |
Greece | 1.17 | 0.53 |
Hungary | 1.79 | 0.76 |
Iceland | 0.97 | –0.24 |
Ireland | 0.71 | 0.07 |
Italy | 0.83 | –0.01 |
Kosovo | –0.49 | 0.26 |
Latvia | 1.21 | 0.59 |
Lithuania | 2.06 | 0.96 |
Luxembourg | 2.37 | –0.37 |
Macedonia | 0.58 | 0.52 |
Malta | 1.75 | –0.06 |
Moldova | 1.05 | 1.14 |
Montenegro | 0.16 | 0.42 |
Netherlands | 1.04 | 0.09 |
Northern Cyprus | 1.10 | 0.29 |
Northern Ireland | 0.14 | –0.09 |
Norway | 0.19 | –0.07 |
Poland | 0.40 | 0.89 |
Portugal | 1.40 | 0.96 |
Romania | –0.27 | 0.56 |
Russian Federation | 0.46 | 1.16 |
Serbia | 0.44 | 0.50 |
Slovakia | 1.35 | 0.76 |
Slovenia | 1.07 | 0.70 |
Spain | 0.15 | 0.13 |
Sweden | 1.36 | –0.30 |
Switzerland | 2.28 | –0.08 |
Turkey | 0.74 | –0.11 |
Ukraine | 1.40 | 0.90 |
Difference in average life satisfaction: full-time employed minus unemployed, and full-time employed minus retired.
- The correlation coefficient for full-time employed vs unemployed is -0.158, which indicates a weak negative correlation. Looking at the scatterplot (Solution figure 8.12), it is difficult to see a clear relationship between the two variables. The correlation coefficient for full-time employed vs retired is 0.4843, which indicates a moderate positive correlation (the gap in life satisfaction between employed and retired is positive and wider in countries with higher average work ethic).
Part 8.3 Confidence intervals for difference in the mean
-
Choice of countries for this example:
- top third: Turkey
- middle third: Spain
- lower third: Great Britain.
- The table for our chosen countries is as shown in Solution figure 8.14.
Full-time | Retired | Unemployed | |||||||
---|---|---|---|---|---|---|---|---|---|
Country | Average | SD | Count | Average | SD | Count | Average | SD | Count |
Great Britain | 7.53 | 1.85 | 334 | 7.93 | 1.98 | 289 | 6.03 | 2.19 | 78 |
Spain | 7.34 | 1.70 | 377 | 7.21 | 1.93 | 181 | 7.19 | 2.14 | 73 |
Turkey | 6.50 | 2.55 | 330 | 6.61 | 2.60 | 201 | 5.76 | 3.13 | 299 |
Summary table of life satisfaction, by employment status.
Country | Difference in means | SD of difference in means | Number of observations |
---|---|---|---|
Great Britain | –0.40 | 2.71 | 623 |
Spain | 0.13 | 2.58 | 558 |
Turkey | –0.11 | 3.64 | 531 |
Calculated values for differences in life satisfaction (full-time vs retired).
Country | Difference in means | SD of difference in means | Number of observations |
---|---|---|---|
Great Britain | 1.51 | 2.86 | 412 |
Spain | 0.15 | 2.73 | 450 |
Turkey | 0.74 | 4.04 | 629 |
Calculated values for differences in life satisfaction (full-time vs unemployed).
Country | Difference in means | SD of difference in means | Number of observations | CI distance to sample mean | Total width of CI |
---|---|---|---|---|---|
Great Britain | –0.40 | 2.71 | 623.00 | 0.21 | 0.43 |
Spain | 0.13 | 2.58 | 558.00 | 0.21 | 0.43 |
Turkey | –0.11 | 3.64 | 531.00 | 0.31 | 0.62 |
Calculated width of 95% confidence interval for differences in life satisfaction (full-time vs retired).
Country | Difference in means | SD of difference in means | Number of observations | CI distance to mean | Total width of CI |
---|---|---|---|---|---|
Great Britain | 1.51 | 2.86 | 412.00 | 0.28 | 0.55 |
Spain | 0.15 | 2.73 | 450.00 | 0.25 | 0.51 |
Turkey | 0.74 | 4.04 | 629.00 | 0.32 | 0.63 |
Calculated width of 95% confidence interval for differences in life satisfaction (full-time vs unemployed).
- Solution figures 8.19 and 8.20 provide column charts for the example countries showing the difference in life satisfaction and confidence intervals.
-
For full-time and retired: In Great Britain, the retired have higher life satisfaction than full-time workers on average (0.4 points higher on a 1–5 scale), and this difference has been estimated with reasonable precision, so we can be fairly confident that this difference is unlikely to have occurred if really there was no difference in wellbeing between the two groups. In Turkey, the retired have slightly higher life satisfaction but this difference is both small (0.1 points) and not precisely estimated (the confidence interval is quite wide), so it is well possible that the difference we observed is consistent with there actually being no difference between the two groups. The same conclusions can be drawn for Spain, except that full-time workers have a slightly higher life satisfaction than the unemployed on average.
For full-time and unemployed: In all three countries, full-time workers have higher life satisfaction than the unemployed on average. The difference is largest for Great Britain (1.5 points on a 1–5 scale, which is considerable), and is precisely estimated, so we can be fairly confident that this difference is unlikely to have occurred if really there was no difference in wellbeing between the two groups. While we find a smaller difference for Turkey, it is estimated with precision and we come to the same conclusion as for Great Britain. For Spain, the difference is small and not very precisely estimated, so it is well possible that the difference we observed is consistent with there actually being no difference between the two groups.
Recall that 95% confidence intervals may not always contain the respective population means, so the above conclusions are never definite.
- A natural experiment can control for variables that affect both the dependent and independent variables. The method allows us to isolate the effect of employment status on life satisfaction. The ceteris paribus effect of employment status on life satisfaction, if obtained, has a causal interpretation.
- If we have data on the same individual over time, then we can calculate the difference in life satisfaction for the same person under different employment statuses, instead of comparing different individuals (as we did in this project).