Job satisfaction among public and privatesector employees: an international comparison

Pauli Forma

Director of working life services

Keva

Presentation in Nordic conference on working life, Tampere 2.11.2016

Background of the study• The role of the public sector varies in different countries

– Institutions: large, institutional welfare states vs. marginal welfare states

– Spending: High public expenditures versus low expenditures

– Number of public sector employees: large number of employees vs. small number of employees

– Working conditions: Well-being of the public sector employees?

• Well-being of the employees in the public sector can be influenced by:

– Role of the public sector in the society -> work characteristics

– Budget pressures, restructuring of the public sector

– On the other hand: according to the public service motivation (PSM) theory, some individuals may have desire to work in the public sector.

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Research questions and studiedcountries

The aim of the study is to analyze differences in job satisfaction and self-rated health in countries which have different types of public sectors.

Research questions:

1) How does job satisfaction and self-rated health among public sector employees vary between different countries?

2) What is the gap regarding job satisfaction and self-rated health between private and public sector employees in different countries?

Studied countries:

• Australia, Austria, Denmark, Finland, France, Norway, Sweden, Switzerland, United States, Germany, United Kingdom.

• Countries are different when it comes to the size and role of the publicsector.

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Data and methods

• It was quite difficult to find a comparative data including a variable for sector of employment and variables measuringthe well being in working life.

• ISSP (International Social Survey Programme) data wasobtained from DAS (Leibniz Institute for Social Sciences).

• The data was collected in 2012, the theme of thestudy was changing family and gender roles.

• Descriptive methods and multivariate regression analysis(standardized beta coefficients) were used.

• Background-variables which could be used in the analyseswere gender, age and education.

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Employment in the public sector in different countries (% share of the labor-force working in the general

government and public corporations).

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

2000 2008

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Source: OECD statistics.

Structure of the labour force in the public and private sector in thestudied countries (Figures for private sector in parentheses).

%-share of female workers

Average age of the workers

Average educationin years

Australia 52 (44) 45 (48) 15 (14)

Austria 54 (52) 41 (40) 13 (11)

Denmark 65 (38) 45 (43) 14 (13)

Finland 74 (43) 44 (45) 16 (15)

France 72 (60) 44 (42) 16 (15)

Norway 66 (36) 46 (44) 15 (14)

Sweden 71 (41) 48 (45) 14 (13)

Switzerland 54 (40) 45 (44) 15 (14)

United States 52 (47) 44 (42) 15 (14)

Germany 54 (44) 46 (43) 14 (12)

United Kingdom 65 (46) 44 (44) 13 (14)

62.11.2016 Pauli Forma Source: ISSP 2012.

Job satisfaction and self-rated health amongpublic sector employees, %

0 20 40 60 80 100

Germany

Denmark

Australia

Finland

Norway

Switzerland

United Kingdom

France

United States

Austria

Sweden

Self-rated health

0 20 40 60 80 100

France

United Kingdom

Australia

Sweden

Finland

Germany

Denmark

Norway

Austria

United States

Switzerland

Job satisfaction

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Percentage share of the respondentssaying their health is ”excellent”, ”verygood”, or ”good”.

Percentage share of the respondents saying”completely satisfied” and ”very satisfied”.

Job satisfaction among public and privatesector employees, %

0

10

20

30

40

50

60

70

80

90

100

Public Private

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Percentage share of the respondents saying ”completely satisfied” and ”verysatisfied”.

Self-rated health among public and privatesector employees, %

0

10

20

30

40

50

60

70

80

90

100

Public Private

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Percentage share of the respondents saying their health is ”excellent”, ”verygood”, or ”good”.

Multivariate regression analysis, betacoefficients, all studied countries included in the analyses

Jobsatisfaction

Self-ratedhealth

Age (years) .06*** -.16***

Gender (female) -.02 -.01

Education (years) .02 .09***

Sector of employment (public) -.01 -.04***

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Levels of statistical significance: * p ≤ 0.05; ** p ≤ 0.01; p ≤ 0.001.

Multivariate regression analysis, betacoefficients: Job satisfaction

AU AST SWI DK FIN FRA

Age (years) .12*** -.09* .14*** .08* .10* -.01

Gender (female) .02 .05 -.01 -.03 -.04 -.01

Education (years) .09* .07 .00 .03 .02 .08**

Sector of employment (public) .01 -.02 -.02 -.02 .08* .02

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AU AST SWI DK FIN

Age (years) -.05 .11** .04 .11* .13***

Gender (female) -.05 .03 -.04 .10* .00

Education (years) -.03 .03 .10* .03 -.04

Sector of employment (public) .07* -.04 -.04 .02 .12*

Levels of statistical significance: * p ≤ 0.05; ** p ≤ 0.01; p ≤ 0.001.

Multivariate regression analysis, betacoefficients. Self-rated health.

AU AST SWI DK FIN FRA

Age (years) -.10** -.31*** -.13*** -.12*** -.20*** -.20***

Gender (female) .02 -.01 -.07 .04 -.01 -.07*

Education (years) .08* .09* .15*** .05 .10** .11***

Sector of employment (public) -.05 -.03 -.09* -.04 -.01 -.02

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DEN NOR SWE UK USA

Age (years) -.29*** -.08* -.07 -.14** -.06

Gender (female) .00 .04 .01 .07 .02

Education (years) .17*** .10* .13** .09* .16**

Sector of employment (public) -.04 -.07 -.05 -.09 -.02

Levels of statistical significance: * p ≤ 0.05; ** p ≤ 0.01; p ≤ 0.001.

Main findings1) How does job satisfaction and self-rated health among public sector employees vary between different countries?

• Job satisfaction of the public sector employees varies betweendifferent countries.

• Only moderate differences were found when it comes to self-ratedhealth among public sector employees in the different countries.

2) What is the gap regarding job satisfaction and self-rated health between private and public sector employees in different countries?

• In some countries, a small gap between employment sectors werefound when it comes job satisfaction and self-rated health.

• However, the gap between sectors of employment was notsystematic.

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Conclusions

• In the studied countries, sector of employment dividesnot the labour-force when it comes to job satisfactionand self rated health.

• Individual-level variables like education and age aremore important than the employment sector.

• Because of the limitations of the data, more researchis needed.

• Currently, when public sectors are adjusted in manycountries, it is important to analyse also the quality of the working life in the public sector.

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Limitations of the data and researchdesign

• Sectors of employment are large and heterogeneous: there might be interestingdifferences behind the averages.

• Only two dependent variables were used: morespecific variables could reveal more detailedpicture about working conditions and well-being of the employees.

• Job satisfaction is not necessarily a good variablefor measuring well-being at work.

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