Luechinger, Meier, and Stutzer 1009
many, there are two types of public sector workers: public servants “Beamte”, who enjoy the strictest dismissal protection, and other people working in the public sector,
who are employed under the regular labor law Ebbinghaus and Eichhorst 2009. The largest public sector employers in Germany are the subfederal units, the Laen-
der. Over the entire period, 77,929 observations are for the private sector, and 26,329 observations are for the public sector including 8,939 public servants. Individual’s
sector of employment is defined on a year-to-year basis. Thus our sample includes individuals who changed between sectors over time for a detailed description of
sectoral transitions, see Appendix 1. The implications of the inclusion of changers for the estimations are discussed in Section IVC. We also test the robustness of the
results focusing on those who never changed the sector or the public servant status.
Regional unemployment is measured at the state or Laender level see Appendix 1 for additional information. Between 1984 and 2004, the average unemployment
rate was 8.7 percent with a minimum of 4 percent in Baden-Wuerttemberg in 1991 and a maximum of almost 20 percent in West Berlin in 2003.
Table 1 presents summary statistics of the main variables separately for individuals working in the private sector, the public sector, and as public servants for detailed
descriptions of the variables, see Appendix 1. Important for our analysis, individuals working in the public sector or as public servants differ somewhat in observable
sociodemographic characteristics from individuals working in the private sector. For example, on average, people working in the public sector earn more than people in
the private sector. They also are better educated. Since all these factors may be important in determining individuals’ well-being, we control for them in the empir-
ical analysis. Moreover, private sector and public sector worker differ in employment specific dimensions. Most importantly, they differ in tenure and in their unemploy-
ment history, with public sector workers having longer tenure and being less likely to have experienced personal unemployment. In Section IVC, we test whether these
differences influence the results for the privatepublic sector life satisfaction gap.
B. Sectoral Differences in the Costs of General Unemployment
The results for the privatepublic life satisfaction gap are presented in two steps: in a graphical analysis, raw differences are studied while the main analysis applies
multiple regression techniques. Figure 3 plots the unemployment rate right axis and the difference in life satisfaction between public servants and nonpublic servants
left axis in West Germany between 1984 and 2004. The bigger the difference, the more satisfied are public servants relative to nonpublic servants. The raw differences
show a clear relationship with the unemployment rate. If the unemployment rate increases, the life satisfaction differential grows; public servants become more sat-
isfied relative to nonpublic servants.
The results from the graphical analysis are studied further in econometric model specifications that allow us to quantify the observed correlation and to control for
important socioeconomic characteristics. We estimate regressions of the following form:
¯ SWB ⳱g
 Sector Ⳮ UR Ⳮ Sector ⳯UR Ⳮ X Ⳮ⌿ Ⳮ⍀ ⳭH Ⳮε
1
its 1
its 2
ts 3
its ts
4 its
t s
i its
1010 The Journal of Human Resources
Table 1 Summary statistics
1 2
3 4
Private sector Public sector Public servants Total
Life satisfaction 7.255
7.369 7.540
7.284 1.659
1.617 1.516
1.649 Concerns about job security
1.673 1.350
1.126 1.591
0.707 0.593
0.381 0.694
Concerns about own economic situation
1.889 1.684
1.455 1.837
0.676 0.665
0.589 0.679
Lnhourly income 2.118
2.262 2.530
2.154 0.478
0.449 0.410
0.475 Lnhousehold income
10.252 10.317
10.476 10.268
0.525 0.512
0.472 0.523
Actual working hours 40.192
37.947 40.594
39.625 11.203
10.334 9.451
11.033 Working part-time ⳱1
14.2 20.8
11.9 15.9
Female ⳱1 36.8
48.5 29.0
39.7 Age
39.382 41.546
42.917 39.929
10.935 10.848
10.656 10.954
Single ⳱1 22.0
20.6 17.5
21.7 Married ⳱1
67.4 67.5
71.6 67.4
Separated ⳱1 1.8
2.2 2.5
1.9 Divorced ⳱1
6.8 8.0
7.6 7.1
Widowed ⳱1 1.5
1.6 0.8
1.5 Household size
12
1.723 1.664
1.669 1.708
0.398 0.385
0.377 0.395
Children in household ⳱1 46.3
40.9 42.0
45.0 Head of household ⳱1
60.4 59.9
71.3 60.3
Lnyears of education 2.401
2.514 2.640
2.430 0.208
0.233 0.224
0.220 NonEU foreigner ⳱1
13.7 5.0
0.2 11.5
EU citizen ⳱1 75.3
91.3 99.1
79.3 German citizen ⳱1
11.0 3.7
0.7 9.2
Partner unemployed ⳱1 2.9
2.1 1.3
2.7 Tenure
9.944 13.201
18.025 10.771
9.002 10.084
10.675 9.396
Unemployment history 0.034
0.022 0.007
0.031 0.096
0.077 0.042
0.091 Parent ⳱1
58.4 57.6
54.9 58.2
Risk preferences only for year 2004
4.794 4.619
4.880 4.745
2.255 2.138
2.030 2.224
Number of observations 77,929
26,329 8,939
104,258 Number of individuals
15,162 5,675
1,713 19,022
Note: Tables shows percentages for dummies and for continuous variables means and standard deviation in parentheses.
Source: GSOEP 1984–2004.
Luechinger, Meier, and Stutzer 1011
Figure 3 Unemployment and the Life Satisfaction Differential Between Public Servants and
Nonpublic Servants in West Germany
Source: GSOEP 1984–2004 and Federal Statistical Office Germany.
where is individual i’s subjective well-being in time t in state s.
SWB Sector
its its
stands for the dummy variables capturing whether people work in the public sector ⳱1 or in the private sector ⳱0, and whether people are public servants ⳱1
or not ⳱0, respectively. Since all public servants work in the public sector, the estimated coefficient for public servants shows the difference in life satisfaction for
being a public servant over and above the effect of working in the public sector at the mean rate of regional unemployment.
is the means adjusted rate of un- UR
ts
employment in year t and state s. In order to see how the difference in life satisfac- tion between the public and the private sectors varies with the unemployment rate,
the two variables for public sector employment are interacted with the rate of un- employment
. is a vector of personal characteristics.
and ¯
Sector ⳯UR X
⌿
its ts
its t
are time and state-level fixed effects to control for time-invariant differences ⍀
s
between the states and for factors affecting West Germany as a whole in a given year. They are included in all the regressions.
is an individual fixed effect which H
i
absorbs any person-specific and time-invariant effects. are robust standard errors
ε
its
adjusted for clustering at the level of the individual.
9
is the function that deter- g
. mines the type of regression method used OLS or ordered probit.
The estimated coefficients ,
, and show the effect of working in the public
  
1 2
3
sector and the differential effect of unemployment on public and private sector
9. Generally, clustering at the level of the individual yields the largest standard errors, that is the most conservative estimates of statistical significance, for the coefficients of interest. Exceptions are the standard
errors for the direct effect of unemployment, which are slightly larger if a correlation between the errors at the state level is allowed for see Table A1 in the Appendix 2.
1012 The Journal of Human Resources
worker’s life satisfaction. If public sector workers report higher life satisfaction at the mean unemployment rate, we would expect
. If unemployment negatively  ⬎ 0
1
affects private workers’ life satisfaction, is expected. If people in the public
 ⬍ 0
2
sector are less hurt by unemployment than people in the private sector, we would expect
; that is, the interaction term between the unemployment rate and the  ⬎ 0
3
public sector would be positive. In the following, we estimate six different variations of this regression: As the
dependent variable is ordinal, we compare methods in which assumes cardinal
g .
OLS and ordinal ordered probit dependent variables. As documented in previous studies on subjective well-being Ferrer-i-Carbonell and Frijters 2004, we do not
find substantial differences between treating the dependent variable cardinally or ordinally. In a next step, we add personal characteristics,
, to the regressions. In ¯
X
its
Section IVC, we additionally let a number of control variables interact with the unemployment rate. Individuals differ with regard to many time-invariant unobserv-
able characteristics such as optimism that might be correlated with reported subjec- tive well-being and the sector of employment. We control for such time-invariant
individual characteristics by adding individual fixed effects,
, and compare the H
i
results to estimations without individual fixed effects. Table 2 shows the main results. Columns 1 and 2 report results of OLS and
ordered probit estimations without controlling for personal characteristics and with- out individual fixed effects. The results for both models are very similar and show
the following pattern: Importantly, regional unemployment is negatively correlated with the life satis-
faction of people working in the private sector p ⬍ 0.01. Estimating marginal effects of the ordered probit regression shows that, if regional unemployment in-
creases by one percentage point, the fraction of private sector workers reporting life satisfaction of 8 or higher is reduced by 0.87 percentage points. The coefficient on
the first interaction term indicates that public sector employees are less affected by regional unemployment than are people working in the private sector. The estimated
effect for the ordered probit regression of a one percentage point increase in the unemployment rate is a reduction of 0.26 percentage point in the probability of
experiencing high life satisfaction a score of 8 or higher for these workers public sector but not public servant workers ⳮ0.87 Ⳮ 0.61. The second interaction term
indicates that public servants may be even less affected by regional unemployment n.s.. The differential effect of regional unemployment on the life satisfaction of
private and public sector workers in total indicates that general unemployment hurts the latter group much less.
The panel at the bottom in all of the following tables summarizes the effect of unemployment on the different groups of employees. It shows that while for private
sector employees unemployment has a significant negative effect on life satisfaction, it does not have this effect for public sector employees. An F-test for the joint
significance of the two interaction terms that is, whether unemployment affects workers in the public sector including public servants differently from workers in
the private sector shows that they are significant at the 99 percent level. These results suggest that the negative effect of unemployment on the employed is mainly
due to sector-specific economic risks and not due to general regional effects.
Luechinger,
Meier, and
Stutzer 1013
Table 2 Baseline regressions
Dependent variable 1
2 3
4 5
6 Life satisfaction
OLS Ord. Probit
OLS Ord. Probit
FE OLS FE POLS
Sector and position Private sector
Reference group Public sector
0.033 0.023
0.026 0.019
0.010 0.005
0.027 0.017
0.027 0.017
0.030 0.018
Public servant 0.246
0.150 0.067
0.051 ⳮ
0.061 ⳮ
0.027 0.044
0.028 0.044
0.029 0.077
0.046 Unemployment rate UR
State unemployment rate ⳮ
0.032 ⳮ
0.022 ⳮ
0.031 ⳮ
0.021 ⳮ
0.036 ⳮ
0.023 0.011
0.007 0.011
0.007 0.012
0.007 Interaction terms
Public sector ⳯ UR 0.025
0.015 0.021
0.014 0.012
0.007 0.009
0.006 0.009
0.006 0.009
0.005 Public servant ⳯ UR
0.017 0.010
0.014 0.007
0.034 0.019
0.015 0.010
0.015 0.010
0.015 0.009
Individual characteristics No
No Yes
Yes Yes
Yes State-specific effects
Yes Yes
Yes Yes
Yes Yes
Year-specific effects Yes
Yes Yes
Yes Yes
Yes Individual-specific effects
No No
No No
Yes Yes
continued
1014 The
Journal of
Human
Resources
Table 2 continued
Dependent variable 1
2 3
4 5
6 Life satisfaction
OLS Ord. Probit
OLS Ord. Probit
FE OLS FE POLS
F, Wald
2
19.56 788.93
33.54 1990.73
26.810 31.100
R
2
, Pseudo R
2
, R
2
within 0.011
0.004 0.043
0.012 0.031
0.035 Number of observations
104,258 104,258
104,258 104,258
104,258 104,258
Number of individuals 19,022
19,022 19,022
19,022 19,022
19,022 Effect of unemployment for
Private sector employees ⳮ
0.032 ⳮ
0.022 ⳮ
0.031 ⳮ
0.021 ⳮ
0.036 ⳮ
0.023 0.011
0.007 0.011
0.007 0.012
0.007 Public sector employees
ⳮ 0.007
ⳮ 0.007
ⳮ 0.010
ⳮ 0.008
ⳮ 0.025
ⳮ 0.016
0.013 0.008
0.013 0.008
0.014 0.008
Public servants 0.010
0.003 0.005
ⳮ 3.4E-4
0.009 0.003
0.016 0.010
0.016 0.010
0.017 0.010
Test for joint significance of interaction terms F,
2
7.00 13.28
5.28 9.82
5.86 5.49
Notes: Robust standard errors in parentheses adjusted for clustering on the individual level. Individual characteristics include lnhourly income, lnhousehold income, working hours, working hours squared, household size, lnyears of education and dummies for working part-time, gender, age categories, marital status, children in
household, head of household, citizenship, and whether partner is unemployed. For the full results, see Table A2 in the Appendix 2. Source: GSOEP 1984–2004.
Level of statistical significance: p ⬍ 0.1 p ⬍ 0.05, p ⬍ 0.01
Luechinger, Meier, and Stutzer 1015
Additionally, the results show that not controlling for any observable character- istics, public servants report a statistically significant higher life satisfaction than
other public sector employees. The difference between public and private sector employees is small and statistically insignificant.
The two sectors may differ in other aspects than job security. In particular, the comovement of wages and working hours with economic shocks may be quite dif-
ferent between the two sectors and as a consequence may explain the sectoral dif- ferences in how workers’ well-being is affected by high unemployment rates. Fur-
thermore, as was apparent in the summary statistics, public sector workers differ in various observable characteristics such as education. Columns 3 and 4 show OLS
and ordered probit estimations controlling for differences in wages, working hours and a number of personal characteristics the full results of Table 2 can be found
in Table A2 in Appendix 2.
Adding personal characteristics has little effect on our main results. As before, the effect of unemployment on public sector employees is only around one third the
effect on private sector employees. The point estimate of the interaction term for public servants suggests again no effect of regional unemployment on their life
satisfaction. The two interaction terms are jointly highly statistically significant. Thus, differences in the wage curves between the sectors cannot explain the finding
that public sector workers are less affected than private sector workers by high levels of unemployment. The additional control variables for observed individual charac-
teristics, however, explain about two-thirds of the difference in average life satis- faction between public servants and nonpublic servants.
10
Columns 5 and 6 show the effect of regional unemployment on life satisfaction within individuals. We control for individual heterogeneity by adding individual
fixed effects in either an OLS regression or in a Probit-adapted OLS regression.
11
The qualitative results for the effect of unemployment are the same as in Columns 1 and 2. The test of whether the interaction terms between the rate of unemployment
and public sectorpublic servant status jointly differ from zero shows that people working in the public sector are less affected by general unemployment than people
working in the private sector p ⬍ 0.01. Looking at the results in Column 5, public sector employees below the status of public servant experience a negative effect
from unemployment that is about one-third smaller than that experienced by workers in the private sector. When regional unemployment increases by one percentage
point, life satisfaction is reduced by 0.025 points for the former, and by 0.036 points for the latter group. The point estimate for public servants is even slightly positive
10. The results for the control variables reproduced in Table A2 in Appendix 2 are in line with previous findings for Germany. In particular, wages and household income are positively correlated with subjective
well-being. Other control variables show that life satisfaction increases with the number of weekly working hours up to about 33 hours and decreases afterward. Unemployment of a person’s partner results in sub-
stantially lower reported life satisfaction. 11. Even though the previous results showed almost no difference in treating the dependent variable as
ordinal or cardinal, the Probit-adapted OLS method allows us to estimate individual fixed effects models taking into account that the dependent variable is ordinal. Thereby, we transform the dependent variable
by taking the expectation of a double truncated standard normal variate where the truncation points are derived from the marginal distribution of the satisfaction variable see Ferrer-i-Carbonell and van Praag
2004.
1016 The Journal of Human Resources
at 0.009 points but not statistically different from zero. If the two groups of em- ployees in the public sector are taken together, the life satisfaction of workers in the
private sector is reduced by 0.035 points, while that of workers in the public sector is reduced by 0.017 points by an increase of unemployment of one percentage
point. To put the size of the effects in perspective, the negative effect on life satisfaction of an increase in unemployment from the lowest value in the sample
3.7 percent in Baden-Wuerttemberg in 1991 to the highest value around 20.2 percent in Berlin in 2003 is 0.60 points for people working in the private sector—
similar to the negative effect of becoming personally unemployed see Stutzer and Frey 2004.
In sum, the results show that general unemployment mainly affects employees in the private sector and less so those in the public sector.
12
In the public sector, public servants are the least affected. This is the group that enjoys the strictest dismissal
protection. This finding suggests that economic insecurity is an important reason for the reduced individual welfare that occurs in an economic downturn. The different
specifications show that treating the dependent variable ordinally or cardinally leads to almost identical results. Adding individual control variables, like wages or work-
ing hours, and individual fixed effects affects the direct effect of working in the public sector somewhat. This reflects that individual-specific differences across sec-
tors are correlated with reported subjective well-being. However, controlling for personal characteristics and time-invariant heterogeneity does not affect our main
result that public sector workers’ life satisfaction is much less affected by general unemployment than that of workers in the private sector. While we find no effect
of regional unemployment for all public sector employees in models that do not control for individual heterogeneity, in models with individual fixed-effects this ef-
fect completely vanishes only for public servants. The following section further tests the robustness of this result with regard to a number of alternative explanations
based on sample selection and self-selection into the public sector. In light of the above findings, we estimate both ordered probit regressions without fixed-effects
and OLS regressions with fixed-effects.
C. Robustness Tests
