15
One may therefore conjecture that unemployment differences are able to explain the
differences in average happiness across the countries in our sample. On the other hand,
unemployment rates are still relatively low in Eastern Europe during this early phase of
economic transition. By referring to Table 1 we can see that, in the aggregate, only six percent
of respondents were unemployed. Although in later transition years the national differences in
unemployment rates will be much more pronounced, there is some variation across countries.
The unemployment rate based on our sample ranges from 2.9% in the Czech Republic to
9.8% in Bulgaria. However, low unemployment rates in a process of transition may not signal
good economic conditions for a country but rather a delay in implementing market reforms,
as, for example, in Romania with an unemployment rate of only 3.4% in our sample. This
could affect life-satisfaction in the country negatively.
Calculating the correlation coefficient between average happiness values and the
unemployment rates yields a value of -0.64. Thus, countries with a higher unemployment rate
display lower average life-satisfaction. Moreover, the estimates for the country dummies in
Table 3 already control for the influence of unemployment on an individual level but the
correlation between these dummies and national unemployment rates is still -0.63, compared
to only 0.40 with GDP per capita as reported above. Thus, the national differences can only
be explained by referring to aggregate effects of unemployment that go beyond the loss in
happiness suffered as a result of being unemployed. An analysis of how exactly the aggregate
effect of unemployment might work on happiness is beyond the scope of the present paper.6
Estimating a model that explains average happiness in Eastern Europe by GDP per capita and
unemployment leads to the results in equation (1):
(1) Happiness = 2.42 + 0.054 (GDP per capita/1000) - 0.063 (Unemployment rate in %)
(0.23) (0.042) (0.032)
The variables have the signs (SEs in brackets) in accordance with our theoretical priors (p-
values: GDP per capita: 0.27, unemployment: 0.12) and the explained variation of average
happiness is sizeable (R2 = 0.58). The partial R2 values for GDP per capita (0.29) and
unemployment (0.48) are not trivial. The absolute impact on happiness is also not small. To
5 As in the case of gender, Cummins (2000) argues that education does not play an important role in explaining
differences in life satisfaction.
6 The literature on sociotropic versus egotropic voting may provide some leads for further research (see
Nannestad and Paldam 1994).