Happiness in Eastern Europe



12

Continued Table 3

Community size:

5001-20000

0.02

**

0.02

**

-0.04

**

20001-100000

0.03

*

0.02

**

-0.05

**

> 100000 inhabitants

0.03

**

0.02

**

-0.05

**

Church attendance:

Every week

-0.03

**

-0.03

**

0.07

**

Frequency in %
(actual / predicted)

13.8 / 11.4

58.1 / 63.0

29.1 / 25.6

Coming now to the interpretation of the individual-level variables, we find that age has a non-
linear relationship with happiness. Being one year older lowers the probability of being in the
highest happiness category by 1%, and increases the probability to be in one of the lower
categories by 0.4%, respectively. The inclusion of the squared age term implies that we need
to take account of this non-linear effect as well. Here the marginal probabilities are
misleading, as age squared cannot change by one unit if age changes by one unit. Computing
the resulting difference in age squared for adding another year to the mean age (46.49), and
multiplying this with the marginal effects for age squared, we get a “pseudo-marginal” effect
of 1.58% increase in the probability of being in the highest happiness category. The net
marginal effect of the two age variables on the “very satisfied” category is positive (0.58%).
This is in accordance with the finding that minimum happiness, conditional on the other
explanatory variables, is observed at an age of 40 (based on the coefficients in Table 2). The
influence of age on happiness becomes positive when people reach 80 years of life.

How does this finding relate to the results previously reported in the literature? Table 4
compares the influences of core socio-demographic and economic variables across studies on
East European and Western countries. The first line of this table reports estimates for the
happiness-age relationship.

A non-linear association between age and happiness is a typical finding in the literature.
Moreover, the shape of the non-linearity is strikingly similar across Eastern Europe and
Western Countries. This is all the more noteworthy as the number and coding of other control
variables varies across the listed studies. However, the estimates for Russia by Ravallion and
Lokshin (2000) diverge substantially in this respect. This outlier may be the result of using a
qualitatively different dependent variable, namely the subjective rank of the respondent within



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