Population happiness, life satisfaction and well-being in transitional societies

Definitions and Indicators. WVS itself is not a tool dedicated specifically to the measurement of happiness and well-being in the world. Nevertheless, both concepts are operationalized in the WVS questionnaire through a number of indicators which constitute conceptual framework for measurement of happiness and wellbeing:

¦ Feelings and emotions (feeling of happiness; emotions; sense of life)

¦ Life satisfaction (general life satisfaction; financial life satisfaction; satisfaction with the development of the country; satisfaction with the job)

¦ Aspects of respondent's life influencing happiness (security; self-realization; religion and religious practices);

¦ Social contacts and close social environment (marital status; family; children; trust to relatives, friends, neighbours);

¦ Behavioural practices (leisure practices; participation in activity of volunteer organizations and free associations);

¦ Features of the respondent influencing happiness (level of income; education; immigration background; physical and psychological health).

In the further analysis we are considering two main indicators which characterize population well-being. Happiness is considered as a mental or emotional state of well-being involving positive or pleasant emotions that can range from contentment to intense joy. General life satisfaction is considered as an overall assessment of one's life as whole and the way how the individual thinks about desirable prospects and the reality. Thus if estimation of subjective happiness tends to reflect a relatively short-term, often dependent on the situation mood or emotional condition, self-reports of overall life satisfaction appear to measure a longer-term, more stable evaluation of one's life. Subjective well-being is a summarizing index calculated basing on the two indicators which comprises both emotional and more rational assessments of one's life and mediates short-term and long-term evaluations.

The WVS uses a four-point scale to measure population happiness: «Taking all things together, would you say you are very happy, rather happy, not very happy or not at all happy?» Part of those respondents who are «not happy at all» varies from 0.2-0.3% in the world's happies countries like Uzbekistan, Kyrgyzstan, Kazakhstan, Qatar up to 44% in Egypt and in most surveyed countries does not exceed 3%. The share of respondents who report being «not very happy» has a similar distribution with 3% and 30% as extreme min and max values in the same countries as mentioned above. In additional to Egypt, quite high the part of «not very happy» population is in Romania (26%), Belarus (27%), Iraq (26%), Georgia (25%) and Yemen (24%). Option «quite happy» is the most popular among the respondents in vast majority of countries. People reporting being «rather happy» on average constitute between 40% and 70% in different countries while the part of those who is “very happy” is the smallest in Egypt (5%) and the biggest in Mexico (68%).

For measurement of general life satisfaction, WVS proposes a 10-point scale: «All things considered, how satisfied are you with your life as a whole these days? Using this card on which 1 means you are «completely dissatisfied» and10 means you are “completely satisfied” where would you put your satisfaction with your life as a whole?» The part of population who reports being completely satisfied with their lives (10 on a 10-point scale) is the biggest in Mexico (44%), Colombia (38%), the Philippines (37%), Brazil (33%) and Qatar (30%). The share of respondents being completely dissatisfied with their lives (1 on a 10-point scale) is the biggest in Egypt (20%), India (12%), Tunisia (11%) and Armenia (11%). Ten-point scales are usually analyzed through reduction of dimension or comparison of means. Both approaches will be used in further analysis. For the comparison of means for happiness and overall life satisfaction, first indicator is multiplied by 2.5 in order to bring both scales to the same range of values. Finally, the subjective well-being index is calculated using the formula as proposed by Inglehart and Welzel which allows to find an appropriate summarizing value between the emotional and rational evaluations of one's life: SWB=GLS- 2.5*H, where SWB is subjective well-being index, GLS is general life satisfaction and H is happiness [12].

Population happiness and general life satisfaction. Using the first two indicators allows us allocating all the countries on the imaginary worldmap (Figure 1). Two axes show the level of population happiness (OY) and life satisfaction (OX) for every surveyed country. We use the «world mean» (mean for the aggregated wave data-set) to divide all the countries into four clusters. Analysing general trends, should be stated that people are inclined to give higher estimations to their happiness while the level of life satisfaction - which reflects a more rationale assessment of state of different domain of one's life - is usually a bit lower.

The correlation between life satisfaction and happiness of the population is quite high (0.46). Thus, groups of countries where the population is happy, but not satisfied or satisfied with the life, but unhappy are relatively small. Countries whose population reports being happy and satisfied are mainly located in Latin America (Mexico, Columbia, Ecuador, Brazil) and South and South-East Asia (Philippines, Malaysia, Japan, Singapore). To the countries with the happiest population belong also Nordic European countries (Denmark, Sweden, Norway, Netherlands), Australia, New Zealand and the USA. Countries whose population reports being generally satisfied with the life, but less happy are most countries of Central Europe (Germany, Slovenia, Spain, Poland), also some Asian (Hong Kong, China) and Latin American countries (Peru, Chile). Inglehart noted that generally lower lev-els of happiness and life satisfaction are inherent to post-socialist and post-communist countries in different parts of the world [10].

Figure 1 Population Happiness and Life Satisfaction**

*Country means are presented on the chart; values vary from 1 (low level) to 10 (high level) **Red line = world mean Source: World Values Survey 6 (2010-2014)

Countries whose population is happy, but less satisfied with the life are primarily developing countries from Asia and Africa (Zimbabwe, Ghana, Nigeria, Rwanda). Countries whose population is less happy or unhappy and less satisfied with the life, are countries of Middle East and North Africa (Morocco, Tunisia, Yemen, Bahrain, Lebanon, Jordan, Iraq) whose population has been involved into the revolutions and unrests in in 2011-2014. In particular, the lowest level of happiness and life satisfaction is noted in Egypt with the both indicators hardly reaching 5.00 on a 10-point scale. For a comparison, oil-exporting countries of GCC -Gulf Cooperation Council- report much high levels of happiness and life satisfaction, belonging in this regard to the same group as Norway, Sweden etc. In particular, Qatar is the third happiest country (after Mexico and Uzbekistan) and the second country in terms of population life satisfaction (after Mexico and Colombia). population country democratic happiness

Looking at transitional societies of Post-Soviet Eurasia, we can see that they are divided into two groups: countries of Eastern Europe (Moldova, Ukraine, Russia and Belarus) as well as Georgia and Armenia report very low levels of both population happiness and life satisfaction. While Central Asian countries (Kazakhstan, Kyrgyzstan, Uzbekistan) as well as partly Azerbaijan belong to a group on the opposite side of the scale. The lowest level of population happiness and life satisfaction is fixed in Moldova while the highest - in Uzbekistan. Thus, historical development in details studied by Inglehart including the number of years under communist rule, has certain limitations as a factor influencing population happiness, and despite approximately similar number of the years spent within the USSR by Central Asian and Eastern European countries, nowadays these countries reveal different revels of satisfaction with their life [10].

Another important group of factors is cultural and religious. In particular, primarily Orthodox countries of Eastern Europe, as well as Orthodox Georgia and Armenia are much less happy and less satisfied with their life than Central Asian countries and Azerbaijan where religious majority (60% and more) is represented my Muslims. Despite the proved evidence that majority of world's happiest countries are represented by historically Protestant societies, particular religious denomination per se cannot be considered as a predictor of happiness. For instance, Muslim societies of Northern Africa reveal quite low levels of population happiness comparing to Muslim Gulf and central Asian States. Besides, among world's happies nations are also primarily Catholic Mexico, Philippines and Brazil, but at the same time Poland and

Figure 2. Happiness and General life satisfaction in Post-Soviet Eurasia and other countries (%)*

*Happy people=very happy + rather happy; Satisfied people = 8+9+10 on a 10-point scaleSource: World Values Survey 6 (2010-2014)

Figure 3. Dynamics of life satisfaction in the world (1)*

* General Life Satisfaction Index varies from 0 to 1 Source: World Values Survey 1 to 6 (1981-2014)

Spain where the part of Catholics is around 87% and 70% correspondingly indicate much lower levels of population happiness. Thus, importance of religion as the predictor of happiness could be understood through its role as a part of the culture, forming people's norms, traditions, behavioural practices and attitudes.

World Happiness Report 2015 provides a slightly different hierarchy of world countries in terms of population happiness. Due to a different methodology of measurement (ranking is based on means for a Cantril ladder as surveyed by World Gallup Poll), the respondents are asked to estimate their current life in terms of “best” and “worst” possible life for themselves: «Please imagine a ladder with steps numbered from zero at the bottom to ten at the top. Suppose we say that the top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. If the top step is 10 and the bottom step is 0, on which step of the ladder do you feel you personally stand at the present time?». Thus, the focus in such estimation exercise is moved from simple categories of «happiness» and «satisfaction” into the sphere of comparison and evaluation of one's life in terms of achievement, under-achievement and potential life heights. The top ranks in the World Happiness Report hierarchy belong to Nordic and Western European countries (Switzerland, Denmark, Iceland, Norway), and also Canada and the USA. The Report places lower countries of Central and Latin America with Mexico being on 14 place as well as the countries of GCC with the UAE leading the list and being on position 20 [13].

One of the statements, being quite widespread in the literature, is that transitional societies and in particular countries of Post-Soviet Eurasia are characterized by low levels of population happiness. Looking at the survey findings in more detail (Figure 2), could be noted that the level of population happiness in post-Sovietcountries does not differ so much from other world countries. The level of happiness exceeds 90% in Sweden, Qatar, but also in Uzbekistan, Kyrgyzstan, Kazakhstan with being at the level of 60-80% in the remaining countries of former USSR. However, essential difference exists in the level of population satisfaction with life with varying from 41% in South Africa to 67% in Ecuador and Qatar and only 22% in Moldova and Armenia (which is three times less) and up to 62% in Uzbekistan.

Looking at the dynamics of life satisfaction over time, different patterns could be found in different parts of the world. We use the General Life Satisfaction index on a scale from 0 (low level) to 1 (high level) calculated for all 6 waves of the World Values Survey. Looking at the countries who participated in all 6 waves of the study, dynamics of this index for the whole period -from 1981 to 2013- could be traced. All the countries reveal different national patterns. For instance, life satisfaction has reduced over time in Australia, USA and Sweden. Dynamics is ambiguous and controversial is Spain. Slight increase of life satisfaction has shown population of Argentina. Life satisfaction in Chile and China has decreased between 1984 and 1991, but is slowly increasing since then. Despite all these changes, in general level of life satisfaction in all the countries remains stable: the variation hardly exceeds one decimal (0.1) in the 30-years period. This allows a conclusion that the level of life satisfaction differs more essentially between the countries and regions rather than inside the countries. In particular, in his analysis Inglehart concluded that «it seems that cultures, as well as individuals, have a normal baseline level of well-being that varies only moderately in response to current event» [9]. In his earlier work Inglehart (1990) demonstrated that life satisfaction levels were quite stable in the period between 1973 and 1988 in most West European countries. Similar findings have beenpresented by Easterlin (2005), Diener and Oishi (2000) and Krueger (2006) [14]. Thus, we can talk about certain «national» level (or rather interval) of life satisfaction which is relevant for a particular world country and does not change essentially unless some dramatic changes occur.

Figure 4 Dynamics of life satisfaction in the world (2)*

* General Life Satisfaction Index varies from 0 to 1 Source: World Values Survey 1 to 6 (1981-2014)

Following the conclusion made in the last paragraph, it would be relevant to test this theory on transitional societies of post-Soviet Eurasia (Figure 4). We use the same time-framework (1984-2013) and those countries who participated in at least 2 survey waves. Due to organizational limitations, the only country that participated in the first WVS wave was Russia (country region proved to be representative for the nation-level results). In wave two the survey was joined by Belarus, and in wave 3 - by all the other countries. Among the countries of Central Asia, data on dynamics of life satisfaction is available only for Kyrgyzstan. Looking at patterns, a different picture could be observed in this part of the world. Almost all the countries are characterized by increase of life satisfaction between 1999 and 2013 with year 1995 being the lowest point on every nation's chart. Data available for Russia and Belarus for 1984-1991 indicates that the level of life satisfaction was quite high in these countries before the collapse of Soviet Union - 0.67 on a scale from 0 to 1 which is equal to the level of life satisfaction in Italy, for instance. However, in 1995 this indicator went down to 0.35 in Russia (which is 2 times lower than before the transition) and 0.36 in Belarus. Similar paths of historical development and features of social and economic transformations in the period between 1991 and 1995 allows to suggest that Ukraine, Moldova, Armenia and Azerbaijan might have had similar high levels of life satisfaction in 1984 before the post-Soviet transition began which later have decreased 2-3 times during the social and economic crisis in the 1990s with the consequent low recovery in 2000-2015.

Therefore, developing the theory of «national» levels of life satisfaction for particular cultures, we have reasons to assume that the actual «national» level of life satisfaction in most post-Soviet countries is actually much higher and successful completion of social, politic and economic reforms might lead to restoration of life satisfaction and increase of population happiness up to a «normal baseline». Lack of data on countries of Central Asia does not allow to check this theory for this part of the world though.

Subjective Well-being Index. We calculate the Subjective Well-being Index basing on two indicators described above using the formula as suggested by Inglehart and Wel- zel. It allows to neutralize the extremes as well as inconsistent values for happiness and general life satisfaction [12]. Taking into account the relative stability of the level of happiness and life satisfaction over time, as has been proved in previous section, we use the data from both WVS wave 5 (2005-2009) and WVS 6 (20102014). For the compact presentation of the countries hierarchy, we divide countries in a number of groups by regions (Figure 5). Obtained ranking to a large extent corresponds with the countries distribution in Figure 1. Countries with the highest values of Subjective Well-being are primarily Western and Northern European countries, USA, Canada Australia, but also several countries of Central and Latin America as well as South-East Asia. Countries of Central and Southern Europe are characterized by lower subjective well-being, in particular some of them (Hungary, Romania, Lithuania, Serbia and Bulgaria) in terms of population well-being are on the same level as Ukraine, Russia, Belarus, Armenia and Moldova. Central Asian countries reveal much higher levels of subjective well-being and reach the bottom line of Western and Norther European group.

Taking into account that the level of population well-being differs so much between world countries and regions, in the current paper we will analyse predictors of well-being in order to find out if different levels of well-being are the result of influence of different factors or not. In other words, we will try to answer the question if there is a common way to population happiness or if country-specific factors have the priority. We use OLS regression with subjective well-being index as dependent variable and a number of variables representing economic, political, social and cultural factors affecting happiness as independent variables. According to the obtained results, there is a number of factors which are affecting population well-being in all world regions. In particular, the strongest factor influencing well-being and life satisfaction is satisfaction with financial situation of the respondent (or in the household). Level of satisfaction with financial condition by itself defines 23.8% of the variance in the level of well-being. Level of income introduced in the same model has an essentially smaller impact on subjective wellbeing. Thus, for personal well-being more important is own perception of income rather than its absolute value. The second factor defining well-being is respondent's health - both physical and psychological. Self-evaluation of health adds around 8% to the explained variance in the level well-being, increasing it up to 31.6%. The third major factor which positive affect on subjective well-being is most visible is freedom of choice and control over the own life. These three factors together define 35.7% of variance in the level of subjective well-being and are relevant for all the world countries despite their cultural background, political system or geopolitical location. Among the other factors whose influence is less essential, but still significant could be mentioned values system in the society - emancipative and secular values, feeling of personal security, family status and state policy - democratic rule in the country. The summarizing explanatory capacity of the model is around 38% of variance. WVS-based results on the predictors of population well-being have been confirmed by findings from other studies. In particular, the World Happiness Report proposes the following main factors influencing population happiness: GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity, and perceptions of corruption [15].

For the analysis of region-specific impact of the factors, all the considered countries have been divided into 6 groups: Central and Latin America (LA), Eastern Europe and Post-Soviet Eurasia (Eurasia), Eastern and South-East

Figure 5. Subjective Wellbeing Index**

"Countries are divided into groups by world regions for convenience of reading Source: World Values Survey 5 (2005-2009) and 6 (2010-2014)

Asia (Asia), Sub-Saharan Africa (Africa), Middle East and North African countries (MENA) and the last group includes mainly OECD states (USA, Canada, Australia and the EU member states). Hierarchy of factors is quite similar for all distinguished groups of countries with several exclusions. In particular, economic factors (satisfaction with financial situation) have the biggest influence on population happiness in all the world regions, except for Post-Soviet Eurasia where population health appeared to play the role of the most important factor. Economic development by improving population incomes and the stability of the situation in the country enables satisfaction of basic survival needs and allows to move on the next step of Maslow's pyramid of needs which changes also the values system of the individual and the society. This shift of values has been described as switch from survival values toward self-expression values and free choice which appeared to be a “more direct way to maximize happiness and life satisfaction” [12]. Thus, the strongest correlation between economic factors and population well-being is observed in the countries of Sub-Saharan Africa and MENA region which belong to societies with prevailing traditional and survival values and lower GDP per capita. It is necessary to add that numerous studies have proved that rising prosperity has a time-limited effect on happiness (Diener, Suh, Lucas, & Smith, 1999; Kahneman, Krueger, Schkade, Schwartz, & Stone, 2004). In long-term perspective, once economic well-being of population reaches a certain mark, further increase in income affects happiness very insubstantially. In short-term perspective, following the increase in income and after a period of adjustment, people return to their baseline level of happiness and well-being which is described by the concept of «hedonic treadmill» [22].

Group of factors comprising dimensions of individual's physical and psychological health are raking on the second place in terms of their influence on happiness. Here special role belongs to freedom of choice and control over own life which affect well-being and happiness across all major cultural zones [23]. People value freedom and free choice in many societies; the role of personal freedom in predicting happiness and wellbeing increases with improvement of economic situation and rising economic security. Possibility to control your own life and to have freedom of choice is especially important in countries of Europe, USA, Australia and Canada which have crossed the poverty line long ago and where the role of economic factors is getting less decisive with evolved self-expression and emancipative values moving the issue of personal freedom to the foreground. Citizens of new independent states established in post-Soviet Eurasia also value freedom of choice and possibility to control own life. Despite remaining unresolved issues of economic transition with the majority of population being unsatisfied with their incomes, high value of personal freedom could be explained by both past experience of life in a controlled authoritarian society and newly emerged need for a stable social structures and political institutions which allow to transform everyday life from a patchwork of unpredictable experiences into a system of social exchanges with more or less expected outcomes and thus a possibility to influence them and to control own life.

Link between physical and psychological health and well-being is well described in the literature and self- evident: bad psychological health - depression, psychological disorder - is characterized by condition being opposite to happiness and thus negatively affects wellbeing. However, such psychological conditions like feeling of insecurity, lack of confidence, feeling of inability to control own life which are common for transitional societies when old social institutions and mechanisms do not work anymore and the new one haven not been established or fully developed yet, also negatively affect well-being and happiness. Health remains an important predictor of well-being in post-Soviet societies as well as in African countries and Western societies.

The link between population well-being and democratic rule is probably one of the best studied by both sociologists and political scientists; theoretical explanation as well as numerous survey evidence are broadly described in the literature. In short, democratic regimes provide a wider range of freedoms and free choices which contribute to increase of individual's happiness and well-being, and thus democratic rule and democratic government are one of predictors of population well-being. However, democratization per se does not automatically make population happier; an important factor remains performance of political institutions and the way how democracy works in the country. Successful and well functioning democracies not only contribute to higher well-being of society, but also tend to reduce gaps in the level of happiness between different social groups and classes in society [24].

Declared democratic vector of political transformations in post-Soviet states did not automatically provide higher level of population well-being. The effect from democracy on wellbeing in these countries will be more clearly observed after political systems finish the transition and after the final shaping of the political regimes. An important dimension in defining the influence of democratic government and political regime on population well-being is the performance of the political system and political institutions. If performance of the government, parliament, political parties and other bodies is estimated by population as very low - like in Ukraine, Moldova, Georgia, for example - this might cause a negative correlation between wellbeing and development of political system despite its declared ideology.

Among the other important groups of factors affecting well-being could be mentioned value system in the society. Intolerant social norms which are often elements of non-democratic political regimes narrow and restrict people's life choices and reduce well-being of population. Support for gender equality and tolerance of outgroups are strongly linked with happiness because living in a tolerant society enhances everyone's freedom of choice. Feeling of security inthe neighbourhood to a certain extent affects well-being in all countries, but most important this factor is in the MENA region where in the last several years characterized by population uprisings and activation of terrorism people started valuing security much higher. Among demographical characteristics being relevant for all cultural zones as predictor of happiness and well-being is marital status: those respondents who report being in registered relationship or unregistered partnership both reveal higher level of happiness.

Table 1. Predictors of Subjective Wellbeing (1)**

** Standardized coefficients Beta are presented in the table; significance of all coefficients at the level 0.000

Table 2. Predictors of Subjective Wellbeing (2)**

* Regression model based on WVS-6 data (2010-2014)

** Standardized coefficients beta are presented in the table; significance of all coefficients at the level 0.000

Previous section considers a number of factors affecting population well-being. However, only one of the analysed factors belong to the group of social and demographic characteristics. Does it mean that members of all different social groups are equally happy and have same levels of well-being? No at all. The reason for omitting demographic factors in regression model is that their influence on well-being in different parts of the world is ambivalent. We will consider now the level of happiness inside different social and demographic groups on the example of 5 countries: Ukraine, Belarus, Kyrgyzstan, Sweden and Brazil. Three out of five countries represent Post-Soviet Eurasia while Sweden and Brazil belong to societies with high level of population happiness and well-being and could be used for comparison. Inside each of the national datasets we have built 2 groups: a group of «happy» people (those who reported about high level of both personal happiness and life satisfaction) and «unhappy» people (those respondents who noted that they are both unhappy and unsatisfied with their life). Groups have different size inside each of the samples. Comparing social and demographic portrait of «happy» and «un- happy» people the first finding is that there is no different in the level of happiness between male and female respondents and thus they are more or less equal in the level of subjective well-being.

The first characteristic which has essential influence on happiness is age. This observation is particularly relevant for Ukraine and Belarus (and we have reasons to extend it to other Eastern-European post-communist countries) where the part of «hapy people» among those aged 18-35 is 41% and 30% correspondingly while among respondents in the age of 56 and older - only 20% and 16%. This means that in the group of people who are older than 55 only one out of five respondents consider themselves being happy while the other four report being unhappy and much less satisfied with their life. Looking at the link between age and happiness, we can observe a completely different pattern in the other countries. In particular, in the population of Qatar and Sweden older people (55 years and more) appear to be happier than young and middle-aged respondents: 68-73% «happy» among older respondents while only 52-61% are «happy» among young people in the age of 18- 35. Population of Kyrgyzstan does not reveal any difference in the level of happiness among people of different age. Such countries like Germany and Spain, despite having a lower level of population happiness than Qatar, Sweden and Kyrgyzstan, also have equally happy age groups in their population.

Certain influence on population well-being has the level of education. In particular, in Ukraine, Sweden and Kyrgyzstan respondents who obtained higher education tend to be happier and report higher level of well-being. Should be added, that the link between education and happiness is much stronger than, for example, between education and life satisfaction. In Belarus which similar to Ukraine has quite a high percent (over 40%) of population with higher education, there is no significant difference in the level of education between «happy» and «unhappy» people. In Brazil the percent of people with higher education is essentially low (16%) and it does not affect population happiness essentially. In general, countries of Central and Latin America which are characterized by very high level of population happiness (Mexico - happiest country, according to WVS-6) constitute one of the main «puzzles» in explaining this happiness. Taking into account the leading role of GDP in affecting nation's happiness, in OECD countries high GDP could be used to explain high happiness while in post-communist countries low level of GDP could be used to explain correspondingly low level of population happiness. Latin American countries in this regard stay out of the trend, having low GDP per capita and high level of population happiness. As a partial confirmation of the challenging nature of population happiness in Latin American countries, the regression model developed in previous section has the weakest explanatory capacity exactly for LA region.

Another characteristic which was tested is the settlement type. According to the analysis results for 5 selected countries, there is no different in settlement patterns of «happy» and «unhappy»people. Approximately equal parts of them live in small towns and villages and big cities. This observation is valid despite the different level of urbanisation in the selected 5 countries as well as different traditions of city size. Two other characteristics which have certain impact on population well-being is social class and level of income. «Happy» respondents in general put themselves on higher steps on social ladder as well as report higher level of income. This correlation is working for all the analysed countries except for Brazil where only the level of income matters. The biggest difference in social class and level of income between «happy» and «unhappy» people is in Ukraine and Belarus. In the other countries it constitutes only few percent. Finally, absent of work affects population happiness and well-being primarily in Ukraine where among unhappy people around 50% reported that they do not have paid job (this groups in addition to unemployed economically active population, includes also pensioners, housewives etc.).

Conclusions