Many previous studies show that homeownership is related to various aspects of well-being, although the causal nature of this relationship is difficult to identify. We analyze the association between homeownership and material security, measured through subjective expectations of being better or worse off in the future, using data from 15 European countries. Our findings show that homeowners have a higher level of material security than renters, with larger differences among those living in big cities. We find that material security increases with the value of owner’s property and at the same time find no significant relationship with education, income or financial situation. We interpret the results as support for one of the most commonly emphasized mechanisms behind the positive effects of homeownership for well-being – that homeownership provides a particular form of material security in old age.
Vast empirical literature links homeownership to numerous outcomes, such as well-being, health or mobility (Costa-Font, 2008; Dietz and Haurin, 2003; Rohe and Stewart, 1996 among others). In most cases the specific causal link with homeownership per se is however difficult to demonstrate. This because homeownership, especially in old age, usually reflects the financial resources accumulated over the life course through labor market history, as well as health and family developments (Angelini et al., 2013). This means that many unobservable characteristics can obscure the relationship between homeownership and welfare outcomes and bias the estimated parameters.
Material security is an important aspect of well-being, facilitating longer-term planning of financial decisions, smoothing of expenditures across periods of lower contemporaneous incomes and allowing exceptional spending when faced with various negative shocks. It seems particularly relevant in old age when people’s ability to adjust their current income to their specific needs is significantly reduced, and material needs increasingly depend on health. As people age and as their ability to maintain labor market activity diminishes, the material resources available to them, and the security these can provide, are increasingly composed of pensions and accumulated assets. Among the latter, fixed assets, and in particular ownership of one’s home, play a very special role, as they provide some financial backup and secure a flow of regular consumption in the form of accommodation.
It is reasonable to expect that homeownership would influence well-being through the channel of material security, particularly in old age. Surprisingly, the findings in the literature directly exploring this mechanism are so far scarce. We address this gap using data collected in the Survey of Health, Ageing and Retirement in Europe (SHARE) on individuals aged 50 years and above. We take advantage of the 2006 edition of the survey from 14 European countries and Israel and develop a measure of perceived future material security using two consecutive questions on ‘the chances that five years from now the standard of living [of the participant] will be better/worse than today’. Participants reported the estimated chances on a scale from 0 to 100, where 0 means ‘absolutely no chance’ and 100 denotes ‘absolutely certain’. In line with previous behavioral literature, we calculate a difference between the chances of being better vs. worse off, and recode into a categorical variable with 5 outcomes spanning from ‘very likely worse off’, through ‘rather likely worse off’, ‘equally likely’, ‘rather likely better off’ and ‘very likely better off’ (more details in Garten et al., 2022). In our sample, ‘equally likely’ is the most frequent category (30 percent of total responses), and being either ‘very’ or ‘rather likely worse off’ was more frequently reported than being better off (48 percent of total responses coded as either outcome for being worse off as compared to 22 percent for the two categories of being better off).
The Impact of Homeownership on Expectations of Future Standard of Living
We regress the measure of perceived material security on an extended vector of characteristics including basic demographics, education, marital status, labor market status, the relative position in the distributions of income and financial assets, and physical and mental health. Our main variable of interest is a categorical measure of homeownership, where individuals are split between renters and homeowners, who are further divided based on the country-specific quartiles of their home value. This measure is then interacted with being a big city resident. Below we present some selected results, which are reported in full in Garten et al. (2022).
In Figure 1 we report the results for each outcome of perception of material security for owner occupiers (depending on the value of their home) as compared to renters, by place of residence. The correlation with material security is particularly strong among those living in cities. However, among other respondents, those in the top quartile of the home value distribution are also more likely to report being optimistic about their material conditions in the future. For big city dwellers, the differences between renters and home owners are statistically significant already for owners with home values in the second quartile of the distribution, and the effects carry through to higher quartiles. The differences for selected perceptions of material security are not only statistically significant but also large in magnitude in the case of city dwellers who own the most expensive properties. As compared to renters they are 3.7 percentage points more likely to expect that their future situation will be either ‘rather’ or ‘very likely’ better. Among those living in big cities, 17.5 percent and 8.5 percent respectively, declare these positive expectations. This means that proportionally, the estimated 3.7 percentage points correspond to respective increases of 21.2 percent and 43.3 percent.
Figure 1. Marginal effects of homeownership for outcomes of perception of material security
We relate the marginal effect of owning a property in the top quartile of the home value distribution, as compared to owners with properties in the bottom quartile or renters, to the effect resulting from: higher education, being in the top income quartile or in the top financial assets quartile. While education, income and financial assets affect the perception of future material situation in the expected direction, the estimated relationships are statistically insignificant, and their magnitude is much lower compared to the estimated relationship with homeownership.
Relative to renters, individuals owning their homes tend to have higher levels of well-being across numerous dimensions (see Garten et al., 2022 for an overview). Due to the complex nature of the accumulation of wealth and its interaction with different spheres of life over the life cycle, the identification of the causal character of this relationship is a nearly impossible task. Although many mechanisms behind this relationship have been suggested, few have actually been put to the test against real-life data. Therefore, better understanding of these mechanisms might be a way to verify the hypothesis that homeownership actually matters for well-being.
Our findings confirm that homeowners – in particular those living in big cities – enjoy a higher level of self-perceived material security and are more likely to express optimism about their material standard of living in the future as compared to renters. Such feeling of security for the coming years may contribute to a more general positive outlook, and consequently to the higher reported levels of well-being and life-satisfaction observed in the literature. The examined relationship is especially strong among those in the top quartile of the distribution of property values, although for dwellers in big cities the effect is also strong for those with lower property value. While these findings cannot be interpreted as strictly causal, we suggest that owning a home offers a very particular type of material security in old age and that this security might be an important mechanism leading to the observed positive relationship between homeownership and overall well-being.
The authors wish to acknowledge the support of the German Science Foundation (DFG, project no: BR 38.6816-1) and the Polish National Science Centre (NCN, project no: 2018/31/G/HS4/01511) in the joint international Beethoven Classic 3 funding scheme – project AGE-WELL. For the full list of acknowledgements see Garten et al. (2022).
- Angelini, V., Laferrère, A., and Weber, G. (2013). Home-ownership in Europe: How did it happen?, Advances in Life Course Research, 18(1), pp. 83–90.
- Costa-Font, J. (2008). Housing assets and the socio-economic determinants of health and disability in old age, Health & Place, 14(3), pp. 478–491.
- Dietz, R. D. and Haurin, D. R. (2003). The social and private micro-level consequences of homeownership, Journal of Urban Economics, 54(3), pp. 401–450.
- Garten, C., Myck, M., and Oczkowska, M. (2022). Homeownership and the Perception of Material Security in Old Age, SSRN Electronic Journal. doi:10.2139/ssrn.4196268.
- Howden-Chapman, P. L., Chandola, T., Stafford, M., and Marmot, M. (2011). The effect of housing on the mental health of older people: the impact of lifetime housing history in Whitehall II, BMC Public Health, 11(1), p. 682.
- Rohe, W. M., and Stewart, L. S. (1996). Homeownership and neighborhood stability, Housing Policy Debate, 7(1), pp. 37–81.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
This brief summarizes the insights shared in the online workshop “Dimensions of Well-being“, where participants presented and discussed their latest research relating to the dimensions of well-being. The two-day workshop was organized by the Stockholm Institute of Transition Economics (SITE) as part of the Forum for Research on Gender Economics (FROGEE) and took place on 28-29 June, 2021.
It has been roughly 18 months since the first cases of Covid-19 were reported in Europe. So far the total number of deaths worldwide has passed 4.4 million (John Hopkins University, 2021), unemployment is trending upward in most countries (ILOSTAT, 2021), roughly half of the world’s students have been affected by school closures (UNESCO, 2021), and an alarming increase in domestic violence has been reported across the globe (UN Women, 2020).
It is safe to say that this pandemic crisis has had a multifaceted impact on our lives. Identifying what factors contribute to overall well-being and understanding how they interact with one another is central in designing and implementing solid and effective recovery policies.
Stockholm Institute of Transition Economics invited international experts to an online workshop where they discussed and presented their recent research relating to the dimensions of well-being. The workshop was organized as part of the Forum for Research on Gender Economics (FROGEE).
Well-being in a Pandemic
The government response policies intended to contain the spread of Covid-19 have undoubtedly had a major impact on society. However, estimating the overall effect of these policies on individuals’ well-being is not necessarily straightforward. Economic support policies likely have a positive effect on income and decrease poverty. But at the same time, other responses such as lockdowns and mobility restrictions may not only have an opposite effect on these outcomes but also influence other known determinants of well-being such as social life or education.
Anthony Lepinteur, researcher at the University of Luxembourg, presented his recent work on the well-being consequences of the pandemic policy responses in Germany, France, Spain, Italy, and Sweden. Lepinteur and co-authors link survey data on subjective well-being measures to data on government economic policy and stringency indices. The former index records financial policies such as income support, furlough schemes, and debt relief while the latter measures the strictness of Covid-19 containment and closure policies. The results show that more stringent policies reduce life satisfaction, and this negative effect is stronger for women, the unemployed, and those with relatively high incomes. Economic support policies are found to have no significant impact on reported life satisfaction.
As many countries have experienced major disruptions in many sectors of their economy, concerns have been raised about deteriorating labor markets and the effect this might have on living conditions and, ultimately, the well-being of individuals. Knar Khachatryan, associate professor at the American University of Armenia, shared research studying the impact of Covid-19 on multidimensional deprivation from labor market opportunities in Armenia. Knachatryan and co-authors base their analysis on two surveys from 2018 and 2020. To measure labor market opportunities, they adopt the “Alkire-Foster method” to develop a multidimensional index of labor market deprivation – a basket of indicators explaining an individual’s degree of labor market opportunities (e.g. education, employment status, income, type of work contract, and union membership). With respect to this index, they find that education is the most important determinant of multidimensional labor market deprivation – those having less than a bachelor’s degree are very likely to be deprived in terms of labor market opportunities. The results also show that the pandemic has widened the gender gap in labor opportunities. The number of people classified as deprived has increased more for women than men during the pandemic. This is primarily because women experienced stronger income reductions and more frequent job losses.
Thesia Garner, researcher at the U.S. Bureau of Labor Statistics, discussed how ex-ante levels of well-being have affected the outcomes of economic support policies during the pandemic. More specifically, her study investigates the role of individual’s well-being in determining their reported use of economic impact payments (EIP) in the U.S. Garner and co-author assess well-being using both objective measures (e.g. income sources, employment status) and subjective ones (e.g. depression, financial difficulty, expectations about job-loss or eviction). The findings show that those who report lower levels of subjective well-being are more likely to use the EIP to pay off debt, and this likelihood increases as the well-being measures worsen. Respondents who report having experiences of financial difficulty and negative expectations about the economy are more likely to spend the stimulus on nondurables and tend to allocate it to a wider range of spending categories.
In contrast to the U.S. and most other countries in the world, Belarus’ government offered very little support to its citizens during the pandemic. Lev Lvovskiy, researcher at BEROC, presented findings on how different sectors of the Belarusian economy and society were affected by the pandemic. Using the BEROC/Satio survey data, Lvovskiy and co-authors examine that the country still had sharp drops in mobility and economic shocks mainly caused by lockdowns of major trade partners. The pandemic significantly increased the probability of income reductions and they show that financial distress associates with the incidence of depression of Belarusians.
Gender and Wellbeing
Another central topic discussed at the workshop concerned the gender aspects of well-being and other related topics from gender economics.
An essential channel through which gender differences in well-being can arise is unequal representation in politics. Sonia Bhalotra, professor at the University of Warwick, presented a study on the relationship between maternal mortality and women’s political power in 174 countries. Maternal mortality is the leading cause of death and disability for women aged 15-44, and significantly higher in low-income countries – at levels similar to what high-income countries had in the early 1900s. Bhalotra and co-authors document that the costs of providing access to prenatal health services, antibiotics, and skilled birth attendance are relatively low. They therefore argue that there are likely other barriers to adopting these solutions. Male policymakers might have a weaker preference for preventing maternal mortality or less information on its prevalence and treatment. To gain insight, the authors use a staggered event-study approach and study the effect of gender quota implementations on the maternal mortality ratio (MMR, maternal mortality per birth). They find that, in countries that adopted quotas, the MMR declined by 10% following implementation, and this effect is stronger for larger quotas. Focusing on the mechanisms, the results show that gender quotas lead to a 5-8 percentage point (p.p.) increase in skilled birth attendance, a 4-8 p.p. increase in prenatal care utilization, 6-7 % decline in birth rates, and an increase in girl’s education by 0.5 years.
Elizaveta Pronkina, researcher at Université Paris-Dauphine, also shared findings relating to gender and politics but from a historical perspective. Her research studies historic institutional differences across communist regimes and women’s work experiences. The paper focuses on Lithuania and Poland, two countries that experienced different gender policies under a communist regime. After the second world war, Lithuania was controlled by the central government of the Soviet Union while Poland’s government was able to preserve its independence although being part of the Soviet bloc. Based on anecdotal evidence, the two countries had the same religious and political policies but different enforcement – Lithuania faced a hard and Poland a soft form of communism. To isolate the impact of the Soviet policies on women’s life decisions and account for differences in the countries’ pre-communist era, the authors only include regions that were part of the Russian empire until the end of the first world war. The findings show that women living under the Soviet regime were more likely to educate themselves and have on average two additional years of work experience (by 50 years of age).
A productive environment and reliable social interactions at work are also likely to be formative elements of people’s well-being, and gender might factor in here. Yuki Takahashi, PhD candidate in economics at the University of Bologna, presented his paper on how being corrected by others affects one’s willingness to collaborate with them in future work, as well as gender differences in these responses. Takahashi conducts a quasi-experimental design in which roughly 3000 participants individually and collectively solve a puzzle. The setting allows the researcher to observe individual ability, number of corrections, as well as whether the corrections were good (i.e., a mistake was corrected), or bad (i.e., a good move was corrected). The study analyzes how the different factors affect an individual’s likelihood of being selected as a collaborator in a last puzzle-solving stage where both participants win cash earnings based on joint performance. The results show that both genders respond negatively to a correction, but women more so than men. Men are less likely to collaborate with a person who has corrected their mistake, particularly men with high ability. The gender of the corrector is found not to matter.
Domestic violence (DV) is another gender aspect of well-being that has become particularly concerning during the pandemic. For many victims, lockdowns and curfews have meant more exposure to their perpetrator. Mobility restrictions have also implied more social isolation from family members and friends as well as increased economic distress, two other factors known to exacerbate DV. In a preliminary study presented by Damian Clarke, associate professor at the University of Chile, he and co-authors address the relationship between DV and quarantines in Chile. They use longitudinal data on police DV hotline calls and use of women’s shelters to measure DV incidence, criminal complaints of DV to police to measure reporting, and mobile phone data to measure mobility. Exploiting municipal variation in the timing of lockdown entry and exit, the study shows that lockdowns lead to more DV incidence and less reporting. DV shelter use increased on average by 11% with entry and reversed with exit. DV calls to the police hotline increased by 86% and persists after lockdown exit. DV crime reports decrease by 5% and increases by 10% with exit. Moreover, the authors document that lockdowns activate both DV mechanisms – increased economic distress and decreased mobility. In municipalities where lockdowns had a stronger impact on unemployment and mobility, they also find larger changes in DV.
Expectations About the Future and Parenthood
Two other studies presented at the workshop discussed the relationship between future expectations and well-being. Claudius Garten, researcher at the Technical University of Dortmund, presented findings on the role of homeownership. Garten and co-authors utilize individual-level survey data from 2007 covering 14 European countries. It contains information on homeownership status and wellbeing measures expressed as respondents’ expectations about future living standards five years from today. They find that expectations about future living standards are higher among homeowners relative to renters and strongly associated with the value of housing assets, suggesting that material security through housing ownership works as a channel for future wellbeing. Garten further argued that since most countries included in the sample have experienced rising house property prices and increased rents since 2007, the divergence between renters and owners is likely to be even more significant today, especially in urban areas.
The second presentation that discussed expectations about well-being in later life was by Alina Schmitz, researcher at the Technical University of Dortmund. Unlike housing, which is seen as a form of material security, Schmitz’s study focuses on the role of health infrastructure quality. Availability of care services may be seen as a safety net in case of illness and care dependency and should thus have a positive effect on wellbeing. The study performs a multilevel analysis on the individual, regional and, country level using micro-survey data on individuals’ life satisfaction and macro-data on the availability of long-term care beds, covering 96 regions from six European countries in 2015. The results show that the quality of care infrastructure is significantly related to the wellbeing of those aged above 50. Moreover, care infrastructure is particularly important for the wellbeing of those with health limitations (i.e. those who require that infrastructure either now or in the future).
Parenthood is another factor that is commonly thought of as a source of happiness. Contrary to this idea, European populations are aging rapidly and the young today have fewer children than the generations before them. The reason why people choose to have few children could be several – e.g. high opportunity costs and/or low benefits of having a large family. Is the fertility rate we see in the developed world today a result of the well-being-maximizing decisions of individuals? This is the main question asked in the paper presented by Barbara Pertold-Gebicka, assistant professor at the Institute of Economic Studies at Charles University. Her study utilizes European survey data to investigate the effect of having an additional unplanned child in five developed countries. To measure the effect of an additional unplanned child and deal with the fact that happy individuals tend to have more children, Pertold-Gebicka and co-author compare people who had twin births in their second pregnancy with parents of two children. Apart from life satisfaction, the most common wellbeing measure, the authors construct a second measure of wellbeing denoted as the happiness index – normalized value summarizing five questions about feelings over the last 5 months, interpreted as the relative frequency of positive feelings. They find no significant effect of having a third child on the well-being of parents. However, when separately looking at groups divided by age of children, they find that the effect of having an additional child on well-being is negative for fathers of younger children and positive for those of teenagers. For the parents of younger children, they show that the negative effect of having a third child is likely driven by increased feelings of nervousness and problems relating to accommodation.
Measuring Inequality and Social Deprivation
Some aspects of wellbeing such as feelings of unfairness or social connections can be quite ambiguous to study as they depend on context and are hard to quantify.
Nicolai Suppa, researcher at the Centre for Demographic Studies at the UAB, presented his research aimed to improve the measurement of deprivation in social participation (DSP) and complementing previous work with an additional outcome variable measuring a different dimension of deprivation. The study uses German survey data to measure how often common social activities are performed and then uses an intersectional approach (similar to the “Alkire-Foster method”) to assign individuals as deprived based on if and how often they practice these activities. The findings show that while the DSP measure correlates positively both with income poverty and material deprivation measures, it identifies a different sample of individuals. Being deprived in terms of social participation is associated with a significant loss of life satisfaction, a magnitude comparable to the loss of being unemployed.
Ingrid Bleynat, researcher at Kings College London, also discussed how to improve measurement but presented a study focusing on a different dimension of well-being, inequality. While quantitative approaches may give little account of the detailed mechanisms of inequality and its multidimensionality, qualitative studies often focus on a subset of the population which make results difficult to generalize. Bleynat and co-authors suggest a mixed approach, combining quantitative and qualitative assessments of inequality. They utilize neighborhood-level data on average household income in Mexico City to randomly select five households in each decile of the income distribution and conduct semi-structured interviews in these households to better understand the nuances of inequality. Based on these interviews they construct two qualitative measures. The first is called inequality of lived experiences and measures qualitative experiences in work, education, and health services across the income distribution. The second is called lived experiences of inequality, and measures feelings of stigma, discrimination, and social hierarchy across gender, ethnicity and location. The quantitative data confirms that Mexico City is highly unequal across the income distribution in terms of not only income but also social factors such as housing, health and food security. The results concerning the qualitative measures, such as inequalities in lived experiences or lived experiences of inequality confirm the existing understanding – e.g., that households belonging to the lower deciles are more likely to be mistreated in the public health sector, have a hostile school environment, and worse working conditions, or that women across the income distribution bear most of the childcare responsibilities, – but provide nuanced details on the interaction between material inequality and the reported experiences.
There is no doubt that the impact of Covid-19 on our well-being has been many-sided, and the presentations of the workshop have clearly demonstrated the broad spectrum of related problems and concerns, as well as their variation across institutional, social, political, economic, and cultural contexts.
Although we are well underway, further research and comprehensive data collection on how people have coped with and responded to the pandemic is needed to design sensible recovery policies and incentivize governments to implement them.
List of Participants
- Sonia Bhalotra (University of Warwick)
- Ingrid Bleynat (King’s College London)
- Damian Clarke (University of Chile)
- Thesia Garner (US Bureau of Labor Statistics)
- Claudius Garten (TU Dortmund)
- Barbara Pertold-Gebicka (Charles University)
- Knar Khachatryan (American University of Armenia)
- Anthony Lepinteur (University of Luxembourg)
- Lev Lvovskiy (BEROC)
- Elizaveta Pronkina (University Carlos III)
- Alina Schmitz (TU Dortmund)
- Nicolai Suppa (Centre for Demographic Studies at the UAB)
- Yuki Takahashi (University of Bologna)
Part 1 | Online Workshop on Dimensions of Well-being
Part 2 | Online Workshop on Dimensions of Well-being
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
We assess the effect of the Russo-Georgian conflict of 2008 and the Ukrainian-Russian conflict of 2014 on the well-being of minorities in Russia. Using the Russian Longitudinal Monitoring Survey (RLMS), we find that the well-being of Georgians in Russia suffered negatively from the 2008 Russo-Georgian conflict. In comparison, we find no general effect of the Ukrainian-Russian conflict of 2014 on the Ukrainian nationals’ happiness. However, the life satisfaction of Ukrainians who reside in the southern regions of Russia in close proximity to Ukraine is negatively affected. We also show that the negative effect of conflict is short-lived with no long-term legacy. Additionally, we analyze the spillover effect of conflict on other minorities in Russia. We find that while the well-being of non-Slavic and migrant minorities who have recently moved to Russia is negatively affected, there is no effect on local minorities who have been living in Russia for at least ten years.
Militarized conflict affects a myriad of socioeconomic outcomes, such as the level of GDP (Bove et al. 2016), household welfare (Justino 2011), generalized trust and trust in central institutions (Grosjean 2014), social capital (Guriev and Melnikov 2016), and election turnout (Coupe and Obrizan 2016). Importantly, conflict has also been found to directly affect individual well-being (Frey 2012, Welsch 2008).
However, previous research studying individual well-being in transition countries largely abstracts from heightened political instability and conflict proneness, while this has been particularly pertinent in transition countries. Examples of transition countries facing various types of conflicts are abound, such as Yugoslavia, Ukraine, Tajikistan, Russia, Armenia, Azerbaijan, Moldova, and so on. Therefore, it is imperative to explore how conflict shapes well-being in transition countries.
In a new paper (Gokmen and Yakovlev, forthcoming), we add to our understanding of well-being in transition in relation to conflict. We focus on the effect of Russo-Georgian conflict of 2008 and the Ukrainian-Russian conflict of 2014 on the well-being of minorities in Russia. The results suggest that the well-being of Georgians in Russia suffered negatively from the 2008 Russo-Georgian conflict. However, we find no general effect of the Ukrainian-Russian conflict of 2014 on the Ukrainian nationals’ happiness, while the life satisfaction of Ukrainians who reside in the southern regions of Russia in close proximity to Ukraine is negatively affected. Additionally, we analyze the spillover effect of conflict on other minorities in Russia. We find that while the well-being of non-slavic and migrant minorities who have recently moved to Russia is negatively affected, there is no effect on local minorities who have been living in Russia for at least ten years.
Data and Results
We employ the Russian Longitudinal Monitoring Survey (RLMS) which contains data on small neighborhoods where respondents live. Starting from 1992, the RLMS provides nationally-representative annual surveys that cover more than 4000 households with 10000 to 22000 individual respondents. The RLMS surveys comprise a broad set of questions, including a variety of individual demographic characteristics, health status, and well-being. Our study utilizes rounds 9 through 24 of the RLMS from 2000 to 2015.
In this survey, we identify minorities with the question of “What nationality do you consider yourself?” Accordingly, anybody who answers this question with a non-Russian nationality is assigned to that minority group.
We employ three measures of well-being. Our main outcome variable is “life satisfaction.” The life satisfaction question is as follows: “To what extent are you satisfied with your life in general at the present time?”, and evaluated on a 1-5 scale from not at all satisfied to fully satisfied. Additionally, we use “job satisfaction” and “health evaluation” as outcomes of well-being.
Our results suggest that our primary indicator of well-being, life satisfaction, for Georgian nationals has gone down in the Russo-Georgian conflict year of 2008 compared to the Russian majority (see Figure 1). The magnitude of the drop in life satisfaction is about 39 percent of the mean life satisfaction. Our estimates for the other two well-being indicators, job satisfaction and health evaluation, also indicate a dip in the conflict year of 2008. Lastly, our estimates show that the negative impact of the conflict does not last long. Although there is a reduction in the well-being of Georgians both on impact in 2008 and in the immediate aftermath in 2009, the rest of the period until 2015 is no different from the pre-2008 period.
Figure 1. Life Satisfaction of Georgian Nationals in Russia
Furthermore, when we investigate the effect of the Ukrainian-Russian conflict of 2014, we find no negative effect on the life satisfaction of Ukrainians. One explanation for why the happiness of Ukrainians in Russia does not seem to be negatively affected in 2014 is that the degree of integration of Ukrainians into the Russian society is much stronger than the degree of integration of Georgians. On the other hand, our heterogeneity analysis reveals that in the southern parts of Russia closer to the Ukrainian border, where there are more Ukrainians who have ties to Ukraine, Ukrainian nationals are differentially more negatively affected by the 2014 conflict. The differential reduction in the happiness of Ukrainians is about 19 percent of the mean life satisfaction.
Moreover, we also look into whether there is any spillover effects of the Russo-Georgian and the Ukrainian-Russian conflicts on the well-being of other minorities. We first carry out a simple exercise on non-Slavic minorities of Russia. We pick the sample of non-Slavic ex-USSR nationals that are similar to Georgians in their somatic characteristics, such as hair color and complexion. This group of people include the nationals of Azerbaijan, Kazakhstan, Uzbekistan, Kyrgyzstan, Turkmenistan and Tajikistan. We treat this group as “the countries with predominantly non-Slavic population” as their predominant populations are somatically different from the majority Russians, and thus, might either have been subject to discrimination or might have feared a minority backlash to themselves during the times of conflict. This conjecture finds some support below in Figure 2 in terms of violence against minorities. We observe in Figure 2 that hate crimes and murders based on nationality and race peak in 2008.
Our estimates also support the above hypothesis and propose that there is some negative effect of the 2008 conflict on non-slavic minorities’ happiness as well as their job satisfaction, whereas 2014 conflict has no effect.
Figure 2. Hate Murders in Russia over Time
Source: Sova Center
Next, we investigate the spillover effects of conflict on Migrant Minorities. Migrant minorities are minorities who have been living in their residents in Russia for less than 10 years. We conjecture that these minorities, as opposed to the minorities who have been in place for a long time, could be more susceptible to any internal or external conflict between Russia and some other minority group for fear that they themselves could also be affected. Whereas other types of longer-term resident minorities, which we call Local Minorities, are probably less vulnerable since they have had more time to establish their networks, job security, and most likely also have Russian citizenship. Our estimates back up the above conjecture and demonstrate that migrant minorities suffer negatively from the spillover effects of the 2008 conflict onto their well-being captured by any of the three measures, and not from the 2014 conflict, whereas there is no negative impact on local minorities.
In this paper, instead of focusing on the direct impact of conflict on happiness in war-torn areas, we contribute to the discussion on conflict and well-being by scrutinizing the well-being of people whose country of origin experiences conflict, but they themselves are not in the war zone. Additionally, we show that some other minority groups also suffer from such negative spillovers of conflict. Being aware of such negative indirect effects of conflict on well-being is essential for policy makers, politicians and researchers. Most policy analyses ignore such indirect costs of conflict, and this study highlights the bleak fact that the cost of conflict on well-being is probably larger than it has been previously estimated.
- Bove, V.; L. Elia; and R. P. Smith, 2016. “On the heterogeneous consequences of civil war,” Oxford Economic Papers.
- Coupe, T.; and M. Obrizan, 2016. “Violence and political outcomes in Ukraine: Evidence from Sloviansk and Kramatorsk”, Journal of Comparative Economics, 44, 201-212.
- Frey, B. S., 2012. “Well-being and war”, International Review of Economics, 59, 363-375.
- Gokmen, Gunes; and Evgeny Yakovlev, forthcoming. “War and Well-Being in Transition: Evidence from Two Natural Experiments”, Journal of Comparative Economics.
- Grosjean, P., 2014. “Conflict and social and political preferences: Evidence from World War II and civil conflict in 35 European countries” Comparative Economic Studies, 56, 424-451.
- Guriev, S.; and N. Melnikov, 2016. “War, inflation, and social capital,” American Economic Review: Papers & Proceedings, 106, 230-35.
- Justino, P., 2011. “The impact of armed civil conflict on household welfare and policy,” IDS Working Papers.
- Welsch, H., 2008. “The social costs of civil conflict: Evidence from surveys of happiness” Kyklos, 61, 320-340.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The question concerning the material situation of older people and its consequences for their wellbeing seems to be more important than ever. This is especially true given rapid demographic changes in the Western World and economic pressures on governments to reduce public spending. We use data from the Survey of Health, Ageing and Retirement in Europe (SHARE) to examine different aspects of old-age poverty and its possible effects on deterioration in health. The data contains information on representative samples from 12 European countries including the Czech Republic and Poland. We use the longitudinal dimension of the data to go beyond cross sectional associations and analyze transitions in health status controlling for health in the initial period and material conditions. We find that poverty matters for health outcomes in later life. Wealth-defined and subjective poverty correlates much more strongly with health outcomes than income-defined measure. Importantly subjective poverty significantly increases mortality by 58.3% for those aged 50–64 (for details see Adena and Myck, 2013a and 2013b).
When measuring poverty, the standard approach is to define the poverty threshold at 60% of median equalized income. This standardized measure offers some advantages, such as simplicity and comparability with already existing studies. However, there are valid arguments against its use when analyzing old-age poverty. The permanent-income theory provides arguments against current income as a major determinant of quality of life of older people. Moreover, poverty defined with respect to current income while taking account of household size through equalization, ignores other important aspects of living costs such as disability or health expenditures. Additionally, most analysis using income-poverty measures ignore such aspects as housing ownership and housing costs.
Our analysis examines different aspects of poor material conditions of the elderly. The first poverty definition refers to respondents’ wealth as an alternative to income-defined poverty. Poor households, defined with reference to wealth (“wealth poverty” – WEALTH), are those that belong to the bottom third of the wealth distribution of the sample in each country. For this purpose, household wealth is the sum of household real assets (net of any debts) and household gross financial assets. Secondly, we compare the above poverty measures to a subjective measure of material well-being. This measure is based on subjective declarations by respondents, in which case (“subjective poverty” – SUB) individuals are identified as poor on the basis of a question of how easily they can make ends meet. If the answer is “with some” or “with great” difficulty, individuals in the household are classified as “poor”.
One reflection of potential problems with the standard income poverty measure becomes visible when it is compared with the subjective measure. The graph below shows the differences in country rankings when using one or the other poverty measure. The country with the greatest disproportion is Czech Republic. While being ranked as second according to the income measure, it is ninth according to the subjective measure.Figure 1. Country Ranks in Old-Age Poverty According to an Income versus a Subjective Measure
Even more striking is the fact that the differences between ranks are not because of over or under classification of individuals as poor, but rather because of misclassification. Figure 2 shows that there is little overlap between different poverty measures. The share of individuals classified as poor according to all three measures is only 7.95%, whereas it is 60% according to at least one of the measures.Figure 2. Poverty Measure Overlap
We examine three binary outcomes measuring the well-being of the respondents – two reflecting physical health, and one measuring individuals’ subjective health. The two measures of physical health are generated with reference to the list of twelve symptoms of bad health and the list of twenty-three limitations in activities of daily living (ADLs). In both cases, we define someone to be in a bad state if they have three or more symptoms or limitations. The two definitions are labelled as: “3+SMT” (three or more symptoms) and “3+ADL” (three or more limitations in ADLs). Subjective health “SUBJ” is defined to be bad if the subjective health assessment is “fair” or “poor”. Finally, we also analyze mortality as an “objective” health outcome.
Poverty and Transitions in Well-Being and Health
There is some established evidence in the literature that poverty negatively affects health and other outcomes at different stages of life. At the same time, there is little evidence on how the choice of the poverty measure might result in under- or over-estimation of the effects of poverty. We address this question by examining different poverty measures as potential determinants of transitions from good to bad states of health.
The results confirm that living in poverty increases an individual’s probability of deterioration of health. In a compact form, Figure 3 presents our results from 12 separate regressions (4 outcomes, three poverty measures). Here we report the odds ratios related to the respective estimated poverty dummies. Individuals classified as poor according to the income measure are 37.7% more likely to report bad subjective health in a later wave of the survey than their richer counterparts; they are 4.5% more likely to suffer from 3 or more symptoms; 18.7% more likely to suffer from 3 or more limitations; and 5% more likely to die. The last three effects, however, are not statistically significant.
In contrast, the effects of wealth-defined poverty and subjectively assessed poverty are 2-8 times stronger than those of income poverty, and they are also significant for all outcomes but death. Overall, wealth-defined poverty and subjective assessment of material well-being strongly correlate with deterioration in physical health (exactly the same goes for improvements in health, see Adena and Myck 2013b).Figure 3. Poverty and Transitions from Good to Bad States Overlap
Poverty and Mortality in the Age Group 50-64
Our analysis reveals differences between age groups and confirms the decreasing importance of income (and thus income defined poverty) with age. As compared to the average effects presented in Figure 3, for the younger age group 50–64 income poverty proves more important as a determinant of bad outcomes, with transition probabilities between 20 and 40% for all outcomes (see Figure 4). The magnitudes are closer to those of other poverty measures, but still lower in all cases. Importantly, we find that wealth-defined and subjective poverty is an important determinant of death in the age group 50–64.Figure 4. Poverty and Transitions from Good to Bad States 50-64 Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0, Wave 3, release 1, Wave 4, release 1).
The role of financial conditions for the development of health of older people significantly depends on the measure of material well-being used. In this policy brief, we defined poverty with respect to income, subjective assessment, and relative wealth. Of these three, wealth-defined poverty and subjective assessment of material well-being strongly and consistently correlate with deterioration and improvements in physical and subjective health. We found little evidence that relative income poverty plays a role in changes in physical health of older people. This suggests that the traditional income measure of household material situation may not be appropriate as a proxy for the welfare of older populations, and may perform badly as a measure of improvements in their quality of life or as a target for old-age policies. To be valid, such measures should cover broader aspects of financial well-being than income poverty. They could incorporate aspects of wealth and the subjective assessment of material situations as well as indicators more specifically focused on the consumption baskets of the older population.
- Adena, Maja and Michal Myck (2013a): “Poverty and transitions in key areas of quality of life”, in: Börsch-Supan, Axel, Brandt, Martina , Litwin, Howard and Guglielmo Weber (eds.) “Active Ageing and Solidarity between Generations in Europe – First Results from SHARE after the Economic Crisis.”
- Adena, Maja and Michal Myck (2013b) Poverty and Transitions in Health, IZA Discussion Paper 7532, IZA-Bonn.
 For a literature review, see our publications.