The Rollercoaster of Subjective Well-Being in Times of Multiple Crises: Evidence of Five Waves of Bi-Annual Panel Data of FReDA Survey

Bujard, Martin; Hudde, Ansgar; Kriechel, Lisa Article — Published Version The Rollercoaster of Subjective Well-Being in Times of Multiple Crises: Evidence of Five Waves of Bi-Annual Panel Data of FReDA Survey Social Indicators Research Suggested Citation: Bujard, Martin; Hudde, Ansgar; Kriechel, Lisa (2025) : The Rollercoaster of Subjective Well-Being in Times of Multiple Crises: Evidence of Five Waves of Bi-Annual Panel Data of FReDA Survey, Social Indicators Research, ISSN 1573-0921, Springer Netherlands, Dordrecht, Vol. 180, Iss. 3, pp. 1353-1385, https://doi.org/10.1007/s11205-025-03707-6 This Version is available at: https://hdl.handle.net/10419/333350 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ ORIGINAL RESEARCH Received: 30 September 2024 / Accepted: 20 August 2025 / Published online: 21 October 2025 © The Author(s) 2025 Lisa Kriechel [email protected] 1 Federal Institute for Population Research (BiB), Wiesbaden, Germany 2 Institute for Medical Psychology, Medical Faculty, University Heidelberg, Heidelberg, Germany 3 Institute of Sociology and Social Psychology, University of Cologne, Cologne, Germany The Rollercoaster of Subjective Well-Being in Times of Multiple Crises: Evidence of Five Waves of Bi-Annual Panel Data of FReDA Survey LisaKriechel1· MartinBujard1,2 · AnsgarHudde3 Social Indicators Research (2025) 180:1353–1385 https://doi.org/10.1007/s11205-025-03707-6 Abstract In times of polycrisis, such as COVID-19, the Russian war against Ukraine, and inflation, fear and uncertainties challenge many people. While the impact of the pandemic on subjective well-being was thoroughly studied, the medium-term effects and impacts of more recent crises are still to be observed. Based on the first five waves of the bi-annual (and once tri-annual) large-scale panel FReDA, we show the trend of life satisfaction over 16 time points between April 2021 and January 2023. In addition, we conduct fixed effects and random effects for five subwaves. Results reveal a mostly increasing level of life satisfaction, with setbacks during times of COVID-19 and the Ukraine war. These setbacks also result from restrictions during the pandemic and a higher consumer price index. In a comparison between groups that differentiate between household incomes, the lowest income tercile is particularly affected by crises. Risk factors are unemployment or a bad financial situation. Having children and being in a committed relationship exhibited protective factors. We further observed that the rise in inflation widens the happiness gap so that single parents are disadvantaged. Our research design proved the high potential of combining a higher-frequency panel with monthly information within a wave. As the first study applying this with FReDA data, it paves the way for future analyses of short-term fluctuation with panel data. Our findings on the discontinuity of life satisfaction in times of polycrisis point out that a monitoring of future trends, vulnerable groups, and policy support is indispensable. Keywords Life satisfaction · Subjective well-being · High-frequency panel · COVID-19 · Polycrisis · Uncertainties 1 3 L. Kriechel et al. 1 Introduction In early 2020, the Covid-19 pandemic hit the entire world and disrupted social life. This was, however, not the only crisis that many societies, including Germany, have since experienced. Increasing summer heat and floods such as in the Ahr-region in Germany in 2021 that killed more than 180 people make climate change perceptible in concrete terms. The elevating threat of climate change increases both the frequency and the intensity of such extreme weather occurrences (Markard & Rosenbloom, 2020). In early 2022, Russia initiated its full-scale war against Ukraine which shook many people’s sense of security and sparked fears of more aggressions. Furthermore, given Germany’s dependence on cheap gas from Russia, this war initiated an energy crisis and consumer price shock: the 2022 inflation rate was the highest that Germany has seen in about 50 years (destatis, 2024a). In total, since the early 2020 s, Germany has been amidst a phase of multiple crises. These multiple crises or polycrisis (Lawrence et al., 2024) appear more severe in their closely timed form and vehemence than those in recent decades; particularly, because they are occurring on health, environmental, political-military, and economic levels at the same time. In contrast to individual events of crisis happening over the life course, such as separation, illness, death of relatives, or unemployment (Bernardi et al., 2019), these crises are external, occurring in Europe or even globally. They are potentially affecting many individuals either directly such as through school closures with negative consequences on adolescents’ mental health (Ludwig-Walz et al., 2022) or indirectly by increased uncertainty during crises (Comolli, 2023). The COVID-19 pandemic, which spread throughout Europe in 2020, and its restriction policies changed everyday lives of nearly everybody fundamentally. Therefore, it is not surprising that there is a vast and ever-increasing amount of research observing the implications of the pandemic. Subjective well-being is often the focus of such studies (Bachmann et al., 2023; Easterlin & O’Connor, 2023; Guan et al., 2024; Hudde et al., 2023; Rogowska et al., 2020). However, previous research varies in the operationalization: many compare pre-COVID levels to COVID levels. Others observe a few weeks or months during the pandemic. What is yet to be further observed, due to the recency of the official end of the pandemic, is research on post-COVID life courses (for commendable exceptions see: Huebener et al., 2024; Patzina et al., 2024) for two reasons: first, to analyze medium and longterm effects of the pandemic to examine if the observed reductions in well-being during the pandemic are persisting or if and under which circumstances baseline levels are reached again. Second, to analyze the influence of other crises, in particular the Russian war against Ukraine which also impacted other European countries due to war anxiety, energy crises, and increasing prices. Therefore, in the beginning of 2022, multiple crises affected citizens simultaneously and offered an unpredictable future which might impact life satisfaction. Though life satisfaction is often stable over an extended time, it can be affected by changes in one’s life (Headey et al., 2013). For instance, life satisfaction increases upon marriage by 0.14, possibly due to increasing relationship quality (Gattig & Minkus, 2021). In contrast, within the year of the respective event, life satisfaction decreases by 0.59 due to the death of one’s child and by 0.54 after the death of one’s partner (Asselmann & Specht, 2023). However, looking at monthly data has the advantage that such changes can be observed more closely: compared to the month before the loss of one’s partner, the bereaved partner’s life satisfaction one month after their loss has decreased by 1.03 (Hudde & Jacob, 2023). 1 3 1354 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… In times of multiple crises, events of crises at specific points in time (such as the fullscale war in Ukraine since February 2022, vaccination campaign etc.) are of interest (for monthly effects of crises on fertility see: Bujard & Andersson, 2024). While many of the large panels(for an overview see Bujard & Wagner, 2023) such as the European Social Survey (ESS), the Generations and Gender Survey (GGS), the German Socio-Economic Panel (GSOEP), Household, Income and Labour Dynamics in Australia (HILDA), or the Survey of Health, Ageing and Retirement in Europe (SHARE) interview the participants only once a year or even less, many social scientists tried to find measurements on a monthly basis such as through the German Internet Panel(Blom et al., 2020) or temporarily the UK Household Longitudinal Study (McFall & Garrington, 2011). The rapid increase of computer-assisted web interviewing (CAWI) mode for surveys in the last years was sometimes accompanied by a reduction of questionnaire length and an increase of subwaves within a year (Gummer et al., 2020). The family demographic panel FReDA(Hank et al., 2024; Schneider et al., 2021) we used for our analyses is an example for a large-scale panel with semi-annual data. The costand web-technology-driven semi-annual CAWI designs(Wolf et al., 2021) and the information for specific months in a yearly panel(Hudde & Jacob, 2023) offer a potential for analyses over the course of a year which is rarely used yet, since the yearly analysis patterns of panel remains predominant. However, in order to analyze the course of life satisfaction during multiple crises, closelytimed regular information on life satisfaction and longitudinal data is necessary. There are only few examples of panel studies measuring life satisfaction in the context of (post-) pandemic times or multiple crises with more than one wave per year in 2022-23 (Easterlin & O’Connor, 2023; Huebener et al., 2024). However, they suffer from a low number of cases (Huebener et al., 2024) or lack some life-course relevant variables and are therefore analyzed on the macro level (Easterlin & O’Connor, 2023). Also, by tackling these issues, our paper contributes to the literature in a twofold way: First, we analyze the development of subjective well-being in times of multiple crises on an almost monthly basis. Thereby, to our knowledge, we are the first to conduct group-specific analyses with several observation points per year and estimate their individual level determinants with fixed and random effects. Second, we are using information of subwaves of a semi-annual (and once tri-annual) panel and profit from the information on different survey months in the field phase of each subwave. We are the first to our knowledge to combine between-(sub)wave and within-wave information of a semi-annual panel, which allows for descriptive analyses for life satisfaction for six to eight months a year. We discuss advantages and pitfalls of our approach using semi-annual and monthly information. We analyze five panel waves of FReDA between early 2021 and the beginning of 2023, benefitting from information on about 20,000 anchor interviews each wave. This allows us to account for life satisfaction and its individual determinants during multiple crises, namely the COVID-19 pandemic, prevalent especially during 2021, as well as the increased Russian aggressions in Ukraine accompanied by the energy crisis from 2022 until the end of the survey period, and finally the persistent climate crisis. 1 3 1355 L. Kriechel et al. 2 Background and Literature Review 2.1 Well-Being During COVID-19 Many studies focused on shortand medium-term consequences of the pandemic (for a review, see Patzina et al., 2024). Some recent studies used several time points during the pandemic and thus highlighted the dynamic relations between COVID-19 and well-being or psychological health. For instance, Easterlin and O’Connor (2023) find that pandemic severity, measured by deaths due to COVID-19 affected life satisfaction across Europe until the summer of 2022. By summer 2022, satisfaction levels had mainly returned to pre-pandemic levels in most countries. Patzina et al. (2024) study satisfaction trends in Germany, finding negative trends and no recovery by summer 2022. Importantly, they find no clear heterogeneity in trends between sociodemographic groups, but rather uniform negative effects of the pandemic. Carlsen et al. (2022) compared life satisfaction among those whose work situation and infection status has changed between early and late 2020. They found that life satisfaction suffered from a COVID-19 infection as well as from job-related changes. There is also evidence that those who were afraid of COVID-19 exhibited lower life satisfaction (Dymecka et al., 2021). Therefore, changes in life satisfaction differed by country and further experiences. We thus hypothesize: H1 Life satisfaction suffers from increasing pandemic-related restrictions. Analyses with a higher frequency such as monthly panels are important, because the number of infections and restrictions were associated with people’s mental health which explains the heterogeneity in adverse health during times of the pandemic (Reis et al., 2023). Conducting a weekly survey, it was found for Germans that while their life satisfaction suffered from lockdowns, their psychological strain benefitted from two weeks of contact restrictions (Levacher et al., 2023). Another weekly panel study showed that such short-term increases in mental health are associated with changed time-use (e.g., gardening, exercising), whereas an increasing time spent to read news about the pandemic attenuated psychological well-being (Bu et al., 2021). These dynamics might also originate from the altering influences on life satisfaction: Bakkeli (2021) found that before time COVID-19, life satisfaction was predominantly predicted by health and work-life balance, whereas during the pandemic, the strongest factor was sharing a household with one’s partner. Since the analyses within this paper also focus on parents, their situation during times of the pandemic will be explained. Parents experienced multiple institutions restricting their lives: regional governments, employers, and childcare facilities all had their own set of policies that also changed several times. Especially inconsistencies in such policies burdened parents (Dinh et al., 2024). Moreover, parents experienced more dynamic shifts in restrictions because schools could close, classes could be cancelled, or children could be sent home due to symptoms on short notice. Parents were responsible for maintaining their own structures and well-being as well as of their children. Parents’ well-being suffered from changes in daily routines (Adams et al., 2021; Cusinato et al., 2020) and distress increased among parents during those times (Adams et al., 2021; Freisthler et al., 2021). Moreover, the more children parents had, the more did perceived pandemic burden attenuate their life satisfaction (Schmid et al., 2024). Especially parents of children attending kindergarten or schools 1 3 1356 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… faced difficulties due to closings and worries about infections. Parents who were obligated to home school their children during the pandemic experienced significant increases in psychological distress (Adams et al., 2021; Calear et al., 2022). This also resulted from the dual burden of parents to pursue their paid job at home while also monitoring their children’s virtual learning (Dinh et al., 2024). The pandemic distressed many parents enough to engage in child abuse and neglect (Griffith, 2021). In Germany, limited in-person schooling stretched until mid-2022. Overall, parents experienced a greater extent of restrictions compared to those without (young) children. Nevertheless, it was found that parents were more satisfied with their lives compared to those without underage children (Bujard et al., 2023; Schmid et al., 2024), which is even fostered by a good quality of family relations (Bujard et al., 2023). Moreover, we also looked at the disparate courses of life satisfaction for differing household income groups. This stems from the finding that those with lower incomes also reported the highest depression rates during the pandemic (Ettman et al., 2024). Previous research showed that the association between financial worries and depression is stronger than between income loss and depression (Hertz-Palmor et al., 2021). The reason for that is that financial distress mediates the association between both income loss and job loss and mental health indicators (Miquel et al., 2022). Therefore, in the case of the pandemic, changes in income or a job loss are less influential than the perceived financial status which we substituted with household incomes. 2.2 Beyond COVID-19: Polycrisis, Uncertainty, and Well-Being Given its recency, there are less studies on the role of other and more recent elements of the current polycrisis. Beyond the few available studies, we can learn from related research, e.g., from previous occurrences of crisis-events on well-being. Previous research shows that other elements of the current polycrisis also harm well-being. For instance, following Russia’s full-scale war against Ukraine, Germany has recently experienced its highest inflation rate since about half a century (destatis, 2024a) and it is well-established in economic research that inflation negatively affects life satisfaction (e.g., Cupák & Širaňová, 2023; Di Tella et al., 2001). Our second hypothesis therefore states: H2. Life satisfaction suffers from increasing consumer prices. Furthermore, while Russia’s war against Ukraine has centrally affected Ukrainians, its negative impact on well-being also extends towards Europe more generally (Celuch et al., 2024). A study with a convenience sample traced well-being in several European countries during the weeks surrounding Russia’s invasion of Ukraine and found a decline directly following the invasion and on days with greater news coverage of the war (Scharbert et al., 2024). As further element of the polycrisis, climate change increases the risk and severity of extreme weather events while extreme weather reduces the life satisfaction of the affected (e.g., Möllendorff & Hirschfeld, 2016). Although the salience of the climate crisis may increase following extreme-weather events, the climate crisis is rather a continuous background threat (Falzon et al., 2021). In sum, various elements of the current polycrisis are detrimental to people’s well-being and life satisfaction. The polycrisis is, however, more than just a sequence of distinct crises. In the polycrisis, people are affected by new crises while previous ones are still ongoing or have ended 1 3 1357 L. Kriechel et al. so recently that societal recovery processes are far from complete (Tooze, 2021). At the individual level, the lack of sufficient recovery time between crises might prevent people from restoring their pre-crisis baseline level of well-being. While some adversity can build resilience, excessive cumulative stress during a polycrisis might exceed the harm that each individual crisis element would have if experienced in isolation (cf. Pearlin et al., 2005; Seery et al., 2010; Turner & Lloyd, 1995). Beyond the more direct consequences of the specific crisis, the polycrisis may foster general anxiety, uncertainty, and pessimism which in turn harm well-being. The repeated or continued experience of specific crisis-events induces a sense of unspecific or generalized danger. Cooper and Nagel build upon Ulrich Beck’s concept of the “risk society” and describe the current era as a time where people have the sense that “anything can go wrong at any time” (Cooper & Nagel, 2022, p. 333). This feeling hampers well-being and creates “sustained uneasiness” (Cooper & Nagel, 2022, p. 333). The fact that risk itself harms well-being is shown by Möllendorff and Hirschfeld (2016) who find that people living in regions at risk of hurricanes exhibit lower life satisfaction, even when that risk did not materialize and they did not experience any tangible damage. This matches the findings from a recent qualitative investigation in Poland that analyzes the effect of both the COVID-19 pandemic and Russia’s attack against Ukraine. They report people’s feelings of anxiety and of an omnipresence of risk. These risks harm people’s well-being not only by affecting their present lives, but also by harming their outlook, their “imagined futures” (Pustulka et al., 2024). The consequences of uncertainty, pessimism, and harmed future outlooks are also shown by family demographic research. Such research finds that the societal uncertainly and pessimism induced by crises – including economic crises and COVID-19 – depresses people’s fertility plans (Comolli, 2023; Ivanova & Balbo, 2024; Vignoli et al., 2020). Crises can cause pessimism and this pessimism is in a reciprocal relationship with satisfaction. Experiencing lower well-being at one time – e.g., due to one crisis – induces pessimism and the experience of pessimism reduces future satisfaction (Joshanloo, 2024). Thereby, the polycrisis of contemporary societies may harm well-being beyond the crisis’ more direct effect and via increased anxiety uncertainty and pessimism. In sum, it is important that studies conceptualize different elements of the polycrisis not only as isolated from one another, but consider them as connected. With our analyses, we aim to contribute to such research and to the continuous tracing of people’s well-being as the polycrisis evolves. 2.3 Short-term Analyses with Panel Data 2.3.1 Overview of Different Types of Panel Studies These findings and the characteristic of multiple crises, which comprise several external events and short-term changes of threat or disadvantages on living conditions, reinforce the need for data that enables tracing such change. There are various ways in which panel studies with different designs can be used to trace short-term changes and the following sections describe those and synthesize them in Table 1. We focus on three types of panel survey designs: typical annual surveys with short survey periods, annual surveys with stretched survey periods, and higher-frequency surveys. 1 3 1358 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… First, in the most typical design for survey panel studies, people are surveyed yearly and interviews are clustered in a main field period that covers a few weeks to a few months of the year. Examples for this design are the GSOEP, the British Household Panel Study (BHPS), or HILDA. For instance, In the GSOEP’s main samples, more than half of the interviews are conducted in February and March and about 95% of interviews are conducted in the first half of the year. Second is a modified version of the typical design, in which people are surveyed yearly but interviews are spread evenly across the year. Possibly the most important benchmark example is Understanding Society, the follow-up project of the BHPS. Here the whole sample was divided into monthly sub-samples, each of them representative of the UK popula- (1) Annual waves, field period during few months (2) Annual waves, field period distributed evenly over the year (3) Multiple waves per year Example study GSOEP1; British Household Panel Study Understanding Society (main study) FReDA, Understanding Society Covid19 Study Mode CAPI, PAPI or CAWI CAPI, PAPI or CAWI Usually CAWI Study trajectories around individual life events or crisis-induced life changes Requirement: Detailed information on timing of life events (e.g., monthly) X X X Study effect shortly after macro-trends and crises, betweenindividuals design Requirement: Sufficiently large and representative sample per survey period (e.g. month) X X Study effect shortly after macro-trends and crises, within-individuals design Requirement: Variables of interest included in several subannual waves X Table 1 Possibilities for shortterm analyses with panel data with different survey designs 1This concerns the GSOEP main sample, certain subsample deviate from this. 1 3 1359 L. Kriechel et al. tion (Buck & McFall, 2012). This study design was chosen so that “differences over time within a wave can be compared using nationally representative samples” (Buck & McFall, 2012, p. 10). Third are panel studies that survey people more frequently than yearly. Several highfrequency panel studies cover a brief time and are initiated in response to a specific crisis, such as the COVID-19 pandemic. For instance, Understanding Society has added nine survey waves with a shortened and adjusted questionnaire during the first two years of the COVID-19 pandemic. As further example, the German COMPASS survey was started after the onset of COVID-19 and collected data by conducting 17 waves within 30 months. A few such studies are continued over several years, such as the German Internet Panel (GIP; Blom et al., 2020) which conducts six waves per year. However, the number of cases for COMPASS and GIP are in the lower four-digit range. Finally, our chosen data set FReDA surveys individuals twice per year (Bujard et al., 2024; Hank et al., 2024; Schneider et al., 2021). With a nationally representative sample of more than 20,000 individuals (plus more than 8,000 partner interviews), we are not aware of any panel study that features multiple interviews per year for a comparably large sample. 2.3.2 Analytical Potential of Different Types of Panel Studies Table 1 gives an overview on different possibilities for short-term analyses with panel data. Panel studies with all of these types of survey designs can be used to trace changes due to individual life events in detail, such as changes in well-being as people enter unemployment, move to a new home, or become parents. Such analyses are feasible as long as the studies ask respondents about their detailed life calendar, such as in which specific month they experienced these transitions and life events. Hudde and Jacob (2023) have illustrated this previously untapped potential for life course research by leveraging the month-specific temporal distance between life events and panel survey interviews. For a detailed description and an illustration via simulation methods, see Hudde and Jacob (2023), for an application and modification, Hudde (2024). This approach can also be applied in the context of macro-level crises. For instance, one could trace people’s well-being surrounding job loss in the course of an economic crisis (e.g., in several European countries following the 2007-08 financial crisis) or if their apartment rent spikes during a period of high inflation. Most major panel studies – including GSOEP, Understanding Society, and FReDA – include information on major life events like family and employment changes with at least month-specific information, however, they may not cover all interesting changes, such as apartment rents, on a monthly basis. While the typical panel design of studies like GSOEP is sufficient to apply this approach to most life events and individual consequences of societal change, it reaches its limits when external shocks are sudden. Suppose that a major wave of pandemic infections of employment layoffs happen in January of a given year and survey interviews are conducted during the first half of the calendar year. This would allow to trace well-being following the first half-year after infection, but not during the second half-year, because no one is interviewed six to twelve months after the shock. To better study population responses to macro-level shocks and changes, fieldwork periods need to cover extended parts of the year. Sufficient fieldwork coverage can be achieved 1 3 1360 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… tember 2021. During this time, the fourth COVID-19 wave occurred. By November 2021, mean life satisfaction was rather high. The receding and preceding months were characterized by important political changes: the new government was elected and came into office, booster vaccinations were available, the Omicron variant was on the rise, and the health sector was requested to be vaccinated or tested to work. Moreover, as Fig. 2 shows, both restrictions due to the pandemic as well as consumer prices increased in the winter of 2021. This might explain the drop in mean life satisfaction in January 2022. In 2022, restrictions decreased, while the consumer prices rose distinctly after the enhanced Russian aggressions towards Ukraine. Mean life satisfaction decreased in June 2022. Despite its broad confidence interval due to a smaller sample (n = 199), mean life satisfaction peaked in July 2022. Thereafter, life satisfaction decreased again, though the values were higher compared to mid-2021. However, life satisfaction has not converged to the levels seen before these crises, which were between 7.3 and 7.5 between 2015 and 2019, as analyses based on GSOEP data show (Bujard et al., 2023). Mean levels within this article and those of the GSOEP should be compared cautiously, since different populations are observed. Therefore, it is the authors’ assumption (which can be critically questioned) that mean life satisfaction has not converged to pre-pandemic levels. In the appendix, the course of life satisfaction over time, which illustrates adjusted means (Figure 7), can be found. To avoid that time trends are confounded, the model controlled for the same covariates as the regression models (i.e., OSI, CPI, education level, employment status, number of children, degree of urbanization, living in East Germany, sex, age, and migration background). All mean values were slightly higher than the weighted means. This especially applied to the respective last months of each wave. Therefore, participation in the end of a survey might be selective. Between April 2021 and November 2021, the adjusted means increased almost continuously. With the increased aggressions against Ukraine, the adjusted means were lowered only slightly. After their peak in the July of 2022, the adjusted means decreased again, but were above the values of mid-2021. 4.2 Semi-and Tri-Annual Analyses To Predict Life Satisfaction Figures 3 and 4 depict the random and fixed effects. In the appendix, Table 4 contains all information on the models, including confidence intervals and p-values. The random effects that can be taken from Fig. 3 show that higher OSI levels were related to lower levels of life satisfaction (std. beta = − 0.04, p =.003). Similarly, a higher CPI was associated with worse well-being (std. beta = − 0.11, p =.021). People with higher education (std. beta = 0.04, p <.001), who were not unemployed, or who exhibited a better financial situation (std. beta = 0.21, p <.001), reached a higher life satisfaction. Moreover, the financial situation was the strongest predictor of life satisfaction in the between model. Furthermore, those who were in a partnership (std. beta = 0.15, p <.001) or had children also exhibited a better wellbeing during times of multiple crises. As compared to those living in cities, inhabitants of rural areas were more satisfied with their lives (std. beta = 0.02, p =.003). The same applied to men (std. beta = 0.02, p =.003), younger respondents (std. beta = − 0.09, p <.001), and firstgeneration migrants (std. beta = 0.04, p <.001). Finally, mean life satisfaction became better in each survey wave. The broad confidence intervals during times after the more severe war in Ukraine still signal a certain heterogeneity within the sample. The number of changes between groups can be taken from Table 5. 1 3 1367 L. Kriechel et al. Fixed effects can be taken from Fig. 4. When OSI (b = −0.01, p <.001) and CPI (b = −0.03, p <.001) levels increased, life satisfaction was attenuated. Moreover, those who left unemployment experienced an upward trend in their well-being which especially applied to those starting out as self-employed (b = 0.44, p <.001). Compared to the magnitudes of life changes and their impact on life satisfaction, as mentioned in the introduction, this coefficient was rather high. When comparing the fixed and random effects of the employment status, the trajectories seem to be more relevant to life satisfaction than the between comparisons. An improving financial situation was also accompanied by increasing levels in life satisfaction (b = 0.18, p <.001). The strongest predictor of life satisfaction among the fixed effects was a new partnership which increased life satisfaction (b = 0.48, p <.001). The large disparities in coefficients also shows that entering a partnership (fixed effects) and being in a relationship (random effects) are differently related to life satisfaction. Furthermore, the birth of at least the third child was associated with increasing life satisfaction (b = 0.12, p =.035). Fig. 3 Random effects to predict life satisfaction. Standardized beta coefficients are presented. Categorical variables are printed in italics. 95% confidence intervals were used. Stars indicate significance levels (*** p <.001, ** p <.01, * p <.05). OSI = Oxford Stringency Index; CPI = Consumer Price Index; ref = reference category of categorical variables; Migr. Backgr. = migration background; gen. = generation 1 3 1368 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… 4.3 Group Differences in the Course of Life Satisfaction during Times of Multiple Crises 4.3.1 Economic Differences The respondents’ household equivalent incomes at the times of the second panel wave in the summer of 2021 was transformed into terciles. The groups differentiated by this baseline value were observed over 2-month intervals (see Fig. 5). Over the time, the tercile with the highest income kept exhibiting the highest mean life satisfaction, while the lowest mean life satisfaction was reported by those with the lowest income. Nevertheless, the course of life satisfaction over time was different at times. Mean life satisfaction of the more affluent decreased in the winter of 2021, while it increased among those with the lowest income. This convergence quickly changed when the lowest income tercile reported a steeper decline in mean life satisfaction than the other two groups with the Russian war in early 2022. By the end of the year, with the exploding CPI, mean life satisfaction of the group with the lowest baseline income reached an all-time low. Fig. 4 Fixed effects to predict life satisfaction. Unstandardized coefficients are presented. 95% confidence intervals were used. Stars indicate significance levels (*** p <.001, ** p <.01, * p <.05). OSI = Oxford Stringency Index; CPI = Consumer Price Index; ref = reference category of categorical variables 1 3 1369 L. Kriechel et al. 4.3.2 Differences Due To Household Constellations Figure 6 depicts the course of life satisfaction for different household constellations, namely differentiation by partnership status as well as parenthood. Couples overall reached higher mean life satisfaction values than those without a partner. Single parents mostly exhibited the lowest life satisfaction. Especially with the Russian war, the former convergence between single parents and singles without children stopped. However, by the end of the year, their man life satisfactions converged again, indicating the recovering well-being of single parents. 4.4 Robustness Checks To test the robustness of our findings, we first observed if there were any differences when we excluded those who did not participate in all panel waves. The multivariate results can be taken from the Appendix (see Table 6). Since those results hardly differed from those of our main analysis in regard to coefficients and significance levels, we conclude that our results are not biased due to panel attrition. Fig. 5 The course of life satisfaction for household income terciles at baseline. Weighted mean values of life satisfaction are illustrated over survey months (months are in the first row of the x-axis labels, years in the second row). The three groups indicate the baseline quantile of the household equivalent income (GCEE) in the second survey wave (summer 2021). The first quantile received the lowest equivalent household income, while the third quantile received the highest amount 1 3 1370 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… We further controlled whether the other macro level variables differently affected life satisfaction. The results can be taken from Table 7 in the Appendix. We found that there were no significant random effects for the search engine indicators, however, the random effects of OSI (std. beta = − 0.03, p =.018) and CPI (std. beta = − 0.16, p =.00) could still be observed. Moreover, the coefficients of the search engine indicators were close to zero. Regarding the fixed effects, all macro level predictors were associated with a lower life satisfaction. 5 Discussion This article has two central aims. The first is to observe the course of subjective well-being during times of multiple crises and thereby also during and after the COVID-19 pandemic. Second, the methodological aim is to scrutinize the potential of higher-frequency information with panel data and pave the way for a more frequent use of this information. Based on data of the semi-annual panel FReDA for its first five subwaves 2021–2023, we trace life satisfaction trends with information on a survey period that includes 16 different months and relate them to the course of COVID-19, the Ukrainian war, and the salience of climaterelated issues, family constellations, and economic indicators. In addition, we run panelanalyses for these five waves. We find the sharpest reduction in life satisfaction during Fig. 6 The course of life satisfaction for different household constellations. Weighted mean values of life satisfaction are illustrated over survey months (months are in the first row of the x-axis labels, years in the second row). The groups indicate the partnership and parenthood status 1 3 1371 L. Kriechel et al. strict COVID-19 related restrictions. During multiple crises, life satisfaction has a monthly fluctuation between 6.5 and 7.4; plus, with levels around 6.8 in early 2023 not recovered to the levels seen before 2020. These findings contrast the idea of high stability in life satisfaction and the reported fluctuations contribute to our understanding of the rollercoaster of subjective well-being. Moreover, such strong changes might correspond to Diener’s (2006) theory. Though we only know pre-COVID levels of life satisfaction in Germany from other datasets, the severe ups and downs in life satisfaction during times of our used survey and the comparatively low level in the most recent wave could possibly indicate that baseline levels from before the pandemic have not been reached yet. This might be an indicator of changing setpoints for some of the affected people (Diener et al., 2006), or an additive negative effect of different crises that constitute the polycrisis on life satisfaction. In this case, the hedonic treadmill argument of a recovery within about a year (Diener et al., 2006) would not be fulfilled. Overall, the field is just at the beginning of understanding which elements of people’s lives are most affected by the current polycrisis and how this differs between societal subgroups. With our analyses taking advantage of a large-scale, nationally representative study based on semi-annual panel data, we aim to contribute to this emerging literature. Particularly affected during crises were people from the lowest income quintile, whereby having children, a (new) partner, higher education, and leaving unemployment turned out to be potential resilience factors during crises. In detail, our panel analyses show negative effects of both indicators of COVID-19 restrictions and economic crisis following the energy shock after the Russian war against Ukraine, namely the Oxford stringency index (OSI) and consumer price index (CPI). Therefore, hypotheses 1 and 2 were confirmed. The recovery of life satisfaction after the majority of people got vaccinated and societies opened up again in the autumn of 2021 was only partial and was not completed by 2022 or the beginning of 2023. Our analyses suggest that the economic consequences of the Russian war, in particular the increasing inflation, contributed to lower life satisfaction after the most acute phase of the COVID-19 crisis had ended. Furthermore, having children turned out to be a potential resilience factor, despite the burden parents had to endure during the pandemic. As previous research also identified having children to be related to higher life satisfaction, even during the pandemic, such and our findings suggest that having children is a strong protective factor, potentially buffering detrimental impacts of the pandemic. Nevertheless, since especially those with partners were more satisfied with their lives, it can be assumed that it is especially the social support within a family (Bujard et al., 2023) that is responsible for the better well-being in families. Apart from the resilience factors, we identify potentially economic risk factors. The comparison of household income terciles over time reveals that the lowest tercile remains with particular lower levels of life satisfaction especially after the summer of 2022. The same applied to single parents, though their life satisfaction converged to singles without children by the end of the survey period. Policy implications are that vulnerable groups should be acknowledged during straining times as they need more support to sustain adequate life satisfaction. In Germany, social policies were conducted such as short-time work schemes (“Kurzarbeit”) at the beginning of the COVID-19 lockdown in March 2020 or the “gas and electricity price brake” (“Gasund Strompreisbremse”) in February and May 2022 which included a one-time payment for energy price compensation of 300€ for all employees and several benefits for families, companies, and those entitled for housing allowances. How1 3 1372 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… ever, despite these measures, the lower income tercile remained particularly vulnerable amidst crises. Our analyses contribute to our understanding of people’s well-being in a time of the polycrisis. In this phase, however, the attribution of the effects of the individual crises is limited, for reasons of data and theory. From a theoretical standpoint, the polycrisis may generate a general anxiety, uncertainty, and pessimism, which in turn harm well-being (Cooper & Nagel, 2022). Concerning data, these more general consequences of a phase of multiple crises cannot be captured by single indicators for single crises, such as pandemic intensity or changes in cost of living. We can identify, however, that life satisfaction during this polycrisis was continuously suppressed. This suggests that, on average, cumulative strain of crises exceeds people’s resilience-building across the general population (cf. Seery et al., 2010). While previous research has gained insight from addressing subjective individual uncertainties and their narratives in the context of economic uncertainties (Vignoli et al., 2020), we suggest to extend such approaches to the current polycrisis, including crises of war, health, and climate. Moreover, future research could also implement further dependent variables, such as mental health indicators. It was found that while emotions were impacted by the pandemic more strongly, they converged to their baseline level more quickly as compared to life satisfaction (Helliwell et al., 2021). Therefore, further comparisons during the polycrisis are worth revisiting. Our analyses have important implications for the use of large-scale panel data, in particular with a semi-annual design, for short-term fluctuations of variables. We show the possibilities of monthly information by combining the semiand tri-annual subwaves with the field period during several months for each subwave. Descriptively, this allows to display monthly rates of life satisfaction for the majority of months within two years; for panel analyses with fixed effects, this allows for five observation points within two years. In particular, in times of crises but also for life course events such as births of children, moving to another apartment, or change of occupation or partnership status, short-term information within one year have a high analytic potential. However, this potential is rarely used, since most users analyze panel data such as BHHP, GSOEP or FReDA by only comparing yearly information. Though several major studies have added high-frequency surveys in reaction to the COVID-19 pandemic, it is important to run such studies continuously. Only continuous high-frequency panels will allow for the analyses of before, during, and after-trends surrounding future crises. In addition, the use of monthly respectively semi-annual data has a high potential for policy advice in times of short-term changes or crises. To this end, a prompt data release, which often takes more than one year after field work, is important; this becomes an increasing quality testing stone for future data infrastructures. This study has several limitations. First, the impact of specific crises on life satisfaction can usually only be related indirectly to the information of time trends. However, we tested for monthly macro factors such as OSI and CPI as proxies for the burden of COVID-19 crises and inflation. Second, we do not have information for every month during the period analyzed and the information we have is irregularly distributed. However, we obtain information on six to eight months per year to show trends for life satisfaction and relate them to crises. Third, the within-person panel analyses can only use the semi-annual information and compare the different waves (subwaves), they cannot (or only to a limited degree) use the monthly information within one wave. Fourth, since our analyses focused on two years of multiple crises, we have no comparison to the time before 2020 and to the time the crises 1 3 1373 L. Kriechel et al. might be coming to an end. Therefore, analyzing long-term effects on life satisfaction in the course of the next years is an important revenue for future research, in particular to see, which resilience and risk factors are at play. Current research is only at the beginning of observing such impacts. 6 Conclusion Our paper shows that cumulative negative events in life can lead to a longer-term attenuated life satisfaction which might not be the case for a singular crisis. However, since life satisfaction was lower during times of the pandemic than during the polycrisis it can be concluded that COVID-19 has a stronger impact on life satisfaction than the Russian war, climate change, or inflation. While subgroups show disparate trends and are differently affected by crises, partnership is among the strongest protective factors and financial problems a crucial risk factor. To grasp the dynamics of the multiple crises and the pandemic, we profited from the semi-annual panel FReDA and its monthly information. By doing so, we revealed and uncovered the potential of panel data that has rarely been systematically exploited to date. This can stimulate future research on short-term fluctuation of life satisfaction or other variables which is in particular relevant for times of macro-crises as sudden events of special hardening for many people in society. Appendix Survey month Number of observations April 21 26,502 May 21 9,105 June 21 2,037 July 21 18,002 August 21 3,659 September 21 313 November 21 16,598 December 21 2,794 January 22 785 May 22 20,488 June 22 2,908 July 22 199 October 22 16,745 November 22 4,536 December 22 1,038 January 23 116 Table 3 Number of observations per survey month for descriptive statistics 1 3 1374 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… Fig. 7 Adjusted mean life satisfaction during the pandemic. Adjusted mean values of life satisfaction are illustrated over survey months (months are in the first row of the x-axis labels, years in the second row). The model controlled for the same covariates as the regression models (i.e., OSI, CPI, education level, employment status, number of children, degree of urbanization, living in East Germany, sex, age, and migration background) 1 3 1375 L. Kriechel et al. Table 4 Overall predictors of life satisfaction during times of multiple crises Random Effects Fixed Effects Coef. std. beta CI p Coef. CI p OSI -0.00 -.04 -0.00; -0.00 .003 -0.01 -0.01; -0.01 <.001 CPI -0.05 -.11 -0.09; -0.01 .021 -0.03 -0.04; -0.03 <.001 Education (ISCED) 0.05 .04 0.03; 0.06 <.001 Employment status (ref = unemployed) employed 0.57 .14 0.44; 0.69 <.001 0.37 0.25; 0.50 <.001 self-employed 0.64 .07 0.50; 0.78 <.001 0.44 0.29; 0.60 <.001 out of the workforce 0.54 .13 0.42; 0.67 <.001 0.34 0.22; 0.46 <.001 Financial Satisfaction 0.31 .21 0.30; 0.33 <.001 0.18 0.17; 0.20 <.001 In Partnership 0.65 .15 0.61; 0.70 <.001 0.48 0.42; 0.54 <.001 Children (ref = no children) 1 child 0.26 .05 0.21; 0.31 <.001 0.03 -0.05; 0.11 .441 2 children 0.24 .05 0.19; 0.29 <.001 0.04 -0.06; 0.14 .406 3+ children 0.22 .04 0.15; 0.28 <.001 0.12 0.01; 0.24 .035 Degree of urbanization (ref = city) Smaller town or suburb 0.03 .01 -0.01; 0.07 .110 -0.01 -0.14; 0.12 .841 Rural area 0.08 .02 0.03; 0.13 .003 -0.11 -0.28; 0.07 .229 East Germany (ref = West) 0.04 .01 -0.01; 0.08 .166 -0.07 -0.17; 0.04 .205 Men (ref = women) 0.06 .02 0.02; 0.09 .003 Age (centered) -0.02 -.09 -0.02; -0.02 <.001 Migration background (ref = no migration background) 1. generation migrant 0.27 .04 0.21; 0.33 <.001 2. generation migrant -0.05 -.01 -0.11; 0.01 .107 Survey time point (ref = Apr-Jun 2021) Jul-Sep 2021 0.17 .04 0.11; 0.22 <.001 Nov 2021-Jan 2022 0.50 .11 0.37; 0.64 <.001 May-Jul 22 0.55 .12 0.27; 0.84 <.001 Oct 22-Jan 23 0.69 .15 0.25; 1.13 .002 Intercept 4.10 3.89; 4.32 <.001 5.66 5.50; 5.82 <.001 Observations 85001 118795 R² within 0.03 0.03 R² between 0.21 0.15 Respondents 18966 40335 Change Number of observations Unemployed ↔ other employment indicator 1,199 No children ↔ children 4,749 City ↔ other area 638 West ↔ East Germany 681 Without a partner ↔ partner 3,478 Table 5 Number of observations for changes over time 1 3 1376 The Rollercoaster of Subjective Well-Being in Times of Multiple Crises:… Bujard, M., Laß, I., Lines, E., & Ludwig-Walz, H. 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