Fixed-term Employment and Subjective Well-being: A Comparison of Natives,Migrants and Refugees

Abstract

This article examines the impact of fixed-term employment on subjective well-being among natives, migrants and refugees in Germany and the underlying mechanisms of this relationship. Utilizing longitudinal data from 2016 to 2021, we employ fixed-effects panel models and mediation analyses. We find that refugees experience stronger negative effects of fixed-term employment on their well-being than natives and migrants, especially shortly after their arrival. For migrants and natives, subjective job insecurity significantly mediates these effects, while it is less relevant for refugees. Our results indicate that it is essential to acknowledge the heterogeneous effects for vulnerable groups when studying the impact of fixed-term employment. During their integration process, refugees encounter complex labour market challenges which can pose threats to their subjective well-being. Therefore, we suggest engaging more in debates about non-standard forms of employment and taking aspects of the quality of employment into account when designing integration measures for this group.

Keywords

job insecurity life satisfaction mediation analysis migration

Introduction

Over the past decades, global economic competition has increased the need for flexible employment arrangements. Among others, the use of fixed-term employment (FTE) – that is, a pre-defined limited duration contract – presents a form of non-standard employment that enables employers to react to possible market changes with flexibility (Brady and Biegert, 2017; Kalleberg, 2000). In 2022, the share of FTE reached 11% in OECD countries and 12% in Germany (OECD, 2024). In Germany, a shift towards non-standard forms of employment has been reinforced by labour market reforms in the early 2000s, particularly the Hartz reforms, which aimed to reduce unemployment but also expanded non-standard employment. Among other measures, restrictions on FTE were relaxed and companies gained more legal flexibility to hire workers on a short-term basis (Eichhorst and Tobsch, 2015). Although FTE might allow for labour market flexibility, studies show that it comes with increased job insecurity and lower wages (Gebel, 2009), making certain groups more vulnerable and increasing social inequality (Giesecke, 2009).

For Germany, previous studies show that migrants are markedly overrepresented in FTE (Kogan, 2011) and at higher risk of experiencing subjective job insecurity during crises like the COVID-19 pandemic (Bürmann et al., 2022). Given additional barriers such as language difficulties, unrecognized qualifications, limited social networks, discrimination or bureaucratic hurdles (Kosyakova and Kogan, 2022), their overrepresentation in FTE might exacerbate these challenges. In this article, we therefore look at the situation of employees in FTE by migration status; that is, comparing natives, migrants and refugees in Germany to explore group-level inequalities more deeply. Focusing on Germany is particularly relevant due to its status as one of the largest immigrant-receiving countries in Europe and its reliance on labour migration to address workforce shortages (Ette et al., 2016). With more than 1.5 million asylum applications filed between 2014 and June 2017 (BAMF, 2017), the labour market integration of refugees has become a key policy and research concern.

The literature on job insecurity and its objective measures like permanent or fixed-term contracts have often put a focus on the consequences for individual subjective well-being (SWB). Studies frequently find a negative impact of FTE – compared to permanent employment – on SWB (e.g. Karabchuk and Soboleva, 2020; Scheuring, 2020). Nevertheless, some findings are mixed, with studies also reporting no or even positive effects of FTE on well-being (see De Cuyper et al. (2008) for an overview). Previous authors note that a gap in the literature still exists regarding the underlying mechanisms and the ways in which FTE can impact SWB (Scheuring, 2020). Additionally, little is known about the differences between refugees, other migrants and natives in terms of how FTE affects their SWB.

The literature highlights subjective job insecurity to be of importance for understanding how objective job insecurity affects well-being (Witte, 1999). Whereas objective job insecurity refers to aspects like the contract type, subjective job insecurity is understood to reflect the individual assessment of insecurity and emotions related to it (Borg and Elizur, 1992; Jiang and Lavaysse, 2018). Research shows that objective and subjective job insecurity are intertwined, with workers in FTE experiencing a greater fear of job loss (e.g. Muñoz De Bustillo and De Pedraza, 2010) as it presents a chronically stressful situation (Lee et al., 2018). At the same time, the literature also emphasizes the need to consider individual characteristics and possible heterogeneous outcomes. For example, Morgenroth et al. (2022) show that FTE increases the fear of job loss for women more than it does for men, and a meta-analysis by Cheng and Chan (2008) shows that the negative effect of job insecurity on health outcomes is more severe for older than younger employees. In this article, we therefore concentrate on subjective job insecurity – that is, fear of job loss – and aim to understand its mediating role for the effect of FTE on SWB for natives, migrants and refugees in Germany – a differentiation that is understudied in the literature to date. In summary, our research questions are: (1) What effect does FTE have for the SWB of refugees, migrants and natives and are there substantial differences between groups? (2) Is the relationship of FTE and SWB mediated by subjective job insecurity and are there differences between refugees, migrants and natives?

For our analysis we use panel data from the German Socio-Economic Panel (SOEP) (Goebel et al., 2019; Kroh et al., 2018), the integrated IAB-BAMF-SOEP Survey of Refugees (Brücker et al., 2025) and the IAB-SOEP Migration Sample (Brücker et al., 2014) from the years 2016 to 2021, focusing on those in employment. In the case of refugees, our analyses mainly reflect the experiences of male refugees, given the later entry of female refugees into the labour market (Kosyakova et al., 2023). Our hypotheses are grounded in the latent deprivation theory by Jahoda (1982) and the relative deprivation theory (Walker and Pettigrew, 1984). First, we examine differences in effects of FTE between the three groups using a fixed-effects model. Second, we investigate possible mediators of this relationship by applying the Karlson–Holm–Breen (KHB) method for a mediation analysis. For further in-depth analysis, we conduct a heterogeneity analysis for refugees based on their years since arrival, allowing us to better understand their employment and integration trajectories.

Our contribution to the literature is twofold. First, we are the first to analyse how the effect of FTE on SWB differs by migration status. Second, we examine this relationship further by using a mediation analysis, offering explanations for potential differences. Understanding the mechanisms behind the effect of FTE on SWB and how it varies across groups is essential for addressing the negative consequences of FTE. Analysing the role of FTE on SWB by migration status is crucial for evaluating the magnitude of the problem posed by FTE and its role on social inequality as well as for designing successful policies that improve the labour market integration of those groups (Kleppe and Støren-Váczy, 2019).

Theoretical background

Consequences of fixed-term employment (FTE) for subjective well-being (SWB)

For a theoretical consideration of how FTE impacts SWB, we draw on the latent deprivation theory by Jahoda (1982), originally developed to explore the impact of unemployment on individuals. Widely applied across disciplines and to other settings of unstable employment, like, for example, underemployment (Beck et al., 2024), it offers a foundational perspective on the psychological benefits of stable employment. The theory suggests that employment fulfils essential latent functions beyond providing income, like the provision of a social role and identity (Jahoda, 1982). Previous research applied the theory to show that FTE might impact SWB negatively (Gash et al., 2007; Gundert and Hohendanner, 2014). Following Scheuring (2020), we argue that although some of the latent functions of employment might still exist in FTE to some extent, they are likely weaker than in permanent jobs. For instance, fixed-term employees might miss out on long-term workplace relationships or feel less connected to their organization’s goals. Drawing on this theory, we thus hypothesize that FTE in general has a negative impact on SWB:

H.1: Being in FTE as opposed to permanent employment yields lower levels of SWB.

Heterogeneity by migration status based on the relative deprivation theory

Jahoda’s model has been criticized for being unable to explain why some individuals seem less affected by precarious working conditions than others (Gundert and Hohendanner, 2014). To explore how FTE affects different groups dependent on migration status, we therefore additionally make use of the relative deprivation theory (Walker and Pettigrew, 1984). This theory argues that individuals judge their situation based not only on absolute conditions but also by comparing themselves to others. Accordingly, people evaluate their socio-economic circumstances relative to a reference group or a personal benchmark (Kudrna, 2024; Runciman, 1966). Disparities between what individuals have (their current conditions) and what they believe they deserve (their expectations or comparisons to others) can lead to feelings of deprivation, negatively affecting their SWB. The emotional experience of deprivation, which includes frustration, anxiety or resentment, arises when individuals perceive themselves as disadvantaged relative to their reference group (Walker and Pettigrew, 1984).

Considering relative deprivation theory, the extent to which FTE negatively affects SWB is likely influenced by the expectations and reference points of different groups. FTE, compared to permanent employment, is typically associated with lower job security, fewer benefits and reduced opportunities for career advancement. We would expect that natives generally carry expectations of stability, security and long-term career progression, as these are deeply rooted in social norms (Auer and Cazes, 2003; Morgenroth et al., 2022). This is also reflected in German law, where – even though rules have been relaxed over time – fixed-term contracts are still subject to legal scrutiny and require justification from the employer (TzBfG, 2000: §14). Consequently, FTE stands in conflict with these expectations and could thus trigger feelings of relative deprivation when individuals compare themselves to natives in permanent jobs.

Refugees, on the other hand, often face cumulative disadvantages such as legal barriers, language challenges and social exclusion (Kosyakova and Kogan, 2022; Phillimore and Goodson, 2006). Their primary focus may be on securing any form of employment as a way to earn a livelihood and facilitate integration. FTE, though less desirable than permanent employment, might still represent progress from unemployment or informal work. Their comparison may be with their previous conditions, such as unemployment or precarious living conditions before arrival, rather than with natives in secure roles. As a result, the negative effects of FTE compared to permanent employment on their SWB may still be negative but weaker than for natives.

In this context, we expect migrants that came to Germany outside the asylum context to hold an intermediate position between natives and refugees. They may have more stable lives than refugees and thus higher expectations but still face challenges like discrimination or job market segregation (Glitz, 2014). FTE might trigger some sense of relative deprivation compared to their peers in permanent roles, but we expect that the emotional toll may be less severe than for natives. Based on these theoretical considerations, we hypothesize that natives will experience the most negative effect of FTE compared to permanent employment on SWB, followed by other migrants, with refugees experiencing the least negative effect:

H.2a: FTE decreases SWB more strongly for natives than it does for migrants and refugees.

However, several explanations rooted in the evaluation of the labour market and broader socio-economic situation of refugees also allow for a competing hypothesis: first, refugees are disproportionately concentrated in low-status, precarious jobs that do not match their skills (Kogan, 2011; Kosyakova and Kogan, 2022). This horizontal and vertical segregation in the labour market (McGovern, 2007) could amplify the negative effects of FTE for these groups.

Second, many refugees face cumulative disadvantages, such as legal uncertainties (e.g. temporary residency status), limited access to social networks and systemic discrimination (Kosyakova and Kogan, 2022). FTE might exacerbate these vulnerabilities, as it provides less protection and fewer opportunities for long-term integration compared to permanent contracts. The insecurity of fixed-term roles could heighten stress related to their precarious overall situation, undermining their SWB more than anticipated.

Third, for refugees, FTE might signal not just insecurity but also ongoing marginalization within the host society. FTE may be perceived as a structural barrier preventing refugees from achieving parity with natives. This precarity could heighten feelings of social isolation or exclusion, compounding the emotional price of FTE. The lack of social and institutional support available to many refugees could exacerbate these effects, as they generally tend to lack the financial safety nets that natives have built over the years (Dhawan and Zollmann, 2023). We therefore also formulate the competing hypothesis:

H.2b: FTE decreases SWB more strongly for refugees than it does for migrants and natives.

Both hypotheses are rooted in the idea of reference groups, which is key to the relative deprivation theory (Gartrell, 2001). Refugees might compare themselves to peer refugees or peers in the home country (supporting H.2a) or to natives of the host country (supporting H.2b). Other authors have stated before that there is no consensus in the literature of how a reference group (or a single person) is chosen (Åberg Yngwe et al., 2003). We will therefore test both hypotheses, H.2a and H.2b.

The mediating role of subjective job insecurity

Previous literature proposes to differentiate between objective and subjective measures when looking at job insecurity (De Witte and Näswall, 2003; Helbling and Kanji, 2018). Objective job insecurity refers to job insecurity that is based on measurable and observable job-related factors (De Witte and Näswall, 2003). This form of insecurity is usually measured by the type of contractual arrangement (e.g. Mauno et al., 2005). However, Helbling and Kanji (2018) argue that subjectivities should not be neglected in studies of non-standard work as they are not inherently reflected in objective conditions. We therefore ask if subjective job insecurity plays a mediating role.

Subjective job insecurity refers to an individual’s personal perception, worry or fear about the stability of their job (De Witte and Näswall, 2003; Greenhalgh and Rosenblatt, 1984). It is usually differentiated into the affective and cognitive component. While the latter refers to the evaluation and rational judgement of an individual about the likelihood of losing one’s job, the former presents the emotional and psychological response; that is, the fear or anxiety resulting from this evaluation (Greenhalgh and Rosenblatt, 1984; Jiang and Lavaysse, 2018). In our study, we concentrate on the affective component of job insecurity; that is, the fear of job loss.

The differential impact of subjective as compared to objective measures is also found in previous studies. For example, a study by De Witte and Näswall (2003) finds that temporary employment as an objective measure did not directly correlate with reduced job satisfaction whereas individuals’ subjective perception of job insecurity did. Previous studies also show that subjective measures are more relevant for outcomes such as poor well-being and health than the formal employment contract (De Witte and Näswall, 2003; Origo and Pagani, 2009). In our analysis, we assume that while FTE creates a measurable and external reality of job insecurity, the effect on SWB is mediated by an individual interpreting and responding to this external factor. Through the negative emotions attached to experiencing objective job insecurity, FTE is thus expected to diminish SWB. Our hypothesis therefore states:

H.3: The effect of FTE on SWB is mediated through subjective job insecurity.

Our theoretical considerations are summarized in Figure 1. As outlined, we expect that FTE affects SWB (H.1) with differential effects by migration status; that is, for natives, migrants and refugees (H.2a, H.2b). Moreover, we expect that part of this relationship of FTE and SWB is mediated through subjective job insecurity (H.3).

Figure 1.

Summary of theoretical expectations.

To further elaborate on the theoretical framework, we consider how the number of years since arrival in the host country might influence the mediating role of subjective job insecurity. The arrival period for refugees can significantly shape their expectations and perceptions of employment stability. Over time, refugees become more integrated into social networks and acquire skills as well as managing the transferability of previously acquired skills, which enhances their labour market integration (Damelang et al., 2020; Kosyakova and Kogan, 2024). This adaptive process could lead to a nuanced shift in how they perceive job insecurity. For instance, after several years, they may experience diminished fear of job loss as they establish themselves in the workforce, resulting in a less pronounced mediating effect of subjective job insecurity on SWB. Conversely, recent arrivals might feel heightened insecurity due to their precarious status and a lack of established support systems (Kosyakova and Kogan, 2022), thus experiencing a stronger relevance of subjective job insecurity for mediating the impact of FTE on SWB. We consider time since arrival as a critical factor influencing the subjective evaluation of job security and its subsequent impact on well-being. Therefore, we hypothesize that the mediating role of subjective job insecurity will vary, being of greater importance for newer arrivals compared to those who have been in the host country longer:

H.4: For refugees, the relevance of subjective job insecurity as a mediating factor is stronger with fewer years since arrival.

Data and methods

Data

For our empirical analyses, we rely on data from the German Socio-Economic Panel (SOEP, v.38.1, EU version), comprising the general SOEP-CORE population survey (Goebel et al., 2019; Kroh et al., 2018) and two integrated studies: the IAB-SOEP Migration Sample (Brücker et al., 2014) and the IAB-BAMF-SOEP Survey of Refugees (Brücker et al., 2025). As a large-scale longitudinal representative study, the SOEP-CORE population survey was launched in 1984 and is since then conducted annually among private households in Germany (Kroh et al., 2018). In 2013, the IAB-SOEP Migration Sample was launched. The target population was drawn from register data of the Federal Employment Agency and is representative of immigrants arriving in Germany since 1995 and second-generation individuals born after 1976 (Brücker et al., 2014; Kroh et al., 2015). Owing to the refugee migration to Europe, the IAB-BAMF-SOEP Survey of Refugees was launched in 2016 as a further integrated study to the SOEP. The target population was drawn from the Central Register of Foreigners and is representative of refugees arriving in Germany between January 2013 and June 2019, irrespective of their current legal status (Brücker et al., 2025; Kroh et al., 2017). Together, these studies allow for a comparative approach to investigate differences among natives and several migrant groups. The data are unique in their longitudinal character and allow us to study integration trajectories and changes over time.

Sample

For our analyses, we use data of the surveys from the years 2016 to 2021, to allow the integration of the refugee samples that started in the year 2016. The data for these years include 175,781 observations. We restricted the sample to individuals aged 18 to 65 years (31,988 observations dropped) who are employed (45,264 observations dropped). Following the definition of the International Labour Organization, employment was defined as work performed in return for pay or profit (International Labour Organization, 2023). As we want to compare FTE to standard permanent employment and following previous studies (Gebel and Voßemer, 2014; Giesecke, 2009; McGinnity, 2005), we excluded individuals in self-employment (9299 observations) and employment without contract (2938). To secure representativeness for our target refugee population, we only included refugees from the IAB-BAMF-SOEP sample who arrived between 2013 and 2019 (1470 observations dropped). We further excluded individuals in internships or apprenticeships (4974 observations) because of the educational character of these categories. Although fixed-term contracts are used for individuals doing apprenticeships, it is not considered employment but rather vocational training in the German educational system. Lastly, we dropped observations with missing values in the main dependent (295 observations) and explanatory variables (9079 observations),¹ as well as individuals without information on migration status (308 observations). These data restrictions resulted in a sample of 70,166 person-year observations (stemming from 23,001 individuals). Of those, 4159 observations come from refugees, 11,996 from individuals with a direct migration background (excluding refugees) – that is, those born outside of Germany with an own migration experience (hereafter ‘migrants’) – and 54,011 come from individuals born in Germany (hereafter ‘natives’). Second-generation migrants – that is, individuals born in Germany to at least one parent who is an immigrant – were thus included in the category ‘natives’.

Core variables and descriptive statistics

Dependent variable

As the outcome variable, we utilize life satisfaction to quantify SWB, aligning with its widespread use in prior social science research (e.g. Safi, 2010; Stam et al., 2016). Respondents were asked, ‘Overall, how satisfied are you with your life currently?’, and answer the item on a scale from ‘0’ (completely dissatisfied) to ‘10’ (completely satisfied). As introduced by Diener et al. (1985), life satisfaction represents a cognitive evaluation of one’s overall quality of life, distinct from affective or momentary evaluations, and constitutes a central component of SWB. In a meta-review, Erdogan et al. (2012) conclude that life satisfaction should also be considered an essential factor in the work-related context.

Main independent variable

Our main independent variable is FTE, which is equal to ‘0’ if the individual is in permanent employment (has an open-ended contract) and ‘1’ for individuals in FTE (with a pre-defined limited duration contract). Individuals in self-employment, unpaid work, internships and apprenticeship, as well as those without a formal contract, were excluded by the above-mentioned sample restrictions.

Mediators

The mediation analysis concentrates on the mediating factor of subjective job insecurity. Depending on the sample, subjective job insecurity was measured based on the questions ‘Do you worry about losing your job?’ or ‘How concerned are you about the following issues? – If you are employed: your job security?’, each capturing worries related to the respondent’s current job security. Answers were given on a three-point scale, including: ‘Yes, I worry a lot’, ‘Yes, I worry somewhat’ and ‘No, I don’t worry at all’, or ‘Very concerned’, ‘Somewhat concerned’ and ‘Not concerned at all’. These two answer scales translate to the same in the German version of the questionnaire (Große/Einige/Keine Sorgen). From these two items we created a dummy variable, coded ‘1’ for individuals who worry a lot or somewhat about their job security and ‘0’ for those who do not worry at all about it.

In addition, to test the mediating role of further objective measures, we propose two further mediating factors: wage and job level. Wage measures the individual’s logarithmic gross wage of the last month before the interview in euros and was constructed as a continuous variable. The measure considers overtime payments but no irregular one-time payments such as holiday bonuses. To avoid losing too many observations due to missing values, we used an imputed version of this variable. In a two-step procedure, individual longitudinal information was used for imputation and, alternatively, if no information is available, the imputation was carried out with a Mincer regression (for further information see SOEP Group (2022)).

The variable job level was defined based on the German Classification of Occupations (Klassifikation der Berufe, KldB) 2010. Using the five-digit code, we determined the job level of each occupation, reflecting on the complexity and the requirements needed to carry out the related tasks (Paulus and Matthes, 2013). For our analysis, the job level variable was divided into three categories, namely: (1) helper, (2) skilled worker and (3) specialist or expert.

Heterogeneity analysis

For a further extension of the mediation analysis, we allow for heterogeneous effects among refugees depending on their years since arrival. Information for this variable was taken from the questionnaire by subtracting the year of arrival from the current year of the interview. We grouped the years into three categories: zero to two years, three to four years and five years or more.

Control variables

Several control variables are included to avoid confounding the relationship between FTE and well-being. This includes variables that are likely to causally affect both the main independent variable (FTE) and the outcome variable (life satisfaction). First, age is included, measured as a continuous variable. Gender is included as a categorical variable that takes the value ‘1’ for male and ‘0’ for female individuals. A dummy variable west is included as a control to capture broad regional differences between German federal states. Federal states that formerly belonged to the German Democratic Republic, as well as Berlin, are coded ‘0’ and all other federal states are coded ‘1’. Education is controlled for using the ISCED-11 classification, captured as a categorical variable that takes the value ‘1’ for low education (ISCED-2011, levels 0–2), ‘2’ for medium education (ISCED-2011, levels 3–4) and ‘3’ for high education (ISCED-2011, levels 5–8). Lastly, to account for time variation, we also control for the survey year.

Descriptive statistics

Table 1 provides the mean, standard deviation and minimum and maximum value for all variables and means of each variable for natives, migrants and refugees separately. Differences in the summary statistics between groups can be observed for the main variables of life satisfaction, FTE and worry for job loss. Additionally, refugees are 31.56 years on average younger than natives and migrants. Owing to looking only at employed individuals, as given by our research question, the refugee sample tends to be observed in later survey years, as their integration into the labour market increases over time. Notably, with 91%, the refugee sample consists mainly of male individuals, which is explained by the comparably later entry of female refugees into the labour market (Kosyakova et al., 2023). Results of subsequent analysis should therefore be interpreted to mainly reflect on the situation of male refugees.

Table 1.

Descriptive statistics.

Variable	Mean	Std dev.	Min	Max	Mean per migration status
Migration status					Native	Migrant	Refugee
Native	0.85	0.354	0	1
Migrant	0.14	0.348	0	1
Refugee	0.01	0.073	0	1
Dependent variable
Life satisfaction	7.50	1.497	0	10	7.46	7.75	7.29
Main independent variable
FTE	0.11	0.313	0	1	0.10	0.16	0.56
Mediators
Subjective job insecurity	0.32	0.468	0	1	0.31	0.42	0.54
Job level: Helper	0.10	0.304	0	1	0.08	0.24	0.48
Job level: Skilled worker	0.51	0.500	0	1	0.52	0.47	0.46
Job level: Expert or specialist	0.38	0.487	0	1	0.4	0.29	0.06
Gross wage last month (log)	7.81	0.746	0	11.51	7.83	7.68	7.20
Heterogeneity analysis (excluding natives)
Years since arrival: 0–2	0.02	0.140	0	1	–	0.02	0.13
Years since arrival: 3–4	0.05	0.226	0	1	–	0.04	0.39
Years since arrival: 5+	0.93	0.261	0	1	–	0.94	0.49
Control variables
Age (years)	44.20	11.794	18	65	44.31	44.00	31.56
Gender: male	0.52	0.500	0	1	0.52	0.49	0.91
Region: West Germany	0.80	0.400	0	1	0.78	0.92	0.85
Education: Low	0.08	0.267	0	1	0.06	0.18	0.56
Education: Medium	0.58	0.493	0	1	0.6	0.51	0.24
Education: High	0.34	0.474	0	1	0.35	0.32	0.20
Survey year: 2016	0.16	0.367	0	1	0.16	0.17	0.04
Survey year: 2017	0.18	0.380	0	1	0.17	0.18	0.10
Survey year: 2018	0.17	0.372	0	1	0.16	0.17	0.15
Survey year: 2019	0.18	0.384	0	1	0.18	0.19	0.20
Survey year: 2020	0.16	0.370	0	1	0.16	0.15	0.22
Survey year: 2021	0.16	0.363	0	1	0.16	0.14	0.28

Note: FTE: fixed-term employment.

Source: Authors’ own calculations based on the IAB-BAMF-SOEP refugee sample, IAB-SOEP Migration Sample and SOEP-CORE, v.38.1. Survey weights applied.

Figure 2 shows that refugees are highly concentrated in non-standard employment with 56% in FTE, more so than other migrants (16%) and natives (10%).

Figure 2.

Shares of natives. Migrants and refugees by contract type.

Figure 3 demonstrates that both for refugees and migrants, their employment quality measured by type of contract is lowest shortly after arrival and increases over time. At zero to two years after arrival, 72% of employed refugees work in FTE, but after seven or more years this figure has decreased to 42%. The same pattern arises for migrants, though the share of those in FTE is generally lower than among refugees.

Figure 3.

Fixed-term employment by migration status and years since arrival, in percent.

Lastly, we see differences in life satisfaction for refugees depending on their contract type, but not for natives and only to a small extent for migrants (Figure 4). While refugees in permanent employment show on average a life satisfaction of 7.5, refugees in FTE indicate an average life satisfaction of 7.1. The difference of 0.4 points on the 0–10 scale can be considered substantial on the basis of previous literature on life satisfaction. For example, Infurna et al. (2017) find that the anticipation of spousal loss leads to a decline in life satisfaction of 0.77 points.

Figure 4.

Life satisfaction by contract type for natives, migrants and refugees.

Modelling strategy

First, we are interested in the heterogeneous effects of FTE on SWB across the three different groups. Using linear fixed-effects (FE) regression models, we estimate the effect of FTE on SWB by migration status with the inclusion of interaction effects. The choice of FE estimation is particularly appropriate in this context because of potential unobserved heterogeneity that would bias standard ordinary least squares (OLS) results. For example, we cannot rule out that factors like individual motivation or ability are correlated with FTE as well as SWB, resulting in endogeneity of the independent variable. As the unit of analysis, FE measures within-individual differences, accounting for observed and unobserved time-constant factors (Brüderl and Ludwig, 2015). To estimate unit-level differences, we introduce an interaction effect of FTE across natives, migrants and refugees. The standard FE interaction estimator allows interactions of a time-constant variable and a time-varying variable in FE to be estimated (Giesselmann and Schmidt-Catran, 2022), as has been done before; for example, in SWB research, differentiating by gender (Heyne and Voßemer, 2023). The estimated model is represented by the following equation:

l i f e s a t_{i t} = ß_{0} + ß_{1} F T E_{i t} + ß_{2} F T E_{i t} * m i g b a c k_{i} + ß_{3} c o n t r o l s_{i t} + α_{i} + ε_{i t}

(1)

Here, lifesat_it is life satisfaction for person i at time t. FTE_itis the main independent variable which is interacted with migration status. For the FE estimation, gender is excluded as a control variable as it is time-constant. The remaining control variables include age, east/west Germany, education and survey year. α_i represents an individual-specific component, that is constant over time for a specific individual i and ε_it is an idiosyncratic error term, that varies over time and individuals. As indicated above, FE depends on demeaning equation (1); hence, the estimation would include time-varying variables and drop any time-constant variables (Brüderl and Ludwig, 2015). Standard errors are clustered at the individual level.

For the second research question, we disentangle how much the influence of FTE on life satisfaction is mediated by subjective fear of job loss, using pooled-linear regression models, estimated separately for each group, natives, migrants and refugees. We decompose the effect of FTE on life satisfaction into direct and indirect effects. Standard errors are clustered at the individual level:

l i f e s a t_{i t} = α_{0} + α_{1} F T E_{i t} + α_{2} c o n t r o l s_{i t} + ε_{i t}

(2)

As hypothesized previously, one part of the total effect of FTE (α₁in equation (2)) operates indirectly by influencing the mediators (Z), namely subjective job insecurity (later: wages and job level), included either separately or altogether in one equation. Adding those mediators in equation (3), we calculate the indirect effect and the mediation percentage. The indirect effect (∆_i) is the difference between the total effect of FTE – α₁ in equation (2) – and the direct effect – α₄ in equation (3). The mediation percentage reflects the percentage of the relationship that is mediated by Z:

l i f e s a t_{i t} = α_{3} + α_{4} F T E_{i t} + α_{5} c o n t r o l s_{i t} + α_{6} Z + ε_{i t}

(3)

Using the KHB method (Kohler et al., 2011), we estimate the mediating effects accounting for the rescaling bias by including the residuals of the mediators (Z) in the reduced model. This avoids differences between the full model and the reduced model due to rescaling. It allows us to calculate the mediation effect without alterations in scales (Kohler et al., 2011). These residuals are included in the reduced model, instead of including the mediator itself, and implemented in Stata (version 18.0) using the KHB command.

Results

Fixed-effects estimation

For the first part of the multivariate analysis, we exploit the panel structure of our data and estimate linear FE models. Figure 5 shows the effects of FTE on life satisfaction by migration status. Model 1 presents the estimated average effect independent of migration status. We see no significant effect of FTE for life satisfaction. Thus, we do not find sufficient evidence to support H.1.

Figure 5.

Fixed-effects estimation for the effect of fixed-term employment on life satisfaction by migration status.

This contrasts with studies finding a large average negative effect for Germany (e.g. Scheuring, 2020). Potential explanations might be the use of different datasets, time frames and methods (here: FE; Scheuring (2020): OLS). In general, FE results infer the causal effect of FTE on well-being through estimating within-person changes and do not consider the between-individual differences (Brüderl and Ludwig, 2015).

Model 2 presents the results from the estimation where FTE is interacted with migration status to allow for effect heterogeneity. The results show that for natives and migrants, FTE does not reduce life satisfaction (statistically insignificant), while for refugees it reduces life satisfaction by 0.22 points (= 0.043 – 0.263). The difference of 0.263 in the effect of FTE for refugees compared to natives is statistically significant at the 1% level. From the two competing hypotheses, we find support for H.2b, indicating that FTE decreases SWB more strongly for refugees than it does for natives. Nevertheless, a difference between refugees and migrants as well as migrants and natives are not statistically significant.

Mediation analysis

To explain the differences across natives, migrants and refugees for the effect of FTE on SWB, we suggest a mediating effect of subjective job insecurity. In Table 2, we test this assumption by reporting estimates of the mediating effects of subjective job insecurity for the three groups. We present the total effect from the model without any mediators (M1, M3 and M5), as well as the direct and the indirect effect and the percent mediated by subjective job insecurity (M2, M4 and M6).

Table 2.

Mediation analysis with subjective job insecurity by migration status.

	Refugees		Migrants		Natives
	(M1)	(M2)	(M3)	(M4)	(M5)	(M6)
FTE	−0.304*** (−2.84)	−0.246** (−2.28)	−0.095 (−1.27)	0.005 (0.07)	−0.091** (−2.26)	−0.013 (−0.33)
Subjective job insecurity		−0.448*** (−4.02)		−0.525*** (−8.42)		−0.609*** (−19.54)
∆i mechanism (z-value)		−0.0583** (−3.08)		−0.100*** (−5.18)		−0.0781*** (−8.75)
% mediated		19.17		105.16		85.59
N	4159	4159	11,996	11,996	54,011	54,011
Bic	17,563.7	17,519.9	42,779.5	42,403.2	19,6173.7	19,4287.4

Notes: Coefficients from pooled linear regression models averaging over all the years (dependent variable: life satisfaction on a 0–10 scale). t in parentheses. Control variables included (age, gender, east/west Germany, education and survey year). *p < 0.05, **p < 0.01, ***p < 0.001.

Source: Authors’ own calculations based on data from the IAB-BAMF-SOEP refugee sample, IAB-SOEP Migration Sample and SOEP-CORE, v.38.1. Survey weights applied.

For the mediating effect of subjective job insecurity, we find that worry for job loss explains a substantial part of the effect of FTE on well-being for the three groups. This supports hypothesis H.3. Nevertheless, the mechanism is explained by subjective job insecurity to varying degrees depending on migration status. The mediating role of subjective job insecurity accounts for 86% of the total effect for natives, 105% for migrants and only 19% for refugees, and is statistically significant for the three groups. Thus, we find support for subjective job insecurity to explain the relationship between FTE and SWB for migrants and natives, and explains only a part of the relationship for refugees.

Next, we conduct additional mediation analyses for refugees to explain the relationship of FTE and SWB further. In Table 3, we report estimates of the mediating effects of subjective job insecurity, job level and wages, and the results of a model including all these mediators. Results show that the mediating role of job level (M3) and wages (M4) account for 14% and 11% of the total effect, respectively. Adding these mediators, the direct effect decreases in magnitude as compared to the total effect in M1. In M5, we add the three mediators simultaneously. In this model, the direct effect decreases to −0.175 and is not significant anymore. All three mediators explain 43% of the total effect of FTE on SWB for refugees and therefore bring more understanding to the relationship. In the Supplemental Tables A1 and A2, we present the same analysis with those additional mediators for migrants and natives.

Table 3.

Mediation analysis with additional mediators for refugees.

	(M1)	(M2)	(M3)	(M4)	(M5)
FTE	−0.304*** (−2.84)	−0.246** (−2.28)	−0.263** (−2.52)	−0.270** (−2.54)	−0.175 (−1.64)
Subjective job insecurity		−0.448*** (−4.02)			−0.456*** (−4.15)
Job level (ref.: Helper)
Skilled worker			0.286** (2.47)		0.252** (2.23)
Expert or specialist			0.325* (1.74)		0.240 (1.33)
Wage				0.205*** (3.14)	0.213*** (3.28)
∆_i mechanism		−0.0583** (−3.08)	−0.0407* (−2.32)	−0.0345** (−2.66)	−0.130*** (−4.18)
% mediated		19.17	13.84	11.34	42.99
N	4159	4159	4159	4159	4159
Bic	17563.7	17519.9	17559.3	17547.1	17499.3

Notes: Coefficients from linear regression models averaging over all the years (dependent variable: life satisfaction on a 0–10 scale). t in parentheses. Control variables included (age, gender, east/west Germany, education and survey year). *p < 0.05, **p < 0.01, ***p < 0.001.

Source: Authors’ own calculations based on data from the IAB-BAMF-SOEP refugee sample, IAB-SOEP Migration Sample and SOEP-CORE, v.38.1. Survey weights applied.

We conduct a further heterogeneity analysis for refugees by their years since arrival. Table 4 reports the results of the mediation analysis with subjective job insecurity (M2, M5 and M8) and alternatively with all mediators used before (M3, M6 and M9) for zero to two years, three to four years and five or more years since arrival. Results of these estimations show that first, the role of FTE for SWB decreases over time and is highest in the first years after arrival, and second, the extent to which subjective job insecurity mediates the relationship changed over time and is lowest shorty after arrival. We do not find sufficient support for our hypothesis that subjective job insecurity mediates the relationship between FTE and SWB more strongly in the first years after arrival (H.4).

Table 4.

Mediation analysis for refugees by years since arrival.

	0–2 years			3–4 years			5 or more years
	(M1)	(M2)	(M3)	(M4)	(M5)	(M6)	(M7)	(M8)	(M9)
FTE	−0.650** (−2.05)	−0.572* (−1.83)	−0.508* (−1.69)	−0.196 (−1.22)	−0.137 (−0.85)	−0.072 (−0.46)	−0.260* (−1.69)	−0.204 (−1.32)	−0.111 (−0.74)
Subjective job insecurity		−0.357 (−1.20)	−0.381 (−1.30)		−0.490*** (−3.15)	−0.505*** (−3.27)		−0.438*** (−2.76)	−0.443*** (−2.83)
Job level (ref.: Helper)
Skilled worker			0.510 (1.65)			0.218 (1.41)			0.250 (1.58)
Expert or specialist			0.332 (0.52)			0.440 (1.59)			0.112 (0.51)
Wage			0.167 (1.12)			0.196** (2.23)			0.287*** (2.75)
∆_i mechanism		−0.0772 (−1.13)	−0.142 (−1.37)		−0.0596* (−2.22)	−0.124** (−2.87)		−0.0562* (−2.09)	−0.150** (−3.16)
% mediated		11.89	21.80		30.37	63.34		21.62	57.51
N	554	554	554	1637	1637	1637	1968	1968	1968
Bic	2542.8	2546.1	2556.3	6977.1	6960.5	6967.2	8109.4	8090.2	8079.0

Source: Authors’ own calculations based on data from the IAB-BAMF-SOEP refugee sample, IAB-SOEP Migration Sample and SOEP-CORE, v.38.1. Survey weights applied.

Discussion

We do not find support for all of our hypotheses; therefore, our findings invite a more careful reconsideration of the theoretical framework. Based on Jahoda’s (1982) latent deprivation theory, we expected that FTE would provide fewer non-financial benefits, leading to lower SWB (H.1). Since this hypothesis is not supported, our results suggest that the theory is limited in explaining the effects of FTE on SWB for the general population. It instead confirms our motivation to conduct analyses separately for different population groups. Following the relative deprivation theory, we hypothesized that because refugees may compare their current situation to their past or peers from their home country, the negative effects of FTE on SWB would be weaker for them than for natives or migrants, who are more likely to compare themselves to peers with permanent jobs (H.2a). However, the empirical findings contradict this expectation and instead support our competing hypotheses (H.2b) that refugees face more negative effects than natives. This finding highlights the importance of identifying the correct reference group when applying the relative deprivation theory (e.g. Åberg Yngwe et al., 2003). Our findings suggest that refugees may compare themselves to natives rather than peer refugees when forming labour market expectations. Structural disadvantages and broader socio-economic vulnerabilities may amplify the negative effects of FTE for refugees in particular. This is in line with and expands on the findings from a similar article showing that job insecurity reduces self-reported health more for migrants than for natives (Nappo, 2022).

Further results regarding the mediating role of subjective job insecurity (H.3) highlight the importance of studying subjectivities along with objective measures when evaluating the impact of non-standard forms of employment. Nevertheless, our results show that in this case also, analyses should allow for group differences. Lastly, we also find no evidence in support for our hypothesis regarding the role of years since arrival (H.4), indicating that while FTE is strongly associated with reduced well-being early in employment, the mediating role of subjective job insecurity is less significant at this stage. This suggests that early in their labour market integration, refugees may be more affected by broader integration-related stressors, such as social isolation or worries for family in the origin country. Over time, job-related concerns grow more relevant, leading to an increased mediating effect of subjective job insecurity on well-being – indicating a gradual assimilation to the experiences of natives. This highlights the complex interplay of various stressors in the refugee experience and underscores the importance of considering broader psychosocial factors in understanding the implications of FTE.

Several limitations of the article should be acknowledged. First, while fixed-effects models account for unobservable time-constant characteristics of individuals, our mediation analysis does not. Second, further research is needed to analyse if the different wording used in the questionnaire to measure subjective job insecurity plays a role. While refugees were asked ‘Do you worry about losing your job?’, natives and migrants were asked ‘How concerned are you about the following issues? – If you are employed: your job security.’ We argue that both questions capture the subjective feeling of fear of job loss, reflecting on a sense of powerlessness and inability to continue in a job (Shoss, 2017). Even though different items have been used to assess subjective job insecurity before (Grzywacz et al., 2009), we are unaware of any study that compares these two items directly and further research needs to validate this assumption. Third, while life satisfaction is a well-established measure for SWB, future research could include other aspects of affective well-being, such as feelings of fear, anger or happiness (Schumann and Kuchinke, 2020). Fourth, since our data cover the years 2016 to 2021, a potential impact of the COVID-19 pandemic must be considered. As a robustness check, we carried out our analysis with the exclusion of the survey year 2020. The FE results from this do not substantially change our findings and conclusions.

The article raises several future research questions. Future studies could look into further job characteristics, like job sector, industry or tenure, that might provide underlying mechanisms for our findings. Table A3 shows that changes from permanent to FTE are much more likely for refugees than for migrants and natives. Thus, differences in the dynamic of employment trajectories and more volatile employment situations for refugees should also be considered in future research.

In this article, as 91% of the refugee sample consists of male refugees, we are unable to go into more detail about gender-specific analyses, leaving the experiences of female refugees potentially not well captured. From previous literature, we have learned that refugees face heterogeneous employment integration trajectories based on their gender. Among others, female refugees are found to experience lower returns for their human capital in Germany than male refugees and face higher structural barriers due to their need to balance work and family responsibilities (Kosyakova et al., 2023). Therefore, conducting future analyses separately by gender could yield valuable insights and should be carried out once sufficient data are available.

Lastly, since our results reveal a much stronger negative effect of FTE on SWB for refugees than for natives, questions about the relevance of legal status are raised. Table A4 provides results of the mediation analysis by legal status. For refugees with a rejected or undecided asylum application, a much lower share of the relationship between FTE and SWB is mediated through subjective job insecurity and additional objective factors. This provides first evidence for the relevance of legal status, and future research could shed more light on the question of how insecure legal status in combination with insecure employment affects the well-being of refugees.

Conclusion

In this article, we ask which effect FTE has on the SWB of migrants, natives and refugees and which factors mediate this relationship for each group. We find that: (1) refugees are far more concentrated in FTE than migrants and natives, especially so shortly after arrival. (2) The negative effect of FTE on SWB is heterogeneous and largest for refugees. (3) For refugees, subjective job insecurity explains only a small part of this relationship, whereas it explains a larger share for natives and migrants. (4) Objective factors, such as job level and wages, partially account for the effect. (5) For refugees, the negative FTE effect is strongest shortly after arrival and declines over time, while the mediating role of subjective job insecurity grows with time in the host country.

For future research in this area, two important implications can be reached from the results. First, when conducting well-being research, referring to average effects across the population should be done with caution. Second, the effect of FTE is rather dynamic and changes over time depending on the uncertainty of the individual’s situation. Therefore, adopting a time-sensitive approach when studying the effects of FTE and increasing the focus on groups facing more complex labour market situations is crucial.

For policy makers, further implications emerge. Importantly, sustainable labour market integration should not be measured solely in terms of employment rates but must also consider the quality and stability of employment. Short-term contracts can undermine well-being precisely when stability is most needed. Relying heavily on short-term contracts for newly arrived populations may undermine long-term integration goals and reinforce existing social inequalities. Evaluating integration success solely by employment rates may therefore risk masking vulnerabilities and welfare losses in the long term. For policy makers, our results point to interventions that accelerate access to stable, permanent employment and raise job quality. Taken together, the evidence highlights that improving contract stability and job quality is central to sustainable integration and to reducing emerging inequalities linked to non-standard employment.

Supplemental Material

sj-docx-1-wes-10.1177_09500170251393618 – Supplemental material for Fixed-term Employment and Subjective Well-being: A Comparison of Natives, Migrants and Refugees

Supplemental material, sj-docx-1-wes-10.1177_09500170251393618 for Fixed-term Employment and Subjective Well-being: A Comparison of Natives, Migrants and Refugees by Laura Goßner and Maye Ehab in Work, Employment and Society

Footnotes

Acknowledgements

We thank our colleagues, the anonymous reviewers and the editor for providing helpful comments on earlier versions of this article and all those who commented on earlier presentations of this work at the following events: 20th IMISCOE Annual Conference, 21st IMISCOE Annual Conference, IAB-Workshop ‘Social Policy and the Labour Market in Turbulent Times: (No) Need for Change?’ and ECSR Annual Conference 2023. Any errors are the responsibility of the authors.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Laura Goßner

Maye Ehab

Supplemental material

Supplemental material for this article is available online.

Notes

Laura Goßner studied International Cultural and Business Studies (BA) at the University of Passau, and Economics (MSc) at Friedrich Alexander University Erlangen-Nuremberg. She is a doctoral candidate in sociology at the University of Bamberg. She works as a researcher in the ‘Migration and International Labour Studies’ department at IAB (Institut für Arbeitsmarkt- und Berufsforschung). Her research focuses on integration processes of refugees, gender inequalities and aspects of refugee health.

Maye Ehab works as a researcher in the ‘Migration and International Labour Studies’ department at IAB (Institut für Arbeitsmarkt- und Berufsforschung) and as a lecturer at the University of Bamberg. Ehab received her doctorate from the University of Bamberg. Her recent publications address gender inequalities and women’s labour force participation, geographic mobility, and job quality and health outcomes. She was recently nominated for the Bettina Paetzold Award for Good Gender Education in 2025.

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