A simple theoretical framework
With our simple theoretical framework, we seek to better highlight the link between immigrants’ assimilation into the host country culture and their subjective well-being. Our framework is based on a model proposed by Stark and Jakubek (2013) to study the interplay of integration, relative (material) deprivation, and immigrants’ optimal investment in human capital. Rather than conducting a formal equilibrium analysis, we focus on the main assumptions of the original model and adapt them to our context to derive meaningful, testable hypotheses.
Consider a population of homogeneous immigrants who live in the host country, and let F and N denote the sets of immigrants and native agents in this country, respectively. Conducting a profitable economic and social life (i.e., finding a job, accessing fundamental public services, engaging in civic life) requires the acquisition of destination-specific human capital. Let x denote the level of human capital that an immigrant can acquire; we assume x ∈ [0,1 − 𝜃
x
0], where x = 1 is the human capital of a native, and 𝜃
x
0, where 𝜃, x
0 ∈ [0,1], represents the fraction of the stock of human capital carried by the immigrant from the country of origin that can be converted into destination-specific human capital. Acquiring destination-specific human capital is costly, so c
C(x) denotes the cost of assimilating, with c > 0 and C(x) denoting a convex function. For simplicity, we convert destination-specific human capital (x + 𝜃
x
0) into earnings on a one-to-one basis. In turn, we denote the subjective well-being of an immigrant with the following (separable) function of the investmentin destination-specific human capital:
$$ \text{SWB}(x)=Y(x+\theta x_{0})-\gamma \text{CD}(x+\theta x_{0})-cC(x)+\text{OF} $$
(1)
The first term on the right denotes a strictly concave function that captures the well-being the immigrant obtains from income. The OF term captures other (constant) immigrant-specific factors that positively affect subjective well-being. It is the second term on the right that represents the distinctive element of the model: CD(x + 𝜃
x
0) is cultural dissimilation with respect to the host culture, as experienced by the immigrant, and γ ≥ 0 is immigrants’ sensitivity to CD (x + 𝜃
x
0). Even in this case, we assume that destination-specific human capital gets converted into cultural capital on a one-to-one basis, to simplify the model. Coherent with the original formulation proposed by Stark and Jakubek (2013), we assume that cultural dissimilation increases with the difference between the average destination-specific human capital of each immigrant’s reference group and the immigrant’s own level: \(\text {CD}(x~+~\theta x_{0})~=~\sum \limits _{j\in J}\max (0;x_{j}~-~x~-~\theta x_{0})\), where x
j
is the average human capital of the reference group j and J is the set of the reference groups. Stark and Jakubek (2013) use definitions of reference groups to distinguish non-integrated and integrated immigrants: The former includes in a reference group only fellow immigrants living in the same host country, such that J = {F}. If populations were homogeneous, the immigrant would not experience any cultural dissimilation with respect to other members of the community: CD(x + 𝜃
x
0) = 0. For the latter group of integrated immigrants, both fellow immigrants and the native population represent reference groups, such that J = {N, F}. If we assume homogeneous populations and normalization of natives’ human capital, immigrants only experience cultural dissimilation with respect to the native population: CD(x + 𝜃
x
0) = max(0; 1 − x − 𝜃
x
0).
With their original formulation, Stark and Jakubek (2013) study optimal investments in destination-specific human capital, chosen by the immigrant to maximize subjective well-being. Non-integrated immigrants, whose reference group only includes fellow immigrants, make relatively limited investments in human capital because they do not suffer any deprivation (or cultural dissimilation, in our framework) relative to natives. However, integrated immigrants, who include natives in their reference group, invest more in destination-specific human capital to reduce their material (or cultural, in our framework) gap with natives.
Although highly stylized, this theoretical framework provides meaningful, testable predictions about the association between assimilation with the host culture and the subjective well-being of immigrants. With our empirical exercise, we thus aim to assess whether cultural assimilation is positively associated with the level of subjective well-being per se, after we control for several potential confounding factors, such as the immigrant’s (subjective) characteristics and other socio-economic conditions. Additional qualifications also apply when we account for the integration status of immigrants. As suggested by Eq. 1, we expect the association between assimilation with the host culture and subjective well-being to be stronger for integrated than for non-integrated immigrants.
Data and empirical strategy
To study the relationship between cultural assimilation and immigrants’ subjective well-being, we used data from the German Socio-Economic Panel (SOEP), a longitudinal survey that has been collecting information about the socio-economic status, health, and well-being of private households since 1984 (see Wagner et al. 2007). An interesting aspect of this survey is that it oversamples the resident migrant population in Germany, offering a unique source of information about the living conditions of immigrants over time. These data feature heterogeneity with respect to the country of origin of immigrants; the top five origins are Turkey, ex-Yugoslavia, Greece, Italy, and Spain.
To capture subjective well-being (SWB), the questionnaire asks, “How satisfied are you with your life, all things considered?” and the responses range from 0, indicating “completely dissatisfied,” to 10, or “completely satisfied.” Flourishing literature investigates the determinants of subjective well-being using self-reported evaluations of life satisfaction or happiness, and one of the most intriguing issues pertains to how the conclusions change when the focal question refers to happiness (a proxy of emotional well-being) rather than the more general concept of life satisfaction. As Kahneman and Deaton (2010, p. 16489) note, “emotional well-being (sometimes called hedonic well-being or experienced happiness) refers to the emotional quality of an individual’s everyday experience—the frequency and intensity of experiences of joy, fascination, anxiety, sadness, anger, and affection that make one’s life pleasant or unpleasant. Life evaluation refers to a person’s thoughts about his or her life.”Footnote 9 The relevance of the longitudinal dimension of the SOEP data set—which stretches over 30 years for some respondents—prompted us to focus on the more general, retrospectively oriented (rather than emotionally variable) concept of subjective well-being, measured as the self-reported level of satisfaction with life as a whole. It must be pointed out that subjective well-being measures are not exempt from potential criticisms mainly related to their validity (the degree to which these measures succeed in capturing the conditions of the respondent), reliability (the degree to which survey techniques secure consistent data upon repeated application), and comparability over time and over respondent samples (see Sachs, 2013, for a discussion of these issues). Our paper does not contribute to this methodological discussion and we rely on the established literature which validates the use and interpretation of these measures. Rather, by following Kahneman and Krueger (2006) and Layard (2005), we believe that subjective well-being measures present, in our context, two main advantages relative to standard objective indicators. First, in a policy perspective, they allow for more direct welfare analysis that can be conducted on specific social groups, such as immigrants living in the host country. Second, these measures lead to a shift in emphasis from the importance of standard economic variables (such as income and job status) to more subjective and socially oriented determinants of individuals’ well-being, such as social contacts and civic participation, cultural orientation and health conditions.
Next, to measure cultural assimilation, we relied on direct information about immigrants’ sense of identification with the host culture and their German language proficiency. Following Casey and Dustmann (2010), we built a measure of cultural assimilation using information from a question that asked immigrants to report how strongly “German” they felt, on a scale from 1 (“not at all”) to 5 (“completely”). The gauge of writing and speaking skills also used a 5-point scale, from 1 (“no knowledge at all”) to 5 (“very good knowledge”). We measured language proficiency as the average of the writing and speaking scores. We also included SOEP information about immigrants’ identification with the native culture and proficiency in the native language, to control for the potential interplay between host and native cultures.
Figures 1 and 2 show the Epanechnikov kernel density of life satisfaction, according to the strength of the identification with Germany and the native country, respectively. A strong score corresponds to the categories “mostly” and “completely,” whereas the weak score refers to all other categories. The probability mass is more concentrated at high satisfaction levels for those with strong identification with the host country than for those with a weak German identity. Yet, the contrary is true for foreign identity: The densities in Fig. 2 look similar, but that for people with a weak home identity is more concentrated at higher levels of life satisfaction.
As we show in Fig. 3, the previously documented life satisfaction gap between natives and immigrants (Baltatescu 2007; Amit 2010; Bartram 2010; Safi 2010) depends on the level of cultural assimilation of immigrants and reverses for those who feel completely integrated in German society. A Kolmogorov-Smirnov test also shows that the differences in the distributions in Figs. 1, 2, and 3 are all statistically significant at the 1 % level.
These figures seem to confirm a positive relationship between cultural assimilation and immigrants’ subjective well-being at a descriptive level, yet we need a more formal analysis to account for potential confounding factors. Therefore, in our empirical analysis, we focus on first- and second-generation immigrants and estimate a linear panel data model with individual and time fixed effects:
$$ \text{SWB}_{i,t}=\alpha_{i}+\alpha_{t}+w_{it}^{\prime}\beta+\text{assimilation\_host}_{it}^{\prime}\gamma+\varepsilon_{i,t} $$
(2)
$$\bigtriangledown i=1,..., n\text{ \ \ and }\bigtriangledown t=1,..., T $$
where i = 1,...,n indicates individual respondents; t = 1,...,T indicates the survey year; and w
i
t
is a vector of control variables. In line with the theoretical framework we presented in the previous subsection, we focus on the sign and significance of the γ parameters and test whether assimilation with the host culture is positively and significantly associated with immigrants’ subjective well-being, γ > 0.
With individual and time fixed effects (FE), we control for time-invariant, unobserved, individual heterogeneity and time-related common shocks. The first component, individual FE, is crucial for addressing potential differences in reporting styles across respondents (Angelini et al. 2014). Thus, a relevant methodological issue is that measures of life satisfaction might not be interpersonally comparable if different people interpret and use distinct response categories for the same subjective question, a phenomenon known as differential item functioning (Holland and Wainer 1993). As long as the reporting style used by each individual respondent does not vary over time, individual fixed effects can account for this bias. Individual FE also provides a control for every unobserved factor that refers broadly to the “character” of the person, does not vary over time, and is likely to affect both self-reported life satisfaction and subjective measures of cultural assimilation, such as personal traits, optimism, religion, and ethnicity.Footnote 10 The German identity variable shows substantial within-respondent variation over time: 64.55 % of the immigrants in our sample show at least a one-unit change in the German identity variable during the survey period. By employing a linear specification, we also treat life satisfaction as a cardinal rather than ordinal construct, such that we can carry out the fixed effects analysis using the “within” estimator for the whole sample, and the results are easier to interpret (see Clark et al. 2008). From a practical perspective, assuming cardinality or ordinality of life satisfaction has no significant effect on the results (Ferrer-i-Carbonell and Frijters 2004).Footnote 11
The individual characteristics that we control for when estimating the association between life satisfaction and cultural assimilation include the previously detailed, subjective measures of identification with the culture of origin, demographics, health, and socio-economic status. The demographic variables include a quadratic polynomial for age,Footnote 12 the number of own children, a dummy that takes a value of 1 if the respondent is married, a dummy identifying divorced people, and another dummy defining whether a person has been widowed. We measure the person’s objective health status as the number of annual doctor visits and a dummy that indicates whether the person spent at least one night in the hospital in the previous year. Finally, the set of variables aimed to define individual socio-economic status include income and dummies for whether the person has a full-time job, a part-time job, or is undergoing a program of vocational training (a residual category includes people who are not working at all).
Table 1 presents the descriptive statistics for all the variables we used in the regressions. The immigrants in our sample are mostly married (72.2 %) and have one child on average; 58.3 % work either full- or part-time, 3.7 % are in vocational training, and the remaining 38 % are outside the labor force. The average immigrant is 38.9 years of age and went to the doctor three to four times in the previous year. Our final sample contains an unbalanced panel of 22,636 observations (6167 persons) from 10 survey waves over 18 years (1985, 1986, 1987, then every 2 years until 2003, except 1993).Footnote 13
Table 1 Descriptive statistics
In the second part of our analysis, in line with our theoretical framework, we tested whether the positive association between assimilation with the host culture and subjective well-being is stronger for integrated than non-integrated immigrants. We use the time since migration as a proxy for social integration and repeat the estimation procedure on three subsamples of immigrants: recent immigrants who have been in Germany for less than 10 years and are likely not to be fully integrated, established immigrants who migrated to Germany more than 10 years ago and have been exposed to a sufficiently long integration process since their arrival,Footnote 14 and second-generation immigrants, who have only an indirect migration background.
Finally, we checked whether controlling for additional external social conditions affects the magnitude or sign of the association between cultural assimilation and life satisfaction. For this effort, we used data collected by Eurostat for the European Labour Force Survey and aggregated at the regional level.Footnote 15 To measure general openness in a region to foreign-born members, we constructed indexes by region and year for the concentration of immigrants, defined as the percentage in the total population (Fig. 4). We also split this general index into the concentration of (un)employed immigrants, defined as the percentage of (un)employed immigrants on the total un(employed) population. If immigrants contribute actively to the host society through the labor force, society should be more open to them, such that non-natives should feel more accepted overall. These data are available only since 1995, and when we introduce them in the analysis, our sample drops to 11,262 observations (4444 persons). On average, immigrants represent about 10 % of the total population and 21 % (9 %) of the unemployed (employed) population in Germany.
The regions hosting more immigrants relative to their population are concentrated in south-west Germany—the richest area of the country. Probably due to their historical heritage, characterized by closed attitudes toward external influences, and the renewed strength of anti-immigration political parties, the northeast regions instead display a very low concentration of immigrants. More recent years of the SOEP also provide information about the extent to which immigrants are concerned about the situation for foreigners in Germany. On average, 32.8 % of immigrants are very concerned, though this variable shows a downward trend over time, with the exception of a temporary increase in 2001, probably due to the 9/11 attacks.