heterogeneity in individual characteristics, job choices and career objectives, different search and negotiation behaviors of different groups, structural reasons such as unequal burdens of bringing up children, or even biased location choices of couples.
The ongoing public debate notwithstanding, our knowledge about labor market chances of highly skilled women and immigrants in Germany, and the potential problem of additive disadvantages faced by female immigrants, is limited. In this paper, we draw on survey data from a large-scale graduate tracer study conducted by the University of Kassel International Centre for Higher Education Research (INCHER-Kassel). Alumni across all disciplines from 37 German universities (with a raw sample size of more than 15,000 individuals) were surveyed about their employment situation roughly nine to 18 months after graduation. Controlling for individual differences in employability, we analyze three different indicators of labor market outcomes for this sample: wage differentials, job satisfaction, as well as the perceived match of competences and job requirements. For our sample of recent German university graduates, gender differences in labor market outcomes generally appear to be more substantial than those related to immigration status. Our results indicate a systemic wage gap for women, but not for male immigrants. In contrast to earlier work for the U.S. (Le and Miller, 2010) we find no evidence that female immigrants suffer from a “double-negative effect” of being disadvantaged twofold (in terms of genderandimmigration status). Similar patterns are obtained for job satisfaction and the match quality of competences and job requirements.
Table 3 applies the instrumental variable strategy outlined in Section 4 . Our 2SLS estimate
for the full population (column 1) is more than 2.5 times larger (in absolute value) than that from OLS, consistent with our prior that the correlation between economic growth andimmigration should bias OLS estimates downwards. 9 The magnitude of the coefficient increases further when including time-varying controls (column 2). We also find more pronounced gender differences, at least when measured in percentage points. A 10 percentage point increase in immigrant share decreases the probability of males working a night shift by .74 percentage points (column 3, 35% of native mean), and .44 percentage points for women (column 5, 39% of native mean). Note however that the relative impact with respect to the sample means is similar across genders. Time-varying CZ-level controls again increase the magnitudes when estimating separately by gender, but decrease the precision (columns 4 and 6).
whole and for each of the fifteen countries separately. A striking feature of Table 8 is how females are more likely to over-estimate the immigrant share of the population (see too Figure 7). This proneness to exaggeration is also linked to low educational levels, religiosity, being politically conservative (in the sense of self-identifying as right-wing), being xenophobic, being unhappy, unsatisfied with life, and unhealthy, and not believing that immigration is culturally enriching. Curiously, perhaps, those who are more socially liberal, as reflected in higher stated tolerance towards gay people, are also more likely to over-estimate the immigrant share. One way of thinking about why some groups get it right more than others is that they have a greater motivation or opportunity to get accurate information. So socially conservative individuals, anxious about the effects of immigration on society, put more efforts into finding out the facts. The politically conservative, on the other hand, are perhaps more ideologically motivated and perceive the facts to be consistent with their concerns—a form of cognitive dissonance. But such an interpretation is necessarily ad-hoc.
Immigration Data. We obtained individual-level data on all visa and permanent residence permits granted by the Chilean Department of State. This data includes basic demographic statistics such as date of birth, nationality, municipality of intended residence at time of application 8 , gender, and self-reported variables on education and labor market experience. Information on population comes from INE (National Institute of Statistics) estimates using projections from census data, which allows to calculate the rate of immigration by municipality for each year. For the 2008-2017 period, the database includes more than 2 million individuals. As shown in Table I , immigration rose considerably within our study years, though growth rates vary substantially by region. While in 2008, none of the regions received more than 2 percent of their population as new immigrants per year, at least five regions were above this level in 2017, mostly comprised of migrants from other Latin America countries. Figures I and III describe the immigrant composition during our sample period by country of origin.
4. Econometric analysis
First, we focus on 2010 and use ordered logit regressions to analyze the nexus between bitterness and attitudes on immigration with the following additional control variables: gender, age, age squared, tertiary education, marital status, child in the household, employment status, household income and regional fixed effects. Standard errors are clustered at the individual level. For the purpose of interpretation, we report marginal effects for having big worries. The corresponding results are reported in table 1. It becomes obvious that strong link between bitterness and big worries about immigration holds when controlling for socio-demographic and regional differences. The main finding that bitter people are more likely to have big worries about immigration holds also in 2005, suggesting that the pattern is stable over time (table 2). Next, we tested in how far our results survive when we include measures of locus of control. For this purpose, we constructed two variables capturing locus of control of respondents following the approach of Caliendo et al. (2015). The first measure is a standardized full index of locus of control, while the second measure is a dummy variable taking the value of one if the respondent has an internal locus of control. In contrast to Caliendo et al. (2015), we exclude the question on bitterness in constructing the locus of control measures. The corresponding results are displayed in table 3. We do not find any significant effect of locus of control on native attitudes on immigration. More important, neither the magnitude nor the significance of our bitterness coefficients are affected when introducing locus of controls variables. This finding strongly supports our claim that the question used for defining bitterness is indeed not a locus of control measure.
Additionally, we collected biographical information about each judge in the sample. Our primary data source for collecting judges’ characteristics is the judge reports from the Transactional Records Access Clearinghouse (TRAC) which is a data collection, research, and data warehouse based out of Syracuse University. Their website contains reports for judges each year in which the judge decides at least 100 cases. The judge information was collected from “a variety of official sources including press releases, testimony, other biographical information released by the Department of Justice, and responses received to specific TRAC inquiries” (TRAC (2008)). Unfortunately, the 100 decision per year threshold in the TRAC data leaves 30 of the 262 judges missing. We used internet searches, relying on DOJ and other government documents or newspaper articles, to compile information about these judges. We were able to obtain gender for all judges and year of appointment for all but four. Unfortunately, information on the backgrounds of these judges was not as readily available and as such, we
A similar result appears in the traditional tax competition literature. In these models, when mobility costs tend to infinity, regional governments can perfectly tailor the level of local goods to satisfy the preferences of immobile local residents, without attracting residents from other regions. In other words, under complete immobility, changing the level of local goods in one region does not affect other regions, so the centralized and decentralized solutions coincide. Mobility in our framework, however, involves not only moving across regions within the host nation, but also across international borders. As a result, illegal immigrants are able to respond to differential levels of g i by entering the host country through different
Income inequality has been on the rise in many industrialised countries since around the 1980’s. In Sweden the increase of income inequality has been particularly large. This in spite of Sweden’s encompassing redistribution system and public policy that prioritize equality among its population. Why income inequality is unfavourable for a nation has both economic and normative sides. While early studies imply that inequality has a positive relationship with economic growth, more recent studies have found negative links between the two (see for example Alesina and Rodrik, 1994 cited in Rodríguez C., 2000, paragraph 2.1). There are several theories in favour of a relationship between low inequality and higher long-term growth. Mainly it is believed that a redistribution of income to the poor will lead to more spending on healthcare and education which are both positively associated with economic growth. The poor will also stay out of violence and protests that otherwise would restrict investment and in turn growth. Further, a polarized economy will experience problems making necessary reforms that are important in a growth process (Rodríguez C., 2000). When inequality reaches higher levels it becomes a violation of human rights. The life expectancy is longer for rich than for poor and poor individuals are more likely to have health issues than those who are rich (Therborn, 2013). A study by Atkinson et al. (cited in Aaberge et al., 2000, p78) shows that Sweden was among the countries with the lowest income inequality in the late 1980’s. After a comparatively large increase, Sweden still has a relatively small income inequality (OECD, 2011). However, because of the increasing pattern, research regarding causal factors of variation in income inequality is needed. It is essential to acquire knowledge on what groups of the population to target in order to efficiently reduce income inequality and limit the consequences of it.
appropriate procedure is the Diff-in-Diffs. Model OLS and Model RE suggest that the change in immigration policy has no effect on the probability to remit (note that the interaction of affected and post-reform cohort is our main covariate as it captures the policy effect). However, when we account for time-varying heterogeneous trends and use matching individuals on their propensity score (which is our main model), the re- sult shows that the policy change influences positively and statistically significantly the probability to remit (5.6%), but not the amount of remittances sent (which is negative but insignificant). As we control for income and education, the results on the effect of the policy change perhaps capture an increase in the perceived level of riskiness of settlement among immigrants in the second cohort. Given that we control for a wide range of individual characteristics, including education levels, labour force status, re- gion of origin, and other covariates (see full results in Appendix B), this result partly captures elements related to individuals becoming more risk averse and saw remittances as a possible insurance policy.
a State Secretariat for Economic Affairs SECO, Holzikofenweg 36, CH-3003 Bern Email: email@example.com. This paper was written when Kathrin Degen was with the Swiss National Bank. The views and opinions expressed in this paper are solely those of the authors and do not necessarily reflect the positions of the Swiss National Bank or the State Secretariat of Economic Affairs. The authors would like to thank Barthélémy Bonadio, Martin Brown, Tommaso Frattini, Sarah Lein, Albert Saiz, Steven Stillman, and an anonymous referee for their valuable comments. The authors also benefited from discussions with Urs Hausmann and Dieter Marmet from Wüest & Partner and numerous students from Swiss Universities. Data and code are available from the authors. The authors acknowledge use of the dataset described in Mack and Martinez-Garcia (2011).
We believe that our results are important for several literatures. First, our results speak to the literature on immigration, cheap labour, and the organization of coordinated labour markets (King and Rueda 2008; Emmenegger and Careja 2012; Alt and Iversen 2017). The labour supply shock constitutes the introduction of cheap labour into a well- organized labour market and illustrates that it can have important economic consequences also in this context. Still, we find no impact on natives’ union membership. This does not mean that labour immigration constitutes no threat to unions or to labour market organization, after all, we have seen that immigrants are less likely to organize. However, our results imply that the main task for unions is to organize the newcomers. As Cools et al. (2018) show, immigrants’ unionization slowly catch-up with natives’ with years since arrival. The slow catch-up process implies that unions might want to spend more resources on recruitment policies target to these groups. Still, catch-up is happening, which shows that universal, encompassing unions can incorporate the type of diversity that labour immigration of this type represents. We suspect that union organization along ethnic and geographical lines–as King and Rueda (2008) seem to favor as a response to non-organized immigrant labour–is a less fruitful road for worker organization, a topic we leave to future research. We believe that empirical evaluations of successful union strategies and policies to organize immigrants is a topic ripe for research, in particular since it relates to the issue of immigrant integration into host societies more generally.
The second trend has been the development of policies to favour the settlement and participation of migrants, especially if from NESB, to Australia’s economic activity. This was accompanied by the introduction of instruments, including ad hoc data col- lections, to analyse their economic outcomes. Even with higher skill levels than compa- rable natives or migrants with an English-speaking background (Watson (1996)), NESB immigrants were characterized by substantially lower economic outcomes. To overcome a linguistic disadvantage, Australia had put in place a publicly funded system to pro- vide new adult NESB immigrants with free language courses (as well as locally-funded technical training). Immigrants were paid to attend these courses, which lasted between one and six months and led them to attain a level of language ability that was ade- quate for employment. By 1990, Australia’s Adult Migrant English Program (AMEP) ”was the largest government-funded English teaching program for migrants worldwide, catering to over 70,000 immigrants per year including large number of unemployed pro- fessionals” (Hawthorne (2005)). The government actively pursued the private sector to adopt Equal Opportunity principles towards NESB as well as facilitated to ease the admission of ’professionals’ from NESB (managed by professional associations) with the funding of specialist labour market programs designed to prepare NESB professionals for mandatory entry exams in a range of professions like medicine, engineering and nursing.
Instead of competing with indigenous work forces, specific patterns of the interaction between migrants and markets have been identified. In particular IMs traditionally occupy labour market segments that are rejected or for other reasons not filled by indige- nous workers (Iglitzka, Gmay and Maroukis 2011). Irregular migrant labour encourages a further divi- sion of labour into its more and less productive ele- ments. For example, the bricklayer’s work is divided into bricklaying by a skilled British worker and han- dling the bricks by an unskilled irregular immigrant (Jordan and Düvell 2002). In the process the pro- ductivity of skilled native workers is raised. IMs even create new markets for jobs and allow indigenous populations to enter the labour market (Young 1999). For instance, it is only because IMs offer cheap la- bour that lower-income households can afford to hire, for instance, domestic workers. As a result, a market is created for low-paid domestic work which did not previously exist. Second, this frees indige- nous women from the constraints of housework and allows them to (re-)enter the labour market, which raises their productivity. Third, the household in- come increases and thus their overall spending power. Fourth, because previously non-working in- digenous populations enter employment they pay taxes and thus raise state revenues. Fifth, low-wage workers enable firms to offer lower-priced goods and services, which have a diminishing impact on inflation. A cycle is thereby generated which posi- tively affects large numbers of households, the state budget and even the economy at large.
Compensating Differentials and Returns to Skills
As the immigrant share increases, the return to working in an occupation with more exposure to hazardous conditions appears to fall. Column 1 of Table 5 reports OLS results from estimating equation 12, and columns 1 and 5 of Table 6 report the corresponding IV results. Most of the results indicate that a 1 percentage point increase in the immigrant share reduces an occupation’s return to hazard exposure by about 0.1 to 0.2 percent, on average. Alternatively, the coefficient in column 5 of Table 6 (-0.169) implies that the average immigration shock to a state during this period (0.036) caused the wage elasticity of hazard exposure to decline by 0.006 points relative to its trend – a small but statistically significant effect. The estimates indicate larger effects among men than among women, and the estimated coefficient on the interaction term is not significantly different from zero for women when using the geographic shift-share IV.
To that end, we first experiment with excluding states that have passed a statewide Trust Act. Trust Acts are adopted with the purpose of increasing community trust and cooperation with the police following the implementation of tougher immigration enforcement measures, such as the 287(g) agreements that promoted information sharing between local, state, and federal government agencies (Skogan and Frydl 2004, Fagan and Meares 2008, Fagan and Tyler 2008, Tyler 2010). We exclude states with a state-wide Trust Act to more accurately capture the impact of intensified immigration enforcement, which should be lax or close to null in those areas. As a result, we would expect the estimated impact of intensified immigration enforcement to be, if anything, greater in magnitude. Table 6 displays the results from this exercise. The mean increase in immigration enforcement over the period under examination (i.e. 𝜇𝜇 𝐼𝐼𝐼𝐼 = 0.564) raises the overall share of Hispanic children entering the foster care system by approximately 17.62 percent. 30 The 18 percent increase
Specifically, we consider a host-country economy consisting of two sectors: manufacturing and agriculture. While there is perfect competition in agriculture, the
manufacturing sector is characterized by mixed oligopoly – some firms are unionized while others are not, and all firms engage in oligopolistic competition. We investigate the impacts of immigrationand remittance on respectively wages, employment, the union-nonunion wage gap and national welfare, and find that an increase in permanent immigration brings positive effects on these variables (except the competitive wage), and raises the wage gap. That is, while permanent immigration increases the welfare of the whole nation, it also causes income redistribution, benefiting relatively the labor unions and landowners, and hurting those
More recent studies in this field compare the outcomes of native and immigrant workers. For example, Chiswick and Miller (2008) and Chiswick and Miller (2010) report lower returns to schooling for foreign-born workers compared to natives in the U.S. and Australia respectively and explain this outcome with low international transferability of immigrant’s human capital skills implying more frequent skill mismatch of foreign-born workers. Aleksynska and Tritah (2013) consider a large set of European countries and find that immigrants are more likely to be both under- and overeducated than the native born for the jobs that they perform. How- ever, immigrants outcomes converge to those of the native born with the years of labor market experience. In our data we also observe this type of integration in the German labour market. Piracha and Vadean (2013) present an overview of this literature and show that the percentage of correctly matched immigrant employees is, for example, about 5.0% lower compared to native employees in Denmark and reaches up to 15.6% in the United States. The only exceptions are Finland and Italy, where the mismatch incidence seems to be higher for natives. They also point out that different measurement methods often lead to significantly different estimates of incidence rates. In particular, mismatch is more frequent when self-reported rather than when objective measures are used. Our empirical estimates for Germany are similar to the U.S. with the percentage of correctly matched immigrant employees 15.5% lower compared to natives. We contribute to this literature by explicitly comparing job search channels of workers and mismatch outcomes associated with these channels which was not done before. Moreover, we show that referral hiring generates occupational mismatch more frequently than other search strategies and it is this channel which is more often used by immigrant workers contributing to stronger occupational mismatch of this group.
others do not find such effects (Card, 2012; Ottaviano and Peri, 2012; Manacorda, Manning and Wadsworth, 2012; Dustmann, Frattini and Preston, 2013; Card and Peri, 2016; Foged and Peri, 2016), especially when taking into account other benefits of immigration such as innovation (Kerr and Lincoln, 2010; Peri, 2012). Furthermore, it remains unclear whether fears of labor market effects from immigrants actually shape policy preferences (Scheve and Slaughter, 2001; Hainmueller, Hiscox and Margalit, 2015). Furthermore, voters choose their preferred level of immigration based on how they think migrants affect taxes and welfare benefits. This fiscal effect of immigration has been estimated in a number of studies, yield- ing inconclusive results. Preston (2014) describes the difficulty of accounting for the total fiscal effect given immigrants’ diversity in demographics, skills, and customs. Dustmann and Frattini (2014) find that migrants from outside the European Economic Area generally have made a negative contribution. However, this impact is not found for more recent immi- grants. Expecting immigrants to come at a fiscal cost is often justified by their poor labor market performance (Storesletten, 2003). For France, Germany, and the United Kingdom, Algan et al. (2010) find substantially lower employment rates among both first- and second- generation immigrants from Turkey and African countries. Nevertheless, in the context of population aging, some point out potential fiscal benefits from immigration. Prior research has emphasized that it matters whether natives think of migrants as recipients of welfare benefits or as providing complementary labor (Mayda, 2006; Facchini and Mayda, 2009). In addition, perceptions about migrants in Europe are significantly shaped by concerns about fiscal effects of immigration (Boeri, 2010). A third significant factor shaping attitudes to-
ers who have adopted Swiss citizenship? Or let’s take tennis, Roger Federer has a South African mother, and the name of the other great Swiss tennis profes- sional Stanislas Wrawrinka says it all.
A small country relies on an intensive interchange with foreign countries for its economic success. This interchange cannot be restricted purely to trading in goods. Immigration provides for an international interchange of knowledge and know-how in particular. As we know, knowledge is a commodity which has become significantly more important over recent decades. Economic specialisa- tion also requires access to foreign skilled labour. Without this access, sectors such as financial services, the chemicals and pharmaceutical industry or the machine industry in Switzerland would not have been able to reach the level of importance they have today. We don’t know what other sectors will develop into the areas of Swiss speciality expertise in the future. I am convinced that the possibility of benefitting from a foreign workforce will continue to be a decisive factor for the competitiveness of the Swiss economy.
2015, among others). As we will show, our findings prove robust to the use of these alternative ways of predicting immigrants’ legal status.
In addition, to address concerns of differential response rates among noncitizen women (Johnson and Dye 2005; Van Hook and Bachmeier 2013), we perform various checks. First, we examine the population weights for our group of likely undocumented immigrants to assess the extent of survey non-response among our population of interest over the period under examination. If non-response rose, the weights should have risen, other things equal. Yet, an initial inspection reveals that the weights remained stable over the period under study –a result in line with the findings from a series of studies using the ACS over the 2000 through 2014 period in order to assess non-response rates or the loss of representativeness of the ACS following the intensification of enforcement (see, for example, Bohn et al. 2014; Pope 2016; and Orrenius and Zavodny 2016). Secondly, we check whether samples being collected show different characteristics in MSAs with higher enforcement. If likely undocumented women are significantly less likely to respond in MSAs with stricter enforcement, we should observe a higher citizen to non-citizen ratio in those MSAs, when compared to MSAs with less enforcement. Yet, as we show in Table 5, those shares do not differ with the level of