Abstract
In this paper, we analyze the impact of immigration on Greek politics over the 2004–2012 period, exploiting panel data on 51 Greek regional units. We account for the potential endogenous clustering of migrants into more “tolerant” regions by using a shift-share-imputed instrument, based on their allocation in 1991. Overall, our results are consistent with the idea that immigration is positively associated with the vote share of extreme-right parties, though the effects appear to be stronger during the Greek fiscal crisis. This finding appears to be robust to alternative controls, sample restrictions and different estimation methods. We do not find supportive evidence for the conjecture that natives “vote with their feet,” i.e., move away from regions with high immigrant concentrations. We also find that the political success of the far-right comes at the expense of “Leftist” parties, thereby rejecting the idea that migration divides the society into different camps. Importantly, our analysis suggests that labor market concerns play a significant role in shaping native attitudes toward immigration.
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Source: Authors’ elaborations on data from the European Election Database
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Notes
In 2011, the top-5 sending countries were Albania, Bulgaria, Romania, Pakistan and Georgia (above 50% of total immigrants).
The evidence on the labor market consequences of immigration on the Greek labor market is scant. A recent study by Chletsos and Roupakias (2019), in the spirit of Borjas, suggests that there is significant positive association between migration and unemployment. On the other hand, Chassamboulli and Palivos (2013) employing a simulation-based approach argue that immigration exerts a favorable impact on the labor market outcomes of skilled laborers, while its impact on unskilled ones is ambiguous.
Evidence consistent with the idea that migration contributes to the political success of far-right parties is also reported in a recent published study by Edo et al. (2018) for the case of France.
A partial exception is Hangartner et al. (2017) who examine the impact of Syrian refugees on the “Golden Dawn” vote share in the Aegean Islands in 2015 by exploiting a difference-in-differences approach. However, since these authors focus on a particular group of migrants, they can estimate the response of natives along the intensive margin. In contrast, our study identifies the effects of general migration at extensive margin (considering both economic migrants and refugees), though the number of refugees is negligible in our sample, since we consider data before the outburst of the refugee crisis in 2015.
A complete list of regions is offered in the Appendix Table 11.
As shown in Schüller (2016), education plays a moderating role with respect to natives’ attitudes toward immigration.
In total, our dataset contains about 3,050,000 observations. We note, however, that there is still room for measurement error concerns because of undocumented migration.
Appendix figure A3 illustrates the vote shares of the Greek far-right parties across regions in the 2004 and 2012 elections.
We also note that an IV strategy can also attenuate the bias related to measurement error in the immigrant share variable, arising mainly due to undocumented migration.
To construct our instrument, we aggregate immigrants into 13 origin groups: Africa, Australia and New Zealand, Eastern Asia, Eastern Europe, Northern America, Northern Europe, South America, Southern Asia, Southern Europe, Western Asia, Western Europe and other countries. The full list of origin countries is reported in “Appendix.”
Following Ottaviano and Peri (2006), we have also experimented with distance from border and distance from the main getaways in Greece as instruments. However, these variables do not appear to explain much of the variation in the distribution of immigrants across regions, and thus, they are not included in the analysis.
We have also run regressions in which estimate whether different age cohorts of natives exhibit different attitudes toward migration, as expressed in the ballot box. To that aim, we have plugged into our model interactions between the share of pensioners or the share of younger adult voters and the immigrant share variable. The underlying assumption is that older cohorts might perceive migrants differently from the younger, mainly for two different reasons. First, senior voters might have been immigrants themselves during the emigration episodes that took place in the 1960’s and thus share common experiences with migrants residing currently in Greece. Second, they might be more favorably disposed toward migrants because they do not feel the labor market pressure in which their younger counterparts are exposed. Instead, old natives make extensive use of cheap caring services provided by immigrants. The results (not reported for brevity, available upon request) indicate our finding that immigration associated with increased support for far-right parties is mainly driven by voters aged between 18 and 64 years old.
We impute data for 1996 and 2006 from the 2001 and 2011 Censuses, respectively.
See, for instance, Eurostat’s statistics (available at: https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset-=ilc-lvho02&lang=en) regarding the distribution of population by tenure status.
Data on crime rates were downloaded from the Hellenic Statistical Authority (available at: http://www.statistics.gr/).
What is more, this strategy enables us to test for overidentifying restrictions. Indeed, the Hansen J-statistic (not shown in Table 5) is well above the 5% threshold, thereby suggesting that our instruments are not correlated with the second-stage error term.
We compute for each of the variables indicated in the text the median value in 1991. Crime rate at NUTS-3 level is an exception, since it is available from 2011 onwards only.
We omit technical details on the construction of the index for brevity and refer the interested reader to Ottaviano and Peri (2006) for more information.
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Acknowledgements
We thank the Journal Editor, Professor Martin Andersson, and one anonymous referee for excellent comments that significantly improved the paper. Any remaining errors are, of course, the authors’ responsibility.
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Appendices
Appendix: Variables: definitions and sources
Share of immigrants The ratio of foreign-born individuals over total working age (16–64) population. Source: Integrated Public Use Microdata Series (International).
Population Logarithm of total population. Source: Integrated Public Use Microdata Series (International).
Population density Logarithm of population per square kilometer. Source: Integrated Public Use Microdata Series (International) and Wikipedia.
GDP per capita The ratio of Gross Domestic Product over total population. Source: Hellenic Statistical Authority.
Share of university graduates The ratio of natives with tertiary education over total working age (16–64) population.
Share of women The ratio of native women over total working age (16–64) population.
Share of pensioners The ratio of pension receivers over adult population.
Unemployment The proportion of unemployed natives (16–64) in total labor force.
Voter turnout The total number of votes cast divided by the number of eligible voters. Source: European Election Database.
Crime rate Reported crimes over the total population. Source: Hellenic Statistical Authority.
Election outcomes The vote share for each party. Source: European Election Database (Table 11).
Countries included in the construction of the shift-share instrument and fractionalization index
Integrated Public Use Microdata Series-International and United Nations (2015), Trends in International Migrant Stock: Migrants by Destination and Origin.
Origin countries Afghanistan, Africa, Albania, Algeria, Argentina, Armenia, Asia, Australia, Austria, Azerbaijan, Bangladesh, Belarus, Belgium, Bosnia and Herzegovina, Brazil, Bulgaria, Cameroon, Canada, Central African Republic, Central/South America and Caribbean, Chile, China, Colombia, Comoros, Congo, Croatia, Cuba, Cyprus, Czech Republic/Czechoslovakia, Democratic Republic of Congo, Denmark, Dominica, Dominican Republic, Egypt, Ethiopia, Finland, France, Georgia, Germany, Ghana, Hungary, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Japan, Jordan, Kazakhstan, Kenya, Korea, Kyrgyzstan, Lebanon, Libya, Lithuania, Luxembourg, Macedonia, Malta, Mexico, Moldova, Morocco, the Netherlands, New Zealand, Nigeria, Norway Oceania, Pakistan, Palestinian Territories, Panama, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia/USSR, Samoa, Saudi Arabia, Senegal, Serbia, Slovakia, Somalia, South Africa, South Sudan, Spain, Sri Lanka (Ceylon), Sudan, Sweden, Switzerland, Syria, Tanzania, Thailand, Tunisia, Turkey, Ukraine, the UK, the USA, Uzbekistan, Venezuela, Vietnam, Yemen, Yugoslavia, Zambia, Zimbabwe (Fig. 3).
Far-right vote share in 2004 and 2012. This figure depicts the aggregate vote share for the anti-immigration parties considered in this study, namely “Golden Dawn,” “Independent Greeks” and “Popular Orthodox Rally”
