Impact of high-skilled migration to the UK on the source countries (EU8) economies

Kasnauskiene, Gindrute; Palubinskaite, Juste Article Impact of high-skilled migration to the UK on the source countries (EU8) economies Organizations and Markets in Emerging Economies Provided in Cooperation with: Faculty of Economics and Business Administration, Vilnius University Suggested Citation: Kasnauskiene, Gindrute; Palubinskaite, Juste (2020) : Impact of high-skilled migration to the UK on the source countries (EU8) economies, Organizations and Markets in Emerging Economies, ISSN 2345-0037, Vilnius University Press, Vilnius, Vol. 11, Iss. 1, pp. 55-68, https://doi.org/10.15388/omee.2020.11.23 This Version is available at: https://hdl.handle.net/10419/317153 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ 55 Organizations and Markets in Emerging Economies ISSN 2029-4581 eISSN 2345-0037 2020, vol. 11, no. 1(21), pp. 55–68 DOI: https://doi.org/10.15388/omee.2020.11.23 Impact of High-Skilled Migration to the UK on the Source Countries (EU8) Economies Gindrute Kasnauskiene (Corresponding author) Vilnius University, Lithuania [email protected] https://orcid.org/0000-0003-0741-6538 Juste Palubinskaite MSc in Economic Analysis, Vilnius University, Lithuania [email protected] Abstract. The majority of studies into the economic effects of high-skilled migration focus on aggregate impact on the economic output in the countries of destination. The economic impact of migration of the highly qualified on the economies of the countries of their origin has been examined less. This qualitative research aims to address that gap by identifying the economic effects of high-skilled migration on Central and Eastern Europe, the region which faces many long-term challenges to its economic development. We use the available data from the UK International Passenger Survey for the 2004- 2016 period to test whether the outflow of highly qualified workers from the EU8 countries to the UK is detrimental or beneficial for the growth of sending economies in the short and long term. In order to test these hypotheses, econometric time series analysis methods of structural vector autoregression and cointegration were applied. Our results have shown a positive short-term effect of brain outflow on regions’ GDP and wage growth as well as unemployment; on the other hand, we presented empirical evidence in support of the hypothesis of the negative long-term effect of high-skilled migration on EU8 countries’ GDP and wage growth as well as unemployment. These results are fairly robust to imply that a negative view on high-skilled migration from EU8 is broadly consistent with the previous findings of “harmful brain drain” scholars. Keywords: high-skilled migration, economic growth, EU8 migration, UK immigration Received: 11/120/2019. Accepted: 2/15/2020 Copyright © 2020 Gindrute Kasnauskiene, Juste Palubinskaite. Published by Vilnius University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Contents lists available at Vilnius University Press 56 ISSN 2029-4581 eISSN 2345-0037 Organizations and Markets in Emerging Economies Introduction Movement of the highly educated across international borders for better opportunities abroad as a significant part of global migration flows has become an increasingly discussed topic among policy makers and researchers (Iredale, 2005; Breinbauer, 2007; Agrawal et al., 2011). It poses a challenging question in terms of economic growth. In addition, facing shortages in skilled workers in some professions and rapid ageing of the societies are the issues likely to gain more importance in the future. While there is a preexisting notion that immigration of skilled professionals is not the most effective method of solving demographic issue of ageing societies (Segendorf & Theobald, 2019), it may have a positive effect on reducing average age structure in receiving countries and expanding of the workforce. Therefore, ageing populations in the developed countries cause competition for skills and talent from abroad in order to sustain existing levels of innovation and entrepreneurship as well as to keep the welfare systems intact (Huber et al., 2010). Developing countries, on the other hand, may face labour shortages due to the increased demand in foreign labour markets for such labour force. As a result, ‘human capital flight’ requires changes in the policy area – facilitation and effectiveness of skill transfer among countries (with the ultimate goal of brain circulation) is taking up an important part of policy agenda in developed and developing nations and the EU in general. The central contribution of this paper to the literature in the field is that current research is one of the few studies that consider the impact of emigration on the particular set of sending countries. The aim of the present paper is to examine the effects of highskilled migration to the United Kingdom on sending countries’ (EU8) main economic indicators – GDP per capita, wage growth, and unemployment. 1. Modern approaches to the economic implications of brain mobility In this section, we review the body of literature that helps contextualize our approach. Historically, since the 1960s, in order to reflect the phenomenon of international highly educated labor force mobility, the terms of “brain drain”, “brain gain”, and “brain waste” came into academic, political and public discourse (Docquier, 2014). These migration concepts describe labor force mobility as bipolar and long term (as it was the case in South-North migration), also as a zero-sum game process, leading to new asymmetries and inequalities between sending and destination countries, where developing countries lose their human capital and are deprived of economic development, whereas developed countries acquire human capital and continue with economic growth. The most commonly used term “brain drain” refers to the international transfer of “human capital resources”, mainly in the sense of the migration of highly educated individuals from less to more prosperous countries (Beine, Docquier & Rapoport, 2008). In the rapidly growing literature on the relation between migration and economics, it is argued that nowadays brain migration is somewhat different – it is a complex, 57 Gindrute Kasnauskiene, Juste Palubinskaite. Impact of High-Skilled Migration to the UK on the Source Countries (EU8) Economies non-unidirectional and not necessarily long-term process (Breinbauer, 2007; de Haas, 2010). Due to the weakening of labor market constraints and more flexible immigration policies, high-skilled migration may no longer be the subject of one-sided benefits for the receiving country. On the contrary, many researchers believe that migration of highly educated individuals could result in both the sending and receiving countries being better off if brains “circulate” (Iredale, 2005; Saxenian, 2005; Teferra, 2005; Velema, 2012). According to the European Commission (2005), “brain circulation” is the process when the sending country experiences positive effects due to return migration or diaspora networks if qualified professionals acquire the skills and know-how abroad and invest (or encourage investments) in their countries of origin therefore generating spillover effects on the whole developing economies. Naturally, such different views of “migration pessimism” in the sixties and “migration optimism” three decades later pose a question of whether there is empirical evidence of economic costs and benefits to a country of origin from high-skilled migration. Grubel and Scott (1966) and Berry and Soligo (1969) were the first researchers confronting the negative and positive implications of the brain drain for the sending countries. It should be noted that relationship between high-skilled migration and economic indicators was investigated through a range of disciplinary lenses, the notion of coevolution from evolutionary economics is highly relevant to address; recently, it also attracted a considerable amount of attention (Simandan, 2019; Saviotti, & Metcalfe, 2018). Factors in donor/sending countries affected by brain migration include economic growth, wages, unemployment, remittances, knowledge sharing from current migrants to home country governments or businesses, transnational networks, involvement in trade, foreign direct investments. Beine, Docquier and Rapport (2008) find a negative relationship between brain emigration and GDP per capita due to reduction in human capital. Moreover, emigration could also have detrimental effects on demography of a sending country if young talent migration is prominent, thus decreasing GDP per capita (Marchiori, Shen & Docquier, 2012). The authors distinguish technological process as a mechanism through which high-skilled emigration could affect GDP change in a negative manner. The authors suggest that total factor productivity could decrease as a result of lost talents who otherwise would innovate and adopt technologies in their countries of origin. Positive effect of brain migration could be also found in the scientific literature. Sending countries might nevertheless benefit from highly qualified emigration through remittances, reduced level of unemployment (and associated spending), transnational networks or knowledge transfer. Saxenian (2005) argues that some brains are particularly prone to circulation and beneficial brain drain, such as engineers and entrepreneurs, who armed with linguistic and cultural know-how might adopt business models or attract foreign direct investment (FDI) in their home countries, where there is information asymmetry for foreign investors. Estimates by other authors find a positive effect on reduced information asymmetry and increase in FDI flows (Docquier & 58 ISSN 2029-4581 eISSN 2345-0037 Organizations and Markets in Emerging Economies Lodigiani, 2010). Valema (2012) discusses that circulation of scientists and academics has significant spillover effects on home scientific communities and helps create the institutional framework where science and research could prosper and economies grow in the long term. Empirically, Lodigiani (2008) calculations found a positive impact in terms of externalities on productivity as high-skilled migrants abroad might be essential in technology diffusion from more advanced economies to their less developed domestic economies. The economic indicator that might be affected by high-skilled migration is wages. Iravani (2011) has proposed that there is a negative relationship between high-skilled migration and wages in sending economies and suggests that such effect is the most prominent in countries exporting massive amounts of human capital. The author attributes the negative relationship to “demonstration effect of foreign salaries that artificially inflates local salaries” in spite of lower productivity that exists in a local economy (Iravani, 2011, p. 288). In some cases, the wages could also be kept low on purpose by employers who avoid overinvesting as they are expecting a professional worker to emigrate. Other authors claim the opposite to be true: as Elsner (2013) and Dustmann et al. (2015) claim, wages should increase because of a negative supply shock in human capital – as human capital becomes scarce and a bargaining power of professionals increases. Lastly, the effects of unemployment on the labour market should be considered. Iravani (2011) and Vojtovich (2013) suggest that high-skilled migration should decrease the unemployment if there is surplus brain, overproduction of brain or brain waste in sending countries with high unemployment. Interestingly, Iravani (2011) and Vojtovich (2013) claim that in general, labour force emigration “solves” unemployment problem more efficiently than economic growth does, thus making emigration a non-problematic phenomenon contrary to common beliefs. Such diverse findings require further investigation of economic consequences of emigration and an update in existing ones using different sample countries and time periods. It should be noted that the complex impact of high-skilled migration has been investigated through a range of various disciplinary lenses. The notion of co-evolution from evolutionary economics helps to understand competitive move-countermove dynamics, and it is highly relevant to address the phenomenon under discussion (Simandan, 2019; Saviotti, & Metcalfe, 2018). This paper contributes to a more than 50 years’ worth of literature on the link between migration of the high-skilled and economic development. 2. Data and Methodological Approach In this section, we describe our data and actions to be taken to empirically investigate our research problem. Despite an increasingly negative public and political discourse around the influx of large numbers of migrants, it is generally agreed that highly qualified workers who come 59 Gindrute Kasnauskiene, Juste Palubinskaite. Impact of High-Skilled Migration to the UK on the Source Countries (EU8) Economies to the UK are the most economically valuable migrants and often fill skills shortages faced by particular sectors and employers (Hopkins & Levy, 2012). Moreover, migrant groups with higher levels of education are more likely to have higher rates of employment in the UK. However, one important aspect is that the interest in the topic gained its momentum when the countries were considered as potential new EU member states and right after they joined the EU. Numerous researchers have analysed flows and patterns of migration to the UK. A large body of research after 2004 was dedicated to finding out the causes of EU8 migration to the UK (and other EU countries in the West) and applying general migration theories to this particular migration flow (Dobson, 2009; Kurekova, 2011), whereas only some concentrated on analyzing determinants of brain migration from some of the CEE countries (Ienciu & Ienciu, 2015). Despite a rapidly growing scholarly interest in push and pull factors behind the individual migration decisions of skilled workers which are well established (such as salary, economic environment, availability of job and/or career opportunities, quality of life, working and living conditions, the size of diaspora communities etc.), consequences of CEE migration, especially high-skilled, have been less explored. Researchers have mainly been interested in particular Eastern European countries’ cases but not so much in the implications on a rather homogenous region of EU8 (Kaczmarczyk, 2006; Brzozowski, 2007; Anniste et al., 2012; Kasnauskiene & Budvytyte, 2013). Considering some shortages in the EU8 migration literature, this article contributes to the field of research by analyzing consequences of migration in a particular set of sending countries (EU8) and focuses precisely on the outflow of high-skilled labour force. EU8 region is considered to be a suitable sample due to several reasons. Firstly, all countries (Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia and Slovenia) became EU member states during the third EU enlargement in 2004, which guaranteed free movement of the labour force to the Western EU countries. Secondly, after the enlargement, these Central and Eastern European countries witnessed a negative net migration making such sample highly relevant in testing migration effects. The last reason is the destination country – the United Kingdom has become one of the most attractive places for EU8 immigrants since these countries joined the EU. Due to data constraints, identifying the impact of the skilled migration on welfare and development in originating countries is complex (Docquier, 2014). Unfortunately, official data sources offer a very weak basis for an analysis of the highly skilled mobility and its economic impact. An additional problem is associated with identifying “the highly skilled”. Different approaches to defining and measuring the highly skilled can be found in the literature. Generally, the most commonly used way of establishing that somebody is highly skilled consists in verifying whether they have a tertiary education diploma. In our study, skilled migration data are based on one of the most politicized and publicized statistics of current times in the UK, that is International Passenger Survey (IPS). The IPS is a voluntary survey of passengers travelling to and from the United Kingdom, which allows for extracting immigration numbers from EU8 to the UK by occupation 60 ISSN 2029-4581 eISSN 2345-0037 Organizations and Markets in Emerging Economies for 2004 – 2016 (Office for National Statistics, 2017). These data need to be treated cautiously; skilled migration is reflected by occupation category “managerial and professional workers”. There are four main problems associated with IPS data: • Firstly,methodologicalconcernsarethatIPSaskspersonsmovingtotheUK about their intentions to stay; those who indicate their intention to stay for at least 12 months are classed as movers, and these intentions might not materialize. • Secondly,obviously,someimmigrantsholdingatertiaryeducationdiplomaare not recognized as managerial and professional workers and do not fall into the high-skilled category. • Thirdly,theexistingEU8immigrationdataareinsufficientlydetailedanddonot allow separating the migration flows by smaller regions or countries. • Fourthly,twobroadtypesofvariabilityassociatedwithmigrationestimatesfrom the IPS exist. These are: variability because of the many different samples that could have been drawn during the interview period (known as “sampling error”); and variability due to other factors (“non-sampling error”). These caveats must be always taken into account. Economic variable statistics for EU8, such as GDP per capita, unemployment rate and average monthly wage, are provided by Eurostat and country-specific statistical data authorities. y = -1.319x + 76.615 y = -0.346x + 11.192 0 10 20 30 40 50 60 70 80 90 100 110 20042005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Total Persons holding professional and managerial positions Linear (Total) Linear (Persons holding professional and managerial positions ) FIGURE 1. Number of immigrants from EU8 to the UK, total and persons holding professional and managerial positions before migration, 2004-2016, thousands Source: compiled by the authors from Office for National Statistics, 2017 61 Gindrute Kasnauskiene, Juste Palubinskaite. Impact of High-Skilled Migration to the UK on the Source Countries (EU8) Economies Figure 1 illustrates the importance of the subject matter. It shows that the number of EU8 movers (total and managerial and professional workers) to the UK between 2004 and 2007 increased; in 2008-2013, overall migration levels remained broadly stable followed by a significant decrease since 2014. Yet, the figure reflects negative trends over the period of 13 years; the number of total immigrants and managerial and professional workers entering the UK has yearly decreased on average by 1319 and 346 persons, respectively. However, recently published data in the UK indicated that over the last year 7,000 more EU8 citizens left the UK than arrived following the result of the UK referendum on leaving the EU, which was held in June 2016 (Office for National Statistics, 2019). Our objective in this article is to test whether the emigration of highly qualified workers from the EU8 countries to the UK is detrimental for growth in sending economies. R software was used to achieve the results. Our conceptual methodological approach, based on a ‘pessimistic’ outlook on the impact of the outflow of the high skilled on the sending countries, is expressed in the form of the two hypotheses, H1 for short-term emigration, and H2 for long-term emigration, further broken down to denote their impact on GDP, unemployment and average monthly wages. Specifically, we hypothesize that: H1: Emigration of the high-skilled has a negative impact on EU8 economies in the short term. H1a: Emigration of the high-skilled has a negative impact on EU8 GDP per capita in the short term. H1b: Emigration of the high-skilled has a negative impact on EU8 unemployment in the short term. H1c: Emigration of the high-skilled has a negative impact on EU8 average monthly wages in the short term. H2: Emigration of the high-skilled has a negative impact on EU8 unemployment in the long term. H2a: Emigration of the high-skilled has a negative impact on EU8 GDP per capita in the long term. H2b: Emigration of the high-skilled has a negative impact on EU8 economies in the long term. H2c: Emigration of the high-skilled has a negative impact on EU8 average monthly wages in the long term. The modelling methodology employed describes a goal-oriented procedure; it is commonly used in recent empirical migration analysis. The methods and sequence used for statistical data analysis are the following econometric time series models: a structural vector autoregression (SVAR), impulse-response analysis (IRF), forecast error variance decomposition (FEVD) and cointegration analysis – the Johansen procedure (Enders, 2014). 62 ISSN 2029-4581 eISSN 2345-0037 Organizations and Markets in Emerging Economies Structural vector autoregressive model is chosen for empirical analysis as it examines the impact of short-term structural shocks (innovations) in one variable (migration) to other ones (socio-economic variables) or vice versa. Partridge and Rickman (2006) have used SVAR model in explaining the impact of migration shocks to the labor market in the US. Other researchers considered implementing SVAR model for analyzing socio-economic determinants of net in-migration among US states (Cebula & Alexander, 2006). Vector autoregressive model is also used in constructing impulse-response functions and forecasts error variance decomposition. Correspondingly, these models are helpful in forecasting the influence of migration shocks on economic variables over time and accounting for explained variance in other economic indicators. Cointegration has been widely used in empirical testing of theoretical general equilibrium models with various socio-economic variables. Fromentin (2013) has used the Johansen cointegration test in order to find out the economic implications of immigration on labour market in France; Agbola and Acupan (2010) and Altaf (2015) have implemented the same analysis method to determine long-run migration determinants using developing countries’ cases of the Philippines and Pakistan; Akkoyunlu and Siliverstovs (2009) aimed at using the Johansen cointegration test to investigate general equilibrium relationship between migration growth and trade. In this paper, the Johansen procedure is essential in answering the research question of how economic variables of GDP per capita, wages and unemployment respond to emigration in the long run. The study is prone to certain limitations and assumptions. Due to the nature of data for emigration variable, which had yearly frequency, conversion to quarterly data was performed (Sax & Steiner, 2013). This means emigration variable is an approximation rather than the real emigration values. Nevertheless, the conversion procedure allowed for keeping quarterly time series similar to yearly in terms the way values change over time and should not disrupt the overall findings. Another limitation is the limited number of observations and time interval at hand (2004 – 2016), which means that the results should be interpreted cautiously. This is due to the fact that this study considers the effects after the structural change, i.e. joining the EU, and the data set used provides immigration statistics only from 2004. Lastly, the available migration data required the assumption that EU8 countries are homogeneous and interpretion of results is applicable for all. While the countries are indeed similar in terms of high emigration rates and joining the EU together, in fact the effects of migration on the economy may vary, based on specific country cases. Regardless of these data limitations, our estimates are sufficiently accurate and point to the empirical magnitude of brain movement. 3. Results Our models are used to investigate the interactions between the emigration of the highly skilled from the EU8 countries and main economic variables. That is, two hypotheses stated in the previous section are tested: