The fiscal impact of immigration in the EU

Christl, Michael; Bélanger, Alain; Conte, Alessandra; Mazza, Jacopo; Narazani, Edlira Working Paper The fiscal impact of immigration in the EU JRC Working Papers on Taxation and Structural Reforms, No. 01/2021 Provided in Cooperation with: Joint Research Centre (JRC), European Commission Suggested Citation: Christl, Michael; Bélanger, Alain; Conte, Alessandra; Mazza, Jacopo; Narazani, Edlira (2021) : The fiscal impact of immigration in the EU, JRC Working Papers on Taxation and Structural Reforms, No. 01/2021, European Commission, Joint Research Centre (JRC), Seville This Version is available at: https://hdl.handle.net/10419/248823 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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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/ The fiscal impact of immigration in the EU JRC Working Papers on Taxation and Structural Reforms No 01/2021 Michael Christl, Alain Bélanger, Alessandra Conte, Jacopo Mazza & Edlira Narazani This publication is a Technical report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking p rocess. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication. For information on the methodology and quality underlying the data used in this publication for which the source is neither Eurostat nor other Commission services, users should contact the referenced source. The designations employed and the presentation of material on the maps do not imply the expression of any opinion whatsoever on the part of the European Union concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. EU Science Hub https://ec.europa.eu/jrc JRC124744 Seville: European Commission, 2021 © European Union, 2021 The reuse policy of the European Commission is implemented by the Commission Decision 2011/833/EU of 12 December 2011 on the reuse of Commission documents (OJ L 330, 14.12.2011, p. 39). Except otherwise noted, the reuse of this document is authorised under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed provided appropriate credit is given and any changes are indicated. For any use or reproduction of photos or other material that is not owned by the EU, permission must be sought directly from the copyright holders. All content © European Union, 2021. How to cite this report: Christl M., Bélanger A., Conte A., Mazza J. & Narazani E. (2021), The fiscal impact of immigration in the EU, JRC Working Papers on Taxation and Structural Reforms No 01/2021, European Commission, Joint Research Centre, Seville. JRC124744 Executive Summary In recent decades, many EU Member States have been experiencing low growth rates and rising economic inequality, as well as declining fertility and ageing population. These developments raise concerns about the sustainability of many European welfare systems that have been designed according to different demographic dynamics and structures. The current situation places the burden of providing the necessary budgetary resources to support European social protection standards on a shrinking active population. Potential solutions to these challenges, including reducing the social protection scheme, raising the retirement age in line with increasing life expectancy, and increasing labour market participation of all segments of the potentially active population, are strongly discussed among policymakers. In this complex policy portfolio, immigration can also be seen as an important element as it could partially compensate for the demographic deficit, broaden the tax base and thus contribute to economic growth. However, immigration also poses challenges, as the long-term net fiscal impact depends crucially on the integration of migrants into the labour market. Today, few comprehensive analyses at EU-wide on the net fiscal impact of immigration have answered how immigration affects the resources needed for social welfare systems. This is our goal in this paper. To assess the net fiscal impact of immigration we use EUROMOD, the tax-benefit microsimulation model for the European Union. EUROMOD is a unique tool for international comparative research on the effects of taxes and benefits, using individual and household data from the European Union Survey of Income and Living Conditions (EU-SILC). We expand EUROMOD with information on Value Added Taxes (VAT) by simulating VAT rules and using the Household Budget Survey (HBS) to account for different consumption patterns of migrants and natives. We also add information on in-kind benefits related to education, health care provision and social housing to the standard tax-benefit model. We combine static microsimulation modelling with a life-cycle approach to estimate the long-term implications of immigration. We calculate two concepts of net fiscal impact for natives, intra-EU and extra-EU migrants: the average net fiscal impact (ANFI) revealing the current impact of migrants on state budgets; and the life-cycle deficit (LCD) to obtain an estimate on the long-term implications. Simulation results suggest that, when considering the ANFI, both intra-EU and extra-EU migrants have a negative but higher net fiscal impact than the native population. This means that the average immigrant is currently less costly to the public budget than the average native. However, when we control for the age structure and obtain an estimate of the net fiscal impact over the life cycle (LCD), the estimates indicate that natives have a higher (less negative) net fiscal impact than intra-EU migrants, who in turn show a higher (less negative) net fiscal impact than Extra-EU migrants. Simulations also show substantial differences in both concepts of the net fiscal impact between EU Member States. This potentially reflects the differences in the characteristics and history of migration between Member States. Especially in traditional welfare states, such as Austria, Belgium, Denmark, Finland, the Netherlands and Sweden, the differences in the net fiscal impact between natives and extra-EU migrants throughout the lifecycle are considerable, while the differences between natives and intra-EU migrants seem to be less pronounced. This divergent picture draws attention to the present challenge of labour market integration of extra-EU migrants particularly and suggests that better integration into the labour market could be the key to improving their fiscal contribution. The fiscal impact of immigration in the EU Michael Christla,∗ , Alain B´ elangerb, Alessandra Contec, Jacopo Mazzac, Edlira Narazania aJ.R.C. Seville, European Commission bI.N.R.S, Montreal. cJ.R.C. Ispra, European Commission Abstract The increasing flows of immigrants in Europe over the last decade has generated a range of considerations in the policy agenda of many receiving countries. One of the main considerations for policy makers and public opinions alike is whether immigrants contribute their ”fair” share to their host country tax and welfare system. This paper seeks to answer this question based on an empirical assessment of the net fiscal contributions of immigrants in the 27 EU Member States using EUROMOD, a EU-wide tax-benefit microsimulation model. In addition to the traditional view of the tax-benefit system, we add indirect taxation and in-kind benefits to the analysis of net contributions. Our findings highlight that migrants on average contributed about 250 euro per year more than natives to the welfare state in 2015. However, when we take an average age-specific life-cycle perspective, we find that natives generally show a higher net fiscal contribution than both, intra-EU and extra-EU migrants, while extra-EU migrants contribute on average less than intra-EU migrants. Keywords: Migration, Microsimulation, Tax-benefit system, EUROMOD JEL codes: F22, J15, H2, H5 ∗Corresponding author. Email: [email protected] The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission. 1. Introduction The number of third-country nationals living in the EU has grown in recent years. According to the most recent figures by Eurostat for 2018, there are over 22 million third-country nationals residing in the 27 Member States (MSs) of the EU and the UK. This is up from 19 million in 2014 - the first available year for this series - corresponding to a 14% increase in five years. For many MSs, this phenomenon inevitably generates a range of social, political and economic considerations. One of the main considerations for policy makers and public opinions alike is whether migrants contribute their ”fair” share to their host country tax and welfare system. Fears of welfare abuses are common among European citizens (Boeri,2010) together with worries that the European welfare systems might act as a magnet for welfare-dependent migrants (De Giorgi and Pellizzari,2009). These concerns are so deep that they outshine even worries about labour market effects of immigration in public opinion’s assessment (Dustmann and Preston,2007) and are hard to ignore for governments. Apart from public attitudes on migration and questions of perceived fairness, understanding the fiscal impacts of immigration is especially salient for the EU MSs’ decision-making processes, because it enables the design of an appropriate immigration strategy. The EU countries maintain a comparably extensive and generous welfare coverage1against the backdrop of deteriorating fiscal balances, in some MSs more than others, since the onset of the global financial crisis. Migration can have both positive and negative consequences for the economies and the public purse of the receiving countries. On the one hand, a growing migrant population, mostly migrating in their most productive years, can help alleviate the financial burden that an ageing population imposes on the pension systems of many MSs. On the other hand, migrants may represent a burden because of the costs associated with their integration and inclusion, family structure and/or to the safety net for their labour career. Depending on whether positive or negative effects prevail, the fiscal impact of migrants might be different from that of the typical native on whom the European welfare states were originally designed. In this article, we study the fiscal impact of immigration on the EU. For this purpose, we use EUROMOD, the tax-benefit microsimulation model for the EU that represents a unique tool for international comparative research on the effects of taxes and benefits. EUROMOD is based on detailed information at the individual level on taxes paid and benefits received contained on the European Union Statistics on Income and Living Conditions (EU-SILC). We complement the individual-level data with detailed information on in-kind benefits and indirect taxation. In this way we are able to provide a thorough assessment on the fiscal impact of migration. Additionally, contrary to the National Transfer Accounts approach (see e.g. Istenic et al. (2016)), our approach allows us to distinguish between natives, intra-EU and extra-EU migrants and account for the socio-economic factors, such as education or labour force differentials, that drive the difference in their net fiscal contributions. We estimate the net fiscal impact for natives and migrants in two steps. First, we compute the present impact of migrants on state budgets and recover the average net fiscal effect of migration. 1According to the OECD, on average, EU MSs spent 23% of their GDP to fund their social security programmes in 2018. The average for the other non-EU OECD members was 18%. (Source: https://stats.oecd.org/Index. aspx?datasetcode=SOCX_AGG, last accessed 07/11/2019.) 1 Second, following the approach of Hinte and Zimmermann (2014), we estimate the life-cycle contribution of each population group. By focusing on the whole EU and on three origin groups - natives, intraand extra-EU migrants - our analysis goes beyond previous studies on the fiscal impact of immigration that focus on one country (Chojnicki and Ragot,2016;Dustmann and Frattini,2014;Storesletten,2003) or on subpopulations only, such as intra-EU migrants (Nyman and Ahlskog,2018). Rather, we are able to account for the different statutes governing welfare provisions across the EU and compute the fiscal positions for the whole population. Our research is also quite unique in combining both ‘static’ and ‘perspective’ approaches allowing us to determine the extent to which differences in the age structure between migrants and natives determine their fiscal balance. The life-cycle approach can offer precious indications to policy makers on the possible evolution of the fiscal balance once recently arrived migrants will start to age approaching the age distribution of natives. Therefore, it also indicates a more longterm perspective of the net fiscal impact of immigration. Our main findings can be summarized as follows: First, the average net fiscal impact (ANFI) for all three groups is negative, but natives show the highest imbalance, indicating that currently, the average immigrant is less costly in monetary terms for the state. Accounting for the demographic composition further increases the overall deficit for all groups, but improves the relative position of natives who in a life cycle contribute in net terms more than intra-EU migrants, who in turn exhibit a less negative net fiscal position than extra-EU migrants. Second, we also find substantial differences across EU MSs regarding both concepts of the net fiscal impact. Most likely, this reflects the differences in types and history of migration characterizing the EU MSs. Especially in the traditional welfare states, differences in the net fiscal impact between natives and extra-EU migrants over the life cycle are substantial, while differences between natives and intra-EU migrants seem to be less pronounced. The paper is organized as follows. In Section 2.2, we discuss the literature related to the fiscal impact of immigration focusing on the European context and the general immigration patterns in the EU. Section 3describes the data and methodology that we use. In Section 4, we present the simulation results both from an EU perspective as well as from the perspective of each MS. Section 5concludes and comments on our main results. 2. Background 2.1. Evidence on the fiscal impact of migration The analysis of the fiscal impact of immigration in Europe has gained attention in recent years due to growing concerns about the sustainability of welfare states in a context of major demographic changes and challenges for Europe (Lutz et al.,2019). The empirical evidence on this topic is mixed and depends largely on the economic context, the methodology adopted, as well as the characteristics of migrants. This literature adopts two main approaches: either static or dynamic. The static accounting approach captures a snapshot of public finances over one or more years by allocating the contributions made and benefits received between the native and immigrant populations. The results of static analyses largely depend on the demographic unit of analysis (individuals or households) and its demographic and socio-economic 2 characteristics as well as on the benefits and taxes covered and years analysed. The advantage of the static approach is that it does not require assumptions on future demographic trends or public spending. However, the results lack the forward-looking perspective that is increasingly required to inform public fiscal policy. Usually, the fiscal impact of immigration is quantified as modest and on average below (+/-) 1% of the national GDP (Chojnicki,2013). Studies using this approach find that the favorable demographic structure of migrants, skewed towards a younger and active population, advantages their fiscal position (Bogdanov et al.,2014;Dustmann et al.,2010;Chojnicki,2013). The socioeconomic factors influencing the fiscal impact commonly identified in the literature are the age at arrival in the host country,2the number of children in the family3and whether migrants are highskilled (who generally contribute positively to the fiscal balance) or low-skilled (who typically have a less favorable fiscal position).4 Dynamic approaches typically focus on the entire life cycle. They can be classified in three groups: Net Present Value (NPV) Approach, Generational Accounting Analysis (GA) and Dynamic Applied General Equilibrium Model (DAGEM). This evidence is forward-looking and the results depend heavily on assumptions over future developments of population and migration trends, government taxes and expenditures, or migrants’ rights to access public services and benefits (Vargas-Silva,2015). Studies using an NPV approach have been conducted for example in Sweden, where Storesletten (2003) and Ekberg (2011) estimate a negative net contribution of immigrants. They estimate that immigration to a traditional welfare state such as Sweden typically causes a fiscal burden to the state, however this result crucially depends on the characteristics of migrants.5 Studies using a GA approach account for the intertemporal distribution of public debt (OECD, 2013). Evidence using this methodology is available for several countries while cross-country comparisons are rather scarce (Hinte and Zimmermann,2014). Results show considerable variation, depending on immigration and integration policy, but in general tend to show a positive effect of increasing immigration flows on the tax burden of future native generations.6For Bonin et al. (2000), immigration generates a positive fiscal effect and reduces the fiscal burden of future generations in Germany; however, this effect is not enough to eliminate the future fiscal imbalance resulting from the ageing of the German population.7 2This is due to potential savings on education in young ages (Economics,2018). 3E.g. Dustmann and Frattini (2014) estimate that migrants from European Economic Area (EEA) countries contributed positively to the UK public finances over the period 1995-2011, while the net fiscal impact of non-EEA migrants was negative. The higher number of children of non-EEA migrants may also explain these results as they represent a fiscal cost for the destination country. 4For Ruist (2014), a cohort of Bulgarian and Romanian migrants in Sweden contributed positively to the country’s finances in 2011, however, the lack of language skills was an important barrier to entering the labour market. See also Christl et al. (2020). 5Storesletten (2003) attributes the negative effect that he encounters to migrants’ difficult assimilation in the labour market. It has also to be noted that he finds a positive contribution for those aged 20-30 years. Similarly, Gustafsson and ¨ Osterberg (2001) show the importance of labour market integration on the net fiscal impact of migration. 6See, e.g., Collado et al. (2004), Mayr (2005), Chojnicki et al. (2011), Chojnicki (2013)orChojnicki and Ragot (2016). 7Other analyses that take into account the life cycle of immigrants show that greater fiscal gains can come from 3 Figure 2: Net fiscal contributions by migration status in the EU -15,000 -10,000 -5,000 0 5,000 10,000 15,000 Euros -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Natives Intra-EU migrants Extra-EU migrants (a) Net contributions -15,000 -10,000 -5,000 0 5,000 10,000 15,000 Euros -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Tax: VAT Tax: Income Tax: SIC Ben: In-kind Ben: Rest Ben: Pension Ben: Unemployment Net contributions (b) Natives -15,000 -10,000 -5,000 0 5,000 10,000 15,000 Euros -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Tax: VAT Tax: Income Tax: SIC Ben: In-kind Ben: Rest Ben: Pension Ben: Unemployment Net contributions (c) Intra-EU -15,000 -10,000 -5,000 0 5,000 10,000 15,000 Euros -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Tax: VAT Tax: Income Tax: SIC Ben: In-kind Ben: Rest Ben: Pension Ben: Unemployment Net contributions (d) Extra-EU 10 readily explained with natives’ higher current wages and past social security contributions, respectively. The third fact is mostly explained by differences in socio-demographic characteristics, such as number of children or people employed within a family and so on. Looking at gender differences, Figure 3, we can see that women generally have lower net fiscal contributions during their working age time span most likely because of the unequal share of unpaid work in most European countries and a persistent gender gap in labour force participation. This also results in lower pension entitlements and therefore a less negative impact of net fiscal contribution, on average. Again, natives and intra-EU migrants tend to have a similar NFI for both genders over the life cycle. On the other hand, the NFI of extra-EU migrants is found to be lower, but the gender gap between natives and extra-EU migrants is almost null. Figure 3: Net fiscal contributions by migration status and gender in the EU -30,000 -25,000 -20,000 -15,000 -10,000 -5,000 0 5,000 10,000 15,000 EUROS -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Natives Intra-EU migrants Extra-EU migrants (a) Females -30,000 -25,000 -20,000 -15,000 -10,000 -5,000 0 5,000 10,000 15,000 EUROS -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Natives Intra-EU migrants Extra-EU migrants (b) Males Finally, we decompose the net fiscal effects by three levels of education. As shown in Figure 4c, there are no significant differences in net fiscal effects between highly educated migrants and natives. In fact, the shape of the net fiscal contributions is very similar. The picture looks very different for lower educated individuals, shown in Figure 4a: natives and extra-EU migrants behave in a very similar way, while intra-EU migrants do not. Indeed, intra-EU migrants contribute much more than the rest of population and consequently are entitled to higher pensions. 4.2. The net fiscal impact over the life cycle An analysis of the average net fiscal effect of migrants can reveal useful information on the current impact of migrants on the public budget. However it does not help reveal any element on their contribution over their lifetimes. As argued by Hinte and Zimmermann (2014), only analysing the net fiscal effects of immigration for one fiscal year alone leaves out an important part of the picture. A life-cycle perspective approach could help to add additional information on the long-term impact of migration. When comparing the results attained under both concepts, the ANFI and the LCD, it can be seen that at the EU level migrants have a negative ANFI (-208 euro for intra-EU and -219 euro for extra-EU), although higher than natives (-476 euro). This means that 2015 migrants are less of a burden on the EU public budget than natives. However, when looking at the aggregate LCD 11 Figure 4: Net fiscal contributions by migration status and education in the EU -30,000 -25,000 -20,000 -15,000 -10,000 -5,000 0 5,000 10,000 15,000 EUROS -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Natives Intra-EU migrants Extra-EU migrants (a) Low education -30,000 -25,000 -20,000 -15,000 -10,000 -5,000 0 5,000 10,000 15,000 EUROS -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Natives Intra-EU migrants Extra-EU migrants (b) Middle education -30,000 -25,000 -20,000 -15,000 -10,000 -5,000 0 5,000 10,000 15,000 EUROS -15 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 75+ age groups Natives Intra-EU migrants Extra-EU migrants (c) High education estimate (controlling for age structure), it can be seen that the fiscal impact is less negative for natives (-723 euro) than for intra-EU migrants (-1106 euro) and extra-EU migrants (-2411 euro). These numbers suggest that the negative fiscal impact of migrants over the life cycle is expected to be more than that of natives. Table 1: Average net fiscal impact and life-cycle deficit in the EU in euro, 2015 ANFI LCD (0-80) LCD (0-75) LCD (0-85) Natives -476 -723 208 -1825 Intra-EU -208 -1106 46 -2411 Extra-EU -219 -2600 -1622 -3799 There are several reasons for the higher magnitude of negative life-cycle impact as compared to the ANFI. First, the life-cycle impact is estimated by selecting a sample from the age of 0 to the age of 80 (80.6 years was the official average life expectancy in 2015 in the EU). However, migrants may have different mortality rates than natives. As a a robustness check, we also add LCD estimates for different age limits (75 years and 85 years). We can see that if we assume a 12 lower age limit, the LCD turns positive, at least for natives and intra-EU migrants. However, the LCD for extra-EU migrants stays negative. When assuming an age limit of 85, the LCD turns substantially more negative. Second, this approach controls for different population weights. Currently, in most countries, more people are of working age (15-64) and thus on average net contributors, while fewer people are young (0-15) and older (65 and more), people who are usually net recipients. When using an average indicator, such as the ANFI, this obviously has an impact on the fiscal outcome. For the LCD, however, those differences do not matter. The differences between ANFI and LCD indicators clearly stand out. When we take a look on the ANFI, migrants tend to have a better NFI for the state than natives. However, when we focus on the LCD, migrants, and especially extra-EU migrants, exhibit a substantially higher deficit than natives, which stems from their more favourable age structure which the ANFI estimates do not control for. Focusing on the long-run fiscal impact of migration, the LCD might be the more interesting concept, while focusing on the immediate impact on the welfare state, the ANFI might be the indicator of interest. 4.3. Country-specific differences in ANFI and LCD In this section we discuss the current ANFI of migrants at the country level. In addition, we compare these static impacts with country-specific estimates derived from the LCD approach. Figure 5shows the ANFI for all MSs. It can be observed that in Austria, Belgium, Spain, Finland, Denmark, the Netherlands, Ireland, Italy and Portugal the current fiscal impact of intraEU migrants is higher than for natives. In addition, in countries, such as Austria, Cyprus, the Czech Republic, the Netherlands, Denmark, France, Italy and Portugal, ANFI is higher even for extra-EU migrants as compared to natives. There are also substantial differences between intra-EU and extra-EU migrants. However, these results can be driven by the age structure of the three sub groups. Therefore, we also analyse the LCD related to our three groups of interest. As expected, those results are substantially different to the ANFI. Again, results on the country level show different patterns across different MSs. Figure 6highlights substantial differences across the different migration statuses when looking at the LCD. In general, figures on LCD of natives and intra-EU migrants are often quite similar. However, in some countries, such as Belgium and some Eastern European countries, the NFI of intra-EU migrants over the life cycle is even higher than for natives. Extra-EU migrants typically show a significantly higher LCD than natives and migrants. Looking further in the data, it can be seen that this is mostly related to their lower labour market participation. Especially in the traditional welfare states, such as Austria, Belgium, Denmark, Finland, the Netherlands and Sweden, differences in the NFI between natives and extra-EU migrants (but also differences across intra-EU and extra-EU migrants) over the life cycle are substantial.15 One has to be cautious when interpreting these results. The LCD approach does not account for the fact that many first-generation migrants have attained their education level in their country 15Please note that in most of the Eastern European countries, extra-EU migrants are a very small group, which leads to substantial uncertainty in our results. 13 Figure 5: Average net fiscal impact (ANFI) by country and migration status -5,000 0 5,000 10,000 Average net contribution in Euro AT BE BG CY CZ DEDK EE EL ES FI FR HR HU IE IT LT LV MT NL PL PT RO SE SI SK UK Natives Intra EU Extra EU Note: In some countries, intra-EU and extra-EU migrants are combined into one group due to data limitations. of origin. This means that educational costs of migrants are often not payed by the host country. Therefore, ignoring them would lead to an overestimation of the average costs in young ages of migrants and an increase of the LCD estimated for migrants. Figure D.7 in the Appendix highlights the differences in the net contribution by migrant status in all EU MSs over the life cycle. 14 Figure 6: Life-cycle deficit (LCD) by country and migration status -6,000 -4,000 -2,000 0 2,000 Life cycle deficit in Euro AT BE BG CY CZ DEDK EE EL ES FI FR HR HU IE IT LT LV MT NL PL PT RO SE SI SK UK Natives Intra EU Extra EU Note: In some countries, intra-EU and extra-EU migrants are combined to one group due to data limitations. 5. Conclusion and discussion There is a long-lasting discussion on the NFI of migration. For decades, economists and especially policy makers have been asking whether a more favorable account balance is expected from migration. In other words, whether the expenditures on benefits, pensions and other social security services could be more or less balanced by revenues collected in the form of taxes and social security contributions. Our paper tackles this question by estimating the NFI for natives and migrants using detailed micro-data from the EU-SILC. To compute the NFI of migration, we extend the EU-SILC data in several ways. First, we take into account indirect taxes and in-kind benefits. Second, we add VAT taxes by simulating VAT rules using the HBS to take into account the different consumption patterns of migrants and natives. Third, we enrich the EU-SILC with information on in-kind benefits, based on OECD statistics that allow us to apportion the cost of education, social housing and health care provisions among individuals. In this paper, we combine static microsimulation modelling with a life-cycle approach to estimate long-term implications of migration, following Hinte and Zimmermann (2014). To this end we exploit EUROMOD to calculate two concepts of NFI: the average net fiscal effect that reveals the current impact of migrants on the state budgets; and the life-cycle contribution to obtain an estimate on long-term implications. Our results suggest that when considering the ANFI, both intra-EU and extra-EU migrants have a negative but higher NFI than natives. This means that, currently, the average immigrant is less of burden on the public budget than the average native. 15 However, this result might be influenced by the difference in the demographic composition of each group. To account for the impact of demographic composition of the three groups, we control for age structure and obtain an estimate of NFI over the life cycle. The estimates indicate that the net fiscal contributions appear to be even more negative over the life cycle although natives show a higher contribution than intra-EU migrants, who in turn exhibit a higher (less negative) NFI than extra-EU migrants. Additionally, we find that there are substantial differences across EU MSs regarding the net fiscal impact of migration, in both concepts. This potentially reflects the differences in types and history of migration characterizing the EU MS. Especially in the traditional welfare states, such as Austria, Belgium, Denmark, Finland, the Netherlands and Sweden, differences in the NFI between natives and extra-EU migrants over the life cycle are substantial, while differences between natives and intra-EU migrants seem to be less pronounced. 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Miller, eds., Handbook of the Economics of International Migration, Vol. 1 of Handbook of the Economics of International Migration, North-Holland, 2015, pp. 845–875. 18 Appendix A. Tax and benefit disaggregation Tax and benefit systems differ substantially across EU Member States. Nevertheless, EUROMOD allows us to aggregate all the benefits and taxes in each country in a comprehensive way. By taking advantage of this aggregation feature of EUROMOD, we aggregate the calculated outcome variables into several categories according to the nature of the variables themselves. On the government expenditures side, we have information about the following cash benefits received by every individual in the survey: •family and child benefits, which include child care and child education, family, maternity and parental leave benefits; •health and health-related benefits and pensions, which include accidents, receiving care, caring, disability and health benefits, disability and health pensions; •housing benefits and pensions, which include housing, heating and municipality benefits; •old age and age-related benefits and pensions, which include old age, survivors and early retirement benefits, civil servant, minimum, old age, survivors and early retirement pensions; •work-related benefits, which include unemployment and work-related benefits; •social assistance benefits and pensions, which include social assistance and military benefits; •social insurance contributions. In terms of direct benefits received, we therefore aggregate the benefits to the following categories: •”BENEFITS: unemployment”: Covers all unemployment benefits (contributory, as well as non-contributory) as well as work-related benefits; •”BENEFITS: pension”: Covers all pension benefits (survivor pensions, old-age pensions); •”BENEFITS: rest”: Covers all the additional benefits, such as family benefits, health benefits, housing benefits and social assistance benefits. On the government revenue side, we have information on income and other types of taxes as well as on social security contributions. We aggregate them as follows: •”TAXES: on income”: Covers all taxes on income sources (labour income, capital income, property income and other specific taxes such as church, health, municipal, pension insurance, wealth and early retirement tax) that are simulated in EUROMOD; •”TAXES: social insurance contributions”: Covers all social security contributions paid by the employer, the employee and the self-employed. To calculate the final net contribution of individuals we subtract the sum of all benefits received from the individual from the contributions (income taxes and social insurance contributions) made: •”NET Contributions (contributions - benefits)”: Covers all individual contributions net of benefits received. 19 Appendix D. Additional graphs 26 Figure D.7: Net contribution by country and migration status -4000 -2000 0 2000 4000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups BG -6000 -4000 -2000 0 2000 4000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups HR -4000 -2000 0 2000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups RO -10000 -5000 0 5000 10000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups CZ -6000 -4000 -2000 0 2000 4000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups EE -10000 -5000 0 5000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups EL -6000 -4000 -2000 0 2000 4000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups HU -6000 -4000 -2000 0 2000 4000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups LT -6000 -4000 -2000 0 2000 4000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups PL -15000 -10000 -5000 0 5000 10000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups PT -10000 -5000 0 5000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups SK -15000 -10000 -5000 0 5000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups CY -15000 -10000 -5000 0 5000 10000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups ES -10000 -5000 0 5000 10000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups SI -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups DE -20000 -10000 0 10000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups IE -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups IT -30000 -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups NL -30000 -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups AT -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups BE -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups DK -30000 -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups FI -30000 -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups FR -30000 -20000 -10000 0 10000 20000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups SE -15000 -10000 -5000 0 5000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups MT -4000 -2000 0 2000 4000 Euros -15 15_to_24 25_to_34 35_to_44 45_to_54 55_to_64 65_to_74 75+ age groups LV natives EU mobile citizens non-EU born migrants Note: In some countries, intra-EU and extra-EU migrants are combined to one group due to data limitations. 27 GETTING IN TOUCH WITH THE EU In person All over the European Union there are hundreds of Europe Direct information centres. 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