Location: Poland
Human Capital Loss Among Belarusian and Ukrainian Migrants to the EU

This policy brief examines the underutilization of human capital among involuntary migrants from Ukraine and Belarus in Poland and Lithuania. Focusing on those who migrated after 2020 (Belarus) and 2022 (Ukraine), the brief investigates the factors influencing the conversion of their pre-migration skills into gainful employment in their host countries. Our findings show that despite many migrants possessing high levels of education and professional qualifications, structural barriers and low convertibility of their skills, hinder their full labor market integration. This skill underutilization not only limits migrants’ professional growth and earning potential but also deprives the host countries of valuable skills and potential economic gains.
Effective labor market integration substantially benefits both host and sending countries and migrants themselves. For host nations, successful integration can alleviate critical skill shortages, boost productivity, and drive economic growth (Boubtane, Dumont, & Rault, 2016; Boubtane, 2019; Engler, Giesing, & Kraehnert, 2023; Bernstein et al., 2022). Conversely, inadequate integration leads to underemployment, diminished potential, and economic inefficiency. Countries of origin can benefit from remittances, the return of migrants with enhanced skills, and strengthened international economic ties. However, poor integration risks an uncompensated “brain drain” (Reinhold & Thom, 2009; Barrett & O’Connell, 2001; Iara, 2006; Barrett & Goggin, 2010; Co, Gang, & Yun, 2000). For migrants, the ability to continue their careers means higher earnings and less stress from the acquisition of a new profession, while the non-utilization of existing skills results in their depreciation, potentially causing permanent wage reductions even upon return to the home country (Bowman & Myers, 1967).
Migrants can be broadly categorized into voluntary migrants or forced migrants. Voluntary migrants assess labor market prospects beforehand and often possess convertible human capital – one that can be used in a new labor market. This group often includes professionals like IT specialists and scientists and those in low-skilled but highly transferable professions. Forced migrants, on the contrary, may be utterly unprepared for changes in jurisdiction and possess skills of limited transferability. For example, even highly specialized professions requiring extensive training and substantial human capital, such as lawyers, officials, and teachers, often prove “non-convertible“ (Duleep & Regets, 1999). These individuals’ skills are frequently country specific.
Low convertibility of skills generates significant negative consequences. Highly educated professionals, for instance, may find themselves relegated to low-paying, unskilled jobs, unable to leverage their expertise. This hinders their professional development and deprives host countries of valuable skills and potential contributions to economic growth. Addressing these mismatches is crucial for maximizing the benefits of migration for stakeholders in both home and host countries.
Forced Migration from Belarus and Ukraine
The political crisis in Belarus, starting with the contested 2020 presidential elections, led to widespread repression and significant forced migration. Belarus’s role in supporting Russia’s 2022 invasion of Ukraine exacerbated this situation, resulting in approximately 300,000 Belarusians seeking refuge in the European Union (Eurostat). This number accounts for a substantial proportion of the country’s 9 million population and its approximately 5 million-strong labor force (Belstat).
Russia’s full-scale invasion of Ukraine triggered the most significant wave of migration in Ukrainian history, with over 6 million of the pre-war 44 million population fleeing to the EU (UNHCR). About 90 percent of the initial refugees were women and children due to a mobilization law preventing most men aged 18 to 60 from leaving (UNHCR).
Online Survey and Migrant Differences
To better understand the situation of migrants, their integration into the EU labor market, and to develop data-driven recommendations for improving their conditions, the CIVITTA agency, in partnership with BEROC, conducted an online survey in the summer of 2024. This brief is based on the survey results. The survey includes responses from 616 Ukrainian nationals who migrated to Poland or Lithuania after Russia’s full-scale invasion of Ukraine in 2022, as well as 173 Belarusian migrants who left their home country after 2020. The research focuses on individuals aged 28 to 42, providing insights into their experiences and challenges in the labor market in their host countries. While we acknowledge the sample’s limitations in terms of representativeness, we believe the findings provide valuable insights into the specific challenges faced by involuntary migrants and their adaptation strategies in the new labor market.
Key differences characterize these migration waves. Ukrainian migration comprises of more women, while Belarusian migrants show a more balanced gender distribution, with 47 percent women in our sample versus 62 percent for Ukrainians. Family separation is also notable, as 91 percent of married Belarusians live with their spouses, compared to only 75 percent of Ukrainians (due to the mobilization law).
Survey respondents from both groups possess high levels of human capital with 60 percent of Ukrainians and 90 percent of Belarusians holding higher education degrees. Among Belarusians, 94 percent had over five years of work experience before migration, with and 79 percent of Ukrainians stating the same.
Ukrainian return intentions are split: 38 percent plan to return, 19 percent will not, and the rest are undecided. An end to the war and changes in Russian foreign policy would increase return rates to 70 percent. For Belarusians, 35 percent plan to return, 38 percent will not, and the rest are undecided. Education level is key, as less-educated Belarusians are more likely to stay abroad. An end to repression would increase the share of those Belarusians who want to return to 70 percent, and a regime change would increase this percentage to 82 percent.
Factors Conditioning Human Capital Loss
As expected, due to the involuntary nature of migration of the two groups in focus, a large fraction of survey participants reported losing their profession after migration. As Figure one shows, 48 percent of Belarusians and 63 percent of Ukrainians in our sample reported full loss of their prior careers. The lower percentage of Ukrainians fully retaining their careers (23 percent) compared to Belarusians (44 percent) could be attributed to several factors, including the more recent and disruptive nature of the Russo-Ukrainian war leading to more significant displacement and challenges in finding comparable work. The higher percentage of Ukrainians starting their careers from scratch (49 percent compared to 29 percent among Belarusians) also supports this idea.
Figure 1. Preservation of careers in the EU

Source: Authors’ computations based on survey data.
To foster an evidence-based discussions on the smooth integration of migrants into the EU labor market and the prevention of human capital loss, it is crucial to examine the individual factors that influence career continuity for Belarusian and Ukrainian migrants. We therefore utilize a logistic regression model to identify key predictors that increase the likelihood of migrants remaining in their profession after relocating to Poland and Lithuania.
In our quantitative analysis, an outcome binary variable for staying in the profession is equal to 1 if an individual either “continued career started in a home country (in the same position)” or “remained in the same profession but started working in a position lower than the one held before emigration.” As predictors, we consider a set of sociodemographic variables reasonably related to the probability of staying in the profession and dummy variables for the most common spheres of employment (see Table 1).
Table 1. Overview of model variables
Who Maintains Their Career After Emigration?
Based on the regression coefficients in Table 2, we can identify characteristics related to losing career-specific human capital. In our regression, we control for both home and host country factors. One noteworthy finding is that, while Ukrainian migrants in our sample report significantly higher rates of career loss than Belarusian migrants, nationality itself does not emerge as a significant predictor of career loss once other characteristics are accounted for.
Our results also show that the probability of staying in a profession is higher among men, those with more extended work experience and higher income before emigration, and those who were invited to a host country by an employer. The same holds for entrepreneurs, those who do not plan to return, and those employed in the fields of Architecture & Engineering and Information and Communication Technologies.
Table 2. Results of regression analysis

Note: *** Significant at the .001 level. ** Significant at the .01 level. * Significant at the .05 level.
Conclusion
Several conclusions and policy advice can be derived from the survey results.
The higher likelihood of entrepreneurs staying in their profession suggests that supporting migrant entrepreneurship can be a valuable strategy to retain human capital. This can be done, for example, by:
- Providing access to resources, mentorship, and funding for migrant entrepreneurs.
- Streamlining the procedures for migrants to start and operate businesses.
- Facilitating access to capital for migrant-owned businesses.
The research highlights the disproportionate impact of human capital loss on women. Therefore, policies should include gender-specific programs that address women’s unique challenges in integrating into new labor markets. This could include:
- Skills retraining and certification programs: Designed to align women’s existing skills with the demands of the host country’s labor market, with consideration for childcare needs and other barriers women may face.
- Connecting women migrants with established professionals in their fields to facilitate knowledge transfer and career guidance.
- Language training programs: Tailored to the specific needs of women, potentially incorporating childcare support to enable participation.
The study highlights the positive role of international companies in supporting employee relocation. Respondents who were invited by an employer demonstrated the most successful integration into the new labor market. To enhance and strengthen these networks, policies may focus on:
- Encouraging corporations to hire and train migrant workers, potentially through tax breaks or other incentives. This could include partnerships with migrant-serving organizations to connect companies with qualified candidates.
- Developing digital platforms that connect migrants with diaspora networks, potential employers, and relevant resources.
In addition, policies should address the non-recognition of foreign qualifications, simplifying and expediting the procedures for recognizing foreign degrees and professional certifications. Initiatives to create targeted training programs could complement such policies and allow migrants to quickly acquire any missing skills or certifications required by the host country’s professional bodies. These policy measures would enhance the utilization of migrants’ human capital, benefiting both migrants and host countries while also supporting sending countries. This could be achieved by fostering a successful diaspora or facilitating productive reintegration in the case of return migration.
References
- Barrett, A., & Goggin, J. (2010). Returning to the question of a wage premium for returning migrants. National Institute Economic Review, 213, R43–R51. https://doi.org/10.1177/0027950110389752
- Barrett, A., & O’Connell, P. J. (2001). Does training generally work? The returns to in-company training. ILR Review, 54(3), 647–662. https://doi.org/10.1177/001979390105400403
- Bernstein, S., Diamond, R., McQuade, T. J., & Pousada, B. (2022). The contribution of high-skilled immigrants to innovation in the United States (No. w30797). National Bureau of Economic Research. https://doi.org/10.3386/w30797
- Boubtane, E. (2019). The economic effects of immigration for host countries. L’Economie politique, 84(4), 72–83. https://doi.org/10.3917/leco.084.0072
- Boubtane, E., Dumont, J.-C., & Rault, C. (2016). Immigration and economic growth in the OECD countries 1986–2006. Oxford Economic Papers, 68(2), 340–360. https://doi.org/10.1093/oep/gpv024
- Bowman, M. J., & Myers, R. G. (1967). Schooling, experience, and gains and losses in human capital through migration. Journal of the American Statistical Association, 62(319), 875–898. https://doi.org/10.2307/2283723
- Co, C. Y., Gang, I. N., & Yun, M.-S. (2000). Returns to returning. Journal of Population Economics, 13, 57–79. https://doi.org/10.1007/s001480050121
- Duleep, H. O., & Regets, M. C. (1999). Immigrants and human-capital investment. American Economic Review, 89(2), 186–191. https://doi.org/10.1257/aer.89.2.186
- Engler, P., Giesing, Y., & Kraehnert, K. (2023). The macroeconomic effects of large immigration waves. IAB-Discussion Paper. https://doi.org/10.5167/uzh-239271
- Iara, A. (2006). Skill diffusion in temporary migration? Returns to Western European working experience in the EU accession countries (Development Studies Working Paper No. 210). Centro Studi Luca d’Agliano. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=921492
- Reinhold, S., & Thom, K. (2009). Temporary migration and skill upgrading: Evidence from Mexican migrants. University of Mannheim, unpublished manuscript.
- UNHCR. (n.d.). Operational Data Portal. https://data.unhcr.org/
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Three Years On – Ukrainians in Poland after Russia’s 2022 Invasion

The wave of Ukrainian refugees which followed the full-scale Russian invasion on February 24th, 2022, was in Poland met with unprecedented levels of support and solidarity. According to data from the Polish Household Budget Survey, 70 percent of households offered some help, and over 10 percent (1.3 million households) provided direct personal assistance. Overall, by early 2025, 1.9 million refugees had registered in the dedicated social security registry (PESEL-UKR system) and 1 million continue to be registered as residing in Poland. Drawing on other data sources we argue in this policy paper that the latter figure is highly overstated, giving rise to unjustified criticisms of low school enrolment among Ukrainian children, and low rates of labour market activity among adult refugees. We highlight the risks that these critical voices may become prominent in the ongoing campaign ahead of the Polish presidential elections. During the crucial months of prospective peace negotiations, when presidential candidates are appealing for voters’ support, we argue that the public debate in Poland concerning Ukraine and Ukrainian refugees, ought to be grounded in reliable evidence.
Introduction
The dramatic events of late February 2022 shook the populations across Ukraine, Europe and the world. The objective of the massive, full-scale Russian aggression was clear – to rapidly take over Kyiv, force Ukraine to surrender and take over full control of the country thus subjugating it into Kremlin’s rule. Three years later, while thousands of Ukrainian soldiers and civilians have lost their lives, and while Russia has imposed a massive economic and social burden on Ukraine, its key objective has badly failed and remains far from being realised. This thanks to the commitment of the Ukrainian government, the country’s army and the mobilisation of the Ukrainian population. In turn, the country’s resistance would not have been possible without substantial support from the outside, primarily from countries in the European Union and the U.S. International aid from governments to Ukraine between February 2022 and October 2024 amounted to over €230 billion (bn) with the largest part contributed by the US (€88 bn), the European Commission and European Council (€45 bn) and Germany (€16 bn). Proportional to 2021 GDP levels, the highest support came from Estonia (2.20 percent), Denmark (2.02 percent) and Lithuania (1.68 percent) (Kiel Institute, 2024). Support for Ukraine has come in many forms – military, material, financial, political and diplomatic. The international community has also imposed substantial economic and political sanctions against Russia, and has excluded it from many international forums, marginalising its voice in international discussions and meetings.
On top of that, Ukraine’s neighbours and many Western countries opened their borders and welcomed a massive wave of refugees escaping the immediate military invasion in the east and north of Ukraine, seeking safety from continued bomb and drone attacks on the entire country, and running away from the risk of a complete Russian take-over. It is estimated that up to 8 million Ukrainians left the country in the first months after the full-scale war started, initially moving mainly to Poland, Romania and Slovakia (Polish Economic Institute, 2022; UNCHR, 2022). At the same time the Russian aggression resulted in internal displacement of more than 3.6 million Ukrainians (IOM UN Migration, 2024). While many of the international and internal refugees have since returned, over 6.8 million Ukrainians still reside outside of Ukraine’s borders (UNCHR, 2025).
The wake of the war was met with an unprecedented wave of support among the Polish population (Duszczyk and Kaczmarczyk, 2022). We use data from one of the largest representative Polish surveys – the Household Budget Survey 2022 and 2023 – to show the degree of involvement among Polish households in direct and indirect support to Ukrainian refugees. We also show that declarative general sympathy towards Ukrainians reached over 50 percent in 2023 – twice as high compared to 16 years earlier. This support has by now fallen close to the levels from just before the full-scale war (40 percent). As the immediate need for help has become less urgent, and the refugees have organised their lives in Poland, the involvement of Polish households in supporting the Ukrainian population has also declined. At its peak at the beginning of the war the proportion of Polish households that were actively involved in helping the Ukrainian population reached nearly 70 percent, with over 10 percent (i.e. more than 1.3 million) of the households providing direct assistance to the refugees.
In this policy paper we call into question some of the official data on the number of Ukrainian refugees who continue to reside in Poland (almost 1 million) (EUROSTAT, 2025). We argue that inconsistency across different sources with regard to precise numbers – such as likely inflated refugee count in the official social security register – may be used to build unfavourable claims against the refugees and the Ukrainian cause overall, as arguments and narratives develop based on marginal anecdotal evidence and incorrect statistics. As the new U.S. administration tries – in its own way – to bring an end to the war, Ukraine will need continued strong support from all Western allies to end the war on favourable terms for Ukraine and to get significant additional help to rebuild the country. Ukraine’s safety and economic security will depend on Western military guarantees and closer integration with the EU. All of this requires the support of populations in these countries, which gets increasingly undermined by internal disputes and external political interferences.
As negotiations to end the war begin to take shape, Poland enters a crucial electoral campaign ahead of its May 2025 presidential elections. This combination is likely to place the Ukrainian question among the top issues on the local agenda. At the same time, there is a risk that the extent of support towards Ukraine and Ukrainian residents in Poland will be used in the battle for electoral votes. We argue that any debate around this topic should draw on reliable, up to date data sources. In this regard, the government should provide more information to clarify data inconsistencies, to shed more light on the situation among Ukrainian citizens currently residing in Poland, and to ensure that any doubtful narratives raised in the public debate are quickly addressed.
Ukrainian sovereignty, its peaceful development and prosperity are very much in the interest of both Poland and the rest of Europe. Therefore, the Polish government must provide arguments to reinvigorate the support for Ukraine among its population. This will be fundamental to ensure Ukraine’s military success and stability, to guarantee the mutual benefits of integration of the Ukrainian population in Poland, and for the future economic cooperation with Ukraine in the prospective enlarged European Union.
The Outbreak of the Full-Scale War: Ukrainians in Poland
In the first couple of months after the full-scale Russian invasion of Ukraine on February 24th 2022, over 2 million refugees fled to Poland through the common land border, with as many as 1.3 million people crossing the border during the first two weeks of the war (Figure 1a). The exact number of refugees who arrived in Poland is difficult to gauge as some people left Ukraine via the border with Romania or Slovakia and could have entered Poland across the uncontrolled borders of the Schengen area.
BOX 1. Ukrainian citizens in Poland before the war in 2022 Before February 24, 2022, the migration of Ukrainian citizens to Poland was regulated by existing legal mechanisms concerning all foreigners coming from non-EU countries (European Parliament, 2010). Migrants could apply for a temporary residence permit for a maximum of three years, most often in connection with prearranged employment or education (Sejm RP, 2013). Since 2017 Ukrainian citizens with biometric passports could travel to Poland and other EU countries without a visa, but their stay was limited to 90 days (European Parliament, 2017). Access to the Polish social transfer system for migrants and their families was strictly regulated and limited. Labor migrants and temporary visitors under the visa-free regime had no right to public benefits or healthcare (Sejm RP, 2003). |
At the time, application for refugee status was possible, but required undergoing a lengthy and burdensome asylum procedure. Those with refugee status granted had access to public transfers and healthcare (Sejm RP, 2003).
In accordance with the European regulations of Council Directive 2001/55/EC of 20 July 2001, the Polish government responded to the refugee crisis by establishing a special residence status for those fleeing the war. The regulations were introduced as early as March 12, 2022, and as a result, all Ukrainian refugees who arrived in Poland since 24 February could register themselves (and their family members) in a special social security registry, the so-called PESEL-UKR (Sejm RP, 2022). This registration immediately provided the refugees with an official status of temporary protection and legalized their stay in Poland until a specified date, which – as the war continued – has been regularly extended. In comparison to other, non-EU migrants, the PESEL-UKR status grants the refugees simplified access to the Polish labour market and gives them access to public healthcare and social transfers – including general support available to all legal residents, as well as special financial and non-monetary aid targeted specifically at refugees (Duszczyk and Kaczmarczyk, 2022). The registration process was streamlined and widely accessible in all municipality offices throughout Poland and resulted in rapid registration of the majority that had arrived to Poland since February 24, 2022. By the end of June 2022, 1.2 million individuals had registered for the PESEL-UKR status. The number grew to 1.4 million by October 2022 and continued to grow to 1.9 million registrations by January 2025. As evident from Figure 1b not all of those who crossed the Polish border (or arrived in Poland having left Ukraine through a different country) stayed in the country. Some continued their journey to other EU countries and beyond, while some decided to return to Ukraine. It is worth noting though that of all the registrations carried out by the end of 2024, nearly half happened in the first 8 weeks following the invasion.
Figure 1. Number of Ukrainian citizens crossing the border between Poland and Ukraine and registering for PESEL-UKR, 2021-2024

Note: Weekly data on crossings via all land borders with Ukraine.
Source: Open Data Portal (2025a, 2025b).
A notable and important legal change was introduced in October 2022, whereby individuals are automatically withdrawn from the PESEL-UKR registry after a period of 30 days when they (1) leave Poland, (2) apply for a residence permit, or (3) apply for international protection status (Sejm RP, 2022). This change is the reason for the substantial drop in the number of registered refugees at the end of 2022, with over 400 000 individual withdrawals (Figure 1b). This change in legislation was aimed at estimating more precisely the number of Ukrainian refugees currently residing in Poland. However, since withdrawals from the system require that departures from the territory of Poland are officially recorded at the border, or follow a parallel registration in another EU country, or are recorded as departures from the Schengen area through another country, the numbers in the system may still be far from the actual number of refugees currently residing in Poland.
Since late 2022 the number of registered Ukrainian refugees in Poland has been fairly stable at slightly below 1 million. Similarly, the shares of different age cohorts have not changed. In Figure 2 we show the split of those in the PESEL-UKR registry by age. Children under the age of 18 account for about 40 percent of all refugees, of which 30 percent are in schooling age (7-17). 7 percent of the refugees are aged 62 years or older. Among those aged 18-61 years old, 70 percent are women. It is worth noting that out of about half a million children recorded in the first 7 months, almost 400 000 are still registered in the PESEL-UKR registry, a number that has been stable since the end of 2022. As we show below, these values are significantly higher compared to the number of refugee children reported by two other administrative sources. This in turn casts doubt on the reliability of the estimates of the total number of Ukrainian refugees in Poland.
Figure 2. Ukrainian citizens registered with PESEL-UKR, by age group

Note: Based on registered year of birth, age as of 2025.
Source: Open Data Portal (2025b).
Where Are All the Registered Children?
To check the reliability of the PESEL-UKR registry data, we match the information from the registry with information from school registers provided by the Ministry of National Education, and the number of children benefitting from social transfers provided by the Social Insurance Institution (ZUS). As evident in Figure 3, the number of registered school-age children in the PESEL-UKR registry and the number of those who are officially registered in Polish schools significantly differ, and the difference seems stable over time. According to school records, most of the Ukrainian parents promptly enrolled their children in schools right after their arrival in Poland – about 120 000 pupils joined Polish schools as early as March 2022. The numbers grew in September 2024, which followed the introduction of obligatory schooling for all Ukrainian children aged between 7 and 17 (Sejm RP, 2024), with online classes in Ukraine permitted only for those in their final year. When we compare data for late 2024 and early 2025, we see that while about 270 000 children aged 7-17 were registered in the PESEL-UKR database, only 152 000 attended Polish schools – resulting in a very low enrolment rate of about 56 percent – raising legitimate concerns over the children’s academic and social development (see for example CEO, 2024).
Figure 3. Number of school-age children among Ukrainian refugees

Note: School registrations: all school types except preschool education, post-secondary schools, schools for adults and grades in which children are at least 18 years old. Ukrainian refugees only. Child benefit data points as reported in June, October and December.
Source: Open Data Portal (2025b, 2025c); information on 800+ benefit recipients: unpublished data from the Social Insurance Institution (ZUS).
As evident from Figure 3 though, from late 2023 all the way until early 2025, the ‘800+ benefit’ (which is a universal child benefit paid to all children aged 0-17) was paid to around 150 000 Ukrainian refugee children aged 7-17. Given the ease of claiming the benefit, and the relatively high value of the transfers (about 23 percent of net minimum wage per child per month), it seems very unlikely that so many families would opt out of the support. Looking at the close match between the numbers from ZUS and from the Ministry of Education, the more likely interpretation of the figures is not that children stay away from school and fail to claim social transfers, but rather that far fewer children continue to reside in Poland.
An additional argument supporting the inaccuracy of the PESEL-UKR data comes from a report published by the Narodowy Bank Polski (the Polish Central Bank) (NBP, 2024). Using information from a large survey conducted among Ukrainians living in Poland the report shows that 83 percent of school-age children in refugee families were enrolled in either a Polish or a Ukrainian school physically based in Poland. This is very far from the 56 percent rate calculated with reference to administrative data, again suggesting that the PESEL-UKR numbers of school-age children are highly inflated. If that is the case, not only the number of refugee children but the overall PESEL-UKR numbers (992 000 by January 2025) should be called into question.
How Many of the Registered Adults Are Active on the Labor Market?
The accuracy of the overall number of refugees is important because it is one of the key references for policy discussions. While international regulations specify that victims of war and conflict are granted the same basic rights and privileges as other legal residents, including access to the labour market, healthcare and other public services (Duszczyk et al., 2023), negative sentiments towards Ukrainian citizens have recently grown in Poland. Further, various restrictions on access to public support for Ukrainian refugees have already been publicly discussed and proposed in Parliament. These sentiments feed on the claims of fraudulent behaviour, unwillingness to engage in official employment and crowding out of public services for Polish nationals. Such claims about Ukrainians are spread more easily if not met by accurate numbers.
Figure 4. Number of Ukrainian men and women contributing to pension insurance in Poland

Note: ‘Other countries’ refers to other registered foreigners.
Source: Social Insurance Institution ZUS (2024).
Looking at labour market activity, the number of Ukrainians who were officially active on the Polish labour market (as employees, self-employed or receiving unemployment benefit) and who thus paid pension contributions to social security in December 2023 stood at 759 000 (see Figure 4). Of those 396 000 were men and 363 000 were women. While ZUS, the Social Insurance Institution, does not distinguish between migrants (those with the right to stay before February 24th, 2022) and refugees (with PESEL-UKR status) it seems safe to assume that those who registered in the ZUS database in 2022 and 2023 belong to the latter group. The difference between the number of Ukrainians contributing to social security in December 2021 and December 2023 is 132 000 and, as seen in Figure 4, the additional numbers of those registered differ only for Ukrainian women. New Ukrainian male refugees certainly also appear in the database in 2022 and 2023, but their number is difficult to estimate as some earlier migrants returned to Ukraine after the outbreak of the war, and as a result the net effect of men between 2021 and 2023 is essentially zero. Focusing on women, we can compare the number of new registrations in the ZUS database to the total number of women aged 18-59 (excluding students) in the PESEL-UKR database (about 335 000 in December 2023). Such a ratio would suggest that only about 40 percent of female Ukrainian refugees are formally contracted on the Polish labour market (on contracts paying social security contributions). This is much lower than the values presented in the NBP report (2024), suggesting that in July 2024, around 70 percent of the adult war refugees were working and further 19 percent were looking for a job. This comparison once again suggests that the PESEL-UKR numbers are significantly inflated.
Addressing the public concerns with regard to school enrolment and labour market activity with correct figures could help counter the growing negative sentiments towards Ukrainians in Poland as well as towards the overall support for the process of securing peace in Ukraine and integrating it closer with Poland and the EU. In the next section we show that when the full-scale war started in February 2022, not only the sentiments were strongly in favour of supporting Ukraine. Additionally, the level of engagement of the Polish population in actively assisting Ukrainian refugees was truly unprecedented.
Individual Support in Response to the Outbreak of the War
In the first few weeks after the full-scale Russian invasion the Polish society almost uniformly united in providing help and assistance to Ukrainians affected by the war. The Polish Economic Institute estimated that during the first 3 months the financial, humanitarian and material help provided by the Polish society alone reached 9-10 billion PLN, which corresponded to 0.34-0.38 percent of Poland’s GDP (Baszczak et al. 2022). Polish private businesses were also quick to join the assistance efforts, donating money, food, medical and other specialized equipment, and providing services such as transportation, insurance, and education free of charge (WEI 2023). Until May 2022, 53 percent of Polish enterprises engaged in different kinds of relief or support.
The assistance to refugees has been documented in numerous anecdotes, formal reports and extensive media coverage. The scale of support is also reflected in the Polish Household Budget Survey, a regular household survey conducted by the Central Statistical Office. Already in the first quarter of 2022 the survey included several questions related to the assistance given by the interviewed households to Ukrainian refugees. These questions were then included in the survey throughout 2022 and 2023. As shown in Figure 5, when the inflow of refugees from Ukraine started in late February 2022, nearly 70 percent of Polish households offered some form of assistance. Most of this help took the form of gifts and money transfers, but 10.4 percent, i.e. over 1.3 million Polish households, offered direct help such as transport, providing an overnight stay, delivering goods to accommodation venues, etc. The fraction of those offering assistance stayed very high through the first half of 2022, and 23 percent of Polish households still provided some form of assistance in the last quarter of 2022 (Figure 5). As the war stalled, and the Ukrainian population settled and became more independent, and the Polish government took official responsibility of assisting those still in need, the level of direct support from households fell. However, in late 2023 9 percent of Polish households still continued to provide some form of assistance. What is really special about the initial wave of support is that the positive attitudes towards the refugees and the Ukrainian cause were nearly universal. As seen in Figure 6, assistance was offered by high and low educated households (79 and 59 percent), those living in large cities and in rural areas (73 and 68 percent), the young and the old (66 and 63 percent). Households who declared good material conditions were more likely to offer help (75 percent), but even among those who declared difficulties with their financial status 41 percent came forward to offer some assistance.
Figure 5. Polish households engaged in assisting Ukrainian refugees, 2022-2023 (by quarter)

Note: Help covers support and transfers to individuals and institutions in Ukraine as well as to Ukrainian refugees in Poland. “Personal assistance” – direct help to refugees (with job search, doctor’s visits, public matters, language lessons, translation, etc.), “Other help” – help at the border, in reception points, temporary accommodation points, gift collection points, transportation, hosting or subletting own housing free of charge, blood donation.
Source: own compilation based on the Polish Household Budget Surveys 2022-2023.
Figure 6. Polish households engaged in assisting Ukrainian refugees (any help) in the first quarter of 2022, by household characteristics

Notes: Urban status – A: rural area, B: city below 100 000 inhabitants, C: city over 100 000 inhabitants. Material situation (self-assessed) – D: bad or rather bad material situation, E: average material situation, F: good or rather good material situation. Age of head of household – G: 18-29, H: 30-59, I: 60 and older. Education of head of household – J: lower than secondary, K: secondary or postsecondary, L: tertiary. Source: own compilation based on the Polish Household Budget Survey 2022.
It is worth noting also that by the time the full-scale war broke out in February 2022 the sentiments among the Polish population towards Ukrainians had improved compared to attitudes in the 1990s and early 2000s. These sentiments have been regularly surveyed by the Public Opinion Research Center CBOS, and we summarize them in Figure 7. As evident, in the early 1990s the proportion of Poles declaring positive sentiments towards Ukrainians was very low. It steadily increased until about 2017 and then grew rapidly from 2018 till 2020. In 2022 the sentiments towards Ukrainians reached their peak, with over 50 percent of Poles declaring fondness towards them – on par with nations such as Lithuania and Slovakia. At the same time positive attitudes towards Russians reached an all-time low of 6 percent. Positive sentiments towards Ukrainians declined in 2024 – the last year for which the data is available – but even after the drop they are still high when compared with attitudes before 2023.
While the general positive sentiments towards Ukrainians in Poland has improved over the years, 2022 was truly unique when it comes to attitudes toward Ukrainian refugees (see Figure 8). Between 2015 and 2018, i.e. after Russia’s annexation of Crimea in 2014, around 50-60 percent of Poles declared that refugees from the conflict areas in Ukraine should be welcomed in Poland. When the same question was asked again in March 2022, 95 percent agreed that Ukrainian refugees should be welcomed in Poland and nearly 60 percent declared that they ‘definitely’ agreed with such a policy. However, the proportion of Poles in support of welcoming Ukrainian refugees has decreased. In late 2024 the share was more or less back at the level prior to the full-scale war, i.e. at over 50 percent.
Figure 7. Share of survey participants declaring fondness towards foreigners of different origin

Source: The Public Opinion Research Center CBOS (2024a).
Figure 8. Opinion survey: If Poland should accept Ukrainian refugees coming from the conflict territories

Note: The surveys were discontinued between 2018 and 2022.
Source: Public Opinion Research Center CBOS (2024b).
Why Have Sentiments Shifted?
At the crucial time of a possible long-awaited end to the Russian invasion, when coordinated support of Western governments will be essential to secure a just and long-lasting solution, the willingness of these governments to firmly stand behind Ukraine will, to a large extent, depend on the sentiments among their voters. Thus, the wavering enthusiasm for the Ukrainian cause in countries such as Poland can be seen as a worrying sign, in particular given how high the level of support was in the early days of the invasion. This support will be particularly important over the next few months, given the likely period of intensive international negotiations and the battle for votes in the upcoming Polish presidential elections.
It is not unusual to try to put the blame for various unfortunate developments on external forces, including global trends, external conflicts and all things ‘foreign’. Thus, the fact that many people in various countries, including Poland, blame their perceived worsened economic conditions on the consequences of the war and the related influx of Ukrainian refugees is far from surprising. While some politicians might want to explain the complex broad context, others will take advantage of these sentiments and continue to fuel the negative discourse. With that in mind, three main topics have been particularly visible in the public debate in Poland:
- access to social transfers, in particular to the ‘800+’ child benefit for Ukrainian refugees
- Ukrainian refugees’ participation in the Polish labour market and tax contributions to the local budget
- risks to particular groups of interest, most prominently reflected in Poland by the crisis surrounding imported Ukrainian grain (see Box 2)
The first two issues are strongly related to the general approach to immigration and integration of migrants in the Polish society. The popular media discourse – in traditional and social media – tends to focus on instances of abuse of social support and public services, and to build up negative sentiments along the lines of supposed unwillingness to engage in legal economic activity among those who have settled in Poland. While one can certainly identify anecdotes which selectively confirm all sorts of misbehaviour, the overall evidence would clearly reject such claims. As discussed, the surveys conducted by the NBP show that a significant majority of migrants and refugees from Ukraine find legal employment in Poland. Further research based on administrative data demonstrates that many Ukrainians establish and successfully run their businesses in Poland (Polish Economic Institute, 2024). Between January 2022 and June 2024 Ukrainian migrants and refugees established almost 60 000 enterprises in Poland, and as Vézina et al. (2025) argue, these firms did not crowd out Polish businesses, meaning they represent a true value added to the national and local economies.
Recent public discussions, however, have focused on the combination of employment and benefit claims. The debate started with two parliamentary initiatives by the right wing Konfederacja and Prawo i Sprawiedliwość opposition parties and was then picked up by the leading government party’s presidential candidate, Rafał Trzaskowski (money.pl, 2025). The proposed legislative changes are broadly similar, suggesting that access to the main child benefits – the ‘800+ benefit’ – should be limited to those refugee families where at least one of the parents is formally employed. Such conditionality does not apply to Polish families, and according to current legislation, to no other families legally residing in Poland (Konfederacja, 2025; Prawo i Sprawiedliwość, 2025). The supposed aim of the changes would be to, first of all, limit fraudulent claims among those who no longer reside in Poland, and secondly, to restrict access to the benefits to those who contribute with their taxes to the public budget only. On both counts the policy seems badly misconceived. As shown above, the ‘800+’ claims closely match the numbers of children officially registered in Polish schools, far below the numbers registered in the PESEL-UKR database. Moreover, such a policy is unlikely to lead to much higher employment among refugee parents. The benefit is universal and received by all families regardless of employment status or income; previous research has shown a similar benefit to have negligible effects on employment (see for example: Myck and Trzcinski, 2019). Therefore, the most likely reason for some refugee parents to not take up work is not unwillingness, but rather other constraints – constraints which will not change as a result of the proposed restrictions. Most Ukrainian families who fled the war are mothers whose partners could not join them due to military restrictions on the mobility of Ukrainian men. While many women settled and found jobs, family obligations may significantly limit some refugee’s options for regular employment. For these families, withdrawing the eligibility for the ‘800+ benefit’ would be a significant loss of income with potentially dire consequences for their children. It is thus difficult to understand the initiatives as anything other than attempts to address the growing critical sentiments towards the refugees to gain support among voters who are convinced by the anecdotal narrative. As argued above – with the exception of anecdotes – there is very little evidence in support of such legislative changes. Even from the point of view of potential budgetary gains, the proposed limitations on benefit claims would impose heavy administrative costs which would likely exceed any resulting savings. The politicians coming forward with such proposals would be well advised to consider data from various sources and avoid raising issues which have a clear potential to fuel negative sentiments towards refugees and migrants.
BOX 2. The dispute over the Ukrainian grain In February 2022, Russia’s full-scale invasion destabilized the Ukrainian market, in particular the agricultural sector, due to blocked exports through the Black Sea. To enable exports, so-called Solidarity Lanes were established, including corridors crossing Poland (European Commission 2022). However, Poland was not prepared to handle and re-export large volumes of Ukrainian agricultural products, due to insufficient capacity of Polish sea ports (farmer.pl, 2023; for such quantities experts argue that road transport is unprofitable; Kupczak, 2023). This led to a surplus of grain in multiple storehouses throughout the country, especially in Southeastern Poland. Overall, Polish grain stocks increased by over 250 percent, from 3.8 to almost 10 million tones (Supreme Audit Office, 2023). The drastic surplus of grain, together with much lower prices for Ukrainian crops, led to a dramatic price drop—one could buy mixed Polish-Ukrainian grain for half the price it cost the previous year (rp.pl, 2023). Apart from its impact on quantity and price, Ukrainian grain drew public attention also due to concerns regarding its quality (money.pl, 2023). Imported agricultural and food articles must undergo rigorous quality controls at the border, depending on their purpose – human consumption, animal fodder or cultivation, conducted by the respective state inspection office. Random controls held in 2022 by the Food Articles Inspection revealed that 2.4 percent of the grain samples were banned from entering the market (rp.pl, 2023). According to a report by the Supreme Audit Office (2023), controls run by the Veterinarian Inspection were drastically limited as of May 2022 which allowed poor quality fodder grain to enter the Polish market (Supreme Audit Office 2023). Since technical grain – used in the production of biofuels, insulating materials or oils – is exempt from border quality controls, its imports and sale as consumable grain could be particularly profitable. Several incidents of such forgery were subject to investigation confirming that large quantities of technical grain originating from Ukraine were sold as consumable to Polish companies (gov.pl, 2024). The tightened border controls that followed, resulted in multiday delays in the transportation of food products from Ukraine. To mitigate these constraints an agreement was reached, and, as of March 8, 2023, grain transit through Poland to other final destinations (within EU or to a third country via Polish ports) is exempt from border controls at the Polish-Ukrainian border and sealed by the National Revenue Administration. These seals can be removed only at the final destination (gov.pl, 2023a). Throughout this period Polish farmers held demonstrations opposing the influx of Ukrainian grain. The border crossings with Ukraine were temporarily blocked by protests aimed at disrupting the flow of goods. The symbolic dumping of Ukrainian grain on the ground at the Medyka border crossing resulted in a famously cited statement by the Ukrainian President Volodymyr Zelensky that this event may be seen as evidence of the “erosion of solidarity” with Ukraine (BBC, 2024). After the EU-level temporary embargo on four types of grains and oil seeds from Ukraine was lifted in mid-September 2023 (which was in effect since May 2023), Ukraine agreed to introduce export measures to avoid grain surges (European Commission, 2023). Nevertheless, Poland administered a unilateral ban on selected products and their derivatives (gov.pl, 2023b), which led Ukraine to file a complaint with the World Trade Organization (WTO, 2023). While the ban still applies (gov.pl, 2025), the Polish government has on multiple occasions actively sought to convince the EU to include wheat (and other grains) among the crops covered by the quotas under the EU-level 2022 regulation on temporary trade liberalization with Ukraine (the Autonomous Trade Measures Regulation; OKOpress, 2024; European Commission, 2024). |
Conclusions
Considering the current approach by the U.S. administration under President Donald Trump, Ukraine’s position in the prospective negotiations will strongly depend on the support it can gather from its European allies. This in turn is likely to reflect the sentiments towards the Ukrainian cause among European voters. In Poland, where critically important presidential elections are scheduled for May 2025, the importance of these sentiments might be particularly salient. On the one hand, the candidates are likely to voice support for Ukraine to secure peace and stability in the region. On the other hand, they may appeal for support among voters who are critical of the generous approach of Polish public institutions towards Ukrainian refugees.
As shown in this policy paper, the critical voices highlighting instances of abuse of privileges granted to refugees are largely unfounded, and much of the critical discourse is linked to – in our view – highly inaccurate numbers of officially registered refugees with the PESEL-UKR status system. The government would do a service to the quality of the debate about Ukrainian refugees in Poland, and at the same time defuse some of the critical claims, by verifying the PESEL-UKR database.
Using administrative data on school enrolment and benefit claims we show that these match almost perfectly, with around 150 000 children aged 7-17 in both registries in late 2024. This is far less than the 270 000 children in this age group registered in the PESEL-UKR database and assumed to be residing in Poland. Similarly, survey data suggests that about 70 percent of Ukrainian refugees are active on the Polish labour market. This proportion is much lower when official data based on social security contributions is compared to the total number of adult refugees in the PESEL-UKR registry. The comparison once again suggests that the figures in the latter database are significantly overstated. It is thus very unlikely that the number of Ukrainian refugees in Poland is as high as the numbers officially reported in the registry (992 000 in January 2025).
The accuracy of the numbers is important for several reasons, and the ability to address various critical claims in the public debate is only one of them. At the time of an electoral campaign ahead of a highly significant presidential election, this reason, however, may prove fundamental to avoid further polarization of the debate about continued support for Ukrainian refugees in Poland. It is also crucial for securing strong support for Ukraine by the Polish government in the coming challenging months of peace negotiations. While it is likely impossible to restore the level of positive attitudes toward Ukrainian citizens seen in Poland in February and March 2022, that degree of solidarity should serve as a foundation for a deepened relationship between the two countries.
Acknowledgement
The authors acknowledge the support from the Swedish International Development Cooperation Agency, Sida. We are grateful to Patryk Markowski for helpful research assistance. The Polish Household Budget Survey data (2022, 2023) used in the analysis was provided by Statistics Poland (Główny Urząd Statystyczny). We are grateful to the Social Insurance Institution ZUS (Zakład Ubezpieczeń Społecznych) for providing us with unpublished data on child benefit recipients.
References
- Baszczak, Ł., Kiełczewska, A., Kukołowicz, P., Wincewicz, A., & Zyzik, R. (2022). Pomoc polskiego społeczeństwa dla uchodźców z Ukrainy. Polish Economic Institute. https://pie.net.pl/wp-content/uploads/2022/07/Pomoc-pol-spol-UKR-22.07.2022-D-1.pdf
- BBC. (2024). Polish farmers block Ukraine border in grain row. BBC News. https://www.bbc.com/news/world-europe-68337795
- CEO Center for Citizenship Education. (2024). Students from Ukraine with refugee experience in Polish schools: What changed in the school year 2024/2025? https://ceo.org.pl/uczniowie-z-ukrainy-w-polskich-szkolach-nowy-raport/
- Duszczyk, M., Górny, A., Kaczmarczyk, P., & Kubisiak, A. (2023). War refugees from Ukraine in Poland – one year after the Russian aggression: Socioeconomic consequences and challenges. Regional Science Policy & Practice, 15(1), 181-200. https://doi.org/10.1111/rsp3.12642
- Duszczyk, M., & Kaczmarczyk, P. (2022). Poland and war refugees from Ukraine – Beyond pure aid. CESifo Forum, 23(4), 26-33. https://www.cesifo.org/DocDL/CESifo-Forum-2022-4-duszczyk-kaczmarczyk-ukrainian-refugee-crisis-july.pdf
- Duszczyk, M., & Kaczmarczyk, P. (2022). The war in Ukraine and migration to Poland: Outlook and challenges. Intereconomics, 57(3), 164-170. https://www.intereconomics.eu/contents/year/2022/number/3/article/the-war-in-ukraine-and-migration-to-poland-outlook-and-challenges.html
- European Commission. (2022). EU-Ukraine solidarity lanes. https://commission.europa.eu/topics/eu-solidarity-ukraine/eu-assistance-ukraine/eu-ukraine-solidarity-lanes_en
- European Commission. (2023). Following the expiry of the restrictive measures on Ukrainian exports of grain. https://enlargement.ec.europa.eu/news/following-expiry-restrictive-measures-ukrainian-exports-grain-ukraine-agrees-introduce-measures-2023-09-15_en
- European Commission. (2024). EU trade relations with Ukraine. https://policy.trade.ec.europa.eu/eu-trade-relationships-country-and-region/countries-and-regions/ukraine_en
- European Parliament. (2001). Council Directive 2001/55/EC of 20 July 2001 on minimum standards for giving temporary protection. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32001L0055
- European Parliament. (2010). Regulation (EU) No 1231/2010 extending Regulation (EC) No 883/2004 and Regulation (EC) No 987/2009. https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:344:0001:0003:EN:PDF
- European Parliament. (2017). Regulation (EU) 2017/850 amending Regulation (EC) No 539/2001 on visa requirements (Ukraine). https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32017R0850&from=EN
- EUROSTAT. (2025). Temporary protection for persons fleeing Ukraine – monthly statistics. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Temporary_protection_for_persons_fleeing_Ukraine_-_monthly_statistics
- farmer.pl (2022). Import zboża z Ukrainy. Co ze zbożem technicznym?. https://www.farmer.pl/produkcja-roslinna/zboza/import-zboza-z-ukrainy-co-ze-zbozem-technicznym-ruszyly-dodatkowe-kontrole-aktualizacja,126026.html
- farmer.pl (2023). Przepustowość polskich portów ogranicza możliwości opróżnienia silosów. https://www.farmer.pl/produkcja-roslinna/zboza/przepustowosc-polskich-portow-ogranicza-mozliwosci-oproznienia-silosow,131743.html
- gov.pl (2023a). Tranzyt zbóż z Ukrainy – ważne ustalenia ministrów Polski i Ukrainy. https://www.gov.pl/web/rolnictwo/tranzyt-zboz-z-ukrainy–wazne-ustalenia-ministrow-polski-i-ukrainy
- gov.pl (2023b). Rozporządzenie na temat zakazu przywozu z Ukrainy produktów rolnych. https://www.gov.pl/web/kas/rozporzadzenie-na-temat-zakazu-przywozu-z-ukrainy-produktow-rolnych
- gov.pl (2024). Rekordowa kara za oszustwa związane z importem produktów rolnych z Ukrainy. https://www.gov.pl/web/ijhars/rekordowa-kara-za-oszustwa-zwiazane-z-importem-produktow-rolnych-z-ukrainy
- gov.pl (2025). Relacje handlowe z Ukrainą. https://www.gov.pl/attachment/1f3a8fed-3556-42ed-b4dc-98960a498744
- IOMM UN Migration. (2024). https://dtm.iom.int/ukraine
- Kiel Institute. (2024). Ukraine Support Tracker. https://www.ifw-kiel.de/publications/ukraine-support-tracker-data-20758/
- Konfederacja. (2025). Projekt ustawy o zmianie ustawy o pomocy obywatelom Ukrainy. https://orka.sejm.gov.pl/Druki10ka.nsf/Projekty/10-RPW-2793-2025/$file/10-RPW-2793-2025.pdf
- money.pl (2023). Zboże techniczne w mące?. https://www.money.pl/gospodarka/zboze-techniczne-w-mace-takie-ziarna-nadaja-sie-do-spalenia-w-piecu-6887330302552992a.html
- money.pl (2025). https://www.money.pl/gospodarka/800-plus-dla-pracujacych-ukraincow-trzaskowski-ma-pomysl-rzad-ma-problem-7119211731655488a.html
- Myck, M., K. Trzciński (2019) From Partial to Full Universality: The Family 500+ Programme in Poland and its Labor Supply Implications, ifo DICE Report, 17(03), 36-44.
- Narodowy Bank Polski. (2024). Sytuacja życiowa i ekonomiczna migrantów z Ukrainy w Polsce w 2024 r.
- OKOpress. (2024). Zboże z Ukrainy demoluje polski rynek?
https://oko.press/czy-zboze-z-ukrainy-psuje-rynek-w-polsce - Open Data Portal (2025a). Daily statistics from the Polish Border Guard Headquarters. https://dane.gov.pl/pl/dataset/3595,bazy-ruchu-granicznego-straz-graniczna
- Open Data Portal (2025b). Statistics from the Ministry of Digital Affairs of Poland. https://dane.gov.pl/pl/dataset/2715,zarejestrowane-wnioski-o-nadanie-statusu-ukr
- Open Data Portal (2025c). Statistics from the Ministry of National Education of Poland. https://dane.gov.pl/pl/dataset/2711,uczniowie-uchodzcy-z-ukrainy
- pap.pl (2025). Kwestie historyczne to papierek lakmusowy pokazujący stan relacji polsko-ukraińskich. https://www.pap.pl/aktualnosci/ekspertka-kwestie-historyczne-papierek-lakmusowy-pokazujacy-stan-relacji-polsko
- Polish Economic Institute. (2022). Pomoc polskiego społeczeństwa dla uchodźców z Ukrainy. https://pie.net.pl/wp-content/uploads/2022/07/Pomoc-pol-spol-UKR-22.07.2022-D-1.pdf
- Polish Economic Institute. (2024). Tygodnik Gospodarczy PIE 1 sierpnia 2024 r., 31/2024. https://pie.net.pl/wp-content/uploads/2024/08/Tygodnik-PIE_31-2024.pdf
- Prawo i Sprawiedliwość. (2025). Projekt ustawy o zmianie ustawy o pomocy obywatelom Ukrainy. https://orka.sejm.gov.pl/Druki10ka.nsf/Projekty/10-RPW-1978-2025/$file/10-RPW-1978-2025.pdf
- Public Opinion Research Center CBOS. (2024a). Attitude towards other nationalities. https://www.cbos.pl/SPISKOM.POL/2024/K_025_24.PDF
- Public Opinion Research Center CBOS (2024b). Ukrainians in Poland and the war in Ukraine. https://www.cbos.pl/SPISKOM.POL/2024/K_099_24.PDF
- Rp.pl (2023). Dlaczego zboże z Ukrainy zostało w Polsce?. https://www.rp.pl/polityka/art38318551-dlaczego-zboze-z-ukrainy-zostalo-w-polsce-suski-wina-putina
- Sejm RP. (2003). Ustawa z dnia 28 listopada 2003 r. o świadczeniach rodzinnych. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20032282255/U/D20032255Lj.pdf
- Sejm RP. (2003). Ustawa z dnia 13 czerwca 2003 r. o udzielaniu cudzoziemcom ochrony na terytorium RP. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20031281176/U/D20031176Lj.pdf
- Sejm RP. (2013). Ustawa z dnia 12 grudnia 2013 r. o cudzoziemcach. https://www.asylumlawdatabase.eu/sites/default/files/aldfiles/EN%20-%20Poland%20act_on_foreigners_en_0.pdf
- Sejm RP. (2022). Law of 12 March 2022 on assistance to citizens of Ukraine. https://isap.sejm.gov.pl/isap.nsf/DocDetails.xsp?id=WDU20220000583
- Sejm RP. (2024). Act of 15 May 2024 Amending the Act on Assistance to Citizens of Ukraine. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20240000854/O/D20240854.pdf
- Supreme Audit Office. (2023). Działania organów państwa w zakresie importu i obrotu zboża. https://www.nik.gov.pl/kontrole/D/23/506/
- UNCHR. (2022). https://web.archive.org/web/20220410070535/http://data2.unhcr.org/en/situations/ukraine
- UNCHR. (2025). https://www.unhcr.org/emergencies/ukraine-emergency
- Vézina, P.-L., Aksoy, C. G., & Lewandowski, P. (2025). Refugees and entrepreneurship: Evidence from Ukrainians in Poland. Unpublished draft.
- Warsaw Enterprise Institute. (2023). Kompendium polskiej pomocy dla Ukrainy. https://wei.org.pl/wp-content/uploads/2023/11/Kompendium-PL.pdf
- WTO World Trade Organisation. (2023). Ukraine initiates WTO dispute complaints. https://www.wto.org/english/news_e/news23_e/ds619_620_621rfc_21sep23_e.htm
- ZUS Social Insurance Institution (2024). Cudzoziemcy w polskim systemie ubezpieczeń społecznych 2019-2024. https://www.zus.pl/baza-wiedzy/statystyka/opracowania-tematyczne/cudzoziemcy
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Christmas Time in Poland Through the Lens of Gender Equality

In the Christmas season, we examine how people in Poland allocate their precious minutes in the days before and during the holidays. We use data from the Polish Time Use Survey and show that, in several aspects of time use, Christmas is indeed special, and that there are notable differences in how men and women allocate their time to work and pleasure. Women spend more time than men on household chores and preparing meals, and in the latter case the imbalance is particularly striking: on average women spend two hours more per day cooking ahead of the holidays.
Introduction
Every year, billions of people around the world spend the end of December enjoying time with friends and family. Many celebrate Christmas on the 25th and 26th, while others bid farewell to 2024 and welcome a new year. Celebrations and fun are often preceded or combined with intensive preparations—cooking, cleaning, shopping, and travel. Time is of the essence, and as with other major celebrations, the 2024 Christmas season is likely to feel too short, intensive, and possibly stressful.
In this policy brief we look at how people in Poland allocate their precious minutes during these special days. Every ten years the Polish Central Statistical Office collects detailed data on time use, interviewing over 35 000 individuals, most of whom fill in diaries of their time allocation over two different days. This results in over 70 000 diaries with information divided into 144 ten-minute intervals. We use the latest available survey wave from 2013 in which we have information from 72 967 correctly completed diaries, on average almost two hundred diaries per day (the 2023 data is not yet available for research purposes). Particularly interesting is that the data collection in 2013 was carried out in the days running up to Christmas and continued through the 2013 holiday season. This gives us a unique chance to examine the allocation of time over this period, and specifically compare how men and women spend their time in preparation for celebrations, and during the holidays. We compare Christmas time allocation to diaries filled in on weekdays and Sundays in November to show, on the one hand, that the way people in Poland spend their holidays differ in several ways from a regular Sunday, and that allocation of time is particularly unique in the days running up to Christmas. This relates both to how much time is spent on getting ready – preparing meals, cleaning the house, etc., as well as to how these chores are allocated between men and women.
Time Use Diaries in Poland
Polish time use data is unique in its scope and content. During the year of data collection over 35 000 participants complete detailed time use diaries on two days – one weekday and one weekend day. Every ten-minute slot is assigned a category for the ‘main activity,’ with the option to record a ‘secondary activity’ for multitasking. The 163 detailed categories range from broad types like “sleeping” or “time devoted to main job” to specific activities such as “repairing household equipment” or “handcrafts”. The large number of diaries and narrow activity focus enables unique analyses of time use and allows studying specific days (for an example, see Adena et al., 2023).
In 2013 the diaries cover 355 days and on these ‘active’ days the number of completed diaries varied from 116 (on 6th November) to 562 (6th January). The diaries were completed also on the 24th and 23rd of December respectively, (239 diaries) and on both days of Christmas (25th and 26th of December, 250 diaries). These special four days – which happened to start on a Monday – are compared to four November weekdays, the consequent days starting on Monday the 25th of November (549 diaries), and two November Sundays (17th and 24th of November, 737 diaries).
Is Christmas Time Different?
The 163 different categories of time use are aggregated into 10 groups: (1) preparing meals, (2) household work and cleaning, (3) meals, meetings and celebrations, (4) church and prayer, (5) watching TV, using computer, (6) walks, games and hobbies, (7) shopping, (8) work and study, (9) personal care, (10) sleeping.
These broad categories include activities which are similar and/or related to the broad headings. For example, ‘household work and cleaning’ includes vehicle maintenance or cleaning the basement, while ‘meals, meetings and celebrations’ include also ‘phone calls with family and friends’ or ‘reading, playing and talking with children’. The broad activity categories were identified by examining the most common activities given the time allocated by respondents to the listed activities in November and December. Other less common activities were then added to those main categories. The average number of minutes allocated to the ten categories in the weekdays and Sundays of November, the two days before Christmas, and the Christmas holidays is presented in Table 1.
Table 1. Time Allocation: average number of minutes per day allocated to ten aggregate activity categories

Notes: ‘November weekdays’: 25th-28th November 2013; November Sundays: 17th and 24th of November 2013. Numbers represent unconditional averages.
Source: Own calculations using the Polish Time Use Survey 2013.
As evident there are interesting differences in the pattern of time allocation between the four groups of days which seem to be a result of discernible differences in behaviour. On ‘usual weekdays’ in late November respondents spend on average about 70 minutes on meal preparations and almost 90 minutes on housework. This increases significantly on the 23rd and 24th of December, respectively, to nearly three hours (169 minutes) and over two hours (125 minutes). As expected this then drops substantially over the two days of Christmas. In terms of housework and cooking, Christmas days differ slightly from a typical Sunday. However, even on these days, cooking and household tasks do not come to a complete halt: there is still work to be done! It is clear, though, that the brunt of the preparation is conducted in the days leading up to Christmas. It should be noted also that in Polish tradition the main Christmas celebration usually takes place in the evening of the 24th, although preparations often run all the way up to that evening meal. We can observe for example that the average working time on 23rd-24th December is much lower compared to late November and the time spent on attending mass or prayer is already significantly higher. The preparations on those two days seem to ‘eat in’ to the amount of sleep and time spent in front of the TV. We see more time devoted to meals and celebrations compared to normal weekdays in November, although the values listed are averages over the two days including the 23rd.
The average allocation of time on the two days of Christmas stands out in a few categories. In particular more time is allocated to pleasure: ‘walks, games and hobbies’ take up 171 minutes per day on average over the Christmas holidays, which is over an hour more compared to a normal Sunday. Watching TV is another favourite Christmas pass-time (191 minutes), although people seem to watch slightly less TV on Christmas compared to November Sundays. While meals and celebrations take up more than four hours per day on average, this is only slightly longer than on a normal Sunday (263 vs 247 minutes), and Christmas sleeping patterns are also very similar compared to Sundays – with little catching up on sleep lost in the lead-up to the holidays.
Work and Pleasure over Christmas – Gender Differences in Time Allocation
In Figure 1 we present the average allocation of time in Poland in the run up to Christmas and over the two holidays separately for men and women. The figure depicts the ten aggregated categories, and for each set of days the outer ring represents the average time allocation among women, while the inner ring shows the average time allocation among men. We see some striking differences. Women spend almost 3.5 hours on average on cooking on each of the two days before Christmas, which is nearly 1.5 hours more compared to men. The difference in household work is not as striking, and men tend to spend more time on pre-Christmas shopping (35 vs 26 minutes per day on average). Men also spend more time at work during these two days (189 vs 110 minutes), although much of the time which is not spent on cooking seems to go to leisure: on average men watch more TV and spend more time eating and socializing.
Work and leisure are also unequally divided between men and women on the two days of Christmas. Women spend more than 2 hours per day on average on cooking and cleaning, while men spend only about 50 minutes per day. Over Christmas men spend more time in front of the TV, but they also devote more time to paid work, with an average of about 100 minutes per day. Celebrations and meals over the Christmas season naturally take up much of the time, and in this case the disproportions are not as large, though both in the run up and during Christmas men tend to spend slightly more time ‘at the table’ than women. The difference is more pronounced for the days running up to Christmas (23-24th December) which is noteworthy, given that the evening on the 24th is traditionally the main family celebration time in Poland.
Figure 1. Christmas time allocation among women (outer rings) and men (inner rings)

Notes: A: preparing meals; B: household work and cleaning; C: meals, meetings and celebrations; D: church and prayer; E: watching TV, using computer; F: walks, games and hobbies; G: shopping; H: work and study; I: personal care; J: sleeping. The rings represent a full 24-hour day with all reported activities collected into ten aggregate activity categories. The values are averages for the samples interviewed on 23rd and 24th of December 2013 (Figure 1a) and on the two days of Christmas (25th and 26th of December 2013). Source: Own calculations based on the Polish Time Use Survey 2013.
Is Christmas Time Special? The Gender Perspective
In this section we examine the data in a more formal way by adjusting the patterns of time use of men and women for differences in age, education and household size. We focus on six out of the ten categories distinguished above and regress time (in minutes) within these categories separately for the four sets of days detailed in Table 1: weekdays in November (25th-28th), Sundays in November (17th and 24th), as well as for 23rd-24th December and 25-26th December. The estimates of the coefficient on the female indicator included in these regressions reflect how much more or how much less time women spend on a specific activity category compared to men, conditional on the controls.
Figure 2. Women vs men: differences in time allocation in November and over Christmas

Notes: The bars represent coefficients on the female dummy estimated in linear regressions of time spent on a specific activity in a specific set of days. Control variables include age, education and household size. The specific days are;
‘November: weekdays’: 25th-28th November 2013; ‘November: Sundays’: 17th and 24th of November 2013.
Source: Own calculations using the Polish Time Use Survey 2013.
In Figure 2 we present the results for the six time-use categories, in each case showing the estimated coefficient on the female indicator for the four sets of days. Since the samples are quite small (see Table 1), the standard errors of the estimates are relatively large. However, they still allow us to infer interesting patters of time use differences between men and women. The most visible difference concerns the time allocated to preparing meals in the run up to Christmas. While women spend more time preparing meals in all four-day categories, the days just before Christmas are clearly special (Figure 2a). On average on the 23rd-24th of December, women spend almost two hours longer on this activity per day compared to men, while on a ‘normal’ Sunday or weekdays this difference is ‘only’ 51 and 61 minutes, respectively. Interestingly, women continue spending more time than men on meals preparation also over the holidays, although the extra minutes in this case resemble a usual Sunday. The latter similarity seems to be repeated in the estimates related to ‘household work and cleaning’ (Figure 2b) – women once again spend more time doing chores: 18 minutes more than men on a normal Sunday and 21 minutes more over Christmas. In this category we do not see any statistically significant imbalances during the days leading up to Christmas (the point estimate however suggests that also on those days women ’out-perform’ men by about 15 minutes per day). On the other hand, while (except for November Sundays) the differences are not statistically significant, women seem to spend more time on ‘walks, games and hobbies’ compared to men and the difference is highest over the Christmas holidays (35 minutes per day, see Figure 2c). Since the day is 24 hour long for everyone, we should see some differences going the other direction – activities where women spend less time compared to men. Once again we see some striking patterns in the days running up to Christmas with women spending much less time compared to men on ‘meals, meetings and celebrations’ (60 minutes, see Figure 2d) as well as on ‘work and study’ (80 minutes, see Figure 2f).
With all the work that seems to be going into preparing meals and other housework, it is perhaps good to see that at least on the 25th and 26th of December women spend as much time as men on Christmas celebrations (Figure 2d). It should be noted though that men get some additional ‘passive’ rest in front of the TV on those days (Figure 2e). Differences in TV watching patterns over Christmas are similar to those observed on ‘normal’ Sundays and the days just before the holidays – men watch TV by an average of 57 and 41 minutes/day more than women. Differences between men and women in the time spent on ‘work and study’ just before Christmas are not very different compared to ‘normal’ weekdays when men on average work nearly 100 minutes per day more compared to women. For this category Christmas days seem different from a ‘normal’ Sunday: women tend to work less during the holidays compared to men (by about 46 minutes/day), but we see virtually no difference in labor market activities on a normal Sunday.
Conclusion
If patterns of time-use have not changed much over the past ten years, Poles will spend almost four and a half hours per day on average enjoying meals and celebrations during the coming Christmas. They will add to this, on average, slightly more than three hours in front of the TV and about the same time enjoying walks, games and hobbies. The holiday will be preceded by intense preparations – in particular regarding preparing meals (170 minutes per day on the 23rd and 24th of December) and household work and cleaning (125 minutes per day). As we show in this brief, in 2013, the time burden of holiday preparations and household chores related to Christmas, was certainly not shared equally between men and women. Women spent much more time on those activities, especially in the days running up to Christmas, but also on the 25th and 26th of December.
With the upcoming release of the 2023 Polish time use data we will be able to examine whether patterns of Christmas time use have changed over the last decade. However, how our precious time over this year’s holiday season will be allocated is entirely up to us.
Merry Christmas!
Acknowledgment
Data used for the analysis in this brief come from the 2013 Polish Time Use Survey provided by the Polish Central Statistical Office (GUS). GUS bears no responsibility for the presented results and interpretation. I am very grateful to Daniel Hamermesh for his suggestions and comments.
References
- Adena, M., Hamermesh, D., Myck, M., Oczkowska, M. (2023) Home alone: Widows’ well-being and time, Journal of Happiness Studies, 24, 813–838. doi: 10.1007/s10902-023-00622-w.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
“Active Parent”: Addressing Labor Market Disadvantages of Mothers in Poland

In 2023 only one out of four children aged 0-3 years was covered by the Polish system of formal childcare. Traditional social norms with regard to provision of childcare at home, together with high costs of existing formal and informal childcare arrangements constitute important constraints with regard to labor market participation among mothers with the youngest children. While labor market activity rate among women aged 25-49 years stands at 84 percent overall, it is more than 20 percentage points lower for mothers with children aged 1-3 years. In this policy brief we provide an overview and an evaluation of “Active parent”, a recently introduced policy aimed at supporting earlier return to work after birth among mothers in Poland. We argue that the success of the program will be strongly determined by the extent to which it manages to stimulate growth of high-quality formal childcare for those aged 0-3 in the next few years.
Gender Gaps in Employment and Childcare in Poland
The average labor market activity rate among women aged 25-49 in Poland stands at 84 percent, which is slightly above the EU average (by 2 p.p.; see Figure 1). The rate, however, differs substantially by age group, and even more by the number and age of children. For childless women just below 30 years, the activity rate almost exactly matches the rate for men (88 percent vs 90 percent). However, among women with children, and especially among those with the youngest child being between 1 and 3 years old, this number drops to 62 percent. For fathers with such children, the activity rate however stands at 98 percent. Women gradually return to work when the youngest child is growing up – 3 out of 4 of those with a child aged 4 to 6 years are active in the labor market, and this share grows to 84 percent for mothers of teenagers (aged 13-14 years). At the same time women in Poland are much less likely to work part-time than women in the EU on average (7 vs. 28 percent, respectively; Eurostat, 2021). Rates of part-time employment are higher if women have more and younger children, though not by much (11 percent for mothers of 3+ children, 10 percent when a child is up to 3 years old; PEI, 2022).
While in most Polish households with children both parents are working for pay, traditional gender norms still largely prevail with respect to providing childcare or handling household duties. According to a survey conducted by the Polish Economic Institute (PEI), in only 18 percent of double-earner families do both parents take care of a child to the same extent (Polish Economic Institute 2022). For 68 percent of such families, it is the mother who provides most care. In only 1 in 10 families the father is the main care provider.
Figure 1. Labor market activity rates in Poland in 2022

Source: Authors’ compilation based on: PEI, 2022; Eurostat.
Traditional attitudes towards childcare responsibility are clearly visible in the actual gender split of parental leave in Poland. Despite the introduction of a non-transferable 9-week long parental leave dedicated to fathers (out of the total of 41 weeks of parental leave) on top of a two-week paternity leave, the division of care duties for the youngest children has essentially remained unaffected. While 377 000 mothers claimed parental leave benefits in 2021, only 4 000 fathers decided to stay at home with their child (Social Insurance Institute, 2021). Besides, many fathers still do not exercise their right to the fortnight of the paternity leave. According to the PEI survey conducted among parents of children aged 1-9 years, 41 percent of fathers reported virtually no work gap after the birth of their child and further 43 percent acknowledged only a short break from work (up to 14 days). On the other hand, 85 percent of mothers took a work break after childbirth of more than 8 months. For 40 percent it lasted between 12-18 months and for 28 percent the separation from work exceeded one and a half years.
Evaluating the Consequences of the “Active Parent” Program
To address the resulting disadvantages for mothers on the labor market the current Polish government introduced a program called “Active parent” in October 2024. The program is targeted at parents of children aged 12 to 35 months and consists of 3 options. The highest benefits in the program amounting to 350 EUR per month, are granted within the “Active at work” option to households in which parents are active on the labor market. For couples, the minimum work requirement is half-time work for each parent, while lone parents are required to work full-time. The same monthly amount can be granted if the child is enrolled in institutionalized childcare (“Active in nursery” option), though in this case the benefit does not exceed the cost of the nursery. This option covers both formal public or private nursery as well as semi-formal care provided in “kids clubs”. Finally, in case the child stays at home with a non-working parent (“Active at home” option), the family receives 115 EUR per month.
The main objective of the program is to increase the number of women returning to work after the period of maternity and parental leave (which in Poland cover the first 12 months of a newborn), before the child becomes eligible for kindergarten (where a place for each child aged 3 to 6 years is to be guaranteed by the local government). It is worth noting that after exhausting the parental leave, Polish parents are entitled to up to 3 years of childcare leave. Though this is unpaid, many parents, once again almost entirely mothers, opt for staying at home, often due to the lack of alternative forms of childcare. For children under the age of 3, formal childcare is highly limited. In 2023, nursery places were available only to one out of four children aged 0-3 years (CSO Poland). Additionally, these places are unevenly accessible throughout the country – in 2023 formal childcare for the youngest kids (public or private) did not exist in as many as 45 percent of Polish municipalities (CSO Poland). At the same time, while family help with childcare in Poland is still provided on a massive scale, it is limited only to those who have parents or other family members living close by, already in retirement and without other caring obligations (e.g. for older generations).
Within the new program parents who receive the “Active at work” benefit have complete discretion of how to use these funds. Many may choose to send the child to a formal childcare institution, but the lawmakers also expect a surge in undertaking formal contracts with grandparents or other relatives – including those already in retirement. There’s an additional benefit embedded in this particular solution, namely social security contributions resulting from contracts concluded with “a carer” (regardless of if it is a third person or a family member) which are covered by the state. These contributions are added to the carer’s pension funds and translate into higher retirement benefits – with regular recalculations of pension funds among those already retired and higher expected pension benefits for those still below retirement age.
A recent policy report (Myck, Krol and Oczkowska, 2024), evaluated the impact of the “Active parent” program using the microsimulation model SIMPL. The analysis (based on the Polish Household Budget Survey from 2021) focused on the estimation of the expected costs of the program to the public budget and the distribution of financial gains among households. We find that families eligible to receive support, i.e. those with children aged 12-35 months, are concentrated in the upper half of the income distribution (12.6 percent among the richest households and only 5.4 percent living in the poorest households). Thus, taking the observed work and childcare use patterns from the data we find that the average net gains related to the entire “Active parent” program are also concentrated among the richer households (see Figure 2).
Figure 2. Average net monthly gain from the “Active parent” program, assuming no change in parental behavior in reaction to the roll-out of the program

Source: Authors’ calculation with SIMPL microsimulation model based on the Polish Household Budget Survey 2021 data, indexed to 2024. Note: Introduction of the new program automatically withdrew the existing support targeted at families with children in the respective age range: “Family Childcare Fund” of 115 EUR/month for families with the second or next child aged 12-35 months and the co-payment for nursery up to 90 EUR/month. 1 EUR = 4.3 PLN.
Households from the highest income decile group on average gain 220 EUR per month, while those from the poorest income group receive 170 EUR per month. In relative terms, these gains correspond on average to as much as 17 percent of their income, while for the former group the gains do not exceed 4 percent of their income. When disaggregating by the three options of the program, eligible households from the bottom part of the distribution receive much higher gains from the “Active in nursery” or “Active at home” options, as these households are much less likely to have both parents working.
Clearly, some parents may adjust their work and childcare choices in reaction to the introduction of the program, which, in fact, is one of its key objectives. If a family decides to take up work or send their child to a nursery, they become eligible for higher support. Rather than receiving 115 EUR from the “Active at home” option, they become eligible for up to 350 EUR under the other alternative options. In almost 200 000 out of the overall 550 000 families with an age-eligible child, one of the parents (usually the mother) is observed to be out of work. Using this, we estimate the likelihood of taking up work among these non-working mothers and conditional on the expected probabilities of employment we assigned additional families to the two more generous options of the program – either to “Active at work” (those with highest work probability) or to “Active in nursery” (those with lowest work probability). This allows us to evaluate potential changes in the cost and distributional implications of the program under different scenarios. Table 1 presents a set of “gross” and “net” costs of selected combinations of parental reactions. The “gross” costs correspond to the total expenditure of the “Active parent” program, while the “net” costs account first for the withdrawal of previous policies (see note to Figure 2), and second for the budget gains related to taxes and social insurance contributions paid by the parents who are simulated to take up work.
Table 1. “Active parent”: aggregate costs to the public budget under different assumptions concerning work and childcare adjustments among parents

Source: see Figure 2.
Assuming no change in parental behavior (0 percent increase in work and 0 percent increase in enrollment in nursery), the total, “gross” cost of the program for the public finances amounts to 1.72 bn EUR, on average, annually. Savings related to the withdrawal of existing policies lower this cost by 0.5 bn EUR. Any modelled increase in nursery enrollment (with no concurrent reaction in the labor market) means an increase in both the “gross” and the “net” costs, while on the other hand an increase in labor market participation of the non-working parent (when nursery enrollment is held constant) expands the “gross” costs but reduces the “net” costs due to higher taxes and contributions paid in relation to simulated additional earnings.
The final distributional household effects of the program will depend on the actual reactions among parents. However, according to our simulations, the families who are most likely to either increase employment of the second parent or sign up their child for a nursery, and, thus, gain from the “Active at work” or “Active in nursery” options, are those currently located in the 2nd, 3rd, and 4th income decile group in the distribution (for more details see: Myck, Krol and Oczkowska, 2024).
Conclusion
The main objective behind the introduction of the new “Active parent” scheme is to increase the labor market participation among mothers with the youngest children. As the program aims to facilitate balancing professional careers with family life among parents, it can also be expected to contribute to increases in the fertility rate, which has recently fallen in Poland from 1.45 in 2017 to 1.16 in 2023 (CSO Poland).
The success of the “Active parent” program should be evaluated with respect to three important indicators:
- the resulting increase in the number of mothers who have taken up work,
- the increase in the number of children registered for nurseries,
- and, related to the latter – the increase in the availability of childcare places in different Polish municipalities.
It is worth noting that the “Active parent” program was introduced in parallel with the prior “Toddler +” program that aimed at creating new childcare institutions and more places in the existing ones in 2022-2029 in Poland. Central funding was distributed to reach these goals among local governments and private care providers. However, a 2024 midterm audit of the “Toddler +” program demonstrated the progress to be “insufficient and lagging” (Supreme Audit Office Poland, 2024). The “Active parent” program will play an important role in providing additional stimulus to the provision of new childcare places for the youngest kids in different Polish regions, which should help the “Toddler +” program to finally gather momentum. In the medium and long run, the development of high-quality formal childcare for children below 3 years will be a crucial determinant of an increase in early return to work among mothers.
Acknowledgment
The authors wish to acknowledge the support of the Swedish International Development Cooperation Agency (Sida) under the FROGEE project. The views presented in the Policy Brief reflect the opinions of the Authors and do not necessarily overlap with the position of the FREE Network or Sida.
References
- CSO (Central Statistical Office) Poland. Local Data Bank: Formal childcare: rate of children, number of places; Fertility rates.
- Eurostat. Labour force participation and part-time work.
- Myck, M., Krol, A., Oczkowska, M., (2024). “Active at work, in a nursery, or at home: Financial consequences of the “Active parent” program”, CenEA Report (in Polish).
- PEI (Polish Economic Institute). (2022). “Work vs. home. Parental challenges and their consequences”, PEI Report (in Polish).
- Social Insurance Institute. (2021). Number of parental leave benefits.
- Supreme Audit Office Poland. (2024). “Development of childcare system, including administration of the program “Toddler+”, Post-control results report (in Polish).
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Gender Gap in Life Expectancy and Its Socio-Economic Implications

Today women live longer than men virtually in every country of the world. Although scientists still struggle to fully explain this disparity, the most prominent sources of this gender inequality are biological and behavioral. From an evolutionary point of view, female longevity was more advantageous for offspring survival. This resulted in a higher frequency of non-fatal diseases among women and in a later onset of fatal conditions. The observed high variation in the longevity gap across countries, however, points towards an important role of social and behavioral arguments. These include higher consumption of alcohol, tobacco, and fats among men as well as a generally riskier behavior. The gender gap in life expectancy often reaches 6-12 percent of the average human lifespan and has remained stubbornly stable in many countries. Lower life expectancy among men is an important social concern on its own and has significant consequences for the well-being of their surviving partners and the economy as a whole. It is an important, yet under-discussed type of gender inequality.
Country Reports
Belarus Country Report | FROGEE POLICY BRIEF |
Georgia Country Report | FROGEE POLICY BRIEF |
Latvia Country Report | FROGEE POLICY BRIEF |
Poland Country Report | FROGEE POLICY BRIEF |
Gender Gap in Life Expectancy and Its Socio-Economic Implications
Today, women on average live longer than men across the globe. Despite the universality of this basic qualitative fact, the gender gap in life expectancy (GGLE) varies a lot across countries (as well as over time) and scientists have only a limited understanding of the causes of this variation (Rochelle et al., 2015). Regardless of the reasons for this discrepancy, it has sizable economic and financial implications. Abnormal male mortality makes a dent in the labour force in nations where GGLE happens to be the highest, while at the same time, large GGLE might contribute to a divergence in male and female discount factors with implications for employment and pension savings. Large discrepancies in life expectancy translate into a higher incidence of widowhood and a longer time in which women live as widows. The gender gap in life expectancy is one of the less frequently discussed dimensions of gender inequality, and while it clearly has negative implications for men, lower male longevity has also substantial negative consequences for women and society as a whole.
Figure A. Gender gap in life expectancy across selected countries

Source: World Bank.
The earliest available reliable data on the relative longevity of men and women shows that the gender gap in life expectancy is not a new phenomenon. In the middle of the 19th century, women in Scandinavian countries outlived men by 3-5 years (Rochelle et al., 2015), and Bavarian nuns enjoyed an additional 1.1 years of life, relative to the monks (Luy, 2003). At the beginning of the 20th century, relative higher female longevity became universal as women started to live longer than men in almost every country (Barford et al., 2006). GGLE appears to be a complex phenomenon with no single factor able to fully explain it. Scientists from various fields such as anthropology, evolutionary biology, genetics, medical science, and economics have made numerous attempts to study the mechanisms behind this gender disparity. Their discoveries typically fall into one of two groups: biological and behavioural. Noteworthy, GGLE seems to be fairly unrelated to the basic economic fundamentals such as GDP per capita which in turn has a strong association with the level of healthcare, overall life expectancy, and human development index (Rochelle et al., 2015). Figure B presents the (lack of) association between GDP per capita and GGLE in a cross-section of countries. The data shows large heterogeneity, especially at low-income levels, and virtually no association from middle-level GDP per capita onwards.
Figure B. Association between gender gap in life expectancy and GDP per capita

Source: World Bank.
Biological Factors
The main intuition behind female superior longevity provided by evolutionary biologists is based on the idea that the offspring’s survival rates disproportionally benefited from the presence of their mothers and grandmothers. The female hormone estrogen is known to lower the risks of cardiovascular disease. Women also have a better immune system which helps them avoid a number of life-threatening diseases, while also making them more likely to suffer from (non-fatal) autoimmune diseases (Schünemann et al., 2017). The basic genetic advantage of females comes from the mere fact of them having two X chromosomes and thus avoiding a number of diseases stemming from Y chromosome defects (Holden, 1987; Austad, 2006; Oksuzyan et al., 2008).
Despite a number of biological factors contributing to female longevity, it is well known that, on average, women have poorer health than men at the same age. This counterintuitive phenomenon is called the morbidity-mortality paradox (Kulminski et al., 2008). Figure C shows the estimated cumulative health deficits for both genders and their average life expectancies in the Canadian population, based on a study by Schünemann et al. (2017). It shows that at any age, women tend to have poorer health yet lower mortality rates than men. This paradox can be explained by two factors: women tend to suffer more from non-fatal diseases, and the onset of fatal diseases occurs later in life for women compared to men.
Figure C. Health deficits and life expectancy for Canadian men and women

Source: Schünemann et al. (2017). Note: Men: solid line; Women: dashed line; Circles: life expectancy at age 20.
Behavioural Factors
Given the large variation in GGLE, biological factors clearly cannot be the only driving force. Worldwide, men are three times more likely to die from road traffic injuries and two times more likely to drown than women (WHO, 2002). According to the World Health Organization (WHO), the average ratio of male-to-female completed suicides among the 183 surveyed countries is 3.78 (WHO, 2024). Schünemann et al. (2017) find that differences in behaviour can explain 3.2 out of 4.6 years of GGLE observed on average in developed countries. Statistics clearly show that men engage in unhealthy behaviours such as smoking and alcohol consumption much more often than women (Rochelle et al., 2015). Men are also more likely to be obese. Alcohol consumption plays a special role among behavioural contributors to the GGLE. A study based on data from 30 European countries found that alcohol consumption accounted for 10 to 20 percent of GGLE in Western Europe and for 20 to 30 percent in Eastern Europe (McCartney et al., 2011). Another group of authors has focused their research on Central and Eastern European countries between 1965 and 2012. They have estimated that throughout that time period between 15 and 19 percent of the GGLE can be attributed to alcohol (Trias-Llimós & Janssen, 2018). On the other hand, tobacco is estimated to be responsible for up to 30 percent and 20 percent of the gender gap in mortality in Eastern Europe and the rest of Europe, respectively (McCartney et al., 2011).
Another factor potentially decreasing male longevity is participation in risk-taking activities stemming from extreme events such as wars and military activities, high-risk jobs, and seemingly unnecessary health-hazardous actions. However, to the best of our knowledge, there is no rigorous research quantifying the contribution of these factors to the reduced male longevity. It is also plausible that the relative importance of these factors varies substantially by country and historical period.
Gender inequality and social gender norms also negatively affect men. Although women suffer from depression more frequently than men (Albert, 2015; Kuehner, 2017), it is men who commit most suicides. One study finds that men with lower masculinity (measured with a range of questions on social norms and gender role orientation) are less likely to suffer from coronary heart disease (Hunt et al., 2007). Finally, evidence shows that men are less likely to utilize medical care when facing the same health conditions as women and that they are also less likely to conduct regular medical check-ups (Trias-Llimós & Janssen, 2018).
It is possible to hypothesize that behavioural factors of premature male deaths may also be seen as biological ones with, for example, risky behaviour being somehow coded in male DNA. But this hypothesis may have only very limited truth to it as we observe how male longevity and GGLE vary between countries and even within countries over relatively short periods of time.
Economic Implications
Premature male mortality decreases the total labour force of one of the world leaders in GGLE, Belarus, by at least 4 percent (author’s own calculation, based on WHO data). Similar numbers for other developed nations range from 1 to 3 percent. Premature mortality, on average, costs European countries 1.2 percent of GDP, with 70 percent of these losses attributable to male excess mortality. If male premature mortality could be avoided, Sweden would gain 0.3 percent of GDP, Poland would gain 1.7 percent of GDP, while Latvia and Lithuania – countries with the highest GGLE in the EU – would each gain around 2.3 percent of GDP (Łyszczarz, 2019). Large disparities in the expected longevity also mean that women should anticipate longer post-retirement lives. Combined with the gender employment and pay gap, this implies that either women need to devote a larger percentage of their earnings to retirement savings or retirement systems need to include provisions to secure material support for surviving spouses. Since in most of the retirement systems the value of pensions is calculated using average, not gender-specific, life expectancy, the ensuing differences may result in a perception that men are not getting their fair share from accumulated contributions.
Policy Recommendations
To successfully limit the extent of the GGLE and to effectively address its consequences, more research is needed in the area of differential gender mortality. In the medical research dimension, it is noteworthy that, historically, women have been under-represented in recruitment into clinical trials, reporting of gender-disaggregated data in research has been low, and a larger amount of research funding has been allocated to “male diseases” (Holdcroft, 2007; Mirin, 2021). At the same time, the missing link research-wise is the peculiar discrepancy between a likely better understanding of male body and health and the poorer utilization of this knowledge.
The existing literature suggests several possible interventions that may substantially reduce premature male mortality. Among the top preventable behavioural factors are smoking and excessive alcohol consumption. Many studies point out substantial country differences in the contribution of these two factors to GGLE (McCartney, 2011), which might indicate that gender differences in alcohol and nicotine abuse may be amplified by the prevailing gender roles in a given society (Wilsnack et al., 2000). Since the other key factors impairing male longevity are stress and risky behaviour, it seems that a broader societal change away from the traditional gender norms is needed. As country differences in GGLE suggest, higher male mortality is mainly driven by behaviours often influenced by societies and policies. This gives hope that higher male mortality could be reduced as we move towards greater gender equality, and give more support to risk-reducing policies.
While the fundamental biological differences contributing to the GGLE cannot be changed, special attention should be devoted to improving healthcare utilization among men and to increasingly including the effects of sex and gender in medical research on health and disease (Holdcoft, 2007; Mirin, 2021; McGregor et al., 2016, Regitz-Zagrosek & Seeland, 2012).
References
- Albert, P. R. (2015). “Why is depression more prevalent in women?“. Journal of Psychiatry & Neuroscience, 40(4), 219.
- Austad, S. N. (2006). “Why women live longer than men: sex differences in longevity“. Gender Medicine, 3(2), 79-92.
- Barford, A., Dorling, D., Smith, G. D., & Shaw, M. (2006). “Life expectancy: women now on top everywhere“. BMJ, 332, 808. doi:10.1136/bmj.332.7545.808
- Holden, C. (1987). “Why do women live longer than men?“. Science, 238(4824), 158-160.
- Hunt, K., Lewars, H., Emslie, C., & Batty, G. D. (2007). “Decreased risk of death from coronary heart disease amongst men with higher ‘femininity’ scores: A general population cohort study“. International Journal of Epidemiology, 36, 612-620.
- Kulminski, A. M., Culminskaya, I. V., Ukraintseva, S. V., Arbeev, K. G., Land, K. C., & Yashin, A. I. (2008). “Sex-specific health deterioration and mortality: The morbidity-mortality paradox over age and time“. Experimental Gerontology, 43(12), 1052-1057.
- Luy, M. (2003). “Causes of Male Excess Mortality: Insights from Cloistered Populations“. Population and Development Review, 29(4), 647-676.
- McCartney, G., Mahmood, L., Leyland, A. H., Batty, G. D., & Hunt, K. (2011). “Contribution of smoking-related and alcohol-related deaths to the gender gap in mortality: Evidence from 30 European countries“. Tobacco Control, 20, 166-168.
- McGregor, A. J., Hasnain, M., Sandberg, K., Morrison, M. F., Berlin, M., & Trott, J. (2016). “How to study the impact of sex and gender in medical research: A review of resources“. Biology of Sex Differences, 7, 61-72.
- Mirin, A. A. (2021). “Gender disparity in the funding of diseases by the US National Institutes of Health“. Journal of Women’s Health, 30(7), 956-963.
- Oksuzyan, A., Juel, K., Vaupel, J. W., & Christensen, K. (2008). “Men: good health and high mortality. Sex differences in health and aging“. Aging Clinical and Experimental Research, 20(2), 91-102.
- Regitz-Zagrosek, V., & Seeland, U. (2012). “Sex and gender differences in clinical medicine“. Sex and Gender Differences in Pharmacology, 3-22.
- Rochelle, T. R., Yeung, D. K. Y., Harris Bond, M., & Li, L. M. W. (2015). “Predictors of the gender gap in life expectancy across 54 nations“. Psychology, Health & Medicine, 20(2), 129-138. doi:10.1080/13548506.2014.936884
- Schünemann, J., Strulik, H., & Trimborn, T. (2017). “The gender gap in mortality: How much is explained by behavior?“. Journal of Health Economics, 54, 79-90.
- Trias-Llimós, S., & Janssen, F. (2018). “Alcohol and gender gaps in life expectancy in eight Central and Eastern European countries“. European Journal of Public Health, 28(4), 687-692.
- WHO. (2002). “Gender and road traffic injuries“. World Health Organization.
- WHO. (2024). “Global health estimates: Leading causes of death“. World Health Organization.
- Łyszczarz, B. (2019). “Production losses associated with premature mortality in 28 European Union countries“. Journal of Global Health.
About FROGEE Policy Briefs
FROGEE Policy Briefs is a special series aimed at providing overviews and the popularization of economic research related to gender equality issues. Debates around policies related to gender equality are often highly politicized. We believe that using arguments derived from the most up to date research-based knowledge would help us build a more fruitful discussion of policy proposals and in the end achieve better outcomes.
The aim of the briefs is to improve the understanding of research-based arguments and their implications, by covering the key theories and the most important findings in areas of special interest to the current debate. The briefs start with short general overviews of a given theme, which are followed by a presentation of country-specific contexts, specific policy challenges, implemented reforms and a discussion of other policy options.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Active Labor Market Policy in the Baltic-Black Sea Region

This brief outlines the characteristics of active labor market policy (ALMP) in four countries in the Baltic-Black Sea region: Belarus, Lithuania, Poland, and Ukraine. An analysis of the financing expenditure structure within this framework reveals significant differences between the countries, even for Poland and Lithuania, where the policies are to be set within a common EU framework. Countries also differed in terms of their ALMP reaction to the economic challenges brought about by the Covid-19 pandemic, as Poland and Lithuania increased their ALMP spending, while Ukraine, and, especially, Belarus, lagged behind. Despite these differences, all four countries are likely to benefit from a range of common recommendations regarding the improvement of ALMP. These include implementing evidence-informed policymaking and conducting counterfactual impact evaluations, facilitated by social partnership. Establishing quantitative benchmarks for active labor market policy expenditures and labor force coverage by active labor market measures is also advised.
Introduction
This policy brief builds on a study aimed at conducting a comparative analysis of labor market regulation policies in Belarus, Ukraine, Lithuania, and Poland. In comparing the structure of labor market policy expenditures, the aim was to identify common features between Poland and Lithuania, both of which are part of the EU and employ advanced labor market regulation approaches. We also assessed Ukraine’s policies, currently being reformed to align with EU standards, contrasting them with Belarus, where economic reforms are hindered by the post-Soviet authoritarian regime.
The analysis of the labor market policies for the considered countries is based on an evaluation of the structure of pertinent measures between 2017 and 2020 (Mazol, 2022). We used the 2015 OECD systematization of measures of active labor market policy, as presented in the first column of Table 1.
Our study reveals substantial differences in active labor market policies within the four considered countries. Still, motivated by OECD’s approach to ALMP, we provide a range of common policy recommendations that are relevant for each country included in the study. Arguably, aligning with the OECD approach would have more value for current EU and OECD members, Poland and Lithuania, and the aspiring member, Ukraine. However, these recommendations also hold value when considering a reformation of the Belarusian labor market policy.
ALMP Expenditures in Belarus, Lithuania, Poland and Ukraine
Labor market policy comprises of active and passive components. Active labor market policy involves funding employment services and providing various forms of assistance to both unemployed individuals and employers. Its primary objective is to enhance qualifications and intensify job search efforts to improve the employment prospects of the unemployed (Bredgaard, 2015). Passive labor market policy (PLMP) encompasses measures to support the incomes of involuntarily unemployed individuals, and financing for early retirement.
Poland and Lithuania are both EU and OECD members, so one would expect their labor market policies to be driven by the EU framework, and, thus, mostly aligned. However, our analysis showed that the structure of their expenditures on active labor market policies in 2017-2019 differed (Mazol, 2022). In Lithuania, the majority of the funding was allocated to employment incentives for recruitment, job maintenance, and job sharing. From 2017 to 2019, the share for these measures was between 18 and 28 percent of all expenditures for state labor market regulation. In Poland, the majority of funding was allocated to measures supporting protected employment and rehabilitation. The spending on these measures fluctuated between 23 and 34 percent of all expenditures for state labor market regulation between 2017 and 2019.
The response to the labor market challenges during the Covid-19 pandemic in Poland and Lithuania resulted in a notable surge in state labor market policy spendings in 2020, amounting to 1.78 percent of GDP and 2.83 percent of GDP, respectively. Both countries sharply increased the total spending on employment incentives (see Table 1 which summarizes the expenditure allocation for 2020). Poland experienced a nine-fold increase in costs for financing these measures (29.4 percent of total expenditures on state labor market regulation). Meanwhile, in Lithuania, financing for employment incentives increased more than tenfold, amounting to 42.5 percent of all expenditures for state labor market regulation. In both countries it became the largest active labor market policy spending area.
Table 1. Financing of state labor market measures in Baltic-Black Sea region countries in 2020 (in millions of Euro).

Source: DGESAI, 2023. Author’s estimations based on World Bank data (World Bank, 2023), National Bank of Belarus data, National Bank of Ukraine data.
In Ukraine, the primary focus for active labor market policy expenditures was, from 2017 to 2020, directed towards public employment services, comprising 18 to 24 percent of total labor market policy expenditures. Notably, despite the Covid-19 pandemic, there were no significant changes in either the structure or the volume of active labor market policy expenditures in Ukraine in 2020. Despite Ukraine’s active efforts to align its economic and social policies with EU standards, the government has underinvested in labor market policy, with expenditures accounting for only 0.33-0.37 percent of GDP between 2017 and 2020. This is significantly below the levels observed in Lithuania and Poland.
In Belarus, labor market policy financing is one of the last priorities for the government. In 2020, financing accounted for about 0.02 percent of GDP, amounts clearly insufficient for having a significant impact on the labor market. Moreover, Belarus stood out as the sole country in the reviewed group to have reduced its funding for labor market policies, including both active and income support measures, during the Covid-19 pandemic. The majority of the financing for labor market policy has been directed towards protected and supported employment and rehabilitation, including job creation initiatives for former prisoners, the youth and individuals with disabilities.
ALMP Improvement Recommendations
As illustrated above, the countries under review do not have a common approach to active labor market policy spendings. Further, countries like Poland and Lithuania took a more flexible stance on addressing labor market challenges caused by the Covid-19 pandemic, by implementing additional financial support for active labor market policies. However, Ukraine and Belarus did not adjust their expenditure structures accordingly. Part of these cross-country differences can be attributed to differing legal framework: Poland and Lithuania are OECD and EU member states, and, thus, subject to corresponding regulations. Ukraine is in turn motivated by the prospects of EU accession, while Belarus currently has no such prosperities to take into account.
Another important source of deviation arises from the differences in current labor market and economic conditions in the respective countries, and the governments’ need to accommodate these. While such a market-specific approach is well-justified, aligning expenditure structures with current labor market conditions necessitates obtaining updated and reliable information about the labor market situation and the effectiveness of specific labor market measures or programs. An effective labor market policy thus requires establishing a reliable system for assessing the efficiency of government measures, i.e., deploying evidence-informed policy making (OECD, 2022).
To achieve this, it is crucial to establish a robust system for monitoring and evaluating the implementation of specific measures. This involves leveraging data from various centralized sources, enhancing IT infrastructure to support data management, and utilizing modern methodologies such as counterfactual impact evaluations (OECD, 2022).
Moreover, an effective labor market regulation policy necessitates the ability to swiftly adapt existing active measures and service delivery methods in response to changes in the labor market. This might entail rapid adjustments in the legal framework, underscoring the importance of close cooperation and coordination among key stakeholders, and a well-functioning administrative structure (Lauringson and Lüske, 2021).
To accomplish this objective, it is vital to foster close collaboration between the government and institutions closely intertwined with the labor market, capable of providing essential information to labor market regulators. One of the most useful tools in this regard appears to be so-called social partnerships – a form of a dialogue between employers, employees, trade unions and public authorities, involving active information exchange and interaction (OECD, 2022).
A reliable system to assess labor market policy and in particular to facilitate their targeting, is an essential component of this approach.
Ukraine and Belarus are underfunding their labor market policies, both in comparison to the levels observed in Poland and Lithuania, and in absolute terms. It is therefore advisable to establish quantitative benchmark indicators to act as guidance for these countries, in order to ensure that any labor market policy implemented is adequately funded. Here, a reasonable approach is to align the costs of implementing labor market measures with the average annual levels for OECD countries (which are 0.5 percent of GDP for active measures and 1.63 percent for total labor market policy expenditures (OECD, 2024). Furthermore, it’s essential to ensure a high level of labor force participation in active labor market regulation measures. A target standard could be set, based on the average annual coverage from active labor market measures, at 5.8 percent of the national economy labor force, as observed in OECD countries (OECD, 2024).
Conclusion
The countries under review demonstrate varying structures of active labor market expenditures. Prior to the Covid-19 pandemic, employment incentives received the most financing in Lithuania. In Poland the largest share of expenditures was instead directed to measures to support protected employment and rehabilitation. In Ukraine, the main expenditures were directed towards financing employment services and unemployment benefits while Belarus primarily allocated funds to protected and supported employment and rehabilitation. Notably, Lithuania and Poland responded to the economic challenges following Covid-19 by significantly increasing spending on employment incentives, while Ukraine and Belarus did not undertake such measures.
Part of the diverging patterns may be attributable to the countries varying legal framework and differences in the countries respective labor market and economic conditions.
While some of the differences in labor market policies are thus justified, ensuring funding at the OECD level for labor market measures, alongside adequate tools for monitoring and evaluating labor market policies, are likely to benefit all four Baltic-Black Sea countries.
References
- Bredgaard, T. (2015). Evaluating What Works for Whom in Active Labour Market Policies. European Journal of Social Security, 17 (4), 436-452.
- DGESAI. (Directorate-General for Employment, Social Affairs and Inclusion). (2023. Expenditure by LMP intervention – country https://webgate.ec.europa.eu/empl/redisstat/databrowser/explore/all/lmp?lang=en&subtheme=lmp_expend.lmp_expend_me&display=card&sort=category&extractionId=LMP_EXPME
- Lauringson, A. and Lüske M. (2021). Institutional Set-up of Active Labour Market Policy Provision in OECD and EU Countries: Organisational Set-up, Regulation and Capacity. OECD Social, Employment and Migration Working Papers no. 262.
- Mazol, A. (2022). Active Labor Market Policy in the Countries of the Baltic-Black Sea Region. BEROC Policy Paper Series, PP no. 115.
- OECD. (2015). OECD Employment database – Labour market policies and institutions https://www.oecd.org/employment/Coverage-and-classification-of-OECD-data-2015.pdf
- OECD. (2022). Impact Evaluation of Vocational Training and Employment Subsidies for the Unemployed in Lithuania. Connecting people with jobs. Paris: OECD Publishing.
- OECD. (2024). OECDstats: Labor market programs https://stats.oecd.org
- World Bank. (2023). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Widowhood in Poland: Reforming the Financial Support System

Drawing on a recent Policy Paper, we analyse the degree to which the current system of support in widowhood in Poland limits the extent of poverty among this large and growing group of the population. The analysis is set in the context of a proposed reform discussed lately in the Polish Parliament. We present the budgetary and distributional consequences of this proposal and offer an alternative scenario which limits the overall cost of the policy and directs additional resources to low-income households.
Introduction
Losing a partner usually comes with consequences, both for mental health and psychological well-being (Adena et al., 2023; Blanner Kristiansen et al., 2019; Lee et al., 2001; Steptoe et al., 2013), and for material welfare. Economic deprivation may be particularly pronounced in cases of high-income differentials between spouses and in situations when the primary earner – often the man – dies first. Many countries have instituted survivors’ pensions, whereby the surviving spouse continues to receive some of the income of her/his deceased partner alongside other incomes. The systems of support differ substantially between countries and they often combine social security benefits and welfare support for those with lowest incomes.
In this Policy Brief we summarise the results from a recent paper (Myck et al., 2024) and discuss the material situation of widows versus married couples in Poland. We show the degree to which the ‘survivors’ pension’, i.e. the current system of support in widowhood, limits the extent of poverty among widows and compare it to a proposed reform discussed lately in the Polish Parliament, the so called ‘widows’ pension’. In light of the examined consequences from this proposal we relate it to an alternative scenario, which – as we demonstrate – brings very similar benefits to low-income widows, but, at the same time, substantially reduces the cost of the policy.
Reforming the System of Support in Widowhood
Our analysis draws on a sample of married couples aged 65 and older from the Polish Household Budget Survey – a group representing a large part of the Polish population (almost 1,7 million couples). Each of these couples is assigned to an income decile, depending on the level of their disposable income. Incomes of 9.5 percent of the sample locate them in the bottom decile, i.e. the poorest 10 percent of the population, while 4.4 percent of these older couples have incomes high enough to place them in the top income group – the richest 10 percent of the population.
Next, in order to examine the effectiveness of the different systems of support, we conduct the following exercise: incomes of these households are re-calculated assuming the husbands have passed away. This simulates the incomes of the sampled women in hypothetical scenarios of widowhood. The incomes are calculated under four different systems of support as summarized in Table 1.
Table 1. Modelled support scenarios.
Using these re-calculated household incomes, we can identify the relative position in the income distribution in the widowhood scenario as well as the poverty risk among widows under different support systems.
The change in the relative position in the income distribution following widowhood under the four support systems is presented in Figure 1. The starting point (the left-hand side of each chart) are the income groups of households with married couples aged 65+, i.e. before the simulated widowhood. The transition to the income deciles on the right-hand side of each chart is the result of a change in equivalised (i.e. adjusted for household composition) disposable income in the widowhood simulation, under different support scenarios (I – IV).
Figure 1. Change in income decile among women aged 65+, following a hypothetical death of their husbands.

Source: Own calculations based on HBS 2021 using SIMPL model; graphs were created using: https://flourish.studio/
Figure 1a shows that, without any additional support, the financial situation of older women would significantly deteriorate in the event of the death of their spouses (Figure 1a). The share of women with incomes in the lowest two deciles would be as high as 54.7 percent (compared to 17.5 percent of married couples). The current survivor’s pension seems to protect a large proportion of women from experiencing large reductions in their income (Figure 1b), although the proportion of those who find themselves in the lowest two income decile groups more than doubles relative to married couples (to 38.3 percent). The widow’s pension (Figure 1c) offers much greater support and a very large share of new widows remain in the same decile or even move to a higher income group following the hypothetical death of their spouses. For example, with the widows’ pension, 8.0 percent of the widows would be in the 9th income decile group and 5.3 percent in the 10th group, while in comparison 7.0 and 4.4 percent of married couples found themselves in these groups, respectively. The proposed alternative system (Figure 1d) raises widows’ incomes compared to the current survivor’s pension system, but it is less generous than the system with the widow’s pension. At the same time 4.6 percent and 3.4 percent of widows would be found in the 9th and 10th deciles, respectively.
Importantly, the alternative support system is almost as effective in reducing the poverty risk among widows as the widow’s pension. In the latter case the share of at-risk-of poverty drops from 35.3 percent (with no support) and 20.7 percent (under the current system) to 11,0 percent, while under the alternative system, it drops to 11.8 percent. Because the alternative system limits additional support to households with higher incomes, this reduction in at-risk-of poverty would be achieved at a much lower cost to the public budget. We estimate that while the current reform proposal would result in annual cost of 24.1 bn PLN (5.6 bn EUR), the alternative design would cost only 10.5 bn PLN (2.5 bn EUR).
The distributional implications of the two reforms are presented in Figure 2 which shows the average gains in the incomes of ‘widowed’ households between the reformed versions of support and the current system with the survivor’s pension. The gains are presented by income decile of the married households. We see that the alternative system significantly limits the gains among households in the upper half of the income distribution.
Figure 2. Average gains from an implementation of the widow’s pension and the alternative system, by income decile groups.

Source: Own calculations based on HBS 2021 using the SIMPL model. Notes: Change in the disposable income with respect to the current system with survivor’s pension. 1PLN~0.23EUR.
Conclusions
While subjective evaluations of the material conditions of older persons living alone in Poland have shown significant improvements, income poverty within this groups has increased since 2015. This suggests that the incomes of older individuals have not sufficiently kept up with the dynamics of earnings of and social transfers to other social groups in Poland. As shown in our simulations, the current widowhood support system substantially limits the risk of poverty following the death of one’s partner. However, while the current survivor’s pension decreases the poverty risk from 35.3 percent in a system without any support to 20.7 percent, the risk of poverty among widows is still significantly higher compared to the risk faced by married couples.
The simulations presented in this Policy Brief examine the implications of a support system reform; the widow’s pension which is currently being discussed in the Polish Parliament, as well as an alternative proposal putting more emphasis on poorer households. The impactof these two reforms on the at-risk-of poverty levels among widowed individuals would be very similar, but the design of the alternative system would come at a significantly lower cost to the public budget. The total annual cost to the public sector of the widow’s pensions would amount to 24.1 bn PLN (5.6 bn EUR) while our proposed alternative would cost only 10.5 bn PLN (2.5 bn EUR) per year.
An effective policy design allowing the government to achieve its objectives at the lowest possible costs should always be among the government main priorities. This is especially important in times of high budget pressure – due to demographic changes or other risks – as is currently the case in Poland.
References
- Adena, M., Hamermesh, D., Myck, M., & Oczkowska, M. (2023). Home Alone: Widows’ Well-Being and Time. Journal of Happiness Studies.
- Blanner Kristiansen, C., Kjær, J. N., Hjorth, P., Andersen, K., & Prina, A. M. (2019). Prevalence of common mental disorders in widowhood: A systematic review and meta-analysis. Journal of Affective Disorders, 245, 1016–1023.
- Lee, G. R., DeMaris, A., Bavin, S., & Sullivan, R. (2001). Gender Differences in the Depressive Effect of Widowhood in Later Life. The Journals of Gerontology: Series B, 56(1), S56–S61.
- Myck, M., Król, A. & Oczkowska, M. (2024). Reforming financial support in widowhood: the current system in Poland and its potential reforms. FREE Network Policy Paper Series.
- Steptoe, A., Shankar, A., Demakakos, P., & Wardle, J. (2013). Social isolation, loneliness, and all-cause mortality in older men and women. Proceedings of the National Academy of Sciences, 110(15), 5797–5801.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Reforming Financial Support in Widowhood: The Current System in Poland and Potential Reforms

In this policy paper, we discuss the material conditions of widows and widowers compared to married couples in Poland, and analyse the degree to which the current support system to those in widowhood in Poland limits the extent of poverty among this large and growing share of the population. The analysis is set in the context of a proposed reform recently discussed in the Polish Parliament. We present the budgetary and distributional consequences of this proposal and offer an alternative scenario which limits the overall cost of the policy and directs additional resources to low income households.
Introduction
According to the National Census in 2021 there were about 2.2 million widows and 450 000 widowers in Poland. In the following year over 123 000 women and about 47 000 men became widowed. Apart from the severe consequences for mental health and psychological well-being, losing a partner typically has implications also for material wellbeing, in particular in cases of high income differentials between the spouses and in situations when the primary earner – often the man – dies first. Material conditions of the surviving spouse in widowhood depend on the one hand on the couple’s accumulated resources, and, on the other hand, on the available support system. Many countries have instituted so-called survivors’ pensions, whereby the surviving spouse continues to receive some of the income of her/his deceased partner alongside other incomes. The systems of support differ substantially between countries and they often combine social security benefits and welfare support for those with the lowest incomes.
In this policy paper we discuss the material situation of widows and widowers versus married couples in Poland and analyse the degree to which the current Polish support system for people in widowhood limits the extent of poverty within this group. We compare the current system of survivors’ pension with a proposed reform discussed lately in the Polish Parliament;the introduction of a ‘widow’s pension’. We present the budgetary and distributional consequences of the announced scheme and offer an alternative scenario which limits the overall cost of the policy and focuses additional resources on low income households. Our results show significant income gains for widows/widowers from the implementation of the recently proposed widow’s pension. The policy however, would come at a substantial cost to the public purse, and the most significant benefits would be accrued by surviving partners at the top of the income distribution. Our proposed alternative scenario is better targeted at poorer households and achieves the objective of limiting poverty in widowhood at a substantially lower cost.
The Material Situation of Widows and Widowers in Poland
Numerous research papers show a strong impact of losing a spouse on mental health and overall well-being (Blanner Kristiansen et al., 2019; Lee et al., 2001; Ory & Huijts, 2015; Sasson & Umberson, 2014; Schaan, 2013; Siflinger, 2017; Steptoe et al., 2013). Adena et al. (2023) use a comprehensive dataset on older women observed a number of years before and after the death of their spouses. The study finds a sharp deterioration in mental health among widows after their partner’s death, displayed as a higher likelihood of crying (Figure 1a) or an increased probability of depression (Figure 1b). The authors provide evidence that, in comparison to similar women who remained partnered, widows suffer from poorer mental health and experience worsened quality of life for several years after their partners’ death.
Figure 1. Women’s mental health before and after their partners’ death.

Source: Adena et al. (2023). Notes: The control group consisted of women from statistical “twin” marriages with an identical distribution of selected characteristics; Figure 1b) Risk of depression defined as 4 or more depression symptoms according to the EURO-D scale. For methodological details see Adena et al. (2023).
While the impact of spouse’s death on widows mental health is largely undisputed, the impacts on their material situation are ambiguous (Ahn, 2005; Bíró, 2013; Bound et al., 1991; Corden et al., 2008; Hungerford, 2001).The differences across countries in the material situation of widowed versus partnered elderly people undoubtedly reflect countries’ various social security systems for those in widowhood. At the same time, these differences may also stem from variations in other factors that widows and widwers can rely on such as the prevalence of property ownership or accumulation of wealth and savings. It should be noted though, that in contrast to the immediate effects of spouse’s death on mental health, the consequences for widows’ and widowers’ material situation may unfold over a number of years. This is reflected in the results from poverty surveys which often point to the poorer material standing of widows and widowers (Panek et al., 2015; Petelczyc & Roicka, 2016; Timoszuk, 2017, 2021).
Similar conclusions can be derived from subjective evaluations of households’ material situation reflected in the Central Statistical Office’s Polish Household Budget Survey (HBS). In Figure 2a we present the percentage of people aged 65 and over who declared a ‘bad’ or ‘rather bad’ material situation of their household between 2010 and 2021, split between widows, widowers and married couples.. Throughout the analysed period, the share of both widows and widowers reporting a rather bad material situation was significantly higher than for married couples aged 65+. While in 2010 30 percent of widows and 20 percent of widowers reported a rather bad material standing, this share amounted to just above 10 percent among married couples. In all social groups the ratio of those in a rather bad material situation declined significantly over the analysed decade. A particularly significant drop was observed among widows; in 2021 the share of widows declaring a rather bad material situation declined to the level observed for married couples eleven years earlier.
Data capturing the risk of poverty from Eurostat, based on the EU Statistics on Income and Living Conditions Survey (EU-SILC), also display significantly worse material conditions of older individuals living alone compared to those living with another adult (Figure 2b). While this data does not explicitly allow us to divide the sample based on marital status, it is highly likely (and assumed hereafter) that the majority of single-person households 65+ cover widows or widowers, while two-person households aged 65+represent married couples. As compared to Figure 2a, the dynamics of the poverty levels among people aged 65+ in Figure 2b differ from the dynamics of the assessment of the overall material situation. Among two-person households, the risk of poverty in Poland declined between 2010 and 2013, and then remained relatively stable at about 15 percent until 2020. Among one-person households the poverty rate also declined during the first five years (from 33 percent in 2010 to 25 percent in 2015), however, it then increased to 37 percent in 2020. Consequently, the gap in poverty risk between two-person and one-person households increased substantially, from 8 percentage points in 2010 to 22 percentage points in 2020.
Figure 2. Material situation among households with individuals aged 65 and over.

Source: Own compilation based on: a) HBS; b) Eurostat. Notes: a) Widows and widowers aged 65+ living in one-person households; married couples living in two-person households with at least one spouse aged 65+; b) Eurostat data does not allow for division by gender or marital status. In two-person households both persons are adults, at least one is aged 65+. At-risk-of-poverty rate is defined as 60 percent of the median equivalized income of the entire population.
When analyzing poverty risk information, it should be noted that this indicator is based on income thresholds calculated separately for each year, accounting for the whole population. Poverty risk threshold may therefore increase as a result of income boosts among other groups and in consequence raise the risk of poverty of older people even if their real incomes are stable or grow. Thus the substantial increase in o the poverty risk share among Polish individuals 65+ and living alone after 2015, is related to the sharp rise in income of families with children and wage dynamics, which, in turn raised the poverty threshold considered in the analysis. Based on Figure 2b it is also worth noting that in comparison to Poland the risk of poverty among single-person households 65+ grew even faster in the Czech Republic (though the situation among two-person households 65+ was stable there). The relative position of these households deteriorated also in Germany (the share at risk of poverty increased from 24 percent in 2010 to 31 percent in 2020). It is therefore clear that even though absolute material conditions may have improved among widowed households in Poland over the last decade, their relative position in the income distribution – as in many other countries – places them at a significantly greater risk of poverty compared to partnered older individuals. Questions regarding the level of state support directed towards widowed older individuals are therefore highly relevant for government policy.
Figure 3. The living situation of widows, widowers and married couples aged 65 and over, in Poland.

Source: Own compilation based on HBS. Notes: Widows and widowers aged 65+ living in one-person households. Married couples in two-person households with at least one spouse aged 65+.
To better understand the broader context of material conditions in widowhood, and to try to address the discrepancy between the trends in subjective evaluation and widows’ relative position in the income distribution, it is also worth examining other aspects of material well-being. In Figure 3a we present some statistics on property ownership. As we can see, the majority of individuals aged 65+ in Poland, both widowed and married, owned the house or flat they lived in. For example, in 2010 62 percent of all widows and 68 percent of all widowers owned their dwelling, and these shares increased to 72 percent for both groups by 2021. Moreover, among older owner occupiers, the size of the house or apartment per person living in it was on average two times larger for widows and widowers (50 m2) as compared to married couples (25 m2), as depicted in Figure 3b. The high share of widows and widowers owning housing assets may therefore be one of the most important explanations to the discrepancies between the dynamics of income poverty and the declarations about the overall material situation observed in recent years. Although the risk of relative income poverty among widows and widowers have increased since 2016 (after a period of decline between 2010 and 2015), widowhood in Poland is not unequivocally associated with poor material conditions. While some widowed individuals clearly face a challenging material situation, for many the current system of survivor’s pension seems to offer adequate protection against the risk of a significant financial deterioration following the loss of a spouse. This suggests that any additional support through a new social security instrument should be directed principally to a relatively narrow group of widows and widowers in order to help particularly those in a difficult financial situation.
Survivor’s Pension, Widow’s Pension and an Alternative Solution
In this part of the paper we present simulations of changes in the level of household income and the relative position in the income distribution among widows under different scenarios of support through the social security system. In the first step we use the 2021 HBS data (uprated to 2023 income levels) to calculate disposable incomes of the entire sample of nearly 31 000 households under the 2024 Polish tax-benefit system using the SIMPL tax and benefit microsimulation model (henceforth the ‘baseline’ system; more details on the SIMPL model: Myck et al., 2015, 2023a; Myck & Najsztub, 2014). Based on the baseline system, we divide the households into ten income decile groups according to their disposable income (equivalised, i.e. adjusted for household composition). In the second step we focus on the sample of 4188 married couples aged 65 and over, representing 1.7 million Polish households (almost 13 percent of the total population). 65 percent of these couples lived in two-person households and the remaining 35 percent cohabited also with other people. In the baseline system, the incomes received by these households placed 9.5 percent of them in the lowest (1st) income decile group and 4.4 percent in the highest (10th) group (see Table 1).
Table 1. Relative position of households with married couples aged 65+ in the income distribution.

Source: Own calculations based on HBS 2021 using the SIMPL model. Notes: The baseline system for calculating the equivalised income thresholds was the January 2024 system; the thresholds for the income decile groups were calculated on the basis of a full sample of households.
Figure 4a shows a comparison of men’s and women’s gross retirement pensions in our sample of married couples 65+ in the baseline system. Every dot corresponds to one married couple and a combination of the spouses’ pensions. The greater concentration of combinations of these values above the 45-degree line indicates that in most marriages , the husbands’ retirement pensions are higher than the wives’. The differences are also apparent in Figure 4b, which presents the percentages of individuals receiving a pension benefit within the given value range of the pension. The share of women are greater than the share of men at lower benefit values (below 3000 PLN gross per month), and the opposite is true for higher pension amounts. Overall, for 65 percent of all couples, the husband received a higher retirement pension than his wife. There are also older people who did not receive retirement benefits – either because they continued to work or because they were not entitled to a retirement pension (this is the case for 9 percent of husbands and 10 percent of wives), as illustrated by the first column in Figure 4b. It is worth noting that for 2 percent of the couples only the husband received a retirement pension (the wife had never worked and was not eligible for retirement pension or she still worked). In the current Polish system of support for surviving spouses, the amount of own and spouse’s retirement pension is crucial for the choice of the benefit one makes when a spouse dies. A widowed person can choose to continue receiving their own full retirement pension or to receive a survivor’s pension, which is equivalent to 85 percent of the pension of the deceased spouse. Given the differences between men’s and women’s pensions, many women choose the latter option, either because their own retirement pension is significantly lower than the survivor’s pension or because they are not entitled to their own retirement pension.
Figure 4. Retirement pension amounts received by husbands and wives aged 65+

Source: Own compilation based on HBS 2021. Notes: Both spouses aged 65 and over; gross monthly retirement pensions; in less than 1 percent of the marriages at least one spouse received a retirement pension higher than 10000 PLN (not included in the Figure). 1PLN~0.23EUR.
We treat the sample of married couples aged 65 years or more as a reference sample in our analysis of the consequences from the implementation of various support schemes within the social security system, in the case of widowhood. The calculations presented below reflect the financial situation of the analyzed sample after the hypothetical death of husbands. We focus on widows, as they represent the vast majority of widowed individuals (due to, e.g., longer life expectancy of women and age differences between spouses). We simulate four support scenarios:
I) a system with no support for widowed individuals – this would be the situation without the current survivor’s pension, in which widows would need to rely fully on their own social security incomes (pensions);
II) the current system of survivor’s pension: in which the widow must choose between 100 percent of her own pension or the survivor’s pension (85 percent of her deceased husband’s gross pension)
III) a system with the widow’s pension (currently debated in the Polish Parliament): the widow must choose between: a) 100 percent of her own pension + 50 percent of the survivor’s pension (42,5 percent of the deceased husband’s gross pension), b) 50 percent of her own pension + 100 percent of the survivor’s pension (85 percent of her dead husband’s gross pension);
IV) an alternative system in which the widow chooses between: a) 100 percent of her own pension + 50 percent of a minimum pension if her husband received at least minimum retirement pension (50 percent of the husband’s pension if it was lower than the minimum pension), b) 100 percent of the survivor’s pension (85 percent of the husband’s pension) increased to the minimum pension if the husband received at least minimum retirement pension.
While the simulations are based on a hypothetical death of a husband, they provide a realistic picture of the financial situation of households in which women face widowhood. It is also important to note that the simulations of the financial conditions of ‘widowed’ households take into account other potential forms of public social support such as housing benefits and social assistance for low-income households. The results thus include the most relevant forms of financial support individuals might receive from the Polish government.
Figure 5 shows the results of the four aforementioned scenarios in the form of flow charts between income decile groups. The starting point (the left-hand side of each chart) are the income groups of households with married couples aged 65+, i.e. before the simulated widowhood. The transition to the income deciles on the right hand side of each chart is the result of a change in equivalised disposable income in the widowhood simulation, under different support scenarios (I – IV). Thus, on the right hand side we observe the income groups in which the women would find themselves after the death of their husbands, conditional on the assumed system of support: without the survivor’s pension (system I, Figure 5a), with the survivor’s pension (system II, figure 5b), with the widow’s pension (system III, Figure 5c) and under the alternative system (system IV, Figure 5d).
Figure 5a shows that without any additional support the financial situation of older women would significantly deteriorate in the event of the death of their spouses (Figure 5a). The share of women whose income would place them in the lowest two decile groups would be as high as 54.7 percent (compared to 17.5 percent of married couples), and 82.8 percent of the widows would be in the bottom half of the income distribution (compared to 57 percent of married couples). The current survivor’s pension seems to protect a large proportion of women (Figure 5b), although the proportion of those who find themselves in the lowest two income decile groups still more than doubles relative to the situation of married couples, to 38.3 percent. Further, 74.9 percent of the widows would find themselves in the bottom half of the distribution. The proposed widow’s pension (Figure 5c) offers much greater support with a very high share of new widows remaining in the same decile or even moving to a higher income group. For example, with the widows’ pension 8.0 percent of women would be in the 9th income decile group and 5.3 percent in the 10th group, while, in comparison, 7.0 percent and 4.4 percent of married couples found themselves in these groups, respectively.
Figure 5. Change in income decile among women aged 65+, following a hypothetical death of their husbands.

Source: Own calculations based on HBS 2021 using SIMPL model; graphs were created using: https://flourish.studio/
The proposed alternative system (Figure 5d) raises widows’ incomes compared to the current survivor’s pension system, but it is less generous than the system with the widow’s pension. Importantly however, it increases the incomes of widows in the lower income groups, which means that, compared to the current system, the number of women dropping to the poorest income groups following their husband’s death would be significantly reduced (24.0 percent would be in the lowest two deciles). At the same time 4.6 percent and 3.4 percent of the widows would be placed in the 9th and the 10th decile groups, respectively.
Table 2 shows the change in the poverty risk among the women in five considered scenarios, i.e. before they become widowed and after the hypothetical death of their husband under the considered four systems of support. 10.5 percent of married couples aged 65+ had equivalised disposable incomes which placed them below the poverty line calculated in the baseline system. After the simulated death of a husband, in a scenario without the survivor’s pension, the poverty rate among widows would increase to 35.3 percent, while the current survivor’s pension limits it to 20.7 percent. Poverty would be further reduced in the two systems with considered reforms: to 11.0 percent the widow’s pension system and to 11.8 percent in the alternative system.
Table 2. At-risk-of-poverty rates in the analysed scenarios.

Source: Own calculations based on HBS 2021 using the SIMPL model. Notes: The at-risk-of-poverty threshold is set at 60 percent of median equivalised disposable income in the baseline system.
Total Costs of the Considered Schemes
As mentioned above, the presented simulations take into account the conditions of current older couples. Therefore, we cannot directly calculate the consequences of the two suggested systems (the widow’s pension system and the alternative system) for those who are already widowed. This applies in particular to the present-day cost from the suggested changes to the widowhood support schemes to the public budget . In order to accurately estimate the changes in already widowed people’s incomes, we would have to have the information on the values of widow’s pensions and of pensions that their deceased spouses received when they were still alive, information that is not available in the HBS.
Nevertheless, our simulations allow us to compare the aggregated costs of support for women in the simulated widowhood scenarios under different support systems. Such calculations suggest that an implementation of the widow’s pension would increase the gross benefits received by widows by 34.2 percent compared to the current survivor’s pension system., while the alternative system would raise them by 14.7 percent. Applying these growth rates to the social security benefits currently received by widows and widowers (from the HBS data) implies additional annual costs of 24.1 bn PLN (5.6 bn EUR) under the widow’s pension system, and 10.5 bn PLN (2.5 bn EUR) under the alternative system.
Who Gains the Most?
From a distributional perspective, the simulated outcomes of the two suggested systems of support in widowhood can be compared to the baseline situation. In Figure 6 we show average changes in widowed women’s disposable income resulting from a change from the current system with survivor’s pension to the system with widow’s pension, and to our alternative design. Gross monthly survivor’s pensions of the widows are divided into seven groups, starting from 0-500 PLN up to 5501 PLN and more. One can clearly see that women who would, on average, gain the most from the implementation of the widow’s pension are those who already have a relatively high survivor’s pension in the current system. The average rise in disposable income (net) among those with gross monthly pensions between 4501 and 5500 PLN would be 1200 PLN, if widow’s pension was implemented. In contrast, women who receive 501-1500 PLN (gross) per month under the current survivor’s pension, would see a net monthly gain of about 350 PLN. These women would benefit slightly more under the alternative system – on average about 390 PLN, while much lower increases (on average about 220 PLN per month) would be faced by women in the 4501-5500 PLN group. Women in the last group, with gross monthly pensions of 5501 PLN and more under the current survivor’s pension system, would additionally gain even less in the alternative system – on average about 170 PLN. Thus overall, greater gains would accrue to those with lower current benefits in the alternative system.
Figure 6. Average increase in disposable income among widows by current survivor’s pensions’ value group.

Source: Own calculations based on HBS 2021 using the SIMPL model. Notes: Change in the disposable income with respect to the current system with survivor’s pension. 1PLN~0.23EUR.
In Figure 7 we categorise the sample of widows in terms of the range of their gains resulting from the two analysed reforms. The gains are calculated as changes in disposable income between the current system of support and the modelled reforms. We see that 20 percent of widows would gain over 1000 PLN extra per month as a result of the widow’s pension’s reform, while a further 24 percent would gain between 801 to 1000 PLN and 28 percent could expect to see a gain of between 601-800 PLN per month. The reform would leave the incomes of only about 12 percent of the widows unchanged – most of them are women who are not eligible for their own retirement pensions. In the alternative system the incomes of 34 percent of the analysed widows would remain unaffected. This group of women includes not only those without their own retirement pensions, but also those whose husbands received much higher pensions than themselves. This means that even if a widow’s retirement pension were to increase by 50 percent of the minimum pension, it would still be lower than 85 percent of her spouse’s retirement pension (see Figure 4a). In the alternative system about 17 percent of women in the sample would increase their disposable income by less than 400 PLN per month. For 28 percent, the increase would be in the range of between 400 and 600 PLN per month. While 21 percent would receive increased benefits under the alternative system, none of the hypothetical widows would receive more than 800 PLN per month.
Figure 7. Share of women by ranges of increases from the widow’s pension and the alternative scenario.

Source: Own calculations based on HBS 2021 using the SIMPL model. Notes: Change in the disposable income with respect to the current system with survivor’s pension. 1PLN~0.23EUR.
Figure 8 presents the average effect of the modelled reforms on disposable incomes of women in the sample, divided by income decile groups. Households were assigned to one of ten income groups based on their equivalised disposable income in the baseline system (i.e. according to the joint income of the couples). Figure 8 reflects the distribution of gains from the implementation of the widow’s pension or the alternative system. In the first case, the highest gains would be concentrated among the richest households. While women in the 8th and 9th income decile would, on average, receive an increase in their disposable income of about 1100 PLN per month, those in the 2nd decile group would, on average, receive only an additional 470 PLN per month. The distribution under the alternative system is far more concentrated on low income households. The highest average additional gain of about 420 PLN per month would be granted to widows from the 3rd income decile group, and benefits to women in the upper half of the income distribution would be significantly lower. Women in the top decile would gain, on average, only about 280 PLN per month. In many of the poorest households in our sample of couples, neither partner qualifies for a retirement pension. As a result, widows in this group would experience significantly lower average gains under both analyzed systems compared to those in higher income brackets.
Figure 8. Average gains due to the implementation of widow’s pension and the alternative system, by income decile group.

Source: Own calculations based on HBS 2021 using the SIMPL model. Notes: Change in the disposable income with respect to the current system with survivor’s pension. 1PLN~0.23EUR. Assignment to the income group was done prior to the hypothetical death of husbands.
Conclusion
In 2021 only 10 percent of the Polish widows and 8 percent of the Polish widowers aged 65 and more evaluated their material situation as rather bad, percentages that had dropped significantly since 2010. According to the HBS the majority of widowed individuals in Poland are also owners of the dwelling they live in. At the same time, income poverty among older persons living alone has increased in Poland since 2015, suggesting that despite the subjective evaluations, incomes of these older individuals – many of whom are widowed – have not managed to keep up with the dynamics of earnings and social transfers aimed at other demographic groups in Poland. As showed in our simulations, the current widowhood support system in Poland substantially limits the risk of poverty following the death of one’s partner. However, while the current survivor’s pension decreases the poverty risk from 35.3 percent (in a system without any support) to 20.7 percent, the risk of poverty among widows is still significantly higher compared to the risk faced by married couples.
The simulations analysed in this Policy Paper has covered the proposal of a support system reform, thewidow’s pension, which is currently discussed in the Polish Parliament. The simulations also covered an alternative alternative proposal putting more emphasis on poorer households. Both of these reforms would provide additional support to individuals affected by widowhood. In the case of the widow’s pension the average value of social security benefits would increase by 34.2 percent, whereas the alternative scenario would increase these benefits by 14.7 percent. If the pensions of current widows and widowers were to be increase by these proportions, the total annual cost to the public sector would amount to 24.1 bn PLN (5.6 bn EUR) and 10.5 bn PLN (2.5 bn EUR) per year, respectively. As shown above, the impact of these two reforms on poverty levels among widowed individuals would be very similar – the reforms would reduce it to 11.0 and 11.8 percent, respectively. The substantial difference in the total cost of these two alternatives is mainly due to the fact that the bulk of the additional benefits from the implementation of the widow’s pension is concentrated among high-income widows and widowers, while the highest profits in the modelled alternative system are targeted at households at the bottom of the income distribution.
If the aim of the potential legislative changes is to support widows and widowers in a difficult material situation and to reduce the extent of poverty, the widow’s pension currently discussed in the Polish Parliament seems to be far from ideal. As demonstrated in this Policy Paper, additional support addressed to widows and widowers in Poland can be designed in a way that substantially reduces the risk of poverty, with limitations on benefit increases to those already in a favourable financial situation. Our proposed alternative system would generate higher incomes for the poorest widows and widowers similar to the widow’s pension, while its cost to the public budget would be less than half of the cost of the discussed widow’s pension reform.
References
- Adena, M., Hamermesh, D., Myck, M., & Oczkowska, M. (2023). Home Alone: Widows’ Well-Being and Time. Journal of Happiness Studies. https://doi.org/10.1007/s10902-023-00622-w
- Ahn, N. (2005). Financial consequences of widowhood in Europe: Cross-country and gender differences.
- Bíró, A. (2013). Adverse effects of widowhood in Europe. Advances in Life Course Research, 18(1), 68–82. https://doi.org/10.1016/j.alcr.2012.10.005
- Blanner Kristiansen, C., Kjær, J. N., Hjorth, P., Andersen, K., & Prina, A. M. (2019). Prevalence of common mental disorders in widowhood: A systematic review and meta-analysis. Journal of Affective Disorders, 245, 1016–1023. https://doi.org/10.1016/j.jad.2018.11.088
- Bound, J., Duncan, G. J., Laren, D. S., & Oleinick, L. (1991). Poverty Dynamics in Widowhood. Journal of Gerontology, 46(3), S115–S124. https://doi.org/10.1093/geronj/46.3.S115
- Corden, A., Hirst, M., Nice, K., University of York, & Social Policy Research Unit. (2008). Financial implications of death of a partner. Social Policy Research Unit, University of York.
- Hungerford, T. L. (2001). The Economic Consequences of Widowhood on Elderly Women in the United States and Germany. The Gerontologist, 41(1), 103–110. https://doi.org/10.1093/geront/41.1.103
- Lee, G. R., DeMaris, A., Bavin, S., & Sullivan, R. (2001). Gender Differences in the Depressive Effect of Widowhood in Later Life. The Journals of Gerontology: Series B, 56(1), S56–S61. https://doi.org/10.1093/geronb/56.1.S56
- Myck, M., Król, A., Oczkowska, M., & Trzciński, K. (2023a). Komentarze Przedwyborcze CenEA 2023: Druga kadencja rządów Zjednoczonej Prawicy: Wsparcie rodzin w czasach wysokiej inflacji. https://cenea.org.pl/2023/09/13/wybory-parlamentarne-2023-w-polsce-komentarze-przedwyborcze-cenea/
- Myck, M., Król, A., Oczkowska, M., & Trzciński, K. (2023b). Komentarze Przedwyborcze CenEA 2023: Materiały metodyczne. https://cenea.org.pl/2023/09/13/wybory-parlamentarne-2023-w-polsce-komentarze-przedwyborcze-cenea/
- Myck, M., Michał Kundera, Najsztub, M., & Oczkowska, M. (2015). Przedwyborcze miliardy: Jak je wydać i skąd je wziąć (II; Raport Przedwyborczy CenEA 2015). CenEA. http://cenea.org.pl/Badania/Research/raportvat.html
- Myck, M., & Najsztub, M. (2014). Data and Model Cross-validation to Improve Accuracy ofMicrosimulation Results: Estimates for the Polish Household Budget Survey. International Journal of Microsimulation, 8(1), 33–66. https://doi.org/10.34196/ijm.00111
- Myck, M., Najsztub, M., Oczkowska, M., & Trzciński, K. (2019). Pakiet podatkowo-świadczeniowych rozwiązań rządu Zjednoczonej Prawicy. Raport Przedwyborczy CenEA 12/04/2019. https://cenea.org.pl/wp-content/uploads/2019/05/raportcenea12042019.pdf
- Ory, B., & Huijts, T. (2015). Widowhood and Well-being in Europe: The Role of National and Regional Context. Journal of Marriage and Family, 77(3), 730–746. https://doi.org/10.1111/jomf.12187
- Panek, T., Kotowska, I., & Sączewska-Piotrowska, A. (2015). Sytuacja materialna gospodarstw domowych osób starszych. W Rynek pracy i wykluczenie społeczne w kontekście percepcji Polaków. Diagnoza Społeczna 2015. Raport tematyczny. (s. 107–137).
- Petelczyc, J., & Roicka, P. (2016). Sytuacja kobiet w systemie emerytalnym. Instytut Spraw Publicznych. https://www.isp.org.pl/pl/publikacje/sytuacja-kobiet-w-systemie-emerytalnym
- Sasson, I., & Umberson, D. J. (2014). Widowhood and Depression: New Light on Gender Differences, Selection, and Psychological Adjustment. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 69B(1), 135–145. https://doi.org/10.1093/geronb/gbt058
- Schaan, B. (2013). Widowhood and Depression Among Older Europeans—The Role of Gender, Caregiving, Marital Quality, and Regional Context. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 68(3), 431–442. https://doi.org/10.1093/geronb/gbt015
- Siflinger, B. (2017). The Effect of Widowhood on Mental Health—An Analysis of Anticipation Patterns Surrounding the Death of a Spouse. Health Economics, 26(12), 1505–1523. https://doi.org/10.1002/hec.3443
- Steptoe, A., Shankar, A., Demakakos, P., & Wardle, J. (2013). Social isolation, loneliness, and all-cause mortality in older men and women. Proceedings of the National Academy of Sciences, 110(15), 5797–5801. https://doi.org/10.1073/pnas.1219686110
- Timoszuk, S. (2017). Wdowieństwo a sytuacja materialna kobiet w starszym wieku w Polsce. Studia Demograficzne, nr 2(172), 121–138. http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ekon-element-000171500466
- Timoszuk, S. (2021). Wdowieństwo w starszym wieku. O sytuacji finansowej wdów w Polsce.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Greening Politics – Navigating Environmental Policy Consistency Amidst Political Change

The Stockholm Institute of Transition Economics (SITE) and the Forum for Research on Eastern Europe: Climate and Environment (FREECE) would like to invite you to its 2024 SITE Energy Talk. This edition will address the complexities of upholding environmental policies amidst a changing political landscape.
In the ongoing battle against climate change, maintaining our environmental commitments is more crucial than ever. However, the evolving landscape of global politics, marked by shifting international relations and significant concerns regarding democratic regression, presents escalating challenges to the continuity of our environmental objectives and obligations. This year’s SITE Energy Talk will prioritize the identification of risks posed by political transitions to our environmental aspirations and explore strategies for maintaining the credibility of environmental policies in the face of political flux.
Speakers
Michaël Aklin
Michaël Aklin, Associate Professor of Economics and holder of the Chair of Policy & Sustainability (PASU) at the Swiss Federal Institute of Technology Lausanne, who will offer a broader European perspective.
Thomas Tangerås
Thomas Tangerås, Associate Professor, Program Director at the Research Institute of Industrial Economics (IFN), who will address the Swedish perspective on the issue.
Paweł Wróbel
Paweł Wróbel, Energy and climate regulatory affairs professional. Founder of GateBrussels and Managing Director of BalticWind.EU, who will present Polish perspective on green transition in the face of European and regional challenges.
Registration
The event will take place in room Torsten, Sveavägen 65, 113 50 Stockholm (the main building of SSE) and the registration opens at 11.45 near room Torsten.
The event will also be streamed online via Zoom for those who cannot join the event in person. Please register via the Trippus platform:
NOTE: A light lunch will be provided for those who pre-register for in-person participation.
Please contact site@hhs.se if you have any questions regarding the event.
Highlights from Previous SITE Energy Talk Events
SITE Energy Talk is an annual event. The purpose is to bring together scholars and practitioners to discuss recent developments in the energy markets and regulation, such as:
- Energy infrastructure resilience and sustainable future (2023)
- Energy storage: Opportunities and challenges (2021)
- Energy demand management from a behavioral perspective (2018)
- Technological development, geopolitical and environmental issues in our energy future (2017)
- The impact of the technology changes on the energy market (2016)
- Economic impacts of oil price fluctuations (2015)
Polish Parliamentary Elections 2023: Social Transfers and the Voters the Government is Counting On

The heated election campaign preceding the October 15th election in Poland has focused on fundamental issues related to the rule of law, migration, media freedom, women’s and minority rights, climate policy as well as Poland’s role on the international arena. The election outcome will determine Poland’s role in the EU and as well as the country’s future relations with Ukraine. It will also be decisive for the direction of Polish politics and the foundations of socio-economic development for many years to come. Despite these issues, the primary worries for a substantial portion of Polish households concern the domestic challenges of increasing prices and material uncertainty. With this in mind, this Policy Brief summarizes the results of CenEA’s recent analysis, which demonstrates a clear pattern in the United Right government’s policy, that in the last four years has strongly favored older groups of the Polish population. In the 2019 elections financial support directed to families with children was a key factor in securing a second term in office for the governing coalition. It remains to be seen if the focus on older voters pays off in the same way on October 15th.
Introduction
The upcoming parliamentary elections on October 15th will close a very special term of the Polish Parliament, marked by the Covid-19 pandemic, a surge in prices of goods and services, as well as the full-scale, ongoing Russian invasion of Ukraine and the tragic consequences associated with it. An evaluation of the second term of the United Right’s (Zjednoczona Prawica) government should, on the one hand, cover the most important decisions made in response to these crises. On the other hand, the last four years have also been a time of significant decisions with important medium- and long-term consequences, both directly for Polish households’ financial situation and more broadly for the economy at large and the country’s socio-economic development.
The heated election campaign has focused on the fundamental issues related to the rule of law, migration, media freedom, women’s and minority rights, climate policy as well as Poland’s role on the international arena. The upcoming vote is likely to be decisive in regard to Poland’s relations with partners in the EU, the role it will play in the EU and – as recent government declarations have demonstrated – the development of future relations with Ukraine. The result of the October elections will be pivotal also for the direction of Polish politics and the foundations of socio-economic development for many years to come. At the same time however, recent surveys have shown that the main concern for a significant part of the Polish society lies closer to home, driven by the challenges of rising prices of goods and services and related material uncertainty.
In light of this, this policy brief summarizes the tax and benefit policies directly affecting household finances, which were implemented in the first and second term of the United Right’s rule (i.e., 2015-2019 and 2019-2023). The brief draws upon a detailed analysis published recently in the CenEA Preelection Commentaries (Myck et al. 2023 a,b,c). The results show a notable shift in the government’s focus – while families with children were the main beneficiaries of the reforms implemented in the first term, the policies over the last four years have concentrated transfers and tax advantages to older generations. As we approach election day, it seems likely that the government will further try to mobilize support from this group of voters
The United Right’s Second Term: Tax and Benefit Reforms During High Inflation
In recent years, Polish households has, apart from two major crises (the Covid-19 pandemic and the complex consequences from the Russian invasion of Ukraine), faced one of the greatest price increases in the EU. During the closing term of Parliament, from January 2020 to July 2023, prices increased by 35.6 percent and have continued to grow at a rate significantly exceeding the inflation target set by the National Bank of Poland (2.5 percent +/- 1 percentage point per year). By the end of 2023 the combined inflation rate will reach 38.7 percent. Although average wages have also been rising (nominally by 41.7 percent from January 2023 to July 2023), wage growth has not kept up with the inflation for many workers. One needs to also bear in mind that a significant proportion of Polish households rely on income from transfers and state support. At the same time households’ material conditions have deteriorated as a result of a significant reduction in the real value of their savings.
In 2022 and 2023 the government introduced a number of temporary policies designed specifically to assist households facing higher energy and food prices. Throughout the final term in office, it also adopted several reforms which – as we show below – affected some groups more than others, reflecting a clear policy preference:
a) in January 2020 and May 2022 respectively, the government legislated an additional level of support addressed to retirees and disability pensioners. These so-called 13th and 14th pensions have raised the minimum level of pension benefits.
b) in January 2022 the government implemented a major overhaul of the income tax system (the so-called Polish Deal) which significantly influenced the tax burden on most taxpayers, strongly benefitting pension recipients.
c) throughout the term of Parliament, the government has kept the values of most social benefits frozen at their nominal level. This includes its flagship program – the universal 500+ parental benefit (500 PLN, roughly 110 EUR per child per month), introduced in 2016 – as well as means tested family benefits directed to poorer families with children. As a result, both the values as well as eligibility thresholds has fallen by nearly 40 percent.
The implications of these three policy areas are reported in Table 1 for the 2019-2023 term of Parliament and contrasted with benefits and costs from government policies implemented in the first term of Parliament (2015-2019). The results have been calculated using the SIMPL microsimulation model and are based on a representative sample of over 30 000 Polish households from the 2021 Household Budget Survey (for methodological details see Myck et al., 2015; 2023c). The applied method allows for singling out policy effects from other factors affecting household incomes.
Table 1 shows a clear difference in focus; from substantial benefits directed at families with children in 2015-2019 to policies targeted at pensioners, partly at the cost of families with children, in the second term. It is also worth noting that while government policy continued to increase household incomes, the resulting gains in disposable incomes in the second term have been much more modest.
Table 1. The impact of modelled policies in the tax and benefit system on household income in the two terms of the United Right’s government.

Source: CenEA – own calculations using the SIMPL model based on 2021 Household Budget Survey data (reweighted for simulation purposes and indexed to July 2023).
Notes: Simulations with respect to the system and price level from July 2023. Changes are presented in relation to the indexed system from 2015 for the first term of office of the United Right government and the indexed system from 2019 for the second term of office. *Including family allowance with supplements, care benefits, parental leave benefit, and one-off allowance for the birth of a child. The applied exchange rate is 4.6PLN=1EUR.
The contrast is also visible when the totals from Table 1 are divided and allocated to specific family types, as presented in Figure 1. On average lone parent families gained about 800 PLN (170 EUR) per month as a result of policies implemented in the 2015-2019 term, while they lost 160 PLN (35 EUR) in the second term. Married couples with children gained 950 PLN (205 EUR) and lost 259 PLN (55 EUR) in each term, respectively. In contrast to this, gains of pensioner families were modest during the first term, while the policies implemented in the second term imply gains of about 310 PLN (70 EUR) per month for single pensioners and 630 PLN (140 EUR) per month to pensioner couples. Gains and losses by family type resulting from policies implemented between 2019-2023 are shown in more detail in Figure 2. Over 85 percent of single pensioners have seen gains of more than 200 PLN (45 EUR) per month, and a similar proportion of pensioner couples gained over 400 PLN (90 EUR) per month. At the same time the majority of families with children, both among lone parent families and married couples, principally as a result of benefit freezes, saw their incomes fall in real terms. The values of the universal 500+ parental benefit will be indexed in January 2024, and the government has made this indexation an important element of the campaign. However, the indexation will not compensate the losses that families experienced in the last four years, a period with high inflation. It remains to be seen if a promise of higher transfers in the future will translate into political support, as seen in the 2019 elections (Gromadzki et al. 2022).
Figure 1. The impact of modelled policies in the tax and benefit system on household income in the two terms of the United Right’s government, by family types.

Source: CenEA – own calculations using the SIMPL microsimulation model based on 2021 Household Budget Survey data (reweighted for simulation purposes and indexed to July 2023).
Figure 2. Ranges of monthly benefits and losses resulting from the modelled policies introduced in the United Right government’s second term of office (2019-2023), by family type.

Source: CenEA – own calculations using the SIMPL microsimulation model based on 2021 Household Budget Survey data (reweighted for simulation purposes and indexed to July 2023).
Timing and Other Tricks: Securing the Votes of Older Generations
The so-called 13th and 14th pensions are paid once per year, in May and September respectively, to recipients of public pensions, at a value equivalent to a monthly minimum pension (approximately 360 EUR). While the first is a universal benefit, the latter has a withdrawal threshold and is thus targeted at lower income pensioners. In 2023 the government decided to increase the value of the 14th pension to about 580 EUR, with the benefits paid out to pensioners in September, the month before the election. This additional bonus came at the cost of about 7 billion PLN (1.6 billion EUR) – a budget which could have paid for two years of indexation of benefits targeted at low-income families with children or financed the payment of the indexed value of the universal 500+ parental benefit for nearly four months. The decision completes the picture of a clear preference for the older generation in regard to social policy in recent years and suggests a clear focus on this group of voters prior to the upcoming election.
The government has also taken a number of steps to facilitate electoral participation among voters in smaller communities by increasing the number of polling stations and making it obligatory for local administrations to finance transportation for older individuals with mobility limitations. The government is also mobilizing voters in smaller communities with turn-out competition initiatives. Additionally, some commentators have pointed out that the choice of election day – one day ahead of the so-called ‘Papal day’, devoted to the memory of John Paul II – is also non-accidental.
Conclusion
The analysis presented in the recent CenEA Preelection Commentaries and summarized in this brief indicates that in the area of reforms directly affecting household incomes, pensioners are the social group that benefited most from the United Right’s government policies in the 2019-2023 term of office. This is evident both from policies that have become a permanent feature of the Polish tax and benefit system, as well as from various one-off decisions. Taking into account other policies surrounding the approaching parliamentary election, it seems clear that the government is strongly counting on the support of older generations of voters on October 15th. As election day is approaching it becomes more and more evident though, that securing their vote may not suffice to win a third term in office. Numerous policy and corruption scandals, a significant departure from judicial independence and an extreme degree of governing party dominance in public media have come to the fore of public debate ahead of the vote. According to recent polls the final outcome is still uncertain and even small shifts in support might swing the future parliamentary majority. According to Gromadzki et al. (2022), financial support directed to families with children was a key factor for securing a second term in office for the United Right coalition four years ago. It remains to be seen if the policy focus on older voters pays off in the same way on October 15th.
Acknowledgement
The authors wish to acknowledge the support of the Swedish International Development Cooperation Agency (Sida) under the FROGEE and FROMDEE projects. FREE Policy Briefs contribute to the discussion on socio-economic development in the Central and Eastern Europe. For more information, please visit www.freepolicybriefs.com.
References
- Gromadzki, J., Sałach, K., Brzezinski, M. (2022). When Populists Deliver on their Promises: the Electoral Effects of a Large Cash Transfer Program in Poland. http://dx.doi.org/10.2139/ssrn.4013558
- Myck, M., Król, A, Oczkowska, M., Trzciński, K. (2023a). Druga kadencja rządów Zjednoczonej Prawicy: wsparcie rodzin z dziećmi w czasach wysokiej inflacji [The second term of the United Right’s rule: support to families with children in times of high inflation]. CenEA Preelection Commentary 13.09.2023. https://cenea.org.pl/2023/09/13/wybory-parlamentarne-2023-w-polsce-komentarze-przedwyborcze-cenea/
- Myck, M., Król, A, Oczkowska, M., Trzciński, K. (2023b). Druga kadencja rządów Zjednoczonej Prawicy: kto zyskał, a kto stracił? [The second term of the United Right’s rule: who gained and who lost?] CenEA Preelection Commentary, 14.09.2023. https://cenea.org.pl/2023/09/13/wybory-parlamentarne-2023-w-polsce-komentarze-przedwyborcze-cenea/
- Myck, M., Król, A, Oczkowska, M., Trzciński, K. (2023c). Materiały metodyczne [Methodology volume]. https://cenea.org.pl/2023/09/13/wybory-parlamentarne-2023-w-polsce-komentarze-przedwyborcze-cenea/
- Myck, M., Kundera, M., Najsztub, M., Oczkowska, M. (2015). Dwie kadencje w polityce podatkowo-świadczeniowej: programy wyborcze i ich realizacja w latach 2007-2015. IV Raport Przedwyborczy CenEA. (Two terms of the tax-benefit policies: electoral promises and their realization in years 2007-2015. IV CenEA Preelection Report.) https://cenea.org.pl/pl/2015/09/03/dwie-kadencje-w-polityce-podatkowoswiadczeniowej-programy-wyborcze-i-ich-realizacja-w-latach-2007-2015/
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.