Tag: Poland

Active Labor Market Policy in the Baltic-Black Sea Region

Image that shows an overhead view of a large, open pedestrian area with people walking and standing around representing active labour market policy.

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.


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).


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.


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

Image representing a woman and a young girl emphasizing the bond between the mother and child representing 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.


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.


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.


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.


Polish Parliamentary Elections 2023: Social Transfers and the Voters the Government is Counting On

20231009 Polish Parliamentary Elections Image 02

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.


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.


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.


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.


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.

What Can We Learn from Regional Patterns of Mortality During the Covid-19 Pandemic?

Doctor outside COVID-19 isolation center representing covid-19 pandemic mortality

Given the nature of the spread of the virus, strong regional patterns in fatal consequences of the Covid-19 pandemic are to be expected. This brief summarizes a detailed examination of the spatial correlation of deaths in the first year of the pandemic in two neighboring countries – Germany and Poland. Among high income European countries, these two seem particularly different in terms of the death toll associated with the pandemic, with many more excess deaths recorded in Poland as compared to Germany. Detailed spatial analysis of deaths at the regional level shows a consistent spatial pattern in deaths officially registered as related to Covid-19 in both countries. For excess deaths, however, we find a strong spatial correlation in Germany but little such evidence in Poland. These findings point towards important failures or neglect in the areas of healthcare and public health in Poland, which resulted in a massive loss of life.


While almost all European countries currently refrain from imposing any Covid-19 related restrictions, the pandemic still takes a huge economic, health and social toll across societies worldwide. The regional variation of incidence and different consequences of the pandemic, observed over time, should be examined to draw lessons for ongoing challenges and future pandemics. This brief outlines a recently published paper by Myck et al. (2023) in which we take a closer look at two neighboring countries, Germany and Poland.  Within the pool of high-income countries, these are particularly different in terms of the death toll associated with the Covid-19 pandemic. In 2020 in Poland, the excess deaths rate (with reference to the 2016-2019 average) was as high as 194 per 100,000 inhabitants, over 3 times higher than the 62 deaths per 100,000 inhabitants in Germany (EUROSTAT, 2022a, 2022b). While, in relative terms, the death toll officially registered as resulting from Covid-19 infections in 2020 was also higher in Poland than in Germany, the difference was considerably lower (about 75 vs 61 deaths per 100,000 inhabitants, respectively) (Ministry of Health, 2022; RKI, 2021). Population-wise Germany is 2.2 times larger than Poland and, before the pandemic struck, the countries differed also in other relevant dimensions related to the socio-demographic structure of the population, healthcare and public health. The nature of Covid-19 and the high degree of regional variation between and within the two countries along some crucial dimensions thus make Germany and Poland an interesting international case for comparison of the pandemic’s consequences. We show that the differences in the spatial pattern of deaths between Germany and Poland may provide valuable insight to the reasons behind the dramatic differences in the aggregate numbers of fatalities (Myck et al., 2023).

Regional Variation in Pandemic-Related Mortality and Pre-Pandemic Characteristics

We examine three measures of mortality in the first year of the Covid-19 pandemic in 401 German and 380 Polish counties (Kreise and powiats, respectively): the officially recorded Covid-19 deaths, the total numbers of excessive deaths (measured as the difference in the number of total deaths in year 2020 and the 2015-2019 average) and the difference between the two measures. Figure 1 shows the regional distribution of these three measures calculated per 1000 county inhabitants. All examined indicators were generally much higher in Poland as compared to Germany. In Poland, deaths officially registered as caused by Covid-19 were concentrated in the central and south-eastern regions (łódzkie and lubelskie voivodeships), while in Germany they were concentrated in the east and the south (Sachsen and Bayern). Excess mortality was predominantly high in German regions with high numbers of Covid-19 deaths, but also in nearby regions. As a result, these same regions also show greater differences between excessive deaths and Covid-19 deaths. On the contrary, high excessive deaths can be noted throughout Poland, including the regions where the number of Covid-19 deaths were lower. In the case of Poland, spatial clusters are much less obvious for both excess deaths and the difference between excess and Covid-19 deaths. To further explore the degree of regional variation between and within countries with respect to the mortality outcomes, we link them to regional characteristics such as population, healthcare and economic conditions, which might be relevant for both the spread of the virus and the risk of death from Covid-19. In Figure 2 we illustrate the scope of regional disparities with examples of (a) age structure of the population, (b) the pattern of economic activity and (c) distribution of healthcare facilities in years prior to the pandemic.

Figure 1. Regional variation of death incidence in 2020: Germany and Poland.

Note: The panels share a common legend based on the quintile distribution of Covid-19 deaths, with two additional categories added at the top and bottom of the scale. County borders in white, regional borders in yellow and country border in grey. Source: Myck et al. (2023).

Figure 2. Pre-pandemic regional variation of socio-economic indicators: Germany and Poland.

Note: Two top and bottom categories in the legend cover 10% of observations each, the rest of categories cover 20% of observations each. County borders in white, regional borders in yellow and country border in grey. Source: Myck et al. (2023).

Shares of older population groups (aged 85+ years) are clearly substantially higher in Germany compared to Poland, and within both countries these shares are higher in the eastern regions. On the other hand, the proportion of labor force employed in agriculture is significantly higher in Poland and heavily concentrated in the eastern parts of the country. In Germany, this share is much lower and more evenly spread. This indicator illustrates that socio-economic conditions in 2020 were still substantially different between the two countries. The share of employed in agriculture is also important from the point of view of pandemic risks – it reflects lower levels of education, and specific working conditions that make it challenging to work remotely yet entail less personal contact and more outdoor labor. The distribution of hospital beds reflects the urban/rural divide in both countries. It is also a good proxy for detailing the differences in the overall quality of healthcare between the two countries, i.e. displaying significantly better healthcare infrastructure in German counties.

Uncovering the Spatial Nature of Excess Deaths in Germany and Poland

While spatial similarities among regions are present along many dimensions, they are particularly important when discussing such phenomena as pandemics, when infection spread affects nearby regions more than distant ones. With regard to the spatial nature of excess deaths in the first year of the pandemic, a natural hypothesis is thus that the pattern of these deaths should reflect the nature of contagion. This applies primarily to excess deaths directly caused by the pandemic (deaths resulting from infection with the virus). At the same time, some indirect consequences of Covid-19 such as limitations on the availability of hospital places and medical procedures, or lack of medical personnel to treat patients not affected by Covid-19, are also expected to be greater in regions with a higher incidence of Covid-19. On the other hand, spatial patterns are much less obvious in cases where excess deaths would result, for example, from externally or self-imposed restrictions such as access to primary health care, reduced contact with other people, diminished family support, or mental health problems due to isolation. While these should also be regarded as indirect consequences of the pandemic, as they would arguably not have realized in its absence, these consequences do not necessarily relate to the actual spread of the virus. Our in-depth analysis of the spatial distribution of the three examined mortality-related measures, therefore, allows us to make a crucial distinction in possible explanations for the dramatic differences in the observed death toll in the first year of the pandemic in Germany and Poland. We explore the degree of spatial correlation in the three mortality outcomes using multivariate spatial autoregressive models, controlling for a number of local characteristics (for more details see Myck et al., 2023).

We find that in Germany, all mortality measures show very strong spatial correlation. In Poland, we also confirm statistically significant spatial correlation of Covid-19 deaths. However, we find no evidence for such spatial pattern either in the total excess deaths or in the difference between excess deaths and Covid-19 deaths. In other words, in Poland, the deaths over and above the official Covid-19 deaths do not reflect the features to be expected during a pandemic. As the results of the spatial analysis show, these findings cannot be explained by the regional pre-pandemic characteristics but require alternative explanations. This suggests that a high proportion of deaths results from a combination of policy deficits and individual reactions to the pandemic in Poland. Firstly, during the pandemic, individuals in Poland may have principally withdrawn from various healthcare interventions as a result of fear of infection. Secondly, those with serious health conditions unrelated to the pandemic may have received insufficient care during the Covid-19 crisis in Poland, and, as a consequence, died prematurely. This may have been a result of lower effectiveness of online medical consultations, excessive limitations to hospital admissions – unjustified from the point of view of the spread of the virus, and/or worsened access to healthcare services as a result of country-wide lockdowns and mobility limitations. The deaths could also have resulted from reduced direct contact with other people (including family and friends as well as care personnel) and mental health deterioration as a consequence of (self)isolation. Our analysis does not allow us to differentiate between these hypotheses, but the aggregate excess deaths data suggests that a combination of the above reasons came at a massive cost in terms of loss of lives. The consequences reflect a very particular type of healthcare policy failure or policy neglect in the first year of the pandemic in Poland.

Our study also shows that a detailed analysis of country differences concerning the consequences of the ongoing pandemic can serve as a platform to set and test hypotheses about the effectiveness of policy responses to better tackle future global health crises.


The authors wish to acknowledge the support of the German Research Foundation (DFG, project no: BR 38.6816-1) and the Polish National Science Centre (NCN, project no: 2018/31/G/HS4/01511) in the joint international Beethoven Classic 3 funding scheme – project AGE-WELL. For the full list of acknowledgements see Myck et al. (2023).


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.

Social Norms, Conspiracy Theories and Vaccine Scepticism: A Snapshot from the First Year of the Covid-19 Pandemic in Poland

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In January 2022, Poland experienced the highest rate of SARS-CoV-2 transmission since the beginning of the COVID-19 pandemic. Considering the widespread consensus among experts about the efficacy of vaccines in preventing hospitalisation and death resulting from the virus, low vaccination rates and widespread anti-vaccine sentiments in Poland are of great concern. We use data from the DIAGNOZA+ Survey to demonstrate the relationship between various demographic characteristics, opinions around certain gender norms, the propensity for conspiratorial thinking, concern about the pandemic, and vaccine scepticism. While controlling for exogenous demographic characteristics, we measure the strength of the relationship between various beliefs that people hold and how they feel about the COVID-19 vaccine. Our analysis indicates that while respondents who hold more traditional views on gender roles are 6 percentage points less likely to get vaccinated, those who agree with a variety of conspiratorial statements are 43 percentage points less likely to vaccinate against COVID-19.


As of January 2022, Europe finds itself well into the 4th wave of the COVID-19 pandemic, with some countries, including Poland, experiencing the highest rates of transmission since the virus was first detected. There are a few tools available to policymakers and healthcare professionals for combating the spread of the virus, ranging from preventative measures to strict social lockdowns aimed at reducing interpersonal interaction. A comprehensive literature review of 72 academic studies conducted by the BMJ found that the implementation of preventative measures such as hand washing, mask wearing, and social distancing decreased the risk of transmission by 53% (Talic et al., 2021). But even though such measures reduce transmission, the shortcomings in adherence and enforcement make high vaccination rates much more effective in diminishing the risk of hospitalization and death (Moline et al., 2021). With a consensus among experts reaffirming the effectiveness of vaccines in minimising the more severe cases of COVID-19 illness,  the widespread availability of the vaccine has become the most effective and cost-efficient tool in limiting morbidity while avoiding future instances of economically unsustainable lockdowns. The drawbacks of the alternative scenario have already been made evident in 2020, before the development and distribution of COVID-19 vaccines. Over the course of the year, hospital capacities were overwhelmed in many countries around the world, leading to significant spikes in excess deaths. Poland saw an increase of over 18% in all-cause mortality in 2020 (OECD, 2021), the fourth-highest in the OECD and second-highest in the European Union (Eurostat, 2021).

Considering the central role that prevalent vaccination plays in combating the impact of COVID-19, it is important to understand the underlying factors and demographic characteristics of individuals who are driving the low vaccination rates in countries such as Poland. With this in mind, we use an online survey: DIAGNOZA+ (DIAGNOZA Plus, 2020-2021), conducted on a representative sample of adults in Poland throughout the pandemic, allowing for the identification of characteristics that are most strongly correlated with vaccine scepticism. This kind of analysis can provide useful indicators for the targeting of certain policies and information campaigns that encourage vaccinations, and thereby suppress future outbreaks of SARS-CoV-2, as well as any other future pandemics. Below, we first outline the key features of the DIAGNOZA+ data, describe the methodology adopted in this study, and present results on the relationship between key demographic characteristics, social norms, views of respondents, and attitudes towards COVID-19 vaccination. We show a strong correlation between traditional family values, conspiratorial views, and reservations relating to the vaccination programme. Having traditional family values (expressed by about 40% of the sample) is associated with an over 10 percentage point (p.p.) lower probability to declare a willingness to get vaccinated. This drops to about 6 p.p. when we extend the model to account for conspiratorial thinking, which strongly dominates the relationship. Individuals who express strong conspiratorial and anti-establishment views (about a quarter of the sample), conditional on other demographic characteristics, were more than 40 p.p. less likely to declare a willingness to get vaccinated.


The following analysis is based on data from DIAGNOZA+, an online survey collected in seven waves over the course of the COVID-19 pandemic (DIAGNOZA Plus, 2020-2021). The panel survey was conducted with the purpose of assessing changes in the labour market situation of adults in Poland between April 2020 and July 2021. The survey consistently included standard questions on individual and household characteristics such as age, gender and education, as well as questions on as well as questions about the respondent’s labor market status, hours worked, and financial situation. Waves 3 and 4 included additional modules where respondents were asked to express their opinions on a variety of statements surrounding gender norms such as “In general, fathers are as well suited to look after their children as mothers”, “A pre-school child is likely to suffer if his or her mother works” and “When jobs are scarce, men should have more right to a job than women”. The questions were answered on a scale of 1 (strongly agree) to 4 (strongly disagree). For the analysis, these categorical variables are dichotomised, with a value of 1 assigned to responses 1 and 2 (strongly agree or agree) and a value of 0 assigned to responses 3 and 4 (disagree or strongly disagree). Thus, for each question, we develop a binary variable that categorises respondents as either having a progressive or traditional reaction to each particular gender norms statement.

In consecutive waves, the same respondents were asked questions surrounding their willingness to vaccinate against the virus (in wave 5) and their trust in experts and the government response to the COVID-19 pandemic (in wave 6). For this analysis, we select questions that may influence an individual’s likelihood to vaccinate, starting with their level of concern about the pandemic or their fear of the virus itself. Furthermore, we identify individuals with a high predisposition for conspiratorial beliefs based on information from wave 6. Each variable included in this module is converted into a binary measure of agreement or disagreement, as outlined above for the social norms questions. We consider seven statements from the survey related to conspiratorial views, including “Secret organisations influence political decisions” or “I trust my intuition more than the so-called experts” (see the full list of statements in Figure 2). For each of them, the variable is converted into a binary measure of agreement or disagreement, similarly to the social norms questions above. Those who agreed or strongly agreed with all seven statements are classified as having conspiratorial views.

Due to sample attrition and after dropping respondents who did not answer one (or more) of the questions needed for our analysis, the sample reduces to 726 individuals (see table A1 in the Annex). Although each wave of the DIAGNOZA+ survey is carefully weighted to ensure population representativeness of the survey, these cross-sectional weights are only relevant to each independent wave of the survey. Therefore, for our sample, we develop frequency weights by sex and age using population data from Statistics Poland (Statistics Poland, 2021), which are utilised throughout the analysis. Given the low number of participants in the oldest age groups (those above 60 years old), we limit the sample to individuals aged between 21 and 60. Unfortunately, calibrating the weights according to additional characteristics such as education and municipal population is not feasible with a sample of this size. Clearly, the requirement of consistent consecutive participation in at least three waves of the survey has implications for its representativeness. For example, after the sample of respondents that participated in wave 6 is cut to include only those who also participated in waves 3, 4 and 5, we observe a bias in favour of conspiratorial views among the remaining observations, indicating that individuals who hold these views were more likely to continue their participation in the survey. For example, while 18.1% of the total cross-sectional sample of individuals in wave 6 hold conspiratorial views, the proportion is 23.4% in the sample we analyse (falling slightly to 23.2% when weights are applied). From this perspective, while indicative of existing correlations, the results ought to be treated with some caution.

Limiting the sample to respondents who answered all sets of questions across several rounds of the survey allows us to study vaccine scepticism and respondents’ susceptibility to conspiracy theories in relation to a number of personal characteristics. Furthermore, we consider the relationship between a respondent’s attitudes towards certain social norms (asked in waves 3 and 4), their individual response to COVID-19 (asked in wave 5), and their trust in the government’s response to the pandemic (asked in wave 6). We begin the analysis by assessing the relationship between respondents’ demographic characteristics and their opinions on gender roles, their propensity to hold conspiratorial beliefs, and their concern about the pandemic. This is followed by two models measuring respondents’ willingness to vaccinate. In the first of these models, demographic characteristics and traditional family values are used as explanatory variables, while in the second model conspiratorial views are included as well. Finally, we conclude with a summary of results and policy considerations.

Survey Results

Traditional Family Values in Poland

The respondents of the DIAGNOZA+ survey vary, on average, in the ‘traditionality’ of their attitudes towards gender and family depending on the selected indicator. The shares of answers to the three questions about gender norms are presented in Figure 1. The results demonstrate that progressive views on gender norms in Poland were more common in relation to the workplace than the home and family. For example, the statement to which most respondents were opposed was “When jobs are scarce, men have more right to a job than women”, with 37.2% of respondents disagreeing and 50.3% of respondents strongly disagreeing. On the other hand, slightly fewer respondents disagreed (50.5%) or strongly disagreed (34.8%) with “In general, fathers are not as well suited to look after their children as mothers”. Finally, respondents were most ‘traditional’ in their views in reaction to the statement “A pre-school child is likely to suffer if his or her mother works”, with 28% agreeing and 10% strongly agreeing. There is a natural correlation between these different views, and in our analysis, we examine the significance of different combinations of the three indicators. Given the relatively small sample, only the last indicator proved to be significantly related to our main outcome of interest and we use this one to represent the view on the ‘progressive-traditional’ spectrum

 Figure 1. Gender norms in the survey sample

Source: DIAGNOZA+ survey, waves 3 and 4. Note: Data weighted using weights generated from Statistics Poland’s data on population by sex and age. Sample limited to individuals aged 21-60. The statement “In general, fathers are as well suited to look after their children as mothers” from the questionnaire was adjusted in the graph for better readability.

Conspiratorial Views

In wave 6 of the DIAGNOZA+ survey respondents were asked seven different questions relating to trust in government, politicians, media, and the recommendations of experts. As shown in Figure 2, for five out of the seven statements, a majority of respondents agreed or strongly agreed that the government or media are dishonest, intentionally share misinformation, or have ulterior motives. Nearly three quarters of respondents agreed that “politicians and the media deliberately hide certain information”. This result supports data published by the OECD in 2020 showing that, out of the 38 member countries, Poland had the second-lowest trust in government, with only 27.3% of the population expressing confidence (OECD, 2022). However, the DIAGNOZA+ survey goes further to find that nearly half of respondents in our sample reported that they trust their own intuitions more than the experts during the pandemic, while the least widespread belief out of the seven was that “secret organisations influence political decisions”. Still, even this statement, which suggests deep-seeded nefarious behaviour behind the scenes of government, found 39.8% of respondents to be in agreement. Note that we aim to identify individuals who have a general propensity for conspiratorial thinking, rather than those who simply find some of the statements particularly compelling. To this end, we only categorise those respondents who agreed with all seven statements as having a high propensity for conspiratorial thinking, which was the case for 23.2% of our sample after reweighting.

Figure 2. Conspiratorial beliefs and trust in authority

Source: DIAGNOZA+ survey, wave 6. Note: Data weighted using weights generated from Statistics Poland’s data on population by sex and age. Sample limited to individuals aged 21-60.


Table 1 presents regression results on the relationship between specific beliefs reported in the different waves of the survey and a number of individual characteristics. We show these results for three dependent variables: traditional family values, as defined by the opinion that a pre-school child is likely to suffer if his or her mother works; propensity for conspiratorial views, which identifies the respondents that agreed with all seven statements presented in Figure 2; and concern about the pandemic, a binary variable that identifies individuals who expressed great worry or fear about the pandemic. The results indicate that parents who live with their children are 10.1 p.p. more likely to hold traditional family values. After controlling for age, gender and education, living in a small town or village is associated with a 10.9 p.p higher probability of ascribing to more traditional gender norms, while individuals holding a tertiary degree are 18 p.p. less likely to agree that “a pre-school child is likely to suffer if his or her mother works” compared to those with primary education. Interestingly, neither age nor gender significantly correlates with family values, suggesting that the DIAGNOZA+ survey did not capture an intergenerational or gender-driven divide on these issues. This might relate to the online nature of the survey and the implied sample selection, in particular among older individuals.

 Table 1. Regression results on views and attitudes

Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Note: Data weighted using weights generated from Statistics Poland’s data on population by sex and age. Sample limited to individuals aged 21-60. Estimates using the linear probability model.

The results presented in Table 1 also demonstrate a relationship between some demographic characteristics and the likelihood to hold conspiratorial views (as defined by expressing agreement to the seven related statements in wave 6). A number of characteristics strongly correlate with conspiratorial thinking: being a parent living with their children aged 0-17, and living in small cities, towns and villages. Each of these characteristics is associated with a higher probability of believing in secret organisations and mistrusting experts. A number of characteristics strongly correlate with conspiratorial thinking: holding such views are 9.3 p.p. more likely among parents living with their underaged children and 10 p.p. more likely among individuals living in smaller towns or villages compared to those living in cities of over 500 thousand inhabitants. Higher education is strongly negatively correlated with the likelihood of holding conspiratorial views – those with tertiary education are 14.5 p.p. less likely to have these views compared to individuals with primary education.

One simple explanation for the increased vaccination rates among certain demographic groups in Poland could be that some segments of the population are more worried about the virus, and thus choose to take greater precautions. The analysis presented in Table 1 demonstrates that people were increasingly likely to be concerned about the pandemic in higher age groups. When asked “To what extent are you concerned about the COVID-19 pandemic?”, the probability of expressing serious concern increases progressively with age. This is an intuitive result considering the strong relationship between age and the severity of COVID-19 symptoms and the associated risk of mortality (CDC, 2021).  Respondents aged between 31 and 40 were 10 p.p. more likely to report being very concerned or frightened than respondents between the age of 21 and 30, while in the age groups 41-50 (12.6 p.p.) and 51-60 (21.4 p.p.) the probability was even higher. There is also a weak but positive correlation (7.7 and 8.6 p.p.) between living in a city with a population of 10,000 to 500,000 inhabitants and expressing fear about the pandemic, as compared to respondents who lived in cities with a population of more than 500,000 people. The relationships between the remaining demographic characteristics and the probability of being seriously concerned about the pandemic are not statistically significant. Below, we use this data to examine the link between people’s beliefs and the likelihood of getting vaccinated.

Vaccine Scepticism, Demographic Characteristics and Conspiratorial Views

In light of the widespread scientific consensus on the safety and effectiveness of COVID-19 vaccines, low vaccination rates in Poland are difficult to explain. In this section, we analyse to which extent they may be driven by the underlying beliefs, on top of the socio-demographic characteristics. Overall, 54% of respondents in the selected sample from the DIAGNOZA+ survey planned to be or had already been vaccinated. Thus, the survey sample closely reflects the actual proportion of the population that was fully vaccinated in Poland as of January 2022. (ECDC, 2022). In Model A of Table 2, we present the relationship between the response to the question “Do you plan to get vaccinated against COVID-19 or are you already vaccinated?” and traditional family values, alongside the usual demographic characteristics. We find that those in the 51-60 age group were 14.5 p.p. more likely to plan to vaccinate than those aged between 21 and 30. This also reflects the higher level of concern about the virus expressed by those over the age of 50, as presented in Table 1, and the risk of serious illness associated with increasing age. However, the relationship between age and the probability of vaccination was much weaker than the relationship between age and the probability of expressing general concern about the pandemic, implying that concern does not translate directly into a willingness to vaccinate. We also find that tertiary education has a particularly strong effect, and respondents who have a university degree were much more likely (17.7 p.p.) to get vaccinated than those with less than secondary education.

Through this analysis we also discover several less intuitive relationships between individual characteristics and the propensity to vaccinate. We find that women are 11.5 p.p. less likely to plan to vaccinate against COVID-19 than men. Moreover, individuals living in a city with less than 500,000 inhabitants were much less likely to vaccinate, with the strongest correlation (-23.5 p.p.) observed for respondents living in medium-sized cities of 100,000 to 500,000 people. However, a strong relationship can also be seen for smaller cities of 10,000 to 100,000 inhabitants (-19.3 p.p.) and small towns and villages (-17.2 p.p.). Respondents’ expressions of traditional family values are also a strong predictor of their propensity to vaccinate. After controlling for gender, age, education and municipality size, those categorised as holding traditional views are 10.6 p.p. less likely to plan to vaccinate against COVID-19. Our findings demonstrate that while population density, education, age and gender, are all strong indicators of vaccine scepticism in Poland, so is the degree of traditionalism in people’s beliefs.

Table 2. Regression results on vaccination: probability of being vaccinated or planning to get vaccinated

Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Note: Data weighted using weights generated from Statistics Poland’s data on population by sex and age. Sample limited to individuals aged 21-60. Estimates using the linear probability model.

A commonly cited explanatory factor for vaccine scepticism is the susceptibility to conspiratorial beliefs, as well as scepticism towards information disseminated by figures of authority (Hornsey et al., 2018). Thus, in Model B, we seek to identify a relationship between conspiratorial beliefs and scepticism towards the COVID-19 vaccine in Poland. When adding to our model a binary indicator for agreement with all seven of the conspiratorial statements included in the survey, we find that those who agreed across the board were 43.3 p.p. less likely to get vaccinated. Therefore, it seems that the propensity for conspiratorial thinking is a very strong correlate of willingness to vaccinate, and the characteristic most strongly associated with vaccine scepticism. The impact of the demographic factors goes in the same direction for both models, although the scale diminishes in Model B after controlling for conspiratorial views, reflecting the higher propensity of older individuals to hold such views. Furthermore, the effect of traditional family values is much weaker in Model B, suggesting a positive correlation between traditional family values and conspiratorial beliefs (Figure A1 in the Annex shows how values and views in the analysis views overlap with each other). This is in line with past research that ties traditional moral values and conservatism with conspiratorial beliefs, both before and during the COVID-19 pandemic (Pennycook et al., 2020; Romer and Jamieson, 2021).

One explanation for the strong relationship between conspiratorial beliefs and vaccine scepticism could be that respondents who do not trust the media and figures of authority believe that the dangers of the pandemic have been exaggerated and would thus not be concerned about its consequences. We account for this possibility in Model C by including the indicator for fear of the pandemic. We find that those who are very concerned or frightened are 21.1 p.p. more likely to vaccinate than those who are not. However, including this variable in the model has little effect on the estimates of the relationship between traditional gender views or conspiratorial thinking and the likelihood to vaccinate. Further research is needed to understand what is driving these relationships in this particular context. These findings demonstrate that while individuals that believe in conspiracies are the most susceptible to vaccine scepticism, other elements such as fear of the pandemic, education attainment, and where people live play an important role as well.


By January 2022 most European countries have reached a plateau in their vaccination rates, with free vaccines readily available since the summer months of 2021 to all those who are willing to take them. Not only have the high rates of hospital admissions among the non-vaccinated population proven the epidemiological models about the efficacy of vaccines in reducing hospitalisation and death to be true (a study in the United States showed a more than tenfold reduction in the risk of each measure; Scobie et al., 2021), but disparities between countries in the proportion of the population that is vaccinated have created a natural experiment that further substantiates this hypothesis. Poland, a country with a vaccination rate that is 15 p.p. lower than neighbouring Germany, had virtually the same number of cases per 100,000 people in the first two weeks of December, but almost threefold the number of deaths from COVID-19 (ECDC, 2021). Due to the burden COVID-19 related hospitalisations place on healthcare systems, the issues arising from the significant scale of vaccine scepticism are not only related to physical well-being, but also directly impact economic and fiscal stability.

Despite a fairly small sample size available for our analysis from the DIAGNOZA+ survey, a number of important correlations are identified in this study. We find that people living in cities and towns smaller than 500,000 people are less likely to vaccinate than those living in big cities. We show that women, those with less than secondary education, and young people are less likely to be vaccinated. Moreover, those believing that pre-school-aged children suffer when their mothers work are less likely to vaccinate compared to those with more progressive gender views. The most significant predictor of vaccine scepticism, however, is whether a respondent expressed low trust in authority and belief in the conspiracy theories presented in the survey, which was the case for 23.2% of the sample. These individuals are more than 40 p.p. less likely to express willingness to get vaccinated than the rest of the population. This suggests that the low rate of vaccination in Poland can, in part, be attributed to widespread distrust of government, the media, and scientific experts. Poland has already suffered the consequences of the high magnitude of anti-vaccine sentiments in the population, with the severity of the fourth wave of COVID-19 being one of the harshest in Europe (ECDC, 2021). If the government intends to prevent future outbreaks and protect the healthcare system and the economy, it must present a consistent, clear, and transparent message about the safety and efficiency of vaccines to minimise the misinformation that is driving vaccine scepticism among certain demographic groups.


Annex is available in the PDF version.


This Policy Paper was prepared under the FROGEE project, with financial support from the Swedish International Development Cooperation Agency (Sida). FROGEE papers contribute to the discussion of inequalities in Central and Eastern Europe.  For more information, please visit www.freepolicybriefs.com. The views presented in the Policy Paper reflect the opinions of the authors and do not necessarily overlap with the position of the FREE Network or Sida.

Ukrainian Refugees in Poland: Current Situation and What to Expect

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The 2022 Russian invasion of Ukraine has forced millions to flee from the war zone. This brief addresses Ukrainian refuge in Poland. It provides an overview of the current situation, discusses the ongoing solutions and potential future challenges, and stresses the key areas for urgent policy intervention. It is based on a presentation held at the FREE Network webinar Fleeing the war zone: Will open hearts be enough?, which took place on March 14, 2022. The full webinar can be seen here.

The latest data (from March 15, 2022) shows that since February 24, 1.8 million refugees have already crossed the Polish-Ukrainian border. This number represents over 60 percent of Ukrainians who have fled the country thus far. Among this group that relocated to Poland, approximately 97 percent were people with Ukrainian citizenship. Most of the foreign nationals living in Ukraine before the war, and who came to Poland after its outbreak, have already returned to their countries of origin.

Figure 1. The influx of refugees from Ukraine to Poland since February 24, 2022.

Note: The vertical axis shows the number of refugees per million. Source: Data from Polish Border Guard

Our estimates show that there are currently about 1.1 million Ukrainian war refugees in Poland. Many stay in large cities such as Warsaw, Kraków or Wrocław. The rest of those who crossed the Polish border transited to the other EU Member States or countries outside of Europe, such as Canada or the USA, reuniting with their families and friends.

In the first days after the outbreak of the war, refugee assistance in Poland was mostly provided by Polish families and households, as well as owners of guesthouses and hotels who made them available for the purpose of providing accommodation.

A similar situation took place at the border and at railway and bus stations where refugees were arriving, with a majority of support coming from volunteering citizens. This assistance largely consisted of the provision of basic necessities such as food, hygiene products, and medical or psychological first aid. The level of mobilization among non-governmental organizations, grass-roots initiatives, private citizens, and civil society, in general, is extremely commendable and should be accredited with providing the safe welcome refugees received upon arrival. For example, during the first days, Polish families sheltered several hundred thousand refugees, often in their own houses or apartments. There are currently two main Ukrainian social groups arriving in Poland: women with children and older persons over the age of 60. This is a result of Ukraine’s internal regulations, which prohibit men aged between 18 and 60 from leaving the country.

Among those who have managed to escape the war, there is a large group of people requiring very specialized support, e.g. children suffering from oncological diseases, and elderly with a high degree of disability. So far, these groups have been provided with the necessary support, but if these needs become more frequent, a review of the capacity of the Polish healthcare system and the system of support for the disabled will be needed.

In the first days after the war broke out, the situation at the border was very difficult. The waiting time for crossing reached up to 70 hours. However, this was related to problems with the information system and the limited number of border guards on the Ukrainian side. Currently, crossing the border is quick and seamless. Every day the Polish Border Police register 80 to 100 thousand individuals, a vast majority of them crossing into Poland. This is a many-fold increase compared to pre-war migration flows, which fluctuated around 12-15 thousand people per day. At the same time, over 80.000 people, mainly men, have crossed the Polish border to Ukraine in the last 20 days with the goal of joining the army or territorial defense.

For a long time, the Polish government held the position that there would be no need to build refugee centers. However, the government recently reversed this decision and decided to open a dozen centers, located in market and sports halls. Currently, over 100,000 people are staying in these types of temporary accommodation facilities. However, these centers are not sufficiently adapted for stays longer than a few days. It is necessary to prepare housing infrastructure (temporary accommodation centers equipped with habitable containers) in which refugees can stay for two or three months until they find another place to live.

So far, Poland has essentially dealt with two of three possible migratory waves. In the first, people with family members or friends living in Poland or in other EU Member States arrived. Before the war, there were already approximately 800 thousand Ukrainians working or studying in Poland. In the second wave, after the bombing of civilian facilities in large cities, people without family or friends living in Poland started arriving. They require full assistance. A third wave is possible, and this one may be much larger than the previous two. It may occur if the situation at the front worsens and the repressions by Russian troops become harsher. Such reports are already coming from eastern Ukraine. If the situation worsens, Poland could even face a couple of additional million people that would leave Ukraine. Under these circumstances, we should assume that the third wave would include young men in addition to women, children, and the elderly. This scenario is currently very unlikely, but cannot be completely ruled out.

Since the beginning of March, Poland has seen an increase in the activity of both local representatives of the government administration and the central government. Information has been gathered about vacancies in smaller cities and local communities where refugees could be accommodated. This is because large cities are on the verge of reaching their capacity for the number of refugees they are able to manage. In addition, a special law entered into force on March 13, which provides for a catalogue of support tools for refugees. The main issues are:

1. The possibility of obtaining an individual identification number, which will enable the opening of a bank account and grant access to the labor market, education, and social benefits. It will be possible to apply for the ID number from March 16. Certainly, large queues can be expected in the first days, as the procedure is complicated and rather bureaucratic. The government decided to require all the necessary information at the start of the application process, which could be complicated for some applicants and lead to additional delays. Based on recent numbers, up to 1 million Ukrainians may apply for an individual identification number in the near future.

2. Reimbursement of the costs of hosting refugees from Ukraine in Polish family homes and in private hotels. The government has agreed to cover the value of around 8 euros per day for each person. However, receiving this refund requires submitting a special application to the local administration offices, which may again cause various kinds of perturbations, and even resignation from obtaining such support.

3. Ukrainian children can be enrolled in Polish schools. It will also be possible to open school branches in temporary accommodation centers, as well as parallel Ukrainian classes inside Polish schools. At present, however, the preferred model is the inclusion of Ukrainian children in Polish classrooms. Currently, no major problems have been reported with this process, but only around 10% of Ukrainian children have entered Polish schools so far. Numerous challenges connected with this integration process are expected. Part of the solution could be distance learning or hybrid learning. The priority is to involve children in education as fast as possible so that they do not lose time while living in Poland from an educational development point of view.

4. A simplified system of qualifications recognition has been implemented for nurses and doctors. Unfortunately, contrary to the advice of experts, the act does not provide guidelines for a simplified qualification recognition of teachers, educators or psychologists from Ukraine. In his media statements, the Minister of Education and Science did not rule out introducing a simplified procedure in the near future. Such recognition could, to some extent, solve the problem of understaffing in Polish schools.

5. All adults from Ukraine who arrived after February 24 have open access to the labor market.

Until early March, the Polish government did not apply for support from other EU member states. Now, this position has changed. Over the first weekend of March alone, more than 20 trains were organized that made it possible for refugees interested in moving from Poland to countries such as Germany or other destinations within the EU. Additional relocation measures are expected in the near future. However, in contrast to the European migrant crisis in 2015, the relocation scheme of Ukrainian refugees is carried out on a voluntary, rather than a compulsory basis.

It is very difficult to predict what will happen in the next days or weeks. While it should be emphasized that Poland is managing the migration challenge well, this is not least due to the exceptional commitment of civil society. Certainly, in the coming months, Poland will not be able to cope with the integration of more than 800.000 people into the labor market and education system. Of course, it is possible to provide ad-hoc support, but that is completely different than integrating refugees into Polish society. Ukrainians are still treated as guests who are expected to return to their homes when possible. Such an assumption should not be changed until May when the situation in Ukraine will be more predictable. We must also be aware that we are dealing with dispersed families who will want to reunite as soon as possible. It is not known, however, whether this will take place in Poland or in Ukraine. It depends on how the situation develops in the weeks and months to come.

In the coming weeks, the key issue will be the relocation of Ukrainian refugees from large to smaller cities within not only Poland but also the European Union. It is absolutely necessary to coordinate activities both at the level of the Polish government and the European Commission. As far as the Polish government is concerned, a task force should be established to maintain constant contact with the European Commission and the EU Member States regarding the ability to relocate refugees from Poland to other countries. This team should be composed mainly of civil servants from the Ministry of Foreign Affairs and the Ministry of the Interior. It is also necessary to appoint a team coordinating the actions of voivodes, who are responsible for crisis management in accordance with Polish law. It is also critical to ensure the flow of information between local administrations and the government, as well as to coordinate the activities of non-governmental organizations, whose activity is key in dealing with the challenges related to the migration crisis. In the next stages, it will be necessary to adopt a systemic approach to the inclusion of Ukrainian children in the education system (Polish and Ukrainian, but functioning in Poland – remote learning), and adult refugees to the labor market.

In the end, I would like to recall my opinion, which is now popular in the media and among representatives of the central government, local governments and non-governmental organizations: “Helping refugees and managing migration crises is a marathon, not a sprint.” We must keep this in mind.

The webinar “Fleeing the war zone: Will open hearts be enough?”, was hosted by the FREE Network together with the Stockholm Institute of Transition Economics (SITE) and can be seen here.

Five Years in Operation: the Polish Universal Child Benefit

Family in the golden hour representing Child Benefits

Over the last five years, Polish families with children have been entitled to a relatively generous benefit of approximately €110 per month and child. Initially granted for every second and subsequent child in the family regardless of income and for the first child for low-income families, the benefit was made fully universal in 2019. With the total costs amounting to as much as 1.7% of Poland’s GDP, the benefit reaches the parents of 6.7 million children and significantly affects these families’ position in the income distribution. Its introduction has led to a substantial reduction in the number of children living in poverty. However, since families with children are more likely to be among households in the upper half of the income distribution, out of the total cost of the benefit, a proportionally greater share ends up in the wallets of high-income families. While the implementation of the benefit has significantly changed the scope of public support to families in Poland, there are many lessons to be learnt and some important revisions to be undertaken to achieve an effective and comprehensive support system.


One of the principal commitments in the 2015 Polish parliamentary elections of the then-main opposition party – Law and Justice (Prawo i Sprawiedliwość, PiS), was introducing a generous child benefit. The purpose of this benefit was to support families and encourage higher fertility, which had been one of the lowest in the European Union for a long time. Following PiS’s electoral victory, the new government introduced a semi-universal child benefit of approximately €110 per month (exactly 500 PLN per month, thus the Polish nickname of “the 500+ benefit”) in April 2016. Initially, the benefit was granted for every second and subsequent child in the family regardless of income and for the first child in low-income families. Since July 2019 (nota bene three months before the next parliamentary elections), it was made universal – all parents with children under the age of 18 are entitled to 500PLN per month for every child.  The benefit is relatively generous (for comparison, it accounts for 17.9% of the minimum wage in Poland in 2021), and universal coverage implies substantial costs for the government budget, totalling about 41bn PLN per year (1.7% of the Polish GDP).

Over the last five years, a number of analyses of the consequences of the benefit’s introduction have been conducted. These have encompassed a variety of socio-economic outcomes for Polish families with children – from a comprehensive assessment of these consequences (Magda et al. 2019) to analyses focused on specific effects of the benefit, such as the impact on women’s economic activity (Magda et al. 2018, Myck 2016, Myck and Trzciński 2019) or poverty (Brzeziński and Najsztub 2017, Szarfenberg 2017). The fifth anniversary of the benefit’s implementation seems to be a good opportunity for a summary and update of previous evaluations of the distributional consequences and financial gains for households resulting from this policy (an overview of all the previous CenEA analyses of the child benefit can be found in CenEA 2021). The results presented in this brief are based on analyses conducted using the Polish microsimulation model SIMPL on data from the 2019 CSO Household Budget Survey (more details in Myck et al. 2021). It should be noted that the analyses do not account for the impact of the Covid-19 pandemic on the material situation of households, as the data was collected before the outbreak. As previous studies suggest, the consequences for households of the pandemic and the series of resulting lockdowns varied greatly depending on various factors, such as the sources of income, sector, and form of employment, thus making it impossible to estimate precisely (Myck et al. 2020a).

The Child Benefit on Household Incomes

Due to its universal character, the distributional consequences of the child benefit payments are directly related to the position of households with children aged 0-17 in the income distribution relative to those without. As households with children are more likely to be in the upper half of the distribution (taking into account the demographic structure of households through income equivalisation), out of the total budget expenditure on the benefit, a proportionally greater share goes to high-income families (Table 1). Families with children in the two highest income decile groups (i.e., belonging to the 20% of households with the highest income) currently receive almost 25% of the total annual expenditure on the child benefit. On the other hand, among the 20% of households with the lowest incomes, families with children receive only 11.7% of the total annual cost of the benefit.

Table 1. Household gains resulting from the child benefit by income decile groups

Source: Myck et al. 2021. Notes: Income decile groups – ten groups each covering 10% of the population, from households (HH) with the lowest disposable income to the most affluent households, calculated on the basis of equivalised incomes.

Compared to the poorest 10% of households, families with children in the highest income decile receive 2.5 times more of the total funds allocated to the benefit.

It is also worth noting that the proportion of benefit in the disposable income is relatively evenly distributed if one considers all households in a given decile (with and without children). The proportional benefits in the first nine income deciles are in the range of 3.4% and 5.3% and only fall to 1.9% in the highest income group. A significant differentiation of the benefit in proportional terms can only be seen when accounting solely for households with children within each income decile. The benefit amounts to as much as 26.9% of the disposable income of households with children in the first decile, and the effect falls in subsequent groups – from 18.9% and 16.4% in the second and third deciles, to only 4.1% in the top decile.

The Child Benefit and the Position of Families With Children in the Income Distribution

Taking into account the magnitude of the policy, the position of families with children in the income distribution relative to other households may, to some extent, be the result of receiving the benefit itself. It is, therefore, reasonable to ask what role the benefit plays in shaping this relative position in the income distribution. Figure 1 presents the number of children under 18 in households by income decile groups when the benefit is included in total household income (left panel) and in a hypothetical scenario when the child benefit payment is withdrawn (right panel). As we can see, the withdrawal of the benefit would cause a substantial change in the relative position of families with children in the income distribution, significantly increasing the number of children in the lowest income groups. While in the current system, the poorest 10% of households include 342 thousand children aged 0-17, this number would be 553 thousand in a system without the benefit. However, the benefit also changes the relative position of high-income households with children. In the current system, the richest 10% of households include 762 thousand children. Subtracting the benefit from their household income would reduce this number to 687 thousand.

Figure 1. The child benefit and its impact on the position of families with children in the income distribution

Source: Myck et al. 2021.

Thus, even when taking into account the income distribution without the benefit, the number of children among the richest 10% of households is almost 25% higher than the number of children in the poorest 10% of households. Looking at the income distribution after including the benefit, there are more than twice as many children in the richest 10% of households than among the poorest 10%. This, in turn, inevitably means that, out of the total cost of the benefit, over twice as much money is transferred to households belonging to the richest deciles as compared to the funds transferred to families belonging to the poorest 10% of households.


With the total costs amounting to 1.7% of Poland’s GDP, the child benefit introduced in April 2016 substantially raised the level of direct financial support for families with children. As shown in this brief, the benefit reaches the parents of 6.7 million children aged 0-17 and significantly affects the position of these families in the income distribution. While, on the one hand, a large proportion of families with children have incomes high enough to be in the highest income groups even without this support , the lowest decile group would include over 200 thousand more children in the absence of the benefit. This confirms that the child benefit alone contributes to a significant improvement in the material conditions of families with children and to a significant reduction in poverty (cf. Brzezinski and Najsztub, 2017; Szarfenberg, 2017). However, the scale of this reduction is modest given the size of the resources involved. This is not surprising given that the bulk of the total costs of the benefit comes from the 2019 program extension to cover all children regardless of family incomes, which largely ended up in the wallets of higher-income families (Myck et al. 2020b). One of the key goals of the benefit upon introduction was to increase the number of births in Poland by easing the material conditions of families with children. Yet despite a radical increase in the level of support, the number of births in Poland over the period 2017-2020 has essentially remained the same as that forecasted by the Central Statistical Office in its long-term population projection of 2014 (Myck et al. 2021). It is thus difficult to consider the benefit a success in terms of this major objective. Moreover, the withdrawal of the income threshold has largely eliminated the negative disincentive effects of the benefit with regard to employment (Myck and Trzcinski 2019). However, it is unclear whether the post-pandemic economic situation will allow for an increase in female labour force participation, which declined following the introduction of the benefit in 2016 (Magda et al., 2018).

The effects of every socio-economic programme should be assessed by comparing cost-equivalent alternatives. Despite all gains the “500+” child benefit has brought to millions of families in Poland over the last five years, the flagship programme of the ruling Law and Justice party does not fare well in this perspective. The need for change seems much broader than the reform of the benefit alone. The benefit was introduced on top of two other financial support mechanisms focused on families with children, namely family allowances and child tax credits, and the three elements have been operating in parallel since 2016. A number of suggestions on creating a streamlined, comprehensive system have been made a long time ago (e.g., Myck et al. 2016). However, a major restructuring of the entire support system with clearly defined socio-economic policy goals in mind seems all the more justified now, when many families may require additional assistance due to the difficult financial situation related to the Covid-19 pandemic.


This Policy Brief draws on the CenEA Commentary published on 31.03.2021 (Myck et al. 2021). It has been prepared under the FROGEE project, with financial support from the Swedish International Development Cooperation Agency (Sida). 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.


  • Brzeziński, M., Najsztub, M. 2017. The impact of „Family 500+” programme on household incomes, poverty and inequality”, Polityka Społeczna44(1): 16-25.
  • CenEA 2021. Childcare benefit 500+ in CenEA analyses. https://cenea.org.pl/2021/04/06/childcare-benefit-500-in-cenea-analyses/
  • Magda, I., Brzeziński, M., Chłoń-Domińczak, A., Kotowska, I.E., Myck, M., Najsztub, M., Tyrowicz, J. 2019. „Rodzina 500+– ocena programu i propozycje zmian. (“Child benefit 500+: the evaluation of the programme and suggestions for changes”), IBS report.
  • Magda, I., Kiełczewska, A., Brandt, N. 2018. “The Effects of Large Universal Child Benefits on Female Labour Supply”, IZA Discussion Paper No. 11652.
  • Myck, M. 2016. “Estimating Labour Supply Response to the Introduction of the Family 500+ Programme”. CenEA Working Paper 1/2016.
  • Myck, M., Król, A., Oczkowska, M., Trzciński, K. 2021. “Świadczenie wychowawcze po pięciu latach: 500 plus ile?”(„The child benefit after 5 years – 500 plus what?”), CenEA Commentary 31/03/2021.
  • Myck, M., Kundera, M., Najsztub, M., Oczkowska, M. 2016. „25 miliardów złotych dla rodzin z dziećmi: projekt Rodzina 500+ i możliwości modyfikacji systemu wsparcia” („25 billion PLN to families with children: Family 500+ programme and possible modifications of the family support system”),  CenEA Commentary 18/01/2016.
  • Myck, M., Oczkowska, M., Trzciński, K. 2020a. “Household exposure to financial risks: the first wave of impact from COVID-19 on the economy”, CenEA Commentary 23/03/2020.
  • Myck, M., Oczkowska, M., Trzciński, K. 2020b. „Kwota wolna od podatku i świadczenie wychowawcze 500+ po pięciu latach od prezydenckich deklaracji” („Tax credit and child benefit 500+ after five years since electoral declarations”, in PL), CenEA Commentary 22/06/2020.
  • Myck, M., Trzciński, K. 2019. “From Partial to Full Universality: The Family 500+ Programme in Poland and its Labor Supply Implications”, ifo DICE Report 17(03), 36-44.
  • Szarfenberg, R. 2017. “Effect of Child Care Benefit (500+) on Poverty Based on Microsimulation”, Polityka Społeczna 44(1): 25-30.

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.

Regional Economic Development Along the Polish-German Border: 1992-2012

Image of Europe at night from sky via NASA representing regional economic development

In this brief, we summarize the results of a recent analysis focused on the regional economic development in Poland and Germany along the Oder-Neisse border (Freier, Myck and Najsztub 2021a). Economic activity is approximated by satellite night-time light intensity, a comparable proxy available for regions on both sides of the frontier consistently between 1992 and 2012. This period covers the time of economic transformation and the first eight years of Poland’s membership in the European Union. We find that convergence in overall activity across the border has been complete: Polish municipalities that used to be economically much weaker have caught up with those on the German side of the Oder and the Neisse rivers.


The question of the harmonious development of economic activity is at the heart of the European integration project (Art. 2, Treaty of Rome, 1957), and the Maastricht Treaty (1992) made economic convergence between member states an explicit objective. In a forthcoming paper (Freier et al. 2021), we take a new approach to the question of regional European integration.

This brief derives from a recent publication in Applied Economics (Freier et al. 2021a), in which we examine the degree of regional economic convergence along the German-Polish border by taking advantage of satellite night-time illumination data covering the period between 1992 and 2012. The data allows us to study detailed regional patterns of economic development along the river-delimited part of the frontier and further inland.

The seminal work by Henderson et al. (2012) was the first to use night-time light intensity data which covers the entire globe to measure economic activity. Unlike traditional regional economic indicators, light intensity data is independent of administrative border reforms and has been collected in a consistent format over the studied two decades.

Our analysis suggests that, over the analysed period from 1992-2012, there has been essentially full convergence in economic activity between municipalities on both sides of the Polish-German border. While the average value of night-time illumination in our selected group of municipalities in 1992 was 3.7 (on a scale between 0 and 63) in Poland and 7.7 in Germany, the respective values were 9.0 and 9.7 by 2012, and the latter difference is not statistically significant. This convergence suggests a much stronger rate of growth in economic activity on the Polish side of the border. Additionally, we show that within Germany, the distance to the border has much less relevance for economic activity compared to Poland, where it reflects interesting trends. In 1992, Polish towns farther from the border showed significantly higher economic performance. Within Poland, this gap has been greatly reduced over the 20 years we analyse, with regions closer to the border growing much faster compared to those farther away.

Night Lights Along the Polish-German Border

In our dataset, we include municipalities that are located within 100 km from the river delimited part of the PL-DE border. To avoid the sensitivity of the analysis to top censoring of the night-time light intensity data, we removed regional capital cities: Berlin (with surrounding municipalities), Dresden, Gorzów Wielkopolski, and Zielona Góra. This leaves us with 488 municipalities on the German side of the border and 193 municipalities on the Polish side.

The night lights data series, provided by the National Oceanic and Atmospheric Association (NOAA), starts as early as 1992 and continues in a consistent, comparable format to 2012. The data is independent of the administrative structures of local governments, which over time have changed on both sides of the border. This allows us to aggregate the night-time lights information for municipalities using the most recent available administrative borders. This data is essentially the only source of information on economic activity that is consistently available and comparable on both sides of the border over such a long period of time.

The night-time lights data has been applied widely as a proxy of economic development on the country and regional level (Henderson et al., 2012; Bickenbach et al., 2016). Clearly, the intensity of night-time lights does not capture the entire spectrum of economic activity. It has been pointed out that the relationship between night-time light intensity and conventional measures of economic development, such as GDP, is likely to differ depending on a region’s stage of economic development (Hu and Yao, 2019). However, we focus on mostly rural and sparsely populated areas (where there is little risk of top censoring of the data), and compare dynamics between regions that are similar in terms of their stage of economic development, geography, and weather. All these factors support the use of night lights as a proxy for regional development in our application (a number of technical steps are necessary to validate and calibrate the data for use in our analysis, see: Freier et al. 2021).

Economic Convergence Along the PL-DE Border

To understand the overall development of economic activity over the period of interest, we map the changes in the night-time light intensity in Figure 1. The colour scale on the map represents differences in light emissions between 1992 and 2012, with the range going from -40 to 40. A negative value indicates a reduction, and a positive value highlights an increase in light intensity. The negative values have been coloured in a blue-green scale (-40 to 0), while positive values in a red scale (0 to +40).

Figure 1. Night lights: changes in light intensity between 1992 – 2012 along the Polish-German border

Notes: municipalities along the PL-DE river border up to 100 km to the border; municipalities marked in grey treated as outliers and excluded from analysis due to high proportion of top-coded lights pixels in 1992; municipality borders as of 2013 (DE) and 2012 (PL). Source: GeoBasis-DE / BKG 2013, PRG 2012, DMSP OLS v4, OpenStreetMap, own calculations. For details see Freier et al. (2021).

As notable in Figure 1, the red areas are predominant. This exemplifies that between 1992 and 2012, nearly all municipalities in this area witnessed positive economic development as manifested in the intensity of night-time lights. We have a few areas that reflect negative dynamics on the German side of the border. This is mainly due to the regional implications of shutting down activity in agriculture and traditional industries as they were unable to compete with West-German technology and productivity. In Poland, green-blue areas are essentially non-existent, illustrating a universally positive economic development over the studied period. This difference in the pace of changes in light intensity between the German and the Polish side reflects a process of rapid convergence of economic development between municipalities on both sides of the border. These developments are represented in Figure 2 which shows the difference between the night-time light intensity in Germany and Poland by year and provides a test for its statistical significance. The estimation is done on mean log pixel values per municipality and clearly highlights the steep path of convergence. In the early nineties, the difference in mean light intensity was around 100 percent – i.e., the mean difference was as high as the mean level of lights on the Polish side of the border.  Already ten years later it reduced to around 50 percent and disappeared by the end of the analysed period. It is notable that, after an initial steep convergence, the difference in light intensity had a period of stagnation between 2002 and 2008. Interestingly, the full convergence which followed coincides with Poland’s entry into the Schengen agreement in December 2007. As seen in Figure 2, the difference in the average night-time light intensity between Poland and Germany was statistically insignificant and essentially zero since 2009.

Figure 2. Difference in mean night-time lights between Germany and Poland over time

Notes: Difference in log of average pixel values per municipality; year fixed effects included, weighted by municipality area; 95% CI. Source: see Figure 1.

Regional Development and Distance from the Border

Thanks to its high degree of geographical precision, the night-time lights data allows us to study the detailed spatial patterns within each country and, in particular, the relationship between distance to the border and economic activity. This is done by looking across the years 1992 to 2012 and examining three-year windows at each end of the analysed period. Our results, which are reported in Table 1, confirm a strong positive relationship between economic activity and distance to the border on the Polish side of the Oder-Neisse rivers. Overall, Polish regions farther from the border show a greater degree of economic activity, but this relationship has substantially diminished over time. While in Germany, economic activity was higher in regions farther from the border and increasing at the average rate of about 0.3% per km, this rate was about three times higher in Poland, falling from about 1.2% per km in 1992-94 to 0.6% in 2010-2012.

 Table 1. Total night-time lights along the Polish-German border, 1992-2012

Notes: Notes: municipalities along the PL-DE river border up to 100 km to the border; municipality borders as of 2013 (DE) and 2012 (PL); mean municipal total lights calculated using average pixel values per municipality and weighted by municipality area. Standard errors in parentheses, statistical significance: + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001. Source: see Figure 1.

Table 2 reports changes in light intensity between the beginning and the end of a specific period. Here, we find some interesting and perhaps disconcerting results on the relationship between the distance to the border and changes in light intensity. While the distance-to-border coefficient in the Polish case for the full period is negative, suggesting that regions closer to the border were catching up to the more developed regions farther away, the corresponding coefficient for the final three years is positive. This means that, in the years 2010-2012, economic development was faster in municipalities farther away from the border. Although the relationship is not very strong (the change in light intensity grows by about 0.1% per kilometre of distance to the border), it still suggests a reversal in the fortunes of municipalities close to the border on the Polish side. This result points towards the fact that homogeneity of development cannot be taken for granted and that physical distance might continue to play a role in determining the regional rate of growth in the future.

Table 2. Changes in night-time lights along the Polish-German border: 1992-2012

Notes: Notes: municipalities along the PL-DE river border up to 100 km to the border; municipality borders as of 2013 (DE) and 2012 (PL); mean municipal total lights calculated using average pixel values per municipality and weighted by municipality area. Standard errors in parentheses, statistical significance: + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001. Source: see Figure 1.


In this brief, we report results from a forthcoming paper (Freier et al. 2021) in which we evaluate regional development in municipalities on the German and Polish side of the Oder-Neisse border between 1992 and 2012, using night lights data as a proxy for economic activity. We find that driven by rapid growth in Polish municipalities and somewhat sluggish growth in German ones, the light intensity levels across the Oder-Neisse border show no significant differences by the end of our observation period. This is despite significant initial differences just 20 years earlier and the fact that municipalities on the German side also experienced increases in economic activity. In as far as economic development can be proxied by the intensity of night-time illumination, it seems that economic convergence between regions on both sides of the border was complete by 2012.

We also show interesting patterns regarding the relationship between economic activity and distance from the border. For Germany, this relationship is weakly positive and remains stable throughout the analysed period. In Poland, distance is strongly and positively correlated with light emissions at the beginning of the period, hence indicating that municipalities farther from the border show higher average economic activity. By 2012, however, the border regions have closed most of the gap and the distance to the border is a substantially weaker predictor of economic activity, suggesting a much more homogenous pattern of activity.


This brief draws on results reported in Freier et al. (2021a). The authors gratefully acknowledge the support of the Polish National Science Centre (NCN), project number: 2016/21/B/HS4/01574. For the full list of acknowledgements and references see Freier et al. (2021a).


  • Bickenbach F, Bode E, Nunnenkamp P and Söder M (2016) Night Lights and Regional GDP. Review of World Economics 152(2): 425–47.
  • Freier, R., Myck, M., Najsztub, M (2021a) Lights along the frontier: convergence of economic activity in the proximity of the Polish-German border, 1992-2012. Applied Economics, available online: doi: 10.1080/00036846.2021.1898534.
  • Freier, R., Myck, M., Najsztub, M (2021b) Night lights along the PL-DE border 1992-2012. Dataset used in Freier et al. (2021a), Zenodo, DOI: 10.5281/zenodo.4600685.
  • Henderson JV, Storeygard A and Weil DN (2012) Measuring Economic Growth from Outer Space. American Economic Review 102(2): 994–1028.

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.

COVID-19 | The Case of Poland II

An image of COVID-19 virus representing the COVID-19 outbreak in Sweden

Poland in the FREE Network Covid-19 Project (May 26, 2020)

Current Health Situation in Poland

Poland noted its first coronavirus infection in early March 2020. After the initial rapid spread of the disease throughout the country and spike in the total number of registered infections, since early April the infection curve stabilized at a relatively low level (compared to other European countries) of 250-350 new daily cases. The flattening of the curve was a result of drastic health and social restrictions gradually imposed on society (more details below). Since the first reported case, the testing capacity has also been substantially improved, with the number of tests conducted daily increasing from 2K to 15-20K in late April, and holding steady since then.

Figure 1. Number of Covid infections per 100K inhabitants in districts in PL (as of May 25)

Source: own compilation based on data collected by Michał Rogalski (https://www.micalrg.pl/) from Voivodeship Offices, Voivodeship and Powiat Epidemiological-Sanitary Stations, media and materials sent on request. Note: first/last class covers 10% lowest/highest obs., other classes – 20% obs.

Even though Poland has not yet reached an apparent decrease in the number of new daily infections, since the end of April the government introduced a strategy of a slow, four-step re-opening of the economy (more details below). As of 26 May 2020, the total number of Covid infections in Poland approached 22K, with the number of fatalities as high as 1K, and cases reported in all but 7 districts of the country (out of over 300 – see Figure 1). At this point in time, Poland also found itself at the third phase of the lifting of restrictions on economic activity.

Government Health Policies

Lockdown Introduction

The Minister of Health announced a state of epidemic risk in the territory of Poland on March 14 [7], raising it further to a state of epidemic 6 days later [8]. Measures counteracting the epidemic were introduced centrally in Poland by the Minister of Health, and were gradually extended:

  • Restriction on the size of public gatherings: since 14.03.2020 limited to 50 [7]; since 25.03.2020 – 2 people (except for families and funerals up to 5 people) [9],
  • Ban on all non-essential mobility since 25.03.2020 [9]; since 01.04.2020 limitations on access to public spaces like parks, playgrounds and recreational areas; distance of 2 meters between people in public places; further restrictions for minors [10],
  • Bars and restaurants closed and allowed only to provide take-away food since 14.03.2020 [7],
  • Childcare institutions, all schools and higher education institutions closed on 12.03.2020, formally online education provided since 25.03.2020 [11, 12],
  • Since 15.03.2020 foreigners banned from travelling into Poland (with exceptions), while all Poles arriving from abroad quarantined for 14 days after arrival [7],
  • Shopping malls, sports and recreation centers, sports events, cinemas, theatres, etc. closed since 14.03.2020 [7]; since 01.04.2020 – hairdressers, beauty salons, physiotherapy, hotels etc. [10],
  • Restrictions on the number of people using public transport since 25.03.2020 [9],
  • Since 01.04.2020 restrictions on the number of people in shops and designated shopping hours for 65+ only [10], since 02.04.2020 obligation to wear disposable gloves [10],
  • Restrictions in workplaces since 02.04.2020: distance between coworkers, access to protective equipment [10],
  • Since 16.03.2020 certain hospitals devoted exclusively to patients with (suspicion of) Covid-19 [13],
  • Since 16.04.2020 mandatory covering of mouth and nose in all public places, inside and outside [17].

Gradual Ease of Restrictions

On March 16, 2020, the Minister of Health announced a gradual strategy of lifting the restrictions imposed on social life and economic activity. The plan is divided into four steps. The first stage was implemented on 20.04.2020 [18]:

  • increase in the limit of customers in shops,
  • public spaces like parks and recreational areas (except playgrounds) open,
  • mobility restrictions lifted for minors over 13 y.o.

The second stage was introduced on 04.05.2020 [19, 20, 21]:

  • shopping malls open with restrictions on the number of customers, shopping hours for 65+ cancelled,
  • museums, libraries, physiotherapy, hotels open,
  • sports facilities open with restrictions on the number of users,
  • 14-day quarantine for workers from neighbouring countries cancelled,
  • since 06.05.2020 some nurseries and kindergartens open.

The third stage started on 18.05.2020 [22, 23]:

  • mobility restrictions lifted for minors under 13 y.o.
  • hairdressers, beauty salons, outdoor cinemas open, restaurants and bars – with restrictions on the number of customers,
  • increase in the number of people using public transport,
  • sport trainings allowed with restrictions,
  • some classes (practical or individual) in post-secondary schools allowed,
  • since 25.05.2020 classes for children from the 1st – 3rd grade in primary schools and final-year graduates allowed,
  • since 01.06.2020 consultations with teachers at schools allowed.

The fourth stage is planned for the near future, without a specific date. It involves the opening of cinemas and sports centers.

Government Economic Policies

The government implemented several stages of the so called “Anti-crisis shield”, the first of  which came into force on  April 1. The overall package includes a number of broad measures to support enterprises and workers for a period of three months and covers both direct financial support as well as provisions regarding financial liquidity for companies [14, 15]. In March the National Bank of Poland decreased interest rates and announced that it will support access to credit through targeted longer-term refinancing operations and if necessary will provide monetary stimulus through large scale open market operations [16].

Short Summary of Measures

Labor market [14]:

  1. Increased flexibility of employee daily and weekly hours of work;
  2. Extension of childcare leave for parents with children aged 0-8;
  3. In case activities affected by revenue reduction (revenue fall by 15% year-to-year or 25% month-to-month):
    1. Self-employed or employees on non-standard contracts to receive a monthly benefit equivalent to 80% of minimum wage for up to three months;
    2. Companies to receive support equivalent to 50% of the minimum wage for inactive employees due to the stoppage, provided individual salaries are not reduced by more than 50%;
    3. Companies to receive support equivalent to up to 40% of average wage for employees whose hours are reduced by 20%;
    4. Alternative support to employment provided to SMEs (up to 249 employees) in case of revenue loss from the Labour Fund: depending on the level of revenue loss (>30%, >50%, >80%) support to employees expressed as ratio of the Minimum Wage (respectively: 50%, 70% and 90%);
    5. Relaxation of work and stay permits for foreigners.

Social transfers:

  1. No specific measures have been implemented but the government is considering:
  • a tourism voucher of 1000 PLN paid to employees with a 90% contribution from the government (10% paid by employers); paid to employees on wages below the national average wage;
  • additional support to housing benefit for those who become eligible to housing benefits due to the economic slowdown;

Tax breaks [14]:

  1. 100% of social security contributions to be paid by the government for self-employed and employees employed in micro enterprises (up to 9 employees) and 50% paid by the government in small enterprises (10-49) for three months;
  2. Tax payments and social security contributions on earnings and profits can be delayed till 01.06.2020;
  3. Losses from 2020 will be deductible from the 2021 tax base.

Emergency loans, guarantees and support [14]:

  1. Small-scale loans to small companies;
  2. Reduced administrative requirements and relaxation of numerous regulatory rules;
  3. Increased liquidity of firms through channels supported by the Polish Development Fund (PFR):
    1. extension of de minimis guarantees to SMEs;
    2. subsidies to SMEs which suffered revenue losses due to the pandemic;
    3. equities and bond issues to be financed by PFR;
    4. subsidies to commercial loan interest payments from BGK;
    5. commercial turnover insurance from Export Credit Insurance Corporation (KUKE);
  4. Relaxation of regulations related to contracts with public institutions (e.g. related to delays).

Monetary policy [16]:

  1. On 17.03.2020 NBP lowered the main reference interest rate by 0.5 pp and reduced the rate of obligatory reserves from 3.5% to 0.5%. The main reference rate was lowered further to 0.5% on 08.04.2020.
  2. NBP announced the readiness to engage in large scale open market operations;
  3. Targeted longer-term refinancing operations to allow credit refinancing by commercial banks.


[1] OECD Health Statistics, https://stats.oecd.org/viewhtml.aspx?datasetcode=HEALTH_REAC&lang=en.

[2] Central Statistical Office in Poland (GUS), bdl.stat.gov.pl.

[3] Supreme Medical Chamber (Naczelna Izba Lekarska), https://nil.org.pl/rejestry/centralny-rejestr-lekarzy/informacje-statystyczne.

[4] Ministry of Health, https://twitter.com/mz_gov_pl?lang=pl.

[5] Warsaw Stock Exchange (Giełda Papierów Wartościowych), https://www.gpw.pl/gpw-statistics.

[6] Central Bank of Poland (Narodowy Bank Polski), https://www.nbp.pl/home.aspx?f=/kursy/kursya.html.

[7] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/433.

[8] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/491.

[9] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/522.

[10] ministry of Health, http://dziennikustaw.gov.pl/DU/2020/566.

[11] Ministry of Science and Higher Education, http://dziennikustaw.gov.pl/DU/2020/405.

[12] Ministry of National Education, http://dziennikustaw.gov.pl/DU/2020/410.

[13] https://www.gov.pl/web/koronawirus/lista-szpitali.

[14] Polish Development Fund (Polski Fundusz Rozwoju Przewodnik Antykryzysowy dla Przedsiębiorców 02.04.2020), https://pfr.pl/tarcza.

[15] Polish Development Fund (Polski Fundusz Rozwoju Przewodnik Antykryzysowy dla Przedsiębiorców 05.05.2020), https://pfr.pl/tarcza.

[16] Central Bank of Poland (Narodowy Bank Polski), https://www.nbp.pl/home.aspx?f=/polityka_pieniezna/dokumenty/komunikaty_rpp.html.

[17] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/673.

[18] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/697.

[19] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/792.

[20] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/780.

[21] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/779.

[22] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/878.

[23] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/871.

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.

Income Inequality in Transition. New Results for Poland Combining Survey and Tax Return Data

20200113 Income Inequality in Transition FREE Policy Brief Image 01

We re-examine the evolution of income inequality in Poland in the process of post-socialist transition focusing on the previously neglected problem of under-coverage of top incomes in household survey data. Multiple statistical techniques (Pareto imputation, survey reweighting, and microsimulation methods) are applied to combined household survey and tax return data in order to obtain top-corrected inequality estimates. We find that the top-corrected Gini coefficient grew in Poland by 14-26% more compared to the unadjusted survey-based estimates. This implies that over the last three decades Poland has become one of the most unequal European countries among those for which top-corrected inequality estimates exist. The highest-income earners benefited the most during the post-socialist transformation: the annual rate of income growth for the top 5% of the population exceeded 3.5%, while the median income grew on average by about 2.5% per year. This brief summarizes the results presented in Brzezinski et al. (2019).


There is a large economic literature documenting income inequality changes experienced by former communist countries during their post-1989 transformations. While in Russia and in many post-Soviet economies, inequality exploded during the transition, Poland is often perceived as a country where inequality grew rather moderately. However, these conclusions may be unreliable as they are based on inequality measures estimated using income data only from household surveys.

Many recent studies show that surveys are plagued by significant under-coverage of top incomes, which leads to a severe downward bias of the inequality estimates. Several approaches have been proposed to correct for this problem. One of them is to combine survey data with income information taken from administrative sources such as tax returns. While top-corrected inequality estimates have been produced for many advanced economies, transition countries received little attention in this context so far.

For Poland, Bukowski and Novokmet (2019) provided series of top income shares estimated using tax data. However, their estimates are constructed for gross (pre-tax) income distributed among tax units. This kind of income concept deviates considerably from the primary measure of the standard of living analysed in income distribution literature, namely disposable equivalized household income defined for the entire population. Estimates based only on tax data are not directly comparable to standard survey-based measures, which makes it difficult to decide which of the two kinds of results are closer to the underlying inequality trends and levels.

In a recent paper (Brzezinski, Myck, Najsztub 2019), we provide the first estimates of top-corrected inequality trends for real equivalized disposable incomes in Poland over the years 1994-2015. These estimates can be readily compared with standard survey-based estimates available from Statistics Poland or from Eurostat. Our analysis re-evaluates distributional consequences of post-socialist transition in Poland.

According to the standard view, the Polish transition to a market economy was an almost unqualified success story. Poland managed to achieve fast and stable economic growth (around 4.3% per year since 1994) that was at the same time broadly inclusive and shared rather equally by various social classes and segments of the income distribution. Survey-based estimates suggest that the Gini index for Poland has not increased significantly since 1989 and reached the average level among the EU countries in 2015. In contrast to the standard view, our top-corrected results show that the inequality of living standards in Poland grew sharply over 1989-2015. The adjusted Gini index grew by 4-8 p.p. to a level that ranks Poland among the most unequal European countries for which comparable estimates exist.

Data and Methods

We use data from two sources. Our survey income data comes from the representative Polish Household Survey (PHBS) conducted annually by Statistics Poland since 1957. We use the PHBS data for 1994-2015 as the pre-1994 surveys do not contain data on individual incomes (required for our microsimulation modelling) and 2015 is the last year for which estimates of tax-based inequality measures are available. We adjust the baseline PHBS survey weights to match the census-based number of males and females by age groups (population weights). We also create a further adjusted set of weights to match the number of PIT payers in each tax bracket according to the Polish tax scale (tax weights).

Our main income variable is real equivalent household disposable (post tax and transfer) income. We obtain it from the Polish microsimulation model SIMPL applied to the PHBS data. The microsimulation model allows us to construct a gross (before PIT and employee SSCs) income distribution among the tax units, which is unavailable in the raw PHBS data. This is crucial as it is the gross income distribution between tax units to which we impute top incomes estimated using tax-based statistics.

Our second data source is the series of tax-based top income shares for Poland taken from Bukowski and Novokmet (2019). To construct top-corrected inequality estimates, we follow the methodological approach of Bartels and Metzing (2019). Using the microsimulation model applied to the PHBS data we obtain the distribution of gross income among tax units (individuals). In the next step, we use data on top income shares to estimate the parameters of a Pareto distribution for gross income distribution in terms of tax units. Then, we replace the top 1% (or 5%) of tax units’ incomes with the incomes implied by the estimated Pareto distribution. The resulting imputed gross distribution is subsequently reweighted using either population or tax weights. After imputing top incomes, we again use the microsimulation approach to compute top-corrected real equivalized household net incomes.

Corrected Income Inequality Trends

Figure 1: The Gini index for Poland, 1994-2015: unadjusted vs top-corrected estimates

Note: Vertical lines show 95% confidence

Figure 1 presents our income inequality estimates in terms of the Gini coefficient. For the period 1994-2005, we present two top-corrected series, which can be considered as lower and upper bound estimates of the “true” Gini. The results for this period are more uncertain as they are affected by the 2004 tax reform in Poland that introduced an optional flat tax for non-agricultural business income, which reduced the marginal tax rate for the highest income taxpayers from 40% to 19%. Research suggests that before the reform the problems of tax evasion and avoidance could have been more pronounced in Poland and some of the top incomes were unreported or under-reported. The upper bound series on Figure 1 corrects for the possible higher tax evasion and avoidance before 2005.

The unadjusted Gini series suggests that income inequality in Poland was rather stable over 1994-2015.  On the other hand, our top-corrected series point to a very different story.  Until 2005, our two correction procedures show similar inequality trends, but somewhat different levels. After 2005, our corrected series shows systematic and high divergence between unadjusted and top-corrected Ginis ranging from 4 to 8 p.p. The top-corrected Ginis increase in the range from 14 to 26% over 1994-2015.  While according to the unadjusted data Poland is only moderately unequal, the comparison of top-corrected estimates shows that in 2015 Poland has higher level of income inequality than even high-inequality EU countries such as Germany, Spain or UK.

We also show that each percentile of the disposable income distribution in Poland saw income increases in absolute terms between 1994 and 2015. This implies that on average the incomes of all social groups increased during the transition to market economy. However, these gains were shared unequally. According to our adjusted estimates, the cumulative growth in real income over 1994-2015 for the top 1% of Poles reached 122-167%, while for the bottom 10% the corresponding number is at most 57%.

Redistribution and Progressivity of the Tax System

We also analyse how our correction procedures affect measures of redistribution and progressivity of direct taxation (income taxes, employees’ mandatory social security contributions, and health insurance). The top-corrected estimates show that the percentage reduction in the Gini index due to social insurance contributions and PIT has fallen from 19.2% in 1999 to 11.6% in 2015.

While the unadjusted series suggests that the progressivity of the Polish system of PIT and social insurance contributions has decreased only mildly over time, the top-corrected series points to a much steeper fall, especially during 2005-2009. Without the top-correction, the progressivity in 2015 is overestimated by 2.3 p.p. (or by 40%). Much of the decline in tax progressivity over 2005-2009 is due to the reduction from three PIT brackets and marginal tax rates to just two brackets and rates (18% and 32%) in 2009. Even in terms of the unadjusted data, Poland ranks in the recent years as the country with the lowest PIT and SICs progressivity in the EU.


Our recent paper on estimating the top-corrected measures of income inequality shows that while Poland was already a relatively unequal country in the early 1990s, it has become one of the most unequal European countries (not including Russia) among those for which comparable estimates exist. The results have important implications for the assessment of the distributional consequences of post-socialist transformations or modernization processes in emerging countries. They indicate that using income tax data and imputation or reweighting techniques to account for the problem of missing top incomes in survey data can significantly alter the conclusions about income inequality levels and trends. More reliable inequality estimates would contribute not only to a better understanding of economic transformation and modernization processes but could also shed some light on recent political turmoil in many transition and emerging countries (such as Turkey, Hungary or Poland). As suggested by some recent research, the growing distributional tensions in emerging countries of Eastern Europe and Central Asia may be associated with more distrust in governments and an increased propensity to vote for radical political parties.


The authors gratefully acknowledge the support of the Polish National Science Centre (NCN) through project number: UMO-2017/25/B/HS4/01360. For the full list of acknowledgements see Brzezinski et al. (2019).


  • Bartels, C., Metzing, M. (2019). An integrated approach for a top-corrected income distribution. The Journal of Economic Inequality, 17(2), 125-143.
  • Brzezinski M., Myck M., Najsztub M. (2019), Reevaluating Distributional Consequences of the Transition to Market Economy in Poland: New Results from Combined Household Survey and Tax Return Data. IZA DP No. 12734.
  • Bukowski P., Novokmet F. (2019), Between Communism and Capitalism: Long-Term Inequality in Poland, 1892-2015. CEP Discussion Paper No 1628 June 2019.