Tag: Labor Market Participation

Georgia’s Growth Dilemma: Structural Transformation, Inequality, and the Future of Inclusive Development

Posted on May 19, 2025 | Policy Papers

This policy paper examines Georgia’s economic growth and labor market developments between 2017 and 2023, with a focus on structural transformation and income distribution. While growth has been strong and absolute poverty has declined, challenges remain in labor reallocation, wage inequality, and regional disparities. Redistribution mechanisms, particularly social transfers, have played an important role in mitigating poverty; however, the pace of inclusive structural change has been limited. Key policy priorities include fostering productivity growth, expanding employment opportunities, and addressing inequality through targeted labor market and social policies.

Georgia’s Economic Rebound: Growth Beyond Recovery or Superficial Expansion?

In recent years, Georgia’s economy has demonstrated remarkable resilience and dynamism. Following a sharp contraction of real GDP by approximately 6.8 percent in 2020 due to the Covid-19 pandemic, the economy rebounded strongly, posting a growth rate exceeding 10 percent in 2021. This robust performance was maintained also in 2022 and 2023. The recovery was among the fastest in the region, fueled by a combination of strong private consumption, booming external demand, and exceptional inflows of remittances and capital.

According to national accounts data, output in 2023 not only recovered the losses sustained during the pandemic but significantly surpassed pre-pandemic levels. Georgia’s real GDP is on a trajectory above its previous trend, with potential output estimates also being revised upward (see Figure 1). Potential output — the level of economic activity the country can sustain without triggering inflation — is not directly observable and was estimated using a statistical technique known as the Kalman filter. This method uses historical GDP data and economic patterns to produce a smooth estimate of potential output over time, allowing policymakers to assess the gap between actual and sustainable growth. The economy’s output gap, which turned sharply negative during the pandemic, gradually closed by 2022 and moved into slightly positive territory by 2023, indicating that output had surpassed its estimated potential level as the recovery matured.

Figure 1. Output Growth, Output Gap, and Potential Output in Georgia

Source: Geostat. Author’s calculations.

Georgia’s recent economic growth is largely propelled by geopolitical factors linked to the Russo-Ukraine war. The sharp increase in remittance inflows from Russia — which soared by 403 percent to $2.1 billion in 2022 — provided a major boost to domestic consumption. At the same time, the relocation of capital, businesses, and skilled individuals intensified, with over 30,000 Russian-owned firms registered and nearly 115,000 Russian migrants arriving between 2022 and 2023, significantly stimulating investment and labor market activity. In addition, the rapid expansion of re-exports — particularly of motor vehicles and machinery — further accelerated external trade, with re-exports to Russia, Armenia, Kazakhstan, and Kyrgyzstan rising 6.6 times in 2024 compared to 2019, which strengthened the logistics and transport sectors.At the same time, substantial fiscal stimulus during the pandemic years, followed by a gradual normalization of fiscal policy, helped support aggregate demand without triggering immediate macroeconomic instability. Monetary policy remained broadly accommodative, while inflationary pressures — although pronounced — were largely kept under control relative to peer economies.

Despite these positive developments, the underlying composition of growth raises important questions. High headline growth figures do not automatically translate into widespread improvements in living standards or reductions in inequality. Growth that is driven by consumption booms, remittance surges, or temporary trade redirection may lack the deep, productivity-enhancing underpinnings necessary for long-term sustainability. Without broad-based sectoral upgrading and inclusive labor market outcomes, there is a risk that economic expansion will remain concentrated in a few dynamic sectors while leaving large parts of the population behind.

Moreover, the post-pandemic growth episode coincided with rising concerns about external vulnerabilities, including Georgia’s dependence on remittances (17.5 and 13.5 percent of GDP in 2022 and 2023, respectively (NBG, Geostat)) and commodity prices, as well as regional political risks. If these external drivers were to weaken, maintaining high growth rates without deeper structural changes could become increasingly difficult.

Therefore, while Georgia’s recent economic record is impressive by regional standards, it is crucial to assess whether this growth has been accompanied by meaningful structural transformation — namely, a reallocation of labor from low to high-productivity sectors, rising labor incomes, and reduced inequality. A deeper analysis of sectoral dynamics and employment patterns is required to determine whether Georgia’s economy is evolving toward a more inclusive and sustainable growth model.

Structural Shifts of the Economy: Progress Without Transformation?

The structural transformation of Georgia’s economy between 2017 and 2023 (see Figure 2) reveals both encouraging and concerning trends. The analytical framework used to assess structural transformation in Georgia between 2017 and 2023 draws on the methodology developed by McMillan and Rodrik (2011). This influential study emphasizes the role of labor reallocation across sectors as a key driver of aggregate productivity growth in developing and transition economies.

The analysis of the change in sectoral employment shares against relative sectoral productivity shows that, broadly speaking, labor reallocation has followed a growth-enhancing direction. The fitted trend line across sectors exhibits a positive slope, suggesting that workers have been moving, though slowly, away from low-productivity sectors and toward relatively higher-productivity activities. However, the shallow gradient of the trend line indicates that the pace and quality of this transformation have been modest. The most significant dynamic during this period is the continued exit of labor from agriculture. Agriculture remains a highly unproductive sector, with a large share of labor in subsistence agriculture, and experienced a substantial decline in its employment share—a positive signal for economic modernization. Nevertheless, much of the displaced labor appears to have been absorbed by mid-productivity services such as construction, retail trade (wholesale and retail trade; repair of motor vehicles and motorcycles), accommodation and food service activities, and transportation. These sectors have seen rising employment shares but remain relatively close to or below the economy-wide average in terms of labor productivity. Consequently, while labor mobility is evident, the migration has largely been into sectors that do not substantially enhance overall economic efficiency.

Figure 2. Structural Transformation and Productivity Alignment in Georgia, 2017–2023

Source: Geostat. Author’s calculations. Note: Each bubble represents a sector, with its position determined by the change in its employment share (horizontal axis) and its relative productivity level (vertical axis). Bubble size corresponds to the sector’s share of total employment in 2017. The positive slope of the fitted trend line indicates modest progress in reallocating labor toward more productive activities, although the shift remains shallow and incomplete.

In contrast, high-productivity sectors, notably information and communication, financial and insurance activities, and real estate, have exhibited strong relative productivity but absorbed very limited shares of the labor force. These findings point to persistent barriers in accessing higher-value employment opportunities, likely stemming from skill mismatches, limited educational attainment, and structural rigidities in the labor market.

Public administration, education, and health — traditionally labor-intensive sectors — have maintained relatively large shares of employment while operating below average productivity levels, reflecting a lack of dynamism in these essential public service areas.

Overall, the observed pattern suggests that Georgia’s recent economic growth has been accompanied by low-quality structural transformation. Although there has been a reallocation of labor from extremely low-productive sectors, the transition has not been sufficient to significantly lift aggregate productivity or to broaden access to high-wage, high-skill employment.

These trends underscore the critical need for policy interventions aimed at improving the quality of labor mobility. Investment in education and vocational training to match labor supply with demand in high-productivity sectors is essential. Moreover, facilitating entrepreneurship, promoting innovation in services and manufacturing, and supporting labor market flexibility could help ensure that future structural changes generate more inclusive and sustainable economic growth.

Labor Market Dynamics: Recovery in Numbers, Challenges in Structure

Following the period of sectoral shifts and structural transformation outlined above, it is equally important to examine how the Georgian labor market has evolved in recent years. Labor market dynamics provide critical insight into the inclusiveness and sustainability of economic growth. Between 2017 and 2023, the number of employed individuals exhibited a general upward trajectory, particularly after the sharp decline during the Covid-19 pandemic in 2020 (see Figure 3). Employment numbers, which fell significantly in 2020 and 2021, recovered steadily in the following years, reaching approximately 1.33 million in 2023. Preliminary assessments suggest that this recovery is expected to continue into 2024, further consolidating the labor market’s post-pandemic rebound.

Figure 3. Employment and Unemployment Trends in Georgia

Source: Geostat. Author’s calculations.

This recovery has been accompanied by notable improvements in Georgia’s wage dynamics. After a period of stagnation in nominal and real wages between 2018 and 2020, the economy experienced a sharp acceleration in wage growth, beginning in 2021. Average nominal wages rose rapidly, while real wage growth, which accounts for inflation, also turned positive after years of stagnation (see Figure 4). These wage dynamics indicate that the labor market tightening contributed to upward pressure on wages, suggesting better bargaining conditions for workers in certain sectors.

Figure 4. Nominal and Real Wage Dynamics in Georgia

Source: Geostat. Author’s calculations.

At the same time, unemployment rates declined significantly. The unemployment rate, which had hovered between 17 and 20 percent prior to the pandemic, began a gradual downward trend from 2021 and onwards, falling to approximately 14 percent by 2023 (see Figure 3). This suggests that job creation in the recovery phase was relatively strong. However, the persistently high levels of unemployment earlier in the period underscore structural issues that remain unresolved.

Nevertheless, despite these positive headline trends, several deeper challenges persist within Georgia’s labor market. Employment growth has been concentrated primarily in low- and mid-productivity service sectors, as indicated previously. Informality remains high, particularly in agriculture and small-scale services, and labor underutilization (32.1 percent) — including underemployment and discouraged workers— continues to affect a significant segment of the workforce.

Moreover, the share of labor income relative to GDP provides important additional context (see Figure 5). As shown in Figure 5, the wage share of GDP fluctuated throughout the period, declining during the pandemic years and rebounding sharply in 2023. While this recovery is promising, it may however partially reflect inflationary effects or nominal wage adjustments rather than deep, productivity-driven gains.

Figure 5. Share of Wages in GDP and Economic Growth

Source: Geostat. Author’s calculations.

Taken together, recent labor market developments in Georgia reflect a cyclical recovery reinforced by external demand and domestic consumption. Yet, the underlying structure of employment, informality, and the relatively slow reallocation of labor into high-productivity sectors suggest that the labor market’s transformation remains incomplete. Sustainable improvements in labor incomes and employment quality will require addressing skills mismatches, boosting formal sector job creation, and ensuring that future growth translates into widely shared labor market opportunities.

Despite the improvements in employment and wage dynamics, it remains critical to assess whether these labor market gains have translated into broader improvements in income distribution and living standards. Strong aggregate indicators do not necessarily imply that growth has been inclusive or that inequality has diminished. The following section examines how the distribution of income has evolved in recent years, focusing on wage structures, inequality measures, and the extent to which economic growth has been shared across different segments of the population.

Income Inequality and Distributional Shifts: A Fragile Middle and Growing Extremes

Following the developments observed in the labor market, it is crucial to assess how economic growth and labor dynamics have translated into income distribution outcomes. Understanding the evolution of income inequality provides deeper insight into whether the benefits of growth have been broadly shared or have remained concentrated.

Wage income distribution patterns between 2017 and 2023 show a complex trajectory. The wage distribution curve (see Figure 6) reveals that while average earnings have increased over time, the overall shape of the distribution has also evolved significantly. The peak of the distribution has become sharper and shifted toward higher income brackets, particularly around the 1200–2400 GEL range. However, the right-hand tail of the distribution has simultaneously elongated, suggesting the emergence of a relatively small group of very high-income earners.

Figure 6. Wage Income Distribution Curves, 2017–2023

Source: RevenueServices. Author’s calculations.

This dual movement — a general upward shift combined with increasing dispersion — is captured through key statistical measures:

First, the standard deviation of incomes, which reflects the average distance of individual incomes from the mean, increased notably (57 percent) between 2017 and 2023. An increasing standard deviation indicates that income differences within the population have become more pronounced, with greater dispersion around the average wage. In simple terms, not only are people earning more on average, but the spread between low and high earners has widened substantially.

Second, the changes in skewness and kurtosis provide further depth to this picture. Skewness measures the asymmetry of the income distribution. In 2017, the distribution had a skewness of about 1.74, indicating a moderate right-skew, with income values concentrated around the lower and middle ranges and a gradual tapering toward higher incomes. By 2023, skewness had increased to 3.81, suggesting that the income distribution has become much more asymmetrical. A few individuals or households are earning disproportionately high incomes compared to the rest of the population. The visible downward shift in the 2023 wage distribution curve at the lower income ranges likely reflects two reinforcing trends. First, persistent inflation during the post-pandemic recovery years eroded the real value of wages, effectively pushing nominal incomes upward and compressing the lower tail of the distribution. Many workers who previously occupied the lowest wage brackets may have moved into higher nominal categories without corresponding improvements in purchasing power (average real wages declined until 2021, after which they began to recover, rebounding steadily through 2023 following the Covid-19 shock (See Figure 4)). Second, due to low rate of job creation, Georgia has experienced a high rate of labor emigration in recent years, especially to the EU and the U.S., particularly among low-skilled workers. This outflow of labor likely reduced the number of individuals earning wages in the lowest income ranges, further contributing to the observed contraction of the left side of the distribution curve. Together, these factors help explain why the red curve in 2023 dips below previous years in the lowest wage intervals.

Kurtosis, meanwhile, captures the “tailedness“ or the concentration of extreme outcomes. Georgia’s wage distribution moved from a kurtosis of about 5.16 in 2017 to 15.75 in 2023. Higher kurtosis indicates that extreme deviations (very low or very high incomes) have become more common relative to a normal distribution. In Georgia’s case, it points to an increasingly peaked distribution with fat tails: most people are concentrated around a modal income, but extreme earnings at the high end have become more significant.

In parallel, the Lorenz curves for 2017 and 2023 (see Figure 7) offer a graphical representation of these dynamics. The curve for 2023 lies slightly closer to the line of equality than that of 2017, reflecting a marginal improvement in income equality in the early part of the period. However, the difference is modest, and the curve’s arched shape hints at a persistent structural inequality. It should be mentioned that the calculations are based on household expenditures and therefore reflect the redistributive effects of government fiscal policy on income inequality. The Gini index, a summary statistic derived from the Lorenz curve, plots the cumulative share of income held by cumulative shares of the population. It measures income inequality on a scale from 0 (perfect equality) to 1 (perfect inequality) and thus provides a concise way to track changes in distributional dynamics over time.

In the case of Georgia, the index supports the discussion regarding the Lorenz curve. Between 2017 and 2021, the Gini index declined from 0.3711 to 0.3090, suggesting a reduction in income inequality during these years, likely influenced by pandemic-driven wage compression, social transfers, and temporary labor market adjustments. However, from 2021 onwards, inequality began creeping upward again, reaching 0.3271 in 2023. This suggests that the initial equalizing effects of crisis responses were short-lived and that structural disparities in income distribution have reasserted themselves as the economy recovered.

Figure 7. Lorenz Curves (2017 and 2023 comparison)

Source: Geostat. Author’s Calculations.

Together, these metrics paint a coherent picture: the Georgian economy experienced nominal wage growth and a partial strengthening of middle-income segments during the recovery phase, however, this was accompanied by greater income dispersion, higher asymmetry (favoring high-income earners), and an increased concentration of wealth at the very top.

Thus, although the average worker is better off in absolute terms compared to 2017, the relative disparities within the labor force have widened, especially after 2021. Growth has been unevenly distributed, increasingly favoring highly skilled, capital-intensive, or well-connected sectors and workers.

Poverty trends during 2017–2023 (see Figure 8) add an important additional dimension to the analysis of income distribution. Over this period, Georgia achieved a substantial reduction in absolute poverty, with the share of the population unable to meet basic consumption needs falling from 21.9 percent in 2017 to 11.8 percent in 2023. This sharp decline reflects real improvements in living standards for a significant portion of the population and indicates that economic growth, combined with social policy interventions, had a meaningful impact in alleviating extreme deprivation. However, developments in relative poverty tell a more nuanced story.

Relative poverty, which measures economic disadvantage in relation to the median income, declined only modestly from 22.3 percent to 19.8 percent over the same period. The persistence of relative poverty, despite improvements in absolute poverty, suggests that while more people were able to meet basic needs, the income distance between lower-income households and the median population did not significantly narrow. This implies that, although economic growth has lifted many out of extreme poverty, underlying income inequality has remained largely intact. Crucially, redistribution plays a central role in shaping these poverty outcomes. Although Georgia’s tax system is largely regressive and heavily reliant on indirect taxes, fiscal transfers — particularly the old-age pension — play a powerful equalizing role. The pension system alone is estimated to reduce the national poverty rate by up to 18 percentage points, highlighting the critical role of targeted redistribution in mitigating deprivation. These fiscal tools are especially important in the absence of highly progressive taxation, and they help explain why absolute poverty declined so markedly despite ongoing structural labor market weaknesses. At the same time, the relatively limited change in relative poverty underlines the limits of redistribution in addressing inequality in the absence of more inclusive labor market outcomes and equitable income growth.

Figure 8. Evolution of Absolute and Relative Poverty Rates in Georgia, 2017–2023

Source: RevenueServices. Author’s calculations.

An important part of the labor market story is the role of public employment initiatives, particularly those targeting the labor market. While government employment programs have had a visible impact on official labor statistics (see Figure 9), particularly in peripheral regions, a closer examination reveals critical concerns regarding the quality and sustainability of the jobs created. Many of the positions facilitated through this program are characterized by very low wages, limited or no skills development opportunities, and lack of formal career advancement paths. Rather than serving as a bridge to stable, productive employment, these jobs often appear to fulfill administrative or social functions, providing basic income support without contributing meaningfully to workers’ long-term economic mobility.

Figure 9. Share of Social Service Agency (SSA) Program Employment in Total Regional Employment (2023)

Source: Social Service Agency, Geostat, Author’s Calculations. Note: Bars represent regions in Georgia.

Moreover, there is evidence that the expansion of employment facilitated by the government program has, in some regions, been used as a tool for political management, particularly at the municipal level. By creating a network of publicly funded low-skill jobs tied to local government structures, employment program may inadvertently reinforce patronage systems and political dependence, particularly around electoral cycles.

This raises important concerns about the role of public employment programs in structural transformation. While temporary income support can be vital for vulnerable populations, overreliance on low-productivity public sector jobs can entrench regional stagnation and undermine incentives for private sector dynamism. For employment programs to contribute positively to structural transformation, it is essential that they be reoriented toward genuine skills development, pathways into productive sectors, and integration with broader labor market activation strategies.

Taken together, these trends suggest that while Georgia’s economic growth has lifted many individuals out of absolute poverty and improved average incomes, it has also led to greater wage dispersion, increasing concentration of incomes at the top end, and significant concerns about the depth and quality of labor market transformations. Without deliberate policy efforts to promote inclusive structural change, Georgia risks entrenching a dualistic economy, where prosperity coexists with persistent inequality and regional marginalization.

Conclusion and Policy Recommendations

In light of the findings discussed above, a set of targeted policy actions is proposed to foster a more inclusive, sustainable, and equitable economic transformation in Georgia. These recommendations aim to address the structural weaknesses identified in the labor market, income distribution, and regional economic development, ensuring that future growth benefits a broader cross-section of the population.

The findings of this policy paper highlight the need for a more deliberate approach to structural transformation in Georgia. While recent economic growth has been strong, labor reallocation toward high-productivity sectors remains incomplete, income distribution dynamics point to persistent inequalities, and improvements in living standards have not been evenly shared. To ensure that growth translates into broad-based prosperity, the following policy actions are recommended:

Georgia must accelerate the movement of labor from low-productivity sectors, particularly agriculture and informal services, into higher-productivity activities. Policymakers should prioritize sectoral strategies that support emerging dynamic industries — such as ICT, logistics, manufacturing, and modern services — while also upgrading traditional sectors like agriculture and tourism to enhance productivity and employment absorption.

Addressing skill mismatches is essential to enable labor mobility toward productive sectors. Investment in vocational education, digital skills training, and sector-specific workforce programs must be intensified, especially targeting young people, rural workers, and displaced labor from declining industries.

While public employment programs can play a stabilization role, the primary engine of sustainable job creation must be the private sector. Georgia should focus on creating an enabling environment for small and medium sized enterprises, supporting entrepreneurship, streamlining business regulations, and improving access to finance, especially outside of the capital Tbilisi.

Reducing regional disparities is critical for equitable growth. Targeted infrastructure investment, decentralized support for business development, and place-based labor market policies are needed to ensure that structural transformation benefits all regions, not only urban centers.

Promoting formal labor relations through fiscal incentives, simplified compliance procedures, and stronger enforcement can raise job quality and income security. At the same time, reinforcing social protection systems can mitigate inequality without discouraging labor market participation, helping to build a more resilient workforce.

Ongoing reforms must be informed by robust, high-frequency data. Strengthening labor market information systems, expanding coverage of income and employment surveys, and integrating administrative data into policymaking will enhance the government’s ability to monitor progress on structural transformation and distributional outcomes.

References

McMillan, M. S., & Rodrik, D. (2011). Globalization, structural change and productivity growth. NBER Working Paper No. 17143. National Bureau of Economic Research.

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.

From Integration to Reconstruction: Standing with Ukraine by Supporting Ukrainians in Sweden

Posted on April 7, 2025 | Policy Brief

People gathered in Sweden showing solidarity and supporting Ukrainians with national flags.

Sweden has strongly supported Ukraine through both public opinion and government actions, yet there has been little discussion about the needs of Ukrainian displaced people in Sweden. The ongoing war and the rapidly shifting geopolitical landscape have created uncertainty – geopolitical, institutional, and individual. Ukrainian displaced people in Sweden face an unclear future regarding their rights, long-term status, and opportunities, making future planning or investing in relevant skills difficult. This uncertainty also weakens the effectiveness of integration policies and limits the range of policy tools that can be deployed, which hinders participation in the labor market, affecting both displaced and employers. Addressing these challenges is essential, not only for the well-being of Ukrainians in Sweden, but also for Sweden’s broader role in supporting Ukraine. Helping displaced Ukrainians rebuild their lives also strengthens their ability to contribute both to Swedish society and to Ukraine’s future reconstruction and integration into Europe.

The Swedish Approach to Displaced Ukrainians

In response to the Russian full-scale invasion of Ukraine, the Temporary Protection Directive (2001/55/EC) (commonly referred to as collective temporary protection) was activated in March 2022, granting Ukrainians seeking refuge temporary protection in EU countries, including Sweden. This directive provides residence permits, access to work, education, and limited social benefits without requiring individuals to go through the standard asylum process.

However, the practicalities of the Directive’s use differed significantly between countries. Sweden, despite its, until recent, reputation of being relatively liberal in its migration policies, has at times, lagged behind its Scandinavian neighbors in supporting Ukrainian displaced people. To illustrate this, it is useful to compare the Swedish approach to that of other Nordic states, as well as Poland.

Comparison to Other Nordic States

The Nordic countries have implemented the directive in different ways, adopting varying policies toward Ukrainians demonstrating different degrees of flexibility and support. Despite its generally restrictive immigration policy, Denmark introduced some housing and self-settlement policies for Ukrainians that were more liberal than its usual approach. Norway also initially introduced liberal measures but later tightened regulations, banning temporary visits to Ukraine and reducing financial benefits. Finland, meanwhile, has taken a relatively proactive stance, granting temporary protection to over 64,000 Ukrainians – one of the highest per capita rates in the region. Its strong intake reflects a more flexible and effective implementation of the directive, particularly from late 2022, when it surpassed Sweden and Denmark in number of arrivals.

In Sweden the so-called “massflyktsdirektivet“ grants Ukrainians temporary protection until at least March 2025. Its future beyond that, however, remains uncertain, adding to the challenges faced by refugees and policymakers alike. Sweden – considered liberal in migration policies (at least, up until 2016) – has been criticized for offering limited rights and financial support to displaced Ukrainians, making it one of the least attractive destinations among the Nordic countries (Hernes & Danielsen, 2024). Under “massflyktsdirektivet”, displaced Ukrainians were entitled to lower financial benefits and limited access to healthcare compared to refugees or residents with temporary permits. It was only in July 2023 that they became eligible for Swedish language training, and only in November 2024 could they apply for residence permits under Sweden’s regular migration laws – a pathway that can eventually lead to permanent residence.

Figure 1 illustrates significant fluctuations in the number of individuals granted collective temporary protection in the Nordic countries over the first two years following Russia’s full-scale invasion. As Hernes and Danielsen (2024) show in a recent report, all Nordic countries experienced a peak in arrivals in March-April 2022, followed by a decline in May-June. Sweden initially received the most, but aside from this early peak, inflows have remained relatively low despite its larger population (Table 1). Since August 2022, Finland and Norway have generally recorded higher arrivals than Denmark and Sweden. By August 2023, Norway’s share increased significantly, accounting for over 60 percent of total Nordic arrivals between September and November 2023.

Figure 1. Total number of individuals granted collective temporary protection in the Nordic countries

Source: Hernes & Danielsen, 2024, data from Eurostat.

Table 1. Total number of registered temporary protection permits and percent of population as of December 2023

Source: Hernes & Danielsen, 2024, data from Eurostat.

Comparison to Poland

Sweden’s policies and their outcomes compare rather poorly to those of Poland, one of the European countries that received the largest influx of Ukrainian migrants due to its geographic and cultural proximity. A key factor behind Poland’s relatively better performance is that pre-existing Ukrainian communities and linguistic similarities have facilitated a smoother integration. Ukrainians themselves played a crucial role in this regard, with many volunteering in Polish schools to support Ukrainian children. Sweden also had a community of Ukrainians who arrived to the country over time, partly fleeing the 2014 annexation of Donetsk and Crimea. Since these individuals were never eligible for refugee status or integration support, they had to rely on their own efforts to settle. In doing so, they built informal networks and accumulated valuable local knowledge. Nevertheless, after the full-scale invasion in 2022, they were not recognized as a resource for integrating newly arrived Ukrainian refugees – unlike in Poland.

However, Poland’s approach was shaped not only by these favorable preconditions but also by deliberate policy choices. As described in a recent brief (Myck, Król, & Oczkowska, 2025), a key factor was the immediate legal integration of displaced Ukrainians, granting them extensive residency rights and access to social services, along with a clearer pathway to permanent residence and eventual naturalization.

Barriers to Labor Market Integration

Despite a strong unanimous support for Ukraine across the political spectrum, there is less public debate and fewer policy processes in Sweden regarding displaced Ukrainians, most likely attributable to the general shift towards more restrictive immigration policies. The immigration policy debate in Sweden has increasingly emphasized a more “selective” migration, i.e. attracting migrants based on specific criteria, such as employability, skills, or economic self-sufficiency. This makes it puzzling that displaced Ukrainians, who largely meet these standards, have not been better accommodated. Before the full-scale invasion, Sweden was a particularly attractive destination among those who wanted to migrate permanently, especially for highly educated individuals and families (Elinder et al., 2023), indicating a positive self-selection process.

When large numbers of displaced Ukrainians arrived after the full-scale invasion, many had higher education and recent work experience, which distinguished them from previous refugee waves that Sweden had received from other countries. Despite a strong labor market in 2022, their integration was hindered by restrictions imposed under the Temporary Protection Directive, which limited access to social benefits and housing. At the same time, Sweden explicitly sought to reduce its attractiveness as a destination for migrants in general, contributing to a sharp decline in its popularity among Ukrainians after the war escalated.

In addition to the restrictiveness and numerous policy shifts over time, the temporary nature of the directive governing displaced Ukrainians – rather than the standard asylum process – creates significant policy uncertainty. This uncertainty makes it difficult for Ukrainians to decide whether to invest in Sweden-specific skills or prepare for a potential return to Ukraine, whether voluntary or forced, complicating their long-term planning. It also hinders labor market integration, increasing the risk of exploitation in the informal economy. Another key challenge is the unequal distribution of rights, as entitlements vary depending on registration timelines, further exacerbating the precarious situation many displaced Ukrainians face in Sweden.

A survey of 2,800 displaced Ukrainians conducted by the Ukrainian NGO in Sweden “Hej Ukraine!” in February 2025 provides key insights into their labor market integration (Hej Ukraine!, 2025). Survey results show that, currently, 40 percent of respondents are employed, with 42 percent of them holding permanent contracts while the rest work in temporary positions and 6 percent being engaged in formal studies. Employment is concentrated in low-skilled sectors, with 26 percent working in cleaning services, 14 percent in construction, and 12 percent in hospitality and restaurants. Other notable sectors include IT (11 percent), education (8 percent), warehousing (7 percent), elderly care (5 percent), forestry (3 percent), and healthcare (3 percent). The lack of stable permits, access to language courses (until September 2024), and financial incentives for hiring displaced persons have complicated their integration.

As mentioned above, the Swedish government has over time introduced several initiatives to facilitate the integration of displaced Ukrainians. However, assessing their effectiveness is crucial to identify persistent challenges and to formulate targeted policy solutions.

The Role of the Private Sector and Civil Society

The business sector, civil society and NGOs have also played a role in supporting displaced Ukrainians, filling gaps left by the public sector. This includes initiatives aimed at creating job opportunities that encourage voluntary return. However, broader systemic support, including simplified diploma recognition and targeted re-skilling programs, is needed to enhance labor market participation.

Moreover, there is a lack of information among displaced, potential employers and public institutions (municipality level) about the tools and programs available. For example, a community sponsorship program funded by UNHCR, which demonstrated positive effects on integration by offering mentorship and support networks, was only applied by five municipalities (UNHCR, 2025). Similar programs could be expanded to address structural barriers, particularly in the labor market. Another example is the Ukrainian Professional Support Center established to help displaced Ukrainians find jobs through building networks and matching job seekers with employers (UPSC, 2024). The center was funded by the European Social Fund, and staffed to 50 percent by Ukrainian nationals, either newcomers or previously established in Sweden, to facilitate communication. Experiences from this initiative, shared during a recent roundtable discussion – Integration and Inclusion of Ukrainian Displaced People in Sweden, highlighted that between 2022 and 2024, about 1,400 Ukrainians participated in the project, but only one-third of participants found jobs, mostly in entry-level positions in care, hospitality, and construction. Restrictions under the temporary protection directive, along with the absence of clear mechanisms for further integration, posed significant challenges; the lack of a personal ID, bank account, and access to housing were considered major obstacles. The uncertainty of their future in Sweden was also reported as a significant source of stress for participants.

Implications and Policy Recommendations

The lack of clarity surrounding the future of the EU Temporary Protection Directive, as well as its specific implementation in Sweden, leaves displaced Ukrainians in a precarious situation. Many do not know whether they will be allowed to stay or if they should prepare for a forced return. This uncertainty discourages long-term investment in skills, housing, and integration efforts.

Uncertainty also affects Swedish institutions, making it difficult to implement long-term policies that effectively integrate Ukrainians into society. To address these issues, the following policy recommendations are proposed.

Extend Temporary Protection Status Beyond 2025: Clear guidelines on the duration of protection are necessary to provide stability for displaced Ukrainians
Improve Labor Market Access: Introduce targeted programs for skill recognition, language training, and financial incentives for businesses hiring displaced Ukrainians
Enhance Civil Society and Private Sector Collaboration: Support mentorship and community sponsorship programs that facilitate integration
Acknowledge and Utilize displaced Ukrainians as a Resource: Recognizing displaced Ukrainians as potential assets in rebuilding Ukraine and strengthening European ties should be a priority.
Increase Public and Policy Debate: There is a need for greater discussion on how to integrate Ukrainians in Sweden, as an important complement to the policy priority of providing aid to Ukraine.

By implementing these measures, Sweden can provide displaced Ukrainians with greater stability, enabling them to engage in the formal labour market rather than being pushed into informal or precarious employment. This not only benefits Ukrainians by ensuring fair wages and legal protection, but also strengthens Sweden’s economy through increased tax revenues and a more sustainable labour force.

As Sweden continues to support Ukraine in its fight for sovereignty, it should also recognize the value of displaced Ukrainians within its borders, fostering their contribution to both Swedish society and Ukraine’s eventual reconstruction.

References

Hernes, V., & Danielsen, Å. Ø. (2024). Reception and integration policies for displaced persons from Ukraine in the Nordic countries – A comparative analysis. NIBR Policy Brief 2024:01. https://oda.oslom et.no/oda-xmlui/handle/11250/3125012
Hej Ukraine! (2025). Telegram channel. https://t.me/hejukrainechat
Elinder, M., Erixson, O., & Hammar, O. (2023). Where Would Ukrainian Refugees Go if They Could Go Anywhere? International Migration Review, 57(2), 587-602. https://doi.org/10.1177/01979183221131559
EUROSTAT. Decisions granting temporary protection by citizenship, age and sex – monthly data. Dataset. https://ec.europa.eu/eurostat/databrowser/view/migr_asytpfm__custom_15634298/default/map?lang=en
Myck, M., Król, A., & Oczkowska, M. (2025, February 21). Three years on – Ukrainians in Poland after Russia’s 2022 invasion. FREE Policy Brief. Centre for Economic Analysis (CenEA). https://freepolicybriefs.org/2025/02/21/ukrainians-in-poland/
Ukrainian Professional Support Center (UPSC). (2024). https://professionalcenter.se/omoss/
United Nations High Commissioner for Refugees (UNHCR). (2025). Community sponsorship. UNHCR Northern Europe. Retrieved [March 6, 2025] from https://www.unhcr.org/neu/list/our-work/community-sponsorship

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.

Human Capital Loss Among Belarusian and Ukrainian Migrants to the EU

Posted on March 31, 2025 | Policy Brief

Silhouettes of construction workers on scaffolding at sunset, symbolizing underemployment among human capital migrants in the EU.

This policy brief examines the underutilization of human capital among involuntary migrants from Ukraine and Belarus in Poland and Lithuania. Focusing on those who migrated after 2020 (Belarus) and 2022 (Ukraine), the brief investigates the factors influencing the conversion of their pre-migration skills into gainful employment in their host countries. Our findings show that despite many migrants possessing high levels of education and professional qualifications, structural barriers and low convertibility of their skills, hinder their full labor market integration. This skill underutilization not only limits migrants’ professional growth and earning potential but also deprives the host countries of valuable skills and potential economic gains.

Effective labor market integration substantially benefits both host and sending countries and migrants themselves. For host nations, successful integration can alleviate critical skill shortages, boost productivity, and drive economic growth (Boubtane, Dumont, & Rault, 2016; Boubtane, 2019; Engler, Giesing, & Kraehnert, 2023; Bernstein et al., 2022). Conversely, inadequate integration leads to underemployment, diminished potential, and economic inefficiency. Countries of origin can benefit from remittances, the return of migrants with enhanced skills, and strengthened international economic ties. However, poor integration risks an uncompensated “brain drain” (Reinhold & Thom, 2009; Barrett & O’Connell, 2001; Iara, 2006; Barrett & Goggin, 2010; Co, Gang, & Yun, 2000). For migrants, the ability to continue their careers means higher earnings and less stress from the acquisition of a new profession, while the non-utilization of existing skills results in their depreciation, potentially causing permanent wage reductions even upon return to the home country (Bowman & Myers, 1967).

Migrants can be broadly categorized into voluntary migrants or forced migrants. Voluntary migrants assess labor market prospects beforehand and often possess convertible human capital – one that can be used in a new labor market. This group often includes professionals like IT specialists and scientists and those in low-skilled but highly transferable professions. Forced migrants, on the contrary, may be utterly unprepared for changes in jurisdiction and possess skills of limited transferability. For example, even highly specialized professions requiring extensive training and substantial human capital, such as lawyers, officials, and teachers, often prove “non-convertible“ (Duleep & Regets, 1999). These individuals’ skills are frequently country specific.

Low convertibility of skills generates significant negative consequences. Highly educated professionals, for instance, may find themselves relegated to low-paying, unskilled jobs, unable to leverage their expertise. This hinders their professional development and deprives host countries of valuable skills and potential contributions to economic growth. Addressing these mismatches is crucial for maximizing the benefits of migration for stakeholders in both home and host countries.

Forced Migration from Belarus and Ukraine

The political crisis in Belarus, starting with the contested 2020 presidential elections, led to widespread repression and significant forced migration. Belarus’s role in supporting Russia’s 2022 invasion of Ukraine exacerbated this situation, resulting in approximately 300,000 Belarusians seeking refuge in the European Union (Eurostat). This number accounts for a substantial proportion of the country’s 9 million population and its approximately 5 million-strong labor force (Belstat).

Russia’s full-scale invasion of Ukraine triggered the most significant wave of migration in Ukrainian history, with over 6 million of the pre-war 44 million population fleeing to the EU (UNHCR). About 90 percent of the initial refugees were women and children due to a mobilization law preventing most men aged 18 to 60 from leaving (UNHCR).

Online Survey and Migrant Differences

To better understand the situation of migrants, their integration into the EU labor market, and to develop data-driven recommendations for improving their conditions, the CIVITTA agency, in partnership with BEROC, conducted an online survey in the summer of 2024. This brief is based on the survey results. The survey includes responses from 616 Ukrainian nationals who migrated to Poland or Lithuania after Russia’s full-scale invasion of Ukraine in 2022, as well as 173 Belarusian migrants who left their home country after 2020. The research focuses on individuals aged 28 to 42, providing insights into their experiences and challenges in the labor market in their host countries. While we acknowledge the sample’s limitations in terms of representativeness, we believe the findings provide valuable insights into the specific challenges faced by involuntary migrants and their adaptation strategies in the new labor market.

Key differences characterize these migration waves. Ukrainian migration comprises of more women, while Belarusian migrants show a more balanced gender distribution, with 47 percent women in our sample versus 62 percent for Ukrainians. Family separation is also notable, as 91 percent of married Belarusians live with their spouses, compared to only 75 percent of Ukrainians (due to the mobilization law).

Survey respondents from both groups possess high levels of human capital with 60 percent of Ukrainians and 90 percent of Belarusians holding higher education degrees. Among Belarusians, 94 percent had over five years of work experience before migration, with and 79 percent of Ukrainians stating the same.

Ukrainian return intentions are split: 38 percent plan to return, 19 percent will not, and the rest are undecided. An end to the war and changes in Russian foreign policy would increase return rates to 70 percent. For Belarusians, 35 percent plan to return, 38 percent will not, and the rest are undecided. Education level is key, as less-educated Belarusians are more likely to stay abroad. An end to repression would increase the share of those Belarusians who want to return to 70 percent, and a regime change would increase this percentage to 82 percent.

Factors Conditioning Human Capital Loss

As expected, due to the involuntary nature of migration of the two groups in focus, a large fraction of survey participants reported losing their profession after migration. As Figure one shows, 48 percent of Belarusians and 63 percent of Ukrainians in our sample reported full loss of their prior careers. The lower percentage of Ukrainians fully retaining their careers (23 percent) compared to Belarusians (44 percent) could be attributed to several factors, including the more recent and disruptive nature of the Russo-Ukrainian war leading to more significant displacement and challenges in finding comparable work. The higher percentage of Ukrainians starting their careers from scratch (49 percent compared to 29 percent among Belarusians) also supports this idea.

Figure 1. Preservation of careers in the EU

Source: Authors’ computations based on survey data.

To foster an evidence-based discussions on the smooth integration of migrants into the EU labor market and the prevention of human capital loss, it is crucial to examine the individual factors that influence career continuity for Belarusian and Ukrainian migrants. We therefore utilize a logistic regression model to identify key predictors that increase the likelihood of migrants remaining in their profession after relocating to Poland and Lithuania.

In our quantitative analysis, an outcome binary variable for staying in the profession is equal to 1 if an individual either “continued career started in a home country (in the same position)” or “remained in the same profession but started working in a position lower than the one held before emigration.” As predictors, we consider a set of sociodemographic variables reasonably related to the probability of staying in the profession and dummy variables for the most common spheres of employment (see Table 1).

Table 1. Overview of model variables

Who Maintains Their Career After Emigration?

Based on the regression coefficients in Table 2, we can identify characteristics related to losing career-specific human capital. In our regression, we control for both home and host country factors. One noteworthy finding is that, while Ukrainian migrants in our sample report significantly higher rates of career loss than Belarusian migrants, nationality itself does not emerge as a significant predictor of career loss once other characteristics are accounted for.

Our results also show that the probability of staying in a profession is higher among men, those with more extended work experience and higher income before emigration, and those who were invited to a host country by an employer. The same holds for entrepreneurs, those who do not plan to return, and those employed in the fields of Architecture & Engineering and Information and Communication Technologies.

Table 2. Results of regression analysis

Note: *** Significant at the .001 level. ** Significant at the .01 level. * Significant at the .05 level.

Conclusion

Several conclusions and policy advice can be derived from the survey results.

The higher likelihood of entrepreneurs staying in their profession suggests that supporting migrant entrepreneurship can be a valuable strategy to retain human capital. This can be done, for example, by:

Providing access to resources, mentorship, and funding for migrant entrepreneurs.
Streamlining the procedures for migrants to start and operate businesses.
Facilitating access to capital for migrant-owned businesses.

The research highlights the disproportionate impact of human capital loss on women. Therefore, policies should include gender-specific programs that address women’s unique challenges in integrating into new labor markets. This could include:

Skills retraining and certification programs: Designed to align women’s existing skills with the demands of the host country’s labor market, with consideration for childcare needs and other barriers women may face.
Connecting women migrants with established professionals in their fields to facilitate knowledge transfer and career guidance.
Language training programs: Tailored to the specific needs of women, potentially incorporating childcare support to enable participation.

The study highlights the positive role of international companies in supporting employee relocation. Respondents who were invited by an employer demonstrated the most successful integration into the new labor market. To enhance and strengthen these networks, policies may focus on:

Encouraging corporations to hire and train migrant workers, potentially through tax breaks or other incentives. This could include partnerships with migrant-serving organizations to connect companies with qualified candidates.
Developing digital platforms that connect migrants with diaspora networks, potential employers, and relevant resources.

In addition, policies should address the non-recognition of foreign qualifications, simplifying and expediting the procedures for recognizing foreign degrees and professional certifications. Initiatives to create targeted training programs could complement such policies and allow migrants to quickly acquire any missing skills or certifications required by the host country’s professional bodies. These policy measures would enhance the utilization of migrants’ human capital, benefiting both migrants and host countries while also supporting sending countries. This could be achieved by fostering a successful diaspora or facilitating productive reintegration in the case of return migration.

References

Barrett, A., & Goggin, J. (2010). Returning to the question of a wage premium for returning migrants. National Institute Economic Review, 213, R43–R51. https://doi.org/10.1177/0027950110389752
Barrett, A., & O’Connell, P. J. (2001). Does training generally work? The returns to in-company training. ILR Review, 54(3), 647–662. https://doi.org/10.1177/001979390105400403
Bernstein, S., Diamond, R., McQuade, T. J., & Pousada, B. (2022). The contribution of high-skilled immigrants to innovation in the United States (No. w30797). National Bureau of Economic Research. https://doi.org/10.3386/w30797
Boubtane, E. (2019). The economic effects of immigration for host countries. L’Economie politique, 84(4), 72–83. https://doi.org/10.3917/leco.084.0072
Boubtane, E., Dumont, J.-C., & Rault, C. (2016). Immigration and economic growth in the OECD countries 1986–2006. Oxford Economic Papers, 68(2), 340–360. https://doi.org/10.1093/oep/gpv024
Bowman, M. J., & Myers, R. G. (1967). Schooling, experience, and gains and losses in human capital through migration. Journal of the American Statistical Association, 62(319), 875–898. https://doi.org/10.2307/2283723
Co, C. Y., Gang, I. N., & Yun, M.-S. (2000). Returns to returning. Journal of Population Economics, 13, 57–79. https://doi.org/10.1007/s001480050121
Duleep, H. O., & Regets, M. C. (1999). Immigrants and human-capital investment. American Economic Review, 89(2), 186–191. https://doi.org/10.1257/aer.89.2.186
Engler, P., Giesing, Y., & Kraehnert, K. (2023). The macroeconomic effects of large immigration waves. IAB-Discussion Paper. https://doi.org/10.5167/uzh-239271
Iara, A. (2006). Skill diffusion in temporary migration? Returns to Western European working experience in the EU accession countries (Development Studies Working Paper No. 210). Centro Studi Luca d’Agliano. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=921492
Reinhold, S., & Thom, K. (2009). Temporary migration and skill upgrading: Evidence from Mexican migrants. University of Mannheim, unpublished manuscript.
UNHCR. (n.d.). Operational Data Portal. https://data.unhcr.org/

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Three Years On – Ukrainians in Poland after Russia’s 2022 Invasion

Posted on February 21, 2025 | Policy Papers

Ukrainians in Poland rallying in Kraków, waving Ukrainian and Polish flags.

The wave of Ukrainian refugees which followed the full-scale Russian invasion on February 24^th, 2022, was in Poland met with unprecedented levels of support and solidarity. According to data from the Polish Household Budget Survey, 70 percent of households offered some help, and over 10 percent (1.3 million households) provided direct personal assistance. Overall, by early 2025, 1.9 million refugees had registered in the dedicated social security registry (PESEL-UKR system) and 1 million continue to be registered as residing in Poland. Drawing on other data sources we argue in this policy paper that the latter figure is highly overstated, giving rise to unjustified criticisms of low school enrolment among Ukrainian children, and low rates of labour market activity among adult refugees. We highlight the risks that these critical voices may become prominent in the ongoing campaign ahead of the Polish presidential elections. During the crucial months of prospective peace negotiations, when presidential candidates are appealing for voters’ support, we argue that the public debate in Poland concerning Ukraine and Ukrainian refugees, ought to be grounded in reliable evidence.

Introduction

The dramatic events of late February 2022 shook the populations across Ukraine, Europe and the world. The objective of the massive, full-scale Russian aggression was clear – to rapidly take over Kyiv, force Ukraine to surrender and take over full control of the country thus subjugating it into Kremlin’s rule. Three years later, while thousands of Ukrainian soldiers and civilians have lost their lives, and while Russia has imposed a massive economic and social burden on Ukraine, its key objective has badly failed and remains far from being realised. This thanks to the commitment of the Ukrainian government, the country’s army and the mobilisation of the Ukrainian population. In turn, the country’s resistance would not have been possible without substantial support from the outside, primarily from countries in the European Union and the U.S. International aid from governments to Ukraine between February 2022 and October 2024 amounted to over €230 billion (bn) with the largest part contributed by the US (€88 bn), the European Commission and European Council (€45 bn) and Germany (€16 bn). Proportional to 2021 GDP levels, the highest support came from Estonia (2.20 percent), Denmark (2.02 percent) and Lithuania (1.68 percent) (Kiel Institute, 2024). Support for Ukraine has come in many forms – military, material, financial, political and diplomatic. The international community has also imposed substantial economic and political sanctions against Russia, and has excluded it from many international forums, marginalising its voice in international discussions and meetings.

On top of that, Ukraine’s neighbours and many Western countries opened their borders and welcomed a massive wave of refugees escaping the immediate military invasion in the east and north of Ukraine, seeking safety from continued bomb and drone attacks on the entire country, and running away from the risk of a complete Russian take-over. It is estimated that up to 8 million Ukrainians left the country in the first months after the full-scale war started, initially moving mainly to Poland, Romania and Slovakia (Polish Economic Institute, 2022; UNCHR, 2022). At the same time the Russian aggression resulted in internal displacement of more than 3.6 million Ukrainians (IOM UN Migration, 2024). While many of the international and internal refugees have since returned, over 6.8 million Ukrainians still reside outside of Ukraine’s borders (UNCHR, 2025).

The wake of the war was met with an unprecedented wave of support among the Polish population (Duszczyk and Kaczmarczyk, 2022). We use data from one of the largest representative Polish surveys – the Household Budget Survey 2022 and 2023 – to show the degree of involvement among Polish households in direct and indirect support to Ukrainian refugees. We also show that declarative general sympathy towards Ukrainians reached over 50 percent in 2023 – twice as high compared to 16 years earlier. This support has by now fallen close to the levels from just before the full-scale war (40 percent). As the immediate need for help has become less urgent, and the refugees have organised their lives in Poland, the involvement of Polish households in supporting the Ukrainian population has also declined. At its peak at the beginning of the war the proportion of Polish households that were actively involved in helping the Ukrainian population reached nearly 70 percent, with over 10 percent (i.e. more than 1.3 million) of the households providing direct assistance to the refugees.

In this policy paper we call into question some of the official data on the number of Ukrainian refugees who continue to reside in Poland (almost 1 million) (EUROSTAT, 2025). We argue that inconsistency across different sources with regard to precise numbers – such as likely inflated refugee count in the official social security register – may be used to build unfavourable claims against the refugees and the Ukrainian cause overall, as arguments and narratives develop based on marginal anecdotal evidence and incorrect statistics. As the new U.S. administration tries – in its own way – to bring an end to the war, Ukraine will need continued strong support from all Western allies to end the war on favourable terms for Ukraine and to get significant additional help to rebuild the country. Ukraine’s safety and economic security will depend on Western military guarantees and closer integration with the EU. All of this requires the support of populations in these countries, which gets increasingly undermined by internal disputes and external political interferences.

As negotiations to end the war begin to take shape, Poland enters a crucial electoral campaign ahead of its May 2025 presidential elections. This combination is likely to place the Ukrainian question among the top issues on the local agenda. At the same time, there is a risk that the extent of support towards Ukraine and Ukrainian residents in Poland will be used in the battle for electoral votes. We argue that any debate around this topic should draw on reliable, up to date data sources. In this regard, the government should provide more information to clarify data inconsistencies, to shed more light on the situation among Ukrainian citizens currently residing in Poland, and to ensure that any doubtful narratives raised in the public debate are quickly addressed.

Ukrainian sovereignty, its peaceful development and prosperity are very much in the interest of both Poland and the rest of Europe. Therefore, the Polish government must provide arguments to reinvigorate the support for Ukraine among its population. This will be fundamental to ensure Ukraine’s military success and stability, to guarantee the mutual benefits of integration of the Ukrainian population in Poland, and for the future economic cooperation with Ukraine in the prospective enlarged European Union.

The Outbreak of the Full-Scale War: Ukrainians in Poland

In the first couple of months after the full-scale Russian invasion of Ukraine on February 24^th 2022, over 2 million refugees fled to Poland through the common land border, with as many as 1.3 million people crossing the border during the first two weeks of the war (Figure 1a). The exact number of refugees who arrived in Poland is difficult to gauge as some people left Ukraine via the border with Romania or Slovakia and could have entered Poland across the uncontrolled borders of the Schengen area.

BOX 1. Ukrainian citizens in Poland before the war in 2022

Before February 24, 2022, the migration of Ukrainian citizens to Poland was regulated by existing legal mechanisms concerning all foreigners coming from non-EU countries (European Parliament, 2010). Migrants could apply for a temporary residence permit for a maximum of three years, most often in connection with prearranged employment or education (Sejm RP, 2013). Since 2017 Ukrainian citizens with biometric passports could travel to Poland and other EU countries without a visa, but their stay was limited to 90 days (European Parliament, 2017). Access to the Polish social transfer system for migrants and their families was strictly regulated and limited. Labor migrants and temporary visitors under the visa-free regime had no right to public benefits or healthcare (Sejm RP, 2003).

At the time, application for refugee status was possible, but required undergoing a lengthy and burdensome asylum procedure. Those with refugee status granted had access to public transfers and healthcare (Sejm RP, 2003).

In accordance with the European regulations of Council Directive 2001/55/EC of 20 July 2001, the Polish government responded to the refugee crisis by establishing a special residence status for those fleeing the war. The regulations were introduced as early as March 12, 2022, and as a result, all Ukrainian refugees who arrived in Poland since 24 February could register themselves (and their family members) in a special social security registry, the so-called PESEL-UKR (Sejm RP, 2022). This registration immediately provided the refugees with an official status of temporary protection and legalized their stay in Poland until a specified date, which – as the war continued – has been regularly extended. In comparison to other, non-EU migrants, the PESEL-UKR status grants the refugees simplified access to the Polish labour market and gives them access to public healthcare and social transfers – including general support available to all legal residents, as well as special financial and non-monetary aid targeted specifically at refugees (Duszczyk and Kaczmarczyk, 2022). The registration process was streamlined and widely accessible in all municipality offices throughout Poland and resulted in rapid registration of the majority that had arrived to Poland since February 24, 2022. By the end of June 2022, 1.2 million individuals had registered for the PESEL-UKR status. The number grew to 1.4 million by October 2022 and continued to grow to 1.9 million registrations by January 2025. As evident from Figure 1b not all of those who crossed the Polish border (or arrived in Poland having left Ukraine through a different country) stayed in the country. Some continued their journey to other EU countries and beyond, while some decided to return to Ukraine. It is worth noting though that of all the registrations carried out by the end of 2024, nearly half happened in the first 8 weeks following the invasion.

Figure 1. Number of Ukrainian citizens crossing the border between Poland and Ukraine and registering for PESEL-UKR, 2021-2024

Note: Weekly data on crossings via all land borders with Ukraine.
Source: Open Data Portal (2025a, 2025b).

A notable and important legal change was introduced in October 2022, whereby individuals are automatically withdrawn from the PESEL-UKR registry after a period of 30 days when they (1) leave Poland, (2) apply for a residence permit, or (3) apply for international protection status (Sejm RP, 2022). This change is the reason for the substantial drop in the number of registered refugees at the end of 2022, with over 400 000 individual withdrawals (Figure 1b). This change in legislation was aimed at estimating more precisely the number of Ukrainian refugees currently residing in Poland. However, since withdrawals from the system require that departures from the territory of Poland are officially recorded at the border, or follow a parallel registration in another EU country, or are recorded as departures from the Schengen area through another country, the numbers in the system may still be far from the actual number of refugees currently residing in Poland.

Since late 2022 the number of registered Ukrainian refugees in Poland has been fairly stable at slightly below 1 million. Similarly, the shares of different age cohorts have not changed. In Figure 2 we show the split of those in the PESEL-UKR registry by age. Children under the age of 18 account for about 40 percent of all refugees, of which 30 percent are in schooling age (7-17). 7 percent of the refugees are aged 62 years or older. Among those aged 18-61 years old, 70 percent are women. It is worth noting that out of about half a million children recorded in the first 7 months, almost 400 000 are still registered in the PESEL-UKR registry, a number that has been stable since the end of 2022. As we show below, these values are significantly higher compared to the number of refugee children reported by two other administrative sources. This in turn casts doubt on the reliability of the estimates of the total number of Ukrainian refugees in Poland.

Figure 2. Ukrainian citizens registered with PESEL-UKR, by age group

Note: Based on registered year of birth, age as of 2025.
Source: Open Data Portal (2025b).

Where Are All the Registered Children?

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

Figure 3. Number of school-age children among Ukrainian refugees

Note: School registrations: all school types except preschool education, post-secondary schools, schools for adults and grades in which children are at least 18 years old. Ukrainian refugees only. Child benefit data points as reported in June, October and December.
Source: Open Data Portal (2025b, 2025c); information on 800+ benefit recipients: unpublished data from the Social Insurance Institution (ZUS).

As evident from Figure 3 though, from late 2023 all the way until early 2025, the ‘800+ benefit’ (which is a universal child benefit paid to all children aged 0-17) was paid to around 150 000 Ukrainian refugee children aged 7-17. Given the ease of claiming the benefit, and the relatively high value of the transfers (about 23 percent of net minimum wage per child per month), it seems very unlikely that so many families would opt out of the support. Looking at the close match between the numbers from ZUS and from the Ministry of Education, the more likely interpretation of the figures is not that children stay away from school and fail to claim social transfers, but rather that far fewer children continue to reside in Poland.

An additional argument supporting the inaccuracy of the PESEL-UKR data comes from a report published by the Narodowy Bank Polski (the Polish Central Bank) (NBP, 2024). Using information from a large survey conducted among Ukrainians living in Poland the report shows that 83 percent of school-age children in refugee families were enrolled in either a Polish or a Ukrainian school physically based in Poland. This is very far from the 56 percent rate calculated with reference to administrative data, again suggesting that the PESEL-UKR numbers of school-age children are highly inflated. If that is the case, not only the number of refugee children but the overall PESEL-UKR numbers (992 000 by January 2025) should be called into question.

How Many of the Registered Adults Are Active on the Labor Market?

The accuracy of the overall number of refugees is important because it is one of the key references for policy discussions. While international regulations specify that victims of war and conflict are granted the same basic rights and privileges as other legal residents, including access to the labour market, healthcare and other public services (Duszczyk et al., 2023), negative sentiments towards Ukrainian citizens have recently grown in Poland. Further, various restrictions on access to public support for Ukrainian refugees have already been publicly discussed and proposed in Parliament. These sentiments feed on the claims of fraudulent behaviour, unwillingness to engage in official employment and crowding out of public services for Polish nationals. Such claims about Ukrainians are spread more easily if not met by accurate numbers.

Figure 4. Number of Ukrainian men and women contributing to pension insurance in Poland

Note: ‘Other countries’ refers to other registered foreigners.
Source: Social Insurance Institution ZUS (2024).

Looking at labour market activity, the number of Ukrainians who were officially active on the Polish labour market (as employees, self-employed or receiving unemployment benefit) and who thus paid pension contributions to social security in December 2023 stood at 759 000 (see Figure 4). Of those 396 000 were men and 363 000 were women. While ZUS, the Social Insurance Institution, does not distinguish between migrants (those with the right to stay before February 24^th, 2022) and refugees (with PESEL-UKR status) it seems safe to assume that those who registered in the ZUS database in 2022 and 2023 belong to the latter group. The difference between the number of Ukrainians contributing to social security in December 2021 and December 2023 is 132 000 and, as seen in Figure 4, the additional numbers of those registered differ only for Ukrainian women. New Ukrainian male refugees certainly also appear in the database in 2022 and 2023, but their number is difficult to estimate as some earlier migrants returned to Ukraine after the outbreak of the war, and as a result the net effect of men between 2021 and 2023 is essentially zero. Focusing on women, we can compare the number of new registrations in the ZUS database to the total number of women aged 18-59 (excluding students) in the PESEL-UKR database (about 335 000 in December 2023). Such a ratio would suggest that only about 40 percent of female Ukrainian refugees are formally contracted on the Polish labour market (on contracts paying social security contributions). This is much lower than the values presented in the NBP report (2024), suggesting that in July 2024, around 70 percent of the adult war refugees were working and further 19 percent were looking for a job. This comparison once again suggests that the PESEL-UKR numbers are significantly inflated.

Addressing the public concerns with regard to school enrolment and labour market activity with correct figures could help counter the growing negative sentiments towards Ukrainians in Poland as well as towards the overall support for the process of securing peace in Ukraine and integrating it closer with Poland and the EU. In the next section we show that when the full-scale war started in February 2022, not only the sentiments were strongly in favour of supporting Ukraine. Additionally, the level of engagement of the Polish population in actively assisting Ukrainian refugees was truly unprecedented.

Individual Support in Response to the Outbreak of the War

In the first few weeks after the full-scale Russian invasion the Polish society almost uniformly united in providing help and assistance to Ukrainians affected by the war. The Polish Economic Institute estimated that during the first 3 months the financial, humanitarian and material help provided by the Polish society alone reached 9-10 billion PLN, which corresponded to 0.34-0.38 percent of Poland’s GDP (Baszczak et al. 2022). Polish private businesses were also quick to join the assistance efforts, donating money, food, medical and other specialized equipment, and providing services such as transportation, insurance, and education free of charge (WEI 2023). Until May 2022, 53 percent of Polish enterprises engaged in different kinds of relief or support.

The assistance to refugees has been documented in numerous anecdotes, formal reports and extensive media coverage. The scale of support is also reflected in the Polish Household Budget Survey, a regular household survey conducted by the Central Statistical Office. Already in the first quarter of 2022 the survey included several questions related to the assistance given by the interviewed households to Ukrainian refugees. These questions were then included in the survey throughout 2022 and 2023. As shown in Figure 5, when the inflow of refugees from Ukraine started in late February 2022, nearly 70 percent of Polish households offered some form of assistance. Most of this help took the form of gifts and money transfers, but 10.4 percent, i.e. over 1.3 million Polish households, offered direct help such as transport, providing an overnight stay, delivering goods to accommodation venues, etc. The fraction of those offering assistance stayed very high through the first half of 2022, and 23 percent of Polish households still provided some form of assistance in the last quarter of 2022 (Figure 5). As the war stalled, and the Ukrainian population settled and became more independent, and the Polish government took official responsibility of assisting those still in need, the level of direct support from households fell. However, in late 2023 9 percent of Polish households still continued to provide some form of assistance. What is really special about the initial wave of support is that the positive attitudes towards the refugees and the Ukrainian cause were nearly universal. As seen in Figure 6, assistance was offered by high and low educated households (79 and 59 percent), those living in large cities and in rural areas (73 and 68 percent), the young and the old (66 and 63 percent). Households who declared good material conditions were more likely to offer help (75 percent), but even among those who declared difficulties with their financial status 41 percent came forward to offer some assistance.

Figure 5. Polish households engaged in assisting Ukrainian refugees, 2022-2023 (by quarter)

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

Figure 6. Polish households engaged in assisting Ukrainian refugees (any help) in the first quarter of 2022, by household characteristics

Notes: Urban status – A: rural area, B: city below 100 000 inhabitants, C: city over 100 000 inhabitants. Material situation (self-assessed) – D: bad or rather bad material situation, E: average material situation, F: good or rather good material situation. Age of head of household – G: 18-29, H: 30-59, I: 60 and older. Education of head of household – J: lower than secondary, K: secondary or postsecondary, L: tertiary. Source: own compilation based on the Polish Household Budget Survey 2022.

It is worth noting also that by the time the full-scale war broke out in February 2022 the sentiments among the Polish population towards Ukrainians had improved compared to attitudes in the 1990s and early 2000s. These sentiments have been regularly surveyed by the Public Opinion Research Center CBOS, and we summarize them in Figure 7. As evident, in the early 1990s the proportion of Poles declaring positive sentiments towards Ukrainians was very low. It steadily increased until about 2017 and then grew rapidly from 2018 till 2020. In 2022 the sentiments towards Ukrainians reached their peak, with over 50 percent of Poles declaring fondness towards them – on par with nations such as Lithuania and Slovakia. At the same time positive attitudes towards Russians reached an all-time low of 6 percent. Positive sentiments towards Ukrainians declined in 2024 – the last year for which the data is available – but even after the drop they are still high when compared with attitudes before 2023.

While the general positive sentiments towards Ukrainians in Poland has improved over the years, 2022 was truly unique when it comes to attitudes toward Ukrainian refugees (see Figure 8). Between 2015 and 2018, i.e. after Russia’s annexation of Crimea in 2014, around 50-60 percent of Poles declared that refugees from the conflict areas in Ukraine should be welcomed in Poland. When the same question was asked again in March 2022, 95 percent agreed that Ukrainian refugees should be welcomed in Poland and nearly 60 percent declared that they ‘definitely’ agreed with such a policy. However, the proportion of Poles in support of welcoming Ukrainian refugees has decreased. In late 2024 the share was more or less back at the level prior to the full-scale war, i.e. at over 50 percent.

Figure 7. Share of survey participants declaring fondness towards foreigners of different origin

Source: The Public Opinion Research Center CBOS (2024a).

Figure 8. Opinion survey: If Poland should accept Ukrainian refugees coming from the conflict territories

Note: The surveys were discontinued between 2018 and 2022.
Source: Public Opinion Research Center CBOS (2024b).

Why Have Sentiments Shifted?

At the crucial time of a possible long-awaited end to the Russian invasion, when coordinated support of Western governments will be essential to secure a just and long-lasting solution, the willingness of these governments to firmly stand behind Ukraine will, to a large extent, depend on the sentiments among their voters. Thus, the wavering enthusiasm for the Ukrainian cause in countries such as Poland can be seen as a worrying sign, in particular given how high the level of support was in the early days of the invasion. This support will be particularly important over the next few months, given the likely period of intensive international negotiations and the battle for votes in the upcoming Polish presidential elections.

It is not unusual to try to put the blame for various unfortunate developments on external forces, including global trends, external conflicts and all things ‘foreign’. Thus, the fact that many people in various countries, including Poland, blame their perceived worsened economic conditions on the consequences of the war and the related influx of Ukrainian refugees is far from surprising. While some politicians might want to explain the complex broad context, others will take advantage of these sentiments and continue to fuel the negative discourse. With that in mind, three main topics have been particularly visible in the public debate in Poland:

access to social transfers, in particular to the ‘800+’ child benefit for Ukrainian refugees
Ukrainian refugees’ participation in the Polish labour market and tax contributions to the local budget
risks to particular groups of interest, most prominently reflected in Poland by the crisis surrounding imported Ukrainian grain (see Box 2)

The first two issues are strongly related to the general approach to immigration and integration of migrants in the Polish society. The popular media discourse – in traditional and social media – tends to focus on instances of abuse of social support and public services, and to build up negative sentiments along the lines of supposed unwillingness to engage in legal economic activity among those who have settled in Poland. While one can certainly identify anecdotes which selectively confirm all sorts of misbehaviour, the overall evidence would clearly reject such claims. As discussed, the surveys conducted by the NBP show that a significant majority of migrants and refugees from Ukraine find legal employment in Poland. Further research based on administrative data demonstrates that many Ukrainians establish and successfully run their businesses in Poland (Polish Economic Institute, 2024). Between January 2022 and June 2024 Ukrainian migrants and refugees established almost 60 000 enterprises in Poland, and as Vézina et al. (2025) argue, these firms did not crowd out Polish businesses, meaning they represent a true value added to the national and local economies.

Recent public discussions, however, have focused on the combination of employment and benefit claims. The debate started with two parliamentary initiatives by the right wing Konfederacja and Prawo i Sprawiedliwość opposition parties and was then picked up by the leading government party’s presidential candidate, Rafał Trzaskowski (money.pl, 2025). The proposed legislative changes are broadly similar, suggesting that access to the main child benefits – the ‘800+ benefit’ – should be limited to those refugee families where at least one of the parents is formally employed. Such conditionality does not apply to Polish families, and according to current legislation, to no other families legally residing in Poland (Konfederacja, 2025; Prawo i Sprawiedliwość, 2025). The supposed aim of the changes would be to, first of all, limit fraudulent claims among those who no longer reside in Poland, and secondly, to restrict access to the benefits to those who contribute with their taxes to the public budget only. On both counts the policy seems badly misconceived. As shown above, the ‘800+’ claims closely match the numbers of children officially registered in Polish schools, far below the numbers registered in the PESEL-UKR database. Moreover, such a policy is unlikely to lead to much higher employment among refugee parents. The benefit is universal and received by all families regardless of employment status or income; previous research has shown a similar benefit to have negligible effects on employment (see for example: Myck and Trzcinski, 2019). Therefore, the most likely reason for some refugee parents to not take up work is not unwillingness, but rather other constraints – constraints which will not change as a result of the proposed restrictions. Most Ukrainian families who fled the war are mothers whose partners could not join them due to military restrictions on the mobility of Ukrainian men. While many women settled and found jobs, family obligations may significantly limit some refugee’s options for regular employment. For these families, withdrawing the eligibility for the ‘800+ benefit’ would be a significant loss of income with potentially dire consequences for their children. It is thus difficult to understand the initiatives as anything other than attempts to address the growing critical sentiments towards the refugees to gain support among voters who are convinced by the anecdotal narrative. As argued above – with the exception of anecdotes – there is very little evidence in support of such legislative changes. Even from the point of view of potential budgetary gains, the proposed limitations on benefit claims would impose heavy administrative costs which would likely exceed any resulting savings. The politicians coming forward with such proposals would be well advised to consider data from various sources and avoid raising issues which have a clear potential to fuel negative sentiments towards refugees and migrants.

BOX 2. The dispute over the Ukrainian grain

In February 2022, Russia’s full-scale invasion destabilized the Ukrainian market, in particular the agricultural sector, due to blocked exports through the Black Sea. To enable exports, so-called Solidarity Lanes were established, including corridors crossing Poland (European Commission 2022). However, Poland was not prepared to handle and re-export large volumes of Ukrainian agricultural products, due to insufficient capacity of Polish sea ports (farmer.pl, 2023; for such quantities experts argue that road transport is unprofitable; Kupczak, 2023). This led to a surplus of grain in multiple storehouses throughout the country, especially in Southeastern Poland. Overall, Polish grain stocks increased by over 250 percent, from 3.8 to almost 10 million tones (Supreme Audit Office, 2023).

The drastic surplus of grain, together with much lower prices for Ukrainian crops, led to a dramatic price drop—one could buy mixed Polish-Ukrainian grain for half the price it cost the previous year (rp.pl, 2023). Apart from its impact on quantity and price, Ukrainian grain drew public attention also due to concerns regarding its quality (money.pl, 2023). Imported agricultural and food articles must undergo rigorous quality controls at the border, depending on their purpose – human consumption, animal fodder or cultivation, conducted by the respective state inspection office. Random controls held in 2022 by the Food Articles Inspection revealed that 2.4 percent of the grain samples were banned from entering the market (rp.pl, 2023).

According to a report by the Supreme Audit Office (2023), controls run by the Veterinarian Inspection were drastically limited as of May 2022 which allowed poor quality fodder grain to enter the Polish market (Supreme Audit Office 2023). Since technical grain – used in the production of biofuels, insulating materials or oils – is exempt from border quality controls, its imports and sale as consumable grain could be particularly profitable. Several incidents of such forgery were subject to investigation confirming that large quantities of technical grain originating from Ukraine were sold as consumable to Polish companies (gov.pl, 2024).

The tightened border controls that followed, resulted in multiday delays in the transportation of food products from Ukraine. To mitigate these constraints an agreement was reached, and, as of March 8, 2023, grain transit through Poland to other final destinations (within EU or to a third country via Polish ports) is exempt from border controls at the Polish-Ukrainian border and sealed by the National Revenue Administration. These seals can be removed only at the final destination (gov.pl, 2023a).

Throughout this period Polish farmers held demonstrations opposing the influx of Ukrainian grain. The border crossings with Ukraine were temporarily blocked by protests aimed at disrupting the flow of goods. The symbolic dumping of Ukrainian grain on the ground at the Medyka border crossing resulted in a famously cited statement by the Ukrainian President Volodymyr Zelensky that this event may be seen as evidence of the “erosion of solidarity” with Ukraine (BBC, 2024).

After the EU-level temporary embargo on four types of grains and oil seeds from Ukraine was lifted in mid-September 2023 (which was in effect since May 2023), Ukraine agreed to introduce export measures to avoid grain surges (European Commission, 2023). Nevertheless, Poland administered a unilateral ban on selected products and their derivatives (gov.pl, 2023b), which led Ukraine to file a complaint with the World Trade Organization (WTO, 2023). While the ban still applies (gov.pl, 2025), the Polish government has on multiple occasions actively sought to convince the EU to include wheat (and other grains) among the crops covered by the quotas under the EU-level 2022 regulation on temporary trade liberalization with Ukraine (the Autonomous Trade Measures Regulation; OKOpress, 2024; European Commission, 2024).

Conclusions

Considering the current approach by the U.S. administration under President Donald Trump, Ukraine’s position in the prospective negotiations will strongly depend on the support it can gather from its European allies. This in turn is likely to reflect the sentiments towards the Ukrainian cause among European voters. In Poland, where critically important presidential elections are scheduled for May 2025, the importance of these sentiments might be particularly salient. On the one hand, the candidates are likely to voice support for Ukraine to secure peace and stability in the region. On the other hand, they may appeal for support among voters who are critical of the generous approach of Polish public institutions towards Ukrainian refugees.

As shown in this policy paper, the critical voices highlighting instances of abuse of privileges granted to refugees are largely unfounded, and much of the critical discourse is linked to – in our view – highly inaccurate numbers of officially registered refugees with the PESEL-UKR status system. The government would do a service to the quality of the debate about Ukrainian refugees in Poland, and at the same time defuse some of the critical claims, by verifying the PESEL-UKR database.

Using administrative data on school enrolment and benefit claims we show that these match almost perfectly, with around 150 000 children aged 7-17 in both registries in late 2024. This is far less than the 270 000 children in this age group registered in the PESEL-UKR database and assumed to be residing in Poland. Similarly, survey data suggests that about 70 percent of Ukrainian refugees are active on the Polish labour market. This proportion is much lower when official data based on social security contributions is compared to the total number of adult refugees in the PESEL-UKR registry. The comparison once again suggests that the figures in the latter database are significantly overstated. It is thus very unlikely that the number of Ukrainian refugees in Poland is as high as the numbers officially reported in the registry (992 000 in January 2025).

The accuracy of the numbers is important for several reasons, and the ability to address various critical claims in the public debate is only one of them. At the time of an electoral campaign ahead of a highly significant presidential election, this reason, however, may prove fundamental to avoid further polarization of the debate about continued support for Ukrainian refugees in Poland. It is also crucial for securing strong support for Ukraine by the Polish government in the coming challenging months of peace negotiations. While it is likely impossible to restore the level of positive attitudes toward Ukrainian citizens seen in Poland in February and March 2022, that degree of solidarity should serve as a foundation for a deepened relationship between the two countries.

Acknowledgement

The authors acknowledge the support from the Swedish International Development Cooperation Agency, Sida. We are grateful to Patryk Markowski for helpful research assistance. The Polish Household Budget Survey data (2022, 2023) used in the analysis was provided by Statistics Poland (Główny Urząd Statystyczny). We are grateful to the Social Insurance Institution ZUS (Zakład Ubezpieczeń Społecznych) for providing us with unpublished data on child benefit recipients.

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Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Active Labor Market Policy in the Baltic-Black Sea Region

Posted on June 3, 2024 | Policy Brief

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.

Introduction

This policy brief builds on a study aimed at conducting a comparative analysis of labor market regulation policies in Belarus, Ukraine, Lithuania, and Poland. In comparing the structure of labor market policy expenditures, the aim was to identify common features between Poland and Lithuania, both of which are part of the EU and employ advanced labor market regulation approaches. We also assessed Ukraine’s policies, currently being reformed to align with EU standards, contrasting them with Belarus, where economic reforms are hindered by the post-Soviet authoritarian regime.

The analysis of the labor market policies for the considered countries is based on an evaluation of the structure of pertinent measures between 2017 and 2020 (Mazol, 2022). We used the 2015 OECD systematization of measures of active labor market policy, as presented in the first column of Table 1.

Our study reveals substantial differences in active labor market policies within the four considered countries. Still, motivated by OECD’s approach to ALMP, we provide a range of common policy recommendations that are relevant for each country included in the study. Arguably, aligning with the OECD approach would have more value for current EU and OECD members, Poland and Lithuania, and the aspiring member, Ukraine. However, these recommendations also hold value when considering a reformation of the Belarusian labor market policy.

ALMP Expenditures in Belarus, Lithuania, Poland and Ukraine

Labor market policy comprises of active and passive components. Active labor market policy involves funding employment services and providing various forms of assistance to both unemployed individuals and employers. Its primary objective is to enhance qualifications and intensify job search efforts to improve the employment prospects of the unemployed (Bredgaard, 2015). Passive labor market policy (PLMP) encompasses measures to support the incomes of involuntarily unemployed individuals, and financing for early retirement.

Poland and Lithuania are both EU and OECD members, so one would expect their labor market policies to be driven by the EU framework, and, thus, mostly aligned. However, our analysis showed that the structure of their expenditures on active labor market policies in 2017-2019 differed (Mazol, 2022). In Lithuania, the majority of the funding was allocated to employment incentives for recruitment, job maintenance, and job sharing. From 2017 to 2019, the share for these measures was between 18 and 28 percent of all expenditures for state labor market regulation. In Poland, the majority of funding was allocated to measures supporting protected employment and rehabilitation. The spending on these measures fluctuated between 23 and 34 percent of all expenditures for state labor market regulation between 2017 and 2019.

The response to the labor market challenges during the Covid-19 pandemic in Poland and Lithuania resulted in a notable surge in state labor market policy spendings in 2020, amounting to 1.78 percent of GDP and 2.83 percent of GDP, respectively. Both countries sharply increased the total spending on employment incentives (see Table 1 which summarizes the expenditure allocation for 2020). Poland experienced a nine-fold increase in costs for financing these measures (29.4 percent of total expenditures on state labor market regulation). Meanwhile, in Lithuania, financing for employment incentives increased more than tenfold, amounting to 42.5 percent of all expenditures for state labor market regulation. In both countries it became the largest active labor market policy spending area.

Table 1. Financing of state labor market measures in Baltic-Black Sea region countries in 2020 (in millions of Euro).

Source: DGESAI, 2023. Author’s estimations based on World Bank data (World Bank, 2023), National Bank of Belarus data, National Bank of Ukraine data.

In Ukraine, the primary focus for active labor market policy expenditures was, from 2017 to 2020, directed towards public employment services, comprising 18 to 24 percent of total labor market policy expenditures. Notably, despite the Covid-19 pandemic, there were no significant changes in either the structure or the volume of active labor market policy expenditures in Ukraine in 2020. Despite Ukraine’s active efforts to align its economic and social policies with EU standards, the government has underinvested in labor market policy, with expenditures accounting for only 0.33-0.37 percent of GDP between 2017 and 2020. This is significantly below the levels observed in Lithuania and Poland.

In Belarus, labor market policy financing is one of the last priorities for the government. In 2020, financing accounted for about 0.02 percent of GDP, amounts clearly insufficient for having a significant impact on the labor market. Moreover, Belarus stood out as the sole country in the reviewed group to have reduced its funding for labor market policies, including both active and income support measures, during the Covid-19 pandemic. The majority of the financing for labor market policy has been directed towards protected and supported employment and rehabilitation, including job creation initiatives for former prisoners, the youth and individuals with disabilities.

ALMP Improvement Recommendations

As illustrated above, the countries under review do not have a common approach to active labor market policy spendings. Further, countries like Poland and Lithuania took a more flexible stance on addressing labor market challenges caused by the Covid-19 pandemic, by implementing additional financial support for active labor market policies. However, Ukraine and Belarus did not adjust their expenditure structures accordingly. Part of these cross-country differences can be attributed to differing legal framework: Poland and Lithuania are OECD and EU member states, and, thus, subject to corresponding regulations. Ukraine is in turn motivated by the prospects of EU accession, while Belarus currently has no such prosperities to take into account.

Another important source of deviation arises from the differences in current labor market and economic conditions in the respective countries, and the governments’ need to accommodate these. While such a market-specific approach is well-justified, aligning expenditure structures with current labor market conditions necessitates obtaining updated and reliable information about the labor market situation and the effectiveness of specific labor market measures or programs. An effective labor market policy thus requires establishing a reliable system for assessing the efficiency of government measures, i.e., deploying evidence-informed policy making (OECD, 2022).

To achieve this, it is crucial to establish a robust system for monitoring and evaluating the implementation of specific measures. This involves leveraging data from various centralized sources, enhancing IT infrastructure to support data management, and utilizing modern methodologies such as counterfactual impact evaluations (OECD, 2022).

Moreover, an effective labor market regulation policy necessitates the ability to swiftly adapt existing active measures and service delivery methods in response to changes in the labor market. This might entail rapid adjustments in the legal framework, underscoring the importance of close cooperation and coordination among key stakeholders, and a well-functioning administrative structure (Lauringson and Lüske, 2021).

To accomplish this objective, it is vital to foster close collaboration between the government and institutions closely intertwined with the labor market, capable of providing essential information to labor market regulators. One of the most useful tools in this regard appears to be so-called social partnerships – a form of a dialogue between employers, employees, trade unions and public authorities, involving active information exchange and interaction (OECD, 2022).

A reliable system to assess labor market policy and in particular to facilitate their targeting, is an essential component of this approach.

Ukraine and Belarus are underfunding their labor market policies, both in comparison to the levels observed in Poland and Lithuania, and in absolute terms. It is therefore advisable to establish quantitative benchmark indicators to act as guidance for these countries, in order to ensure that any labor market policy implemented is adequately funded. Here, a reasonable approach is to align the costs of implementing labor market measures with the average annual levels for OECD countries (which are 0.5 percent of GDP for active measures and 1.63 percent for total labor market policy expenditures (OECD, 2024). Furthermore, it’s essential to ensure a high level of labor force participation in active labor market regulation measures. A target standard could be set, based on the average annual coverage from active labor market measures, at 5.8 percent of the national economy labor force, as observed in OECD countries (OECD, 2024).

Conclusion

The countries under review demonstrate varying structures of active labor market expenditures. Prior to the Covid-19 pandemic, employment incentives received the most financing in Lithuania. In Poland the largest share of expenditures was instead directed to measures to support protected employment and rehabilitation. In Ukraine, the main expenditures were directed towards financing employment services and unemployment benefits while Belarus primarily allocated funds to protected and supported employment and rehabilitation. Notably, Lithuania and Poland responded to the economic challenges following Covid-19 by significantly increasing spending on employment incentives, while Ukraine and Belarus did not undertake such measures.

Part of the diverging patterns may be attributable to the countries varying legal framework and differences in the countries respective labor market and economic conditions.

While some of the differences in labor market policies are thus justified, ensuring funding at the OECD level for labor market measures, alongside adequate tools for monitoring and evaluating labor market policies, are likely to benefit all four Baltic-Black Sea countries.

References

Bredgaard, T. (2015). Evaluating What Works for Whom in Active Labour Market Policies. European Journal of Social Security, 17 (4), 436-452.
DGESAI. (Directorate-General for Employment, Social Affairs and Inclusion). (2023. Expenditure by LMP intervention – country https://webgate.ec.europa.eu/empl/redisstat/databrowser/explore/all/lmp?lang=en&subtheme=lmp_expend.lmp_expend_me&display=card&sort=category&extractionId=LMP_EXPME
Lauringson, A. and Lüske M. (2021). Institutional Set-up of Active Labour Market Policy Provision in OECD and EU Countries: Organisational Set-up, Regulation and Capacity. OECD Social, Employment and Migration Working Papers no. 262.
Mazol, A. (2022). Active Labor Market Policy in the Countries of the Baltic-Black Sea Region. BEROC Policy Paper Series, PP no. 115.
OECD. (2015). OECD Employment database – Labour market policies and institutions https://www.oecd.org/employment/Coverage-and-classification-of-OECD-data-2015.pdf
OECD. (2022). Impact Evaluation of Vocational Training and Employment Subsidies for the Unemployed in Lithuania. Connecting people with jobs. Paris: OECD Publishing.
OECD. (2024). OECDstats: Labor market programs https://stats.oecd.org
World Bank. (2023). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Individual Retirement Timing in Russia: Implications for Pension Age

Posted on January 15, 2018 | Policy Brief

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This policy brief summarizes the findings in a paper where individual exit trajectories of Russians from the labor market to economic inactivity are examined using survival analysis methods based on the Russian Longitudinal Monitoring Survey for 1995-2015. Among other results, the analysis shows that the statutory retirement age has a significant impact on the time of exit from the labor market for both men and women, but the effect is very high for women. This is an interesting and unexpected result, given no penalty for working beyond the pension age of those already retired, the five-year difference in statutory retirement age between males and females, and the low pension age in Russia on an international scale. This questions the painlessness of rising the retirement age for women, should the decision finally be taken.

An ageing population, combined with a slowdown in economic growth, challenges the Russian public finances with an increased deficit of the Pension fund. In addition, the persistently negative natural population growth against the backdrop of ageing has predetermined a decline in the working-age population in the foreseeable future. Older cohorts are therefore becoming a potentially attractive source to increase the size of the labor force. All this has actualized the discussion about the need to increase the Russian retirement age (see, for instance, Maleva and Sinyavskaya, 2010). However, little is known about the labor market situation of older age groups and, in particular, about the process of their exit from the labor market

The Russian pension system, unlike the pension systems of many developed countries, hardly penalizes continuation of work after reaching retirement age and documenting a pension (working pensioners lose only pension indexation). The changes in pension law that have entered into effect since 2015 encourage continued work without recourse to retirement, but there have been few responses to the innovation so far. Coupled with the low pension replacement rate (i.e., the proportion of wages substituted by pension), this makes the process of leaving the labor market nontrivial, since a large number of people of retirement age remain on the labor market after reaching retirement age.

Denisova (2017) examines individual exit trajectories of Russians from the labor market to pension-age economic inactivity applying survival analysis to the Russian Longitudinal Monitoring Survey (RLMS-HSE). The major research questions are the following: What determines the length of stay of older age groups in the Russian labor market? What is the role of the statutory retirement age in this process?

Data and research methodology

The RLMS-HSE for the period of over 20 years, from 1995 to 2015, is the empirical basis of the research (http://www.cpc.unc.edu/rlms). I limit the sample to age 45-72 as there is practically no retirement by age before age 45, and 72 years is the upper boundary of the working age definition internationally accepted by statisticians. I exclude from the sample those who are on retirement and did not work or seek work for the entire period of observation, since their decision to end working activity remained outside the observation period.

An episode in the survival analysis of exit from the labor market into pension-age inactivity is an episode of working life. The analytical time in this case is the age of the respondent. The failure event (the moment of exit from the labor market to pension-age economic inactivity) is defined by the simultaneous fulfillment of three conditions: the respondent does not work, does not look for a job, and receives retirement pension. Only the final exits from the labor market into inactivity are considered, while temporary exits are disregarded.

I evaluate proportional hazard models, which suggest that exogenous economic factors shift the baseline hazard function (which reflects the average entire sample hazard rate at each age) proportionally. A semi-parametric Cox model specification with robust errors clustered at individual level is used.

The vector of explanatory characteristics includes education; marital status; experience in the labor market (work at an enterprise with a state share; entrepreneurship versus work for wages); health characteristics (subjective and objective); settlement type; and attainment of statutory retirement age. In all cases, I control for the year of the survey.

Given the differences in the behavior of men and women in the labor market, the regression analysis is run separately for the subsamples of men and women. The statistical significance of the differences in returns to factors between men and women is tested based on the results of the full sample regression with interaction terms.

Averaged process of exit from the labor market

The averaged process of leaving the labor market pending on age is conveniently described through so-called Kaplan-Mayer’s survival function (an estimate of the survival process). As seen from Figure 1, the process of exit prior to age 55 for women and 60 for men is very slow, while the rate of exit becomes almost permanent and slows down after 70 years. Men stay in the labor market longer: 25% of women leave the labor market at the age of 58 years, whereas for men this age is 60. The threshold of 75% of the sample that left the labor market is reached in the sample of women by the age of 70, and 71 for men.

Determinants of exit

The analysis of older cohorts’ exit from the labor market via survival methods confirms important determinants of the process, previously identified in literature. The impacts of health and of financial incentives are in this group of results.

Figure 1. Survival functions, men and women

Source: Author’s calculations based on RLMS-HSE 1995-2015 data

Health status is the key factor for men’s exit into inactivity: the exit to inactivity is accelerated by 71 percentage points for males with bad health, whereas for women this factor is statistically irrelevant.

A higher per capita household income is correlated with later exit from the labor market. A higher income from the main place of employment has no statistically significant effect when we control for household income and is at an extended boundary (15%) of statistical significance if we do not. Both variables indirectly reflect the pension replacement rate, and I interpret the results as an indirect confirmation that workers at the top part of the income distribution, being inadequately insured by the pension system, remain on the labor market longer.

The identified peculiarities of the exit to pension-age inactivity of the Russian elderly are of major interest. Unlike many developed countries, only highly skilled persons remain in the labor market longer than others, while the behavior of middle-skilled groups, and skilled and unskilled workers does not statistically differ between them.

Employment at state-owned enterprises slows down women’s exit to inactivity but is not significant for men. Self-employment and entrepreneurship prolong the presence in the labor force, by 41 percentage points for women.

The regression analysis demonstrates that the statutory retirement age has a significant impact on the time of exit from the labor market for both men and women, and the effect is significantly higher for women: the hazard rate of inactivity rises by 63 percentage points when a woman reaches 55 years, and by 25% when a man reaches 60. For men, an effect comparable in size is the self-assessment of health as poor.

Discussion

The results, on the one hand, confirm those for developed countries: health status is the key factor for men’s exit into inactivity, and financial motives have a significant impact. At the same time, the peculiarities of the Russian labor market are reflected in a differing labor market exit process of various professional groups, in the sense that self-employment and entrepreneurship and work at state enterprises postpone exit into inactivity. The high sensitivity of women to the statutory retirement age, which by 2.5 times exceeds the sensitivity of men, is one of the new and unexpected results, taking into account that the statutory retirement age for women in Russia is very low by international standards. This questions the painlessness of rising the retirement age for women, should the decision finally be taken. Indeed, given the very low pension age for females, an (gradual) increase in the retirement age for women would seem not to raise strong objections. However, our result testifies that the normative border of the retirement age has a decisive influence on women’s choice of time of exit from the labor market, even under control (as far as data permits) on differences in education, situation in the labor market and family circumstances. In this situation, the process of rising the retirement age, if such a decision is taken, can be rather painfully accepted by those who so strongly focus on its current meaning in their life plans.

References

Denisova, Irina, 2017, “Exit of senior age cohorts from the labor market: survival analysis approach” – forthcoming in Population and Economics.
Maleva T.M., Sinyavskaya O.V., 2010 “Raising the retirement age: pro et contra, Journal of the New Economic Association, No. 8, pp. 117-139.

What Expansion of Mandatory Schooling Can and Cannot Do in Conservative Muslim Societies

Posted on April 7, 2014 | Policy Brief

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New research shows expanding mandatory schooling in conservative Muslim societies have broad positive effects on female empowerment but is not enough to overcome the significant barriers to female entry in the labor force.

Does expansion of public education empower women? A large literature documents the positive effects of education on women’s economic and social outcomes in developed countries, but we know less about its causal effects on women’s empowerment in Muslim societies where women’s participation in the labor market is limited and they often do not have control over their earnings or their own bodies (Doepke et al 2012). In fact, even though female education has been successfully expanding in many majority-Muslim countries, the number of legal rights enjoyed by women is few relative to men, and female labor-force participation remains low (UNDP 2005). The lack of a corresponding labor-force participation effect raises concerns over the efficacy of expanding education as a means of improving women’s rights in Muslim societies. On the other hand, education has been shown to have many important non-pecuniary effects outside the labor market, such as in health, marriage, and parenting style (Oreopolous and Salvanes 2011) and to the extent that these effects help empower women, they may constitute alternative mechanisms through which education may lead to women’s empowerment (even in the absence of large labor market returns). However, most of this research comes from countries and societies that are not majority-Muslim and where women do work to a larger degree. As such, disentangling non-pecuniary returns to education from its labor market (and thus pecuniary) returns is particularly challenging in most settings and whether education may empower women in the Muslim world remains an open question.

Even though scholars debate the fundamental causes for the severe degrees of gender inequality in Muslim societies, most posit a nexus of patriarchal culture, strong religious values, and restricting social norms as proximate explanatory factors. Historically, Lewis (1961) claims women’s status was “probably the most profound single difference” between Muslim and Christian civilizations. In more contemporary cross-country studies, Fish (2002) documents a negative cross-country correlation between having an “Islamic religious tradition” and female empowerment, while Barro and McCleary (2006) also show that Muslim countries tend to exhibit higher degrees of religious participation and beliefs. Comparing the effects of a business training program on female entrepreneurship among Hindu and Muslim women in India, Field et al (2010) find evidence in line with significantly stricter constraints to female labor-force participation among Muslim women. To the extent that barriers to entry due to religious values restrain women’s rights, an integral outcome of empowerment is therefore a woman’s ability to independently assert her own beliefs.

In a recent paper, Selim Gulesci and I exploit an extension of compulsory schooling in Turkey to estimate the causal effect of schooling on female empowerment (Gulesci and Meyersson 2014). Compulsory schooling laws have been extensively used to estimate returns to education in Western countries on labor market outcomes (Angrist and Krueger, 1991, Oreopoulos 2006), health and fertility (McCrary and Royer 2011, Lleras-Muney 2005, Black et al 2008) among others. We follow a similar strategy to provide meaningful causal parameters for the effect of a year of schooling on outcomes related to social status of women in Turkey, a majority-Muslim country.

In 1997, Turkey’s parliament passed a new law to increase compulsory schooling from 5 to 8 years. By this law, individuals born on or after September 1986 were bound to complete 8 years of schooling, whereas those born earlier could drop out after 5 years. Using the sample of ever-married women from the 2008 Turkish Demographic Health Survey (TDHS) we are able to observe outcomes 10 years after the law change was implemented.

We adopt a regression discontinuity (RD) design assigning treatment based on whether an individual’s month-and-year of birth was before or after the September 1986 threshold. As such, our identification strategy entails comparing cohorts born one month apart and relies on the assumption that these two groups should exhibit no systematic differences other than being subject to different compulsory schooling laws. We can thus calculate an RD treatment effect, illustrative of the causal effect of education for individuals born around the threshold.

Analysis of the sample of ever-married women focuses the RD treatment effects on a subset of the population that tends to be demonstratively poorer and more socially conservative, i.e. the very subpopulation that the reform was aimed at. In a comparison of ever- and never-married women, the reform only affected education among the former, and as a result, the exclusion of non-married women effectively means exclusion of non-compliers with the reform. This is a likely consequence of ex post single women being more likely to have attended school longer regardless of expanding reforms. We also show that the probability of selection into the married sample is not affected by the law.

Our results are as follow. First, we show the effect of the reform on women’s years of schooling. As a result of the reform, women’s average years of schooling increased by one year, and completion rates for junior-high (secondary) and high school completion increased by 24 and 8 percentage points (ppt) respectively. There is no significant impact of the reform on men’s schooling on average (mainly because the average man’s schooling in Turkey around the age threshold was already at a relatively high level). Thus, the reform effectively served to reduce the education gender gap by half.

Second, our RD estimates reveal that this additional year of schooling had significant secularizing effects. Ten years after the reform was implemented, and relative to sample means, women were 10 percent (8 ppt) less likely to wear a headscarf, 22 percent (10 ppt) less likely to have attended a Qur’anic study center and 18 percent (7 ppt) less likely to pray regularly.

Third, we find no evidence of schooling on the timing of either marriage or birth, nor on the number of children. We do however find significant effects on women’s decision rights with regards to both marriage and fertility decisions; a reform-induced year of schooling results in a 10 ppt (20 percent relative to the sample mean) increase in the likelihood of having a say in the marriage decision, and a 10 ppt (12 percent) increase in the likelihood of having a say in the type of contraceptive method adopted. We further find a reducing effect of schooling on the likelihood that a bride price was received by the women’s parents from their husband’s family upon their wedding.

Fourth, we document less pronounced and largely imprecise impacts on women’s labor market outcomes. Although our estimates indicate positive effects on non-agricultural employment in general, and self-employment in particular, these estimates are sensitive to the specification used. At the same time, we show significant positive effects of schooling on household wealth, largely driven by appliances related to women’s role as housewives. We are unable to explain this by observable increases in spousal quality, measured as husband’s years of schooling.

Altogether, our results indicate significant empowering effects of education, but whereas we document precise effects on decision rights, household wealth, and measures of social and religious conservatism, we fail to find equally concise effects on spousal and labor force outcomes. This prevents an interpretation relying exclusively on either labor market or assortative matching in the marriage market as the main channel of empowerment. In fact, an examination of heterogeneous effects reveal diverging effects depending on how socially conservative women’s backgrounds are; in rural areas, education pre-dominantly allows increased freedom to be more secular, greater decision rights over marriage, and less traditional marriages. In urban areas, education has similar effects, but also leads to increased labor force participation. We interpret this as increased education, and its associated bargaining power in the household, leading to different allocations depending on the preexisting level of women’s rights. Education may thus have only a partial effect on employment, as religious or cultural barriers to entry prevent women from realizing larger gains of education through the labor market.

Our paper adds to the research literature by providing meaningful causal parameters for the effect of a year of schooling on both social and religious outcomes for women in a majority-Muslim country. The findings point to a set of returns to schooling that take into context the socially conservative nature of the Turkish society where policies to increase schooling ultimately seem to improve women’s status (as captured by higher decision-making power and household wealth) but are unable to meaningfully break down the barriers that women face in entering the labor market, particularly in more conservative rural communities. While still having important empowerment consequences for women’s empowerment in Muslim societies, education may not be a magic bullet toward full emancipation. Policies hoping to achieve female empowerment will thus require complementary reforms in health and the labor market to address barriers to entry more directly.

References

Denisova, I., and S.Commander, S.Commander and I. Denisova (2012), ‘Are skills a constraint on firms? New evidence from Russia’, EBRD and CEFIR/NES, mimeo
Hausmann, R., and Klinger, B., (2007), “The Structure of the Product Space and the Evolution of Comparative Advantage”, CID Working Paper No. 146
Volchkova, N., Output and Export Diversification: evidence from Russia, CEFIR Working Paper, 2011
Angrist, Joshua D. and Alan. B. Krueger, 1991, “Does Compulsory Schooling Attendance Affect Schooling and Earnings?” Quarterly Journal of Economics, 106(1): 979-1014.
Barro, Robert and Rachel McCleary, 2006, “Religion and Economy”, Journal of Economic Per- spectives, 20(2): 49-74.
Black, Sandra, Paul Devereux, and Kjell G. Salvanes, 2008, “Staying in the Classroom and out of the Maternity Ward? The Effect of Compulsory Schooling Laws on Teenage Births”. Economic Journal, 118(530): 1025-54.
Doepke, Matthias, and Michelle Tertilt, 2009, “Women’s Liberation: What’s in it for Men?”, Quarterly Journal of Economics, 124: 1541-91.
Field, Erika, Seema Jayachandran and Rohini Pande, 2010, “Do Traditional Institutions Constrain Female Entrepreneurial Investment? A Field Experiment on Business Training in India”, American Economic Review Papers and Proceedings, 100: 125-29.
Gulesci, Selim, and Erik Meyersson, 2014, “For the Love of the Republic – Education, Secularism, and Empowerment”, working paper.
Lewis, Bernard, 1961, “The Emergence of Modern Turkey”, Oxford University Press: London.
McCrary, Justin, 2008, “Manipulation of the Running Variable in the Regression Discontinuity
Design: A Density Test,” Journal of Econometrics, 142(2): 698-714.
Lleras-Muney, Adriana, 2005, “The Relationship between Education and Adult Mortality in the United States,” Review of Economic Studies, 21(1): 189-221.
Oreopolous, Phillip, 2006, “Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter ”, American Economic Review, 96(1): 152-175.
Oreopolous, Philip and K. G. Salvanes, 2011, “Priceless: The Nonpecuniary Benefits of Schooling”, Journal of Economic Perspectives, 25(1): 159-184.
UNDP, 2005, “Arab Human Development Report 2005 – Towards the Rise of Women in the Arab World”.

For Some Mothers More Than Others: How Children Matter for Labor Market Outcomes When Both Fertility and Female Employment Are Low

Posted on November 26, 2012 | Policy Brief

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Authors: Krzysztof Karbownik and Michal Myck, CenEA.

Wide spread entry of women into the labor force has been one of the most pronounced socio-economic developments in the 20th century, and high levels of female employment are crucial from the point of view of continued economic growth and financial stability of many welfare systems (Galor and Weil, 1996). At the same time, demographic changes determined by the current and future fertility levels will play a vital role in shaping these developments and will affect the costs of social programs. Given the potentially strong link between female employment and family size, it seems that understanding the relationship between the two ought to be at the heart of policy discussions, especially in countries that are characterized by both low fertility and low female employment. In particular, in light of rising unemployment in low-fertility countries, which have been most severely affected by the economic crisis such as Greece, Spain and Latvia, our findings may serve as a guide with respect to the relationship between fertility and labor supply in an environment, which will be more common in Europe in the near future.