Project: FREE policy brief

Post-2020 Belarusian Permanent Migration to the EU and Beyond: An Empirical Assessment

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Following the 2020 presidential election, Belarus experienced a sharp increase in outward migration, primarily to the European Union, with Poland and Lithuania becoming the main destination countries. However, the official migration statistics suffer from limitations and inconsistencies. The brief provides an empirical assessment of the scale of Belarusian migration after 2020. The results indicate that 400–418 thousand Belarusians live and/or work in the EU, Russia, and Georgia. The migration significantly affects host countries’ labour markets and social systems, particularly in Poland. In turn, for Belarus, it represents substantial forgone economic potential, with estimated output losses exceeding 3.4% of GDP.

Introduction

After the 2020 presidential election in Belarus, outward migration increased significantly. Belarusian citizens left the country for both political and economic reasons, with the European Union, particularly Poland and Lithuania, becoming one of the main destinations. Belarusian migrants have become a significant source of labour supply in Poland and Lithuania, helping alleviate labour shortages in economies experiencing demographic decline. At the same time, a sizable outward migration is likely to affect both Belarus’ demographic dynamics and the economic outcomes. In this sense, estimating the number of Belarusians residing abroad is important for both host countries and Belarus itself. However, precise data on the number of Belarusians moving abroad after 2020 remains limited.

Existing international estimates provide only a partial picture. The World Migration Report includes both recent migrants and migrants who left Belarus decades ago and later acquired citizenship in other countries (WMR, 2024). It also relies on migration statistics that are not fully comparable across countries and are often available only with a time lag. As a result, these estimates do not capture the most recent migration wave that occurred after 2020.

Belarusian national statistics also underestimate migration flows, as they mainly record individuals who officially leave the country to work abroad under formal employment contracts (MIARB, 2025) .

This policy brief aims to address this gap by providing estimates of migration from Belarus between 2020 and 2024, based on data on residence permits issued in recipient countries, national migration statistics, information on citizenship acquisition, and open-source data. It accesses the number of Belarusian migrants in the main emigration destinations, namely the European Union, Russia, and Georgia, and discusses the implications for the host countries and Belarus.

Assessing Belarusian Migration to the EU

One of the most commonly used sources for analysing migration flows to the European Union is Eurostat data on the number of first permits. These permits indicate that a foreign national has received authorisation for a long-term stay in an EU country for the first time, typically for more than three months. They include various categories such as work permits, study permits, and other forms, including long-term visas. In many cases, the number of first permits corresponds broadly to the number of migrants entering and residing in a country. However, in some countries, there are significant differences between the number of first permits issued and the actual number of migrants. For example, this concerns Poland’s issuance of Poland Business Harbor Visas to Belarusians. The visa allowed Belarusians to live and work in Poland. However, not all visa recipients moved to the country. Many used it for short-term tourism and did not subsequently obtain temporary residence permits.

According to European statistics, more than 90 percent of first permits issued to Belarusian citizens in recent years were granted by Poland and Lithuania. For this reason, estimating the number of Belarusians residing in these two countries is central to assessing the scale of Belarusian migration to the EU.

Lithuania

Assessing the number of Belarusians residing in Lithuania is relevant in light of the ongoing demographic decline and its implications for labour supply. Fertility in Lithuania remains well below replacement level—around 1.1 children per woman in 2024—while population ageing continues to reduce the size of the workforce (Statistics Lithuania; IMF, 2024). The current labour market situation is relatively tight, with unemployment around 7% in 2024. Migration helps mitigate some labour market pressures without constituting a major source of labour supply (European Commission, 2025).

In this context, Belarusians have become the second-largest migrant group in Lithuania. Their numbers increased markedly after 2020, rising from fewer than 18 thousand at the end of 2019 (Migracijos metraštis, 2020) to 57.5 thousand by the end of 2024 (Imigrantai Lietuvoje, 2026).

Estimating the number of Belarusian residents in Lithuania is relatively straightforward because the Migration Department of the Ministry of Interior Affairs publishes detailed statistics on foreigners residing in the country. These data show a close relationship between the number of first permits issued and the growth in the Belarusian population in Lithuania. Between 2020 and 2023, the number of Belarusians living in Lithuania increased slightly less than the number of first permits issued, partly because some individuals work in Lithuania on a rotational basis while continuing to reside in Belarus. An exception occurred in 2022, when the Belarusian population in Lithuania increased more rapidly than the number of first permits issued to Belarusians following Russia’s invasion of Ukraine and the expansion of humanitarian migration channels. Since 2024, the number of Belarusians residing in Lithuania has declined, partly due to the tightening of migration policy (EMT, 2025).

Poland

Compared with Lithuania, Poland has stronger labour demand and even tighter labour market conditions, with significant dependence on migration. Despite a similarly low fertility rate (1.099 in 2024), unemployment remains low at 5.6% (November 2025), even with over one million foreign workers already present (Statistics Poland, 2025, 2026). Combined with population ageing and mounting pressures on social security and healthcare systems, this results in a structurally higher demand for migrant labour than in Lithuania. Against this backdrop, Belarusians—now the second-largest group of foreign workers after Ukrainians—play an important role. Only among social security contributors, their number has more than tripled in recent years – from 42.8 thousand in 2020 to 134.8 thousand in 2024 (ZUS).

However, accurately assessing the scale of Belarusian migration is challenging. Official statistics do not provide a direct measure of Belarusian residents. First residence permits significantly overestimate migration: between 2020 and 2024, Poland issued more than 874 thousand permits to Belarusian citizens, but many were used for short-term mobility rather than permanent relocation. Figure 1 illustrates the gap between the number of first permits issued and the number of residence permits held. At the same time, residence permit data underestimate the true population. Approximately 125 thousand Belarusians held valid residence permits at the end of 2024, increasing to 141.2 thousand at the beginning of 2026; however, these figures exclude individuals awaiting decisions, whose applications may take months or years to process while they remain in the country (USC, 2026).

Importantly, statistics based on social security contributions also underestimate the total number of Belarusians permanently residing in Poland, as they exclude non-working spouses, children, students, pensioners, and other inactive groups. At the same time, combining different administrative datasets would lead to double-counting, as the same individuals may appear in multiple categories—for example, as residence permit holders, applicants awaiting decisions, and recipients of social benefits—meaning that simple aggregation would inflate the total. As a result, neither the number of permits issued nor administrative records alone provide an accurate estimate of the Belarusian population in Poland.

Approaches to Determining the Number of Belarusians in Poland

Luzgina (2025a) suggests two approaches to estimate the number of Belarusians residing in Poland.

The first approach—the gender-statistical approach—is based on estimating the number of Belarusians permanently residing in Poland by taking into account the gender structure of Belarusian citizens holding documents for permanent stay in Poland, as well as estimating the number of young Belarusians under 18, using statistical data on recipients of the 800+ child benefit, which until 2026 was paid to all children under 18. The estimate based on this approach suggests that as of the end of 2024, between 172.8 and 181.1 thousand Belarusians permanently resided in Poland.

Figure 1. Dynamics of issuing first permits and residence permits by Poland to Belarusian citizens: thousands of people.

Source: Urząd do spraw cudzoziemców; Eurostat. Note: First permits are permits issued for initial entry, including long-term visas. Resident permits include temporary residence permits, permanent residence permits, blue cards, and residence cards—that is, permits foreigners obtain for residence in the country after they’ve already entered. Due to the fact that many Belarusians received Poland Business Harbor visas (first permits), but did not use them to obtain a residence permit in Poland, the number of residence permits issued is lower than the number of first permits.

The second approach—the socio-demographic approach—is used to verify the accuracy of these estimates. This approach is based on the analysis of statistics on social security contributions, the age structure of Belarusians in Poland, and their employment status. Key components include data on the number of taxpayers, children under 18, and Belarusians aged 18 and older who are not employed in the Polish labour market. According to this second approach, the number of Belarusians residing in Poland at the end of 2024 ranged from 175.6 to 188.5 thousand individuals.

Thus, based on both approaches, between 172.8 and 188.5 thousand Belarusian citizens entitled to permanent stay were permanently residing in Poland at the end of 2024.

The Total Number of Belarusians in the EU

Based on the above assessment of the total number of Belarusians residing in Poland, the known number residing in Lithuania, and the number who obtained first permits in other countries, it is possible to estimate the number of Belarusian citizens residing in the European Union. If EU statistics are considered, it can be noted that over the period 2016–2024, the share of first residence permits issued by EU countries excluding Lithuania and Poland averaged 7%. We can assume that the number of Belarusians residing in EU countries outside Poland and Lithuania approximately corresponds to this proportion.

In this regard, the total number of Belarusians residing in the EU at the end of 2024 was calculated assuming that approximately 93% of Belarusian citizens migrated to Lithuania and Poland. This results in an estimate of 247.6 thousand to 264.5 thousand individuals.

Based on available data on Polish citizenship obtained by Belarusians in 2020–2024, the total number of Belarusian citizens who do not yet hold citizenship or who obtained it relatively recently but permanently reside in the EU is between 265 thousand and 282 thousand individuals. Moreover, the majority of these individuals relocated to the EU in 2020–2024, a period marked by a significant increase in the number of first residence permits issued to Belarusians, primarily by Poland and Lithuania.

Migration Outside of the EU

Belarusians actively migrate not only to EU countries but also to other states such as Russia and Georgia. It is not possible to calculate how many Belarusian citizens currently live and work in Russia due to the absence of customs and border barriers and the lack of additional labour market legalisation requirements for citizens of the Union State. Nevertheless, there are general figures on the employment of Belarusians in the Russian labour market. As of 2023, approximately 124 thousand Belarusians were employed in Russia. An additional more than 12,000 resided in Georgia (Luzgina, 2025b). Taking these data into account, together with data for EU countries, between 400 and 418 thousand Belarusian citizens lived and worked outside Belarus. This amounts to approximately 4.5% of the country’s total population.

Implications of Belarusian Migration for Belarus

Together with data for EU countries, between 400 and 418 thousand Belarusian citizens lived and worked outside Belarus. This amounts to approximately 4.5% of the country’s total population. Estimating the share of Belarusians of working age (16–60 years) living and working in the countries under study based on the gender-age structure of Belarusians in Poland yields approximately 355 thousand individuals. This corresponds to more than 6% of the country’s total working-age population.

The forgone economic opportunities resulting from the emigration of working-age individuals can be assessed using the Solow growth accounting framework. The potential economic impact of the emigration of working-age Belarusians can be approximated as a static output loss, assuming that capital and total factor productivity remain unchanged. Based on the share of labour compensation in GDP at current national prices for Belarus in 2023 (0.57), and the estimated 6% reduction in the working-age population residing abroad, the immediate reduction in GDP may reach up to 3.42% (PWT 11.0).

Conclusion

Belarusians constitute the second-largest group of foreign nationals in Poland and Lithuania after Ukrainians. Belarusians also make a positive contribution to the labour markets of other EU countries, as well as to those of Russia and Georgia. Consequently, their residence in the host countries has a tangible impact not only on the labour market but also on social security systems, budget, and other sectors of the economy. Accurate data on the number of migrants, their age structure, and their participation in economic activity enable more effective forecasting of pressures on social systems and facilitate better planning of migrant integration into the host country’s economy.

In Belarus itself, the long-term emigration of working-age citizens and their families remains insufficiently accounted for, which distorts assessments of the country’s internal demographic situation and associated economic losses. Large-scale migration, including flows to Russia and Georgia, indicates that up to 6% of the working-age population currently resides outside the country, which, all else being equal, may reduce potential GDP growth by more than 3.42%.

References

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.

Critical Minerals and the New Geopolitics of the Green Transition: Insights from Energy Talk 2026

The green transition promises to reduce Europe’s dangerous dependence on fossil fuels often produced in autocratic states, but it may also create new strategic dependencies. Technologies central to decarbonization — such as batteries, wind turbines, electric vehicles, and solar panels — rely on critical minerals whose mining and processing remain highly concentrated.

At the 2026 Energy Talk, “Critical Minerals and the New Geopolitics of the Green Transition”, organised by the Stockholm Institute of Transition Economics (SITE) in collaboration with the FREE Network, leading researchers and industry representatives examined these tensions from three perspectives: the geopolitical significance of Ukraine’s mineral endowment; the regulatory and distributional challenges of Sweden’s mining sector; and the sustainability and competitiveness pressures facing European firms in critical mineral supply chains. This policy brief summarises the main takeaways from the event.

Background

A central promise of the green transition is to reduce Europe’s exposure to geopolitical risk. For decades, dependence on fossil fuels — concentrated in a handful of autocratic or semi-autocratic states — had made European democracies structurally vulnerable to political coercion. Russia’s full-scale invasion of Ukraine in 2022 brought that vulnerability into sharp relief, accelerating a shift toward renewable energy that climate advocacy alone had struggled to achieve. For the first time, the moral case for decarbonisation and the strategic case for energy security pointed in the same direction.

Yet as the transition accelerates, a new question has moved to the centre of European policy debate: are we escaping one dependency only to construct another? The technologies at the heart of decarbonisation — batteries, wind turbines, electric vehicles, solar panels — depend on critical minerals whose deposits are geographically concentrated and whose processing is dominated, to a degree that should give pause, by a single external power. The logic is uncomfortably familiar. The material has changed; the structural problem has not.

At the same time, many of the raw materials needed for the green transition are known to exist in Europe. What is lacking is not geological potential but a clear idea of how to navigate trade-offs between economic and possibly environmental costs in developing capacity in Europe, and potential future strategic vulnerabilities.

This policy brief grows out of the 2026 Energy Talk, Critical Minerals and the New Geopolitics of the Green Transition, organised by the Stockholm Institute of Transition Economics (SITE) in collaboration with the FREE Network. The event brought together leading researchers and industry representatives to examine these tensions from three angles: the geopolitical stakes surrounding Ukraine’s significant but embattled mineral endowment; the regulatory and distributional obstacles that prevent Sweden — despite its considerable deposits — from translating geological wealth into production; and the sustainability and competitiveness pressures bearing down on European firms operating in critical mineral supply chains.

From Fossil Fuel Dependency to Mineral Dependency: The Geopolitical Stakes

Jesper Roine, Adjunct Professor at Stockholm School of Economics and Deputy Director of SITE, opened by framing critical minerals as a central geopolitical challenge of the green transition. As Roine noted, Russia’s full-scale invasion of Ukraine in 2022 succeeded in making resource dependency an urgent political issue in a way that years of climate advocacy had not. The transition to renewables offers structural relief: unlike fossil fuels, often concentrated in autocratic states, wind and sunlight are globally distributed. Yet the minerals required to build renewable infrastructure are themselves geographically concentrated, and their processing is, to an alarming degree, dominated by a single power. Europe risks replacing one form of dependency with another unless it navigates this landscape carefully.

Jiayi Zhou, Senior Researcher at the Stockholm International Peace Research Institute (SIPRI), provided a broader geopolitical perspective, drawing on two recent SIPRI reports. She argued that critical minerals have undergone a threefold transformation: politicisation, securitisation, and militarisation. What began as industrial policy to reduce dependence on Chinese processing has increasingly shifted toward zero-sum security arguments and, more recently, into direct links with conflict dynamics — in Ukraine, the DRC, and in Trump-era manoeuvres around Greenland and Venezuela. This fragmentation risks slowing the green transition globally and squeezing resource-rich developing countries caught between great powers. One discussed example was the US reportedly considering withholding HIV aid to Zambia unless it expanded access to minerals for American investors — a dynamic Zhou called a race to the bottom.

Ukraine’s Mineral Potential and the Imperative of Industrial Integration

Zhou went on to argue that Ukraine sits at the intersection of these pressures. Russian-occupied territories are estimated to contain 40 to 50 per cent of the assessed value of Ukraine’s critical mineral deposits. Russia’s 2024 Minerals Development Plan explicitly targets integrating those resources into the Russian economy, while the US-Ukraine Reconstruction Investment Fund extends preferential access to American investors amid simultaneous US outreach to Russia on business opportunities. Zhou concluded that the EU is the least equipped among the great powers to compete in a world of militarised resource mercantilism, though it retains normative and standards-based appeal. Ukraine risks becoming a casualty of great-power competition rather than a beneficiary.

Olha Evstigneeva, PhD researcher in climate economics at the Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine, Development Director at the Ukrainian Association of Renewable Energy, and Decarbonisation Expert, spoke from Kyiv. She described Ukraine as undergoing an accelerated and involuntary transition that other countries have yet to fully engage with. The EU’s Carbon Border Adjustment Mechanism already affects roughly 20 per cent of Ukraine’s exports, with around 70 per cent now directed to the EU. “This is no longer about going green,” she noted, but about “controlling value chains, markets, and industrial competitiveness.” Despite losing 30 to 40 gigawatts of generation capacity as a result of the war, Ukraine has continued to advance its climate and EU integration agenda. This includes 61 per cent implementation of EU renewable energy legislation, roughly 85 per cent alignment with its 2030 targets, and the fastest deployment of energy storage in Europe.

On minerals, Evstigneeva urged realism. Ukraine holds significant reserves of lithium, graphite, titanium, manganese, and iron ore, but much of the underlying geological data dates from the 1980s and 1990s and falls short of current investment standards. Confirming a single deposit requires USD 100-300 million and 10-12 years, an especially difficult task under wartime conditions. Ukraine’s lithium is hard-rock spodumene, which requires more energy-intensive processing at a time when the electricity system is severely damaged. The strategic question, she argued, is not whether Ukraine has resources, but whether it will remain a raw material supplier or become part of Europe’s industrial base. She proposed a phased model: extraction and primary processing first, refining and components next, and full battery value-chain integration over time. She also noted that Ukraine’s rapidly expanding drone industry and broader military technology sector are creating domestic demand for many of these same materials. In this sense, critical minerals are no longer just about energy transition but also about technological sovereignty.

Sweden: The Gap Between Mineral Potential and Mining Reality

Sweden holds some of Europe’s most significant mineral deposits, including rare earth elements, iron ore, copper, nickel, and lithium. Alongside Finland, Norway, and Greenland, it has the potential to supply a substantial share of the critical raw materials Europe requires. Yet turning that geological potential into production has proved persistently difficult. The presentations by Maria Sunér, CEO of Svemin, the Swedish Association of Mines, Mineral and Metal Producers, and Daniel Spiro, Professor of Economics at Uppsala University, pointed to a common diagnosis: Sweden has the geology, the institutions, and the technological capactity, but lacks a regulatory and distributional framework that allows mining to work for investors, local communities, and the state alike.

Sunér set Sweden’s mining sector within a broader European context. Europe produces only around 3 per cent of the raw materials it consumes, while accounting for 25 per cent of global production. Sweden alone accounts for 90 per cent of the EU’s iron ore production, yet Europe still imports 70 per cent of its iron ore needs. China, meanwhile, dominates key processing stages, including over 60 per cent of cobalt processing and more than 90 per cent of rare earth refining. The EU’s Critical Raw Materials Act set targets of 10 per cent domestic extraction and 40 per cent domestic processing, but Sunér argued that these are unlikely to be reached under current conditions. Sweden has just 13 active metal mines, and the most recent opened only two years ago, the first in more than a decade. Environmental permitting alone can take seven years, and a full mining project typically takes 15 to 35 years from exploration to production. Four fully permitted mines are currently still seeking final financing. According to Sunér, the main obstacles are the regulatory framework and limited access to capital, particularly for early-stage projects, an area in which Sweden lacks the financing culture found in countries such as Canada or Australia.

Spiro approached the issue from an economic perspective and identified two structural barriers. First, local communities and landowners have little incentive to support extraction. Under Sweden’s current system, landowners receive only 0.15 per cent of the value of minerals extracted from their land, while bearing the environmental costs of hosting a mine. Their main source of leverage, therefore, lies in delaying projects through the regulatory process rather than in negotiated compensation. Second, private investment is discouraged by a hold-up problem: exploration involves high upfront costs and uncertain returns, while a highly profitable discovery may trigger political pressure to revise the tax or royalty regime after the fact. Such uncertainty weakens incentives for long-term investment. The result is a paradox: Sweden has favourable geology, political stability, high human capital, and one of the world’s more generous investor profit-sharing systems, yet private investment remains limited, and firms still argue that conditions are not attractive enough.

To break this deadlock, Spiro outlined three regulatory alternatives. The first is state-led exploration and extraction, with revenues redistributed to local communities. This could help address both the hold-up problem and local opposition, though potentially at the cost of efficiency. The second would require local communities and landowners to conduct exploration themselves, giving them ownership of any discoveries and thereby aligning their interests with project outcomes. The third — Spiro’s preferred approach — adapts elements of the Norwegian model: exploration and investment would be susbsidised by a set percentage, matched by an equivalent excess-profit tax to preserve investment neutrality; a nationally owned company would participare as co-investor to increase transparency and reduce the risk of retroactive rule changes; revenues would be shared with host communities; and projects would be required to carry comprehensive environmental insurance covering long-term liabilities after mine closure.

In the discussion, Sunér challenged some of Spiro’s premises. She noted that Sweden’s environmental code is already among the strictest in the world, and cited polling suggesting that around half of Swedes would accept living near a mine. She also emphasised that 90 to 97 per cent of mine employees at most Swedish sites are local residents. Still, both speakers agreed that the core question remains unresolved: how to ensure that host communities genuinely benefit from large extractive investments. In this respect, mining reflects a broader challenge that Sweden shares with other sectors affected by large-scale industrial projects.

European Firms: Navigating Competitiveness, Sustainability and Geopolitics

Aaron Maltais, Senior Research Fellow at the Stockholm Environment Institute (SEI), presented findings from a 2026 paper in Business Strategy and the Environment, based on interviews with companies downstream in critical mineral supply chains, including utilities, wind and solar firms, battery manufacturers, EV producers, and defence companies. He began with a striking illustration of the material intensity of modern technologies: a single 171-gram smartphone requires around 125 kilograms of mined rock. Scaled to the batteries and clean technologies needed for the green transition, the resulting material demands are staggering.

The firms interviewed were broadly committed to sustainable supply chain management and often saw synergies between sustainability and competitiveness. As one battery-sector respondent put it: “You can’t sell on one end a product for the energy transition and pollute endlessly on the other.” Companies identified human rights, conflict minerals, forced labour, and carbon emissions as key priorities, although the discussion also revealed a tendency to focus more heavily on carbon, partly due to data availability. Corporate practice has also evolved, from reactive controversy management to more systematic risk prioritisation, and from auditing first-tier suppliers to engaging more directly with upstream mining companies. Recycling of critical raw materials was widely viewed as important, but current capacity remains far below what is needed. Europe has roughly one-tenth of the recycling capacity required to meet its 2031 targets, and many planned projects face financing and technical barriers.

EU legislation was broadly welcomed for harmonising standards and reinforcing the credibility of sustainability requirements. At the same time, companies pointed to an overlapping and sometimes contradictory regulatory landscape. For example, pressure to meet EU fleet-emissions targets could lead automakers to relax supply chain sustainability standards to source enough vehicles quickly. Geopolitical dependency was another major concern, particularly where firms saw little real alternative to Chinese suppliers. Firms are responding through vertical integration and longer-term purchase agreements, but these measures do not eliminate underlying structural dependencies. Maltais concluded that the EU needs greater policy coherence across industrial strategy, due diligence legislation, and sustainability objectives, alongside stronger international standards and more credible multi-stakeholder initiatives with genuine civil society participation.

Concluding Remarks

The picture that emerges from the day’s discussions could easily be read as cause for alarm — yet the event pointed toward pragmatism rather than pessimism. The trajectory of Europe’s green transition, while broadly positive, is neither assured nor without risk. Resource endowments are the easier part. Governance, institutions, investment frameworks, distributional fairness, and political will are what determine whether mineral wealth becomes a foundation for resilience — or a new source of vulnerability.

Speakers

  • Jesper Roine – Adjunct Professor, Stockholm School of Economics; Deputy Director, SITE
  • Jiayi Zhou – Senior Researcher, Stockholm International Peace Research Institute (SIPRI)
  • Olha Evstigneeva – PhD Researcher in Climate Economics, Institute for Economics and Forecasting, National Academy of Sciences of Ukraine; Development Director at the Ukrainian Association of Renewable Energy and Decarbonisation Expert
  • Maria Sunér – CEO, Svemin, the Swedish Association of Mines, Mineral and Metal Producers
  • Daniel Spiro – Professor of Economics, Uppsala University
  • Aaron Maltais – Senior Research Fellow, Stockholm Environment Institute (SEI)
  • Chloé Le Coq – Professor, Paris Panthéon-Assas University; Research Fellow, SITE (Moderator)

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.

Consequences of Disability from the Perspective of Time Allocation

A significant proportion of the economics literature on the consequences of disability focuses on its implications for labor market activity and the effects of programs dedicated to supporting the disabled. This focus leaves out fundamental aspects of disability, and poor health more generally, which play a crucial role in directly determining individual and social welfare. In this policy brief, we report key results from a recent paper in which we examine the implications of disability from the perspective of time use (Hamermesh and Myck, 2025). Our analysis is based on the data from the American and the Polish Time Use Surveys and is complemented with time use information from several other countries. We examine how disability affects the variety of activities performed during the day by older individuals and how it changes the amount of time spent on the main, most common activities. Using information on how people value variety, we provide monetary estimates of the time cost of disability.

Introduction

Having a physical disability may in many ways restrict opportunities. Disability reduces employment, labor force participation, and work hours; it has negative consequences for earnings and thus consumption and wealth. It affects happiness, partly through labor-market effects, and partly through its inherent impact. A substantial body of literature has examined the interaction of disability and labor market outcomes with a particular focus on the implications of disability support and labor market activity (Acemoglu and Angrist, 2001; Autor and Duggan, 2003; Kruse et al., 2018). While there are also studies on disability and overall welfare measures (Meyer and Kok, 2019; Deshpande et al. 2021), little is known about how disability affects details of people’s daily routines beyond labor market decisions. We address this gap in a recent paper (Hamermesh and Myck, 2025) in which we look at the implications of physical disability through the lens of time use.

Since utility is jointly determined by income and time, disability-related changes in how people allocate their time during the day may significantly affect their well-being. These effects will be especially important for older people, since they are more likely to have a physical disability and less likely to be working for pay than others. Understanding how disability affects time use may also be informative about policies that ease the daily lives of people with a disability. A physical disability imposes a constraint on how a person spends his/her time. Some things become more difficult, perhaps even impossible, to do, essentially raising the amount of time spent on that activity needed to achieve a given amount of satisfaction from it. For other activities, the rise in the cost of time inputs may be less; but other than passive leisure and passive personal activities, it is difficult to think of endeavors whose cost is not raised by a physical disability. Physical disability could also make switching activities more difficult, which means that additional time spent on certain activities adds nothing to the person’s utility. If so, disability will, in this case, again lead to fewer activities being undertaken. Because variety in time use rises with income (Gronau and Hamermesh, 2008), if supported by the data, these arguments underlie an additional dimension of the loss engendered by a disability.

Disability and Allocation of Time in Time Use Surveys

To examine the implications of disability on how people allocate their time, we take advantage of time use studies from the US (ATUS) and Poland (PolTUS) and complement them with results based on studies from several other countries. Individuals in these studies are asked to complete detailed diaries with information on how they spent their day, usually with well over a hundred activity categories assigned to each of the 144 10-minute slots in the 24 hours covered by the survey diary. On top of the information about how people spend their day, the two surveys include information on self-assessed disability status (in the case of the US data) and on the official certified disability status (in the PolTUS data). Our analysis focuses on older people who are no longer active on the labor market (aged 70+ in the US, 65+ in Poland), for whom we have detailed time use information as well as other necessary basic characteristics, such as age, marital status, ethnicity, education, etc.

In the first step of the analysis, we use samples of all adults to aggregate reported non-work activities into four categories of the most common things people do: activities that, on average, take over 10 minutes per day, more than 5, 2, and 1 minute per day. We then use these categories to examine how a physical disability, conditional on a number of socio-demographic characteristics, affects the time spent on these activities (“total time in category”) and the number of activities within the categories performed on the survey day (“# activities in category”). The summary of results is presented in Table 1.

 Table 1. Relation of Temporal Variety and Disability Status, Older Nonworkers in the USA (ATUS) and Poland (PolTUS)

Source: Hamermesh and Myck (2025). Notes: reported coefficient values on disability measures; controls include standard demographic characteristics, household composition, time, and regional controls. Standard errors reported in parentheses below the parameter estimates. ATUS: N=11,188, PolTUS: N = 14,180 diaries, 7,090 individuals. Total number of activities per category: ATUS: 13, 24, 46, 74; PolTUS: 16, 30, 47, 71. For details see Hamermesh and Myck (2025).

Older individuals in the US and Poland with a self-assessed (US) or certified disability (PL) engage in a reduced number of activities per day compared to those with no disability. The reduction ranges from 0.4 to 1.0 activity in the US, depending on the category, which corresponds to a decline in variety from about 6.6 to 10.3 percent. In Poland, the reductions are smaller – from 0.3 to 0.4, corresponding to declines of between 3.5 and 4.3 percent. ATUS estimates also suggest that older disabled Americans spend more time in each of the four sets of activities than do those without a disability.

These results are confirmed in our analysis using time use surveys from Canada, France, Italy, Spain, and the United Kingdom, which are all available in the Multinational Time Use Study (MTUS) database. While countries use slightly different definitions of disability, and there are country-specific differences in how individuals allocate their time during a typical day, in all countries except for the UK, we find consistent results that older non-workers with a disability/health issue enjoy less variety in their time use than those without a disability. The estimated differences are as high as 17 percent in Italy and 18 percent in Spain.

Evaluating the Monetary Cost of Disability Using Its Effect on Time Use Variety

The above results show that having a disability is associated with fewer different activities undertaken during a day.  Our additional analysis for the US, based on a proposed “sesqui difference” estimator, supports a claim that this relationship is likely to be causal (for details see Hamermesh and Myck, 2025). Thus, in a framework that recognizes the joint roles of time and income for well-being, by reducing the temporal variety that a person can enjoy, a disability directly reduces living standards. While we cannot infer the change in utility from the imposition of these extra costs and the loss in variety, we can ask how much compensation (income) would allow the person with the disability (and thus less time variety) to achieve the same variety in time use as an otherwise identical non-disabled individual.

For this purpose, we re-estimate our models for the data from the US, Poland, Canada, the UK, France, and Spain, using smaller samples for which we also have details about people’s household incomes. The summary of results is reported in Table 2. As the dependent variable we use the group of the top 46 and 47 most common activities in the US and Poland, respectively, and the aggregated activity categories available in the MTUS datasets for the other countries (see Table 2 notes for details). We find positive and statistically significant relations of income to time variety in all of the examined countries and confirm earlier results on the relationship between time use variety and disability measures. We then use the results to compute the monetary compensation C relative to the mean average annual income of older non-workers, YAVE, that would equalize the temporal variety enjoyed by people with/without a disability:

where the αj are the estimated relationships of disability status and income to the variety of time use.  The final row in Table 2 shows the estimate of C in each of the six countries. It ranges from a low of 61 percent of average annual income (the U.K.) to nearly five times average annual income (the U.S.). The weighted average of the six estimates is 2.24.

Table 2. Relationship of Disability Status and Income to Temporal Variety: U.S., Poland, Canada, U.K., France, and Spain

Source: Hamermesh and Myck (2025). Notes: Time use activity category grouping: US top 46 categories; Poland: top 47; Canada, UK, Italy, and Spain, respectively: 55, 54, 44, and 52 aggregate categories available in MTUS database. For Poland: two time use diaries for each of 6059 individuals. Vectors of controls include standard demographic characteristics, excluding educational attainment, given very high correlation of education with household income. Standard errors reported in parentheses below the parameter estimates. For details see Hamermesh and Myck (2025).

Conclusions

In a recent paper, we demonstrated that a physical disability is related to how a person spends time. Fewer different things are done, so that on average each activity undertaken consumes more of the individual’s time (Hamermesh and Myck, 2025). Looking into more details, we find that more time is spent sleeping and watching television, and less is devoted to activities that require active participation, such as cooking, cleaning, and attending religious services. That older people with disabilities engage in fewer activities than otherwise identical individuals implies a loss of well-being because people generally find variety enjoyable— being able to perform more activities on a usual day is income-superior. Indeed, taking the average of the estimates for six different countries, we find that it would take more than twice the value of people’s annual income to compensate them for the loss of time-use variety of someone with disability compared to an older person without it.

With disability rates among older people in the range of 20-50 percent, depending on age, a better understanding of the different dimensions of utility loss that result from it seems necessary to specify appropriate policy recommendations. By analyzing how a disability is related to the time use of older people, we have opened a large variety of questions and areas for future research that will add to our understanding of the impact of disabilities. A comprehensive approach to the consequences of disability, going beyond the limitations at the workplace and beyond the expense of medical interventions, is necessary to structure policies focused on relaxing time constraints and thus, among other things, allowing those with disabilities to enjoy a greater variety of activities.

Acknowledgement

Michał Myck acknowledges the support of the Swedish International Development Cooperation Agency, Sida.

References:

  • Acemoglu, D., Angrist, J. (2001). Consequences of employment protection? The case of the Americans with Disabilities Act, Journal of Political Economy, 109, 915-57.
  • Autor, D., and Duggan, M. (2003). The rise in the disability rolls and the decline in unemployment,  Quarterly Journal of Economics, 118, 157-206.
  • Deshpande, M., Gross, T., Su, Y. (2021). Disability and distress: The effect of disability programs on financial outcomes, American Economic Journal: Applied Economics, 13, 151–78.
  • Gronau, R., Hamermesh, D. (2008). The demand for variety: A household production perspective, Review of Economics and Statistics, 90, 562-72.
  • Hamermesh, D., Myck, M. (2025). The Time Cost of a Disability, Journal of Health Economics, 104, 103079, doi: 10.1016/j.jhealeco.2025.103079.
  • Kruse, D., Schur, L., Rogers, S., Ameri, M. (2018). Why do workers with disabilities earn less? Occupational job requirements and disability discrimination, British Journal of Industrial Relations, 56, 798-834.
  • Meyer, B., Kok, W. (2019). Disabilities, earnings, income, and consumption, Journal of Public Economics, 171, 51-69

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.

Suggested Reading

Breaking Free of Russia’s Energy Grip: How Much Will It Cost Belarus?

The competitiveness of the Belarusian economy is largely determined by its access to cheap Russian energy resources. The country’s total dependence on Russia for oil and natural gas supplies poses a major vulnerability for the Belarusian economy should its citizens strategically choose to integrate with the EU. A severe energy shock – a sharp increase in gas and oil prices – is highly likely to follow if political relations between Belarus and Russia worsen. This study assesses the sectoral and macroeconomic consequences of such a shock for Belarus using a computable general equilibrium model.
The simulation results show that primary raw material processing industries, as well as manufacturing sectors heavily dependent on cheap energy resources, could face significant output losses. In turn, export-oriented, higher-value-added sectors (mechanical engineering, communications, pharmaceuticals, and light industry) have the potential to increase production and exports through the inflow of labor and capital. Should the EU choose to provide carefully designed support – focused on targeted energy subsidies, support for Belarusian firm integration into European production chains, and productivity-oriented financial assistance – the negative short-term consequences of an energy shock could be largely mitigated.

The Need for Strategic Choice

For Belarus, one of the most important strategic choices concerns its future orientation between continued reliance on Russia and deeper integration with the European Union (EU).

At present, the Belarusian economy is strongly integrated with Russia (Kruk, 2024). More than 60% of foreign trade is linked to the Russian market; the country benefits from heavily subsidized energy imports. About 4–5% of general budget revenues come from Russia as transfers; furthermore, Belarus has the possibility to refinance its public debt due to political agreements. Structural dependence makes Belarus highly sensitive to political and institutional changes in relations with Russia, limits opportunities for productivity gains, and undermines household welfare through lower income growth relative to EU countries.

Closer integration with the EU offers a different path. It has opportunities and risks: opportunities in terms of access to larger markets, advanced technologies, and investment, and risks in terms of adjustment costs for sectors reliant on cheap Russian energy resources, and social challenges.

One of the main challenges for Belarus if the country moves toward EU integration will be an energy shock caused by dependence on Russia. Russia is currently Belarus’s sole supplier of natural gas and oil. Prices for these supplies are preferential and politically determined.

Since 2018, Belarus has been importing natural gas from Russia at a contractual price close to $130 per thousand cubic meters. For comparison, according to the World Bank, the average price of natural gas in Europe was more than $400 per thousand cubic meters in 2024–2025 (about $290 in 2010–2019).

Belarus also imports oil from Russia at a price based on Urals crude. Due to the widening discount of Urals relative to the Brent benchmark since 2022, Belarus has received an additional benefit estimated at about $5.5 bn for 2022–2025.

Low energy prices support the competitiveness of entire sectors of the Belarusian economy, at the same time making them extremely vulnerable to sustained energy price hikes. As a result, Belarus’s shift away from Russia and toward the EU could lead to significant (even if transitory) losses in output and household welfare. This study aims to estimate these losses.

CGE Model for Belarus

To assess the consequences of the energy shock, a computable general equilibrium model (CGE) was developed (BELECONOMY, 2025). CGE offers a consistent framework that links sectoral interactions, resource allocation, and household welfare in a general equilibrium setting.

A CGE includes exogenous and endogenous variables, as well as market-clearing constraints. All the equations in the model are solved simultaneously to find an economy-wide equilibrium in which, at a set of prices, the quantities supplied and demanded are equalized in every market (Burfisher, 2021). To conduct an experiment, one or more exogenous model parameters are changed, and the model is then solved to determine the new values for the endogenous variables. Such a simulation shows how the economy’s sectoral structure changes and what the new steady state looks like after an economic shock.

The Belarusian case is a clear example where such modeling is highly useful. The economy’s dependence on Russia creates vulnerabilities that cannot be understood through partial-equilibrium or sectoral analysis alone. A sharp and sustainable increase in energy prices affects not only the directly exposed sectors but also wider economy through changes in costs, relative prices, and resource allocation. A CGE framework is therefore indispensable for capturing these linkages and providing a comprehensive view of outcomes.

The model for the Belarusian economy is based on the basic postulates of the CGE modeling. The factor market supplies factors of production (such as labor and capital) to activities. Activities produce goods and services and are introduced by sectors. The commodities market distributes goods and services produced by sectors. Domestic output enters the commodities market, a part of which is exported, and the imported goods, together with the domestic output consumed domestically, create domestic demand. Commodities are purchased as intermediate consumption by activities, as final consumption by households and government, and for capital formation.

The Belarusian CGE model is implemented in two specifications. Baseline specification includes 17 production sectors, and the external sector is introduced by 4 counterparties – trade partners: Russia, the EU, China, and the rest of the world. In the alternative specification, the activities are disaggregated to 22 production sectors. and the external sector is assumed to be a single counterparty, without explicitly modeling different regions.

The key input used in the model is the 2019 Input–Output table data published by the Belarusian National Statistical Committee. The base year of 2019 is chosen since that year was the last one with compete data and without significant external shocks.

Simulation Design

The developed CGE model has been used to simulate a sharp increase in the prices of natural gas and oil imported by Belarus.

Specifically, if Belarus moves closer to the EU and exits the EAEU, the country’s gas import price is highly likely to approach the European level, regardless of the source of supply. This would mean a powerful shock, roughly equivalent to a threefold increase in the import price of gas.

Regarding oil import prices, the scenario assumes a 10% increase. This roughly corresponds to a long-run effective discount of Urals to Brent that Belarus enjoyed prior to the current sanctions. Accounting for the volumes of oil and natural gas imports, the overall price increase for the product group “oil & gas, petroleum products” will amount to 60%. A shock of this size is incorporated into the simulation scenario.

The scenario also assumes the elimination of inter-budgetary transfers between Belarus and Russia. These transfers are largely linked to obligations within the EAEU, as well as to inflows into the Belarusian budget from reverse excise taxes on oil products from the Russian budget. These transfers are likely to be eliminated if Belarus moves closer to the EU.

Simulation Results

If prices for imported energy resources increase by an average of 60%, domestic production of petroleum products practically ceases. The country’s fuel demand is met exclusively through imports (Figure 1). The near-elimination of domestic petroleum product production under such a severe price shock confirms that the viability of this sector in Belarus was primarily sustained by the redistribution of oil rents from Russia to Belarus through subsidized prices.

A significant increase in energy prices will have a strongly negative impact on industries related to the primary processing of raw materials. The chemical industry, the production of plastics and rubber products, metallurgy, the manufacture of other non-metallic products (primarily construction materials), as well as electricity generation and water supply (utilities), will experience losses in output and exports. Due to intersectoral effects from the oil refining industry, output in wholesale trade, transportation, and other services will also decline. The decrease in construction materials output is also linked to a downturn in construction (Figure 1).

Productive resources from the “losing” industries will be reallocated to sectors with higher export potential (Figure 2). Output and exports will increase in mechanical engineering (electronic, electrical, and optical devices, machinery and equipment), transportation vehicles, light industry, and woodworking, as well as in communication and computer services (ICT).

Figure 1. Exports, imports, and domestic production: results of scenario simulation

Source: Author’s calculations based on CGE.

Figure 2. Factors of production: results of scenario simulation

Source: Author’s calculations based on CGE.

As a result, under a severe energy shock, two groups of industries can be distinguished. The industries that generally produce low- or medium-technology products will suffer substantial losses in value added (Figure 3). In turn, technologically advanced sectors, such as mechanical engineering and information and communications, have the potential to increase value added thanks to their export potential, lower dependence on oil and gas, and the reallocation of labor and capital. (Figure 3).

Figure 3. Sectoral value added: results of scenario simulation

Source: Author’s calculations based on CGE.

The macroeconomic effects of implementing the energy shock scenario will manifest as declines in both public and private consumption, as well as in investment. The resulting GDP losses are estimated at 3.5% of the initial period’s real volume (Figure 4).

Figure 4. GDP and components: models’ comparison of scenario simulation

Source: Author’s calculations based on CGE.

The macroeconomic and sectoral consequences of simulating the energy shock scenario using the alternative model (22 sectors, without separate trading partners) are generally close to those of the baseline model (Figure 4). The greater sectoral disaggregation of the alternative model makes it possible to identify two more industries with potential for output growth: the production of fabricated metal products and pharmaceuticals. This result highlights that, with a significant increase in energy costs, labor and capital resources shift toward more sophisticated sectors with higher value added.

EU Financial Support: Potential Effects

The above economic effects apply over the long term as the economy adapts to new conditions. In the short term, costs will be much higher, and a collapse of energy-intensive sectors cannot be ruled out.

The impact of such a transition on the Belarusian economy can be mitigated with external help.  We conducted additional simulations, assuming the use of the EU’s currently frozen financial support package for the five areas outlined by the EU Commission in 2021, at the amount specified for these five areas – €870 million (EU Commission, 2021).

The results of simulating the energy shock scenario with EU financial support show that €870 million in EU assistance can offset about 1.2 p.p. of Belarus’s GDP decline (Figure 5). This is achieved mainly due to a smaller reduction in household consumption and investment.

If we include the entire declared potential volume of EU financial support for Belarus (€3 bn) in the simulation, then GDP losses may be avoided. Household consumption would remain below the initial level, but the gap would be significantly smaller than in the baseline scenario (Figure 5).

Figure 5. Macroeconomic effects of EU financial support

Source: Author’s calculations based on CGE.

It should be noted that the simulated effects of EU financial support depend on its composition and timing. Therefore, the results of these simulations are largely illustrative and should be seen as an assessment of the scale of assistance needed to mitigate the economic losses from the energy shock in Belarus.

Conclusion

The simulations demonstrate that a powerful energy shock would have a large-scale negative impact on output and consumption. At the same time, it would not cause a full collapse of the Belarusian economy. Without EU support, long-term GDP losses are estimated at 3–4%. The most significant losses would be concentrated in industries linked to the primary processing of raw materials – oil refining, metallurgy, production of building materials, chemical industry, and electric power supply. Nevertheless, other sectors, such as mechanical engineering, light industry, pharmaceuticals, and ICT, may benefit from the reallocation of production resources. This suggests that the economy possesses a degree of structural resilience, with certain sectors able to absorb resources and adapt to changed conditions. In the long term, this reallocation may partially mitigate the overall economic losses, although the transition period would be socially and politically challenging.

The simulation results also shed light on how EU engagement could shape adjustment outcomes, should it choose to act.

First, targeted energy subsidies from the European Union or preferential financing for energy imports during the initial adjustment period could play a crucial role in cushioning the immediate impact of higher oil and gas prices. Such subsidies would prevent an abrupt collapse of energy-intensive industries and allow time for structural adjustment.

Second, efforts to remove barriers to the participation of Belarusian firms in European value chains could significantly ease the negative short-term consequences of deteriorating trade relations with Russia. By facilitating access to new markets, technologies, and standards, integration into European supply chains could not only soften the transition but also enhance long-term competitiveness.

Third, direct financial support from the EU would have the potential to offset a substantial part of GDP and welfare losses. However, to achieve lasting results, such support would need to be targeted toward raising factor productivity through investments in human capital, digitalization, and modern infrastructure.

Fourth, social safeguards are essential. The significant energy shock will unavoidably bring sectoral declines and job displacements. EU support could therefore extend to retraining programs, measures that promote labor mobility, and social protection systems, ensuring that the short-term adjustment costs do not lead to lasting social and political instability.

Acknowledgments

This brief is based on research funded by the EU.

References

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.

Trade Diversification, Export Complexity, and Structural Transformation in the South Caucasus and Central Asia

Large container cargo vessel being loaded at a deep sea port with cranes, colorful shipping containers, and a clear blue sky


This policy paper examines trade diversification, export sophistication, and economic complexity in the South Caucasus and Central Asia during 2019–2024. Using detailed product-level trade data, it assesses how concentrated or diversified countries’ exports and imports are, as well as changes in the sophistication of the products they export. Evidence from the Atlas of Economic Complexity is also used to evaluate diversification opportunities based on countries’ productive capabilities. 

The results reveal substantial heterogeneity across the region. Georgia and Kazakhstan maintain relatively diversified export structures, while Armenia and Azerbaijan exhibit increasing export concentration. Export sophistication improves modestly in several countries, particularly Armenia and Uzbekistan. Overall, the findings suggest gradual but uneven structural transformation across the region, with diversification into more complex export sectors remaining limited.

Introduction

International trade plays a central role in shaping economic growth and macroeconomic stability in the South Caucasus and Central Asia (CCA). The economies of the region are highly open, with trade flows accounting for a large share of GDP in most countries. This strong integration into global markets creates important opportunities for growth, but it also exposes these economies to fluctuations in global demand, commodity prices, and international supply chains, potentially with drastic consequences.

This exposure has become particularly concerning in the context of the global economic environment since 2019. A series of major shocks—including the COVID-19 pandemic, Russia’s invasion of Ukraine, and ongoing conflicts in the Middle East—have disrupted global supply chains, energy markets, and transport corridors. At the same time, geopolitical tensions and shifting industrial and trade policies have increased global policy uncertainty. Frequent changes in tariff policies and strategic trade measures by major economies, including the United States, have further contributed to an increasingly uncertain global trading environment.

In this context, the resilience of national economies depends not only on the scale of trade but also on its structure. Countries with concentrated export baskets or strong dependence on a small number of trading partners are typically more vulnerable to external shocks. By contrast, economies with diversified exports and greater participation in higher-value production tend to be more resilient and better positioned for long-term growth. Three related concepts—trade diversification, product sophistication, and economic complexity—provide useful tools for evaluating these structural characteristics. Diversification captures the breadth of the export basket; product sophistication reflects the income and knowledge intensity of exported goods; and economic complexity reflects the broader productive capabilities that underpin them.

This research brief examines the trade structures of the South Caucasus and Central Asian countries through these three dimensions. Using detailed product-level international trade data, the analysis evaluates export and import diversification, the income and technological content of export baskets, and the broader productive capabilities reflected in economic complexity indicators. By comparing patterns across countries and over time, the brief provides new insights into how the region’s economies are positioned to navigate an increasingly uncertain global trading environment.

Stylized Facts: External Balances and Trade Structure

Recent data highlight two closely related characteristics of South Caucasus and Central Asian economies: substantial variation in external balances and strong exposure to international trade. Current account positions differ significantly across the region and fluctuate over time, reflecting differences in export structures, commodity dependence, and import demand (Figure 1). Resource-rich economies such as Azerbaijan, Kazakhstan, and Turkmenistan periodically record sizable surpluses driven largely by oil and natural gas exports, while several other economies experience persistent deficits associated with narrower export bases and higher reliance on imports. Particularly large deficits were observed in the Kyrgyz Republic during 2022–2023, illustrating the sensitivity of smaller economies to shifts in trade flows and external demand. These dynamics are closely linked to the high degree of trade openness observed across the region: smaller economies such as Georgia, Armenia, and the Kyrgyz Republic exhibit particularly high trade-to-GDP ratios, while larger economies such as Kazakhstan and Uzbekistan show somewhat lower—but still substantial—levels of trade exposure.

Figure 1. Current Account as a percentage share of GDP (2019-2025)

Source: Authors’ calculations, IMF

Figure 2 summarizes the geographic composition of trade across the region and highlights the continued importance of a relatively small number of external partners. The European Union, Russia, China, and other CIS economies dominate both export destinations and import sources. Comparing 2019 and 2024, several broad regional shifts emerge. On the export side, the European Union increased its relative importance as a destination for many exports—particularly energy and resource-based products; exports directed to Russia and other CIS markets also grew in importance after 2022. In turn, the share going to the residual category of other countries fell substantially. On the import side, Russia and China strengthened their positions as key suppliers across much of the region, reflecting geographic proximity, established transport corridors, and China’s growing role in regional trade. Imports from the European Union remained important, especially for machinery, equipment, and higher-value manufactured goods.

Overall, despite some adjustments between 2019 and 2024, the region’s trade patterns remain concentrated among a relatively small group of partners. This concentration increases exposure to destination-specific shocks and may weaken trade resilience. It is therefore important to assess not only how diversified exports are, but also how sophisticated and capability-intensive they are, since these characteristics affect an economy’s ability to adapt and redirect trade over time.

Figure 2. Geographic Structure of Regional Exports and Imports for South Caucasus and Central Asian economies, 2019 vs. 2024

Source: Authors’ Calculation, UN Comtrade. Note: Shares of major partner groups (European Union, Russia, China, CIS, and other countries) in total exports and imports of South Caucasus and Central Asian economies.

Methodology

To analyse the structure and evolution of trade patterns, the study employs four complementary indicators: the Herfindahl–Hirschman Index (HHI), the Theil index, the export sophistication indicators PRODY and EXPY, and the Economic Complexity Index (ECI). These indicators capture different aspects of trade structures, including concentration, diversification, technological sophistication, and productive capabilities embedded in economies.

Trade concentration is first evaluated using the Herfindahl–Hirschman Index (HHI). The index measures the extent to which a country’s exports or imports are concentrated across products. In this study, the index is calculated at the HS-4 product level, allowing for a detailed assessment of trade structures.

The Herfindahl–Hirschman Index is defined as:
\[
HHI_i^X = \sum_{k=1}^{N} \left(s_{ik}^X\right)^2
\]
\[
HHI_i^M = \sum_{k=1}^{N} \left(s_{ik}^M\right)^2
\]

where
\[
s_{ik}^X = \frac{X_{ik}}{X_i}
\]
\[
s_{ik}^M = \frac{M_{ik}}{M_i}
\]

Here

  • $s_{ik}^X$ = the share of the product in country ’s total exports
  • $s_{ik}^M$ = the share of the product in country ’s total imports
  • $X_{ik}$ denotes exports of the product  by country
  • $M_{ik}$ denotes imports of the product  by country
  • $X_i$ denotes the total exports of country
  • $M_i$ denotes the total imports of country

The index ranges between 0 and 1. Values close to zero indicate highly diversified trade structures, while values approaching one suggest strong concentration in a limited number of products.

The HHI provides a simple summary of whether trade is concentrated in a small number of products or partners. To complement this, the analysis also uses the Theil index, which captures how unevenly trade is distributed across all destinations or product categories. This distinction matters because similar levels of overall concentration can mask different underlying structures. In plain terms, the Theil index compares the observed trade distribution with a benchmark of equal shares across all categories: a value of zero indicates perfect equality, and the more uneven the distribution, the higher the index. As a result, comparing the two indicators allows a more nuanced assessment of whether concentration changes reflect dominance by a few categories or broader structural shifts in trade patterns.

Unlike the HHI, the Theil index can also be decomposed into within-group and between-group components, which helps identify the sources of concentration. The Theil index for exports and imports is defined as:
\[
T_i^X = \sum_{k=1}^{N} s_{ik}^X \ln\left(\frac{s_{ik}^X}{\bar{s}}\right)
\]
\[
T_i^M = \sum_{k=1}^{N} s_{ik}^M \ln\left(\frac{s_{ik}^M}{\bar{s}}\right)
\]
where
\[\quad \bar{s} = \frac{1}{N}
\]
and N represents the total number of HS-4 products, so that the terms in brackets measure how far the actual share allocation is from the equal share one. Higher values of the Theil index indicate greater concentration of trade across products, while lower values indicate higher diversification. Compared with the HHI, the Theil index has the advantage of being decomposable into within-sector and between-sector components. That is, the HHI can be broken down into group-specific contributions, but it does not provide the same standard additive decomposition with equally clear interpretation. allowing a more detailed examination of diversification patterns. The policy paper assesses export and import concentration using the HHI and Theil indices not only by product categories but also by trading partner countries (in the formulas above, products are replaced by countries).

While the HHI and Theil indices measure concentration and diversification, they do not say much about the type of goods a country exports. To capture this dimension, the analysis uses the PRODY and EXPY indicators introduced by Hausmann, Hwang, and Rodrik (2007). These indicators assess the sophistication of a country’s export bundle, inferring it from the characteristics of the countries that export the respective products. In particular, a product receives a higher PRODY value when it is exported more intensively by higher-income economies. A country’s EXPY then summarizes the sophistication of its overall export basket by taking a weighted average of the PRODY values of the goods it exports.

More specifically, the PRODY index measures the income content of a product and is calculated as the weighted average of the GDP per capita of countries exporting that product:

\[
PRODY_k = \sum_{c} \theta_{ck} \, Y_c
\]

where

\[
\theta_{ck} = \frac{\frac{X_{ck}}{X_c}}{\sum_{c’} \left(\frac{X_{c’k}}{X_{c’}}\right)}
\]

Here

  • $Y_c$ denotes GDP per capita of country $c$,
  • $X_{ck}$ denotes exports of product $k$ by country $c$,
  • $X_c$ denotes total exports of country $c$,

In plain terms, PRODY asks whether a product is typically associated with richer or poorer exporters.

The PRODY calculation gives more weight to countries for which a product is relatively important in the export basket. This prevents the measure from being driven by very small or incidental exports. As a result, a product receives a high PRODY score when it is a meaningful export to richer economies, not merely when it appears in their trade data.

The weights $\theta_{ck}$ capture the relative importance of the product k  in each country’s export basket. Products exported primarily by high-income economies, therefore, receive higher PRODY values.

Using the PRODY values of individual products, the sophistication of a country’s export basket is measured using the EXPY index:

\[
EXPY_i = \sum_{k} \left(\frac{X_{ik}}{X_i}\right) PRODY_k
\]

EXPY applies the same logic at the country level: it shows whether a country’s export basket is tilted toward products that are more commonly exported by higher-income economies. Higher EXPY values, therefore, suggest a more sophisticated export structure – they indicate that the country exports goods that are typically produced by higher-income economies.

Unlike the HHI, PRODY and EXPY do not lie between 0 and 1. Their values are expressed on the scale of the underlying income measure used in the data, so they are most informative in comparative terms across countries and over time. Also, empirical applications frequently use the natural logarithm of EXPY. This transformation reduces skewness and facilitates interpretation in regression analysis.

Finally, to capture the deeper productive capabilities embedded in economies, the analysis incorporates the Economic Complexity Index (ECI) developed by the Harvard Growth Lab and published in the Atlas of Economic Complexity. The ECI measures the knowledge intensity of an economy by combining information on the diversity of products a country exports and the ubiquity of those products across countries.

The calculation begins with the revealed comparative advantage (RCA) indicator:
\[
RCA_{ck} = \frac{\dfrac{X_{ck}}{X_c}}{\dfrac{\sum_{c} X_{ck}}{\sum_{c} X_c}}
\]
where

  • $X_{ck}$ denotes exports of product $k$ by country $c$,
  • $X_c$ denotes total exports of country $c$.

Countries are considered competitive exporters of product k if their revealed comparative advantage in that product exceeds 1. Based on this country–product matrix relationship, economic complexity is inferred from two simple ideas: diversity and ubiquity. Diversity refers to the number of different products a country can export competitively. Ubiquity refers to how many countries can export a given product competitively. Economies tend to be ranked as more complex (have a higher value of ECI) when they export a broad range of products that relatively few other countries can produce, because this indicates a deeper and more versatile set of productive capabilities.

Taken together, these indicators provide a comprehensive framework for analysing trade structures. The HHI and Theil indices measure trade concentration and diversification at the HS-4 product level for both exports and imports (as well as concentration by countries), the PRODY and EXPY indicators capture the income sophistication of export baskets, and the Economic Complexity Index reflects the underlying productive capabilities of national economies.

Results

The HHI results reveal significant cross-country differences in export diversification. Georgia and Kazakhstan consistently exhibit the lowest export concentration by destination country across the period, with HHI values remaining below 0.15. Although both countries experience a gradual increase in concentration over time, their exports remain comparatively diversified across destination countries relative to the rest of the region.

In contrast, Armenia and Azerbaijan show a noticeable increase in export concentration by destination country after 2021. Armenia’s export HHI rises sharply and remains close to the upper benchmark threshold by 2024, suggesting that exports became increasingly reliant on a smaller set of countries. Azerbaijan also shows a temporary increase in export concentration around 2022, followed by a modest decline by 2024, indicating partial normalization after the peak of external shocks.

The Kyrgyz Republic and Uzbekistan exhibit persistently higher average export concentration by destination country than other countries in the region. Kyrgyzstan reaches particularly high levels during the early pandemic years and remains relatively concentrated thereafter. Uzbekistan also maintains a relatively high concentration, although its export structure shows some signs of gradual diversification toward the end of the period. Tajikistan remains in the intermediate range, with export concentration by country relatively stable across years.

Import concentration patterns differ from those of exports. Several countries maintain relatively diversified import structures by source country throughout the period. Georgia and Azerbaijan show consistently low import HHI values, indicating broad import structures. However, for some other countries in the region, import concentration increases sharply during the shock period. Kazakhstan experiences a substantial increase during 2020–2022, followed by a return to lower levels in subsequent years. Armenia also records a sharp increase in import concentration in 2024, suggesting increased reliance on a narrower set of partner countries. Kyrgyzstan shows a gradual increase toward the end of the sample period.

Figure 3. HHI of Export by Country, 2019–2024

Source: Author’s Calculation, UN Comtrade

Figure 4. HHI of Import by Country, 2019–2024

Source: Author’s Calculation, UN Comtrade

Examining concentration at the HS4 product level provides additional insight into the structure of trade baskets. Changes in overall HHI may arise either because the product distribution becomes more uneven or because a small number of product categories become temporarily dominant.

The HS4-product level export results (Figure 5) reveal substantial cross-country variation in product concentration. Azerbaijan remains the most concentrated exporter throughout the period. Although the figure shows some decline in concentration in the earlier years, this change is not sustained, and the country’s export basket remains heavily concentrated in a narrow set of products. Kazakhstan also shows a relatively high concentration, although the decline after 2022 suggests some gradual diversification. In contrast, Georgia and Tajikistan maintain consistently low HHI values, indicating relatively diversified export baskets across HS4 product categories. Armenia and Uzbekistan remain in the intermediate range, although Armenia shows an increase in concentration in 2024.

Import concentration at the HS4 product level (Figure 6) remains generally lower than export concentration but exhibits greater volatility across countries. Most economies maintain relatively diversified import baskets, with HHI values typically below 0.05–0.06. However, several temporary spikes are visible. Armenia records a sharp increase in import concentration in 2024, suggesting growing reliance on a narrower set of imported goods. Kyrgyzstan experiences a pronounced spike in 2023, while Georgia shows a moderate increase during 2022–2023, then stabilizes. These fluctuations likely reflect temporary supply disruptions, shifts in trade routes, or changes in import demand during periods of economic and geopolitical shocks.

Figure 5. HHI of Export by HS4 Product Categories, 2019–2024

Source: Author’s Calculation, UN Comtrade

Figure 6. HHI of Import by HS4 Product Categories, 2019–2024

Source: Author’s Calculation, UN Comtrade

The country-level Theil index largely reinforces the message from the HHI analysis: across the region, recent changes in export concentration have been driven mainly by shifts in the distribution of exports across destination markets rather than by a restructuring of export baskets.

Armenia shows the clearest increase in geographic concentration, while Azerbaijan also remains relatively concentrated despite some normalization after the 2022 spike. Georgia remains the most geographically diversified case, and Kazakhstan, Kyrgyzstan, and Uzbekistan show only moderate changes over time. Overall, the Theil results add nuance rather than overturning the HHI findings: they suggest that the main source of recent concentration has been unevenness across partner countries, not a uniform narrowing of export structures across all economies.

At the product level, the Theil index points to a more nuanced picture. In several countries, product-level inequality declines or remains moderate even when destination-country concentration rises, suggesting that geographic concentration and product concentration do not always move together. This is especially important for interpretation: an economy may become more dependent on a smaller set of trading partners while still maintaining or even broadening the composition of its export basket. Azerbaijan remains the clearest case of persistently high product concentration, whereas Georgia continues to display a relatively diversified product structure.

In cases where the Theil and HHI measures differ somewhat, the gap likely reflects that the HHI is more sensitive to dominant categories, whereas the Theil index captures unevenness across the full distribution of trade shares.

The product-level Theil index (Figure 7) also provides additional insights into the composition of export baskets. Armenia, Kazakhstan, and Uzbekistan show noticeable declines in product-level inequality between 2019 and 2024, suggesting some diversification across product categories despite rising geographic concentration. This pattern indicates that while exports may increasingly rely on fewer destination countries, the underlying product composition has broadened.

In contrast, Azerbaijan maintains a relatively high product concentration, which is fully consistent with the HS4-product level HHI results showing the highest export concentration across product categories in the region. Georgia shows a slight increase in product-level inequality, although overall concentration remains relatively low compared to most other countries, confirming the diversified structure observed in the HHI product-level analysis.

Overall, the Theil index results reinforce the conclusions drawn from the HHI analysis while providing additional insight into the drivers of concentration. The evidence suggests that recent changes in trade structures across the South Caucasus and Central Asia are driven primarily by shifts in geographic export patterns rather than by widespread narrowing of product specialization. In several countries, product diversification appears to be improving even as exports become more concentrated across trading partners.

Figure 7. Theil Index by Country and Product Categories, 2019 and 2024

Source: Author’s Calculation, UN Comtrade. Note: Higher values indicate greater concentration in the distribution of products.

Export sophistication is measured by the EXPY index, with higher values indicating that a country exports products typically produced by higher-income economies.

Between 2019 and 2024, export sophistication increases for most countries in the region, although the magnitude of change varies (Figure 8). Armenia shows the largest improvement in EXPY, suggesting a shift toward higher-value exports. Uzbekistan and the Kyrgyz Republic also show moderate increases in export sophistication. In contrast, Azerbaijan, Georgia, and Kazakhstan experience only modest changes, indicating relatively stable export structures over the period.

Importantly, increases in export sophistication should be interpreted alongside changes in concentration indicators. When EXPY increases while export concentration remains low or declines, the improvement reflects broader structural upgrading. However, when increases in EXPY coincide with rising concentration, the shift may reflect specialization in a smaller number of higher-value products rather than broad-based diversification.

Figure 8. Export Sophistication (EXPY), 2019 and 2024

Source: Author’s Calculation, UN Comtrade. Note: Higher values indicate a more sophisticated export basket.

The previous indicators evaluate diversification and sophistication based on observed trade patterns. An additional perspective on structural transformation can be obtained by examining future diversification opportunities, using the feasibility analysis derived from the Atlas of Economic Complexity Index (ECI) developed by the Growth Lab at Harvard University (see Figure 9). This framework maps potential export opportunities based on the relationship between product sophistication and proximity to existing productive capabilities.

Figure 9. Economic Complexity Index (ECI), 2012- 2024

Source: Growth Lab at Harvard University

Across the South Caucasus and Central Asia, the feasibility analysis reveals substantial heterogeneity in the pace and depth of structural transformation. Armenia, Kazakhstan, and Uzbekistan show the most pronounced improvements in economic complexity over time, suggesting that a growing number of technologically more sophisticated products are becoming feasible given existing productive capabilities. This pattern indicates a widening diversification frontier and reflects the accumulation of capabilities that can support expansion into more complex sectors.

These findings are broadly consistent with the earlier results on export sophistication (EXPY), which also show noticeable improvements in Armenia and moderate gains in Uzbekistan and Kazakhstan. At the same time, the concentration indicators provide an important qualification. While Armenia shows rising export sophistication, the HHI and Theil indices indicate increasing export concentration in recent years. This suggests that structural upgrading may be occurring alongside a narrowing export base, implying that diversification into complex products has not yet become broad-based. Uzbekistan and Kazakhstan present a more balanced picture, with modest improvements in sophistication accompanied by relatively stable or moderate concentration levels, which is more consistent with gradual structural diversification.

Georgia and Kyrgyzstan display more incremental dynamics in the ECI analysis. Their export structures have become somewhat more sophisticated, but diversification largely occurs within sectors that remain relatively close to their existing productive structures and only moderately more complex than current exports. This pattern aligns with the earlier results showing relatively stable concentration indicators and only modest increases in export sophistication, pointing to gradual capability accumulation rather than rapid structural upgrading.

In contrast, Azerbaijan and Tajikistan remain more constrained by relatively low levels of economic complexity. In these economies, the distribution of feasible products remains concentrated in lower-complexity segments of the product space, and many technologically more sophisticated activities remain distant from their current capability base. This result is partly consistent with the earlier findings from concentration indicators: Tajikistan’s export structure remains relatively stable but limited in diversification, while Azerbaijan’s export structure continues to be influenced by resource-based specialization. As a result, the set of feasible diversification opportunities remains narrower and concentrated in sectors with relatively limited technological sophistication.

Overall, the ECI analysis complements the empirical results obtained from HHI, Theil, and EXPY indicators. While some countries in the region demonstrate signs of capability accumulation and gradual upgrading, the results suggest that structural transformation remains uneven across the region. In several cases, improvements in export sophistication occur alongside persistent concentration in a limited number of products, indicating that diversification into more complex sectors has not yet translated into broad-based structural change.

Conclusion

This brief examined the evolution of trade diversification, export sophistication, and structural transformation in the South Caucasus and Central Asia between 2019 and 2024. The results show substantial cross-country differences. While some economies maintain relatively diversified export structures, others remain more dependent on a narrow set of products. Export sophistication has improved modestly in several countries, but in some cases, this has coincided with rising export concentration. This does not necessarily indicate a negative development: such a pattern may reflect successful specialization based on comparative advantage or upgrading into higher-value activities. However, when sophistication gains are concentrated in a small number of products or markets, the resulting export structure may remain vulnerable to external shocks and less supportive of broad-based structural transformation.

The analysis also points to uneven progress in productive capabilities across the region. Some countries are gradually expanding the range of products they can competitively produce, while others remain constrained by narrower capability bases.

These results highlight the nuanced relationship between diversification, sophistication, and economic complexity. Diversifying into more complex sectors can strengthen economic resilience by broadening the range of activities an economy can rely on, reducing dependence on a limited set of simple or commodity-based exports, and enhancing the capacity to adapt to changes in demand, prices, or trade routes. In this context, the key policy challenge is not diversification for its own sake, but fostering the development of productive capabilities that enable more sophisticated, adaptable, and resilient export structures over time.

References

  • Balland, P.-A., Boschma, R., Crespo, J., & Rigby, D. (2019). Smart specialization policy in the European Union: relatedness, knowledge complexity and regional diversification. Regional Studies, 53(9), 1252–1268.
  • Brummitt, C. D., Gómez-Lievano, A., Hausmann, R., & Bonds, M. H. (2018). Machine-learned patterns suggest that diversification drives economic development.
  • Hausmann, R., Hwang, J., & Rodrik, D. (2007). What you export matters. Journal of Economic Growth, 12(1), 1–25.
  • Hausmann, R., Hidalgo, C., Bustos, S., Coscia, M., Chung, S., Jimenez, J., Simoes, A., & Yıldırım, M. (2014). The Atlas of Economic Complexity: Mapping Paths to Prosperity. MIT Press.
  • Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexityProceedings of the National Academy of Sciences, 106(26), 10570–10575.
  • International Monetary Fund. (various years). Regional Economic Outlook: Middle East and Central Asia.
  • Neffke, F., Hartog, M., Boschma, R., & Henning, M. (2018). Agents of structural change: The role of firms and entrepreneurs in regional diversification.
  • Rodrik, D. (2006). What’s so special about China’s exports? China & World Economy, 14(5), 1–19.
  • World Bank. (2020). Central Asia Trade: Structural Transformation and Diversification.
  • Harvard Growth Lab. (2024). Atlas of Economic Complexity – Feasibility Analysis.
  • United Nations Comtrade Database. (2024). International Trade Statistics.
  • World Bank. (2023). 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.

The Hormuz Shock: EU’s Gas Security and Decarbonization Fragility

The February 2026 conflict in the Persian Gulf and the partial closure of the Strait of Hormuz sent European gas prices sharply higher, reviving questions about Europe’s energy vulnerability. While the EU successfully reduced its reliance on Russian gas after 2022, it has traded one dependency for another: globally traded LNG exposed to fragile shipping routes. We argue that dependence is not only a concern for energy security; it also creates decarbonization fragility — the risk that reliance on imported fossil fuels undermines the clean energy transition itself. Price spikes push producers toward coal, raise emissions, and give politicians reasons to delay climate action. The solution to both problems is the same: faster deployment of domestic clean energy, better electricity grids, and a coordinated EU industrial strategy. Reducing fossil-fuel demand at home is not only a climate goal — it is the most durable foundation for Europe’s energy security.

On 28 February 2026, US–Israeli strikes on Iran triggered a direct military conflict across the Persian Gulf. Iran moved to shut the Strait of Hormuz, a chokepoint for roughly one-fifth of global oil and gas trade (US EIA, 2025), while attacks on Qatar’s Ras Laffan complex resulted in force majeure, removing approximately one-sixth of global LNG supply from the market. Energy markets reacted immediately. European gas prices rose sharply: the TTF benchmark jumped from around €32/MWh in late February to above €50/MWh by mid-March, while Brent crude approached $100 per barrel.

While most attention has focused on the impact on the oil market (see, e.g., Gars, Spiro, and  Wachtmeister, 2026), the shock has also revived another crucial question in European energy policy: dependence on imported fossil gas. This brief examines what the Hormuz shock means for Europe’s gas market, focusing on its implications for supply security and the political momentum of the green transition.

How the 2022 Crisis Redefined EU Gas Security

Natural gas has long been central to Europe’s energy system, heating around 30% of EU households, supporting energy-intensive industries, and providing the flexible generation needed to balance renewables. But this economic importance also came with strategic risk – EU gas imports were dominated by a single supplier, Russia, which by 2021 accounted for around 45% of EU gas imports (IEA, 2022). After the invasion of Ukraine, that dependence turned into a major vulnerability. Russian pipeline gas flows to Europe fell by more than half in 2022, while the TTF gas price rose above €300/MWh in August 2022. The shock forced governments to spend over €680 bln to protect households and firms, and exposed the weakness of Europe’s industrial model.

Yet the crisis triggered a rapid policy shift. The EU responded with storage obligations, demand reduction, supply diversification, and REPowerEU, reframing clean energy and efficiency as tools of security as well as climate policy; the 2030 renewable target rose from 32% to (at least) 42.5% (EC, 2023).

The results were significant: storage reached 99% in the fall of 2023, demand fell by 18% by 2024, Russian gas imports dropped from 150 bcm in 2021 to about 40 bcm in 2025, with a full ban due in 2027 (Bruegel 2022 a, b), and EU gas imports became more diversified (see Figure 1). Between 2022 and 2025, Europe added around 250 GW of renewables (IEA, 2026), raising their share in electricity generation from 37% to 44%. The 2022 crisis had, paradoxically, done more to accelerate Europe’s green transition than a decade of climate negotiations.

The Hormuz Shock: Familiar Pattern, New Vulnerabilities

Given the lessons the EU learned from 2022, should we expect a similar “greening” in response to the Hormuz disruption?

There are clear parallels between the current shock and the 2022 crisis. In both cases, a sudden geopolitical disruption removed a major source of gas supply, pushed European buyers onto the spot LNG market, and drove TTF prices sharply higher. In both cases, uncoordinated competition among member states for scarce supply risked amplifying the price spike. 

Figure 1: Composition of EU natural gas imports in 2019-2025.

Source: Own graph based on data from Bruegel Dataset (2022a).

The differences, however, are equally important. In 2022, oil prices remained relatively contained, allowing some industrial sectors to switch away from gas. Today, with Brent above $100 per barrel, that option offers little relief. In 2022, weak Asian LNG demand, particularly from China, gave Europe room to attract cargoes at a premium. Today, Asian buyers are facing the same supply shock and competing for the same LNG volumes. Europe has also lost the limited buffer that Russian pipeline gas still provided in 2022: that supply has now largely disappeared and will soon be fully banned.

At the same time, the EU is better prepared than it was four years ago. Gas demand is already around 17% lower, regasification capacity has expanded over 50 bcm, reverse-flow interconnections have improved access across the bloc, and the institutional crisis-response framework has already been tested.

Most importantly, the supply directly at risk is much smaller than in 2022. Qatari LNG exposed to the current disruption accounts for no more than 6% of EU gas imports, far below the scale of the 2022 shock (EC, 2025a and ACER, 2024).

The global LNG market has also changed significantly since 2022. Then, Europe’s additional LNG needs hit an already tight global market: EU LNG imports rose by 64 bcm in 2022, while global incremental LNG supply was only 25 bcm. Regasification bottlenecks in Europe compounded the problem. Today, by contrast, the market is entering a major new wave of liquefaction capacity, while the EU has expanded regasification capacity by at least 50 bcm/year since mid-2022, easing the infrastructure constraints seen during the crisis. Any disruption to Qatari LNG would therefore likely create a more manageable, though still important, market squeeze than in 2022 (ACER (2024) and IEA (2025)

That said, the main vulnerability has not vanished; it has changed form. Roughly one-fifth of global trade passes annually through the Strait of Hormuz. A disruption there tightens the LNG market globally, especially in Asia, and because cargoes are traded internationally, price pressure is rapidly transmitted to Europe. That is, in replacing Russian pipeline gas with globally traded LNG, the EU reduced dependence on a single supplier but increased its exposure to geopolitical shocks affecting maritime trade. Europe is therefore more diversified than in 2022, but also more vulnerable to disruptions in strategic chokepoints far beyond its borders.

The Hormuz crisis thus reveals a deeper structural vulnerability in Europe’s post-2022 energy system — what we refer to as decarbonization fragility. The more the EU relies on LNG to secure its energy transition, the more its climate pathway becomes exposed to geopolitical shocks in global fossil-fuel supply routes.

The Environmental and Political Risks of Decarbonization Fragility

The Hormuz shock highlights that Europe’s new gas security model also carries environmental risks. As energy security increasingly depends on globally traded LNG moving through fragile maritime routes, disruptions can drive not only higher prices but also higher emissions.

First, the shock is likely to increase the carbon intensity of the EU gas supply. Facing a gas shortage, the EU may respond by replacing lost gas volumes with new, more emissions-intensive gas sources. In 2022, Russian pipeline gas was partly substituted with more emissions-intensive LNG (Campa, Paltseva and Vlessing, 2023). In the current context, the marginal supplier is likely to be the United States, whose LNG has a significantly higher lifecycle carbon footprint than Qatari LNG (Rystad 2026). (This shift may also raise renewed concerns about the concentration of supply, given that US LNG already accounted for 55% of EU LNG imports in the first half of 2025, EU (2025b)).

Second, higher gas prices can trigger substitution toward more polluting fuels. In 2022, this mainly involved switching from gas to oil products. Today, with Brent above $100 per barrel, oil is less competitive, increasing the likelihood of gas-to-coal switching in sectors unable to reduce demand quickly enough. Given that coal is significantly more carbon-intensive than natural gas, such a substitution would result in a substantial increase in emissions.

While these effects may in principle be temporary, the Hormuz shock occurs in a European political and economic context that makes them harder to reverse. Climate policy momentum in Europe was already weakening, with growing corporate caution and increasingly more firms scaling back or withdrawing net-zero commitments (Guardian, 2025).

By intensifying energy price pressures and supply uncertainty, the shock risks tilting policy priorities away from the energy transition. In a more unstable geopolitical environment, industrial competitiveness is increasingly treated as a component of Europe’s defense strategy, essential for economic resilience and strategic autonomy. At the same time, rising defense spending is placing additional strain on public finances. Together, these pressures shift political focus toward securing affordable energy for industry and maintaining economic strength, potentially at the expense of long-term decarbonisation.

This is the political dimension of decarbonization fragility. When industrial policy prioritizes energy affordability and security, external shocks are more likely to reinforce fossil-fuel dependence than to accelerate the move away from it.

The Green Transition IS Energy Security

The central lesson of both the 2022 energy crisis and the Hormuz shock is clear: energy (in)security and decarbonization fragility are closely intertwined. As long as the transition still relies on imported fossil fuels, external shocks affect more than energy supply and prices. They may also weaken the political and economic conditions on which decarbonization depends by undermining industrial competitiveness, increasing fiscal pressure, and shifting policy attention toward short-term crisis management. Fossil-fuel dependence therefore undermines not only Europe’s energy system, but also its transition pathway.

The answer is therefore not to slow the transition, but to accelerate and broaden it. A rapid transition to solar and wind alone is, of course, unrealistic, given their intermittency and the scale of investment required. Therefore, the transition must become broader in scope. The EU is already giving greater prominence to other net-zero technologies linked to security of supply and industrial resilience, including nuclear and small modular reactors. However, the expansion of domestic low-carbon capacity remains slowed by permitting bottlenecks, grid constraints, and insufficient investment in system flexibility. Moreover, as Figure 2 illustrates, it is largely uneven across the EU, which, per se, may undermine collective action and negatively affect EU energy security (Le Coq and Paltseva, 2022). Further, progress on reducing supply chain dependencies has been limited. The EU continues to rely heavily on imports for critical raw materials, clean-tech components, and key segments of manufacturing value chains, exposing the transition to new geopolitical risks. Reducing structural exposure to external shocks will require not only faster deployment but a more coordinated industrial strategy.

Figure 2. Battery, electric vehicle and solar manufacturing investments by status since 2019

Lasting resilience will not come from shifting between external dependencies, but from reducing them. Expanding domestic low-carbon capacity simultaneously lowers emissions and limits exposure to external shocks. Cutting fossil-fuel demand is therefore not only a climate objective, but the most durable form of energy security.

References:

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.

Discrimination in Work Conditions: The Case of Sexual Harassment

Blurred silhouettes of office workers behind glass symbolizing discrimination work conditions in a modern workplace environment.

The #MeToo movement put a spotlight on the severe and highly prevalent workplace problem of sexual harassment. New research argues that economists should treat sexual harassment as gender discrimination in work conditions. Both men and women are subject to this discrimination when their gender is in the minority in the workplace. These patterns reinforce segregation in the labor market and, by extension, economic gender inequality. By reducing the prevalence of sexual harassment, we not only reduce individual suffering but also have positive impacts at a societal level.

Introduction

Throughout the world, the sorting of women into lower-paying occupations and workplaces fundamentally determines economic gender inequality (see Penner et al. 2023 for an overview). The academic discussion about causes of this gender segregation typically centers on gender differences in preferences for work conditions. Women who have more responsibilities for children and the household prefer occupations and workplaces with more flexible schedules, work-from-home opportunities, and shorter commutes. To get these good work conditions (so-called work amenities), they accept jobs in occupations and workplaces with lower wages (Goldin 2014, Wiswall and Zafar 2016, Mas and Pallais 2017, Le Barbachon et al. 2019).

There is mounting evidence that the interpersonal work environment also matters greatly for job choices. Workers seem to put a large negative value on negative interpersonal work conditions such as hostility, bullying, and sexual harassment (see, for example, Folke and Ricke 2022, Collis and Van Effenterrre 2025, and Le Page et al. 2025). Unlike traditional amenities related to aspects such as schedule flexibility, training, or bonuses, the social work environment does not form part of the employment contract and is not under direct control of the employer. This implies that even among the most well-intentioned employers, the social work environment could differ across individuals – and, in particular, between men and women.

Gender differences in exposure to negative social behaviors may meet the standard definition of discrimination in empirical economics research. The mistreatment may imply that women and men with the same qualifications doing the same job receive different pay. Women and men may have the exact same job contracts and receive the exact same compensation on paper, but one gender may be exposed to negative treatment that dramatically reduces their total payoff from the job.

Sexual Harassment and Gender Inequality in the Labor Market

Folke and Rickne (2022) study how sexual harassment by colleagues and managers affects gender segregation across workplaces and, by extension, gender inequality in the labor market. The starting point is a general equilibrium model where the total pay of a job is a function of the wage and the gender-specific sexual harassment risk.

The model shows that sexual harassment leads to larger gender inequality in the labor market under three conditions. Sexual harassment risks need to increase in the share of opposite sex co-workers, wages should increase in the share of men in the workplace, and sexual harassment should affect labor market choices. The model explains that sexual harassment creates gender segregation by operating as a wedge in the payoff from jobs in gender-imbalanced workplaces. All else equal, women get a lower total compensation in male-dominated workplaces, and vice versa for men in female-dominated ones. This will create gender segregation as both women and men have smaller incentives to become a workplace gender minority. It will also create a larger gender wage gap by channeling women into lower-paying workplaces and men toward higher-paying ones.

Harassment Risks and Pay Across Workplaces

To empirically assess how harassment risks vary across workplaces, Folke and Rickne (2022) use survey data on self-reported sexual harassment from the Swedish government’s biannual survey on work conditions (N=40,000). This nationally representative survey contains questions on unwanted sexual advances, sexist hostility, and gender harassment from colleagues or managers in the last 12 months. The survey data can be linked to administrative data on the full Swedish workforce, enabling the computation of the share of men in each survey respondent’s occupation and workplace.

The relationship between self-reported harassment and sex ratios is shown in Figure 1. Clearly, both women and men self-report more harassment when they are the gender-minority in their workplace. The higher self-reported rate of harassment among gender minorities is not caused by systematically different demographic traits. Nor is it caused by gender minorities being more likely to have opposite-sex supervisors, or to themselves hold subordinate or supervisory positions, or by them having opposite-sex managers. Folke and Rickne (2025) show that these patterns also hold at the occupation level.

Figure 1. Sexual Harassment Incidence across Workplace Sex Ratios.

Source: Replication of the left-hand side of Figure II in Folke and Rickne (2022). Note: The figure shows binned averages of a binary variable for self-reports of sexual harassment in the last 12 months from colleagues or managers. Each sub-sample of men and women is split into 100 equally sized bins of the X-variable. N=19,975 for women, and 17,482 for men.

To examine how wages relate to sex composition, Folke and Rickne (2022) rely on the empirical framework developed by Abowd et al. (1999). This framework estimates workplace fixed effects in a wage regression that also includes individual fixed effects and a host of occupational and demographic controls. The workplace fixed effects (i.e., the wage premiums) capture how much a workplace pays in wages compared to other workplaces with the same occupation structure and workers’ socio-economic traits. The analysis shows that a 10-percentage-point larger share of men is, on average, associated with a 1-percentage-point higher wage premium.

To summarize the first set of results, male-dominated workplaces pay more. At the same time, both men and women face a higher risk of sexual harassment when they work in an occupation or workplace with more men. The combination of these results suggests that women have an incentive to work in lower-paying jobs, while men have an additional incentive to work in high-paying jobs.

Sexual Harassment and Job Choice

Sexual harassment can affect job choice in two ways: it can deter an individual from taking a job, or make a person leave a job that they have previously chosen. Folke and Rickne (2022) examine both these channels.

To examine if sexual harassment risks deter individuals from taking a job, Folke and Rickne (2022) use a survey experiment sent to ~4,000 employed Swedish citizens. The survey experiment follows the standard economic approach of exposing respondents to a hypothetical job choice experiment where they choose between fictional job offers with randomized wages and work conditions (for prominent examples of this approach, see, for example, Wiswall and Zafar 2017 and Mas and Pallais 2017).

Sexual harassment was incorporated into the experiment by showing respondents vignettes of sexual harassment incidents that took place in fictional workplaces (as in Hulin, Fitzgerald, and Drasgow 1996). These vignettes mimic the types of anecdotes or rumors that a prospective employee might hear about a potential employer. Importantly, the vignettes make it possible to vary the victim’s gender, which allows comparison of job choices among respondents who are exposed to a harassment victim of their own gender and respondents exposed to a victim of the opposite gender.

The experiment showed a large negative valuation of sexual harassment—the equivalent of a 10% lower wage in the full sample. This large valuation makes sexual harassment a relevant work condition for shaping people’s total remuneration from work and is quantitatively similar to the valuations of time/space flexibility in previous research (Wiswall and Zafar 2017; Mas and Pallais 2017; Maestas et al. 2018). While men and women had similar valuations, there was a substantial difference between those who see a victim of their own sex compared to the opposite sex: the negative valuation is equivalent to a 17% lower wage for same-sex victims but just 6% for opposite-sex ones.

Figure 2. Event Study of Workplace Transitions.

Source: Replication of Figure V in Folke and Rickne (2022). Note: The figure shows estimated differences in the proportion of employer-to-employer transitions out of the workplace in the Work Environment Survey between people who self-report sexual harassment in that survey or not. The X-axis denotes the number of years since the survey. Demographics controls from administrative records are four dummies for marital and parental status, four dummies for age categories, two dummies for having secondary or tertiary education, and two dummies for being born in a different European country or outside Europe.

Folke and Rickne (2022) rely on the work-environment survey matched to the administrative data to show that sexual harassment also affects the probability of leaving a workplace. Conditional on a host of controls, women who report sexual harassment are about 5 percentage points more likely to have left their workplace 3 years after having answered the survey than women who did not report sexual harassment. The equivalent gap for men was about 3 percentage points.

Conclusions

The case study of sexual harassment in Sweden highlights this work condition as an important barrier to gender equality in the labor market. It shows a higher prevalence of sexual harassment for workplace gender minorities and how it imposes costs on these minorities relative to their gender majority colleagues. The disincentive created by sexual harassment to become—and remain—a workplace gender minority reinforces gender segregation across workplaces. The gender wage gap also grows as women prefer not enter male-dominated workplaces with higher pay, or leave these workplaces and head to ones with more women and lower monetary compensation.  These macroeconomic impacts add to the “business case” for governments to prevent sexual harassment.

Sexual harassment is just one of many forms of discrimination in work conditions that could reinforce inequalities in the labor market. If we want to reduce gender inequality, it is clearly not enough to focus on gender differences in preferences for work conditions. We also need to pay attention to factors, such as sexual harassment, that lead to men and women facing different work conditions in the same job. Addressing this form of discrimination could not only yield large payoffs for individual well-being but also reduce inequalities in the labor market.

References

  • Abowd, J.M., Kramarz, F. and Margolis, D.N., 1999. High wage workers and high wage firms. Econometrica, 67(2), pp.251-333.
  • Folke, O. and Rickne, J., 2022. Sexual harassment and gender inequality in the labor market. The Quarterly Journal of Economics, 137(4), pp.2163-2212.
  • Folke, O., & Rickne, J. (2025). Sexual harassment across occupations: new evidence from Swedish Nationally representative data. European Sociological Review, 41(6), 903-918.
  • Collis, M.R. and Van Effenterre, C., 2025. Workplace Hostility. IZA-Institute of Labor Economics.
  • Goldin, C. (2014). A grand gender convergence: Its last chapter. American Economic Review, 104(4): 1091-1119.
  • Hulin, C.L., Fitzgerald, L.F. and Drasgow, F., 1996. Organizational influences on sexual harassment. Sage Publications, Inc.
  • Le Barbanchon, T., Rathelot, R. and Roulet, A., 2021. Gender differences in job search: Trading off commute against wage. The Quarterly Journal of Economics, 136(1), pp.381-426.
  • Lepage, L.P., Li, X. and Zafar, B., 2025. Anticipated discrimination and major choice (No. w33680). National Bureau of Economic Research
  • Maestas, N., Mullen, K.J., Powell, D., Von Wachter, T. and Wenger, J.B., 2023. The value of working conditions in the United States and implications for the structure of wages. American Economic Review, 113(7), pp.2007-2047.
  • Mas, A, and A Pallais (2017), “Valuing Alternative Work Arrangements”, American Economic Review, 107(12): 3722–3759.
  • Penner, A.M., Petersen, T., Hermansen, A.S., Rainey, A., Boza, I., Elvira, M.M., Godechot, O., Hällsten, M., Henriksen, L.F., Hou, F. and Mrčela, A.K., 2023. Within-job gender pay inequality in 15 countries. Nature human behaviour, 7(2), pp.184-189.
  • Wiswall, M. & Zafar, B. (2017). Preference for the workplace, investment in human capital, and gender. The Quarterly Journal of Economics 133(1): 457-507.

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.

Do Election Results Shape Legitimacy Perceptions in Autocracy?

Elections remain a central feature of many authoritarian regimes despite widespread manipulation and limited political competition. Using a survey experiment with a nationally representative sample of Russian voters, this study examines whether improving perceptions of legitimacy can help explain why autocrats hold elections. The results show that information about high turnout increases trust in government, while information about low turnout reduces it, with effects driven by government supporters and individuals who believe in election integrity. This suggests that authoritarian leaders may use elections and reported electoral outcomes strategically to reinforce legitimacy among their support base and manage public perceptions over time.

Puzzle of Autocratic Elections

In recent decades, many authoritarian regimes have increasingly adopted institutions resembling those of democracies, particularly elections (Guriev and Treisman, 2019). Autocrats often organize multiparty elections and invite international observers, even as they manipulate outcomes through widespread fraud. This combination raises an important puzzle: if elections do not truly determine political power, why do authoritarian leaders hold them?

A large body of research has examined how authoritarian elections are organized (Gandhi and Lust-Okar, 2009; Gehlbach et al., 2016; Egorov and Sonin, 2020), including strategies such as limiting competition (Gandhi and Przeworski, 2007; Egorov and Sonin, 2021), managing media and information (Egorov et al., 2009; Edmond, 2013), and using elections to signal regime strength or monitor elites (Gehlbach and Simpser, 2015). However, less is known about whether these elections actually shape voters’ perceptions of government legitimacy (Dukalskis and Gerschewski, 2017).

One seemingly straightforward way to approach this question is to look at the relationship between electoral participation and trust in government, a key measure of political legitimacy. For example, across OECD countries, higher turnout is strongly correlated with greater trust in national governments (Figure 1). However, this descriptive pattern does not establish causality. Economic conditions may simultaneously shape both trust and electoral outcomes, creating omitted variable bias, while legitimacy itself may influence participation, leading to reverse causality.

These limitations point to the need for causal evidence on whether election results influence perceptions of legitimacy, particularly in non-democratic settings. The importance of such evidence is underscored by recent policy interest, including a commissioned report for the European Parliament on authoritarian legitimation through elections (Demmelhuber and Youngs, 2023). This policy brief presents findings from a recent study that addresses this issue, using a Russian election as a case study.

Figure 1. Trust in government and voter turnout in parliamentary elections in OECD countries (2017-2020)

Note: Trust is measured as a percentage of the population over 15 years old who answered ”Yes” to the following question in a nationally representative survey: “In this country, do you have confidence in the national government?” (Source: OECD). Turnout is the percentage of the registered voting population who voted in the last parliamentary election (Source: IDEA). Countries with compulsory voting are excluded.

Survey Experiment

To causally assess whether reported election outcomes influence perceptions of government legitimacy, the study implemented a survey experiment using a nationally representative sample of 1,603 Russian voters. The central feature of the design was a randomized information treatment that generated exogenous variation in respondents’ exposure to election results.

After completing the initial socio-demographic questions, respondents reported their prior political participation as well as their recollections of how past elections were conducted and their outcomes. Respondents were then randomly assigned to one of five treatment arms and asked to evaluate a hypothetical government formed after an upcoming election, with information about the election outcome randomly varied across treatment arms.

A control group received no information about hypothetical election results. Two groups were informed only about hypothetical voter turnout, which was presented as either low (38%) or high (66%). Two additional groups received information about turnout, either low or high, combined with a high vote share for the leading party (72%).

Following the information treatment, respondents reported their levels of trust in government, perceptions of whether the government represented national and personal interests, and their approval of and willingness to comply with hypothetical laws. These outcomes served as proxies for different dimensions of political legitimacy.

Election Outcomes Shape Trust in Government – but Only for Incumbent Supporters

By comparing responses across treatment groups, the experiment isolated the causal impact of election outcomes on legitimacy perceptions while holding constant respondents’ other characteristics. Respondents exposed to information about low turnout express significantly lower trust in government compared to those who received no information. On average, low turnout reduces trust by approximately 0.77 points on a ten-point scale, equivalent to about 0.25 standard deviations. In contrast, exposure to high turnout increases trust by around 0.68 points, or 0.22 standard deviations.

Providing additional information about the ruling party’s vote share does not significantly alter these effects. When high vote share information was combined with low turnout, trust increased slightly by 0.07 points, while adding vote share information to high turnout reduced trust by about 0.40 points; neither difference is statistically significant.

The impact of turnout information is highly heterogeneous. The observed effects are driven by individuals who expressed support for the ruling party, United Russia. Among these respondents, low turnout substantially lowers trust, while high turnout leads to a significant increase in trust. In contrast, opposition supporters do not update their perceptions in response to any of the information treatments: their trust levels remain statistically indistinguishable from those of the control group.

Moreover, the study examines heterogeneity based on baseline perceptions of electoral fraud. Before administering the information treatments, respondents were asked how frequently they believed irregularities in vote counting occur in Russian elections. Individuals who reported frequent violations are likely to view election outcomes as non-transparent and therefore to distrust official results, suggesting that information about turnout and vote share should have limited impact on their perceptions. Consistent with this expectation, no significant effect of turnout information on trust in government is observed among respondents who report a higher frequency of such violations.

Figure 2. Effect of information on trust relative to the control group

Note: This plot shows the effects of information treatments on trust in government relative to receiving no information (control group). Black circles are coefficient estimates for each group, with horizontal lines showing 95% confidence intervals.

Mechanisms: Expectation Shock and Anchoring

To examine how election information affects perceived legitimacy, the study relies on respondents’ reported recollections of past election results, including turnout and leading party performance. These prior beliefs provide a baseline against which new information is interpreted, as respondents tend to anchor their expectations about future elections to what they remember from previous ones.

When information about hypothetical election outcomes is presented, it generates exogenous shocks to these expectations. The magnitude and direction of each shock is defined as the difference between a respondent’s prior belief and the reported hypothetical outcome. By varying turnout between low and high values and combining turnout with high ruling party results, the experiment produced both positive and negative expectation shocks.

The results indicate that positive shocks, when the reported turnout exceeds prior beliefs, increase legitimacy across treatment groups, while negative shocks, when reported turnout is below the expected one, decrease legitimacy regardless of the treatment arm.

These findings suggest that election outcomes shape legitimacy by generating expectation shocks, and that respondents anchor beliefs about future elections to their perceptions of past results; in the absence of such anchoring, deviations between reported outcomes and respondents’ priors would have had little effect.

However, in the case of the leading party’s vote share, the resulting shock was rather small: an average respondent reported recalling the past vote share as 65%, while the value used in the information treatments was 72%. If respondents indeed anchor expectations about future election outcomes to past results, this may explain the absence of an additional effect of the vote share information, as the treatment did not generate a sufficiently strong expectation shock.

Conclusion

Do election results affect an autocrat’s perceived legitimacy? Using a survey experiment with a nationally representative sample of Russian voters, this study provides evidence that information about election outcomes can shape trust in government in an authoritarian setting. The results show that exposure to high (low) voter turnout increases (decreases) trust in government, with these effects concentrated among government supporters and individuals who believe elections are generally fair. This pattern suggests that autocrats may have limited ability to influence opposition supporters and instead rely on reinforcing legitimacy within their existing support base.

In addition, because voters anchor their expectations to past results, autocrats may be incentivized to generate higher outcomes while exercising caution in revealing lower ones in future elections. This underscores the role of autocratic elections as a tool to manage public perceptions over time.

The results of this study show that information about election outcomes holds strategic significance in non-democracies, as it can shape perceptions of government legitimacy. Policymakers should therefore prioritize support for independent media that provide credible information about election outcomes, even when results in authoritarian contexts appear predictable.

References

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.

Do Remittances Keep Households Out of Poverty? Evidence from Georgia

Remittances play an important role in household living standards in Georgia, alongside labor income and public transfers. Using 2024 household data, this brief estimates the contribution of remittances to poverty reduction by simulating household welfare in their absence. The results indicate that removing remittance income would raise the share of households below the subsistence level by more than four percentage points, with smaller increases in relative poverty and inequality. Income composition patterns further show that poorer and rural households rely more heavily on remittances. Overall, the findings underscore the significant role of private transfers in shaping household welfare and vulnerability in Georgia.

Introduction

Despite notable progress in recent years, poverty reduction remains a central development challenge in Georgia. An important policy concern is whether recent poverty reductions are sustainable or leave households vulnerable to economic shocks.

Assessing this vulnerability requires understanding what keeps households above the poverty line. In Georgia, household consumption is financed not only by labor earnings but also by non-labor income sources. Many households rely heavily on remittances from family members working abroad as well as public transfers such as pensions and social assistance.

While official poverty indicators track overall trends in household welfare, they do not reveal how different income sources contribute to keeping households above the poverty line. Understanding whether poverty reduction is primarily driven by labor income, private transfers, or public support is essential for assessing household vulnerability and the sustainability of poverty reduction.

This question is especially salient in Georgia, where remittance inflows amounted to around 10 percent of GDP in 2024. Such dependence raises concerns about the resilience of household welfare to external shocks that could disrupt migration or remittance flows.

Recent World Bank analysis of fiscal incidence in Georgia highlights that transfers and social expenditures have played a significant role in reducing poverty and inequality, with overall taxes and benefits lowering the share of the population in poverty and compressing the distribution of income (World Bank, 2025). Evidence from studies on international migration and remittances also suggests that private transfers help smooth household consumption and provide critical support to low-income families in contexts with high migration and remittance flows (World Bank, 2023).

Building on this body of evidence, this brief quantifies the short-run welfare impact of remittances in Georgia by simulating household consumption in the absence of remittance income. Comparing observed outcomes with the counterfactual scenario provides clear evidence on the contribution of private transfers to household living standards and the vulnerability of households to changes in remittance flows.

Descriptive Statistics

Household incomes in Georgia are composed of labor earnings, public transfers, and private transfers. Labor and market income, including wages, self-employment, and agricultural sales, accounts for roughly two-thirds of total household resources on average. Transfers nonetheless play a substantial role in household welfare: public transfers such as pensions and social assistance represent over one-fifth of total income, while private transfers, largely driven by remittances from abroad, contribute more than one-tenth. Capital and other income sources remain marginal. In level terms, average monthly cash income and transfers amount to GEL 1,714 per household but fall to GEL 971 among households below the subsistence minimum and rise to GEL 1,814 among those above it. Rural households report lower average cash resources (GEL 1,434) than urban households (GEL 1,877), underscoring both welfare gaps and the differing reliance on income sources across population groups.

Figure 1. Income composition by source and household group

Source: Household Incomes and Expenditures survey, Geostat, 2024.

Income composition differs markedly across household groups, indicating that transfer flows play a particularly important role for households at the lower end of the welfare distribution and in rural areas. Among households below the subsistence minimum, public transfers account for nearly half of total cash resources – roughly equal to labor and market income – highlighting a strong reliance on transfer income for meeting basic living standards. In contrast, households above the subsistence minimum derive over two-thirds of their income from labor earnings, with transfers playing a much smaller role. Rural households are also substantially more dependent on public transfers than urban households, where labor income dominates. Private transfers, largely driven by remittances, constitute a meaningful but secondary income source, particularly among urban and better-off households.

Data and Methodology

The analysis uses microdata from Georgia’s Integrated Household Survey (IHS) for 2024. Household welfare is measured using total consumption expenditure per equivalent adult, which is widely regarded as a reliable indicator of living standards than income, as it better reflects households’ ability to smooth temporary income fluctuations. All results are weighted using survey weights adjusted for household size to reflect population-level outcomes.

Absolute poverty is assessed using the national subsistence level, which varies by quarter to account for seasonal price changes. Relative poverty is defined as consumption expenditure below 60 percent of the median within each quarter. Inequality is measured using the Gini coefficient, and Lorenz curves are used to illustrate changes in the consumption distribution.

To quantify the role of remittances, a counterfactual welfare scenario is constructed by simulating household consumption in the absence of remittance income from abroad. The simulation subtracts the estimated consumption-financed portion of remittances from observed household consumption, while allowing for the share of remittances saved or used for non-consumption purposes. Poverty and inequality indicators are then recalculated under this counterfactual scenario. The approach captures the short-run direct impact of remittances.

As with any short-run simulations, this analysis assumes no behavioral adjustment by households following the removal of remittance income. In practice, households may respond through changes in labor supply, borrowing, or expenditure patterns, which are not captured. In addition, the estimation of the consumption-financed share of remittances is based on observed saving behavior and may vary across households and over time. Despite these limitations, the approach provides a transparent and relevant estimate of the direct welfare role of remittances.

Results

Remittances from abroad play a substantial role in sustaining household living standards in Georgia. In 2024, 13.7 percent of households lived below the subsistence minimum. Simulating household welfare in the absence of remittance income shows that the poverty rate would rise to 18.1 percent, an increase of more than four percentage points. This implies that remittance inflows keep a significant share of households above the minimum living standard threshold.

Table 1. Poverty and inequality indicators with and without remittance income

Source: Author’s calculations based on Geostat data, 2024. Note: The Gini coefficient is a numerical measure of income or wealth inequality that summarizes how evenly income or wealth is distributed across a population. It ranges from 0, indicating perfect equality where everyone has the same income or wealth, to 100, indicating perfect inequality where all income or wealth is concentrated in a single individual.

Relative poverty also increases in the counterfactual scenario, rising from 18.7 to 21.4 percent, though the magnitude is smaller than for absolute poverty. This reflects the stronger role of remittances in preventing extreme vulnerability rather than reshaping the overall income distribution.

Inequality, measured by the Gini coefficient of consumption expenditure, increases modestly from 32.4 to 32.8 in the absence of remittances. The corresponding shift in the Lorenz curve confirms that remittances slightly compress the lower tail of the distribution, benefiting poorer households disproportionately.

Figure 2. Lorenz curves with and without remittances

Source: Author’s calculations based on Geostat data, 2024. Note: A Lorenz curve is a graphical representation of income or wealth distribution that plots the cumulative share of the population (ordered from poorest to richest) against the cumulative share of total income or wealth they receive, illustrating the degree of inequality in a society.

Conclusion

The results indicate that remittances from abroad play a substantial role in sustaining household living standards in Georgia.  In  2024,  removing remittance income would increase the share of households living below the subsistence minimum by more than four percentage points, with a smaller but noticeable rise in relative poverty. The persistence of this pattern under both absolute and relative poverty definitions confirms the robust poverty-reducing role of remittances. Inequality, measured by the Gini coefficient, also increases modestly in the counterfactual scenario, consistent with remittances disproportionately supporting lower-income households.

Income composition patterns further show that poorer and rural households rely more heavily on transfer income than better-off and urban households, underscoring the importance of remittances as a buffer against economic vulnerability. Overall, the findings highlight the significant contribution of private transfers to poverty reduction and the sensitivity of household welfare to changes in remittance flows.

As reliance on external income sources remains high, diversifying income opportunities and improving domestic labor market conditions will be essential for sustainable poverty reduction in the long term.

References

  • World Bank, 2023. Migrants, Refugees, and Societies.
  • World Bank, 2025. Navigating Fiscal Realities for Equitable Growth in Georgia

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.

Strategic Integration of the Belarusian Business and Policy Implications for the EU

The forced internationalization of Belarusian businesses since 2020 has transformed a localized economic crisis into the formation of a sophisticated, high-growth-potential economic diaspora within the European Union. Drawing on a novel survey of over 114 Belarusian-rooted businesses, this brief analyzes their integration patterns and value alignment with Western markets. The findings reveal a cohort characterized by high entrepreneurial orientation, a rejection of state paternalism, and significant growth potential. This makes them a valuable asset to host-country development and a vital resource for Belarus’s future economic reconstruction.

The Context: Scale and Scope of the Exodus

Before 2020, Belarusian business migration was a predominantly economically driven phenomenon of “gradual Europeanization” – businesses strategically pursued access to larger markets, more stable legal frameworks, and new technologies. Moreover, many Belarusian companies were born-globals (Vissak & Zhang, 2016) and considered the domestic and even Russian market as a launch pad for further expansion into developed technological markets (Marozau et al., 2021). By 2020, the private sector’s contribution to Belarus’s GDP reached 55%, surpassing that of state enterprises (Daneyko et al., 2020). However, the political crisis following the 2020 elections and the 2022 invasion of Ukraine fundamentally altered this trajectory, turning migration into a “survival strategy”.

This “forced internationalization” occurred in two distinct waves. The 2020-2021 wave primarily consisted of individual entrepreneurs, top managers, and IT specialists who fled direct political repression. In turn, the post-2022 wave was driven by the relocation of entire high-tech and knowledge-intensive companies in order to preserve client bases and financial access after international sanctions were imposed on Belarus following Russia’s invasion of Ukraine.

Today, the EU has inadvertently become the custodian of a substantial portion of Belarus’s future economic potential. Over 300,000 Belarusians have emigrated, with an estimated 87% of them holding higher education degrees—a dramatic “brain drain” for Belarus that translates into a “brain gain” for the EU (Lvovskiy et al., 2025).

Figure 1. Origin of surveyed Belarusian-rooted businesses

Source: Authors’ estimation.

The number of enterprises with Belarusian founders operating across Central and Eastern Europe is estimated at approximately 10,000 (Marozau & Danilchuk, 2024).

This study utilizes a mixed-methods approach, centered on a 2024 proprietary survey of 114 founders and executives of Belarusian-rooted businesses, primarily located in Poland and Lithuania. The sample covers micro- (62%), small- (30%), and medium enterprises across ICT (39%), services/trade (48%), and manufacturing (13%).

Portrait of the Belarusian Business Diaspora

The Belarusian business presence in the EU is characterized by heavy geographic concentration on the eastern flank (Poland, Lithuania, Latvia), though it shows signs of maturing into a global network.

Nearly half (49%) of the surveyed companies were new local startups that were established from scratch in the current primary jurisdiction (Figure 1). Meanwhile, relocated firms – those that operated in Belarus and have fully or partially moved – make up 42% of the sample. Only 6% continue to operate in Belarus while opening branches abroad. This distribution underscores a shift toward local entrepreneurial formation, suggesting that the diaspora is not merely transplanting existing structures but actively generating new ones. The nearly even presence of relocated and new local startup firms reflects a dual pathway: one of continuity and adaptation, and another of innovation and reinvention.

Analysis of workforce composition reveals a heavy reliance on Belarusian talent, both from recent relocations and the existing local diaspora (Figure 2). Many businesses are still relatively small and founder-driven, with hiring networks often rooted in trusted Belarusian professional circles. However, as these companies grow and mature, many may begin to prioritize specialized skills and experience over nationality, leading to more diverse and internationalized teams over time. In their current phase, however, they continue to play a crucial role in employing and integrating Belarusian talent across EU labor markets (Lvovskiy et al., 2025).

Figure 2. Staff composition of surveyed Belarusian-rooted businesses

Source: Authors’ estimation.

Business Dynamics and Resilience

Despite the trauma of forced relocation, these businesses exhibit a remarkably entrepreneurial orientation and a focus on expansion rather than mere survival. An overwhelming 74% of firms prioritize expansion, a stark contrast to businesses remaining inside Belarus, where only about one-quarter plan to expand (BEROC, 2023). 64% of respondents anticipate increasing their staff over the next year. While they initially provide a “safety net” for other Belarusian emigrants, 40% of firms are now actively recruiting local Polish or Lithuanian specialists to help with localization.

Only 18% of firms would consider moving back to Belarus even if the political situation changed immediately. This indicates that the “exodus” has resulted in a permanent structural change; these businesses are becoming European entities with Belarusian roots.

Navigating the European Market: Challenges, Responses, and Support Needs

As the Belarusian-rooted business becomes more established in new countries, issues of initial adaptation and legalization are becoming a thing of the past.

The most frequently reported barrier is difficulty entering new markets, selected by 39% of respondents (Figure 3). This is followed by high labor costs, particularly in terms of salary expectations (30%), and disparities in treatment of companies with Belarusian origins (29%). These three factors reflect a combination of structural and perception-based challenges that affect firms’ ability to scale operations across borders.

Figure 3. Key barriers hindering growth and expansion

Source: Authors’ estimation.

A substantial share of firms, citing a lack of qualified personnel or management (25%) and noting difficulties related to the legalization of founders and employees (23%), point to significant constraints in human capital and the administrative burdens associated with cross-border employment and residency requirements.

Meanwhile, Belarusian entrepreneurs have shown a high entrepreneurial orientation, focusing on two main strategic directions: optimization of internal processes and adaptation of product/market strategy (Figure 4).

Figure 4. Steps taken to minimize the impact of risks and enhance competitiveness

Source: Authors’ estimation. Note: Several options could be selected.

When asked what would most help the company’s development, Belarusian entrepreneurs in the EU expressed a strong consensus that political and legal normalization is far more relevant than immediate economic aid or market-specific support. The end of the war in Ukraine (58.8%) as the highest-ranked factor underscores that the geopolitical instability caused by the war is the single largest drag on their business, impacting everything from security to market perception (Figure 5).

Figure 5. What would most help business development?

Source: Authors’ estimation. Note: Several options could be selected.

The Analysis of Value Alignment

In general, previous research collectively positions the entrepreneurial class – and by extension, the business diaspora – as a proactive, motivated, and democratically aligned segment of Belarusian society (Bornukova & Friedrich, 2021). The combination of a long-term societal shift toward market principles (Daneyko et al., 2023) and the unique psychological profile of Belarusian entrepreneurs has profound political implications. Their strong preference for self-reliance over state welfare, their belief in the benefits of competition, and their demonstrated risk tolerance are not merely business characteristics; they are foundational democratic values centered on individual agency and responsibility (Audretsch & Moog, 2022).

Compared to a survey of businesses inside Belarus in 2018, the 2024 the Belarusian business diaspora operating outside the country holds a stronger commitment to self-reliance, risk-taking, and core market principles than business representatives operating inside Belarus just a few years earlier (Marozau & Apanasovich, 2026). It strongly supports free pricing, the end of subsidies to uncompetitive firms, and rejection of economic paternalism (e.g., guaranteed jobs over higher salaries) (Figure 6). This alignment means that the diaspora has internalized the “European” institutional mindset, making them natural partners for EU economic initiatives and the primary “agents of transformation” for a future democratic Belarus.

Moreover, the shared experience of forced migration, combined with the resilience and adaptability of Belarusian entrepreneurs (Marozau, 2023), has fostered collaboration and ecosystem-building across Poland and the Baltic states. This commitment to market principles is evident in the rapid emergence of Belarusian business associations and informal networks across the EU (Krasko & Daneyko, 2022). While such spontaneous civil society development is atypical for Belarus, it aligns closely with the EU’s decentralized business environment (Greenwood, 2002). In contrast to post-2020 Belarus, where the state restricts independent business organizations and advocacy (Marozau, 2023), the diaspora has quickly formed self-governing, trust-based networks. These organizations substitute for weak institutional trust at home, mitigate geopolitical risks,   and   provide   advocacy,   networking,   and representation to host-country and EU institutions (Marozau & Danilchuk, 2024), demonstrating the diaspora’s capacity for democratic self-organization.

Source: Marozau & Apanasovich (2026)

Conclusion and Implications

The relocation of Belarusian entrepreneurs to the EU does not represent a break with the past so much as a fulfillment of long-standing aspirations, but these values appear to have developed before, often in defiance of a more centralized and restrictive policy environment in Belarus. Consequently, success abroad is based on the entrepreneurial principles already cultivated under challenging conditions and is not merely the result of adapting to new institutional settings. Strong alignment with liberal market values – including private ownership, individual initiative, fair competition, and transparent governance – positions Belarusian entrepreneurs as a foundational pillar of a future democratic Belarus integrated into the European family. Therefore, supporting this diaspora is not merely a question of solidarity or migration management. It is a high-return strategic investment that strengthens the EU’s economic base, supports democratic transition in its neighborhood, and affirms the values that underpin the Union itself. Tailored interventions are needed to address their legal vulnerabilities and enable their full participation in EU markets.

To unlock the full value of this asset for regional growth and long-term transformation, a strategic recalibration of policy is needed.

First, the Belarusian business diaspora should be understood as a distinct and underutilized contributor to the European economy—shaped by geopolitical disruption yet strongly aligned with EU market norms and integration pathways. The barriers these businesses face are not typical SME challenges but structural frictions that limit investment, scaling, and value creation in host countries. Addressing these frictions would deliver direct benefits to local economies through job creation, tax revenues, and industrial capacity. Fuller market participation could be supported through trust-building within local business ecosystems, consistent access to finance, greater legal predictability for founders and key staff, and appropriate risk-sharing instruments for capital-intensive sectors such as manufacturing. In parallel, regulatory clarity enabling banks to distinguish between sanctioned or state-linked entities and independent Belarusian firms would reduce unnecessary de-risking that suppresses legitimate economic activity within the EU.

Second, the Belarusian business diaspora represents a strategic asset for the future economic and democratic reconstruction of Belarus, whose value depends on being anchored and strengthened within the EU today. Operating in European markets allows these entrepreneurs to accumulate capital, managerial experience, institutional trust, and familiarity with EU regulatory and governance standards – assets that will be critical in a post-authoritarian transition. Retaining this community within the European economic space ensures that future reconstruction efforts can draw on actors already embedded in EU value chains, rather than relying solely on external assistance or ad hoc capacity-building.

Targeted funding mechanisms and professional networks can support this long-term role by enabling transparent links with the remaining private sector in Belarus, preserving skills, business relationships, and market knowledge that would otherwise erode over time. Finally, cross-sectoral initiatives involving entrepreneurs, civil society, and democratic actors can strengthen diaspora cohesion and amplify its contribution as a carrier of economic know-how and democratic practices. Joint efforts around education, skills development, and employability are particularly valuable, as they address EU labor market needs while preparing the groundwork for Belarus’s eventual reintegration into the European economic and institutional space.

References

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.