Tag: Income Inequality
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.
Income Polarization and Climate Policy Backlash
A recurring challenge for climate policy is political backlash. Over the last decade, we have seen prominent examples like the repeal of the carbon tax in Australia in 2014, the ‘Yellow Vests’ protest against the French carbon tax between 2018 and 2020, and the rollback of climate policy in the transport sector in Sweden between 2022 and 2024. A common argument put forward to explain this backlash is distributional concerns – that carbon and fuel taxes are regressive, disproportionately burdening low-income households. Yet, these prominent episodes often look like middle-class revolts. Studies find that the Yellow Vests supporters in France had ‘modest incomes’, but few came from the poorest deciles of the income distribution. Similarly, a study of Swedish fuel tax protesters found that they had relatively high incomes. This brief proposes a complementary explanation to regressivity: when the income distribution becomes more polarized – with stronger growth at both tails relative to the middle – the tax burden can shift toward the middle. A simple three-agent example illustrates how polarization can ‘squeeze’ the middle class, potentially undermining the durability of climate policy even when the poorest are compensated.
Climate Policy Backlash: Why “Not Just the Poor”?
Fuel and carbon taxes have repeatedly triggered political controversy and, in some cases, reversals. In France, the planned 2018 increase in the carbon tax became a focal point of the Yellow Vests protests. In Australia, the economy-wide carbon pricing introduced in 2012 was repealed just two years later. And in Sweden, the current government has reduced transport fuel taxes and the biofuel mandate to lower pump prices.
These episodes are often interpreted through the lens of tax progressivity (Douanne and Fabre 2022; Ewald et al. 2022): if energy and transport fuels are necessities, the tax-to-income burden can be higher for low-income households, with implications for policy stability. But the political patterns are frequently more complex. In France, many protesters were working or middle-class rather than poor (Dormagen et al. 2022). In Sweden, fuel tax protesters had, on average, relatively high incomes (Ewald et al. 2022), and households in the bottom third of the income distribution have no transport fuel expenditure at all, which weakens a simple “regressivity” narrative.
Figure 1. Share of Swedish households with zero transport fuel expenditure, by income decile.

Source: Household expenditure survey data 1999-2012 from Statistics Sweden.
This motivates the question: what if the distributional conflict that matters politically is not only bottom-versus-top, but, more importantly, concerns what happens to the middle class?
This brief introduces a three-agent model to show that under income polarization, the relative tax burden may shift to the middle. Traditional tax progressivity indices may fail to capture this shift as they weight different parts of the income distribution. At the same time, such a change is likely to have large implications for the political action and ultimately, the environmental policy design.
A Simple Model of Tax Burden Shifts
Consider an economy with three types of households: low-income (L), middle-income (M), and high-income (H). When a good like gasoline is taxed at a constant rate, each household’s tax burden depends on how much of their budget they spend on the taxed good; their ‘budget share.’
As incomes grow over time, these budget shares change. The direction of change depends on whether the taxed good is a necessity or a luxury. For necessities — goods where spending doesn’t keep pace with income growth — the budget share falls as income rises. For luxuries, the opposite occurs. The speed at which budget shares change over time is thus governed by two factors: how responsive spending is to income changes (the income elasticity), and each household’s income growth rate.
To track how tax burdens shift between different income groups, we can examine the relative changes in their budget shares. With three income groups, we need to make three comparisons: poor versus rich, poor versus middle, and middle versus rich. If the budget share falls faster for the relatively richer household in all three comparisons, the tax becomes more regressive. If it falls faster for the relatively poorer in all three comparisons, the tax becomes more progressive.
However, a third pattern is possible: the burden can shift in a ‘polarized’ way, where the middle class loses ground relative to both the poor and the rich. In this case, whether the tax is progressive or regressive is ambiguous – it depends on which comparison we prioritize in our social welfare function.
Polarization Squeezes the Middle
We use the example of income polarization to illustrate how this middle-squeeze can occur. Following Esteban and Ray (1994) and Wolfson (1994), we define income polarization as a situation where the middle group’s income grows more slowly than both the bottom and top groups. Under polarization, the middle class shrinks as a share of total income, while both the poor and rich expand their shares. Such income polarization has been well documented in the US and Europe (e.g., Goos et al. 2009; Autor 2022).
Table 1 shows a stylized numerical example of income polarization. Low- and high-income households have higher income growth compared to the middle, whose income share shrinks. Furthermore, gasoline is a necessity (in high-income countries), and we assume uniform income elasticities so that the budget share declines as income grows for all three income groups.
Table 1: Example of income polarization

What happens to relative tax burdens under these conditions? Because low-income households have the fastest income growth, their gasoline budget share falls the quickest. The middle class, with much slower income growth, sees its budget share fall more slowly. This means the middle class shoulders more of the tax burden relative to the poor.
Similarly, high-income households also experience faster income growth than the middle class, so their budget share also falls faster. Again, the middle class ends up shouldering more relative to the rich. The middle is thus ‘squeezed’ from both directions.
Importantly, when we compare the poor directly to the rich, the tax burden shifts in a progressive direction — the poor’s relative burden falls compared to the rich. Yet this ‘traditional’ progressive pattern masks the fact that the middle class is bearing an increasing share of the burden compared to everyone else.
The political implication is clear: when taxing a necessity under income polarization, the middle class can become relative losers even when the tax appears progressive in traditional comparisons between top and bottom. In this case, climate policy backlash would come from working and middle-class groups rather than the absolute poorest, and compensating mainly the poor may be insufficient for political durability.
What This Suggests for Climate policy design
The mechanism illustrated above does not deny that tax progressivity matters. Rather, it highlights an additional vulnerability: in a polarized economy, a carbon tax on necessities may face backlash when the middle class is squeezed. Three practical implications for climate policy design follow from this.
First, protecting the bottom is essential, but may not be sufficient for political durability if the middle becomes the relative ‘loser.’ The traditional focus in the economics literature on the political economy of climate policy and its potential distributional effects is on measures like revenue recycling (‘carbon dividends’) – especially to the poor – to counter regressivity. This compensation may be insufficient for policy stability, however, and targeted measures toward the middle class may be needed (such as a reduction in middle-income tax rates).
Second, backlash may potentially be lower when there are credible substitutes, thereby reducing the budget share of the taxed goods over time. If, for instance, the middle-class are relatively more dependent on private transport, compensatory policies aimed at making electric vehicles more affordable may reduce both the objective burden and the intensity of climate policy aversion.
Third, summary indices of tax progressivity — like the Kakwani (1977) and Suits (1977) indices — may obscure ‘middle-squeeze’ patterns. A useful complement to these summary measures would thus be to report incidence separately for bottom–middle and middle–top comparisons, and to track how polarization changes these margins over time.
References
- Andersson, J. J., & Atkinson, G. (2025). The Progressivity of Gasoline Taxation: The Role of Income Inequality. Working Paper.
- Autor, D. (2022). The labor market impacts of technological change: From unbridled enthusiasm to qualified optimism to vast uncertainty. National Bureau of Economic Research.
- Dormagen, J-Y., & Michel, L., & Reungoat, E. (2022). United in diversity: Understanding what unites and what divides the Yellow Vests. French Politics, 20(3), 444–478.
- Douenne, T., & Fabre, A. (2022). Yellow vests, pessimistic beliefs, and carbon tax aversion. American Economic Journal: Economic Policy, 14(1): 81–110.
- Esteban, J.-M., & Ray, D. (1994). On the measurement of polarization. Econometrica, 62(4), 819–851.
- Ewald, J., & Sterner, T., & Sterner, E. (2022). Understanding the resistance to carbon taxes: Drivers and barriers among the general public and fuel-tax protesters. Resource and Energy Economics, 70.
- Goos, M., & Manning, A., & Salomons, A. (2009). Job polarization in Europe. American Economic Review, 99(2): 58-63.
- Kakwani, N. C. (1977). Measurement of tax progressivity: An international comparison. Economic Journal, 87(345), 71–80.
- Suits, D. B. (1977). Measurement of tax progressivity. American Economic Review, 67(4), 747–752.
- Wolfson, M. C. (1994). When inequalities diverge. American Economic Review, 84(2), 353–358.
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.
Inequality in Europe: The Role of EU Enlargement
A new study reveals that the 2004 enlargement of the European Union helped narrow inequality in Europe. Using data from the World Inequality Database, researchers found that Eastern European countries joining the EU saw strong income growth across all income groups. This growth reduced inequality across the bloc, even though some countries experienced rising gaps internally. The study was conducted by Jesper Roine of the Stockholm School of Economics and Svante Strömberg of Uppsala University.
The Divide Before Enlargement
Before 2004, inequality in Europe reflected a clear divide between richer northern and poorer southern nations. Eastern European countries outside the EU were still adjusting to the post-communist era, facing both rapid economic changes and widening income gaps.
How Enlargement Shifted the Balance
The 2004 expansion brought ten mainly Eastern European states into the EU. These countries experienced rapid income growth that reached both rich and poor households. In contrast, many older member states—especially in Southern Europe—saw stagnating or shrinking incomes for lower- and middle-income earners.
Key Research Findings
- New Eastern European members saw faster income growth than older EU states across all income levels.
- The poorest 50% of the EU population enjoyed annual growth three times higher than the top 10%.
- Many income groups in Southern Europe lost ground in the EU-wide income rankings.
- Overall inequality in Europe fell after enlargement, despite mixed trends within individual countries.
Implications for Future Growth
The findings suggest that future EU expansions—such as the possible accession of Ukraine, Moldova, and Georgia—could also reduce inequality in Europe if new members experience inclusive growth. However, continued stagnation in older members could deepen political divides.
Read the Full Peer-Reviewed Research Paper
Explore the complete findings and analysis by reading the full report in the International Tax and Public Finance journal.
Enhanced Access to Data Can Reduce the Gender Gap
On International Women’s Day, researchers from the FREE Network institutes released the policy brief “Closing the Gender Data Gap” to highlight the crucial role of data in addressing economic inequalities between women and men. The brief explores how improved data collection and access can help reduce the gender gap across labor markets, income, education, pensions, and caregiving responsibilities.
Why Better Data Matters for Gender Equality
In recent decades, progress in documenting historical developments and expanding access to new data sources has significantly improved our understanding of the different economic outcomes experienced by women and men. Today, researchers have deeper insights into:
- Labor market participation and outcomes
- Income levels and wealth accumulation
- Educational investments and pension systems
- Consumption and household decision-making
- Caregiving responsibilities and time use
These insights show that better data reduces the gender gap by revealing disparities and helping shape effective policy responses.
Key Findings
The policy brief emphasizes that to effectively design policies and strategies, data must be more accurate, comprehensive, and regularly updated. The researchers outline four critical recommendations:
- Increase access to digitized information – Governments and public institutions should make more administrative and statistical data available for research.
- Support funding for surveys – Combining survey data with administrative sources enhances both detail and reliability.
- Ensure regular data collection – Continuous monitoring allows researchers to measure the impact of major events such as legislation, conflicts, pandemics, or natural disasters.
- Leverage innovative data sources – Mobile apps, social media, and other digital platforms provide new perspectives on socio-economic trends and gender disparities.
About the Authors
The policy brief “Closing the Gender Data Gap” was authored by:
- Michal Myck (CenEA)
- Monika Oczkowska (CenEA)
- Pamela Campa (SITE)
- Maria Perrotta Berlin (SITE)
- Jesper Roine (SITE)
Media Contact
For press or media inquiries, please contact: Maria Perrotta Berlin, Professor at SITE, Phone: 0737332198, Email: Maria.Perrotta [at] hhs.se