
Carbon Pricing and Redistribution: A Microsimulation Analysis for Belgium
We simulate the distributional effects of a €45/tCO2 carbon price on Belgian households’ heating and transport fuels using microdata from the 2016 Household Budget Survey. Without compensation, the policy is regressive and increases energy poverty, with especially large burdens for singles, seniors, and households heating with oil. We compare three revenue-recycling designs: equal transfers per household, equal transfers per capita, and a fuel-type-differentiated scheme that provides larger supplements to fossil-heated households. Per-household recycling protects vulnerable households better than per-capita recycling, which tends to undercompensate small households. Differentiating transfers by heating fuel further reduces large losses and within-income-group dispersion, and it prevents an increase in energy poverty while preserving overall progressivity of the reform.
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Challenges in measuring subjective poverty: a policy application to Ecuador
Traditional monetary poverty metrics used in policy analysis have well-known limitations: small changes in thresholds or methodology can markedly alter who is counted as poor. Subjective poverty indicators—based on individuals’ own assessments—offer a complementary lens by capturing perceived deprivation.
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Decomposing Child Poverty Drivers using UKMOD and EUROMOD: A Comparative Analysis of the UK and selected European countries
This study investigates the drivers behind the divergent trends in child poverty between the UK and five European counterparts—Finland, Hungary, Ireland, Poland, and Spain—from 2011 to 2024. These countries were selected to represent a diverse spectrum of trajectories: Finland and Spain serve as references for persistently low and high rates, respectively, while Poland reports a significant reduction over the analysed period of time. The analysis further incorporates Hungary, which follows the UK’s experience of rising child poverty, and Ireland, which offers a divergent path despite sharing initial similarities with the UK. The analysis decomposes these trajectories into three core determinants: demographic differences, labour market dynamics, and tax-benefit systems. To capture differences due to demographic characteristics, we employ a coarsened exact matching and reweighting technique to generate synthetic populations. Differences in labour market dynamics are captured using four-stage statistical models (estimating the probability of employment, the probability of unemployment, hourly wages, and hours worked) based on counterfactual projections for employment and earnings in the UK that reflect labour market conditions in the comparator countries. Finally, the contribution of the tax-benefit system is isolated through a difference-in-differences (DiD) approach, comparing child poverty rates computed on original versus disposable incomes. This is facilitated by utilizing the static microsimulation models UKMOD and EUROMOD that allows to compute disposable incomes. By quantifying these components, we determine the extent to which demographic characteristics, labour market dynamics, or tax-benefit systems have driven the UK’s relative child poverty trends.
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Drivers of Income Inequality in Ireland and Northern Ireland
The distribution of income differs in Ireland and Northern Ireland. Differences in demographics, working patterns, wage levels and the tax-benefit system all contribute to these differences and could prove a barrier to increased co-operation on the Shared Island of Ireland. Using harmonised microsimulation models for Ireland (SWITCH) and Northern Ireland (UKMOD), we identify the drivers of the differences in income distribution between Ireland and Northern Ireland. Using a decomposition technique, we isolate the relative contributions of market income differences - attributable to demographics, labour market participation and wage levels - and the tax-benefit system to differences in income distribution in the two jurisdictions. In a final step, we simulate the implementation of the Irish tax-benefit system in Northern Ireland and vice versa. This exercise indicates the potential costs and distributional effect of harmonising the direct tax and welfare system across the two jurisdictions.
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Effectiveness of Minimum Income Support in Bulgaria: A Microsimulation Analysis of 2023 Reform of the Monthly Social Assistance Benefit
Over 15 years since the EU integration of Bulgaria an ambitious reform has been introduced in 2023 regarding the minimum income protection scheme operated within the social policy mix, namely the Monthly Social Assistance (MSA) benefit. The reform addressed European Council’s country specific recommendations (CSRs) to Bulgaria within the framework of the European Semester and had several ambitious goals, among which to improve benefit coverage, adequacy, and targeting. The long years maintained MSA scheme had limited reach due to many strict eligibility criteria so the reform aimed in expanding the inclusion of more vulnerable individuals and families. Besides, the monetary values of the benefit were previously not indexed to inflation as well as outdated means-test thresholds were implemented. From this point of view, the 2023 reform sought to tie the benefit amounts to the national poverty line in order to make them more responsive to the rapidly shifting economic circumstances since the 2022 energy crisis and related inflationary pressures. Moreover, the introduction of annual adjustment aimed in improved reflection of MSA regarding the needs of different groups (e.g., elderly, disabled, single parents). The microsimulation analysis of such effects expected to be achieved by the 2023 MSA reform is performed for the period 2023-2025 using the Bulgarian component of EUROMOD: the tax-benefit microsimulation model of the EU. Most up-to-date dataset is utilized, derived from SILC 2023 survey measuring the incomes for year 2022. Particular indications for the shifts in selected poverty and inequality indicators are evaluated, having in mind that the reform was intended to narrow the poverty gap and improve social inclusion.
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Financing a Universal Child Benefit by taxing Illicit Financial Flows in Ghana
Universal social protection is increasingly recognized as a central instrument for achieving the United Nations 2030 Agenda commitment to “leave no one behind.” By guaranteeing income security for all, universal policies enhance equity, reduce stigma, and limit exclusion errors that commonly affect means-tested programmes, particularly in low-capacity settings. However, their adoption in low- and middle-income countries (LMICs) is often constrained by concerns over fiscal affordability, driven by cost estimates that assume financing through broad-based and potentially regressive taxation.
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Household Demand Responses to Carbon Pricing by Energy Poverty Status: Evidence from Belgium
This paper develops a behavioral microsimulation framework to analyse how carbon pricing affects energy vulnerable households in Belgium. We focus on two groups: energy poor (EP) households, who devote a large share of their income to energy, and hidden energy poor (hEP) households, who spend little on energy as they severely restrict their consumption. Using eleven cross-sections of the Belgian Household Budget Survey (2003–2016), we first document structural differences between EP and hEP households with logistic regressions. We then estimate a demographically specified Quadratic Almost Ideal Demand System (Banks et al., 1997) and develop a two-stage residual inclusion procedure to address the endogeneity of energy poverty statuses. The resulting price and income elasticities by vulnerability profiles are used to simulate responses and welfare impacts of a carbon price on heating and transport fuels, consistent with the forthcoming EU ETS 2. Behavioral adjustments are highly heterogeneous: lower-income and energy vulnerable households show higher fuel price elasticities than wealthier groups, with hEP households responding most strongly to price increases. Consequently, EP households face substantial carbon costs but comparatively smaller welfare losses, whereas hEP households suffer disproportionately large welfare losses despite their low expenditure exposure. These results reveal horizontal equity concerns that are invisible in income-based metrics alone and highlight the need to integrate detailed energy vulnerability profiles into carbon pricing design.
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Mapping the drivers of spatial inequality in Luxembourg.
Understanding spatial disparities in income distribution is crucial for designing effective and targeted public policies. However, small-area analysis is constrained by the limited representativeness of household surveys at fine geographical levels and by the lack of comprehensive income information in administrative and census data. This paper develops a spatial microsimulation framework to map and decompose income inequality across municipalities in Luxembourg by combining EU-SILC survey data, census information, and administrative statistics to simulate complete disposable income distributions at the municipal level for 2012 and 2022. The model integrates labour market behaviour, multiple income sources—including capital income and private transfers—and the tax-benefit system using EUROMOD. Spatial heterogeneity is captured through a two-step procedure that combines census-based reweighting with regression-based alignment to local demographic and labour market control totals. We further decompose overall inequality into between- and within-municipality components, observing a stronger within-municipality component. This suggests that factors operating at the local level—such as demographic composition, labour market participation, and access to specific income sources—play a central role in shaping income disparities. Our results reveal the dominant role of demographic and local structural factors in driving these disparities. By producing timely and spatially detailed estimates of disposable income and inequality, this paper demonstrates how combining spatial microsimulation with dynamic income generation can overcome data limitations and provide a powerful tool for analysing the drivers of spatial inequality and supporting evidence-based local policy design.
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Missing Out on Social Assistance: The Consequences of Benefit Non Take-Up in the UK
Benefit non take-up refers to situations in which individuals or households do not claim social benefits to which they are legally entitled, due to low expected financial gains or costs associated with claiming, including administrative complexity, time and effort, stigma (Moffitt, 1983). While public debate has often focused on benefit fraud, non take-up is considerably more widespread (Ko and Moffitt, 2022). Low take-up undermines the redistributive capacity of welfare states and limits their effectiveness in protecting households against poverty and economic insecurity (Van Oorschot, 1991; Matsaganis et al., 2008). An alternative interpretation, however, views non take-up as a screening mechanism that contains public expenditure by discouraging claims from less needy households (Nichols and Zeckhauser, 1982). In the UK, existing micro-level studies of benefit take-up are relatively dated and rely largely on cross-sectional data (Blundell et al., 1987; Pudney et al., 2006; Zantomio et al., 2010). As a result, there is little evidence on the longer-term consequences of non take-up, partly due to the lack of longitudinal data linking benefit eligibility to observed outcomes. This study addresses this gap by combining longitudinal survey data with tax-benefit microsimulation, complementing recent work on the determinants of non take-up in the UK (Vella and Richiardi, 2024) by focusing instead on its consequences. The main objective of the study is to examine the consequences of non take-up of means-tested benefits for eligible individuals over time, with a focus on labour market outcomes, poverty, physical and mental health, and subjective wellbeing. The analysis combines the UK Household Longitudinal Study (UKHLS) with the UK tax-benefit microsimulation model, UKMOD. UKHLS provides annual panel data on income, employment, household composition, health, and wellbeing. Embedding UKMOD within a longitudinal survey represents a key methodological innovation, allowing benefit eligibility to be reconstructed consistently over time and take-up to be modelled dynamically. Non take-up is identified by comparing observed benefit receipt, based on self-reported information in UKHLS, with simulated eligibility derived from UKMOD. The analysis covers the main social assistance programmes in the UK, namely Universal Credit and its legacy benefits, Pension Credit, and Child Benefit. Prior research shows that eligible individuals who claim benefits differ systematically from those who do not, with non-claimants typically having higher incomes, higher levels of education, and lower dependency loads. In addition, take-up is subject to state dependency, in the sense that individuals who claim benefits once are likely to continue claiming in subsequent periods, and vice versa. To address this selection, propensity score matching is used to construct comparable groups of eligible claimants and eligible non-claimants based on observed characteristics measured prior to take-up. Outcomes are then analysed using a difference-in-differences design, comparing changes over time between the two groups. In addition, individual fixed effects regressions are estimated, exploiting within-person variation in take-up status across waves.
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Signals on Budget Day: Media Attention and Public Beliefs in Ireland
Ireland is an outlier among European countries in that it has no automatic indexation of tax and welfare parameters. As a result, the annual Budget announcement plays a significant role, both in shaping the government’s discretionary policy priorities and in influencing people’s expectations about the future. In this project, we study Budget Day as a signalling device along two margins. First, we ask how discretionary policy choices across spending areas respond to political economy forces: media attention, organised interest-group pressure, and electoral cycles. Second, we examine whether Budget announcements shift individuals beliefs about redistribution and uncertainty about the future, and whether these responses are heterogeneous by predicted exposure to the announced measures. In terms of conceptual framework and methods, we build on the literature on central bank communication, which uses language analysis and treats policy announcements as signals that shape expectations (Hansen et al., 2018; Ehrmann and Talmi, 2020). A related strand of work studies the political economy of budget trade-offs (Adolph et al., 2020) and the role of information flows in distinguishing anticipated from unanticipated fiscal policy in budget announcements (Leeper et al., 2013). Balladares and Garcia-Miralles (2025) trace fiscal drag in Spain over time, while in the Irish context (Boyd and McIndoe-Calder, 2025) the focus is on personal income tax over a shorter horizon (2019-2023), using microsimulation modelling with EUROMOD. However, there is little long-run evidence on Irish budget cycles or their political determinants beyond the aggregate analysis in Cousins (2007). In the first part of this paper, we build a new historical dataset of Irish budgets from the mid-1990s onward, coding discretionary changes by broad policy area. We benchmark each years policy package against a counterfactual that mechanically indexes key tax and welfare parameters to price and wage inflation. Deviations from this benchmark provide a transparent measure of discretionary policy priorities. We then relate these deviations to (i) topic-level media salience indices constructed using text analysis of newspaper coverage, (ii) measures of lobbying intensity proxied by pre-budget submissions and public representations by sector, and (iii) electoral timing and macroeconomic conditions. In the second part, we analyse individual-level survey data to examine perceptions of redistribution, fairness, and uncertainty about the future in relation to budget announcements. Microsimulation using EUROMOD allows us to account for heterogeneity in responses, in particular whether individuals or households that are likely to gain or lose from policy changes react differently. We exploit variation in interview timing relative to Budget Day using the Irish sample of the European Social Survey, complemented by Eurobarometer data. Our work provides a systematic assessment of Irish budget priorities and contributes to the debate on whether indexation would reduce fiscal drag and depoliticise distributional choices, or whether discretionary budgets are instead responsive to public preferences.
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The Distributional Effects of Carbon Pricing in Germany
Even though economists prefer the instrument of carbon pricing to reduce greenhouse gas emissions over regulatory policies, fears of regressive effects that disproportionately burden low-income households lead to low public support, hindering the political feasibility of carbon pricing. In light of an ongoing policy debate and lacking evidence for the German context, this paper investigates the distributional effects of carbon pricing in Germany, as well as possible redistributive polices. I analyze three channels through which carbon pricing affects the distributional outcome: the direct price effect, the indirect price effect and the behavioral response. I then compare a lump-sum transfer, a targeted transfer per income deciles and reductions in labor and income taxes as redistributive policies, providing evidence on their effect on counteracting adverse distributional consequences from carbon pricing.
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Towards a distributionally painless carbon tax through revenue recycling
Carbon taxation is widely seen by economists as one of the top instruments for reducing greenhouse gas emissions and achieving ambitious decarbonization targets. Yet, despite its efficiency, it often faces public opposition, mainly driven by distributional concerns. A broad consensus in the literature holds that, in the absence of revenue recycling, carbon taxes tend to be regressive, disproportionately burdening low-income households. Consequently, a substantial body of research has focused on designing compensatory mechanisms,such as lump-sum rebates, tax shifts or targeted transfers, to restore progressivity and improve public acceptability.
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Who bears the cost of carbon pricing? Gender differentials in carbon footprint and distributional impact of carbon pricing across Europe
This paper examines the gendered distributional effects of carbon pricing across six European Union countries, focusing on differences in household carbon footprints and exposure to carbon-induced price increases. While prior research has primarily emphasized the income-based regressivity of carbon taxes (Maier et al., 2025), this study addresses the relative neglect of gender disparities in emissions patterns and welfare impacts.
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