Joint taxation of married couples remains a central feature of many income tax systems, with significant implications for labor supply and household welfare. By pooling partners’ incomes into a single tax base, joint filing can create disincentives for secondary earners and generate marriage-related penalties, raising concerns about efficiency and equity. This paper studies the impact of joint taxation on the labor supply of couples in Belgium, where the personal income tax is formally individual but substantially adjusted at the household level. We estimate a Random Utility Random Opportunity (RURO) model of labor supply using rich administrative data linking tax records and demographic information. Using the FANTASI microsimulation model of the Belgian personal income tax, we perform a counterfactual analysis of a shift from joint to individual taxation.
This research explores how microsimulation modelling can be used to develop an integrated framework that evaluates economic efficiency, social justice, and ecological effectiveness simultaneously.
When social policies are designed and implemented, analysis often focusses on one or maximum two main objectives: economic efficiency and/or social justice. Policymakers and researchers frequently examine how policy reforms can reduce poverty and inequality, or how they can strengthen work incentives and increase employment levels. Microsimulation models, such as the EU tax-benefit microsimulation model EUROMOD, are useful to analyse these distributive and labour market effects of policies. However, policy designs in the context of the just transition towards climate neutrality increasingly require a multi‑dimensional perspective that goes beyond the traditional efficiency-equity trade-off. Current research shows that a third factor affects the existing trade-off: next to economic efficiency and social justice, policies must also consider ecological effectiveness.
A policy measure that illustrates this challenge, is the implementation of a carbon tax. Research shows that it is an economically and ecologically efficient tool to reduce GHG emissions (Baranzini et al., 2017; Timilsina, 2022). On the one hand, it encourages households, businesses, and governments to reduce their emissions, and it provides incentives for innovation. On the other hand, the cost to the government is relatively low, particularly compared to other policies aimed at reducing GHG emissions. However, empirical findings also show that it is very often regressive: households in lower income groups face a higher tax burden than those in higher income groups (Boyce, 2018). The combination of ecological effectiveness, economic efficiency, and potential social inequity highlights the need for an integrated framework that addresses these trade-offs.
Although existing microsimulation models can analyse each dimension separately, we argue that an integrated framework that considers efficiency, justice, and effectiveness simultaneously is needed. Our research tries to contribute to this by exploring how microsimulations models can be used to examine a framework that integrates various indicators (economic, social, and environmental outcomes) together. As an example, we will apply our framework to carbon taxation in Belgium, using Green EUROMOD (the recently developed environmental extension of EUROMOD), building further on Bursens et al. (2026).
Carbon pricing combined with revenue recycling through lower labor income taxation achieves carbon mitigation and a decrease in distortionary labor income tax. However, due to distributional concern, there is large societal opposition towards such reforms. The burden of the carbon price is higher for low-income households due to their higher relative expenditures on carbon-intensive goods, such as heating and transport. Moreover, also indirect effects of the carbon price, e.g. job loss in the economy, are feared to additionally fall on the shoulders of those same households. In this paper we combine a micro- and macroeconomic approach to gauge the distributional direct and indirect impacts of green tax reform. A computable general equilibrium (CGE) model is used to simulate impacts on commodity prices and real wage rates for different types of labor. These impacts are fed to a microsimulation model (MSM) of incomes and expenditures, so that we can gauge the distributional impact of several scenarios in green tax reform. We build on the existing top-down literature, discuss consistency between the two models, the choice of the numéraire and the (implicit) assumption on the uprating of the tax schedule and benefit amounts. Moreover, we show the importance of allowing automatic stabilizers to play out in the computable general equilibrium model, i.e. the role of progressive income taxation and benefits. In a traditional CGE, income taxation is modelled as a (macroeconomically calibrated) proportional tax rate. Change in market incomes would not change the tax burden in such model. However, since taxation is progressive, the tax burden responds to (real) changes in market income. The MSM, with the detailed modelling of the non-linear tax-and-benefit system captures this. We propose in this paper a simple bottom-up feedback, in which we update the proportional tax rates in the CGE with the results of a first run of the MSM, as an alternative to the estimation of a parametric (macroeconomic) progressive tax-and-benefit function to be included in the CGE. Not accounting for automatic stabilizer, overestimates the revenue recycling budget available by one half. This is also relevant for fully integrated CGE-MSM models. We find that medium-skilled employees are on average net losers of the impacts on prices and labor demand. Traditional revenue recycling schemes, such as lumpsum transfers or linear labor income tax cuts cannot overturn this welfare loss for medium-skilled, while still guaranteeing progressivity of the net impacts of the reform. However, more targeted revenue recycling schemes, inspired by the existing low wage subsidies in Belgium (the work boni) are equipped to target revenue recycling towards those most hit by the impacts on the labor market. However, robustness checks show that the adequacy of such revenue recycling design depends on the labor market assumptions in the model, specifically whether the decreased demand for medium-skilled can be translated in higher involuntary unemployment in equilibrium.
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.
Methodologically, this thesis extends the ifo Tax and Transfer Microsimulation Model, which is based on the GSOEP, with a carbon pricing module. This extension models the direct and indirect price effects by using household consumption data from the EVS combined with data on emission intensities and estimates the behavioral responses with Engel curves. Using the model, I simulate the introduction of a 200€ carbon price per ton of CO2-equivalent on all direct and embedded emissions in household expenditures for the year 2018.
The analysis of the simulation results yields three main findings. First, the carbon price achieves substantial emission reductions of 221 Mt CO2eq and generates 97.09 bn. € in revenue but also decreases household consumption expenditures by an average of 5,171€ per year, corresponding to an average price burden of 2,090€ per household. Second, the policy exhibits regressive distributional effects, as the price burden amounts to 8.1% of disposable income for households in the lowest income decile and 4.4% in the highest decile. Decomposing the channels shows that regressivity is mainly driven by the disproportionately high energy burden of lower-income households and their lower ability to respond to price increases. Third, the evaluation of revenue rebating policies reveals that lump-sum transfers and transfers differentiated by income deciles significantly reduce regressivity, whereas reductions in labor or income taxes have limited equality-enhancing effects. These results enable a detailed ex-ante distributional analysis by embedding carbon pricing into a microsimulation model of the German tax-benefit system. Further, the findings provide empirical evidence to a scarce study base on the distributional effects of carbon pricing and different redistributive policies for the German context. The analysis also highlights the persistence of horizontal inequalities within income groups, suggesting the need for more targeted and differentiated redistribution mechanisms. Beyond contributions to literature, this thesis provides insights for policymaking. Introducing a high carbon price requires the design of effective and equi-table rebating, considering heterogeneous effects over and within deciles.
Corporate tax microsimulation models are essential tools to estimate tax revenue, assess the impact of tax reforms, and carry out distributional analyses at the firm level.
The microsimulation model for firms currently being developed at the Bank of Italy aims at accurately simulating the effective tax burden on corporations to allow for the routine evaluation of fiscal policies geared towards the corporate sector. The model is the first to exploit information on tax liabilities contained in detailed financial statements to reconstruct the corporate income tax base at the firm level, which is next used for model validation. This represents an innovative approach to carry out micro-based model validation despite the lack of access to tax return microdata. The model can quantify the gap between financial accounting and tax accounting results, thanks to the modelling of major fiscal adjustments, such as participation exemptions, limits on interest deductibility, and tax depreciation, and replicate a few key stylized facts, such as: i) the widespread divergence between accounting and tax profits, with one fifth (one fourth) of firms with negative (positive) accounting profits showing positive (negative) tax profits; ii) the inverse U-shape of effective tax rates in firm size; iii) the greater impact of participation exemptions and interest payment deductions on large firms’ effective tax rates; iv) the countercyclical usage of loss carryforwards; v) the weaker impact on effective tax rates of accelerated depreciation schemes for intangible vs. tangible assets The work proposes an ex-ante evaluation of the most sizeable fiscal policy geared towards firms enacted with the Italian budget law in 2026, namely the introduction of a 5% participation threshold for the eligibility to the participation exemption (PEX) regime. The PEX regime seeks to eschew double taxation of corporate profits by making participation income (in the form of either dividends or capital gains) exempt. The EU “Parent-Subsidiary” Directive establishes that double taxation arises when the parent company holds, directly or indirectly, a participation stake worth at least 10%. Prior to the budget law 2026, the Italian PEX regime exempted all participation income. The newly introduced policy therefore partially aligns the Italian regime with the EU benchmark. The ex-ante distributional impact of the reform is hard to gauge. On the one hand, firms receiving participation income are less than 10% of total firms. On the other, there is a large empirical literature documenting that shareholding portfolio diversification increases with firm size. By exploiting Orbis information on the size of direct and indirect shareholdings, this work calculates the impact of the reform on firm effective tax rates, and tries to understand whether it was overall progressive, namely it redistributed the fiscal burden towards the largest firms. Finally, it discusses how potential endogenous responses in terms of portfolio reallocation might influence the results.
European long-term care (LTC) systems face mounting sustainability pressures as population ageing increases the number of older adults living with functional and cognitive limitations. Yet projections of future LTC needs often rely on simplified “need” definitions (e.g., at least one ADL/iADL limitation), overlooking a critical institutional determinant of public expenditure: eligibility rules. Access to publicly funded LTC is not automatic; it is regulated by national (and in some cases regional) legislation that combines multiple vulnerability dimensions—limitations in activities of daily living (ADL), instrumental ADL (iADL), cognition, behavioural issues, and medical needs—into non-linear thresholds for benefit entitlement. Because these rules differ markedly across Europe, they can generate substantially different trajectories of potential demand for publicly financed LTC even under identical demographic and epidemiological trends. This study investigates how the heterogeneity of LTC eligibility criteria shapes the evolution of potential demand for formal domiciliary LTC across European countries in the coming decades. We use longitudinal microdata from the Survey of Health, Ageing and Retirement in Europe (SHARE), Waves 1–9 to operationalize country-specific eligibility rules. Using SHARE’s information on ADL/iADL limitations, mobility constraints, depression symptoms, and cognitive impairment, we construct harmonized indicators of “objective vulnerability” consistent with the assessment-of-need frameworks embedded in legislation. These eligibility indicators are then embedded in a dynamic microsimulation model, the EU-FEM (the SHARE-based version of the Future Elderly Model), which simulates individual life courses through a first-order Markov Monte Carlo process. Transition models generate probabilities of changes in health and functional status over time, allowing heterogeneous trajectories by age, risk factors, and baseline conditions, while the simulated population evolves by ageing and cohort replacement. We produce projections of the population-level prevalence of eligibility for publicly funded domiciliary LTC—interpreted as potential demand—under a baseline “no policy change” scenario. We then conduct counterfactual exercises to disentangle the role of rules versus epidemiology: (i) applying alternative countries’ eligibility rules to the same underlying population trajectories; (ii) simulating a synthetic “single-country” setting to isolate institutional effects; and (iii) evaluating stylized healthy-ageing interventions that reduce the incidence of selected physical and mental limitations by 25% among individuals aged 65–75. The simulations highlight that eligibility-rule heterogeneity translates into markedly different projected pathways of potential LTC demand across Europe. Moreover, the same healthy-ageing intervention can yield very different reductions in projected eligibility depending on which functional domains are targeted and how each country’s rules weight physical, cognitive, and mental limitations. These findings imply that cross-country comparisons of future LTC burdens—and evaluations of prevention-oriented strategies—must explicitly account for institutional eligibility design. Ongoing work extends the framework by incorporating newer SHARE waves, improving harmonization with broader international platforms, and translating projected eligibility into cost trajectories of potential demand.
As populations age, the sustainability of long-term care systems increasingly depends on the availability of informal care, particularly from partners. This paper addresses the question of how much care we may expect partners to provide in the future by projecting demand for long-term care (LTC), the care supply mix based on current patterns, and the resulting care gaps up to 2070. Using a comparative dynamic microsimulation model, we contrast the results for Austria and Italy, two countries at very different stages in the ageing process and with pronounced institutional differences. Our results suggest that delayed widowhood due to improvements in mortality is a mitigating factor for the increased need for formal care in ageing societies, although it can only offset this increase to a limited extent. Even under optimistic assumptions, potential care gaps substantially increase in both countries, primarily due to demographic change. The size of these gaps is influenced by institutional settings, partnership patterns and gains in longevity, but no scenario reverses the overall upward trend. These findings emphasize the need for comprehensive LTC reforms that extend beyond merely promoting informal care and highlight the necessity for substantial investment in formal care infrastructure.
We examine the role of social transfers for self-employed in Belgium using the microsimulation model BELMOD. The self-employed represent a significant and increasing group in Belgium. The measurement of income from self-employment comes with particular methodological challenges and research shows that material deprivations tends to be lower for self-employed compared to employees. Despite the existing limitations we will focus on financial poverty for self-employed. The combination of microsimulation techniques and administrative data allows us to analyze which parts of the tax-benefit system contribute most to the poverty reduction for self-employed. We use administrative data and BELMOD to study the poverty reducing role of various household income sources for the self-employed in more detail. Other incomes in the household, besides the income from the individual self-employed person, reduce the poverty risk significantly. For example, the poverty risk of self-employed is reduced by more than half when taking into account labour incomes from other household members. Furthermore, it is reduced by about a third when taking into account all social benefits in the household. Our results indicate that poverty is reduced substantially by social transfers, but to a different degree for various family types. Child allowances clearly contribute to the reduction of the poverty risk for self-employed with children. For families without children, we see the largest reduction in the poverty risk for the household by pension related benefits, followed by contributory sickness/disability benefits. This work is a first step in trying to identify groups of vulnerable self-employed and assessing the role of the tax-benefit system.
Nearly half of the unemployed persons are excluded from the unemployment benefit system by the re-form which has been gradually implemented since 1 January 2026 in Belgium, particularly those with a long unemployment history. The main feature of the reform is to limit the duration of unemployment benefit payments to a maximum of two years, depending on work experience, instead of unlimited payments in time as in the old system. Further, the progressivity of the benefit scheme has been strengthened by an increase of 10% of the ceiling amount during the six first months of unemployment, and a re-duction to a lump sum for unemployed persons who are entitled to payments after one year of unemployment.
This paper gives the ex-ante evaluation results on income and labour supply of this reform. The simulation exercise concludes that approximately one third of the excluded persons are expected to return to work, approximately 40% are predicted to receive the social minimum income. The remaining fourth withdraw from the labour market without replacement income, resulting in a significant loss of disposable revenue. Nonetheless the impact on the poverty rate is moderate. Older unemployed, aged 55 years and over, are particularly affected by the reform as more than three fourth of them lose their benefit, representing nearly 22% of the excluded sample. Regional differences are substantial, with Flanders being the least impacted and Brussels-Capital region the most.
To fulfil the evaluation, we use:
The data from the Crossroad Bank which is a representative sample of the Belgian population with more than 300,000 individuals. It includes a wealth of economic, social and demographic information at both individual and household level, The microsimulation model EXPEDITION which is a highly detailed transcription of the Belgian fiscal and social laws into a microsimulation program, which enables to compute a.o. the dis-posable income and its components for each household based on gross salary, labour supply and all the individual and household characteristics. For this exercise, we are particularly interested in the net income from work, replacement income from unemployment or social minimum allowance, depending on eligibility, and additional benefits (children benefit e.g.). EXPEDITION offers also summary statistics and distribution analysis, such as inequality measures depending on income decile, family type, age group, etc. The labour supply model LASER which is a Van Soest-style microeconomic model, enhanced by non-parametric random coefficients on the household preference parameters. Furthermore, we introduce unemployment as an additional labour supply ‘’choice’’. Nonetheless, unlike most similar models, we explicitly define equations capturing the unemployment probability, and the potential unemployment duration. In addition, the replacement income from unemployment is de-fined as the average benefit over the expected unemployment period to account for the degressive scheme of the Belgian unemployment benefit (and the limitation in time after reform), when calculating the income associated with the unemployment ‘’choice’’ alternative. Subsequently, each individual (not only those directly affected by the reform) is impacted when choosing the best employment alternative.
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.
While these approaches have provided important insights, they often conflate two distinct objectives: making carbon taxation more progressive on average, and reducing the heterogeneity and intensity of its adverse impacts across households. In practice, large disparities in energy consumption and bills persist even within standard socioeconomic groups (e.g. income deciles or geographic areas), meaning that the households most negatively affected by carbon pricing are not always those conventionally identified as vulnerable. In this paper, we therefore focus on the latter objective, namely reducing the “painfulness” of carbon taxation rather than progressivity per se. We argue that an effective compensation scheme should primarily protect households facing large increases in energy costs, smooth the distribution of impacts, avoid overcompensation of lightly affected households and preserve incentives to reduce carbon-intensive energy use. In this perspective, the change in the Energy Effort Rate (EER), that is the variation in the share of household income devoted to energy expenditures following a carbon price increase, emerges as a relevant indicator of household vulnerability.
We use the Prometheus microsimulation model, developed at the French General Commission for Sustainable Development, to analyze the distributional effects of alternative revenue-recycling schemes in France. Prometheus provides a fine-grained simulation of households’ energy bills for housing and transport, accounting for own- and cross-price elasticities, and is specifically designed to assess the impact of energy transition policies and compensatory measures. Using 2019 as the baseline year, we simulate a €10/tCO₂ increase in the carbon tax and compare three polar, budget-neutral redistribution scenarios, each leading to identical aggregate CO₂ emissions from household energy consumption: (i) a reduction in electricity taxation, in the context of France’s low-carbon electricity mix (ii) a uniform lump-sum rebate, and (iii) a progressive lump-sum rebate targeted at the bottom 50% of the income distribution. The microsimulation framework allows us to characterize the full distribution of changes in households’ EER under each scenario.
Our results highlight important trade-offs between progressivity and the smoothing of impacts from carbon taxation. While the targeted lump-sum rebate is the most progressive scheme by construction, it performs poorly in reducing the dispersion of changes in EER, leaving a non-negligible fraction of households exposed to substantial increases. The uniform rebate and the electricity tax shift exhibit comparable average redistributive profiles, but differ in their ability to smooth the impact of carbon taxation. Although the uniform rebate is slightly more progressive, the electricity tax shift consistently minimizes extreme variations in the EER and achieves the lowest overall dispersion according to several quantitative indicators.
Overall, our findings show that some revenue-recycling instruments, when carefully designed to account for context-specific energy and institutional conditions, can effectively smooth the burden of carbon taxation across households and thereby help improve public support for carbon pricing without compromising its environmental effectiveness.
