Book of Abstracts

We present a continuous-time longitudinal microsimulation module for labour activity careers in microWELT, a comparative microsimulation model for socio-demographic projections and policy scenario analysis. Individual careers evolve through transitions among employment, unemployment, non-participation, retirement, and family-related leave using an event-driven waiting-time approach. Transition processes are modelled with piecewise-constant hazard regressions featuring competing risks and explicit duration dependence, enabling realistic spell dynamics - especially for unemployment - that are often difficult to reproduce in discrete-time transition models. A central design feature is alignment to scenario targets for aggregate unemployment and labour force participation. Because microWELT, like most policy microsimulations, do not model market mechanisms, these targets provide macro-level closure for projections and a transparent instrument for counterfactual scenario design. Estimating transition hazards in microWELT is challenging because the underlying comparative survey data typically have limited longitudinal depth and small effective sample sizes, implying higher parameter uncertainty than administrative-history models such as Austria’s microDEMS. To address this, we adapt the microDEMS hazard-based framework and implement two alignment mechanisms. First, simulated aggregates are calibrated to scenario targets for overall unemployment and participation. Second, an optional but pivotal mechanism for microWELT constructs group-specific targets using cross-sectional imputation models defined by categorical characteristics (age group, gender, education, health, and family status). These group targets are reconciled with aggregate constraints via monthly calibration of the cross-sectional model during the simulation. Operationally, alignment exploits simulated waiting times for selected transitions - entries into unemployment and exits from the labour force - to rank individuals by implied event timing and then induces the required number of events by selecting those with the shortest waiting times to meet target margins. All other transitions remain fully continuous-time; only alignment-induced events are implemented on monthly steps to enforce cross-sectional constraints. We evaluate the framework through benchmarking and retrospective validation, comparing careers generated from hazards estimated on administrative versus survey data and assessing fit to recent observed outcomes. Validation focuses on the distribution of unemployment spell durations and heterogeneity in unemployment risk across population groups, quantifying how alignment delivers target consistency while preserving plausible continuous-time dynamics and empirically observed group differences.

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.

We project the effects of changes in fertility and mortality rates on both the receipt and provision of care in the UK. We investigate the impact on the level and cost of care, as well as its share of total GDP, through the life course and across income and wealth distributions. SimPaths, an open-source dynamic microsimulation model, is employed to design different scenarios over a half-century period. This framework projects life histories over time, developing detailed representations of career paths, family and intergenerational relationships, health, and financial circumstances. Our estimates show that the value of care, as a share of GDP, almost doubles over the five decades of our analysis, with informal care accounting for most of the projected rise.

Background Population health simulation models—including microsimulation, agent-based, system dynamics, and Markov models—are essential tools for understanding noncommunicable disease (NCD) burden and evaluating policy interventions. However, inconsistent reporting practices limit the transparency, reproducibility, and credibility of this work. Unlike clinical trials and observational studies, which benefit from established reporting guidelines (CONSORT, STROBE), no comprehensive standards exist for population health simulation models. The POPCORN initiative (Population Health Modelling Consensus Reporting Network) aims to address this gap by developing the first EQUATOR Network reporting guideline specifically for population health NCD models. Following EQUATOR methodology, guideline development requires three phases: (1) a scoping review to identify current reporting practices and gaps, (2) international Delphi consensus to prioritise reporting items, and (3) pilot testing with modellers and journal editors. This abstract presents findings from the first phase. Methods We conducted a scoping review following the Arksey and OMalley framework with Joanna Briggs Institute guidance. Scoping reviews systematically map the evidence base to identify key concepts, gaps, and research needs—making them ideal for informing guideline development. We searched MEDLINE, Embase, Scopus, and Global Health for studies published July–December 2025. Eligible studies were computational simulation models examining population-level outcomes for eight NCD groups (cardiovascular, cancer, diabetes, respiratory, mental health, neurological, musculoskeletal, injury) or six risk factors (tobacco, diet, physical activity, alcohol, obesity, hypertension). We applied PICOSIM criteria adapted for simulation studies, covering population, intervention/comparator, outcome, study approach, integration of data sources, and model adaptability. Given the high volume of literature, we implemented AI-assisted screening using large language models with retrieval-augmented generation to support title/abstract review alongside five human reviewers. Data extraction captured reporting elements across model structure, inputs, validation, and outputs. Results From 8,474 records, deduplication yielded 6,427 unique citations. Our database search identified 90% of studies from a reference set of 65 known eligible studies. AI-assisted screening achieved 90% sensitivity and 95% specificity compared to human consensus (κ=0.69), missing only 2 of 20 eligible studies in the validation set. Identifying simulation models proved challenging: key discriminating terms were absent from nearly 10% of titles and abstracts. Preliminary extraction revealed systematic reporting gaps in model specification, parameter uncertainty quantification, and validation procedures—precisely the areas where standardised guidance could improve practice. Conclusions This scoping review establishes the evidence base for POPCORN reporting guideline development. Findings confirm substantial variation in how population health models are reported, supporting the need for consensus-based standards. The microsimulation community will play a central role in the upcoming Delphi process, and we welcome collaborators interested in shaping guidelines that serve both modellers and the policy audiences who rely on their work.

At the intersection of transport economics and public finance, this research contributes to the empirical literature on transport pricing as a policy tool for addressing the externalities of vehicle use. In line with recent technological developments and ongoing policy debates, it provides an ex-ante evaluation of a distance-based road pricing scheme that varies by time (peak and off-peak), location (congested and non-congested zones), and vehicle characteristics. While such systems are widely recognized as efficient, as they better align driving costs with externalities, their implementation in passenger transport remains limited. This absence is largely driven by concerns about distributional effects, highlighting the need for robust empirical evidence on equity implications as a key input for policy feasibility. In this context, this research assesses the distributional impacts of a potential distance-based tax in the Brussels-Capital Region, one of the most congested urban areas in Europe. The analysis adopts a behavioral microsimulation approach to examine longer-term effects. By explicitly incorporating behavioral responses, the study addresses an important gap in the literature, which has largely relied on static and aggregate analyses that overlook how individuals adjust their travel behavior in response to pricing policies. The central research question is: what are the distributional impacts of a distance-based road pricing scheme, differentiated by time, location, and vehicle characteristics, considering both static (immediate) and dynamic (post-adaptation) effects? Methodologically, the approach is structured in two complementary layers. The first layer estimates individual behavioral responses using a stated preference survey based on a discrete choice experiment administered to a representative sample of car users. Respondents are asked to evaluate a recent trip and choose between maintaining it or selecting alternatives that vary in cost, travel time, mode, and timing. These choices are used to estimate individual-level price elasticities through a Mixed Multinomial Logit model. The resulting behavioral parameters are then incorporated into the second layer. The second layer consists of a behavioral microsimulation model built on a synthetic microdataset. This dataset is built by enriching the Brussels Travel Behavior Survey (OVG, 2024) with administrative fiscal data and the estimated behavioral responses. Individuals in the OVG (receiver dataset) are matched with similar profiles from the two complementary sources (donor datasets) using machine learning techniques, including kernel canonical correlation analysis, which captures nonlinear relationships and projects observations into a common latent space. Variables of interested are then imputed using similarity-based weighting. The resulting dataset is aligned with aggregate statistics to ensure consistency with real-world distributions. This integrated framework enables a detailed assessment of policy impacts across the income distribution and supports the simulation of compensation mechanisms. Preliminary results suggest that, in static terms, a distance-based tax is not more regressive on average than the current vehicle ownership tax, largely due to lower car ownership among low-income households. However, conditional on being a driver, some regressive effects emerge, driven not only by uniform tariffs but also by the higher prevalence of less efficient vehicles among lower-income groups, which are expected to pay higher per-kilometer charges. Dynamic results indicate stronger behavioral responses among lower-income individuals, raising important policy considerations regarding accessibility and fairness. Overall, the findings aim to provide new evidence on the extent to which distance-based road pricing can better reconcile efficiency and equity objectives.

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.

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.

The relationship between income and carbon dioxide (CO₂) emissions has been debated in the environmental economics literature, primarily through two complementary but conceptually distinct frameworks. At the macro level, the Environmental Kuznets Curve (EKC) hypothesis posits a non-linear relationship between economic development and emissions, whereby emissions initially increase with income growth before stabilising or declining at higher income levels. At the micro level, Environmental Engel Curves (EECs) describe how household-level emissions vary with income within a given country, reflecting differences in consumption patterns, energy use, and access to carbon-intensive goods and services. These two literatures typically developed separately, leaving a gap: we have limited evidence on how the within-country income-emissions relationship evolves as an economy moves along its development path. To our knowledge, only one study examine temporal changes in the distribution of household CO₂ emissions within a single country, notably Sager (2019) for the United States. This paper studies the evolution of Environmental Engel Curves over time using six waves of the Irish Household Budget Survey (HBS) from the early 1980s to 2015, a period during which Ireland experienced exceptionally rapid income growth and major changes in consumption opportunities and energy use. We estimate income-emissions relationship for multiple points along Ireland’s development trajectory and ask: How does the shape of the EEC change as a country transitions from lower- to higher-income status? In doing so, we explicitly separate two mechanisms that are easily confounded in cross-sectional work: (i) changes in the carbon content of given consumption categories (i.e. carbon intensity of heating) and (ii) changes in the prevalence of carbon-intensive durables (i.e. personal vehicles) across the income distribution (extensive margin). We focus, in particular, on direct household energy use, focusing on residential heating fuels and private transport (vehicle ownership), which are plausible channels through which development alters EEC shape. These categories are where diffusion, infrastructure constraints, and policy-induced technology change are most likely to generate non-linearities. By documenting how EECs shift and re-shape across three decades of development within a single country, the paper complements cross-country evidence on heterogeneous distributional incidence (Dorband et al., 2019) and time-series evidence for the United States (Sager, 2019). We show that the EKC can be understood as the outcome of changing Environmental Engel Curves over the development process, driven by the diffusion and saturation of carbon-intensive household technologies. References Dorband, I. I., Jakob, M., Kalkuhl, M., & Steckel, J. C. (2019). Poverty and distributional effects of carbon pricing in low- and middle-income countries – A global comparative analysis. World Development, 115, 246–257. https://doi.org/10.1016/j.worlddev.2018.11.015 Sager, L. (2019). Income inequality and carbon consumption: Evidence from Environmental Engel curves. Energy Economics, 84, 104507. https://doi.org/10.1016/j.eneco.2019.104507

This paper estimates a Random Utility Random Opportunity model of labor supply using linked Belgian administrative data . The framework allows individuals to choose among stochastic wage and hours offers, capturing both participation decisions and hours adjustments within a unified structure. By combining tax records, social security data, and demographic registers, we construct precise measures of earnings, hours, and household characteristics. A detailed micro simulator tailored to the Belgian tax system maps gross income into disposable income, ensuring an exact representation of institutional rules and nonlinear budget constraints. Compared to survey based data, administrative records substantially reduce measurement error and improve the credibility of simulated behavioral responses. The model closely replicates observed distributions of hours, wages, and income across gender and household types. We then revisit an in-work benefit reform previously analyzed using survey data, highlighting how data precision and institutional detail affect predicted labor supply responses and budgetary implications.

Spain records one of the highest rates of in-work poverty in the European Union (Eurostat, 2024). Despite this, the development of policies specifically targeted at supporting low-income workers has been limited, especially when compared to other European countries (Laun, 2019). This policy gap, combined with the expansion of minimum income guarantees schemes, may weaken work incentives by narrowing the income gap between employment and nonemployment, thereby increasing the risk of poverty traps among low-income households (Domínguez-Olabide & Zalakain, 2023). This paper proposes the introduction of an in-work benefit in Spain, inspired by the American Earned Income Tax Credit (EITC), with the aimed of improving the living conditions of the low-wage workers while strengthening labour market incentives. As in the EITC, the benefit is implemented through the Spanish personal income tax system as a refundable tax credit, varying according to household type. In particular, we propose a more generous credit for families with dependent children, as they face higher poverty rates. The reform is simulated using the EUROMOD microsimulation model, based on 2022 EU-SILC data. Labor supply responses are estimated using a structural labour supply model. The main results suggests that the proposed in-work benefit would not generate negative labour supply effects. On the contrary, the reform is associated with an overall increase in labour supply, particularly in full-time employment. Positive effects are found for both single and couples, with stronger impacts among households with dependent children.