Microsimulation is widely used in economics to analyse the distributional effects of policy and the behavioural responses of heterogeneous agents. In agricultural economics literature, farm-level simulation and bioeconomic models have developed in parallel with farm level microsimulation. These models operate at different scales but combine biological processes with economic and policy factors. The modelling literature provides little systematic assessment of how these approaches address economic and environmental outcomes in pasture-based agricultural systems. This paper addresses the gap through a systematic review of 173 peer-reviewed modelling studies published between 2000 and 2024. The analysis traces temporal and geographical trends in the literature, reviews methodological choices, and assesses how economic and environmental outcomes are modelled. The results shows that farm-level simulation approaches account for largest share of the literature, followed by optimisation models, while microsimulation and macro-scale approaches are less common. Most of the studies were at the farm-level and focus mainly on environmental outcomes, particularly land use and greenhouse gas emissions. Policy modelling concentrated on conventional production systems, while organic and low-input systems are underrepresented. Approximately half of the reviewed studies originate from Europe, and macro-level approaches account for less than 10% in literature. The literature exhibits a persistent pattern: models that handle farm-level heterogeneity seldom connect to sectoral outcomes, while those designed for aggregation are seldom applied to pasture-based systems. This limits the evidence base for policies that require both micro-level behavioural responses and macro-level assessment. Closing this gap will require integrated frameworks that couple farm-scale representation with sectoral or economy-wide models.
The simulation of social benefit entitlements is an important application of tax-benefit microsimulation models in social policy research. However, the simulation of social benefits that include a comprehensive means test and overlap with other social benefits is subject to numerous data limitations and simulation inaccuracies. This note examines the validity of the results of an open-source tax-benefit microsimulation model (GETTSIM) on social benefit entitlements. We use accurate administrative data collected during the application process for the simulation to assess the quality of the simulation. We find a low beta error rate and a high match between simulated and recorded benefits, making GETTSIM a powerful tool for the analysis of social policies.
This review explores the role of microsimulation modelling in addressing the multidimensional nature of food security, focusing on affordability, nutrition, and environmental sustainability. Using a hybrid approach that combines qualitative textual synthesis with bibliometric analysis, the study offers both depth and breadth in reviewing current literature. Findings reveal that while affordability and nutrition are frequently examined, environmental aspects remain notably underrepresented in microsimulation-based food security analyses. This gap limits the development of integrated policy responses that address both human and planetary health. The review underscores the need for more interdisciplinary, systems-based modelling approaches that align with global sustainability goals. Bridging these methodological and thematic gaps is important for designing effective, equitable, and environmentally responsible food policies.
The study investigates taxation, poverty, and income inequality in Zambia, aiming to identify fiscal reforms that boost revenue, alleviate poverty, and reduce inequality. It examines the effects of Personal Income Tax (PIT), Value-Added Tax (VAT), Turnover Tax (TOT), and Excise Duties using the MicroZamod microsimulation model and STATA modelling from 2010 to 2019. Key findings show that taxes increased the poverty rate by an average of 2 percentage points, with VAT as the main contributor (72.6%), followed by TOT (19.3%), PIT (4.2%), and Excise Duties (3.8%). VAT, though a major revenue source, fails to reduce poverty, while PIT significantly reduces inequality, contributing 70% of the reduction in the Gini coefficient. This study assesses the cost-effectiveness of various taxes in relation to poverty reduction and inequality by calculating welfare multipliers per 1 billion Kwacha of revenue generated. By doing so, it significantly contributes to the existing literature and advances our understanding of how cost-effectiveness indices can inform the formulation of optimal tax policy. VAT increases the national poverty rate by 0.45 percentage points per billion Kwacha raised, whereas PIT raises poverty by only 0.04 percentage points but reduces the Gini coefficient by 0.68 percentage points. Excise Duties slightly improve income distribution with a 0.05 percentage point reduction in the Gini coefficient, while TOT marginally worsens inequality with a 0.06 percentage point increase per billion Kwacha raised. The research emphasises PIT's potential in reducing inequality and proposes tax reforms to reduce poverty and inequality. Policymakers can use these insights to optimize tax policies, balancing revenue generation with the goals of reducing poverty and inequality.
We introduce SNFsim, an open-source discrete-event simulator for developing and evaluating reinforcement learning (RL) methods for multi-dimensional sequential decision support in Skilled Nursing Facilities (SNFs). SNFs play a vital role in the United States healthcare system, delivering specialized care to individuals with ongoing medical needs. Decision-making within SNFs is often complex due to their fast-paced and stochastic nature. SNFsim provides a modular and extendable simulation of major decision-making processes within SNFs, capturing many of the complexities and uncertainties existing in healthcare environments while still being flexible enough to allow for easy customization. Its potential uses are two-fold: First, as a test bed for the development and comparison of RL algorithms, and second, as the basis of a decision-support system that can be tailored to individual SNFs.
This paper describes the development and operation of the SWITCH model, a tax-benefit microsimulation model for Ireland which is linked to survey and register data. SWITCH is based on the EUROMOD platform but has important advantages over the Irish component of EUROMOD, including a “current income” concept, detailed information on benefit receipt in the underlying data and the modelling of non-cash benefits. We discuss the process of creating an input dataset, including reweighting and uprating. We validate the model’s simulation of the income distribution with respect to a range of external sources and suggest future improvements
We present a methodological approach with relatively low information requirements to quantify the impact of large, unprecedented macroeconomic shocks like the COVID-19 pandemic on living standards across the income distribution. The approach can be produced quickly and, contrary to other "fast-delivery" exercises, does not assume that income losses are proportional across the income distribution, a feature that is critical to understanding the impact on poverty and inequality. Our method is sufficiently flexible to refine the projected effects of the shock as more information becomes available. We illustrate with data from the four largest countries in Latin America: Argentina, Brazil, Colombia, and Mexico, and discuss the estimated effect of COVID-19 on inequality and poverty. We also present the guidelines for adapting our framework to different countries and economic shocks © 2023, Lustig et al
In the last 15 years before the COVID-19 crisis, Germany has experienced a strong and continuous increase in employment - the ‘German job miracle'. During this period, income inequality, which had previously increased sharply, remained relatively stable. This paper analyzes the impact of employment changes on disposable income inequality between 2004 and 2015 and gives an answer to the question why inequality remained constant despite the dramatic increase in employment. It is the first study to examine the effect of changing labor supply patterns due to changes in policies, wages and preferences, as well as the role that labor market constraints have played for inequality of disposable income. It finds that inequality would have increased further due to a transforming population structure, but increasing employment and policy changes almost completely offset this development. The results show that employment growth due to the reduction of labor market constraints has been more important in slowing down the increase in inequality than changes in labor supply © 2023, Mühlhan
In Europe, many people experience financial hardship due to healthcare payments, despite (near- )universal healthcare. In Finland and other countries, austerity has further widened the gaps in coverage through increases in patient payments. However, distributional analyses of austerity have solely concentrated on the effects of tax- benefit policies. We present a method for examining how health payment policies and tax- benefit policies affect household income in conjunction to evaluate the total effect of implemented and planned policies. We linked the national tax- benefit microsimulation model, SISU
In this paper we propose a computational approach to empirical optimal taxation. We develop and estimate a microeconometric model that is run to simulate household labour supply decisions and the implied economic, fiscal and welfare effects. The microsimulation is embedded into a numerical optimization routine that identifies the tax- transfer rule that maximizes a social welfare function. We consider the class of tax- transfer rules where net available income is computed as a 4th degree polynomial transformation of taxable income plus a transfer. We present the results for six European countries: Germany, France, Italy, Luxembourg, Spain and the United Kingdom. For most values of the inequality aversion parameter k that characterizes the social welfare function, the optimized rules provide a higher social welfare than the current rule, with the exception of Luxembourg. The optimized tax- transfer rules are close to a Flat Tax plus a Universal Basic Income (or equivalently a Negative Income Tax).
This paper simulates the effects of policy responses to the COVID-19 pandemic on household income and employment in Argentina, using household survey data and administrative data on employment and wages by economic sectors. The paper also includes a gender and age group analysis. The results indicate that during the COVID-19 crisis, household income decreased. This welfare loss was nonlinear along the income distribution, with the lowest income earners suffering the most due to relatively higher informality at the bottom of the income distribution. The policy responses seem to ameliorate by around one-third what the average drop in household income, and prevented major increases in poverty and inequality © 2022, Martinez-Correa et al
Mitochondrial diseases (MITO) are serious and debilitating conditions, often multisys-temic and requiring life- long monitoring and treatment of symptoms to reduce the risk of a life-threatening episode or acute illness. The disease is caused by mutations either in the mitochondrial DNA (mtDNA) or nuclear DNA (nDNA), resulting in impaired production of cellular energy from the affected mitochondrial organelles. MITO closely resembles other conditions due to its wide clinical presentation and genetic heterogeneity. While mitochondrial diseases are relatively common serious conditions with likely large medical and social costs to patients, carers and government, there is no microsimulation model of the impacts of this condition. Further, there is relatively little data on the medical costs of mitochondrial diseases and almost no data on social costs. What data there is on health costs has serious limitations and costs may be significantly underestimated. We aim to address this gap with the development of a microsimulation model called MitoMOD to estimate the costs of mitochondrial diseases using a cohort of clinically diagnosed adult patients with mitochondrial diseases as the base population. In this paper, we describe the construction of MitoMOD which is designed to capture economic impacts on adults clinically diagnosed with mitochondrial diseases, their carer and government. To date, this is the first microsimulation model of its kind. from a cohort of clinically diagnosed adult MITO participants. We took a broad perspective antici-pating a large range of economic and social impacts of MITO occurring at the patient, family, health service, and whole- of- government level. Our microsimulation model can be used in future studies to report the health and social costs of MITO and to estimate the cost- effectiveness of whole genome sequencing (WGS) compared to current diagnostic tests.
COVID-19 has had a devastating effect on the economy and the health of households around the world. In this study, we evaluate the economic impact of COVID-19, as well as the effect of government interventions aimed at alleviating it, on the welfare of Ecuadorian households in terms of income shocks, poverty rates, and inequality. The empirical strategy used is to measure mean income shock by gender and economic sector based on cross-sectional data from December 2019, May 2020, and September 2020, and use these estimates to simulate individual income shocks from the December 2019 data. This allows us to disaggregate our analysis by demographic and employment profile in order to identify groups at risk and help guide future government COVID recovery programs. We find that by May 2019, poverty had more than doubled, reaching 57%, and average income had fallen by more than 50%. Informal workers, rural populations, indigenous households, and households with young kids were among those most affected. Government interventions thus far have had a negligible effect in the aggregate, but they may have been crucial for the subsistence of households below the poverty line © 2022, Canelas and Robalino
The Covid-19 pandemic had a very quick and damaging impact on several economies around the world, including in Morocco. This economy was hit hard with some sectors strongly exposed to the impact on the households and their children. In this article, we built a micro-simulation model and use it jointly with an input-output model to assess the distributional impact of COVID-19 and mitigation measures targeting households in Morocco with a focus on children living in poor households. Our original results show that the crisis has led to a fairly significant increase in poverty, with more pronounced effects in the urban area. Children under 5 years of age and young adults (over 18 years of age) are the most affected. Just over half a million children under the age of 18 would fall into poverty as a result of the pandemic. The mitigation measures put in place by the government and additional measures we designed and simulated further reduce the negative impact of the pandemic. In addition, the number of vulnerable rural population has decreased in both rural and urban areas. However, the two scenarios focusing on mitigation of the effects of the pandemic do not fully compensate for the negative effects of the pandemic in the urban area as opposed to rural areas. When we focus our analysis by age category, the incidence rates of vulnerability decrease to their initial rates for children under 5 years of age and decrease very slightly for youth aged 5 to 17 years at the national level. However, we find that this vulnerability is deeper and more severe even after the implementation of compensatory measures © 2022, Abdelkhalek et al
Like other African countries, Senegal has been hit by Covid-19 and has implemented measures to contain the epidemic. These measures impact men and women differently, mainly via the impacts on the labour market. We simulate the economic shocks in a computable general equilibrium (CGE) model to assess the economic impacts. We capture the gendered impact on women's employment by linking the CGE model with a micro-simulation employment module. Furthermore, we assess the impact on poverty and inequality by executing a distributive analysis with a sequential top-down layered micro-simulation households module. The results show that the Senegalese economy suffers from Covid-19 measures with a decrease in gross domestic product by 5% and 7% in the moderate and severe scenarios, respectively. While most sectors are negatively affected, some benefit from the increase in foreign demand (e.g., for certain agricultural products). In terms of employment, unskilled workers are the most affected group. Female workers are relatively less affected than male workers due to the predominant presence of women in the agricultural sectors. Indeed, the increased foreign demand for agricultural products positively affects the agricultural sectors. However, poverty increases at the national level for all households, especially for rural households and households living in urban areas except Dakar. Specifically, the poverty gap and severity for rural households increase more than for urban households © 2022, Maisonnave et al
We assess the impact of COVID-19 shocks on household welfare and the effectiveness of select policies implemented to reduce their impact on welfare in Ghana. We adopt a microsimulation approach to assess the effects of COVID-19 on household welfare. Welfare fell by 34.2% to 41.9% between March and June 2020. Over the same period, the poverty headcount and the Gini index increased by 9 to 10.5 percentage points and 0.4 to 0.6 points respectively. The number of poor people increased by 2.8 to 3.2 million. The hardest-hit sector was education, with agriculture, forestry and fishing, trade and repairs, manufacturing, and other services also affected. The effects vary for men, women and children. While women experienced the largest decline in welfare, men experienced the highest increase in poverty incidence. The three policies selected reduced poverty marginally but were unable to offset the increase in poverty that occurred between March and June. The estimated cost of the three policies is GHS3.7 billion excluding administrative costs, which equates to approximately 1% of 2020 GDP © 2022, Cooke et al
The paper addresses the topic of measuring the systemic risk and of identifying Systemically Important Financial Institutions (SIFIs) with an agent-based multi-layer network simulation.The paper starts from the shortcomings of the models currently proposed in the literature and suggests directions for future researches and guidelines to realize a methodology able to accurately model the direct network contagion channel (interconnectedness of balance sheet of financial institutions, including direct losses and liquidity hoarding), also integrating the indirect contagion channel (fire sales and bank runs), in order to reach the full representation of the financial systemic risk.
The COVID-19 pandemic has been a global catastrophe with radical impacts triggering policy responses worldwide. 1Literature on the topic has been unanimous on the deleterious effects of this crisis on the global and national economies, and on poverty, particularly in low-income countries (Miguel and Mobarak, 2022).With varying degrees in terms of the size and nature of packages, countries have put in place measures to mitigate some of the likely devastating impacts of the pandemic.To avoid critical waste of time and resources, simultaneous efforts needed to be invested in assessing the impacts and effectiveness of these interventions, including through the development of country-adapted analytical tools that can produce periodic updates for policy adjustments.This special issue relies on locally-led simulation analyses that produced evidence that has helped local policy-makers to guide the design, or adjustment, of effective policy responses to the COVID-19 crisis.In particular, the five contributions included in this issue developed country-level tools to simulate, on an ongoing basis, the economy-wide and household impacts of the crisis as well as existing and alternative policy responses, to identify the most effective interventions.Especially in developing countries, reliable and nationally representative data are longer to collect and may not be timely.Therefore, the availability of rigorous simulation tools can help policy-makers to respond effectively to sudden economic crises, such as that generated by COVID-19 confinement measures, even when data are not readily available.The COVID-19 crisis challenges governments through the widespread nature of its impacts and the uncertainty concerning their magnitude and duration.By analyzing the likely impacts of various policy responses, simulation models provide policy-makers with valuable evidence to comprehend and respond to these challenges effectively.These simulations could be regularly updated as new data have become available and the country has progressed through the different stages of the crisis: epidemic and lockdown, gradual re-opening and full recovery.There are at least three key considerations when designing policy responses to the COVID-19 crisis and evaluating the impact of the interventions.First is the importance of identifying the sectors (industries, firms) and households/individuals that were likely to be hardest hit by the various economic and social disruptions, and estimating the nature and magnitude of their losses.These impact pathways are complex and heterogeneous across the population.With population confinement measures and the total or partial cessation of many, formal and informal, economic sectors, many workers and family enterprises have lost their sources of income.Furthermore, remittances were significantly disrupted as the pandemic has heavily impacted host countries (Europe, North America and Persian Gulf countries) of migrants sending these remittances.Finally, as a result of the decline in domestic and global production, and the disturbance of global value-added chains, production costs and consumer prices have risen while the global petroleum price was falling.1.
Belgium has implemented, following the example of other countries, in- work benefit policies since the early 2000’s, with the objective of increasing employment rates and fighting poverty. Belgian in- work benefits differ from most other in- work benefits as eligibility requires low hourly earnings. We study the effects extensions of those benefits would have both on labour supply and welfare, using a random- utility - random- opportunity model estimated on cross- sectional SILC datasets. Results show that further increasing the benefits would slightly increase labour supply and welfare of low- to- middle income deciles, but at very high net cost per job created. We compare our results with existing research and explain some mechanisms that possibly led to an underestimation of negative intensive margin labour supply responses in previous simulations.
