Income Distribution in Computable General Equilibrium Modeling

Bourguignon, Françoìs; Bussolo, Maurizio

doi:10.1016/b978-0-444-59568-3.00021-3

Cited by 57 publications

(39 citation statements)

References 38 publications

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“…The Life-Cycle Income Analysis Model (LIAM) stands out as a viable option to provide a general framework for the construction of new dynamic microsimulation models (O'Donoghue et al, 2009) and to be linked to EUROMOD (and other modular-based microsimulation models) in order to exploit the existing parameterisation of tax-benefit systems for the European countries (Liégeois and Dekkers, 2014). Second, most dynamic microsimulation models do not include macro feedback effects and do not have market clearing mechanisms that would require ambitious links to macro models (Bourguignon and Bussolo, 2013). However, due to the number and complexity of the interactions between many social and economic variables involved in the modelling, the integration between dynamic micro and macro models could introduce too much uncertainty in the results to make them useful in a policy context (Li and O'Donoghue, 2013).…”

Section: Dynamic Microsimulation and Lifetime Redistributionmentioning

confidence: 99%

“…More specifically, the linkage of microsimulation models to macro-economic models allows one to consider the interactions of macroeconomic policies or shocks with the tax-benefit systems (see section 3.4). Ignoring the tax-benefit policy effects on income distribution can be justifiable in some circumstances, for example when analysing their impact in developing countries because they may be very limited in size and reform to social expenditures or macro-economic shocks could be much more relevant for re-distribution, but it is more problematic in the context of mature welfare states (Bourguignon and Bussolo, 2013).…”

Section: Microsimulation In the Economic Literaturementioning

confidence: 99%

“…using the parameters of behavioural models or the effective tax rates simulated by micro-simulation models in CGE models), it is rarer to see a fully developed microsimulation model being integrated with a macro model. See Bourguignon and Bussolo (2013) for an excellent review of the different approaches.…”

Section: Macroeconomic Effectsmentioning

confidence: 99%

“…In particular, they are useful tools to analyse: i) the performance of long-term policies such as pensions and other social insurance programmes such as health and long term care, ii) the consequences of different demographic scenarios, iii) the evolution of inter-temporal processes and behaviours such as wealth accumulation and intergenerational transfers, and iv) the geographical trend of social and economic activities if dynamic microsimulation models are supplemented with spatial information (Bourguignon and Bussolo, 2013;Li and O'Donoghue, 2013). The ageing of individual and household characteristics can be implemented as a discrete or continuous process.…”

Section: Dynamic Microsimulation and Lifetime Redistributionmentioning

confidence: 99%

“…On the one hand, micro-oriented policies can have a second round effect due to micro-macro feedbacks: for example, a generous income support scheme can have effects on labour market and saving behaviours. On the other hand, macro oriented policies or exogenous shocks have a redistributive impact which needs to be assessed if the potential implications for the political economy of the reforms is to be understood (Bourguignon and Bussolo, 2013).…”

Section: Macroeconomic Effectsmentioning

confidence: 99%

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Microsimulation and Policy Analysis

Figari

Paulus

Sutherland

2015

Handbook of Income Distribution

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ISER Working Paper Series www.iser.essex.ac.uk Microsimulation and Policy AnalysisNon-technical summary This paper is prepared as a chapter forthcoming in the Handbook of Income Distribution, Volume 2 (edited by A. B. Atkinson and F. Bourguignon, Elsevier-North Holland). Microsimulation methods are increasingly used to study the effects of policies on the income distribution contributing both to policy debates and academic literature. In general terms, microsimulation refers to modelling changes in the state or behaviour of micro-level units. We provide an overview of approaches that address questions related to the impact of taxbenefit policies on household income distribution. We first discuss how microsimulation modelling contributes to the analysis of the income distribution more broadly, pointing out that it can enrich survey and administrative data by checking its consistency, adding further details and enhancing analytical flexibility. In addition, it provides the basis for calculating indicators that cannot otherwise be estimated directly from micro-data such as measures of work incentives, net support for children and automatic stabilisers embedded in tax-benefit systems. We then focus more specifically on the role of microsimulation in policy evaluation. Taxbenefit models can provide information on household disposable income and its components under various policy scenarios and as such constitute a unique tool for ex ante policy analysis, though equally can be used for ex post analysis. We review the formal framework underlying such microsimulation-based decomposition analysis of income distribution and suggest a broader perspective to accommodate a wider range of applications. Our main emphasis is on static modelling methods, though we also consider extensions accounting for behavioural reactions and links with macroeconomic models. As microsimulation models are often concerned with current and future policies, we discuss various approaches to predict the income distribution given that data providing information on the current situation becomes available with a time lag, distinguishing between nowcasting and forecasting. We emphasise the role of comparative analysis as cross-country differences in tax-benefit systems and population structures provide a basis to assess the robustness of results and generalise conclusions. We provide empirical illustrations drawing mainly on analysis using the EU-wide tax-benefit model EUROMOD. Covering 27 countries and made generally accessible this is now one of the most widely used models. There are many remaining challenges to providing estimates of the effects of policy and policy changes that can be used with confidence within policy analysis and we consider three major issues: reconciling the simulated income distribution and that measured using the original micro-data; accounting for benefit non take-up and tax non-compliance, as well as validating and assessing the statistical reliability of microsimulation estimates. While our main focus is on the distributio...

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Section: Dynamic Microsimulation and Lifetime Redistributionmentioning

confidence: 99%

Section: Microsimulation In the Economic Literaturementioning

confidence: 99%

Section: Macroeconomic Effectsmentioning

confidence: 99%

Section: Dynamic Microsimulation and Lifetime Redistributionmentioning

confidence: 99%

Section: Macroeconomic Effectsmentioning

confidence: 99%

See 3 more Smart Citations

Microsimulation and Policy Analysis

Figari

Paulus

Sutherland

2015

Handbook of Income Distribution

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Empirical Evidence Using Microsimulation Models in the Social Sciences

Figari

Lezzi

2021

New Horizons in Modeling and Simulation for Social Epidemiology and Public Health

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Beyond the Energy System: Modeling Frameworks Depicting Distributional Impacts for Interdisciplinary Policy Analysis

Montenegro

Fragkos²,

Dobbins

et al. 2020

Energy Tech

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Since the signing of the 2030 Agenda for Sustainable Development by the United Nations Member States and the Yellow vest movement, it is clear that emission‐reducing policies should consider their distributional impacts to ensure a sustainable and equitable growth compatible with the Paris Agreement goals. To this end, the design of environmental and energy policies should be accompanied by an interdisciplinary analysis that includes potential effects on distinct groups of society (defined by income, age, or location), regions, and sectors. This work synthesizes common modeling frameworks used to assess technical, socio‐economic, and environmental aspects in policy analysis and the recent progress to portray distributional impacts in each of them. Furthermore, the main indicators produced by each method are highlighted and a critical review pointing to gaps and limitations that could be addressed by future research is presented.

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Income Distribution in Computable General Equilibrium Modeling

Cited by 57 publications

References 38 publications

Microsimulation and Policy Analysis

Microsimulation and Policy Analysis

Empirical Evidence Using Microsimulation Models in the Social Sciences

Beyond the Energy System: Modeling Frameworks Depicting Distributional Impacts for Interdisciplinary Policy Analysis

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