Taking the Global View

Taking the Global View Celebrating the advancing geographical reach and policy impact of EUROMOD

2

Taking the Global View | Centre for Microsimulation and Policy Analysis

Contents and contributors An introduction to CeMPA

3

Director’s view

4

The view beyond Europe: the SOUTHMOD project of UNU-WIDER

7

National models around the world

8

The distributional impact of tax and benefit systems in six African countries

10

Income inequality and income taxation in Latin America

13

Microsimulation in Indonesia: an in-house government research tool

14

Harnessing administrative data to model personal income tax options in South Africa

15

Europe through the crisis: discretionary policy changes and automatic stabilisers

16

The distributional effects of COVID-19 around the globe

18

Gantjang Amannullah Director of Welfare Statistics, Statistics Indonesia/ Badan Pusat Statistik Katrin Gasior, Senior Research Officer, University of Essex Dr Helen Barnes Senior Research Fellow, Southern African Social Policy Research Insights (SASPRI) Dr Chrysa Leventi Scientific Advisor – Economist, Council of Economic Advisors of the Greek Ministry of Finance Ali Moechtar Policy Analyst, Centre for Macroeconomic Policy, Ministry of Finance, Government of Indonesia Ratnawati Muyanto Social Policy Specialist, UNICEF Prof Michael Noble CBE Executive Director, SASPRI; and Emeritus Professor of Social Policy; University of Oxford Dr Alari Paulus Senior Economist, Bank of Estonia Prof Matteo Richiardi Director, CeMPA Prof Jukka Pirttilä Professor of Public Economics, University of Helsinki; and Non-Resident Senior Research Fellow, UNU-WIDER Wynnona Steyn Public Finance Specialist, South African Revenue Service.

Expertise: Public Finance.

Dr Iva Valentinova Tasseva Senior Research Officer, University of Essex Dr Holguer Xavier Jara Tamayo Research Fellow, University of Essex Prof Gemma Wright Research Director, SASPRI; and Professor Extraordinarius, Archie Mafeje Institute for Applied Social Policy Research at the University of South Africa (UNISA)

Centre for Microsimulation and Policy Analysis | Taking the Global View

An introduction to CeMPA At the beginning of June 2020 the University of Essex announced the creation of a new Centre for Microsimulation and Policy Analysis (CeMPA), based at the Institute for Social and Economic Research (ISER) CeMPA1 brings together the expert team at ISER with colleagues from different departments at the University of Essex, including Mathematics, Computer Science, Data Analytics, Sociology and Economics, joined by colleagues from leading institutions around the world.

CeMPA research on distributional issues, from tax and benefit systems to family, gender, health, wellbeing, and population change, focuses around two tools developed over the years and that are offered open source to the scientific community, with a wide range of models and applications: the static microsimulation platform EUROMOD, now jointly developed with the European Commission, and the dynamic microsimulation platform JAS-mine.

In the autumn of 2020, CeMPA will also launch the School for Advanced Microsimulation Studies to provide short courses on static and dynamic microsimulation modelling and agent-based modelling.

Microsimulation in the social sciences is structured around three approaches: • static modelling (mostly tax-benefit), tailored to short-term analyses with a fixed population • dynamic modelling, more geared towards long-term projections with an evolving population • agent-based modelling, focused on the effects of social and economic interactions between individual units.

CeMPA is in the unique position to be very strong in all these areas – a comprehensive home of microsimulation.

The activities of CeMPA are structured around three core streams: UKMOD and WORLDMODS, rooted in the static modelling approach; and DYNAMODS, evolving from the dynamic microsimulation and agent-based modelling tradition.

UKMOD and WORLDMODS follow directly from the EUROMOD experience and mark a new focus on non-EU models. DYNAMODS is a galaxy of dynamic models following common components, with the distinctive feature of integrating static tax-benefit calculators within a dynamic context and merging dynamic microsimulation and agent-based techniques.

A key feature of CeMPA, embedded in the EUROMOD and JAS-mine microsimulation tools, is a cross-country comparative perspective, now extended beyond the EU member states to reach a truly ‘global view’.

1 https://www.microsimulation.ac.uk

CeMPA brings together the expert team at ISER with colleagues from different departments at the University of Essex… joined by colleagues from leading institutions around the world.

3

4

Taking the Global View | Centre for Microsimulation and Policy Analysis

Director’s view This publication celebrates the advancing geographical reach and policy impact of EUROMOD, the tax-benefit microsimulation platform developed at CeMPA, and the platform now underpinning national models in over 40 countries

Prof Matteo Richiardi

EUROMOD’s flexibility, both of approach and software, means that it can be adapted to shortcut the process of building tax-benefit models with potentially comparable outputs for any country or region

Since 1996, and with generous funding from the European Commission’s DG-EMPL, EUROMOD has been developed as a taxbenefit microsimulation model for the European Union, growing in size as the bloc itself has grown, with coverage extending to all EU member states.

The European Commission has come to rely so much on EUROMOD that it has decided to directly involve two of its branches – Eurostat and the Joint Research Centre (JRC) in Seville – in the update and development of the policies and datasets for the EU member states, taking full responsibility for these models from 2021 onwards, while the platform itself will be co-developed between JRC and CeMPA. But EUROMOD is no longer just a platform for modelling the impacts of fiscal policy in the EU and its member states. EUROMOD’s flexibility, both of approach and software, means that it can be adapted to shortcut the process of building tax-benefit models with potentially comparable outputs for any country or region.

In recent years the EUROMOD platform has provided the technical infrastructure behind a brand new set of tax-benefit microsimulation models, beginning with the UK, and then expanding beyond Europe into the Global South. Thanks to funding from the Nuffield Foundation, we have built on the UK component of EUROMOD and improved its timeliness and regional coverage, among other things, reaching a large number of new users including local and devolved governments, parliament and devolved assemblies, public sector bodies, think tanks, research institutes and NGOs. Moreover, as part of the ongoing SOUTHMOD2 project funded by UNU-WIDER, EUROMOD provides the ‘engine’ that powers microsimulation models for seven countries: Ghana, Ethiopia, Zambia, Tanzania, Mozambique, Ecuador and Vietnam. The same project has also seen updates to existing EUROMOD-powered models for South Africa (SAMOD3) and Namibia (NAMOD4), managed by our long-term collaborators, Southern African Social Policy Research Insights (SASPRI5).

We have also been involved in the development of tax-benefit models for another six Latin American countries (Argentina, Bolivia, Colombia, Uruguay, Venezuela and Chile), as part of the LATINMOD project supported by CELAG (Centro Estratégico latinoamericano de Geopolítica) with funding by BANDES, the Venezuelan Economic and Social Development Bank, and other individual projects. CeMPA is also involved to various degrees in the development of taxbenefit models6 in countries as diverse as Russia and Indonesia.

2 https://www.iser.essex.ac.uk/research/projects/southmod-simulating-tax-and-benefit-policies-fordevelopment 3 https://www.saspri.org/research/micro-simulation/samod/index.html 4 https://saspri.org/SASPRI/research/micro-simulation/namod/index.html 5 https://www.saspri.org/index.html 6 A full list of the models based on the EUROMOD platform is available at https://www.microsimulation.ac.uk/euromod/models

ANTHONY CULLEN

Centre for Microsimulation and Policy Analysis | Taking the Global View

This line of research on EUROMOD-powered tax-benefit models constitutes a first, fundamental pillar of CeMPA – the second pillar being the development of dynamic models to study the effects of policies in the longer run.

Over the following pages, examples of analysis from each of the SOUTHMOD, LATINMOD and EUROMOD family of models are showcased.

In a study covering six of the African countries included in SOUTHMOD, Katrin Gasior reviews the effect of taxes and benefits on income inequality, finding that (aside from South Africa) tax-benefit systems currently do very little to reduce poverty. But perhaps this is not surprising in a continent where poverty has traditionally been measured in terms of consumption rather than income and where formal employment is much lower than in the West. Nevertheless, as living standards increase, income-based measures of poverty and inequality will become more important – and so will the modelling of the effects of taxes and benefits.

Next, Xavier Jara provides a similar overview of the (modest but not uniform) impact of fiscal systems on reducing income inequality in Latin America. He does so using recently-developed microsimulation models for Argentina, Bolivia, Colombia, Ecuador, Peru, Uruguay and Venezuela. A particularly interesting application in this analysis is a policy swap where Uruguay’s personal income

5

6

Taking the Global View | Centre for Microsimulation and Policy Analysis

I look forward to the consolidation of the new EUROMOD-powered taxbenefit microsimulation models of the Global South – they are in good hands! – and to the further expansion of the platform into Asia and beyond.

tax system is used to replace those in place in the other countries analysed, with varying redistributive effects.

Gemma Wright and colleagues provide a snapshot of work currently being undertaken in a different continent: the development of INDOMOD – a model for Indonesia – in Asia. Gemma also describes the evolving PITMOD project – a complement to the existing South African model, SAMOD, but which will instead run on anonymised individual-level personal income tax data which is held securely at South African Revenue Service (a project partner). As Gemma notes, there are major advantages to using administrative data as input data for existing microsimulation models, a practice that we are already seeing across several country models in the EU. Coming back to the ‘old continent’, Iva Tasseva and Alari Paulus’s analysis explores the fiscal policy response across the EU to the 2007-8 financial crisis and subsequent Great Recession, looking at the response in terms of discretionary policy changes and automatic stabilisers – built-in policy responses to changes to market incomes and population characteristics. Previously, there has been limited empirical evidence focusing on the role of the latter in terms of redistribution after an income shock and the analysis finds that across the EU member states neither response – discretionary change or automatic stabiliser – was sufficient on its own to redistribute incomes but, acting in tandem, the two responses were able to effect reductions in income inequality.

Over the page, we hear from UNU-WIDER’s Jukka Pirttilä about the challenges in establishing SOUTHMOD and the reasons for choosing EUROMOD as the model platform. Also engaging in SOUTHMOD from its conception has been SASPRI – the institution behind the pioneering SAMOD and NAMOD model and expert facilitators (and evangelists!) for much of the EUROMOD-powered tax-benefit microsimulation modelling development currently going on across African and Asian countries.

Finally, CeMPA (and individual CeMPA affiliates) have been very active in applying tax-benefit expertise to analyse the distributional effects of the COVID-19 crisis in many countries. This is crucial at a time of a massive, global economic shock, that has prompted unprecedented policy responses. In the last contribution to this publication I review our COVID-related work, including a project with UNU-WIDER and SASPRI that looks at the impact of the crisis in low and middle income countries.

In drawing to a close, I would like to pay tribute to UNU–WIDER for its contribution to the growth of the SOUTHMOD family of models, both in terms of financial and intellectual support.For the future, I look forward to the consolidation of the new EUROMOD-powered tax-benefit microsimulation models of the Global South – they are in good hands! – and to the further expansion of the platform into Asia and beyond.

Centre for Microsimulation and Policy Analysis | Taking the Global View

The view beyond Europe: the SOUTHMOD project of UNU-WIDER While microsimulation models have been routinely in use in high-income countries for decades, many developing countries have had access to much limited sets of analytical tools At the same time, developing countries have to increasingly rely on their own tax revenues for financing of necessary developmental spending, including the introduction of basic social protection systems.

Therefore, it seemed to us at UNU-WIDER that building up tax-benefit microsimulation models, and initiating research on the basis of the newly-built tools, would a be timely and relevant research project that the institute should champion. This led to the introduction of the SOUTHMOD7 project in 2015.

Why was EUROMOD chosen as a platform and the team maintaining it as a key collaborator? Several factors contributed to the choice. First, it was felt that microsimulation as carried out in EUROMOD was really meant to make modelling user friendly; something we thought would increase the likelihood the tool would be picked up by a varied set of users, not only academics. Second, the idea that the model and the material would be available free of charge for any non-commercial users was a must, given the ambition of the institute to offer open access to all its research. Third, as an international organisation, the idea of caring about comparability across countries, which was part of the EUROMOD genome, would cater well for cross-country learning. And finally, the fact that EUROMOD was already used as an example for modelling taxes and benefits outside of EU-countries, including in Africa by SASPRI8, demonstrated its capability and usefulness also for the wider audience.

Although we could piggyback on all the gained knowledge within the EUROMOD family, the project itself entailed a huge amount of work. Most of the challenges stemmed from the data side. While in Europe the model is underpinned by a harmonised household micro data set, the EU-SILC, African and other developing countries do not have the luxury of using a similar data source. The Living Standards Measurement Survey (LSMS) type of data sets that we use do share many similar features, but they still differ in many crucial ways when it comes to the details of key variables that the model requires. Another challenge was obtaining suitably disaggregated sector-level data for the purpose of external validation, that is, checking how the model performs in predicting key macro-level variables. This all meant that the comparability of the SOUTHMOD models, while improved very recently, naturally falls short of the level of the European models.

However, we would argue that the advantages of the decision to work with EUROMOD and the successes along the way clearly outweigh the challenges we faced. We have been impressed by the experience and know-how already embedded with the EUROMOD family, and the fact that all modelling innovations acquired there are directly available for us has been a huge advantage. We have been privileged to be able to put together fiscal policy experts from many developing and developed countries, and interesting research and analytical work has emerged on the basis of this collaboration. The current goals are to further support the use of the models in the existing countries, increase the country coverage, and via research activities push further the adaptation of tax-benefit microsimulation to the special circumstances of developing countries.

7 https://www.wider.unu.edu/project/southmod-simulating-tax-and-benefit-policies-development 8 https://www.saspri.org/

Prof Jukka Pirttilä

The advantages of the decision to work with EUROMOD and the successes along the way clearly outweigh the challenges we faced… we have been impressed by the experience and know-how already embedded

7

8

Taking the Global View | Centre for Microsimulation and Policy Analysis

National models around the world

Africa Ethiopia ETMOD (SOUTHMOD) Ethiopian Development Research Institute (EDRI), CeMPA, KU Leuven, and SASPRI Ghana GHAMOD (SOUTHMOD) University of Ghana, University of Tampere, and UNU-WIDER Malawi MAMOD (SOUTHMOD) Chimwemwe Magalasi, ISER

Tanzania TAZMOD (SOUTHMOD) University of Dar es Salaam and SASPRI Uganda UGAMOD (SOUTHMOD) Uganda Revenue Authority (URA), Makerere University, and SASPRI Zambia MicroZAMOD (SOUTHMOD) Zambia Institute for Policy Analysis and Research (ZIPAR) and SASPRI

Europe

Mozambique MOZMOD (SOUTHMOD) Ministry of Economy and Finance of Mozambique, and SASPRI

Austria EUROMOD-AT (SORESI) European Centre for Social Welfare Policy and Research

Namibia NAMOD (SOUTHMOD) SASPRI

Belgium EUROMOD-BE University of Antwerp and KU Leuven

South Africa SAMOD (SOUTHMOD) SASPRI

Bulgaria EUROMOD-BG University of National and World Economy, National Social Security Institute, and National Statistical Institute Croatia EUROMOD-HR (miCROmod) Institute of Public Finance (IPF) Cyprus EUROMOD-CY Ministry of Labour, Welfare and Social Insurance Czechia EUROMOD-CZ Center for Economic Research and Graduate Education – Economics Institute (CERGE-EI) Denmark EUROMOD-DK M. Azhar Hussain and Bent Greve Estonia EUROMOD-EE PRAXIS Center for Policy Studies

Centre for Microsimulation and Policy Analysis | Taking the Global View

Finland EUROMOD-FI Research Department of the Social Insurance Institution of Finland (Kela) France EUROMOD-FR Université de la Méditerranée, and Joint Research Centre-Seville Germany EUROMOD-DE Deutsches Institut für Wirtschaftsforschung (DIW Berlin) Greece EUROMOD-EL Athens University of Economics and Business (AUEB), Politecnico Di Milano (PDM), Bank of Greece (BoG), and Council of Economic Advisors of the Greek Ministry of Finance (CEA)

Netherlands EUROMOD-NT CentERdata Poland EUROMOD-PL Centre for Economic Analysis (CenEA) Portugal EUROMOD-PT Lisboa School of Economics & Management, Portuguese Statistics Office and Universidade de Lisboa Romania EUROMOD-RO National Scientific Research Institute in the field of Labour and Social Protection (INCSMPS) Slovakia EUROMOD-SK Ministry of Finance

Hungary EUROMOD-HU TÁRKI Social Research Institute

Slovenia EUROMOD-SI Inštitut Za Ekonomska Raziskovanja (IER), and University of Ljubljana

Ireland EUROMOD-IE Economic and Social Research Institute (ESRI)

Spain EUROMOD-ES Instituto de Estudios Fiscales

Italy EUROMOD-IT University of Milan and University of Insubria Latvia EUROMOD-LV Baltic International Centre for Economic Policy Studies (BICEPS) Lithuania EUROMOD-LT Vilnius University Luxembourg EUROMOD-LU Luxembourg Institute of SocioEconomic Research (LISER) Malta EUROMOD-MT Ministry of Finance

Sweden EUROMOD-SE Ministry of Health and Social Affairs, and Statistics Sweden UK EUROMOD-UK (UKMOD) Centre for Microsimulation and Policy Analysis (CeMPA) Russia RUSMOD Daria Popova and Mikhail Matytsin

North America Mexico LATINMOD-Mexico Luis Huesca, Centro de Investigación en Alimentación y Desarrollo (CIAD) and Linda Llamas, Univerdad Estatal de Sonora

9

South America Argentina LATINMOD-Argentina Mariana Dondo- CIETES- Universidad Nacional de Río Negro- Sede Andina BoliviA LATINMOD-Bolivia Cristina Arancibia Romero and David Macas Romero Chile CHILMOD Centre for Social Conflict and Cohesion Studies (Universidad de Chile), Centre for Economics and Social Policy (CEAS, Universidad Mayor), Millennium Nucleus of Social Development, and Faculty of Economics at Universidad de Chile Colombia COLMOD David Rodriguez, ISER and Externado de Colombia University Ecuador ECUAMOD (SOUTHMOD) H. Xavier Jara (CeMPA), Leonardo Vera, Fernando Martín and Lourdes Montesdeoca (FLACSO) Peru PERUMOD Javier Torres, Universidad del Pacífico Uruguay LATINMOD-Uruguay Rebeca Riella and Joana Urraburu Venezuela LATINMOD-Venezuela Nicolás Oliva, CELAG

Asia Indonesia INDOMOD Indonesian Ministry of Finance, UNICEF Indonesia, SASPRI Vietnam VNMOD (SOUTHMOD) CIEM and KU Leuven

10

Taking the Global View | Centre for Microsimulation and Policy Analysis

The distributional impact of tax and benefit systems in six African countries At the core of the African Union’s agenda is a prosperous Africa based on Inclusive Growth and Sustainable Development, which – among others – should be achieved through better social security systems Katrin Gasior

Dr Chrysa Leventi

Prof Michael Noble CBE

Prof Gemma Wright

Dr Helen Barnes

This, however, requires better knowledge of current systems in place and the extent they provide support and contribute to redistribution. This contribution provides such an assessment for Ethiopia, Ghana, Mozambique, South Africa, Tanzania and Zambia – using the SOUTHMOD tax-benefit models.

Poverty and inequality in this part of the world is mostly measured using consumption data.

This is justified by the high importance of ownconsumption and the low share of people in employment but at the same time fails: • to measure direct effect of taxes and benefits reflected in the level of disposable income; and • to acknowledge that households with similar consumption levels might have very different income levels (e.g. one household might need to spend 100% of the income while another one manages to save).

The percentage of countries using income to measure poverty has risen over time and is associated with rising living standards (World Bank 20189). Accordingly, income-based measures for low- and middle-income countries provide important opportunities for measuring in-country progress. Our research presents indicators using different income concepts – see Figure 1.

The concept of post-fiscal income shows how much of their disposable income individuals are able to consume by also accounting for indirect taxes (in this case Value Added Tax only).

Overall, the country with the most effective tax–benefit system in terms of reducing income inequality is South Africa, while the tax-benefit system has almost no impact on inequality in Ghana and Mozambique (see Figure 2, compare Gini using original income and disposable income). With respect to poverty, using the $1.90 per day poverty threshold, South Africa also has the most poverty-reducing tax–benefit system.

Alarmingly, the other five countries’ tax–benefit systems have no poverty-reducing properties (see

Figure 3, compare poverty using original income and disposable income).

Why do the tax–benefit systems of these countries appear to be mostly ineffective? Our results suggest that with the exception of South Africa, the tax–benefit policies affect only a small minority of each country’s population.

Many individuals will be largely unaffected by the tax-benefit system, apart from indirect taxes: the benefits are very narrowly targeted and their amounts are small, and many individuals are too poor to pay direct taxes. In the context of the Sustainable Development Goals to eradicate extreme poverty by 2030 (Goal 1.1) and to achieve substantial coverage of social protection for the poor and vulnerable (Goal 1.3), it is clear that more needs to be done.

With respect to VAT, it was found that this policy increases income inequality in all six countries, the most extreme example being Tanzania. VAT also increases income poverty in all countries, with the highest increase being estimated for South Africa. This is not in itself surprising, as VAT is widely regarded to be a regressive tax, but it demonstrates the role that VAT plays in diluting (or even reversing) the impact of direct taxes and benefits. Regarding direct taxation, Ethiopia’s personal income tax system appears to be the most income-inequalityreducing (see Figure 2, compare Gini using original income plus pensions and benefits and disposable income).

As observed by the World Bank, ‘it has to be acknowledged that the use of income data is likely to lead to a higher estimated poverty count’ (World Bank 2016, 4010). Results indeed show that the income-based measures result in higher levels of poverty and inequality than consumption-based measures.

Contribution based on Gasior, Katrin, Chrysa Leventi, Michael Noble, Gemma Wright, and Helen Barnes. 2018. ‘The Distributional Impact of Tax and Benefit Systems in Six African Countries’. WIDER Working Paper, WIDER Working Paper, 2018/155.

9 World Bank. 2016. Monitoring Global Poverty: Report of the Commission on Global Poverty. Washington, DC: The World Bank 10 World Bank. 2018. Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle. Washington, DC: The World Bank

Centre for Microsimulation and Policy Analysis | Taking the Global View

11

Figure 1 Different income concepts used in the research Original income

Employment income; self-employed income (inc. farming) and other market incomes

Disposable income

+ Benefits (cash and in-kind) - Direct taxes - SIC

Post-fiscal income

- VAT

Consumption

Including direct taxes

Why do the tax–benefit systems of these countries appear to be mostly ineffective?

Our results suggest that with the exception of South Africa, the tax–benefit policies affect only a small minority of each country’s population

Figure 2 Gini index: 0 indicates low inequality, 100 indicates high inequality

Information for Figures 2 and 3: Source Authors’ representation based on SOUTHMOD models. Poverty rate based on consumption retrieved from WDI, World Bank database. Notes Results are based on the policy system 2015. Results for consumption (WDI) refer to different years (2015 for Ethiopia and Zambia, 2016 for Ghana, 2014 for Mozambique and South Africa, 2011 for Tanzania).

ROD WADDINGTON

Figure 3 Poverty: percentage of people with less than $1.90 per day

12

Taking the Global View | Centre for Microsimulation and Policy Analysis

Modelling the tax-benefit system and understanding its potentiality in reducing income inequality and poverty is a necessary first step to consider public policy reforms in Latin America

DIEGO DELSO

Centre for Microsimulation and Policy Analysis | Taking the Global View

13

Income inequality and income taxation in Latin America Latin America remains one of the most unequal regions in the world and the fiscal system shows modest effects in reducing income inequality On average, the tax benefit systems in Latin America decrease inequality, measured by the Gini coefficient, by around 3 percentage points; while it does by around 20 points on average in the European Union. The limited effect of personal income tax has been highlighted as one of the main factors contributing to the modest redistributive role of policies in the region.

Cross-country characterisations and comparisons of the redistributive role of tax-benefit policies in Latin America require flexible and harmonised microsimulation models. The recent development of such models, under the modelling structure of EUROMOD, has enabled to assess the extent to which differences in the design of tax-benefit policies explain differences in inequality across countries.

Tax-benefit microsimulation models for Latin America include so far Argentina, Bolivia, Colombia, Ecuador, Peru, Uruguay and Venezuela, with others under development (Paraguay and Mexico). In addition to their academic value, these models represent powerful tools to enable governments to assess the margins they have to enhance social protection and increase fiscal capacity.

Our results show a wide variation in the redistributive role of tax-benefits systems across Latin America11. Bolivia and Colombia, which present the highest levels of income inequality, are also characterised by limited redistribution from the tax-benefit system, with inequality decreasing by less than 3 percentage points after taxes and benefits.

In contrast, the less unequal country, Uruguay, is also that with the most redistributive tax-benefit system, with inequality decreasing by 9 percentage points

when measured by the difference between the Gini coefficient from market income relative to disposable income’s Gini.

Our work further exploits the advantages of harmonised multi-country microsimulation techniques to focus on the potential of personal income tax to reduce inequality in the region. More precisely, we simulate a counterfactual scenario where Uruguay’s (the most redistributive country) personal income tax system replaces national personal income tax systems in all other countries.

Applying the Uruguayan personal income tax to other countries increases the redistributive effect of tax-benefit systems, although to different degrees. Uruguay’s personal income tax would have a particularly important effect in Venezuela, where inequality would decrease by 1.06 percentage points. Argentina, Colombia and Bolivia would also experience a decrease in income inequality but by a lower 0.15, 0.14, and 0.53 percentage points respectively. In Ecuador, this swap would have no major effect. The main drivers of the effects are the differences in the value of the exempted tax threshold, and the prevalence of tax deductions.

Modelling the tax-benefit system and understanding its potentiality in reducing income inequality and poverty is a necessary first step to consider public policy reforms in Latin America.

The development of harmonised tax-benefit microsimulation models for Latin America goes in this direction and aims at providing evidence to design reforms to improve the redistributive impact of the tax and social protection systems in the region, by learning from the comparative analysis between systems of different countries.

11 The results are based on: Arancibia, C., M. Dondo, H. X. Jara, D. Macas, N. Oliva, R. Riella, D. Rodriguez, and J. Urraburu (2019).

Income Redistribution In Latin America: A Microsimulation Approach. WIDER Working Paper 2019/1. Helsinki: UNU-WIDER.

Dr Holguer Xavier Jara Tamayo

14

Taking the Global View | Centre for Microsimulation and Policy Analysis

Microsimulation in Indonesia: an in-house government research tool A new tax-benefit microsimulation model for Indonesia called INDOMOD was built in 2019 using the EUROMOD software

Ali Moechtar

Gantjang Amannullah

Ratnawati Muyanto

The project was coordinated by the Ministry of Finance of the Government of Indonesia, which convened a Working Group comprising representatives of key government departments including Statistics Indonesia.

UNICEF Indonesia and Southern African Social Policy Research Insights (SASPRI) a not-for-profit organisation in the United Kingdom, entered into an agreement to support the Government of Indonesia in building INDOMOD. As well as granting permission for the EUROMOD software to be used for this purpose, the EUROMOD team at the University of Essex also provided technical advice while INDOMOD was being built.

INDOMOD was constructed for use as an in-house research tool for the Government of Indonesia. It is underpinned by a dataset that was constructed from SUSENAS (the National Socio-Economic Survey/ Survei Sosial Ekonomi Nasional) for 2018 which was made especially available for this purpose by Statistics Indonesia.

The survey contains almost 300,000 households and 1.1 million individuals. As a result of recent enhancements that have been made to the EUROMOD software by the EUROMOD team, the software was able to accommodate such a large dataset without any difficulties.

The first training event for civil servants took place in Jakarta in July 2019, and the project is

set to continue throughout 2020. INDOMOD will be updated to incorporate national tax and benefit policies for 2019 and 2020; a new SUSENAS dataset for 2019 will be prepared as an underpinning dataset; and the Government of Indonesia’s response packages to the Covid-19 pandemic will be simulated under various assumptions of its potential impact.

Although INDOMOD currently only simulates national tax and benefit policies, the relevant province-level tax and benefit policies will be added to the model during 2020 for five case study provinces: Aceh, Nusa Tenggara Barat, Sulawesi Selatan, Sumatera Selatan, and Yogyakarta. This last activity will involve close collaboration with stakeholders at the level of provincial government and so will raise awareness of INDOMOD across the country.

This new model marks an important addition to the suite of models internationally that make use of the EUROMOD software. Not only is Indonesia probably the largest country to use the EUROMOD software, with a population of 267 million people, but it also comprises around six thousand inhabited islands with a wide range of living standards and cultural diversity. INDOMOD is already being used to explore poverty reduction options that will support the wellbeing of children across Indonesia, and there is a strong commitment to ensure sustainability of the model.

AMELIA GUO

Centre for Microsimulation and Policy Analysis | Taking the Global View

15

Harnessing administrative data to model personal income tax options in South Africa A new project has just started which involves building a model for South Africa’s personal income tax policy – to be called ‘PITMOD’

12 https://www.sars.gov.za/Pages/default.aspx 13 https://www.saspri.org/ 14 https://www.wider.unu.edu/ 15 https://www.euromod.ac.uk/ 16 http://sa-tied.wider.unu.edu/ 17 http://sa-tied.wider.unu.edu/data 18 http://www.treasury.gov.za/

also be enhanced by the EUROMOD team to provide a selection of automated analysis outputs that are tailored for personal income tax. Ultimately the intention is that other tax administrative data would also be brought on to the EUROMOD platform including Corporate Income Tax, Value-Added Tax, and customs duties.

The PITMOD project has been co-designed

by SARS and SASPRI and will be undertaken and published collaboratively. In addition to creating an in-house model for SARS’s use, there is a commitment to place a simplified version of PITMOD in a secure data room17 at the National Treasury18 for use by the research community.

The PITMOD project takes its inspiration from innovations that have made use of EUROMOD and administrative data, especially in Greece.

There is great potential for sharing this knowledge with other African countries that are keen to make best use of their often-constrained tax revenues, including in Uganda.

The PITMOD project takes its inspiration from innovations that have made use of EUROMOD and administrative data, especially in Greece

SA-TIED

This project is a collaboration between the South African Revenue Service (SARS)12, researchers at the not-for-profit organisation Southern African Social Policy Research Insights (SASPRI)13, and the United Nations University World Institute for Development Economics Research (UNU-WIDER)14, with support from the EUROMOD15 team at the University of Essex.

The project is part of a large initiative called the Southern Africa – Towards Inclusive Economic Development16 programme. The SA-TIED programme identifies ways to support policymaking for inclusive growth and economic transformation in the southern Africa region through original research.

The new PITMOD model will complement an existing tax-benefit microsimulation model – called ‘SAMOD’ - which is underpinned by nationally representative household survey data.

PITMOD will be underpinned by anonymised individual-level personal income tax data which is held securely at SARS. A major advantage of using administrative data is that a much finer level of detail can be obtained about income sources than when using survey data, and so the full suite of personal income tax policy rules can be applied. This will yield more detailed understanding of the impact of the current policy rules, as well as the first order effects of potential policy reforms.

Like SAMOD, PITMOD will be run using the EUROMOD software, resulting not only in greater flexibility and functionality, but also a group of users who can use both surveybased and administrative-based models. The EUROMOD platform will enable updates and reforms options to be conducted in-house, transparently and in a standardised way.

EUROMOD’s statistics presenter software will

Prof Gemma Wright

Wynnona Steyn

16

Taking the Global View | Centre for Microsimulation and Policy Analysis

Europe through the crisis: discretionary policy changes and automatic stabilisers The financial crisis of 2007-08 and the subsequent Great Recession posed serious economic challenges to Europe

Dr Alari Paulus

Dr Iva Valentinova Tasseva

Substantial increases to unemployment, losses to wages and self-employment income, increase in governments debt and fall in GDP put strain on fiscal budgets and households’ finances.

In response to such economic challenges, tax-benefit policies have important implications for household net incomes. They affect incomes through two main channels: discretionary policy changes and automatic stabilisers.

Automatic stabilisers characterise the policies’ in-built flexibility to absorb shocks to earnings and people’s characteristics. A large body of literature has shown the importance of discretionary policy changes for the income distribution. But there is little empirical evidence on the redistributive power of automatic stabilisers.

With our paper, we aim to contribute to improved understanding of the link between automatic stabilisers and the income distribution by providing an in-depth account of the relative impact of automatic stabilisers and discretionary policy changes on household incomes between 2007 and 2014 in the EU. Using the tax-benefit model EUROMOD and household micro-data, we decompose changes in the income distribution into: • discretionary tax-benefit policy changes • the automatic stabilisation response of tax-benefit policies, and • gross market incomes and population changes.

We find that, first, discretionary policy changes raised incomes on average in about two thirds of countries and lowered them in the remaining third. In comparison, on average automatic

ANTHONY CULLEN

Centre for Microsimulation and Policy Analysis | Taking the Global View

Figure 1 Decomposition of the change in the Gini coefficient

Notes Countries are ranked by the total change in the Gini coefficient. Changes to incomes are estimated in real terms. The reference period is 2007-2014 for nearly all countries and 2011-2014 for Croatia. Source Own calculations with EUROMOD and EU-SILC/FRS

Figure 2 Decomposition of the percentage change in the Gini coefficient by type of policy instrument

Notes dpc=discretionary policy changes; as=automatic stabilisers. The total change and market income/population effect are omitted. Changes to incomes are estimated in real terms. The reference period is 2007-2014 for nearly all countries and 2011-2014 for Croatia. Source Own calculations with EUROMOD and EU-SILC/FRS.

Substantial increases to unemployment, losses to wages and self-employment income, increase in governments debt and fall in GDP put strain on fiscal budgets and households’ finances

17

stabilisers – responding to changes to market incomes and population characteristics – led to income gains in about a third, losses in another third of countries and no statistically significant changes in the remaining third.

In terms of income inequality, discretionary policy changes lowered it in more than two thirds of countries (see Figure 1). Progressive policy changes were implemented not only in countries where the welfare state expanded in size but also in countries, which implemented fiscal consolidation measures in the economic downturn. Automatic stabilisers had a statistically significant impact on inequality in about half of countries, lowering inequality in most of them (see Figure 1).

Second, discretionary policy changes to benefits – by increasing their level – and the automatic stabilisation response of benefits – mostly to income losses at the bottom of the distribution – were the main instruments raising the incomes of low-income households and narrowing the gap between rich and poor. Policy changes to and the automatic stabilisation response of taxes/ SIC had a mixed effect on the income distribution of the EU countries (see Figure 2). We find that changes in net income due to the stabilisation response of taxes/SIC were negatively associated with changes to market incomes and population characteristics. However, there was effectively no country-level correlation between the latter and the stabilisation response of benefits. Compared to taxes/SIC, benefits are overall more responsive to changes in the population structure (such as household composition changes) than changes in market income.

Third, in terms of prevalence, discretionary policy changes lowered inequality in more countries than automatic stabilisers. But in terms of the size of the effects, we cannot conclude that policy changes contributed to inequality reduction more than automatic stabilisers, or vice versa. Thus, our findings show the importance of both discretionary policy changes and automatic stabilisers to redistribute incomes.

The paper is forthcoming at the Oxford Bulletin of Economics and Statistics.19 19 https://onlinelibrary.wiley.com/doi/full/10.1111/ obes.12354

18

Taking the Global View | Centre for Microsimulation and Policy Analysis

The distributional effects of COVID-19 around the globe

ŽUPABA VUCBA

The COVID-19 crisis has impacted people’s lives around the globe dramatically, hitting different countries asymmetrically due to differences in the health response, in the economic structure, and in the policy response aimed at reducing the effects of the first on the latter Also, within countries COVID-19 has exposed old and new divides in society.

While the health emergency has initially brought people together, and the solidarity moment has resulted in robust policy responses in some countries, cracks are starting to appear and scars are visible that impact different groups differently.

Elderly people (in particular the frail elderly) are more exposed to the health risk, but it is younger people who have suffered more in the labour market, and adolescents and children who have lost precious time for socialising and learning.

Estimates and early evidence show that each month of lockdown shrinks advanced economies by around 2% on an annual basis (OECD, 2020).

Developing countries are particularly exposed to the virus due to the weaker healthcare and welfare systems in place, the risks of famine, volatile commodity prices, and the low standards of living which make it much harder for people to keep safe. It has been estimated that 81 percent of the world’s workforce is affected by lockdown measures (ILO, 2020), that poverty could increase globally by half a billion people (Sumner et al., 2020), that Africa will be hit by at least $100 billion in economic costs this year (te Velde, 2020), and that Latin America will experience a contraction of more than 5% of GDP (ECLAC,

2020). While in advanced economies many have switched to working from home, family tasks have not always been shared equally between partners, with women taking on their shoulders a larger share of the new burden of taking care of young children in absence of childcare, monitoring attendance at online lessons and classes, checking homework, preparing meals and attending the extra housekeeping required by more crowded homes. By contrast, in developing economies the restrictions have pushed even more people into the informal sector, wiping out years of slow and painful advances towards extending basic guarantees to all workers.

Businesses have gone bankrupt, in some sectors more than in others. Workers in those sectors have seen their prospects reduced dramatically, at a time when mobility between jobs and new vacancy openings in other sectors have also gone down. In Europe, increased reliance on public support is undermined by the dynamics of debt accumulation, which although mitigated by the unprecedented, powerful interventions set out at the EU level (from the ECB’s PEPP to the Next Generation EU recovery instrument), will have to be repaid in the end. This may increase the likelihood of other rounds of austerity in the years to come, with possible dire consequences on the most vulnerable people in society.

Centre for Microsimulation and Policy Analysis | Taking the Global View

In the face of these unprecedented challenges, it is vital that distributional consequences are swiftly analysed, to inform policy changes that are also happening at an unprecedented scale. Taxbenefit microsimulation modelling then becomes a crucial tool. However, tax-benefit models apply the tax and benefit legislation to an observed input population, typically derived from nationally representative survey data. These obviously do not reflect the impact of COVID-19 and related lock-down measures on employment and market incomes. To model the distributional effects of COVID-19, the input data have therefore to be adjusted. This nowcasting exercise is a crucial step that can be undertaken using information from external sources such as government forecasting or expert scenarios, early evidence at the aggregate or semi-aggregate level, or by means of macro models. A similar approach is being used by the European Commission to produce Flash Estimates on changes in poverty and income distribution based on a methodology developed by the University of Essex team (Gasior and Rastrigina, 201720; Leventi et al, 201721).

Some results based on the EUROMOD platform have started to appear. In the UK, Bronka et al. (2020)22 develop an input-output model to estimate the size of the employment shock by industry, distribute the sectoral shock to individual workers according to their characteristics, and then make scenario assumptions about the path of recovery from the crisis. They find that the economy contracts by around a quarter in lock-down, a result confirmed by aggregate data for April 2020, but they also find that the emergency measures put in place by the Government are effective in protecting household incomes, especially at the bottom of the income distribution, where the increased generosity of social assistance schemes even improves the

outlook for some individuals. This however comes at a huge cost for the Government, calling into question whether the extended safety net will remain in place for long enough, as well as whether other forms of support will be withdrawn in an effort to reduce the size of the public deficit. Brewer and Tasseva (2020)23 focus on analysing the distributional impact of the crisis in late April 2020. They also find substantial income losses (around 8% net of the support schemes), confirming the earlier projections of Bronka et al., and little effects on inequality due to the generosity of the emergency measures. A similar pattern – substantial market income losses significantly attenuated by public support schemes at a high cost for the public budget – is found for Ireland (Beirne et al., 202024), while in Italy the effects on inequality and poverty are projected to be more pronounced, with an increase in the poverty risk of 15 percentage points among individuals affected by the lock-down and more than 8 percentage points considering the overall population (Figari and Fiorio, 2020)25.

In a new project, researchers at UNU-WIDER, SASPRI and CeMPA are starting to explore the implications of the COVID-19 crisis for low and middle income countries. Due to lack of timely data, they are following the approach of Bronka et al. (2020) and model the size of the economic shock in the SOUTHMOD countries based on detailed input-output tables and scenario assumptions validated by country experts. They will then use the SOUTHMOD tax-benefit models updated with the most recent policy measures to analyse the distributional and budgetary costs of the crisis. A similar analysis is also carried out for Indonesia using INDOMOD. Other exercises based on EUROMOD are being undertaken in other countries, and they will be reported in the special COVID-19 section of the new CeMPA website26.

20 Gasior K, Rastrigina O (2017). Nowcasting: timely indicators for monitoring risk of poverty in 2014 -2016. EUROMOD Working Paper EM7/17 21 Leventi C, Rastrigina O, Sutherland H, Navicke J (2017). Nowcasting risk of poverty in the European Union in Atkinson AB, Guio, AC and Marlier E. (eds) Monitoring social inclusion in Europe. Eurostat: Luxembourg, 353-363.

22 Bronka P, Collado D, Richiardi M (2020). The Covid-19 crisis response helps the poor: The distributional and budgetary consequences of the UK lockdown. Covid Economics 26: 79-106 23 Brewer M, Tasseva I (2020). Did the UK policy response to Covid-19 protect household incomes? EUROMOD Working Paper 12/20 24 Beirne K, Doorley K, Regan M, Roantree B, Tuda D (2020). The potential costs and distributional effect of Covid-19 related unemployment in Ireland. EUROMOD Working Paper 5/20 25 Figari F, Fiorio C (2020). Welfare Resilience in the Immediate Aftermath of the Covid-19 Outbreak in Italy. Covid Economics 8: 92-119 26 https://www.microsimulation.ac.uk/research-and-policy-analysis/covid-19

19

Prof Matteo Richiardi

Centre for Microsimulation and Policy Analysis Institute for Social and Economic Research University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ, UK Telephone +44 (0)1206 872957 Visit our website for the latest working papers, events, training and to sign up for news at www.microsimulation.ac.uk Š CeMPA July 2020