Tell us a bit about you - what is your background?

Karina Doorley: I am a labour/public economist. I have been working at the ESRI since 2017 and heading up the Tax Welfare and Pensions team (and the Irish EUROMOD country team) since 2021. My PhD (from University College Dublin) investigated the impact of tax and welfare policy on redistribution and labour supply. I spent much of my early career in Luxembourg (at the Luxembourg Institute for Socio-Economic Research - LISER) and Germany (at the Institute for Labor Studies - IZA) before moving back to Ireland in 2017.

Luke Duggan: I joined the ESRI and the Irish national team in June 2022, after completing degrees in economics and social data science at Trinity College Dublin. My main research interests are in theoretical and applied microeconomics, e.g., my Masters thesis estimated and tested hypotheses on consumer demand systems using Irish data.

Michael Doolan: I have been a research assistant at the Economic and Social Research Institute since September 2021 and I am part of the EUROMOD National Team for Ireland. I hold a Masters degree in Quantitative Economics from University College Dublin. My interests lie in public economics, in particular, the redistributive and work incentive effects of taxation and welfare policy in Ireland.

When and what was your first contact with EUROMOD?

Karina Doorley: I first used EUROMOD for my Masters thesis in 2008 to investigate the redistributive effect of the Family Income Supplement in Ireland and the Working Families Tax Credit in the UK. I remember being amazed at how functional the model was as well as completely stuck when it bugged (which was often!). I then became a member of the French country team while a doctoral student before joining the Irish country team in 2019.

Luke Duggan: I first encountered EUROMOD upon joining the Irish national team, taking the training course offered by the Fiscal Policy Analysis Unit at the Joint Research Centre. I found the exercises particularly useful for getting up to speed with the model quickly.

Michael Doolan: My first contact with EUROMOD came upon joining the ESRI. I used EUROMOD to analyse the work incentive effects of the Irish Housing Assistance Payment. I was really impressed with both the extensive nature of its policy systems and the ease of use of the user interface.

What are your main responsibilities and what is your experience with EUROMOD?

Karina Doorley: I co-ordinate the Irish country team work and weigh in for the validation towards the end of the cycle. At the ESRI, we also maintain and develop a national model, based on the EUROMOD platform, called SWITCH. SWITCH is based on a more detailed version of SILC, which allows for more detailed modelling. I think that maintaining the two models in tandem helps with the accuracy of both.

Luke Duggan: I help with various tasks in keeping the model accurate, such as updating the spine when new policies are implemented and revising uprating factors to make the underlying SILC as faithful as possible to the current population.

Michael Doolan: As part of the Irish National Team, I have been responsible for amending uprating factors, the macrovalidation of EUROMOD output and drafting the Country Report. I’ve also updated the policy systems of the Irish national model SWITCH, which is based on the EUROMOD platform, and have used SWITCH for the analysis of Irish policy reforms. The capabilities and simplicity of EUROMOD and its add-ons has amazed me. Working with staff at the JRC has also been a pleasure and the support and training they provide is always most helpful.

Would you like to share any recent highlights for your country?

Between 2019 and 2020, the ESRI overhauled its national model, SWITCH, so that it is now based on the EUROMOD platform. This has increased the flexibility of SWITCH while allowing for more straightforward cross-country comparisons. SWITCH is based on a more detailed version of SILC, linked to administrative information, which allows for more extensive modelling e.g. non-cash benefits. Maintaining the two models in tandem definitely helps with the accuracy of both.