# **3.2 Decomposition approach**

The analysis furthermore applies a decomposition approach that helps to quantify the extent to which household incomes were cushioned by automatic stabilizers versus emergency benefits and policy changes introduced during the COVID-19 pandemic, and to assess the lack of sufficient support to fully absorb the shock on labor incomes. Following similar approaches to those by Paulus and Tasseva (2020) and Bargain and Callan (2010), we simulate four scenarios to quantify the contribution of different factors to changes in income distribution amid the COVID-19 pandemic. Table 1 provides an overview of the simulated scenarios.

Scenario A captures the income distribution during the COVID-19 pandemic, namely, it reflects the labor market situation during COVID-19 and takes into account all policies in place during the pandemic. On the other side of the spectrum, Scenario D represents the pre-COVID-19 scenario, meaning that we do not take into account COVID-19-related labor market and policy changes. Scenario B and C provide two in-between counterfactual scenarios where COVID-19-related labor market changes are applied but not all COVID-19-related policy changes are considered. Scenario B only considers monetary compensation schemes but no additionally implemented policy changes. Other COVID-19-related policies refer for example to increases in existing unemployment or social assistance schemes, additional lump-sum benefits for specific groups or COVID-19-specific tax and SIC changes (see Table B2 in the Appendix for a country-specific overview of other measures). Scenario C does not consider any policy interventions to the COVID-19 pandemic. In the latter scenario, we assume that everyone who was selected to transition to a monetary compensation scheme in scenario A is transitioned to unemployment for the duration of being in the monetary compensation scheme in the absence of such monetary compensation schemes. This is an artificial extreme scenario as we do not know the counterfactual reality without the monetary compensation schemes. However, it allows to show the extent to which existing unemployment benefits and other related policies would have been able to cushion the shock as well as the extent the new schemes provided additional support.

_Table 1: Overview of simulated scenarios_

|**Scenario**|**Policy changes**|**Input dataset**|**EUROMOD**|
|---|---|---|---|
|A COVID|All COVID and non-<br>COVID related policy<br>changes|Adjusted for COVID-related<br>labor market changes|LMA Add-on|
|B COVID with<br>monetary<br>compensation<br>schemes|All non-COVID related<br>policy changes plus<br>newly introduced<br>monetary<br>compensation schemes|Adjusted for COVID-related<br>labor market changes|New extension to<br>switch non-<br>compensation<br>scheme related<br>policychanges off|
|C COVID<br>without<br>COVID-<br>related policy<br>changes|Non-COVID related<br>policy changes only|Adjusted for COVID-related<br>labor market changes. Employees<br>and self-employed selected to<br>transition to the monetary<br>compensation scheme are re-<br>transitioned to unemployment|New Add-on based<br>on LMA Add-on<br>for re-transition to<br>unemployment|
|D No COVID|Non-COVID related<br>policy changes only|No adjustment for COVID-<br>related labor market changes|New extension to<br>switch all COVID-<br>related policy<br>changes off|

Source: Author’s elaboration 7