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The COVID-19 resilience of a continental welfare regime - nowcasting the distributional impact of the crisis.

ABSTRACT: We evaluate the COVID-19 resilience of a Continental welfare regime by nowcasting the implications of the shock and its associated policy responses on the distribution of household incomes over the whole of 2020. Our approach relies on a dynamic microsimulation modelling that combines a household income generation model estimated on the latest EU-SILC wave with novel nowcasting techniques to calibrate the simulations using external macro controls which reflect the macroeconomic climate during the crisis. We focus on Luxembourg, a country that introduced minor tweaks to the existing tax-benefit system, which has a strong social insurance focus that gave certainty during the crisis. We find the system was well-equipped ahead of the crisis to cushion household incomes against job losses. The income-support policy changes were effective in cushioning household incomes and mitigating an increase in income inequality, allowing average household disposable income and inequality levels to bounce back to pre-crisis levels in the last quarter of 2020. The share of labour incomes dropped, but was compensated by an increase in benefits, reflecting the cushioning effect of the transfer system. Overall market incomes dropped and became more unequal. Their disequalizing evolution was matched by an increase in redistribution, driven by an increase in the generosity of benefits and larger access to benefits. The nowcasting model is a "near" real-time analysis and decision support tool to monitor the recovery, scalable to other countries with high applicability for policymakers.

Supplementary information

The online version contains supplementary material available at doi:10.1007/s10888-021-09524-4.

SUBMITTER: Sologon DM

PROVIDER: S-EPMC8861260 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Rationale Due to lack of vaccine or cure, the COVID-19 pandemic presents a threat to all human beings, undermining people's basic sense of safety and increasing distress symptoms. Objective To investigate the extent to which individual resilience, well-being and demographic characteristics may predict two indicators of Coronavirus pandemic: distress symptoms and perceived danger. Method Two independent samples were employed: 1) 605 respondents recruited through an internet panel company; 2) 741 respondents recruited through social media, using snowball sampling. Both samples filled a structured online questionnaire. Correlations between psychological/demographic variables and distress and perceived danger were examined. Path analysis was conducted to identify predictive indicators of distress and perceived danger. Results Significant negative correlations were found between individual/community resilience and sense of danger (?0.220 and ?0.255 respectively; p < .001) and distress symptoms (- 0.398 and ?0.544 respectively; p < .001). Significant positive correlations were found between gender, community size, economic difficulties and sense of danger (0.192, 0.117 and 0.244 respectively; p < .001). Gender and economic difficulties also positively correlated with distress symptoms (0.130 and 0.214 respectively; p < .001). Path analysis revealed that all paths were significant (p < .008 to .001) except between family income and distress symptoms (p = .12). The seven predictors explained 20% of sense of danger variance and 34% the distress symptoms variance. The most highly predictive indicators were the two psychological characteristics, individual resilience, and well-being. Age, gender, community size, and economic difficulties due to COVID-19 further add to predicting distress, while community and national resilience do not. . Conclusions Individual resilience and well-being have been found as the first and foremost predictors of COVID-19 anxiety. Though both predictors are complex and may be influenced by many factors, given the potential return of COVID-19 threat and other future health pandemic threats to our world, we must rethink and develop ways to reinforce them. Highlights • Current study was conducted during a peak in the COVID-19 pandemic, 1st wave.• Two pandemic effects, distress symptoms and perceived danger, were examined.• Best pandemic effect psychological predictors: individual resilience well-being.• Best pandemic effect’ demographic predictors: age, gender, economic difficulties.• Community and national resilience did not significantly add to predictions.

Dataset Information

The COVID-19 resilience of a continental welfare regime - nowcasting the distributional impact of the crisis.

Supplementary information

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