The role of automatic stabilizers and emergency tax–benefit policies during the COVID-19 pandemic in Ecuador

Jara, H. Xavier; Montesdeoca, Lourdes; Tasseva, Iva

doi:10.35188/unu-wider/2021/938-9

Cited by 10 publications

(18 citation statements)

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“…In line with the UKMOD (Brewer and Tasseva 2020) and ECUAMOD (Jara et al 2021) studies, this methodology focuses on estimating employment shocks (and enabling poverty and inequality estimates) at the peak of the crisis (i.e. in April when the level 5 lockdown was in place), leaving estimates of further developments in June and beyond to future work.…”

Section: Appendix B: Reweighting the Samod Input Dataset To A 'Pre-covid' Timepoint Appendix C: Modelling Labour Market Transitions On Thmentioning

confidence: 99%

“…These regressors largely match those used by Jara et al (2021) with the addition of race, occupation, and baseline earnings quintile. 22 Occupation was not asked for February employment in NIDS-CRAM, so April occupation is used for those who remained employed in April while last/usual occupation is used for those who were no longer employed in April.…”

Section: Appendix B: Reweighting the Samod Input Dataset To A 'Pre-covid' Timepoint Appendix C: Modelling Labour Market Transitions On Thmentioning

confidence: 99%

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Analysis of the distributional effects of COVID-19 and state-led remedial measures in South Africa

Barnes¹,

Espi-Sanchis²,

Leibbrandt³

et al. 2021

WIDER Working Paper

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Typescript prepared by Gary Smith.United Nations University World Institute for Development Economics Research provides economic analysis and policy advice with the aim of promoting sustainable and equitable development. The Institute began operations in 1985 in Helsinki, Finland, as the first research and training centre of the United Nations University. Today it is a unique blend of think tank, research institute, and UN agency-providing a range of services from policy advice to governments as well as freely available original research.The Institute is funded through income from an endowment fund with additional contributions to its work programme from Finland, Sweden, and the United Kingdom as well as earmarked contributions for specific projects from a variety of donors.

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Section: Appendix B: Reweighting the Samod Input Dataset To A 'Pre-covid' Timepoint Appendix C: Modelling Labour Market Transitions On Thmentioning

confidence: 99%

Section: Appendix B: Reweighting the Samod Input Dataset To A 'Pre-covid' Timepoint Appendix C: Modelling Labour Market Transitions On Thmentioning

confidence: 99%

Analysis of the distributional effects of COVID-19 and state-led remedial measures in South Africa

Barnes¹,

Espi-Sanchis²,

Leibbrandt³

et al. 2021

WIDER Working Paper

View full text Add to dashboard Cite

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“…20. Jara et al (2021) find that COVID-related policies, for example, BDH, BPF and unemployment insurance, played a minor role in mitigating the effect of earning losses, leading to a 0.011 point decrease in the Gini coefficient.…”

Section: Falling Through the Cracksmentioning

confidence: 89%

Falling through the Cracks: Digital Infrastructures of Social Protection in Ecuador

Ludeña¹

2021

Development and Change

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While cash transfers gain prominence as a response to the COVID-19 pandemic, there is a strong impulse to regard them as a stepping-stone towards the formalization of employment and universalization of social protection. This contribution problematizes how populations in informality are included in narrowly targeted social assistance interventions, which are heavily reliant on targeted schemes and fail to make informality legible to programme administrators. The focus of the article lies in the politics of exclusion and inclusion that permeate digital infrastructures, particularly data infrastructures such as social registries, that are used to target Ecuador's most prominent social assistance programme, Bono de Desarrollo Humano, and the COVIDrelated programme Bono de Protección Familiar. The article is based on ethnographic work, interviews and narrative analysis. It finds that social registries compiled for proxy means testing weaken the link between eligibility and informal employment and obscure the processes that perpetuate precarity. More recent data innovations, such as machine learning, are also insufficient to locate vulnerable workers as they learn from historical social registries data and replicate their biases, for example by overlooking non-poor areas where informal employment also occurs. Data infrastructures have shifted attention to the technicalities of the selection of beneficiaries and away from power imbalances in the design of social assistance, despite their selectivity and politics. I would like to thank Kate Meagher for her encouragement and guidance and the editors for their critical comments and insightful suggestions on the earlier version of this article.

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“…Meanwhile Colombia and Mexico are seen as the countries with the least support to increase social assistance to deal against the pandemics. Finally yet importantly, a limited role of COVID emergency transfers in mitigating the impact of the crisis was found in Ecuador (Jara, Montesdeoca and Tasseva, 2021) and Uruguay (Brum and de Rosa, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of the COVID-19 pandemic on poverty and inequality in Mexico

Reynoso

Rembao

Tamayo

et al. 2021

REMEF

Self Cite

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The objective is to quantify the effect of the COVID-19 pandemic on employment, poverty and inequality in Mexico. The methodology is based on a probit model to identify individuals at risk of employment loss, whose earnings are set to zero in ENIGH 2018 to match changes in employment and earnings observed in between December 2019 and the May 2020 according to ENOE and ETOE surveys, respectively. MEXMOD, Mexico’s microsimulation model, is used to simulate tax-benefit policies based on the pre-COVID and COVID-scenarios. The results show that there was a loss of 12.1 million jobs. Poverty reached 60.16% and extreme poverty reached 29.73%; inequality grew 8.2%. It is recommended to strengthen social policy with extra funding (taxing the rich) to achieve greater redistribution. The limitation is that income distribution is held constant as we do not have ENIGH 2020. The originality is to offer timely measures of poverty and inequality using microsimulation techniques to overcome the lack of data during the pandemic. The research concludes that there are not automatic stabilizers to cope COVID-19 negative effects and cash-transfers are not sufficient to do so.

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The role of automatic stabilizers and emergency tax–benefit policies during the COVID-19 pandemic in Ecuador

Cited by 10 publications

References 0 publications

Analysis of the distributional effects of COVID-19 and state-led remedial measures in South Africa

Analysis of the distributional effects of COVID-19 and state-led remedial measures in South Africa

Falling through the Cracks: Digital Infrastructures of Social Protection in Ecuador

The impact of the COVID-19 pandemic on poverty and inequality in Mexico

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