Data · dataset · 2023
G²LM|LIC - Tracking the Value of Time of Informal Sector Workers During and Post-Curfew in Nairobi
Listed in IDSC Dataverse
Poverty entails more than a scarcity of material resources—it also involves a shortage of time.
Description
To examine the causal benefits of reducing time poverty, we conducted a longitudinal field experiment over six consecutive weeks in an urban slum in Kenya with a sample of working mothers, a population who is especially likely to experience severe time poverty. Participants received vouchers for services designed to reduce their burden of unpaid labor.
We compared the effect of these vouchers against equivalently valued unconditional cash transfers (UCTs) and a neutral control condition. Participants completed a detailed survey. As part of this survey, they provided contact information and then they completed a series of subjective well-being measures from prior research.
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Specifically, participants answered questions about their overall subjective well-being and their positive and negative emotions. Participants then completed demographic items including their gender, age, marital status, whether they were currently living with their partner, or were the head of the household. They also reported on the highest level of formal education they had completed, the number of children they had living at home, their current childcare status, and they answered a series of income questions including how many people they financially supported, how many people relied on their income.
Third, they answered a series of employment questions including whether they currently worked for pay, how many jobs they worked, what kinds of jobs they worked in, how much money they earned per month, how their earnings and employment status had changed during the COVID-19 pandemic, and whether they were currently looking for new employment opportunities and why. Fourth, respondents answered questions about the earnings of their household members and the amount of savings and debt that they had, and how these estimates had changed during the COVID-19 pandemic.
Participants also reported how many hours they spent on unpaid labor in the past 7 days, and whether they had experienced any of the negative impacts of COVID-19 for their own health and their concerns with COVID-19 exposure. Participants also reported how valuable they felt their time was on a series of different measures. Lastly, participants reported how much money they expected to earn in the next six months as well as their predictions for their expenses over the next 6 months.
Links
Where it is published
- Dataverse dataset page dataverse.iza.org/dataset.xhtml?persistentId=doi%3A10.15185%2Fglmlic.701.1 ↗
landing page · from dataverse iza org
- DOI doi.org/10.15185/glmlic.701.1 ↗
DOI / persistent id · from dataverse iza org
Catalogue records · 1
- Dataverse API dataverse.iza.org/api/datasets/:persistentId/?persistentId=doi%3A10.15185%2Fglml… ↗
metadata API · from dataverse iza org
Topics
- Stated by source
- Social Sciences
- From keywords
- Economics & Finance · Medicine & Health · Social Science
- Inferred from text
- Epidemiology 72% · Longitudinal study 65%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IDSC Dataverse | doi:10.15185/glmlic.701.1 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4202 | enrichment · dataverse iza org | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].dataverse_subject:social-sciences | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[method].local:method:longitudinal-study | enrichment · dataverse iza org | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| description | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /description |
| publication_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| title | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /name |
| updated_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| version_label | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 |