Evidence map›Paper›PMID 35638083›Full record

ArticleFood policy2022

COVID-19, information management by local governments, and food consumption.

Vivek Pandey, Shyam Singh, Deepak Kumar

Abstract read
In one paragraph

Article in Food policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Vivek PandeyInstitute of Rural Management Anand, India.
Shyam SinghInstitute of Rural Management Anand, India.
Deepak KumarVirginia Tech, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Federal and state governments in developing countries have tasked local governments with managing COVID-19 on the ground. The bottom-up approach is critical to ensuring household food security, especially in rural areas. We have utilized data from a panel of Indian households that participated in two rounds of a livelihoods survey. While the first round was fielded before COVID-19, the second round was conducted telephonically after the COVID-19-lockdown. We developed an Information Management Response Index (IMRI) to measure the strength of local governments' information management initiatives. The difference-in-difference estimates show that local governments could partially mitigate the pandemic's adverse effects on (a) level and distribution (adult-equivalent per-capita) of food and nutrition expenditure and (b) household vulnerability to food and nutrition poverty. For landless households, IMRI led to statistically significant and additional welfare effects. Three channels explain our empirical findings: (a) maintenance of essential commodities through fair-price shops, (b) access to paid employment and cash (income effect), and (c) disease management (substitution effect). The estimates have been adjusted for sample attrition and multiple-hypothesis correction. We conducted robustness checks with respect to index construction, instrumental variable estimation, and sub-group analysis.

Identifiers

PMID35638083
PMCPMC9132884

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.