Evidence map›Paper›PMID 38242959›Full record

ArticleScientific reports2024

Analyzing the impact of COVID-19 on consumption behaviors through recession and recovery patterns.

Rui Chen, Tong Li, Yong Li

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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.

Rui ChenDepartment of Electronic Engineering, Tsinghua University, Beijing, 100084, China.
Tong LiDepartment of Electronic Engineering, Tsinghua University, Beijing, 100084, China. tongli@mail.tsinghua.edu.cn.
Yong LiDepartment of Electronic Engineering, Tsinghua University, Beijing, 100084, China. liyong07@tsinghua.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 outbreak has dramatically impacted the economy, particularly consumption behaviors. Studies on how consumption responses to COVID-19 can be a powerful aid for urban consumption recovery. In this paper, based on a high-frequency consumption dataset from January 6, 2020, to April 28, 2020 covering 18 sectors and dataset from the corresponding lunar period in 2021, we look at how COVID-19 changed how people spent their money by looking at patterns of recession and recovery during the pandemic. Specifically, we first explore the recession-recovery pattern of national consumption and the effects of various policies and quantify it using regression methods. Then, recession-recovery patterns across cities are widely studied. We also reveal how consumption structures change during a pandemic and the relationship between patterns of change in citizens' consumption and the socioeconomic characteristics of cities. And the specific empirical analysis is provided through panel regression models. In general, national consumption represented a Vshaped pattern during the pandemic, experiencing a dramatic decline and a rapid rebound. Consumption is significantly inhibited by lockdown, while it is stimulated positively but gradually by easing policies. Consumption patterns at the city level are associated with socioeconomic characteristics. Cities with high-income groups experience a more significant decline, and cities with a high share of the secondary sector have a higher recovery rate in consumption. The consumption structure redistributes but does not fundamentally change. During the recession and early recovery phase, consumption related to basic living saw a significant rise, whereas leisure-related consumption dropped dramatically and recovered slowly. Our study can assist policymakers in implementing diversified market provisions and targeted lockdown policy adjustments for consumption recovery in cities with different socioeconomic backgrounds.

Indexed as

COVID-19CitiesCommunicable Disease ControlHumansIncomeSocioeconomic Factors

Identifiers

PMID38242959
PMCPMC10798975

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.