Evidence map›Paper›PMID 35844486›Full record

ArticleChina economic review2022

The impact of COVID-19 on employment and income of vocational graduates in China: Evidence from surveys in January and July 2020.

Xiao Liang, Scott Rozelle, Hongmei Yi

Open access · greenAbstract read
In one paragraph

Article in China economic review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
12.8field-weighted citation impact, top 2% of its field
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

4 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
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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 at 2 institutions in 2 countries.

Xiao LiangSchool of Advanced Agricultural Sciences, Peking University, China.
Scott RozelleCenter on China's Economy and Institutions, Stanford University, USA.
Hongmei YiSchool of Advanced Agricultural Sciences, Peking University, China.
Peking University · CNStanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic shocked the economy of China in early 2020. Strict lockdown measures were implemented nationwide to prevent the further spread of the virus. During the lockdown period, many economic activities were affected, which had repercussions for the nation's overall employment. Vocational graduates were among the most affected by the crisis. To estimate the causal effects of COVID-19 on the full-time employment of vocational high school graduates as well as their monthly income and hours worked by week, we exploit variations in the intensity of the pandemic in time and across space using survey data from vocational schools from six provinces in China. The results of the difference-in-differences (DID) estimates indicate that being located in counties with high pandemic intensity significantly reduced both the employment in full-time jobs of vocational graduates as well as their monthly income. Our study's analysis demonstrates that the effects of COVID-19 on the labor market can be attributed to the large-scale contraction of labor demand of the enterprises that were hiring vocational graduates. To cope with this situation, vocational graduates took various measures, including reducing consumption, drawing on their savings, searching for new jobs, taking on part-time jobs, borrowing money, and attending new training programs. In addition, the empirical analysis finds that there were heterogeneous effects with respect to gender, family social capital, the industry in which the vocational graduate was participating, and whether the individual was in a management position.

Indexed as

ChinaCOVID-19 pandemicLabor market outcomeVocational graduates

Identifiers

PMID35844486
PMCPMC9273291
OpenAlexW4285046125

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.