Evidence map›Paper›PMID 35873868›Full record

ArticleJournal of urban economics2023

JUE Insight: COVID-19 and household preference for urban density in China.

Naqun Huang, Jindong Pang, Yanmin Yang

Abstract read
In one paragraph

Article in Journal of urban economics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Naqun HuangInstitute of Urban Development, Nanjing Audit University, Pukou, Nanjing, Jiangsu, 211815, China.
Jindong PangEconomics and Management School, Wuhan University, Luojiashan, Wuhan, Hubei, 430072, China.
Yanmin YangInstitute of Urban Development, Nanjing Audit University, Pukou, Nanjing, Jiangsu, 211815, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper investigates the effect of COVID-19 on both housing prices and housing price gradients in China using transaction level data from 60 Chinese cities. After using a difference-in-differences (DID) specification to disentangle the confounding effects of China's annual Spring Festival, we find that housing prices decreased by two percent immediately after the COVID-19 outbreak but gradually recovered by September 2020. Moreover, our findings suggest that COVID-19 flattens the horizontal housing price gradient, reduces the price premium for living in tall buildings, and changes the vertical gradient within residential buildings. This is likely explained by the changing household preferences towards low-density areas associated with lower infection risk.

Indexed as

Building heightCOVID-19Horizontal housing price gradientHousing pricesVertical gradient

Identifiers

PMID35873868
PMCPMC9295400

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.