Evidence map›Paper›PMID 36255210›Full record

ArticleEvaluation review2023

Impact of Economic Policy Uncertainty and Pandemic Uncertainty on International Tourism: What do We Learn From COVID-19?

Xin Zhao, Muhammad Saeed Meo, Tella Oluwatoba Ibrahim, Noshaba Aziz, Solomon Prince Nathaniel

Abstract read
In one paragraph

Article in Evaluation review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Xin ZhaoSchool of Statistics and Applied Mathematics, 12531Anhui University of Finance and Economics, China.ORCID 0000-0002-6232-9835
Muhammad Saeed MeoSchool of Economics and Management, Xiamen University, China; University of Economics and Human Sciences, Poland; Graduate School of Business, Universiti Sains Malaysia, Malaysia.ORCID 0000-0002-8340-0442
Tella Oluwatoba IbrahimDepartment of Economics, 108285University of Ilorin, Nigeria.
Noshaba AzizSchool of Economics, Shandong University of Technology China.
Solomon Prince NathanielDepartment of Economics, University of Lagos, Nigeria; School of Foundation, Lagos State University, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uncertainty is an overarching aspect of life that is particularly pertinent to the present COVID-19 pandemic crisis; as seen by the pandemic's rapid worldwide spread, the nature and level of uncertainty have possibly increased due to the possible disconnects across national borders. The entire economy, especially the tourism industry, has been dramatically impacted by COVID-19. In the current study, we explore the impact of economic policy uncertainty (EPU) and pandemic uncertainty (PU) on inbound international tourism by using data gathered from Italy, Spain, and the United States for the years 1995-2021. Using the Quantile on Quantile (QQ) approach, the study confirms that EPU and PU negatively affected inbound tourism in all states. Wavelet-based Granger causality further reveals bi-directional causality running from EPU to inbound tourism and unidirectional causality from PU to inbound tourism in the long run. The overall findings show that COVID-19 has had a strong negative effect on tourism. So resilient skills are required to restore a sustainable tourism industry.

Indexed as

COVID-19Economic DevelopmentHumansPandemicsTourismUncertaintyUnited Stateseconomic policy uncertaintyinternational tourismpandemic uncertaintyQuantile on Quantile Approach

Identifiers

PMID36255210
PMCPMC9579821

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.