Evidence map›Paper›PMID 36687794›Full record

ArticleFinancial innovation2023

The transaction behavior of cryptocurrency and electricity consumption.

Mingbo Zheng, Gen-Fu Feng, Xinxin Zhao, Chun-Ping Chang

Abstract read
In one paragraph

Article in Financial innovation, 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

4 authors.

Mingbo ZhengSchool of Economics and Management, Chang'an University, Xi'an, 710064 Shaanxi People's Republic of China.
Gen-Fu FengSchool of Economics and Finance, Xi'an Jiaotong University, Xi'an, 710061 Shaanxi People's Republic of China.
Xinxin ZhaoSchool of Economics and Finance, Xi'an Jiaotong University, Xi'an, 710061 Shaanxi People's Republic of China.
Chun-Ping ChangDepartment of Marketing Management, Shih Chien University, Kaohsiung, 84550 Taiwan.ORCID 0000-0003-1782-4551

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapidly increasing cryptocurrency prices have encouraged cryptocurrency miners to participate in cryptocurrency production, increasing network hashrates and electricity consumption. Growth in network hashrates has further crowded out small cryptocurrency investors owing to the heightened costs of mining hardware and electricity. These changes prompt cryptocurrency miners to become new investors, leading to cryptocurrency price increases. The potential bidirectional relationship between cryptocurrency price and electricity consumption remains unidentified. Hence, this research thus utilizes July 31 2015-July 12 2019 data from 13 cryptocurrencies to investigate the short- and long-run causal effects between cryptocurrency transaction and electricity consumption. Particularly, we consider structural breaks induced by external shocks through stationary analysis and comovement relationships. Over the examined time period, we found that the series of cryptocurrency transaction and electricity consumption gradually returns to mean convergence after undergoing daily shocks, with prices trending together with hashrates. Transaction fluctuations exert both a temporary effect and permanent influence on electricity consumption. Therefore, owing to the computational power deployed to wherever high profit is found, transactions are vital determinants of electricity consumption.

Indexed as

ComovementCryptocurrencyElectricity consumptionTransaction behavior

Identifiers

PMID36687794
PMCPMC9845105

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.