View Complete Reference

Coracioni, A-T and Dănescu, T (2020)

Testing of Published Information on Greenhouse Gas Emissions. Conformity Analysis with the Benfordís Law Method

Audit Financiar XVIII(4) pp. 821-830,.

ISSN/ISBN: Not available at this time. DOI: 10.20869/AUDITF/2020/160/029



Abstract: The issue of greenhouse gas emissions and climate change cannot be overlooked from the scope of concern essential to develop the financial audit profession and implicitly the activity of the financial auditor. Within its professional field, the analysis of data quality on these issues requires applying divers analytical review methods, which incorporates unique statistical or mathematical rules. One of these is the analytical review procedure based on testing compliance of data distribution with Benfordís Law. We present a practical case for testing the verisimilitude of data represented by greenhouse gas emissions, based on the Eurostat database. We applied the Benford's Law method for the first four digits, and the results were tested for likelihood by statistical methods such as Chi-square test or the Kolmogorov-Smirnov test. Information on greenhouse gas emissions is the basis for specific environmental policy decisions, which can be considered at the micro- or macroeconomic level. If this information is affected by subjective influences, then economic decisions or environmental policies will also be affected. Therefore, the objective of this research to test the plausibility of published data on greenhouse gas emissions proves its usefulness in relation with the actions performed by the economic and social players towards a sustainable development of the economy.


Bibtex:
@article{, author = {Coracioni, Alexandru-Teodor and Dănescu, Tatiana}, title = {Testing of Published Information on Greenhouse Gas Emissions. Conformity Analysis with the Benfordís Law Method}, year = {2020}, journal = {Audit Financiar}, volume = {XVIII}, number = {4}, pages = {821--830}, doi = {10.20869/AUDITF/2020/160/029}, }


Reference Type: Journal Article

Subject Area(s): Environmental Sciences, Statistics