Wednesday, March 19, 2025

Adoption of international auditing standards leads to better financial reporting

Enforcement, degree of convergence deepen positive impact, research finds

University of Toronto, Rotman School of Management

Prof. Ole-Kristian Hope — image:
Ole-Kristian Hope is the Deloitte Professor of Accounting at the University of Toronto's Rotman School of Management. He teaches Commerce, MBA, and PhD courses in accounting. He has broad research interests in financial disclosure, financial reporting quality, corporate governance, analysts, valuation, auditing, private firms, corporate finance, and international business issues. He has published extensively in the leading academic journals of his field. He has been awarded the Haim Falk Award for Distinguished Contribution to Accounting Thought, the American Accounting Association Best Dissertation Supervision Award (twice), the American Accounting Association Outstanding International Educator Award, the American Accounting Association Best Paper Award, and the American Accounting Association Outstanding International Dissertation Award, as well as several other awards. He has supervised a number of PhD students who are now teaching at top business schools. He is founder and organizer of the annual Scandinavian Accounting Research Conference and Doctoral Consortium. Prof. Hope’s research findings are regularly cited by leading media outlets (e.g., The Economist, Financial Times, and Wall Street Journal) and he regularly presents his research at workshops, conferences, and consortia around the world.
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Credit: Rotman School of Management

Toronto - Despite a very uncertain economic climate, investors can at least feel confident that audited financial reports are more reliable thanks to the spread of international standards.

New research led by a researcher at the University of Toronto’s Rotman School of Management shows that the quality of financial audits increasing in countries which have adopted the International Standards on Auditing, or ISA, issued through the International Federation of Accountants, the accounting profession’s worldwide body.

“We show improvement in audit quality, on average,” said researcher Ole-Kristian Hope, the Deloitte Professor of Accounting at the Rotman School. However, “our findings also show that the effectiveness of the standards also depends in part on the enforcement.”

The ISA are developed out of best practices from around the world, are based on principles versus strict rules and were first issued as standards in 1991.

Since then and in line with the movement towards economic globalization, a growing list of countries and jurisdictions, more than 160, have voluntarily adopted the ISA either partially or fully into their own domestic practices and regulations. Canada has fully adopted the standards while the U.S. has partially integrated them. Nevertheless, there has not been much large-scale research into whether ISA has accomplished the goal of superior audit quality so that investors and anyone else interested in a company’s financial statements have high confidence that they are getting relevant and reliable information.

Prof. Hope and a team of three other researchers painstakingly hand-coded and analyzed data from 41 countries that had integrated ISA into their own auditing standards somewhere between 2001 and 2018. The fact that the countries did not all adopt ISA at the same time helped with comparisons.

ISA adoption had the most pronounced effect among domestic or smaller auditors. That may be because they had the most to gain from international accounting standards, compared to big global auditing companies that tend to have more stringent auditing practices, even sometimes going beyond ISA standards, due to their size, resources and reach.

The ISA also had a bigger impact in countries with stronger enforcement of auditing standards and where ISA had been more fully integrated into domestic practices, such as by making them mandatory.

To measure audit quality, the researchers primarily focused on the value of discretionary accruals, an accounting practice that allows for adjustment of earnings statements. The lower the value of discretionary accruals, the higher the rating of audit quality. While discretionary accruals can be used legitimately, such as to claim estimated earnings that have not yet been paid, they can also be misused and manipulated, making it hard to gauge a company’s financial health. The study found consistent results with alternative proxies for audit quality.

An exploratory machine learning analysis suggested that ISA enhances audit quality because of the standards’ focus on a company’s viability, compliance with legal requirements, fraud risk, its internal controls system, and related-party transaction.

Prof. Hope’s research was co-authored with Cyndia Wang of the University of British Columbia, Yaqian Wu of Nanjing Agricultural University and Min Zhang of Renmin University of China. The study appears in The Accounting Review.

Bringing together high-impact faculty research and thought leadership on one searchable platform, the Rotman Insights Hub offers articles, podcasts, opinions, books and videos representing the latest in management thinking and providing insights into the key issues facing business and society. Visit www.rotman.utoronto.ca/insightshub.

The Rotman School of Management is part of the University of Toronto, a global centre of research and teaching excellence at the heart of Canada’s commercial capital. Rotman is a catalyst for transformative learning, insights and public engagement, bringing together diverse views and initiatives around a defining purpose: to create value for business and society. For more information, visit www.rotman.utoronto.ca

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For more information:

Ken McGuffin

Manager, Media Relations

Rotman School of Management

University of Toronto

E-mail:mcguffin@rotman.utoronto.ca

Journal

The Accounting Review

DOI

10.2308/TAR-2022-0610

Method of Research

Data/statistical analysis

Subject of Research

Not applicable

Article Title

Does Convergence with International Standards on Auditing Improve Audit Quality?

Article Publication Date

19-Mar-2025

Whose air quality are we monitoring?

U.S. EPA air quality monitors are disproportionally located in predominately white neighborhoods, leaving marginalized communities at risk of pollution exposure

Racial and Ethnic Disparities in Regulatory Air Quality Monitor Locations in the US

University of Utah

EPA monitor coverage map — image:
Environmental Protection Agency regulator monitor map by pollutant. The colors represent the area covered by each monitor.
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Credit: Kelly et. al. (2024) JAMA Netw Open

U.S. Environmental Protection Agency (EPA) air quality monitors are disproportionally located in predominately white neighborhoods, according to University of Utah research. The EPA’s network consistently failed to capture air quality in communities of color across six major pollutants, particularly lead and sulfur dioxide, followed by ozone and carbon monoxide.

EPA regulatory monitors are the key data source driving decisions about pollution reduction, urban planning and public health initiatives. Without equal monitor distribution, the data may misrepresent pollution concentrations, leaving marginalized groups at risk.

“It’s the question behind the question. Researchers, policymakers, we all use air quality data, but whose air is it measuring?” said Brenna Kelly, doctoral student at the U and lead author of the study. “Even though this data is of really high quality, that doesn’t mean that it’s high quality for everyone.”

Research has shown that marginalized communities have the highest rates of exposure to air pollution, but the studies assumed that the data represented all neighborhoods equally. This study is the first to assess disparities in the monitors themselves for all U.S. Census groups, on a neighborhood scale. While disparities existed for all non-white groups, the largest were for Native Hawaiians and other Pacific Islanders, followed by American Indian and Alaska Native populations.

Air quality research and analysis often require artificial intelligence (AI) tools to process the massive volumes of data. While bias in AI algorithms is well-known, the study exemplifies another ethical issue for big-data users—the chance that the datasets themselves are inherently biased.

“If there was a disparity for just one type of monitor, it could conceivably be accidental or just poor design,” said coauthor Simon Brewer, associate professor of geography and executive committee member of the U’s ONE-U Responsible AI Initiative. “The fact that it's a consistent pattern across all pollutants suggests that the decision-making process needs to be looked at carefully—these monitors are not being distributed equitably.”

The study was published in journal JAMA Network Open on Dec. 4, 2024.

Air quality is hyperlocal and can change dramatically from street to street. The authors mapped monitor locations and neighborhood demographics to the census-block level, one of the U.S. Census Bureau’s smallest units for residential patterns. Using the EPA Air Quality System Regulatory Monitoring Repository, they identified monitors for six major air pollutants dangerous to human health—lead, ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide and particulate matter. They used the 2022 American Community Survey Census to estimate the racial and ethnic composition for every census-block in the country. Adjusting for population size, the researchers found systemic monitoring disparities for each criteria pollutant. Relative to the white non-Hispanic population, all groups were associated with fewer lead, ozone, nitrogen dioxide and particulate matter monitors.

Kelly got curious about the EPA’s air quality monitoring network while pursuing her doctoral research in population health sciences, focusing on the risks of air pollution exposure to pregnant people. Epidemiology research identifies the factors that contribute to diseases within a population. Until now, there’s been an underlying assumption that the data represents air quality problems everywhere equally, she explained.

“It's not just that we're missing one pollutant type for one group, it's that we understand less about everything for all these groups. That's concerning,” Kelly said. “If I want to relate air pollution exposure to a disease, I need to measure it well. If I have a better understanding of air quality for one group of people, that’s going to produce biased results.”

Air quality and population health are just two of many fields grappling with the challenges of using big data and AI responsibly. The One-U Responsible AI Initiative is the U’s recent effort to bring together experts to develop best practices.

“This study is particularly relevant in an increasingly data-driven society. One of the goals of the Responsible AI Initiative is to study the fair application of artificial intelligence methods,” Brewer said. “Our results suggest that biases in the data may be as important to consider as any algorithmic bias.”

Other authors include University of Utah researchers Tracy Onega of Population Health Sciences, Thomas Cova of the School of Environment, Society and Sustainability and Michelle Debbink of the Departments of Obstetrics and Gynecology.

Odds of monitor coverage for each group compared to the reference group.

Credit

Kelly et. al. (2024) JAMA Netw Open