The Promise and Challenges of New Datasets for Accounting Research

Accounting, Organizations, and Society 2017 Conference on New Corporate Disclosures and New Media

22 Pages Posted: 12 Mar 2018

See all articles by Siew Hong Teoh

Siew Hong Teoh

UCLA Anderson School of Management

Date Written: 2017

Abstract

I describe a brief summary of the development of databases used in accounting research and discuss the research questions addressed in traditional databases and ‘new’ databases. The new data include online searches such as Google Trends data; textual data from corporate disclosures, analyst reports, conference call transcripts, earnings press releases, and news media articles; social network and social media data from Twitter, LinkedIn, Glassdoor, and other data. New data holds promise for research on attention or cognitive processing constraints; on tone/valence, affect, deceptiveness and credibility for capital market and financial reporting outcomes. I examine the econometric challenges of new data and suggest the potential for new data to offer new auditing tools to detect poor financial reporting, which will help to discourage earnings management.

Keywords: Big Data, Google Trends, Twitter, LinkedIn, Glassdoor, social network, limited attention, behavioral bias, psychological bias, tone management, textual data, stock market returns, earnings, analysts

JEL Classification: G02, G14, M40, M41, M42

Suggested Citation

Teoh, Siew Hong, The Promise and Challenges of New Datasets for Accounting Research (2017). Accounting, Organizations, and Society 2017 Conference on New Corporate Disclosures and New Media, Available at SSRN: https://ssrn.com/abstract=3136029

Siew Hong Teoh (Contact Author)

UCLA Anderson School of Management ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

HOME PAGE: http://www.anderson.ucla.edu/faculty-and-research/accounting/faculty/teoh

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