Does voluntary adoption of XBRL reduce cost of equity capital?

Date29 April 2014
Pages86-102
DOIhttps://doi.org/10.1108/IJAIM-11-2012-0071
Published date29 April 2014
AuthorLizhong Hao,Joseph H. Zhang,Jing (Bob) Fang
Subject MatterAccounting & Finance,Accounting/accountancy,Accounting methods/systems
Does voluntary adoption of XBRL
reduce cost of equity capital?
Lizhong Hao
California State University, Fresno, California, USA
Joseph H. Zhang
School of Accountancy, The University of Memphis,
Memphis, Tennessee, USA, and
Jing (Bob) Fang
The Beacom School of Business, University of South Dakota,
Vermillion, South Dakota, USA
Abstract
Purpose – The paper aims to examine whether or not f‌irms voluntarily f‌iling in XBRL (eXtensible
Business Reporting Language) format enjoy a lower cost of capital. XBRL, or “interactive data” as the
US Securities and Exchange Commission refers to it, is an information format that enables electronic
exchange of standardized business and f‌inancial information.
Design/methodology/approach – The authors investigate whether voluntary adoption of XBRL
impacts cost of equity capital using a sample of US f‌irms participated in the SEC Voluntary Filer
Program, each matched with a pair of non-XBRL f‌ilers (matched by two-digit SIC code, same f‌iscal
yearend, and close total assets in the same year). The authors measure f‌irm-specif‌ic cost of equity
capital at the f‌iscal year of last voluntary XBRL f‌iling, using the PEG ratio model proposed by Easton,
Gode and Mohanram, and Hou et al.
Findings – The results show that cost of equity capital is signif‌icantly and negatively associated
with XBRL adoption. The magnitude of the coeff‌icient on XBRL suggests that f‌irms voluntarily
adopting XBRL are associated with an average reduction in cost of equity capital by 17-20 basis points
(conditional on different cost of capital measures).
Research limitations/implications There is a research limitation due to the sample of voluntary
XBRL adopters as of self-selection bias. The authors address this issue by using the Heckman
two-stage regression procedure.
Practical implications – The study provides evidence on the economic consequence of XBRL
adoption in that it benef‌its shareholders by reducing the cost of equity capital. The evidence should
provide regulatorslike the SEC more incentivesto mandate the XBRL standardand motivate companies
to adopt the standard as well.
Originality/value – By showing that voluntary XBRL adopters are associated with lower cost of
equity capital,the study provides timely and relevantempirical evidence to the economicconsequences
of voluntary adoption of XBRL. It also contributes to the limited empirical research on the economic
consequencesof new information technology andhighlights the importance of institutionalregulation in
shaping the outcomes of new f‌inancial reporting format.
Keywords Information systems,Cost of equity capital, US evidence, XBRL
Paper type Research paper
1. Introduction
The paper examines whether f‌irms voluntarily f‌iling in eXtensible Business Reporting
Language (XBRL) format enjoy a lower cost of equity capital (CofE). XBRL, or
“interactive data” as the Securities and Exchange Commission (SEC) refers to it, is an
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1834-7649.htm
Received 24 November 2012
Revised 5 February 2013
11 March 2013
29 March 2013
Accepted 29 March 2013
International Journal of Accounting
and Information Management
Vol. 22 No. 2, 2014
pp. 86-102
qEmerald Group Publishing Limited
1834-7649
DOI 10.1108/IJAIM-11-2012-0071
IJAIM
22,2
86
information format that enables electronic exchange of standardized business and
f‌inancial information. XBRL specif‌ications were developed by XBRL International,
a non-prof‌it consortium of approximately 550 companies, governments, stock
exchanges, and accounting organizations around the world working together to build
XBRL language and promote its global adoption[1].
In USA, the primarydriver for XBRL f‌iling comes from the SEC.Since early 2004, the
SEC has proposedthe rule (No. 33-8496) to establisha voluntary program and encourage
registrants to use XBRL. In the rule No. 33-8529 regarding the Voluntary Filer Program
(VFP), the SEC assertsthat XBRL benef‌its all users of f‌inancialinformation by means of
improving information transparency and lower CofE (SEC, 2005). While prior research
f‌inds some evidence that XBRL improves transparency of f‌inancial reporting
(Hodge et al., 2004; Tan and Shon, 2009), there is little empirical research to date
supporting the SEC’s assertion that XBRL interactive data reduces CofE and the
economic consequence of such adoption stillremain unclear. Thus, we aim to explore the
impact of XBRL adoption on the CofE for US companies who participate in the VFP.
There are at least three reasons why voluntary adopting XBRL may reduce CofE.
First, XBRL may reduce capital cost through “improved information transparency”. As
an interactive data format, XBRL has the potential to improve comparability and
consistency of information, enhances accessibility and usability to f‌inancial and
nonf‌inancial information, and increase f‌inancial disclosure. Second, XBRL may “reduce
transaction cost”. Implementing XBRL may incur additional costs at the beginning of
such adoption. In the long run, however, XBRL will lower the cost of producing
information through automation and free resources from manual work (SEC, 2005).
Third, adopting XBRL may “increase liquidity” and “decrease f‌irm risk”. Proponents of
XBRL argue that since XBRL-tagged data are more transparent, they should reduce the
uncertainty and risk of investors. Moreover, f‌iling in XBRL interactive data may lead to
“broader analyst coverage”, more market exposure and greater investor interest and
conf‌idence in a registrant’s securities(SEC, 2005). Therefore, XBRL couldlower f‌irm risk
and increase market liquidity, and eventually lower the CofE.
We investigate whether voluntary adoption of XBRL impacts CofE using a sample
of f‌irms participated in the SEC VFP, each matched with a pair of non-XBRL f‌ilers
(matched by two-digit SIC code, same f‌iscal yearend, and close total assets in the same
year). We measure f‌irm-specif‌ic CofE at the f‌iscal year of last voluntary XBRL f‌iling,
using the PEG ratio (Easton, 2004). We then regress f‌irm-specif‌ic CofE on a dummy
variable indicating the type of f‌irms (one for XBRL f‌ilers and zero otherwis e) and a set
of control variables that include f‌irm size and risk. We predict that a f‌irm’s CofE is
negatively associated with XBRL adoption.
Multivariate regression results indicate that CofE is negatively and signif‌icantly
associated with XBRL f‌ilings after controlling for f‌irm size and risk. The magnitude of
the effect is such that, on average, XBRL adoption is associated with a reduction in the
CofE of 1.7 percent points for the sample f‌irms. The primary results persist when we
use alternative CofE measures and apply with different model specif‌ications.
This study contributes to the literature in the following ways. First, it provides
timely and relevant empirical evidence to the economic consequences of “voluntary
adoption of XBRL”. XBRL is a new revolution in f‌inancial reporting and it will
dramatically change the reporting process. However, there is little empirical research
on the capital market effects of XBRL adoption. This study provides evidence that
Voluntary
adoption of
XBRL
87

Get this document and AI-powered insights with a free trial of vLex and Vincent AI

Get Started for Free

Unlock full access with a free 7-day trial

Transform your legal research with vLex

  • Complete access to the largest collection of common law case law on one platform

  • Generate AI case summaries that instantly highlight key legal issues

  • Advanced search capabilities with precise filtering and sorting options

  • Comprehensive legal content with documents across 100+ jurisdictions

  • Trusted by 2 million professionals including top global firms

  • Access AI-Powered Research with Vincent AI: Natural language queries with verified citations

vLex

Unlock full access with a free 7-day trial

Transform your legal research with vLex

  • Complete access to the largest collection of common law case law on one platform

  • Generate AI case summaries that instantly highlight key legal issues

  • Advanced search capabilities with precise filtering and sorting options

  • Comprehensive legal content with documents across 100+ jurisdictions

  • Trusted by 2 million professionals including top global firms

  • Access AI-Powered Research with Vincent AI: Natural language queries with verified citations

vLex

Unlock full access with a free 7-day trial

Transform your legal research with vLex

  • Complete access to the largest collection of common law case law on one platform

  • Generate AI case summaries that instantly highlight key legal issues

  • Advanced search capabilities with precise filtering and sorting options

  • Comprehensive legal content with documents across 100+ jurisdictions

  • Trusted by 2 million professionals including top global firms

  • Access AI-Powered Research with Vincent AI: Natural language queries with verified citations

vLex

Unlock full access with a free 7-day trial

Transform your legal research with vLex

  • Complete access to the largest collection of common law case law on one platform

  • Generate AI case summaries that instantly highlight key legal issues

  • Advanced search capabilities with precise filtering and sorting options

  • Comprehensive legal content with documents across 100+ jurisdictions

  • Trusted by 2 million professionals including top global firms

  • Access AI-Powered Research with Vincent AI: Natural language queries with verified citations

vLex

Unlock full access with a free 7-day trial

Transform your legal research with vLex

  • Complete access to the largest collection of common law case law on one platform

  • Generate AI case summaries that instantly highlight key legal issues

  • Advanced search capabilities with precise filtering and sorting options

  • Comprehensive legal content with documents across 100+ jurisdictions

  • Trusted by 2 million professionals including top global firms

  • Access AI-Powered Research with Vincent AI: Natural language queries with verified citations

vLex

Unlock full access with a free 7-day trial

Transform your legal research with vLex

  • Complete access to the largest collection of common law case law on one platform

  • Generate AI case summaries that instantly highlight key legal issues

  • Advanced search capabilities with precise filtering and sorting options

  • Comprehensive legal content with documents across 100+ jurisdictions

  • Trusted by 2 million professionals including top global firms

  • Access AI-Powered Research with Vincent AI: Natural language queries with verified citations

vLex