General assessment of potential economic consequences of country-by-country reporting under CRD IV : final report.
Date: 2016-02-17
Institutions: Directorate-General for the Internal Market and Services
Subjects: banking, credit institution, disclosure of information, economic consequence, financial institution, investment company, management audit

Study prepared by PwC for European 
Commission DG Markt following the contract 
2014/S 102-177729 

General assessment of potential 
economic consequences of 
country-by-country reporting 
under CRD IV 

Final report September 2014 

Non-confidential version

August 2014   

1 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The information and views set out in this study are those of the authors and do not necessarily 
reflect  the  official  opinion  of  the  Commission.  The  Commission  does  not  guarantee  the 
accuracy of the data included in this study. Neither the Commission nor any person acting on 
the  Commission’s  behalf  may  be  held  responsible  for  the  use  which  may  be  made  of  the 
information contained therein. 

DOI: 10.2780/53352 

ISBN: 978-92-79-38488-2 

© European Union, 2014. 

Reproduction is authorised provided the source is acknowledged. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Following an open call for tenders (Ref MARKT/2013/205/F), the Internal Market and 
Services Directorate General (DG MARKT) has commissioned PwC to undertake a 
general assessment of potential economic consequences of country-by-country 
reporting under CRD IV, including an econometric study of the impact of disclosure 
quality on capital market outcomes and a number of other key outcomes. DG MARKT 
is the addressee of this report. 

Any person who is not an addressee of this report, by reading this report accepts and 
agrees to the following terms: 

1.  The reader of this report acknowledges and understands that the work performed 

by PricewaterhouseCoopers LLP was performed in accordance with our contract with 
our addressee client and was performed exclusively for our addressee client’s sole 
benefit and use. 

2.  The reader of this report acknowledges that this report was prepared at the 
direction of our addressee client and may not include all procedures deemed 
necessary for the purposes of the reader. 

The reader agrees that PricewaterhouseCoopers LLP, its partners, directors, 
employees and sub-contractors, neither owe nor accept any obligation, duty or 
responsibility to it, whether in contract or in tort (including without limitation, 
negligence and breach of statutory duty), and shall not be liable in respect of any loss, 
damage or expense of whatsoever nature which is caused by any use the reader may 
choose to make of this report, or which is otherwise consequent upon the gaining of 
access to the report by the reader. Further, the reader agrees that this report is not to 
be referred to or quoted, in whole or in part, in any prospectus, registration 
statement, offering circular, public filing, loan, other agreement or document and not 
to distribute the report without PricewaterhouseCoopers LLP’s prior written consent. 

The information and views set out in this study are those of the author(s) and do not 
necessarily reflect the official opinion of the Commission. The Commission does not 
guarantee the accuracy of the data included in this study. Neither the Commission nor 
any person acting on the Commission’s behalf may be held responsible for the use 
which may be made of the information contained therein. 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Abstract 

This  report  examines  the  potential  positive  and  negative  economic  consequences  of 
public  country-by-country  reporting  by  banks  and  other  financial  sector  firms  under 
Article  89  of  the  EU  Capital  Requirements  Directive  IV  (Directive  2013/36/EU).    We 
reviewed  relevant  academic  literature  and  subsequently  conducted  an  econometric 
analysis  to  investigate  potential  links  between  accounting  disclosure  quality  and 
economic  impacts  for  the  reporting  institutions.  We  asked  a  range  of  stakeholders 
what  they  thought  the  economic  impact  of  Article  89  might  be  and  we  looked  at  the 
differences  in  the  implementation  and  interpretation  of  Article  89  by  Member  States 
and by reporting institutions.  

From  the  econometric  analysis  we  concluded  that  Article  89  was  unlikely  to  have  a 
significant  negative  economic  impact,  and  could  have  a  small  positive  economic 
impact.  

On  balance,  the  stakeholders  expected  Article  89  to  increase  transparency  of  and 
public confidence in the financial sector, but they expected the economic impact to be 
minimal.  

We  identified  a  number  of  differences  in  the  interpretation  and  implementation  of 
Article  89  by  Member  States  and  reporting  institutions  and  concluded  that  the 
consistency  and  comparability  of  the  implementation  of  Article  89  needed  to  be 
improved in order not to undermine any benefits afforded by the disclosures. 

Ce rapport examine les éventuelles répercussions économiques positives et négatives 
liées à la publication d’informations pays par pays par les établissements de crédit et 
les entreprises d'investissement en vertu de l'article 89 de la Directive 2013/36/EU du 
Parlement  Européen  et  du Conseil  du  26  juin  2013  concernant  l’accès  à  l’activité  des 
établissements de crédit et la surveillance prudentielle des établissements de crédit et 
des entreprises d’investissement (CRD).  

Apres la revue et l’examen de la littérature universitaire, disponible et pertinente à ce 
sujet,  nous  avons  procédé  à  une  analyse  économétrique  afin  d'examiner  les  liens 
potentiels entre la qualité de l'information comptable rendue publique et un ensemble 
de résultats économiques concernant les établissements déclarants. 

Nous  avons  sollicité  l’avis  et  l’opinion  d'un  éventail  de  parties  prenantes,  sur  le 
potentiel  impact  économique  de  l'article  89;  Et  nous  avons  également  examiné  les 
différences dans l'application et l'interprétation de l'article 89 par les États membres et 
par les institutions soumises à cette Directive. 

L'analyse  économétrique,  suggère  que  l'article  89  est  peu  susceptible  d'avoir  un 
impact  économique  négatif  important,  et  pourrait  avoir  un  léger  impact  économique 
positif.  

Dans  l'ensemble,  les  différentes  parties  prenantes  s'attendent  à  ce  que  l'article  89 
augmente  la  transparence  et  la  confiance  du  public  dans  le  secteur  financier;  mais 
l'impact économique est selon eux minime.  

Nous  avons  identifié  un  certain  nombre  de  différences  dans  l'interprétation  et 
l'application de l'article 89 par les États membres et les établissements déclarants;  et 
nous  avons  conclu  que  la  cohérence  et  comparabilité  de  l'application  de  l'article  89 
devraient  être  améliorées  afin  de  ne  pas  compromettre  les  avantages  associés  à  la 
communication des informations pays par pays. 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Contents 

Abstract .......................................................................................................... 3 
List of abbreviations ......................................................................................... 6 
Section one - Executive summary ....................................................................... 7 
Overview of the work performed ...................................................................... 7 
Structure of this report................................................................................... 8 
Conclusions .................................................................................................. 9 
Section two - Background and introduction ........................................................ 11 
Introduction of Article 89 to CRD IV................................................................ 12 
Requirement to prepare an assessment of Article 89......................................... 13 
Section three - Econometric study .................................................................... 14 
Introduction................................................................................................ 15 
Purpose of the study ................................................................................. 15 
Framework for the analysis ........................................................................ 15 
Literature review ......................................................................................... 18 
Introduction ............................................................................................ 18 
Capital market impacts ............................................................................. 20 
Transparency impacts ............................................................................... 24 
Accounting quality impacts ........................................................................ 26 
Wider market impacts ............................................................................... 29 
Applicability of these findings to CBCR ......................................................... 30 
Methodology development and data collection ................................................. 33 
Hypotheses ............................................................................................. 33 
Bank sample............................................................................................ 33 
Measuring disclosure quality ...................................................................... 34 
Disclosure Quality Scores .......................................................................... 38 
Identifying the appropriate methodology ..................................................... 40 
Dynamic system GMM model...................................................................... 40 
Logistic model.......................................................................................... 44 
Impact of disclosure quality on the cost of equity capital ................................... 46 
Modelling approach................................................................................... 46 
Data and summary statistics ...................................................................... 48 
Results ................................................................................................... 51 
Robustness and sensitivity tests ................................................................. 53 
Impact of disclosure quality on bid-ask spreads ............................................... 56 
Modelling approach................................................................................... 56 
Data and summary statistics ...................................................................... 58 
Results ................................................................................................... 59 
Robustness and sensitivity tests ................................................................. 61 
Impact of disclosure quality on transparency ................................................... 64 
Modelling approach................................................................................... 64 
Data and summary statistics ...................................................................... 66 
Results ................................................................................................... 68 
Robustness and sensitivity tests ................................................................. 70 
Impact of disclosure quality on earnings management ...................................... 73 
Modelling approach................................................................................... 73 
Data and summary statistics ...................................................................... 77 
Results ................................................................................................... 79 
Robustness and sensitivity tests ................................................................. 81 
Summary and conclusions............................................................................. 84 
Section four – Stakeholder survey .................................................................... 86 
Overview of the stakeholder survey .................................................................. 87 
Survey participants ...................................................................................... 88 
Views on transparency, accountability and public confidence .............................. 91 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
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Views on the economic impact ....................................................................... 92 
The wider economic impact ........................................................................... 93 
The importance of stakeholder reactions ...................................................... 94 
Impacts of a change in effective tax rates .................................................... 95 
Compliance costs......................................................................................... 97 
Section five - Key challenges with the implementation of Art. 89 ........................... 98 
Overview.................................................................................................... 99 
Initial disclosures....................................................................................... 100 
The reporting ‘institution’............................................................................ 101 
Consolidation ............................................................................................ 103 
Exemption to prevent double reporting ......................................................... 103 
Name, nature of activities and geographical location ....................................... 104 
Turnover .................................................................................................. 105 
Employees................................................................................................ 105 
Tax on profit or loss ................................................................................... 106 
Public subsidies received............................................................................. 107 
Location of disclosures ............................................................................... 108 
Format of disclosures ................................................................................. 108 
Interactions between Article 89 and other CBCR regimes................................. 109 
Appendix 1 – Detailed reference material for the econometric study .................... 111 
Appendix 1.1 Other country-by-country reporting initiatives ............................ 112 
Appendix 1.2 List of banks included in our analysis......................................... 113 
Appendix 1.3 Disclosure quality scoring framework......................................... 115 
Appendix 1.4 Disclosure quality score summary statistics ................................ 119 
Appendix 1.5 GMM methodology tests .......................................................... 120 
Appendix 1.6 Cost of equity estimation methods ............................................ 121 
Appendix 1.7 Logistic regression interpretation and results using odd ratios ....... 123 
Appendix 1.8 Bibliography .......................................................................... 125 
Appendix 2 – Detailed results from the stakeholder survey ................................. 135 
Appendix  3  –  Detailed  issues  arising  from  the  transposition,  implementation  and 
interpretation of Article 89 ............................................................................. 152 
Appendix 4 – The concept of deadweight loss from a tax perspective ................... 160 
Appendix 5 – Text of Article 89....................................................................... 163 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
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List of abbreviations 

•  BEPS 

•  CAPM 

•  CBCR 

•  COEC 

Base erosion and profit shifting  

Capital asset pricing model 

country-by-country reporting  

Cost of equity capital 

•  CRD IV 

Capital Requirements Directive IV 

•  CRR 

•  CSO 

•  EBA 

•  EC 

•  EIOPA 

•  EITI 

•  EPS 

•  ESMA 

•  EU  

•  FS 

•  GMM 

•  GRI 

•  GSIB 

•  IFRS  

•  MEP 

Capital Requirements Regulation 

Civil society organisation 

European Banking Authority 

European Commission 

European Insurance and Occupational Pensions Authority 

Extractive Industries Transparency Initiative  

Earnings per share 

European Securities and Markets Authority 

European Union 

Financial services 

Generalised method of moments 

Global Reporting Initiative 

Global systemically important bank 

International financial reporting standards 

Member of the European Parliament 

•  MKTCAP 

Market capitalisation 

•  MTBV 

•  OECD 

•  PE ratio 

Market to book value 

Organisation for Economic Co-operation and Development 

Price-earnings ratio 

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CRD IV 

Section one - Executive summary 

Overview of the work performed 
The scope of our work was agreed with DG MARKT as set out in our contract number 
MARKT/2013/205/F2/ST/OP.  The  contract  includes  the  terms  of  reference  from  the 
related invitation to tender and from our response to that tender. 

The principal objective of our work, as stated in 3.2.1 of the invitation to tender, was 
to  carry  out  a  general  study  on  potential  economic  consequences,  both  positive  and 
negative, of the public disclosure of information such as the information referred to in 
Article  89(1)  CRD  IV  with  a  specific  focus  on  the  impact  on  competitiveness, 
investment  and  credit  availability  and  the  stability  of  the  financial  system.  The  study 
was  designed  with  the  intention  of  covering  all  institutions  subject  to  the  reporting 
requirement and also sought the views of other stakeholders that have an interest in 
the regime, although they are not subject to it. 

The  work  to  be  performed  as  well  as  the  detailed  methodologies  were  discussed  and 
agreed with DG MARKT at various stages in our work. The next page sets out where 
the methodology, results and conclusions from each element of our work can be found 
within this report. 

In  line  with  the  contract  we  used  a  number  of  methods  to  investigate  the  potential 
economic  impact  of  the  country-by-country  reporting  (CBCR)  requirements  contained 
within Article 89 of the EU Capital Requirements Directive IV (CRD IV). We carried out 
the following: 

(cid:131)  econometric  study  -  an  academic  literature  review  and  based  on  the  literature  we 
developed  a  consistent  methodology  to  quantify  banks’  disclosure  quality  and 
conducted an econometric analysis to investigate potential links between  disclosure 
quality and economic impacts for the reporting institutions 

(cid:131)  stakeholder  survey  -  a  survey  of  a  range  of  stakeholders  including  civil  society 
organisations  (CSOs),  governments,  regulators,  banks  and  trade  associations  to 
obtain their views on likely economic impacts 

(cid:131)  legal implementation analysis - a survey of PwC experts to determine how Article 89 

has been implemented in the 28 EU Member States 

(cid:131)  review  of  disclosures  -  a  review  of  the  first  disclosures  made  under  Article  89  by 
twelve  of  the  fourteen  EU-headquartered  globally  systemically  important  banks 
(GSIBs) that were required to report to the European Commission by 1 July 2014 

Within our response to the invitation to tender we contemplated carrying out economic 
modelling to look at the economic effect should CBCR be thought likely to increase the 
effective corporate income tax rates of financial institutions.  In the course of our work 
it  became  apparent  that  the  assumptions  required  for  such  modelling  would  be  very 
broad and so it was agreed with the Commission to exclude this from the scope of our 
work. A more detailed discussion of this issue can be found on pages 94-97. 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Structure of this report 

Section  one  of  this  report  is  a  high  level  executive  summary  of  our  study  explaining 
the work performed and the conclusions reached. 

Sections  two  to  four  provide  an  overview  of  the  methodologies  and  results  from  the 
different elements of our work highlighting our key findings: 

(cid:131)  Section two - a brief introduction to the background of the study 

(cid:131)  Section three - the methodology and the results from the econometric study 

(cid:131)  Section  four  -  an  overview  of  the  methodology  and  results  from  the  stakeholder 

survey. 

Section  five  contains  a  summary  of  the  key  issues  with  the  implementation  and 
interpretation  of  Article  89  that  we  identify  from  the  stakeholder  survey,  the  legal 
implementation analysis and the review of disclosures. 

The  appendices  provide  detailed  information  on  the  work  performed  and  the  results 
obtained: 

(cid:131)  Appendix 1 – Detailed reference materials for the econometric study  

(cid:131)  Appendix  2  –  Detailed  results  of  the  stakeholder  survey  including  the  results  by 

question and summaries of the comments made by respondents 

(cid:131)  Appendix  3  –  Detailed  explanations  of  the  issues  with  the  implementation  and 
interpretation  of  Article  89  drawn  from  our  legal  analysis,  stakeholder  survey  and 
review of disclosures 

(cid:131)  Appendix  4  –  An  explanation  of  the  concept  of  deadweight  loss  from  a  tax 

perspective 

(cid:131)  Appendix 5 – The text of Article 89 

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Conclusions 
It is very early to form a view on the impact of the provisions of Article 89 of CRD IV. 
However, on the basis of the views that we have obtained from the organisations that 
responded  to  our  survey,  the  balance  of  opinion  suggests  that  these  provisions  are 
likely  to  have  some  impact,  as  intended,  in  improving  the  trust  of  citizens  of  the 
European  Union  in  the  financial  services  sector.  Specifically,  our  stakeholder  survey 
suggests that the respondents expect Article 89 to have some positive impact on the 
transparency  and  accountability  of,  and  on  the  public  confidence  in,  the  financial 
services sector in the EU. 

Furthermore,  the  balance  of  opinion  and  the  work  we  performed  suggest  this 
improvement is likely to be obtained without the public disclosure of such information 
having  noticeable  negative  economic  consequences,  including  the  impact  on 
competitiveness,  investment  and  credit  availability  and  the  stability  of  the  financial 
system. 

Looking at each of these impacts in turn: 

Competitiveness – Although our econometric study has not captured the impacts on 
competitiveness directly, our results suggest that improved disclosure quality, which is 
a  key  objective  of  CBCR,  could  improve  firms’  competitive  outcomes.  The  analysis 
suggests  that  an  improvement  in  disclosure  quality  is  associated  with  a  reduction  in 
earnings management1, which could have positive impacts on firms’ competitiveness.  

Furthermore,  the  stakeholder  survey  indicated  that  53%  of  respondents  felt  there 
would  be  no  impact  on  competitiveness.  The  fact  that  three  of  the  fourteen  GSIBs 
have published their Article 89 disclosures in full in 2014 would suggest that they are 
not overly concerned that there will be a detrimental effect on their competitiveness. 
While  many  stakeholders  recognised  that  there  is  a  compliance  cost  for  firms  in 
complying with Article 89, it was generally felt not to be significant when compared to 
the  overall  cost  of  the  wider  regulatory  compliance  burdens  faced  by  the  reporting 
institutions. The compliance cost associated with Article 89 therefore seems unlikely to 
disadvantage 
to  non-reporting 
institutions. 

institutions  significantly  compared 

reporting 

Credit  availability  –  Our  econometric  results  suggest that  CBCR  is  unlikely  to  have 
any negative impact on banks’ ability to access capital markets. The improvement in 
disclosure quality as a result of CBCR could have an impact on reducing banks’ cost of 
equity capital – an improvement in the disclosure score of 1 reduces the cost of equity 
capital  by  0.2  percentage  points,  and  these  benefits  could  be  passed  onto  non-
financial sector firms and households in the form of lower lending rates.  

This contrasts with the views from the stakeholder survey which indicated that only a 
very  few  respondents  expect  a  positive  impact  on  credit  availability  as  a  result  of 
Article 89. The vast majority of respondents expected that there would be no impact 
on credit availability. 

Investment  –  Related  to  the  point  on  credit  availability,  our  econometric  results 
suggest  that  CBCR  is  unlikely  to  have  a  negative  impact  on  investment.  The 
improvement  in  disclosure  quality,  as  perceived  by  capital  markets  as  a  result  of 
CBCR, could lead to a lower cost of equity capital for banks, which may translate into 

1Earnings  management  is  where  a  firm’s  management  use  accounting  discretion  in 
presenting financial results in order to present the entity to investors in an artificially 
positive light. 

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CRD IV 

lower lending rates and enable firms to invest in their business and expand. However, 
these impacts are likely to be small. 

In terms of investment into reporting institutions, 61% of stakeholders responding to 
the  survey  expected  no  impact  on  the  investment  in  reporting  institutions,  28% 
expected a positive or very positive impact, with regulators and CSOs generally having 
a more positive view than businesses.  

Stability  of  the  financial  system  –  The  evidence  from  our  econometric  analysis 
suggests that an increase in disclosure quality, which is a key objective of CBCR, could 
have a small but positive impact on accounting quality. This means that following the 
implementation  of  CBCR,  the  information  provided  by  financial  institutions  could 
become  more  informative  for  external  stakeholders,  and  better  reflect  the  true 
economic condition of the institution. This could result in lower volatility and increased 
financial stability.  

Three quarters of the stakeholders responding to the survey expected there to be no 
impact on the stability of the financial services sector, with 18% expecting a positive 
impact. It was noted that while there may be a negative effect on specific institutions 
it was felt unlikely that this would significantly affect the sector as a whole. 

Although  our  econometric  results  provide  some  insights  into  the  potential  impacts  of 
CBCR, we are necessarily inferring from the historical relationships between disclosure 
quality and the outcomes of interest (i.e. banks’ cost of equity capital, bid-ask spread, 
accuracy  of  earnings  forecasts  and  the  likelihood  of  earnings  management)  to  draw 
possible  conclusions  for  CBCR.  Caution  is  therefore  required  when  interpreting 
the results and conclusions from our study and their applicability to CBCR. In 
particular,  it  seems  likely  that  the  benefits  of  incremental  improved  disclosure  will 
decline  with  successive  initiatives,  as  the  pre-existing  level  of  disclosure  is  already 
higher. Furthermore, it is impossible to quantify the extent to which CBCR will improve 
disclosure  compared  with  the  historical  improvements  in  disclosure  quality  which  we 
have  observed  from  our  data  and  which  form  the  basis  for  our  model  estimation. 
Nevertheless,  our  academic  literature  review  and  econometric  modelling  do  suggest 
that,  to  the  extent  that  there  is  an  improvement  in  disclosure  resulting  from  CBCR, 
then directionally this would be expected to be associated with positive outcomes for 
the economic performance of the reporting institutions and their customers.   

The  stakeholder  survey  and  our  review  of  the  implementation  and  interpretation  of 
Article 89 as well as our review of the first disclosures of the GSIBs suggest that the 
beneficial impact of Article 89 could be improved by addressing a number of the issues 
that have arisen concerning the implementation and interpretation of Article 89. 

Without changes to improve the clarity and consistency of the interpretation of Article 
89,  and  a  consequent  increase  in  the  comparability  of  the  data  disclosed,  there 
appears to be a risk that benefits associated with the disclosure could be undermined.  

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Section two - Background and introduction 

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Introduction of Article 89 to CRD IV 

In  February  2013,  the  European  Parliament  proposed  the  inclusion  in  CRD  IV  of  a 
requirement  for  credit  institutions  and  investment  firms  to  publish  annually  the 
following tax and financial data for each country in which they operate: 

a)  name(s), nature of activities and geographical location 
b)  turnover 
c)  number of employees on a full time equivalent basis 
d)  profit or loss before tax 
e)  tax on profit or loss, and 
f)  public subsidies received. 

Following  the  agreement  of  the  co-legislators  this  requirement  became  Article  89  of 
CRD IV and will apply in full from 1 January 2015.  

Perhaps  owing  to  being  introduced  late  in  the  legislative  process,  the  CBCR 
requirements  contain  little  detail  and  leave  many  points  open  to  different 
interpretations. This has been a recurring theme throughout our work. 
The full text of Article 89 is included in Appendix 5. 

Only  GSIBs  are  required  by  Article  89  to  report  items  a)  to  f)  by  1  July  2014,  with 
items d) to f) being privately disclosed to the European Commission and items a) to c) 
being publically disclosed.  

All  other  institutions  are  only  required  to  make  full  disclosure  of  all  six  items  from 
2015, but must publically disclose items a) to c) by 1 July 2014.   

The  fourteen  GSIBs2  that  were  required  to  report  to  the  Commission  by  1  July  2014 
are: 

a)  Barclays 
b)  BNP Paribas 
c)  BBVA 
d)  Deutsche Bank 
e)  Groupe BPCE 
f)  Group Credit Agricole 
g)  HSBC 
h)  ING Bank 
i)  Nordea 
j)  Royal Bank of Scotland 
k)  Santander 
l)  Societe Generale 
m) Standard Chartered 
n)  Unicredit 

2 FSB update of group of global systematically important banks, 1 November 2012 

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Requirement to prepare an assessment of Article 89 

Paragraph 3 of Article 89 requires that “the Commission, after consulting EBA, EIOPA 
and  ESMA,  as  appropriate,  shall  conduct  a  general  assessment  as  regards  potential 
negative  economic  consequences  of  the  public  disclosure  of  such  information, 
including  the  impact  on  competitiveness,  investment  and  credit  availability  and  the 
stability  of  the  financial  system.  The  Commission  shall  submit  its  report  to  the 
European Parliament and to the Council by 31 December 2014.” 

Our work, which is detailed in this report, was requested by the Commission, following 
an open call for tenders (Ref MARKT/2013/205/F), to assist it in preparing its report to 
the  Parliament  and  to  Council.    The  scope  of  this  work  was  agreed  with  the 
Commission  as  set  out  in  our  contract  number  MARKT/2013/205/F2/ST/OP.  The 
contract includes the terms of reference from the related invitation to tender and from 
our response to that tender.   

Our work covers the following areas: 

(cid:131)  an  academic  literature  review  and  econometric  study  to  investigate  potential  links 
between  financial  reporting  disclosures  and  a  set  of  economic  outcomes  for 
reporting institutions; 

(cid:131)  a  survey  of  a  range  of  stakeholders  including  civil  society  organisations, 
governments,  regulators,  banks  and  trade  associations  to  obtain  their  views  on 
likely economic impacts; 

(cid:131)  a survey of PwC experts to determine how Article 89 has been implemented in the 

28 EU Member States; and 

(cid:131)  a review of the first disclosures by GSIBs made under Article 89. 

The  work  that  we  have  agreed  to  perform  seeks  to  address  not  only  the  remit  for 
assessment  as  set  out  in  Article  89  (3),  but  also  considers  whether  the  Article  89 
disclosures  will  meet  the  objective  of  restoring  public  trust  in  the  financial  services 
sector as set out in recital (52) to CRD IV, namely: 

“Increased  transparency  regarding  the  activities  of  institutions,  and  in  particular 
regarding  profits  made,  taxes  paid  and  subsidies  received,  is  essential  for  regaining 
the  trust  of  citizens  of  the  Union  in  the  financial  sector.  Mandatory  reporting  in  that 
area can therefore be seen as an important element of the corporate responsibility of 
institutions towards stakeholders and society”. 

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Section three - Econometric study 

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Introduction 

Purpose of the study 

The  macroeconomic  challenges  of  recent  years  have  placed  national  governments 
under severe pressure, attempting to balance programmes of fiscal consolidation with 
the  need  to  maintain  public  services  provision  and  promote  economic  growth.  This 
pressure  has  manifested  itself  in  calls  from  investors,  civil  society  organisations  and 
the  media  for  companies  and  individuals  to  be  seen  to  making  adequate  fiscal  and 
economic  contributions  to  their  jurisdictions  of  residence.  In  particular,  there  is  a 
growing movement towards the development and formalisation of CBCR requirements 
with a view to promoting greater levels of corporate transparency and accountability. 

Within this, a key area of focus for the proponents of greater transparency and quality 
of  corporate  disclosure  has  been  the  financial  services  (FS)  sector,  in  part  driven  by 
the  wider  debate  on  FS  sector  accountability  and  regulation  following  the  financial 
crisis. However, corporate disclosure and CBCR requirements in the FS sector are yet 
to  exhibit  the  levels  of  formalisation  witnessed  in  other  sectors,  most  notably  the 
extractives  industry.  Indeed,  the  extractives  industry  currently  has  a  number  of 
voluntary  and  mandatory  CBCR  requirements  that  aim  to  foster  greater  governance 
and accountability in resource-rich countries.3 

This study seeks to inform the Commission’s understanding of the potential economic 
impacts of the public disclosure of specific  information on a country-by-country basis 
by  reviewing  the  existing  academic  research  and  providing  an  updated  econometric 
analysis  on  the  relationship  between  disclosure  quality  and  economic  impacts.  Our 
econometric  analysis  focuses  specifically  on  the  financial  services  sector.  We  use 
historical  data  in  order  to  test  the  statistical  relationship  between  disclosure  quality 
and a set of economic outcomes. However, as CBCR is yet to be implemented, it is not 
possible  to  observe  the  actual  impact  of  CBCR,  so  we  have  sought  to  infer  what  the 
future  impacts  could  be,  based  on  the  historical  evidence  of  previous  changes  in 
disclosure quality. 

Framework for the analysis 

We explored the historical link between disclosure quality and a range of outcomes by 
conducting a literature review of reputable academic papers to form prior expectations 
for  the  statistical  significance  of  the  link  between  country-by-country  reporting  (and 
disclosure  quality  more  generally)  and  economic  impacts.  There  is  a  general 
consensus  in  the  literature  that  disclosure  quality  does  have  an  impact  on  capital 
market  outcomes,  transparency  and  accounting  quality.  The  literature  also  provides 
evidence  on  the  potential  spillover  impacts  that  result  from  improved  disclosure 
quality, such as competitiveness. We have tested the validity of these relationships for 
our  sample  of  banks,  using  more  robust  statistical  approaches  than  observed  in  the 
prior literature.  

Based on the literature and the results from our econometric analysis, we draw some 
conclusions on the potential implications of CBCR. Where we have found a statistically 
significant result linking the quality of firms’ disclosures and the outcomes of interest 
based  on  historical  relationships,  this  might  imply  that  the  additional  reporting 
measures that raise disclosure quality under CBCR will  also have an impact on  these 
outcomes.  Our  approach  allows  us  to  identify  which  components  of  reporting 

3 Appendix 1.1 sets out some of the other country-by-country reporting arrangements 
that have been implemented worldwide. 

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(specifically  the  public  availability  and  quality  of  segment  reporting)  drive  the 
relationships between disclosure quality and these outcomes.  

We  cover  the  impacts  of  banks’  disclosures  on  a  range  of  outcomes  as  disclosure 
quality  can affect  firms  through  a number  of different  channels.  We have  focused  on 
capital  market  impacts,  transparency  and  accounting  quality,  which  enables  us  to 
draw  conclusions  for  CBCR  across  a  wide  range  of  channels,  and  how  these  link  to 
competitiveness, investment, credit availability and stability.  

We  developed  a  methodology  to  examine  the  impact  of  CBCR  requirements.  An 
overview of our analytical framework is set out in Figure 1.  

Figure 1: An overview of our analytical framework 

1. 

Literature review: We undertook an extensive review of the literature on the 
impact of firms’ disclosure quality. Based on the existing empirical research, we 
identified the key outcomes of interest for our study: 

• 

• 

• 

Capital market impacts: Cost of equity capital and bid-ask spreads. We 
hypothesise that an improvement in disclosure quality is associated with 
improved capital market outcomes, i.e. lower cost of equity capital and lower 
transaction costs in the form of bid-ask spreads. 
Transparency: the accuracy of analysts’ earnings forecasts. We hypothesise that 
an improvement in disclosure quality leads to an improvement in the accuracy of 
analysts’ forecasts, specifically for earnings. 
Accounting quality: the likelihood of earnings management. We hypothesise that 
an improvement in disclosure quality leads to an improvement in accounting 
quality, specifically earnings management. This is defined as the use of 
accounting discretion by the firm’s management in presenting financial results in 
order to present the entity in an artificially positive light to investors. 

The  link  between  disclosure  quality  and  the  outcomes  of  interest  above  are 
explored  in  more  detail  in  our  conclusions  in  Section  one.  This  exercise  also 
informed our selection of the appropriate econometric methodology to be applied 
in our assessment.  

2.  Methodology development: In order to analyse the impact of disclosure 
quality on the outcomes of interest, we developed a scoring framework to 
consistently capture the quality of firms’ disclosure, on the basis of the amount 
and quality of information provided in annual reports. We also developed the 
appropriate econometric methodology to be used in our analysis, which takes 
into account potential estimation problems such as endogeneity.  

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3.  Data collection: Our analysis focuses on large, cross-border banking as CBCR is 

intended primarily to affect these institutions. On this basis, we identified a set 
of criteria to select a sample of large cross-border banks to be included in our 
analysis. Banks were assigned individual scores for disclosure quality, based on 
the scoring framework we have developed. Other data required for our analysis 
were collected for our sample of banks. 

4. 

Econometric analysis: Using the disclosure quality scores, and drawing from 
the existing literature and updated econometric approaches, we investigated the 
relationship between disclosure quality (and specifically the impact of providing 
segmented breakdowns) on the outcomes of interest. 

The outcomes and hypotheses we tested were jointly agreed with DG MARKT. The rest 
of  this  section  of  the  report  sets  out  our  approach  and  the  results  of  our  analysis  in 
more detail. This study provides an updated view on the impact of disclosure quality, 
specifically  for  the  banking  sector.  We  also  improve  on  the  econometric  approaches 
used  in  previous  studies,  by  using  more  sophisticated  econometric  approaches  that 
take into account possible estimation issues. We also consider the impact of the public 
availability  and  granularity  of  segment  information,  which  relates  to  CBCR.  Our 
approach  also  seeks  to  provide  some  evidence  on  other  aspects  of  firms’  disclosures 
that can have an impact on the outcomes mentioned above. 

Our  study  assesses  the  direct  impacts  on  businesses  as  a  result  of  an  increase  in 
disclosure  quality.  We acknowledge  that  there  is  a  range  of wider  impacts  that  could 
result from the implementation of CBCR, such as market-wide/spillover impacts. Due 
to  the  lack  of  readily-available  data  and  in  order  to  maintain  the  tractability  of  our 
analysis this has not been explicitly quantified in our study. 

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Literature review 
This  section  sets  out  our  review  of  the  existing  literature  on  the  impact  of  firms’ 
disclosure quality. This exercise enabled us to understand the ways in which disclosure 
quality can influence firm outcomes and to form a view on which of these appear to be 
the  most  material.  It  informed  our  understanding  of  the  econometric  issues  we  were 
likely to encounter in our analysis and how these can be mitigated. It also provided a 
set of previously documented relationships and econometric results against which we 
were  able  to  assess  the  plausibility  of  both  the  direction  and  magnitude  of  our 
econometric results. 

Introduction 

Companies provide information externally in a number of ways, either on a voluntary 
basis  or  driven  by  mandatory  or  legal/regulatory  requirements.  For  example,  firms 
disclose  information  via  formal  (mandated)  channels  such  as  regulated  financial 
reporting and statements, management discussions and analysis, and other regulatory 
filings.  Firms  can  also  provide  information  on  a  less  formal  basis,  such  as  voluntary 
investor 
disclosures 
presentations, and press releases.  

in  annual  reports,  management 

forecasts,  analyst  and 

The literature concludes that firm disclosures are important for various reasons. They 
have  an  impact  on  the  way  firms  are  perceived  in  the  market  and  on  how  they 
operate. Firm disclosures improve the ability of external parties such as shareholders 
and lenders to understand the true economic condition of the business and so help to 
improve  investment  decisions.  The  public  can  also  gain  an  understanding  of  a  firm’s 
sustainability  policies  and  performance  in  relation  to  environmental  and  ethical 
standards, as well as stakeholder management activities, which could have an impact 
on public perception and confidence in the business. 

Specifically  in  relation  to  the  merits  of  providing  disclosure  at  a  more  granular  level, 
many  users  of  financial  reports  are  interested  in  the  performance  and  prospects of  a 
particular  business  unit  within  a  firm,  as  opposed  to  the  firm  as  a  whole  (Roberts, 
2010).  For  instance,  host  governments  may  be  interested  in  the  performance  of  an 
operating  segment  that  is  based  in  their  jurisdiction.  Segment  information,  be  it  by 
business unit and/or geographic segment, help meet this need. 

Geographic  and  industry  segments  can  differ  significantly  in  terms  of  growth 
opportunities,  political  stability,  potential  investors,  risk  and  profitability  (Herrmann 
and  Thomas,  1997).  Therefore  the  public  availability  of  granular  information,  by 
business  unit4  and/or  geographic  segment,  enables  investors  to  understand  key 
drivers  of  growth,  predict  future  cash  flows,  and  make  more  informed  investment 
decisions.  

This  raises  the  question  as  to  why  mandatory  disclosures  are  necessary;  after  all, 
firms already have an incentive to provide relevant information if the benefits of doing 
so are present (Ross, 1979). However, the literature concludes that there is a role for 
regulators to mandate the disclosure of key information by firms.  

First,  the  natural  dynamics  in  capital  markets  can  create  incentives  for  information 
asymmetries  to  exist.  Firms  could  have  an  incentive  to  withhold  information  should 
they incur costs or be disadvantaged (from a competition perspective) as a result. For 
example,  detailed  information  on  segment  performance  could  reveal  proprietary 
information which could be used by competitors, thus reducing the incentives for firms 

4 The definitions of business units are likely to vary across different entities, and could 
refer to different product lines within a single entity or subsidiaries within a group. 

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to  report  information  publicly  (Feltham  et  al.,  1992,  Hayes  and  Lundholm,  1996). 
Harris (1998) finds that operations in less competitive  industries are less  likely  to be 
reported,  which  could  be  intended  to  avoid  disclosing  supernormal  profits  or  high 
market  shares.  Shleifer  and  Wolfenzon  (2002)  show  that  large  shareholders  and 
insiders  may  be  reluctant  to  commit  to  disclosures  that  limit  their  ability  to  extract 
private benefits, even if the disclosures are beneficial to the firm. Jiang, Kim and Pang 
(2013)  show  that  corporate  insiders  have  an  incentive  to  increase  information 
opaqueness in order to capture unexpected cash flows. Bushee and Leuz (2005) also 
show that disclosure costs are subject to economies of scale, and hence smaller firms 
are disincentivised from providing disclosures by the disproportionate costs they face.  

Secondly,  the  literature  points  out  that  there  could  be  market-wide  effects  or 
externalities associated with firm disclosures which are ignored or not fully internalised 
by  firms  when  making  decisions  about  what  information  to  disclose.  Disclosures  can 
discourage  unethical  management  behaviour,  which  helps  to  maintain  confidence  in 
markets and prevent the loss of market integrity (Kosaiyakanont, 2011).5 It facilitates 
the  market-based  monitoring  of  companies  and  is  central  to  protecting  shareholders’ 
ability  to  exercise  ownership  rights  and  to  influence  management  decisions. 
Disclosures  of  operating  performance  and  governance  arrangements  provide  useful 
benchmarks  for  managerial  efficiency  or  conflicts  of  interest  that  help  outside 
investors evaluate other firms, thereby reducing the overall cost of monitoring for the 
market (Hail, Leuz and Wysocki, 2009).  

In addition, public disclosures also function as a commitment device for companies to 
provide  credible  information  on  a  timely  basis  (Mahoney,  1997,  Rock,  2002).  In  the 
absence  of  commitment,  firms  may  choose  to  withhold  information  under  certain 
conditions,  such  as  during  periods  of  poor  performance  (Miller,  2002).  Disclosure 
requirements could therefore function as a commitment device to force firms to reveal 
information in both good and bad times (Verrecchia, 2001). 

The literature therefore finds that regulated or mandatory disclosures seek to capture 
these  externalities  which  would  otherwise  be  ignored.  The  mandatory  adoption  of 
international accounting standards, such as the adoption of the International Financial 
Reporting Standards (IFRS) in the EU in 2005 is cited as offering a pertinent example. 
This  stems  from  the  premise  that  the  adoption  of  internationally-recognised 
accounting  standards  in  financial  reporting  increases  the  quality  and  quantity  of 
corporate disclosure (Daske and Gebhardt, 2006; Hail and Leuz, 2007). For example, 
Bischof  (2009)  finds  that  the  endorsement  of  IFRS  7  in  Europe  has  led  to  an 
improvement  in  the  quality  of  banks’  financial  disclosures,  with  a  shift  in  focus  from 
market  risk  to  credit  risk  being  observed.6  The  standardisation  of  financial  reporting 
also  promotes  easier  comparisons  of  financial  performance  across  firms.  This  means 
that  the  reported  information  becomes  more  useful  to  investors,  even  when  holding 
the level and quality of disclosures constant (De Franco, Kothari and Verdi, 2010).  

According  to  the  literature,  a  particularly  informative  aspect  of  the  accounting 
standards literature that is related to CBCR is the impact of IFRS 8 and SFAS No. 131. 
These two regulations sought to standardise segment reporting across companies, and 
has  led  to  the  disclosure  of  more  country-specific  information  which  are  viewed  as 

5  Agency  studies  such  as  Shleifer  and  Wolfenzon  (2002),  Shleifer  and  Vishny  (1997) 
and  Lambert  (2001)  demonstrate  how  disclosures  can  mitigate  problems  of 
management appropriation. 
6  IFRS  7,  which  became  effective  in  Europe  for  financial  years  beginning  after  31 
December 2006, required entities that use financial instruments to provide qualitative 
and quantitative information on exposures to credit, liquidity and market risks. It also 
requires  the  disclosure  of  the  significance  of  financial  instruments  and  underlying 
accounting policies, such as underlying fair value assumptions (Bischof, 2009). 

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useful to investors. Following IFRS 8, several academic studies document an increase 
in  the  number  of  geographic  segments  for  which  information  is  available,  and  an 
information 
increase 
(Weissenberger and Franzen, 2012a; Nichols et al., 2012; Cereola et al., 2013). 

in  the  number  of  companies  providing  country-specific 

The existing literature can be classified into the following four categories of the impact 
of disclosure on the economy: 

• 

• 
• 
• 

Capital market impacts, such as the impact on cost of equity capital and market 
liquidity; 
Transparency impacts, such as the impact on the information environment; 
Accounting quality impacts, such as the impact on earnings management; and 
Wider market impacts, such as the impact on competitiveness and other 
spillover impacts.  

We  explain  these  categories  and  set  out  the  literature  on  each  in  more  detail  in  the 
sections that follow.  

Capital market impacts 

The  fundamental  purpose  of  capital  markets  is  to  facilitate  the  appropriate  allocation 
of capital from investors, who wish to earn a return on their savings, to entrepreneurs, 
who need capital in order to establish and expand their businesses.  

There are two key challenges in capital allocation identified in the literature. The first 
is  information  asymmetry,  which,  in  the  context  of  capital  markets,  refers  to  the 
better  information  firms’  managers  have  than  their  prospective  investors  as  to  the 
true  value  and  profitability  of  the  firm.  The  greater  the  gap  in  information  between 
managers  and  investors,  the  greater  the  degree  of  information  asymmetry.  This  is 
illustrated  in  the  well-known  “lemons”  problem  (Akerlof,  1970)  and  means  that 
investors can be unwilling to pay more for securities from high quality issuers because 
they  are  unable  to  distinguish  between  good  and  bad  quality  firms.  Because  of  this, 
high  quality  firms  face  the  same  borrowing  rates  as  bad  quality  ones,  which  is  at  a 
higher  rate  relative  to  that  which  they  would  face  if  there  were  no  information 
asymmetries.  

If  investors  anticipate  that  they  will  face  a  price  discount  induced  by  information 
asymmetry when selling shares, investors are more likely to reduce the price at which 
they  are  willing  to  buy  shares  in  firms’  equity  offerings  (Diamond  and  Verrecchia, 
1991;  Baiman  and  Verrecchia,  1996;  Ljungqvist  and  Jenkinson,  2001).  For  the  firm 
this  raises  the  effective  cost  of  equity  capital.  If  forecasting  risks  are  high  due  to 
uncertainty,  investors  will  demand  excess  returns  for  their  investment,  thereby 
increasing the firm’s cost of capital (Barry and Brown, 1984, 1985, 1986). 

Information  asymmetries  among  market  makers  also  affect  their  ability  to  execute 
trades  at  a  reasonable  cost  (Helfin,  Shaw  and  Wild,  2005).  Market  makers  face 
informed traders who have superior information that is not reflected in market prices 
and  uninformed  traders  who  do  not  have  access  to  such  information.  The  market 
maker  therefore  expects  to  lose  from  trading  with  informed  traders  and  gain  from 
trading  with  less  informed  traders.  The  market  maker  is  therefore  incentivised  to 
establish a large spread to minimise potential losses from the former and to maximise 
potential gains from the latter. 

High bid-ask spreads and low liquidity result in the inefficient allocation of securities, 
which  results  in  additional  trading  costs  for  investors  for  which  they  need  to  be 
compensated  in  the  form  of  a  higher  rate  of  return  or  cost  of  capital  (Garleanu  and 
Pedersen,  2004).  Amihud  and  Mendelson  (1986)  and  Constantinides  (1986)  provide 

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support  for  the  link  between  lower  bid-ask  spreads  and  a  lower  cost  of  capital  by 
finding a significant relationship between higher spreads and higher yields. 

The  second  capital  allocation  challenge  identified  in  the  literature  is  the  agency 
problem.  Investors  typically  delegate  the  responsibility  for  overseeing  the  operations 
of  firms  in  which  they  have  invested  to  managers,  and  these  managers  have 
incentives  to  make  decisions  that  adversely  impact  on  the  interests  of  investors 
(Jensen  and  Meckling,  1976).7  Examples  might  include  excessive  management 
compensation  or  taking  excessively  risky  decision  because  of  potential  management 
bonuses. 

Corporate  disclosures  can  play  an  important  role  in  mitigating  the  information 
asymmetry  and  agency  problems  that  could  arise  in  capital  markets,  which  could 
otherwise  impede  the  optimal  allocation  of  savings  to  investment  opportunities.  The 
disclosure of information reduces uncertainty regarding the true value of the firm, and 
enables  investors  to  make  more  informed  decisions  about  investment  opportunities 
and  evaluate  whether  the  business  has  managed  its  resources  in  the  interests  of 
external owners or shareholders.8 Firms that wish to attract capital therefore have the 
incentive to distinguish themselves from rivals by increasing the quality of their public 
disclosures in order to reduce their effective cost of capital.9  

There is an existing body of literature that seeks to establish the empirical relationship 
between  disclosure  quality  and  capital  market  outcomes.  Studies  that  use  the 
Association  for  Investment  and  Management  Research  (AIMR)  analyst  rankings  of 
corporate  disclosure  as  a  proxy  for  voluntary  disclosure  quality  tend  to  find  a 
statistically  significant  relationship  between  disclosure  quality  and  capital  market 
impacts. For instance, Botosan and Plumlee (2002) study the association between the 
cost  of  equity  capital  and  voluntary  disclosure  quality  for  a  set  of  firms  including 
banks,  measured  by  AIMR  rankings.  They  find  a  significant  negative  relationship 
between  the  firm’s  disclosure  quality  rank  and  their  cost  of  equity  capital.  Similarly, 
Healy,  Hutton  and  Palepu  (1999)  concluded  that  firms  which  experienced  significant 
improvements  in  their  AIMR  disclosure  ratings  are  associated  with  improved  stock 

7  Corporate  governance  refers  to  the  structures  and  processes  in  place  aimed  at 
reducing  the  agency  problem  and  aligning  manager  and  shareholder  interests 
(Armstrong, Guay and Weber, 2010), and are one way of mitigating agency problems. 
Corporate  governance  arrangements  aim  to  ensure  that  management  is  held 
accountable  to  external  stakeholders  and  that  management  takes  business  decisions 
that  are  in  the  interest  of  shareholders.  The  relationship  between  corporate 
governance  arrangements  and  improved  governance  is  supported  by  empirical 
evidence:  Karamanou  and  Vafeas  (2005)  argue  that  the  board  size  improves 
monitoring diligence and Pearsons (2005) finds evidence that banks with independent 
audit committees reduce the likelihood of financial statement fraud. 
8  For  example,  an  increase  in  disclosures  provides  analysts  with  more  information  to 
be  factored  into  sophisticated  financial  models.  Disclosure  therefore  bridges  the 
information  gap  between  what  is  predicted  by  analysts’  financial  models  and 
managers’  private  information,  thereby  enabling  financial  models  to  become  more 
accurate  in  reflecting  a  company’s  underlying  value  and  to  be  more  informative  to 
investors. 
9 In the literature, most studies examine the impact of disclosure on the cost of equity 
capital. We prefer to refer to the effective cost of equity capital. This is because in our 
view the way in which disclosure quality affects the cost to a firm of acquiring equity 
capital is through changes in the asymmetry of information between management and 
investors  on  future  cash  flows,  rather  than  changes  in  the  underlying  cost  of  equity 
itself, which is driven by factors identified in the Fama-French “Three Factor model”. 

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market  performance,  decreases  in  investor  uncertainty  and  increases  in  institutional 
ownership, analyst coverage and stock liquidity.  

Welker  (1995)  finds  that  the  relative  bid-ask  spreads  for  firms  with  AIMR  disclosure 
rankings  in  the  bottom  third  were  approximately  50  percent  higher  than  spreads  for 
firms  in  the  top  third.  Espinosa,  Tapia  and  Trombetta  (2008)  measure  disclosure 
quality  by  the  rankings  of  annual  report  quality  of  Spanish  firms  published  by  a 
business magazine (which is similar to the AIMR rankings for US firms), and also find 
a  significant  relationship  between  increasing  the  quality  of  disclosures  and  lowering 
bid-ask spreads. Therefore, with greater information disclosures and lower information 
asymmetries, bid-ask spreads fall, causing excess required returns to fall, and thereby 
lowering the effective cost of equity capital. By lowering liquidity risks and transaction 
costs, a firm’s ability to raise capital in these liquid equity markets increases and firms 
are  able  to  increase  the  price  of  their  shares,  lowering  their  effective  cost  of  equity 
capital (Leuz and Verrecchia, 2000).  

Other studies have constructed their own specific disclosure scoring indices to analyse 
the  capital  market  impacts  of  disclosure.  Hail  (2002),  for  example,  uses  a  voluntary 
disclosure quality index developed by the Swiss Banking Institute10 to directly measure 
disclosure  quality,  and  finds  a  highly  significant  negative  relationship  between 
voluntary  disclosure  quality  and  the  cost  of  equity  capital.  Poshakwale  and  Courtis 
(2005),  unlike  other  authors,  focus  specifically  on  banks,  and  measured  voluntary 
disclosure  quality  by  incorporating  29  key  aspects  of  financial  and  non-financial 
performance  summarised  under  6  categories:  strategy,  customers  and  markets, 
people and reputation, risk management, financial position, and financial performance. 
The authors find a significant relationship between voluntary disclosures by European 
and non-European banks and a lower effective cost of equity capital. 

Another way for firms to signal their commitment to disclosure quality is by voluntarily 
adopting  international  accounting  standards  such  as  IFRS,  which  prescribe  a  higher 
level and quality of reporting than tends to be required by domestic accounting rules. 
For  example,  listed  companies  in  the  EU  have  opted  to  adopt  IFRS  standards  on  a 
voluntary  basis  before  2005  due  to  the  perceived  benefits  of  providing  high  quality 
financial information. 

The  findings  from  previous  empirical  studies  on  the  impact  of  voluntary  adoption  of 
IFRS  are  mixed.  Kim  and  Shi  (2007)  find  a  significant  negative  relationship  between 
voluntary  adoption  of  IFRS  and  the  cost  of  equity  capital.11  Similarly,  based  on 
observing firms which voluntarily switched from German GAAP to US GAAP, Leuz and 
Verrecchia  (2000)  find  a  significant  relationship  between  switching  and  lower 
percentage bid-ask spreads and higher share turnover, when controlling for firm size, 
financing  needs,  firm  performance  and  ownership  dispersion.  However,  more  recent 
studies  by  Daske  (2006)  and  Hail  and  Leuz  (2007)  find  no  significant  relationship 
between voluntary IFRS adoption and either a lower effective cost of equity capital, or 
increased market liquidity. 

10  The  index  encompasses  three  broad  categories:  background  and  non-financial 
information, trend analysis and management discussion and analysis and risk, value-
based  and  projected  information.  Eugster  measures  disclosure  quality  of  firms  using 
Swiss  GAAP,  excluding  those  from  the  financial  sector,  on  an  index  which  covers 
impression,  background  information,  non-financials,  trend  analysis,  risk  information, 
value  based  management,  management  discussion  and  analysis  of  annual  financial 
statements, goals and credibility and sustainability. 
11 Their sample excludes firms from the US and those from the financial sector due to 
differences in reporting behaviour and the heavily regulated nature of the industry. 

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However,  a  later  study  conducted  by  Daske  et  al.  (2013)  shows  that  on  average 
liquidity and costs of capital often do not change around voluntary adoptions of IFRS. 
However,  when  firms’  discretion  in  adopting  accounting  standards  are  taken  into 
account,  the  authors  show  that  firms  who  voluntarily  adopt  international  accounting 
standards  in  a  genuine  attempt  to  increase their  commitment  to  transparency (i.e.  a 
‘serious’  adopter)  demonstrate  lower  levels  of  cost  of  capital  and  higher  levels  of 
liquidity.  These  effects  are  not  observed  for  firms  who  adopt  the  standards  in  name 
only  while  making  very  few  changes  to  actual  reporting  practices  (i.e.  a  ‘label’ 
adopter).  The  differences  in  outcomes  help  to  explain  why  the  previous  evidence  on 
the voluntary adoption of IFRS is mixed. 

As  discussed  previously,  the  literature  suggests  that  firm  disclosure  decisions  do  not 
always  internalise  market-wide  impacts  and  are  based  solely  on  the  assessment  of 
firm-specific internal costs and benefits, and this does not lead to the socially optimal 
level  of  disclosure.  There  is  therefore  a  role  for  regulatory  requirements  that  compel 
firms to disclose certain information to correct for this market failure. 

One such solution is the mandatory adoption of internationally-recognised accounting 
standards. Regulators expect that the adoption of IFRS will improve the comparability 
of financial statements, and the quality of financial reporting and transparency, to the 
benefit  of  investors.12  There  is  a  range  of  literature  on  the  impact  of  mandatory 
adoption  of  IFRS.  Studies  of  the  mandatory  adoption  of  the  IFRS  in  the  EU  in  2005 
have generally found a statistically significant relationship between IFRS adoption and 
capital  market  outcomes.  Daske  et  al.  (2007)  find  that  the  mandatory  adoption  of 
IFRS  in  the  EU  is  associated  with  a  lower  effective  cost  of  equity  capital.13  This 
suggests  that  improving  the  quality  of  disclosures  is  effective  when  adopted 
universally,  allowing  investors  to  be  able  to  compare  disclosures  and  make  more 
informed  decisions.  Florou  and  Kosi  (2013)  observe  similar  findings  in  debt  capital 
markets, and show that IFRS adoption is associated with an increased likelihood of a 
firm  accessing  the  bond  market,  and  a  decrease  in  their  cost  of  bond  issuance14. 
Similarly, Li (2009) finds that the mandatory switch to IFRS for EU firms has led to a 
lower effective cost of equity capital, due to enhanced information comparability; this 
result is stronger the greater a country’s legal enforcement of the regulation.  

Studies on segment reporting also show that an increase in the granularity of segment 
information  is  associated  with  improved  capital  market  outcomes.  Greenstein  and 
Sami  (1994)  find that  the  implantation  of  the SEC’s  1970 “line  of  business”  segment 
reporting15 significantly lowered bid-ask spreads. Pelaez, Lara and Gine (2009) assign 
scores that proxy for the quality and detail of segment disclosures by designing their 
own index for US firms, and consider if this has an impact on Easton’s (2004) measure 
of  cost  of  equity  capital.  The  authors  find  that  an  increase  in  the  score  is  associated 
with  a  lower  effective  cost  of  equity  capital.  Similarly,  Saini  and  Herrmann  (2012) 
developed  a  scoring  index  to  capture  the number  of  segments  and  depth  of  detail  of 
segment  reporting  in  their  study  of  the  impact  of  SFAS  No.  13116  on  the  quality  of 

12 This aim is stated in EC Regulation No. 1606/2002, which mandates the adoption of 
IFRS  for  EU  listed  companies  for  annual  financial  statements  dated  1  January  2005 
onwards. 
13 See also among others, Hail and Leuz (2007) and De Franco, Kothari and Verdi. 
14  Although  the  authors  do  not  observe  a  significant  relationship  between  IFRS 
adoption and loan rates. 
15  Mandatory  requirement  issued  by  the  SEC  in  1970  for  US  companies  engaged  in 
more than one “line of business” to issues segmented disclosures (Sommer, 1970). 
16  Financial  Accounting  Standards  Board  (FASB)  pronouncement  No.131:  ‘Disclosures 
about  Segments  of  an  Enterprise  and  Related  Information’  (FASB,  1997).  It 
established  standards  for  disclosing  information  on  operating  and  geographic 

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segment  reporting  for  manufacturing  firms.  The  authors  also  find  a  significant 
negative relationship between the granularity of segment disclosures and the effective 
cost of equity capital.  

Transparency impacts 

Disclosure  quality  is  also  linked  to  transparency.  Transparency  refers  to  the  extent 
that disclosures reveal a firm’s underlying economic position in an understandable way 
(Barth  and  Schipper,  2008).  The  term  therefore  encompasses  many  aspects  of 
disclosure  quality,  such  as  the  reliability,  accuracy  and  the  comparability  of 
statements.  

The  impact  of  disclosure  on  transparency  is  linked  to  the  role  of  intermediaries  of 
corporate information. Management disclosures that are provided on a voluntary basis 
tend not to be directly certified by external parties, in a way that financial statements 
are  subject  to  external  scrutiny  by  independent  auditors.  The  costs  of  monitoring  for 
investors  and  external  stakeholders  can  also  be  prohibitive,  which  exacerbates 
information  asymmetries  and  agency  problems.  Therefore  the  credibility  of  voluntary 
management  disclosures  relies  on 
its  use  and  dissemination  by  external 
intermediaries,  such  as  financial  analysts,  industry  experts  and  ratings  agencies 
(whose costs of monitoring are presumably lower), that engage in private information 
production  to  provide  insights  into  managers’  superior  information  or  to  identify  any 
suboptimal  use  of  firm  resources.  In  fact,  Schipper  (1991)  argues  that  financial 
analysts  are  sophisticated  users  of  firm  disclosures,  and  that  it  is  for  them  that  firm 
disclosures  are  ultimately  intended.  These  intermediaries  interpret  firms’  disclosures 
together with other market information in order to provide an independent view on the 
outlook  and  future  performance  of  the  business,  for  example  by  providing  earnings 
and profits forecasts. 

Following  this  logic,  greater  transparency  should  therefore  allow  analysts  and  other 
intermediaries to make more informed judgements or arrive at a consensus about the 
future  performance  and  profitability  of  the  firm,  thereby  mitigating  the  problems  of 
information  asymmetry  and  agency.  For  instance,  Lang  and  Lundholm  (1996)  report 
that firms committed to providing informative disclosures are associated with a higher 
analyst  following,  more  accurate  forecasts  and  lower  forecast  dispersion  and 
volatility.17  Likewise,  Hope  (2003)  finds  a  significant  relationship  between  the  extent 
of  accounting  policy  disclosures  (as  measured  by  the  CIFAR  rankings18)  and  lower 
forecast  dispersion  and  reduced  forecast  errors.  Floyd  (2014)  finds  a  significant 
association  between  increasing  transparency19  and  lowering  forecast  errors  and 
dispersion.  However,  the  following  year;  the  author  finds  no  association  between 
transparency and analyst coverage, suggesting analysts respond more to longer-term 
trends  in  transparency.20  The  readability  and  presentation  of  reports  have  also  been 
shown to improve transparency: Lehavy, Li and Merkley (2011) demonstrate that less 

segments, as well as granular information regarding products and services and major 
customers.  
17 The authors use data from the Financial Analysts Federation Corporate Information 
18  Centre  for  International  Financial  Analysis  and  Research  evaluations  of  corporate 
disclosure levels, which consider the income statement, the balance sheet, cash flow, 
stockholder information and accounting policies of annual statements.  
19 Transparency is measured by the extent to which earnings and changes in earnings 
co-vary contemporaneously with returns (Barth, Konchitichki, Landsman, 2013) 
20  Floyd  uses  OLS  fixed  effects  and  measures  transparency  using  the  empirical 
approach  of  Barth,  Konchitchki  and  Landsman  (2013),  which  uses  a  measure  of  the 
extent  to  which  earnings  and  changes  in  earnings  co-vary  contemporaneously  with 
annual stock returns. 

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reporting complexity leads to increased forecast accuracy and certainty (lower forecast 
dispersion). 

The  impact  of  IFRS  adoption  on  transparency  is  well-documented  in  the  literature. 
Wang, Young and Zhuang (2008) show that the mandatory transition to IFRS in 2005 
for  European  firms  led  to  lower  forecast  errors  and  dispersion,  thus  increasing 
transparency.  Greater  transparency  allows  analysts  to  make  an  informed  decision 
regarding  the  true  value  of  a  firm,  allowing  a  consensus  about  a  firm  to  develop 
among analysts. In a similar study on IFRS adoption in the EU, Horton, Serafeim and 
Serafeim (2008) find that the largest improvement in the information environment (as 
proxied  by  analyst  forecast  accuracy,  following  and  dispersion)  are  for  firms  that 
voluntarily adopted IFRS earlier due to the presence of externalities21. They observe a 
similar  effect  for  firms  that  were  forced  to  adopt  the  IFRS,  but  interestingly,  the 
observed  benefits  were  limited  to  non-financial  sector  firms.  22  Ashbaugh  and  Pincus 
(2000) show that the adoption of the International Accounting Standard (IAS), which 
preceded the IFRS, has a significant relationship with decreasing the absolute value of 
the forecast error, increasing forecast accuracy.  

The  ability  to  compare  financial  statements  efficiently  is  of  considerable  value  to 
analysts, lowering the cost of acquiring information and increasing investor confidence 
and  accuracy.  This  serves  to  aid  the  efficient  allocation  of  capital  and  encourages 
cross-border investment and trade, generating much wider impacts. Stickney and Weil 
(2006) consider that a single firm’s disclosures, on their own provide little context and 
are  therefore  of  little  value  to  investors.  De  Franco,  Kothari  and  Verdi  (2009)  find 
significant  relationships  between  an  increase  in  the  comparability  of  financial 
statements  and  greater  analyst  following,  increased  accuracy,  reduced  forecast 
optimism and a lower dispersion of analyst forecasts.23  

Bradshaw,  Miller  and  Serafeim  (2008)  also  confirm  the  importance  of  adopting 
common accounting methods in improving transparency. The authors find that there is 
a  positive  association  between  US  firms  which  use  atypical  accounting  methods  and 
higher absolute forecast errors and increased forecast dispersion. Atypical accounting 
methods  increase  the  complexity  of  analysis  and  cause  frictions  in  comparing 
disclosures.24  

21  Ernstbereger,  Krotter  and  Stadler  (2008)  show  that  the  voluntary  adoption  of 
international accounting standards such as the IFRS or US GAAP by German firms led 
to improved forecast accuracy compared to firms using German GAAP. These findings 
are corroborated by Daske and Gebhardt (2006). 
22  The  lack  of  improvement  for  non-financial  sector  firms  may  be  due  to  potential 
estimation  errors  and  managerial  bias  arising  from  the  application  of  fair  value 
accounting  (Muller  et  al.,  2008)  and  the  increased  volatility  of  earnings,  relative  to 
historical-based measures. 
23  De  Franco,  Kothari  and  Verdi  (2009)  conceptually  define  financial  statement 
comparability in two ways: (1) if for a given set of economic events, two firms produce 
similar  financial  statements  and  (2)  if  firms  with  correlated  economic  events  and 
similar accounting of these events have correlated financial statements over time, and 
as  such  measure  comparability  by  (a)  the  negative  value  of  the  average  absolute 
difference between the predicted earnings of firm i and firm j and (b) the adjusted R2 
of the pair-wise historical correlation between the earnings of two firms.  
24  A  firm  is  considered  to  use  an  atypical  accounting  method  if  they  do  not  use  the 
accounting  method  used  by  the  mode  of  their  industry  (Fama  and  French  industry 
classifications,  1997).  An  example  is  using  the  “Last  In  First  Out”  (LIFO)  principle 
when  most  firms  in  the  industry  use  “First  In  First  Out”  (FIFO).  This  is  based  on  the 
idea  that  accounting  method  choices  tend  to  cluster  within  industry  (Bowen, 
DuCharme and Shores, 1999). 

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There  is  also  some  evidence  to  suggest  that  segmental  reporting  helps  to  improve 
transparency.  Swaminathan  (1991)  finds  a  negative  relationship  between  the  SEC-
mandated  1970  segment  disclosures  and  the  coefficient  of  variation  of  analysts’ 
forecasts.25 Similarly, Prather-Kinsey (2000) finds a negative relationship between the 
number  of  geographical  segment  disclosures  and  forecast  dispersion  and  the  median 
forecast  error.  Behn  et  al.  (2002)  find  that  geographical  segment  information  under 
SFAS No. 131 lowered analyst forecast errors, proving evidence on the usefulness and 
importance  of  granular  disclosures  to  investors.  Botosan  and  Stanford  (2005)  and 
Venkataraman  (2001)  provide  support  for  this  result,  finding  a  positive  relationship 
between  SFAS  131  segment  reporting  adoption  and  higher  forecast  accuracy.  This  is 
supported  by  Pelaez  et  al.  (2009)  who  use  their  own  segment  quality  index  to  find 
that analysts are better able to forecast the earnings of firms accurately where there 
is higher quality segment reporting.  

Interestingly,  other  studies  have  also  found  that  non-financial  reporting,  specifically 
corporate  governance  disclosures,  can  also  have  an  impact  on  analyst  forecasts. 
Dhaliwal  et  al.  (2012)  find  that  firm  transparency  in  the  form  of  corporate  social 
responsibility  (CSR)  reporting  is  associated  with  lower  analyst  forecast  error  in 
countries  where  CSR  performance  is  more  likely  to  affect  firm  financial  performance. 
There are empirical links between the quality of corporate governance disclosures and 
the  accuracy  of  forecasts.  Beekes  et  al.  (2012)  outline  that  the  more  transparent  a 
firm is regarding the disclosures of its corporate structure and the more independent a 
board  is,  the  more  credible  a  firm’s  overall  disclosures  are  deemed  to  be;  it  is  this 
credibility that drives the relationship, with analysts then placing more weight on the 
information  disclosed  when  forecasting.  Furthermore,  Beekes  and  Brown  (2006)  find 
that disclosures by better governed companies are more informative. Karamanou and 
Vafeas (2005) argue that the board size improves monitoring diligence and disclosures 
and  Ahmad-Zaluki  and  Wan-Hussin  (2010)  conclude  that  effective  corporate 
governance  is  associated  with  higher-quality  disclosures  flowing  from  managers  to 
investors,  increasing  forecast  accuracy.  Therefore,  corporate  governance  also  drives 
accuracy  by  making  disclosures  more  informative,  increasing  the  overall  value  of 
disclosures to analysts. 

Accounting quality impacts 

The  introduction  of  international  reporting  standards  such  as  the  IFRS  (or  its 
predecessor, the IAS) has also prompted research into the impacts of new standards 
on  the  quality  of  accounting  information.  For  instance,  in  the  absence  of  enhanced 
mandated  disclosures,  firms  have  the  ability  to  engage  in  earnings  management  in 
order  to  present  the  entity  in  an  artificially  positive  light  to  investors.  Changes  to 
reporting  and  accounting  standards  that  seek  to  eliminate  these  incentives  could 
improve  accounting  quality.  Accounting  quality  is  therefore  important  to  ensure  that 
financial  reporting  reflects  the  true  economic  condition  of  the  business,  and  enables 
external  stakeholders  to  exert  market  discipline  effectively.  Michael  (2004)  asserts 
that  shortcomings  in  the  comprehensiveness  and  timeliness  of  financial  information 
exacerbated the negative impacts of the Asian financial crisis. Biddle and Hilary (2006) 
also  suggest  that  high  accounting  quality  reduces  information  asymmetry  between 
managers  and  outside  suppliers  of  capital  and  therefore  would  improve  investment 
efficiency.26  Accounting  quality  is  negatively  associated  with  investment-cash  flow 

25  The  coefficient  of  variation  in  analyst’s  forecasts  is  the  square  root  of  dispersion 
scaled by the absolute value of the mean forecast. 
26  The  authors  measure  poor  accounting  quality  as  the  presence  of  the  following: 
earnings aggressiveness, loss avoidance, and earnings smoothing. 

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sensitivity  (Biddle,  Hilary  and  Verdi,  2006).  Real  earnings  management27  can  also 
mask  a  firm’s  current  unbiased  economic  performance,  and  could  endanger  its 
competitiveness in the long term (Wang and D’Souza, 2006, Zang, 2007). 

There  are  three  commonly-used  proxies  for  accounting  quality  as  applied  in  the 
literature.  The  first  of  these  is  earnings  smoothing,  which  can  be  measured  by  the 
variability of change in net income, or the variability of change in net income scaled by 
the  variability  of  change  in  cash  flow  operations.  A  high  variability  is  consistent  with 
less  earnings  smoothing,  and  therefore  there  should  be  a  positive  relationship 
between  variability  and  accounting  quality.  The  second  concerns  accruals  quality. 
Firms  which  manage  their  earnings  are  more  likely  to  display  a  larger  negative 
correlation  between  accruals  and cash flows, as  managers  respond  to  poor  cash  flow 
outcomes by increasing accruals. Similarly, a high magnitude of discretionary accruals 
indicates a greater level of earnings management, or lower accounting quality. 

The  third  measure  concerns  managing  earnings  to  achieve  consistent  positive 
earnings,  which  research  suggests  is  a  common  goal  of  earnings  management. 
Burgstahler and Dichev (1997) suggest firms have strong incentives to avoid reporting 
negative  losses  and  exhibit  consistent  profitability,  with  the  aim  of  maintaining  their 
equity value (DeAngelo et al., 1996). The theory behind this is that firms manage their 
earnings  in  order  to  report  small  positive  earnings  rather  than  negative  ones.28 
Therefore,  the  presence  of  small  positive  earnings  could  be  indicative  of  earnings 
management (Burgstahler and Dichev, 1997; Beatty et al., 2002; Dichev and Skinner, 
2002;  Beaver  et  al.,  2003b;  Phillips  et  al.,  2003,  2004;  Frank  and  Rego,  2006; 
Roychowdhury, 2006; Jorgensen, 2007). Burghstahler and Dichev (1997) explain how 
earnings  slightly  less  than  zero  occur  infrequently,  and  earnings  slightly  above  zero 
occur  more  frequently  than  a  probability  distribution  of  firm  earnings  would  suggest, 
providing evidence for earnings management to achieve small positive earnings.  

Barth et al. (2007) conducted a study on the impact of the application of International 
Accounting  Standards  (IAS)  on  accounting  quality.  In  their  study,  earnings 
management is proxied by the presence of small, positive earnings. They find that the 
application of IAS has reduced the likelihood of small, positive earnings being present. 
The  authors  also  find  that  net  income  volatility  is  higher  for  IAS  firms  and  the 
correlation between accruals and cash flow is significantly negative for non-IAS firms, 
which together, suggest that IAS does lead to improved accounting quality and firms 
are less likely to manage their earnings. 

Further  improvements  to  accounting  standards  introduced  by  the  IFRS  have  also  led 
to  more  recent  studies  in  this  area.  Barth  et  al.  (2008)  present  three  reasons  why 
IFRS  adoption  leads  to  an  improvement  in  accounting  quality.  First,  by  eliminating 
certain accounting alternatives and reducing the scope for managerial discretion, IFRS 
reduces  the  extent  of  opportunistic  earnings  management  and  thus  improves 
accounting  quality  (Ewert  and  Wagenhofer,  2005).  Second,  the  nature  of  IFRS  as  a 
principles-driven standard makes it less susceptible to managerial circumvention, and 
it  is  more  difficult  to  avoid  recognition  of  a  liability  through  transaction  structuring. 
Finally,  IFRS  permits  measurements,  such  as  the  use  of  fair  value  accounting,  which 

27  Accruals-based  earnings  management  is  where  managers  exercise  discretion 
opportunistically  over  estimations  and  judgements  that  go  into  the  process  of 
preparing 
involves 
financial  statements;  whereas  real  earnings  management 
managing  earnings  by  changing  the  timing  or  structure  of  operating,  investing  or 
financial decisions. 
28 In the majority of literature this is measured by the binary variable which takes the 
value  of  one  if  earnings  are  between  0  and  0.01,  where  below  0.01  is  considered 
small. Firms that consistently get a one are considered to be managing their earnings. 

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could  better  reflect  the  true  financial  position  of  the  business  than  domestic 
standards.29  

In  a  similar  vein,  CBCR  could  lessen  incentives  for  earnings  management  at  the 
segment  level  by  requiring  firms  to  report  detailed  financial  information.  Investors 
may  seek  to  reconcile  the  CBCR  data  with  the  annual  accounts  and  the  external 
scrutiny in this regard could lessen incentives to manage earnings   

However,  the  evidence  on  the  impact  of  IFRS  on  accounting  quality  is  mixed,  and  is 
dependent  on  the  conditions  under  which  they  are  adopted.  Barth  et  al.  (2008)  find 
that firms that adopted IFRS voluntarily are less likely to manage earnings towards a 
target  after  controlling  for  potential  incentives  that  drive  the  choice  of  accounting 
standard. Christensen, Lee and Walker (2008) use managing earnings towards small, 
positive  values  as  a  proxy  for  accounting  quality.  The  authors  find  a  significant 
relationship  between  the  adoption  of  IFRS  and  decreased  earnings  management  for 
firms  that  voluntarily  adopted  IFRS,  but  no  such  relationship  for  firms  that  adopted 
IFRS  only  when  it  became  mandatory.  This  finding  provides  some  evidence  for  the 
importance of firm initiatives in driving accounting quality, rather than the imposition 
of mandatory accounting standards.  

Chen  et  al.  (2010)  analyse  the  impact  of  increasing  comparability  as  a  result  of 
mandatory IFRS adoption in the EU on accounting quality. In contrast, the authors find 
that  IFRS  adoption  in  the  EU  led  to  reduced  likelihood  of  earnings  management 
towards  a  target,  a  lower  number  of  absolute  discretionary  accruals  and  higher 
accruals  quality.  However,  the  authors  also  find  that  firms  engage  in  more  earnings 
smoothing  and  less  timely  recognition  of  large  losses  even  after  IFRS  adoption. 
Specific to the FS sector, Gebhardt and Novotny-Farkas (2011) examine the impact of 
IFRS  adoption  by  European  banks  on  accounting  quality,  and  find  that  the  change  in 
the  recognition  and  measurement  of  banks’  main  operating  accrual  item  –  loan  loss 
provision  –  is  associated  with  the  reduced  likelihood  of  income  smoothing  behaviour 
and increases timely loss recognition. 

However,  a  recent  study  by  Ahmed,  Neel  and  Wang  (2013)  provides  preliminary 
evidence  that  firms  that  adopted  the  IFRS  only  when  it  became  mandatory  exhibit  a 
significant  increase  in  income  smoothing  and  aggressive  reporting  of  accruals,  and  a 
significant  decrease  in  the  timeliness  of  loss  recognition  relative  to  benchmark firms. 
These results provide some evidence to suggest that firms who voluntarily adopt the 
IFRS  are  also  more  likely  to  have  stronger  incentives  to  report  higher  quality 
accounting numbers than firms who adopt the IFRS under a mandatory regime.   

Botosan  and  Stanford  (2005)  find  that  firms  were  withholding  segment  information 
under SFAS No. 14,30 concealing profits in less competitive industries in order to deter 
potential  entrants,  and  this  concealment  was  revealed  with  the  mandatory 
implementation  of  SFAS  No.  131.  This  suggests  segmental  reporting  contributes  to 
improving  the  information  environment  and  can  have  an  impact  on  increasing 
competitive pressures. Chen and Zhang (2003) also find that segment disclosures are 
useful  for  investors  and  increase  firm  value  as  they  increase  the  relevance  of 
accounting  numbers  to  fair  value.  Pelaez  et  al.  (2013)  also  find  that  better  quality 
segment information is associated with improved earnings quality. 

29  However,  Barth  et  al.  (2008)  also  acknowledge  that  the  lack  of  detailed  guidance 
leaves managers with some discretion over reporting (Langmead and Soroosh, 2009). 
The lack of accounting alternatives could also lead to managers using less appropriate 
approaches  to  communicate  the  underlying  economics  of  the  business  which  may 
decrease accounting quality. 
30  FAS  14:  “Financial  Reporting  for  Segments  of  a  Business  Enterprise”,  1976.  This 
statement was superseded by SFAS No. 131. 

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Wider market impacts 

The  literature  also  recognises  that  there  could  be  wider  market  impacts  or 
externalities that are associated with improved disclosure quality. 

There  are  studies  that  suggest  that  improvements  in  disclosure  quality  can  have  a 
“domino  effect”,  i.e.  encouraging  more  and  more  firms  to  adopt  better  quality 
reporting  practices.  Grossman  (1981)  and  Milgrom  (1981)  argue  that  rational 
consumers will assume that non-disclosing banks offer higher risk shares than others, 
thereby  motivating  higher  quality  banks  to  improve  disclosures  and  stimulating 
competition  if  lower  quality  banks  respond  positively  to  this  competitive  pressure. 
However,  Verrecchia  (1983)  argues  that  this  is  only  true  if  disclosure  is  costless;  if 
significant administration costs exist, only those with good news have an incentive to 
disclose information.  

Chen,  Young  and  Zhuang  (2011)  find  that  greater  cross-border  comparability  of 
disclosures attributed to the mandatory adoption of IFRS by European firms, leads to 
spillover effects on foreign firms’ investment efficiency, although these firms have not 
adopted IFRS. Sejen (2013) finds a significant relationship between the EU mandatory 
adoption  of  IFRS  and  increased  competition,  as  measured  by  the  Herfindahl  index.31 
The  author  provides  a  theoretical  explanation  for  this  result:  with  harmonised 
accounting,  investors  are  able  to  directly  compare  a  larger  pool  of  banks,  creating 
incentives  for  them  to  differentiate  themselves  from  rivals  and  thereby  stimulating 
competition.  Disclosure  can  also  benefit  other  firms  by  revealing  information  about 
consumer  trends,  technological  developments  and  other  industry  factors  (Leuz  and 
Wysocki, 2008). 

Banks’ disclosures have also been linked to financial stability. Sowerbutts, Zimmerman 
and Zer (2013)32 argue that inadequate public disclosures by banks contributed to the 
financial  crisis.  The  lack  of  information  required  by  investors  to  assess  bank  risk 
caused a dramatic increase in funding costs as investors withdrew lending in times of 
systemic stress. Better quality public disclosures could therefore alleviate problems of 
asymmetric  information  between  banks  and  investors,  allowing  capital  to  continue 
flowing  to  healthy  banks.  Improved  disclosures  therefore  act  as  a  tool  for  market 
discipline,  by  reducing  the  likelihood  of  banks  taking  on  more  risk  than  is  desirable 
without the knowledge of investors, thereby reducing the likelihood of future financial 
crises.  In  a  similar  vein,  Mehran  and  Mollineaux  (2012)  suggest  that  regulatory 
disclosure  requirements  that  promote  the  quality  of  security  prices  can  improve  the 
governance of financial institutions.  

Bischof  and  Daske  (2013)  also  provide  initial  evidence  that  one-time  mandatory 
disclosures about sovereign risk exposure lead to an increase in voluntary disclosures 
in  following  periods.  The  authors  argue  that  the  one-time  mandatory  disclosure  can 
induce  a  shift  in  the  voluntary  disclosure  equilibrium  for  two  reasons:  first,  reporting 
structure  that  is  implemented  to  fulfil  the  one-time  requirement  can  be  used  in  the 
future,  reducing  the  future  cost  of  providing  voluntary  disclosures.  Second,  the 
information from stress tests is used by investors to update their beliefs about banks’ 
sovereign  risks.  If  banks  do  not  continue  to  disclose  their  risk  exposures,  investors 
could  interpret  the  withheld  information  as  unfavourable,  resulting  in  higher  risk 
premia for  the bank or lower cash flow expectations. These two factors contribute to 

31 A measure of the degree of concentration of an industry.  
32  The  authors  set  out  five  areas  where  improvements  in  disclosures  would  be 
desirable. These are: funding risk, group structure, valuation, intra-annual information 
and financial interconnections. 

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the likelihood of firms continuing to provide these disclosures voluntarily following the 
one-off mandatory disclosure requirement.33  

Applicability of these findings to CBCR 

Overall,  the  literature  on  the  quality  of  voluntary  disclosures  and  the  impact  of  the 
adoption  of  accounting  standards  provides  some  evidence  that  improvements  in 
overall disclosure quality (or improvements driven by the adoption of internationally-
recognised  accounting standards)  are  associated  with  better  firm  outcomes  in  capital 
markets, transparency and accounting quality.  

We  may  be  able  to  infer  from  the  literature  that  the  provision  of  segmental  financial 
information  specifically  is  likely  to  lead  to  an  increase  in  the  public  availability  and 
granularity of financial information, which contributes to a lower cost of equity capital 
(Pelaez et al., 2009, Saini and Herrmann, 2012), better transparency (Venkataraman, 
2001;  Botosan  and  Stanford,  2005;  Pelaez  et  al.,  2009)  and  improved  accounting 
quality  (Chen  and  Zhang,  2003;  Botosan  and  Stanford,  2005;  Pelaez  et  al.,  2013). 
This  suggests  that  the  implementation  of  CBCR,  which  requires  the  disclosure  of  key 
information on a country-by-country basis, could result in similarly positive impacts. 

If CBCR leads to an improvement in disclosure quality, it may be cheaper for banks to 
access capital markets, and these benefits could be passed on to non-financial sector 
firms  and  households  in  the  form  of  lower  lending  rates.  Lower  borrowing  rates  for 
banks can also lead to increased credit availability as banks, with the protection from 
bigger  margins,  are  more  willing  to  increase  lending  supply  (Greenwald,  Stiglitz  and 
Weiss, 1984; and Baker and Wurgler, 2013). An increase in credit availability can also 
induce further investment, as credit availability has been identified as a key constraint 
for  further  investment  by  non-financial  sector  firms  (Greenwald,  Stiglitz  and  Weiss, 
1984).  Bassanini,  Scarpetta  and  Hemmings  (2001)  and  Leahey,  Schich  also  show 
empirical evidence linking credit to the non-financial sector to increased investment. 

Reducing  the  cost  of  equity  has  been  linked  to  increased  investment  within  the 
financial  sector  as  it  becomes  more  profitable  to  invest  when  borrowing  costs  are 
lower  (Blundell-Wignall  and  Roulet,  2013).  Investment  decisions  are  theoretically 
based  on  a  comparison  of  the  certainty  equivalent  yield  with  market  interest.  If 
borrowing  costs  are  lower  this  comparison  encourages  investment  due  to  its  relative 
greater returns (Modigliani and Miller, 1958).  

Firms  that  undertake  earnings  management  could  have  a  short-term  competitive 
advantage  over  their  competitors  due  to  their  ability  to  report  better  than  actual 
earnings.  However,  this  can  result  in  the  misallocation  of  resources  and  result  in 
misleading  information  provided  to  external  stakeholders.  The  motivations  seen  to 
underlie  the  decision  to  manage  earnings  are  avoidance  of  debt  covenant  violations, 
evasion  of  regulation,  manipulation  of  perceptions  held  by  market  participants  and 
maximisation of mangers own compensation (Fang, 2012). Earnings management can 
have  damaging,  industry-wide  effects  on  the  credibility  and  quality  of  reported 
earnings,  which  leads  to  the  belief  that  reported  earnings  do  not  reflect  economic 
reality.  This  can  cause  volatility  in  stock  prices  and  undermines  the  allocation  of 
resources  in  capital  markets.  For  example,  it  is  well  documented  that  earnings 
management  causes  inflated  stock  prices  before  price  offerings,  and  the  overly 
optimistic  expectations  then  cause  drops  in  stock  shares  (Tech,  Welch  and  Wong, 
1998; and Beneish and Vargus, 2002; Chou, Gambola and Lui, 2005). 

33  They  show  that  although  the  bid-ask  spreads  of  stress  test  participants  generally 
increased following mandatory stress tests in 2011, the reduction in market liquidity is 
almost  entirely  attributable  to  participants  who  failed  to  commit  to  maintaining  their 
disclosures on sovereign risks voluntarily. 

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Although  earnings  management  in  part  maintains  a  perception  of  stability,  in  the 
longer term, reducing earnings management will increase financial stability. With less 
earnings management the market will be more aware of the true value of banks. Thus 
we  could  observe  fewer  cases  of  over-  or  under-pricing  of  stock,  which  reduces 
volatility  and  improves  financial  stability.  If  the  introduction  of  CBCR  has  a  credible 
impact  on  reducing  the  likelihood  of  earnings  management,  this  results  in  fiercer 
competition to get the larger market share, earnings etc. in order to attract investors 
(Healy and Wahlen, 1999), which could also have a beneficial impact on competition. 

in  practice.  Firstly,  although  accounting  standards  have 

However,  Roberts  (2010)  sets  out  several  reasons  why  the  granularity  of  financial 
information  may  impart  information  of  limited  value  externally  with  few  significant 
introduced 
impacts 
requirements  for  segment  reporting,  the  lack  of  detailed  technical  guidance  on 
segment identification leaves management with significant discretion in identifying its 
primary and secondary reportable segments (the basis for choosing the main business 
units  and/or  geographic  segments  to  report)  and  how  these  are  presented.  This 
means  that  companies  can  report  relatively  broad  segments,  covering  quite  different 
industries and/or distinct geographies. 

Second, even if companies do disclose reasonably granular information, it may not be 
particularly  informative  either  for  management  or  external  stakeholders.  Highly 
integrated  companies  could  have  segments  for  which  their  individual  performance  is 
highly  correlated  with  the  performance  of  other  segments,  rather  than  be  driven  by 
the economic or institutional factors of the jurisdictions within which they reside. The 
segments  may  also  not  be  comparable  with  the  segments  reported  by  other 
companies,  as  operating  segments  are  likely  to  be  determined  by  firm-specific 
characteristics.  Additionally,  the  larger  the  common  costs  that  have  to  be  allocated 
across  different  segments,  the  more  likely  is  the  performance  of  individual  segments 
to  be  dependent  on  the  specific  cost  allocation  method  used,  which  is  also  likely  to 
differ across firms. 

Although  the  literature  offers  some  interesting  insights  on  the  potential  impacts  of 
CBCR,  the  applicability  of  the  evidence  in  the  CBCR  setting  should  be  treated  with 
caution. 

First,  while  the  research  on  voluntary  disclosure  quality  generally  yields  positive 
impacts  in  terms  of  capital  market  outcomes,  transparency  and  accounting  quality, 
these results may not be generalizable in a mandatory setting, which is the case with 
CBCR.  For  instance,  Ashbaugh  and  Pincus  (2001),  Guan  et  al.  (2006)  and  Bae  et  al. 
(2008)  show  that  the  effects  of  mandatory  IFRS  adoption  differ  from  the  effects  of 
voluntary  adoption.  The  magnitude  and  statistical  significance  of  the  effects  could 
therefore  differ  in  comparison  to  previous  studies  following  the  implementation  of 
Article 89.34  

Second, while the research on segmental disclosures offers some evidence to suggest 
that  the  public  availability  of  information  provided  for  individual  business  units  or 

34  There  is  a  general  point  to  be  made  on  the  usefulness  of  event  studies  such  as 
those  on  IFRS  adoption.  National  accounting  standards  such  as  local  Generally 
Accepted  Accounting  Principles  (local  GAAP)  have  been  on  a  long-term  pattern  of 
convergence  towards  IFRS  to  smooth  out  the  marginal  costs  of  compliance  in 
anticipation  of  IFRS  adoption  in  the  EU.  This  limits  the  explanatory  powers  of  event 
studies  that  assess  the  impacts  prior  to  and  following  mandatory  IFRS  adoption,  as 
these local GAAPs already resembled IFRS to an extent. Related to this point, Daske et 
al.  (2007)  also  caution  that  the  mandatory  adoption  of  IFRS  coincided  with 
improvements in enforcement and governance regimes, making it difficult to attribute 
the benefits in their entirety to IFRS. 

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geographic  segments  can  have  significant  economic  impacts,  this  is  based  on  the 
impact of existing segment disclosure requirements (e.g. SFAS No. 131 and IFRS 8), 
which  do  not  require  information  to  be  reported  on  a  country-by-country  basis 
specifically.  We  can  only  draw  general  conclusions  in  this  instance  on  the  impact  of 
increasing granularity of financial information.  

Third,  whilst  there  is  a  significant  body  of  literature  that  considers  the  impacts  of 
disclosures by non-financial firms, similar empirical studies for the financial sector are 
generally lacking.35 Such a study that focuses on the financial sector is timely, as the 
recent  international  financial  crisis  and  other  issues  have  arguably  exposed  the  need 
for regulatory reform and improved reporting and disclosure requirements. 

Fourth, banks have also gradually improved the quality of their disclosures over time. 
The  historical  studies  we  consider  in  this  section  consider  the  impacts  of  earlier 
incremental improvements to disclosure quality, however further improvements could 
be  subject  to  diminishing  returns.  Banks  are  already  subject  to  high  disclosure 
requirements  relative  to  other  sectors,  and  it  is  unclear  whether  the  increase  in 
disclosures will amount to additional valuable information for investors and the general 
public.  

Finally,  econometric  studies  of  this  nature  could  be  subject  to  estimation  problems 
such as reverse causality. For instance, although these studies consider how changes 
in  disclosure  quality  can  influence  firm  outcomes,  there  could  be  some  reverse 
causality,  meaning  that  firm  outcomes  also  influence  their  decisions  on  disclosure 
quality.  If  these  factors  are  not  properly  controlled  for  by  using  the  appropriate 
econometric  techniques,  it  could  lead  to  misleading  results.  The  findings  of  more 
recent  empirical  research,  which  use  more  sophisticated  econometric  techniques  to 
take  into  account  potential  estimation  problems,  have  overturned  results  that  were 
previously  shown  to  be  significant.  For  example,  Eugster  (2014)  overturns  the  result 
in  Hail  (2002)  by  adopting  a  generalised  method  of  moments  (GMM)  approach  to 
control  for  dynamic  endogeneity  to  account  for  the  likely  correlation  between 
voluntary  disclosure  quality  and  the  lagged  values  of  cost  of  equity  capital.  36  We 

35 Many of the studies we reviewed tend to exclude the financial services sector due to 
the  differences  in  the  regulatory  environment  and  the  nature  and  extent  of  the 
industry’s regulated disclosures. 
36 Eugster (2014) uses the disclosure index developed by the Department of Banking 
and Finance at the University of Zurich and scores a sample of 293 Swiss companies. 
This  index  encompasses  different  aspects  of  public  disclosure,  such  as  overall 
impression,  availability  of  background  information,  availability  of  non-financials, 
availability  of  trend  analysis,  availability  of  risk  information,  implementation  pf  value 
based  management,  comprehensiveness  of  management  discussion  and  analysis  of 
annual 
and 
availability 
comprehensiveness of sustainability reporting. 

statements, 

credibility 

financial 

goals 

and 

of 

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therefore  seek  to  address  potential  estimation  problems  using  more  sophisticated 
econometric approaches such as the GMM approach. This is discussed in more detail in 
the following methodology section. 

We  may  conclude  from  the  reasons  above,  that  although  the  literature  can  be  quite 
instructive  on  the  impacts  of  firms’  disclosure  quality  and,  specifically,  the  impact  of 
granular  financial  reporting,  we  should  remain  cautious  about  extrapolating  these 
impacts  to  draw  definitive  conclusions  for  the  impact  of  CBCR.  This  is  because  these 
studies  do  not  relate  directly  to  CBCR  and  therefore  the  results  from  the  literature 
may not be generalisable in the context of CBCR.  

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Methodology development and data collection 
In this section we outline our econometric methodology and the data and variables we 
used to assess the impact of disclosure quality. In particular: 

• 

• 

• 

• 

We summarise our key hypotheses and the outcome variables that we focus on 
in this study 
We set out the sample selection criteria to obtain the list of banks included in our 
analysis. 
We set out the disclosure quality scoring framework used to score the banks’ 
disclosures in annual reports and discuss the patterns in banks’ disclosure quality 
and how this has changed over time. 
We discuss the econometric methods we use in our regressions.  

Hypotheses 

Based  on  the  literature  review,  we  identified  the  following  possible  firm  outcomes 
associated with changes in disclosure quality to be of interest in our study: 

1. 

2. 

3. 

Capital market impacts: Cost of equity capital and bid-ask spreads. We 
hypothesise that an increase in disclosure quality leads to a reduction in the 
effective cost of equity capital and an increase in market liquidity, i.e. lower bid-
ask spreads. 
Transparency: The accuracy of analysts’ earnings forecasts. We hypothesis that 
an increase in disclosure quality leads to an increase in the accuracy of analysts’ 
earnings forecasts. 
Accounting quality: The likelihood of earnings management, which is proxied by 
the presence of small, positive earnings. We hypothesise that an increase in 
disclosure quality leads to an increase in accounting quality, and hence, a 
reduction in the likelihood of earnings management, or the reduced frequency of 
small positive earnings. 

We  focused  on  these  outcomes  primarily  because  the  existing  literature  provides  a 
significant  body  of  evidence  on  the  relationship  between  disclosure  quality  and  these 
outcomes.  The  literature  review  also  informed  the  selection  of  the  appropriate 
econometric methodology to be applied in our assessment. 

Our  study  assesses  the  direct  impacts  on  businesses  as  a  result  of  an  increase  in 
disclosure  quality.  We acknowledge  that  there  is  a  range  of wider  impacts  that  could 
result  from  the  implementation  of  CBCR,  including  market-wide/spillover  impacts, 
such as those on competition. Due to the lack of readily-available data, and in order to 
maintain  the  tractability  of  our  analysis,  this  has  not  been  explicitly  quantified  in  our 
study. 

Bank sample  

Our analysis focuses on large, cross-border banking groups to analyse the impacts of 
disclosure  quality  on  the  outcomes  identified  above.  We  shortlisted  banks  that  meet 
the following criteria: 

• 

• 
• 

Global systemically-important institutions as identified by the Financial Stability 
Board; 
Other large European banks identified by the Liikanen report; and  
Other large banks identified by Bankscope (those with assets exceeding €300 
bn). 

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We  also  restricted  the  sample  to  publicly-listed  banks  where  their  disclosures  are 
publicly available and where their financial year ends in December.37 On this basis, we 
shortlisted  51  banks  from  16  countries,  30  of  which  are  headquartered  in  European 
Economic  Area/European  Union  (EEA/EU)  countries.  The  total  assets  across  these  51 
banking  groups  amount  to  €50.7  trillion.38  Figure  2  shows  the  number  of  banks 
included in our analysis by country of headquarters. A full list of banks included in our 
analysis is provided in Appendix 1.2.  

Figure 2: Banks included in our analysis 

Source: FSB, Bankscope, Liikanen report, PwC analysis 

Measuring disclosure quality 

Our  approach  seeks  to  capture  the  impact  of  disclosure  quality  on  the  outcomes 
identified above. In order to analyse the impact of disclosure quality on the outcomes 
of interest, we needed first to measure the quality of firms’ disclosure, looking at the 
amount and quality of information provided in annual reports.  

In  order  to  measure  disclosure  quality  we  developed  a  scoring  framework  that  we 
have consistently applied to all firms in the sample.39 Approaches of this nature have 
been widely-adopted in studies seeking to analyse the impact of disclosure quality on 
capital  market  outcomes  (Hail,  2002;  Danske  and  Gebhardt,  2006;  Eugster  and 
Wagner,  2011;  Eugster  and  Wagner,  2013;  Sowerbutts,  Zimmerman  and  Zer  2013; 
Eugster,  2014). Disclosure  indices  are  primarily  used  to provide  researchers  with  the 
ability  to  quantify  what  is  inherently  a  subjective  and  heterogenous  subject  matter 
into  a  comparable  metric  which  permits  the  application  of  sophisticated  econometric 
techniques. 

37 Firms with non-December year-ends were excluded from the sample so that market 
information is estimated at the same point in time for each firm-year observation. This 
condition  resulted  in  the  exclusion  of  banks  that  are  based  in  Australia,  Canada  and 
Japan. 
38 Data refers to 2013, source: Thomson Reuters. 
39 The scoring framework is drawn partly from the disclosure index constructed by the 
Department of Banking and Finance of the University of Zurich. 

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We  reviewed  the  quality  and  depth  of  reporting  provided  in  banks’  annual  reports 
and/or  annual  financial  reviews  for  the  years  between  2000  and  2013.  We  only 
reviewed  data  from  annual  reports  and  financial  statements  as  these  are  publicly-
available  and  are  consistently  captured,  rather  than  disclosures  from  other  sources 
such  as  separate  regulatory  reporting,  so  that  we  focus  on  the  main  source  of 
information for investors40. 

Annual reports of listed banks typically consist of two components. The first part of the 
report  typically  contains  a  narrative-based  discussion  of  corporate  strategy,  financial 
year  highlights,  corporate  governance  arrangements,  risk  management  and  a  high-
level  description  of  the  firm’s  activities.  The  second  part  contains  a  set  of  audited 
financial  statements,  including  the  external  auditor’s  report,  financial  statements  and 
accompanying notes. 

We  identified  a  total  of  15  specific  scoring  areas  and  these  form  the  basis  of  banks’ 
disclosure  quality  scores,  drawing  from  the  disclosure  scoring  framework  in  Eugster 
(2014).  Banks  are  assigned  a  score  of  between  1  and  5  for  each  of  these  scoring 
areas,  with  a  score  of  5  representing  the  highest  level  of  detail  and  quality  of 
reporting.  The  maximum  disclosure  score  achievable  is  therefore  75.  The  full  set  of 
scoring  criteria  is  available  in  Appendix  1.3.  These  15  specific  scoring  areas  can  be 
grouped into the following reporting categories:41,42 

• 

• 

• 

• 

• 

• 

Non-financials: The quality and depth of the discussion of future or planned 
investments, employee and customer satisfaction and the discussion of corporate 
social responsibility, sustainability and environmental activities. The maximum 
score achievable is 20.  
Growth targets: This covers information on shareholder returns and the clarity 
of the exposition of specific targets and how they will be achieved. The 
maximum score is 5.  
Market Share: It is considered best practice for a bank to give a detailed 
explanation of its market share in different areas, by geography and/or by 
business unit. This category is scored out of 5.  
Risk management: This covers the quality and depth of discussion regarding 
risk management processes in the past year, the reporting of quantitative risk 
metrics, and risk strategy and objectives for the future. This section was scored 
out of 15.  
Corporate governance: This covers the quality and depth of the discussion of 
corporate strategy, and the reporting of the board structure, committees and 
board members. Banks were scored out of 10 for this area.  
Regional breakdown: Financial information can be segmented by business 
unit, geographic unit (e.g. Europe) or by individual country. Best practice would 
be granular financial data at the country level; additional business unit 
information is also scored highly. This was scored out of 5.  

40  Our  analysis  therefore  omits  any  additional  voluntary  disclosure  provided  by 
companies such as interim reports, conference calls, roadshows and analyst meetings. 
41 For example, under the specific scoring area of “discussion of corporate strategy”, a 
bank  which  provides  a  detailed  discussion  of  strategy  for  each  business  unit  will  be 
awarded a higher score than a bank which only provides a high-level overview of the 
firm’s strategy. Similarly for the scoring area of “specific targets set out”, banks that 
provide  a  detailed  discussion  on  their  growth  targets  across  different  business  areas 
will be awarded a higher score than those that only state their future targets.  
42  The  total  scores  for  each  category  differ  as  some  categories  have  more  disclosure 
criteria  than  others.  The  precise  total  scores  for  each  category  are  less  important  as 
we consider each of the reporting areas in separate regressions. 

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• 

Shareholder returns: This section focuses on whether this information is 
disclosed and if comparisons against other companies are also included. Best 
practice is detailed information on how returns have changed over time. This 
was scored out of 5.  

Banks  are  also  given  a  general  overall  score  out  of  five  for  general  presentation  and 
ease of use. Best practice is considered a report that is easy to navigate around and 
find information.  

We  have  set  out  a  clear  and  simple  scoring  framework  to  reduce  the  degree  of 
subjectivity in the assignment of scores. A random sample of banks’ reports was also 
scored independently by internal reviewers to ensure consistent scoring across banks 
and to minimise the issue of non-replicability. 

This tailored approach to assessing reporting quality allows us to quantify the impact 
of overall disclosure quality, by summing the scores obtained by the banks across the 
individual scoring components. We do not weight the individual components that make 
up the disclosure score as we do not take a view on which types of reporting may be 
more  important  than  others,  as  is  consistent  with  the  approach  taken  in  Eugster 
(2014),  Hail  (2002)  and  Eugster  and  Wagner  (2013).  We  can  also  separate  out  the 
impacts that can attributed to specific components of the disclosure quality score, and 
in  particular,  the  impact  of  the  granularity  of  financial  information  (disaggregated  at 
the country or regional level).43  

Our  scoring  areas  cover  both  disclosures  which  firms  voluntarily  provide  and  those 
which are mandated by external regulations. Some disclosures are provided entirely at 
the  firm’s  discretion  and  are  not  required  by  regulations,  namely  those  in  relation  to 
non-financials, market share information and growth targets. 

Other disclosure items are subject to regulatory requirements. For example, reporting 
on  corporate  governance  arrangements  is  effectively  mandatory44  as  set  out  by  local 
corporate governance codes. Similarly, under EU Capital Requirements Directives and 
Basel  II,  banks  also  report  on  their  key  risks,  such  as  credit,  market,  funding  and 
operational  risks  as  part  of  Basel  Pillar  3  disclosure  requirements  (European  Banking 
Authority,  2012)  in  their  annual  reports.  However,  this  leaves  some  room  for 
management  discretion  in  terms  of  the  breadth  and  depth  of  reporting.  Our  scoring 
method  for  the  areas  of  corporate  governance  and  risk  management  captures  the 
overall quality of these aspects, i.e. both the mandatory and discretionary elements of 
disclosure. 

Financial  statements  must  also  be  prepared  according  to  recognised  accounting 
standards,  such  as  the  IFRS,  US  GAAP  or  national  accounting  standards.  These 
standards  set  out  the  general  principles  for  the  calculation  of  financial  items  and  the 
specific  items  and  statements  that  must  be  disclosed.  The  accounting  standards 

43  In  our  analysis,  we  have  implicitly  treated  the  individual  scores  as  continuous.  We 
believe this is a valid approach because our scoring data is drawn from a reasonably 
large  sample  of  banks  which  are  within  the  same  industry.  Second,  the  scores 
assigned to banks are applied consistently across the whole sample (i.e. measurement 
invariant), which means that a score of 3 for one category for one bank is the same as 
a  score  of  3  for  the  same  category  for  another  bank,  thereby  allowing  a  meaningful 
comparison  across  banks.  In  addition,  we  can  also  reasonable  assume  that  equal 
thresholds  of  quality  apply  when  moving  from  one  score  to  another  (Lubke  and 
Muthen,  2009).  This  approach  is  also  consistent  with  Eugster  (2014),  who  uses  the 
scores from individual components.  
44 For example in the UK the corporate governance code applies a "comply or explain" 
regime. 

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therefore influence the quality of the information provided in the financial statements 
of annual reports, such as the income statement, balance sheet, cash flow statement 
and accompanying notes. Our scoring method does not explicitly capture the quality of 
financial information provided.  

We  also  score  banks’  annual  reports  on  the  public  availability  and  granularity  of 
financial  information  by  geographic  and/or  business  segment,  which  is  particularly 
relevant  to  CBCR.  We  note  that  IFRS  8  (which  applies  to  annual  reports  dated  1st 
January 2009 onwards) does introduce segmental reporting.45 However, management 
retains  some  discretion  in  identifying  its  primary  and  secondary  reportable  segments 
(i.e. there is discretion in choosing the basis of main business units and/or geographic 
segments)  and  how  these  are  presented.  There  is  also  no  external  requirement  to 
provide  market  share  information  (other  than  what  can  be  gleaned  from  segment 
financial information) for firms. Our scoring method for geographic segments therefore 
captures both mandatory and discretionary disclosure elements. 

Overall, the existing evidence shows that accounting standards are only one of many 
factors that influence firms’ reporting incentives. Even where firms are subject to the 
same accounting standards, reporting practices nonetheless differ considerably across 
countries  (see,  among  others:  Ball  et  al.,  2003;  Ball  and  Shivakumar,  2005; 
Burgstahler  et  al.,  2006;  Lang  et  al.,  2006).  As  accounting  standards  tend  to  be 
principles-based,  management  must  use  its  judgement  in  providing  reliable  and 
relevant information, which could lead to substantial variation between banks. Banks’ 
reporting  incentives  are  also  shaped  by  international  and  domestic  regulatory 
requirements,  investor  demands,  legal  institutions,  the  strength  of  the  enforcement 
regime,  capital  market  force,  ownership  and  governance  requirements  and  operating 
characteristics  (Hail,  Leuz  and  Wysocki,  2009;  Sowerbutts,  Zimmerman  and  Zer, 
2013). Ball et al. (2000), Fan and Wong (2002), Leuz et al. (2003), Haw et al. (2004) 
and  Burgstahler  et  al.  (2006)  provide  empirical  support  for  the  importance  of  firms’ 
reporting incentives in influencing reporting and disclosure practices.  

It  is  important  to  note  that  our  disclosure  quality  score  therefore  captures  both  the 
mandatory  elements  (which  are  driven  by  regulatory  and  legal  requirements)  and 
voluntary  elements  (which  are  driven  by  investor  demand,  firm  incentives  etc.)  of 
reporting, although we only take into account what is published in annual reports. 

The  length  of  banks’  annual  reports  has  grown  considerably.  A  report  by  Deloitte 
(2011)  finds  that  the  average  length  of  annual  reports  of  UK  banking  groups  is  300 
pages,  which  is  three  times  more  than  for  the  average  listed  UK  company;  the  two 
longest  annual  reports  of  over  500  pages  were  produced  by  financial  services  firms 
(Grant Thornton, 2013). However, the increase in the amount of information provided 
is  not  always  valuable  to  investors,  especially  if  the  increase  in  length  also  results  in 
increased  complexity,  which  can  limit  relevance  and  make  it  more  difficult  for 
investors  to  gauge  the  financial  health  of  banks  and  to  undertake  an  informed 
assessment  of  risk.  The  disclosure  scoring  framework  we  have  employed  does  not 
take into account the complexity and attendant relevance of disclosure in order to limit 
the subjectivity imparted by the scoring method. 

45 IFRS 8, which introduces segmental reporting for reporting periods beginning on or 
after 1 January 2009, requires companies to adopt a management reporting approach 
in  identifying  and  measuring  the  results  of  reportable  operating  segments,  which  is 
defined  based  on  the  company’s  internal  organisational  structure  and  the  way 
management  decisions  are  made  in  allocating  resources  and  evaluates  performance, 
which could be based on business segments or the regions in which the firm operates. 
IFRS 8 is largely similar to segment reporting requirements under US GAAP accounting 
standards (SFAS No. 131). 

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Disclosure Quality Scores 

The disclosure quality scores are calculated from reviewing banks’ annual reports and 
scoring the quality of banks’ disclosures, assigning a score of between 1 (lowest) and 
5 (highest).  

Each of the 51 banks we reviewed was assigned a score in each of the different areas. 
The sum of the individual scores makes up the total disclosure quality score, with 75 
being  the  maximum  score.  Figure  3  shows  the  boxplot  of  overall  disclosure  quality 
score over time for our sample of banks. The minimum, medium and maximum values 
rise,  on  average,  from  2003  to  2013.  This  is  consistent  with  our  expectations,  as 
banks’  disclosures  quality  have  been  driven  by  increasing  regulatory  pressure, 
changes  to  accounting  standards  and  shocks  to  investor  confidence.  The  chart  also 
shows  significant  within-year  variation  in  the  quality  of  disclosure  among  banks.  The 
standard deviation has varied over time, ranging between 8.93 and 10.82. In general, 
the variation in quality has increased slightly over time.  

Figure 3: Total disclosure quality score over time, out of a maximum of 75 

Source: PwC analysis  

Table  1  shows  the  average  across  time  for  the  scores  of  individual  components  of 
disclosure  quality.  Across  the  categories,  the  quality  of  disclosure  has  generally 
increased.  The  non-financial  component  has  achieved  the  highest  relative  increase 
over time, increasing by 64% between 2000 and 2013.  

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Table 1: Average scores over time of components of total disclosure quality score 

Regional 
Breakdown 
(/5) 

Risk 
Management 
(/15) 

Corporate 
Governance 
(/10) 

Non-
Financials 
(/20) 

Shareholder 
Returns (/5) 

2000 

2.81 

2001 

3.06 

2002 

3.08 

2003 

3.18 

8.35 

9.13 

9.68 

9.60 

2004 

3.41 

10.07 

2005 

3.48 

2006 

3.53 

2007 

3.64 

2008 

3.62 

2009 

3.56 

2010 

3.66 

2011 

3.68 

2012 

3.68 

2013 

3.74 

Source: PwC analysis 

9.86 

10.26 

11.45 

11.79 

11.72 

11.80 

12.08 

12.02 

12.10 

5.29 

5.63 

5.46 

5.83 

5.88 

6.21 

6.51 

6.61 

6.79 

6.80 

6.96 

6.94 

7.26 

7.62 

7.94 

9.00 

9.03 

9.20 

9.44 

10.02 

10.93 

11.14 

11.83 

12.20 

12.16 

12.56 

12.70 

13.06 

2.89 

2.87 

2.84 

2.89 

3.09 

3.00 

2.91 

2.84 

2.84 

2.68 

2.89 

2.82 

2.77 

3.02 

Targets 
(/5) 

Market 
Share 
(/5) 

2.58 

2.13 

2.84 

2.38 

2.59 

2.32 

2.70 

2.30 

2.98 

2.24 

2.88 

2.29 

2.86 

2.47 

3.18 

2.48 

2.98 

2.55 

3.16 

2.54 

3.38 

2.20 

3.42 

2.40 

3.60 

2.42 

3.72 

2.44 

Regional breakdown is one of the scoring areas which has considerably increased over 
time.  As  can  be  seen  in  Figure  4,  the  percentage  of  banks  that  score  five  in  this 
category has increased and the percentage of banks scoring one in this category has 
decreased  over  time.  Overall,  there  has  been  a  movement  towards  higher  quality 
regional  breakdown  disclosure  by  banks  which,  as  mentioned  previously,  could  be 
driven by the changes introduced by IFRS 8.  

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Figure 4: Regional Breakdown Scores as a percentage over time 

Source: PwC analysis 

Identifying the appropriate methodology 

In  this  section  we  set  out  our  rationale  for  using  the  methods  we  applied  in  our 
regressions.  

Regarding  the  cost  of  equity  capital,  bid-ask  spreads  and  analyst  forecast  accuracy, 
our approach seeks to make an improvement on previous academic attempts by using 
more  recent  and  sophisticated  econometric  techniques.  We  opted  to  use  a  dynamic 
system  GMM  approach;  this  choice  was  shaped  by  a  number  of  key  factors.  For  the 
earnings  management  regression,  we  use  a  logistic  regression  (as  in  Chen  et  al., 
2010),  due  to  the  nature  of  the  dependent  variable,  which  is  binary.  We  discuss  the 
use of both below.  

Dynamic system GMM model  

For the cost of equity capital, bid-ask spreads and analyst forecast accuracy, much of 
the  existing  research  uses  an  ordinary  least  squares  (OLS)  regression  approach. 
However,  this  method  is  vulnerable  to  endogeneity  problems,  which  can  stem  from 
three different sources: 

• 

• 

• 

Measurement error: this issue can be overcome by carefully choosing the 
variables used in the econometric model to ensure accuracy; 
Reverse causality: this is known as simulateaity and occurs when there is a 
circular relationship between the dependendent and independent variables, 
specifically that the dependent variable is determining an explanatory variable. 
This causes bias to the coefficients and the model is unreliable; 
Omitted variables: often many variables which influence a dependent variable 
are unobserved or immeasurable, meaning they are omitted from the 
specifitcation. If these factors are correlated with an explanatory variable and 
not accounted for in the model, this generates biased results. 

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First, in the context of disclosure and the effective cost of equity capital, there is likely 
to  be  reverse  causality,  meaning  that  a  high  cost  of  equity  may  incentivise  banks  to 
improve  their  disclosure  quality  (Eugster,  2014).  Dhaliwal  et  al.  (2012)  show  that 
companies  with  a  high  cost  of  equity  capital  are  more  likely  to  initiate  voluntary 
disclosure  in  order  to  influence  their  future  cost  of  equity  capital.  This  problem  of 
reverse  causality  violates  a  strong  assumption  implied  by  the  OLS  approach,  i.e. 
where the current observations of the explanatory variable (e.g. voluntary disclosure) 
are independent of past values of the dependent variable. If this is not corrected for, 
the  estimates  we  derive  for  the  impact  of  disclosure  quality  on  these  outcomes  are 
said to be biased. This suggests that our proposed econometric methodology will need 
to take into account this potential issue. 

Similarly, certain variables, such as the cost of equity capital, can be highly correlated 
with  its  past  values.  This  means  that  our  econometric  strategy  must  also  take  into 
account  the  dynamic  nature  of  the  relationship  between  disclosure  quality  and  the 
outcomes  of  interest,  and  the  underlying  persistence  of  trends  over  time  that  is 
present in some variables. 

Second,  voluntary  disclosures  could  be  influenced  by  unobserved  firm-specific 
characteristics, such as managerial ability or its legal environment. Our review of the 
literature suggests that the quality of disclosures tend to be influenced by a range of 
factors,  not  all  of  which  are  observable.  These  fixed  effects  are  firm  characteristics, 
which  are  time-invariant,  that  can  directly  influence  the  dependent  variable,  e.g. 
managerial  ability  or  the  legal  institutions  to  which  the  firm  is  exposed  to  within  its 
country of headquarters.  

This  implies  that  our  chosen  methodology  ought  to  account  for  banks’  fixed  effects. 
The central principle behind the fixed effects (FE) approach is that there is some factor 
at each firm level which may bias the dependent variable due to correlation between 
the  error  term  and  the  explanatory  variables.  FE  models  serve  to  remove  the  time-
invariant  characteristics  of  the  independent  variables  in  order  to  mitigate  omitted 
variable bias and generate unbiased and efficient estimators.  

Some  of  the  previous  literature  uses  an  FE  model,  which  mitigates  unobserved 
heterogeneity.  However,  this  is  still  problematic  for  two  reasons:  first,  the  approach 
fails  to  overcome  the  problems  of  reverse  causality  endogeneity  identified  above. 
Second, related to the first point, introducing a dynamic element to the standard fixed 
effects  framework,  i.e.  including  the  lag  of  the  dependent  variable  as  an  additional 
explanatory  variable  is  inappropriate  and  will  result  in  inconsistent  estimates 
(Wooldridge, 2002).  

Figure 5 illustrates the concept of endogeneity and how this can be mitigated using an 
instrumental  variable  approach.  Panel  (a)  shows  that  in  the  absence  of  endogeneity, 
both the disclosure score and the error term are correlated with the outcome variable, 
but not with one another. The error term typically accounts for, among other things, 
the  influence  of  omitted  variables  on  the  dependent  variable.  As  long  as  the  omitted 
variables  are  uncorrelated  with  the  included  independent  variables  –  in  this  case  the 
disclosure  score  –  an  OLS  regression  will  produce  unbiased  estimates.  However, 
endogeneity  arises  when  the  omitted  variables  are  in  fact  correlated  with  the 
independent  variables  (panel  (b)),  which  biases  the  estimates  using  the  OLS 
approach.  In  the  context  of  the  impact  of  disclosure  quality  on  the  effective  cost  of 
equity capital, we include the lag of the dependent variable (i.e. cost of equity capital) 
as  an  additional  explanatory  variable.  However,  since  the  lag  of  the  cost  of  equity 
capital is correlated with the error term in the model, this leads to endogeneity.  

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Figure 5: Explaining endogeneity 

One  potential  strategy  to  overcome  both  these  issues  is  to  use  an  instrumental 
variable  (IV)  approach  combined  with  fixed  effects  (Shepherd,  2009).46  This  would 
require  the  use  of  an  instrument,  which  is  a  variable  that  is  strongly  correlated  with 
the  potentially  endogenous  explanatory  variable  but  also  uncorrelated  with  the  error 
term  in  the  model.  The  instrument  should  only  influence  the  dependent  variable 
through  the  potentially  endogenous  explanatory  variable,  as  shown  in  panel  (c)  of 
Figure 5.  

A  good  instrument  must  fulfil  two  criteria.  First,  the  instrument  must  be  valid, 
meaning  that  the  instrument  must  be  independent  of  the  error  term.  47  Second,  the 
instrument  must  be  relevant,  meaning  that  the  instrument  must  have  some 
explanatory  power  over  the  potentially  endogenous  variable  and  whether  the 
instrument is correlated with the endogenous variable you want to instrument for.48 In 
reality, finding an appropriate instrument that meets both the above criteria can be a 
considerable  challenge.  In  the  context  of  disclosure  quality  and  the  cost  of  equity 
capital,  the  instrument  must  directly  influence  disclosure  quality,  but  not  the  cost  of 
equity capital. In addition to the above criteria, Hail (2002), who uses a two-stage IV 
approach in his study of disclosure quality on cost of equity capital, acknowledges that 
the IV approach could lead to unreliable results due to a small sample size. 

Therefore,  a  key  motivation  of  this  study  is  to  overcome  the  issues  that  have  been 
encountered  in  previous  studies  by  adopting  an  econometric  approach  that  accounts 
for  these  problems,  and  to  improve  the  credibility  of  our  results  and  to  attempt  to 
improve  on  the  robustness  of  previous  studies.49  The  above  factors  coupled  with  the 
findings  of  our  preliminary  data  analysis  suggest  that  a  dynamic  panel  system 
generalised method of moments (GMM) estimator is appropriate for our analysis.  

The  GMM  approach  involves  using  an  instrumental  variable-based  approach  where 
higher  lag  values  of  the  lagged  dependent  variable  are  used  as  instruments.  In 
contrast  to  OLS  in  which  the  estimator  minimises  the  squared  vertical  distances 
between  the  observation  and  the  mean  (the  first  moment),  system  GMM  minimises 
the sample average of the second, third and fourth moments: the variance, the skew 
and  the  kurtosis.50  The  GMM  approach  overcomes  the  difficulty  of  instrument 

46  Ben  Shepherd  (2009)  ‘Development  Consultant  Dealing  with  Endogeneity’  Trade 
Economist & International www.Developing-Trade.com. 
47 It is measured by the Sargan/Hansen J test of exogeneity. 
48  The  Kleibergen  Paap  under-identification  test  measures  the  strength  of  this 
correlation. 
49  Our  use  of  “robust”  in  this  context  is  in  reference  to  statistical  robustness,  i.e. 
statistical methods and results that are not unduly affected by deviations of statistical 
assumptions (e.g. non-normality, homoskedaticity). 
50 Kurtosis is a measure of the “peakedness” of the probability distribution.  

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identification  as  it  works  by  using  lagged  historical  variables  in  differences  as 
instruments  for  the  endogenous  variables  in  the  level  regression  (and  vice  versa), 
since lagged values are less likely to be influenced by current shocks.  

This  differencing  also  serves  to  eliminate  any  potential  omitted  variable  bias  and 
unobserved  heterogeneity,  which  means  firms’  fixed  effects,  or  firm  characteristics 
that  are  time-invariant,  are  accounted  for.  The  system  GMM  approach  also  does  not 
specify a particular distribution of the errors. The instrumental variable approach can 
also  deal  with  unobserved  bank  characteristics  that  vary  over  time.  This  is  another 
reason why the system GMM approach is preferable. 

To  ensure  the  statistical  robustness  of  our  specifications,  first,  the  instruments  used 
must be valid. Our study uses various statistical tests to ensure that our specifications 
are  not  affected  by  problems  of  under-identification  or  weak-identification,  as 
proposed by Baum, Schaffer and Stillman (2007). Second, the correct number of lags 
must be used. When testing for the correct number of lags (levels and differences), we 
ensured the model fulfilled certain criteria:  

• 

• 

• 

Blundell-Bond plausibility check: the magnitude of the coefficient of the 
lagged dependent variable (e.g. cost of equity capital) from the system GMM 
estimation approach must be smaller than that when computed using OLS, but 
greater than when computed using a fixed effects model, such that 
OLS>GMM>FE . Hsiao (1986) argues that the OLS coefficient of the lagged 
dependent variable is expected to suffer from an upward bias due to the fact 
that it ignores specific effects, while Nickel (1981) argues that the coefficient in a 
fixed effects model is likely to be downward biased. Hence, Blundell and Bond 
(1998) rationalise that a plausible parameter estimate should lie within the two 
estimates; 

The Hansen J test for instrument validity: assesses the null hypothesis that 
the model is correctly specified and the over-identifying restrictions are valid; it 
tests if the instruments as a group are exogenous, ensuring the validity of the 
instruments. The Sargan51 test also tests for instrument validity, but it is not 
robust to heteroskedasticity, unlike the Hansen test. Due to the presence of 
heteroskedasticity in our model (as tested by the xttest3 command on Stata), 
the Hansen test is our primary test. The criterion is that the Hansen J52 test 
result is greater than 0.05, but less than 0.9, such that 0.05>x>0.9, meaning 
we would be unable to reject the null hypothesis of exogeneity. In addition to 
testing for instrument validity, Roodman (2009) contends that the test can also 
be viewed as a test of structural specification; omitting important variables may 
move components of variation into the error term and make them correlated 
with the instruments, where they may not be in the correct model; 

The Arellano-Bond test for autocorrelation: tests the null hypothesis that 
the model does not suffer from serial correlation; this test can be applied to 
different orders of correlation. We expect the AR test of order 1 to be rejected in 
our dynamic model, due to the historical feedback mechanism between the lag 
of cost of equity capital and the current period cost of equity. We require the AR 

51 Tests for correlation between the instrument and the error term. 
52  The  Hansen  test  is  used  to  assess  the  validity  of  the  instruments,  the  null 
hypothesis  assuming  the  instruments  are  valid.  The  Hansen  test  is  robust  to 
heteroskedasticity, unlike the Sargan test.  

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(2) test to not be rejected, to ensure serial correlation is not evident in the 
model.53 

• 

The Cragg-Donald Wald F test: this assesses whether the instruments are 
weakly identified54; it effectively tests the null hypothesis that the explanatory 
variables are jointly insignificant and equal to 0. The Wald p-value must 
therefore be smaller than 0.05 in order to reject the null hypothesis and prove 
joint significance.55 When more than one combination of lags met the other 
criteria outlined above, we judged which lag combination was most appropriate 
to use by choosing model with the highest Wald statistic.56  

Our  system  GMM  model  specification  also  applies  the  ‘two-step’  command  to  ensure 
that the model  is robust to panel-specific autocorrelation  and heteroskedasticity, and 
the ‘collapse’ command to avoid instrument proliferation.57 

Logistic model 

The  GMM  is  a  linear  regression  where  the  dependent  variable  is  assumed  to  be 
continuous  and  has  a  normal  distribution.  However,  to  test  the  relationship  between 
disclosure quality and earnings management we use a linear probability model. This is 
because  the  dependent  variable  is  binary  (a  dummy  or  a  two-category  variable), 
meaning  that  it  takes  only  two  possible  values,  i.e.  zero  or  one.  This  is  used  to 
indicate the absence or presence of some categorical effect, in this case, the presence 
of  earnings  management  in  that  particular  year.  The  presence  of  ‘small’  positive 
earnings  is  considered  to  be  indicative  of  the  presence  of  earnings  management. 
Therefore,  in  our  study,  we  use  a  dummy  variable  which  equals  one  if  net  income 
scaled by total assets is between 0 and 0.01. 

Although an OLS model could be used, there are several problems with this. First, the 
usual  interpretation  of  the  slope  coefficient,  i.e.  an  increase  in  the  value  of  the 
dependent variable  given  a  single  unit  increase  in  the  explanatory  variable,  does  not 
hold  when  the  dependent  variable  is  binary.  Second,  the  OLS  method  also  no  longer 
produces  the  best  linear  unbiased  estimator  (BLUE),  and  will  therefore  generate 
biased and inefficient variables. This is because the binary dependent variables are not 
normally  distributed  and  its  errors  are  heteroskedastic58,  which  violates  key 
requirements of the OLS in order to generate unbiased and efficient estimates. 

53 Tests for autocorrelation, also known as serial correlation, in which the error term in 
time  t  is  correlated  with  the  error  term  in  time  t-n;  this  reduces  the  efficiency  of 
estimators.  The  AR(1)  test  checks  for  correlation  between  the  value  of  the  current 
dependent  variable  and  its  value  one  period  ago;  the  AR(2)  tests  for  correlation 
between the value of the dependent variable and its value two periods ago.  
54 Whether the instruments are weakly correlated with the exogenous variable.  
55 The p-value measures the probability of a test hypothesis being true. 
56  The  Wald  test  cannot  be  used  to  compare  across  specifications,  only  to  assess 
different lag combinations within a specification.  
57  Instrument  proliferation  can  cause  two  problems  (Roodman,  2009):  1.  By  being 
numerous,  instruments  can  overfit  instrumented  variables,  failing  to  expunge  their 
endogenous  components  and  biasing  coefficient  estimates  towards  those  from  non-
instrumenting estimators. 2. Instrument proliferation also leads to imprecise estimates 
of  the  optimal  weighting  matrix  used  in  the  two-step  variants  of  DGMM  and  SGMM 
estimations.  In  order  words,  the  standard  errors  in  two-step  GMM  will  tend  to  be 
severely downward biased. We therefore use the “collapse” option in Stata to mitigate 
this problem. See Windmeijer (2005).  
58 Heteroskedasticity is where the standard deviations of a variable are non-constant. 

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A  linear  probability  model,  on  the  other  hand,  allows  us  to  interpret  the  slope 
coefficient  as  the  increase  in  the  probability  that  the  dependent  variable  observation 
will  equal  one  given  a  single  unit  increase  in  the  explanatory  variable.  We  use  a 
logistic regression, as used by Chen et al. (2010) and Barth et al. (2007), which is a 
popular  technique  for  modelling  dichotomous  dependent  variables  and  allows  the 
dependent  variable  to  imply  a  probability.  This  is  based  on  a  cumulative  logistic 
 can be interpreted as the probability that the 
probability function as follows, where 
binary dependent variable equals 1: 

A  logistic  regression  transforms  the  binary  dependent  variable  into  a  continuous 
variable by using the log of probability scores as the predicted values of the dependent 
variable, so that by running a logistic regression we obtain the following: 

Where 
  can  be  interpreted  as  the  odds  ratio,  or  the  probability  of  a  “success” 
outcome (in this context, where the dependent variable is 1, indicating the presence of 
earnings  management)  divided  by  the  probability  of  a  “failure”  outcome  (where  the 
dependent variable is 0, indicating the absence of earnings management).  

In our analysis of the impact of disclosure quality on earnings management, we use a 
panel  logit  model  with  random  effects.  A  random  effects  model  accounts  for 
unobserved  differences  between  banks,  but  unlike  a  fixed  effects  model,  it  assumes 
that the unobserved differences are not correlated with the explanatory variables. We 
used  the  Hausman  test  to  assess  whether  the  fixed  effects  or  random  effects  model 
was more appropriate. The null hypothesis states that unobserved differences are not 
correlated  with  the  explanatory  variables,  testing  for  the  random  effects  model  over 
the fixed effects model.  

The estimation for the logistic regression is commonly performed using the statistical 
method  of  maximum  likelihood  estimation,  which  we  use  on  Stata  to  perform  our 
regressions.  An  interpretation  of  the  results  for  this  regression  and  the  specification 
tests specific to logistic regressions are discussed in more detail in the results section 
of earnings management. Similar to the GMM however, a Wald statistic can be used to 
test for joint significance of the included variables.  

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Impact of disclosure quality on the cost of equity capital 
In  this  section  we  outline  our  modelling  approach,  data  and  summary  statistics,  and 
the results from our modelling in more detail.  

Section summary 

We  hypothesise  that  increasing  the  quality  of  disclosures,  as  measured  by  our 
disclosure  quality  index,  will  lower  the  effective  cost  of  equity  capital  through 
mitigating information asymmetries.59 

We  use  a  dynamic  system  GMM  approach  to test  the  relationship  between  disclosure 
quality and the effective cost of equity capital, given the potential estimation problems 
of endogeneity, reverse causation and unobserved heterogeneity across banks.  

Overall,  we  find  that  an  increase  in  the  disclosure  quality  score  has  a  significantly 
negative relationship with the effective cost of equity capital: an increase in disclosure 
scores by 1 unit lowers the effective cost of equity capital by 0.2 percentage points on 
average  for  our  sample  of  banks.  We  find  that  of  the  components  of  the  disclosure 
score,  the  regional  breakdown  of  disclosures  appears  to  be  driving  this  relationship 
with the effective cost of equity capital. An increase in the regional breakdown score is 
associated with a decrease in the effective cost of equity capital. 

Modelling approach 

Our  model  specification  is  based  on  the  Fama-French  ‘Three  Factor  Model’  (1993), 
which  states  that  an  asset’s  expected  return  is  determined  by  market  risk  (beta60), 
size  risk  (market  capitalisation)  and  financial  distress  risk  (market  to  book  value). 
These  variables  need  to  be  controlled  for  because  firms  with  a  higher  market 
capitalisation and market to book value are expected to deliver consistent and stable 
returns,  which  lower  the  cost  of  equity  capital,  and  those  with  high  market  risk  will 
have  a  higher  cost  of  equity  capital.  These  variables  form  the  core  of  our  basic 
specification, which we then augment to include banks’ disclosure quality scores and a 
dummy equal to 1 if the observation falls in the year 2008 and equal to 0 if otherwise. 
We  augment  the  Fama-French  framework  with  our  disclosure  quality  score,  to 
investigate  the  usefulness  of  such  a  factor  in  explaining  the  time-series  variation  in 
cost of equity capital, over and above the role of the Fama-French factors. 

We  use  a  dynamic  system  GMM  model  due  to  endogeneity  concerns.  This  model  is 
likely  to  suffer  from  reverse  causation,  in  which  the  relationship  between  the 
disclosure scores and the cost of equity capital also works in the opposite direction. If 
a bank has a high cost of equity capital, they have a stronger incentive to increase the 

59  In  the  literature,  most  studies  examine  the  impact  of  disclosure  on  the  cost  of 
equity capital. We prefer to refer to the effective cost of equity capital. This is because 
in our view the way in which disclosure quality affects the cost to a firm of acquiring 
equity  capital  is  through  changes  in  the  asymmetry  of  information  between 
management  and  investors  on  future  cash  flows,  rather  than  changes  in  the 
underlying  cost  of  equity  itself,  which  is  driven  by  factors  identified  in  the  Fama-
French “Three Factor model”. 
60 Beta is a measure of the volatility of an asset or portfolio of assets in relation to the 
market as a whole; it measures the systematic risk of an asset due to general market 
movements, as opposed to idiosyncratic factors.  

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quality  of  their  disclosures,  in  order  to  lower  information  asymmetries  and  increase 
investor  demand,  thereby  lowering  their  cost  of  equity  capital  in  the  next  period 
(Dhaliwal et al., 2012; Eugster, 2014). Another source of endogeneity may come from 
omitted  variables,  in  that  the  cost  of  equity  capital  may  be  determined  by 
immeasurable and/or unobservable factors, such as managerial abilities. Our model is 
also likely to be dynamic, with past values of the cost of equity partially determining 
the  current  cost  of  equity  capital,  hence  the  inclusion  of  the  lagged  dependent 
variable.  We  estimate  the  following  basic  specification  using  a  dynamic  system  GMM 
model:  

(1) 

Table 2: List of variables used for econometric analysis 

Variable 

Expected 
Relationship 

Description 

Cost of equityit 

Cost of 
equityit-1 

Disclosure 
scoreit  

Betait 

Log of market 
capitalisationit 

MTBVit 

Year08 

Average cost of equity capital for company i at time t, 
measured  by  the  average  of  the  Claus  and  Thomas 
(2001),  Gebhardt  et  al.  (2000),  Ohlson-Juettner 
(2003)  and  Easton  (2004)  implied  cost  of  equity 
capital approaches. 

Lag of the average cost of equity capital for company i
at time t-1. 

Disclosure  score,  out  of  75,  using  PwC  disclosure 
quality scoring index for company i at time t. 

Measure of an asset’s risk in relation to the market of 
company i at time t. 

Natural log of the equity market value of company i at 
time t. 

Market-to-book value of company i at time t. 

A binary variable equal to 1 if year equals 2008 and 0 
otherwise 

+ 

- 

+ 

- 

- 

+ 

The  2008  indicator  variable  is  needed  as  an  additional  control  because  the  2008 
financial  crisis  and  subsequent  recession  imposed  a  negative  shock  on  investor 
confidence  and  market  liquidity,  increasing  the  cost  of  equity  capital;  this  impact 
needs to be controlled for in our model to avoid omitted variable bias. The inclusion of 
the  dummy  also  takes  into  account  that  the  recession  may  have  had  a  considerable 
impact  on  disclosure  scores,  incentivising  firms  to  increase  the  quality  of  their 
disclosures  to  help  overcome  the  loss  of  investor  confidence  through  increasing 
transparency, preventing bias of the disclosure score coefficient.61 

61  We  tested  the  inclusion  of  dummies  for  all  years  in  our  sample,  and  also  tested 
different  combinations  of  year  dummies  in  our  model  specifications,  in  which  the 

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In our regression we use the lag  of cost of equity as an additional  regressor,  as it  is 
likely  that  the  previous  period’s  cost  of  equity  capital  will  have  some  impact  in 
determining  the  current  period’s  cost  of  equity  capital;  this  introduces  the  dynamic 
element in our model.  

For  the  reasons  highlighted  in  the  methodology  section,  we  use  the  system  GMM 
approach to analyse the relationship between disclosure quality and the effective cost 
of  equity  capital.  To  account  for  endogeneity,  the  system  GMM  approach  uses  an 
instrumental  variable  based  approach  where  higher  lag  values  of  the  lagged 
dependent variable are used as instruments. First differencing also allows us to control 
for firms’ fixed effects, i.e. time-invariant unobserved heterogeneity. 

We also test this specification with the scores of individual disclosure components by 
replacing the total disclosure score with the individual scoring elements. This serves to 
identify which types of disclosure (e.g. the public availability of financial information at 
the  regional  level  or  non-financial  reporting)  may  be  driving  the  overall  relationship 
between disclosure score quality and the effective cost of equity capital. Specifying the 
individual  component  score  separately  from the  overall  score  also  helps  to  avoid  any 
multi-collinearity  that  the  individual  components  may  have  within  the  overall 
disclosure score.  

Data and summary statistics 

We  calculated  the  cost  of  equity  capital  using  a  variation  of  equity  valuation  models 
that derive an internal rate of return, in which actual share prices are a function of the 
present value of expected cash flows (dividends). We infer the cost of equity capital by 
using  the  valuation  models  set  out  in  Claus  and  Thomas  (2001),  Gebhardt  et  al. 
(2000),  Ohlson  and  Juettner-Nauroth  (2003)  and  Easton  (2004).  Using  an  ex  ante 
approach,  we  reverse  engineer  these  models  to  back  out  the  cost  of  equity  capital 
from current prices and future expected dividends. The first two methods are special 
cases  of  Ohlsons’  (1995)  residual  income  valuation  model  whereas  the  other  two 
models are abnormal earnings growth valuation models. 62 

The models assume indirectly that prices reflect the value of the company and at least 
the semi-strong efficient market hypothesis of Fama (1970) holds. These models rely 
on earnings forecasts of financial analysts and so the implied cost of equity capital is 
only assessable for companies with an analyst following, meaning that the company is 
actively  tracked  by  institutions  that  publish  opinions  and  forecasts  on  the  company 
and  its  equity.  The  banks  in  our  sample  are  publicly-listed  and  all  have  an  analyst 
following  of  at  least  five  every  year,  which  allows  the  estimation  of  cost  of  equity 
capital using the methods outlined above. 

Consistent  with  the  literature  (Hail  and  Leuz  2006;  Dhaliwal,  Heitzman  and  Zhen, 
2006; Daske et al., 2007; Hope et al., 2009; Li, 2009; Dhaliwal et al., 2012; Eugster, 
2014) we calculate a cost of equity capital measure for each bank-year observation in 
our  sample  which  is  based  on  an  average  of  these  four  methods.  The  advantage  of 
this  approach  is  that  the  estimates  are  less  noisy  and  less  susceptible  to  any 
idiosyncratic shocks than if one individual method was used. For most banks, all four 
cost of equity capital measures can be calculated.63  

dummy  for  2008  appeared  to  be  consistently  significant  across  these  specifications. 
We included the 2008 dummy in our main specification on this basis. 
62 See Appendix 0 for more details. 
63  Due  to  some  of  the  differences  in  the  model  assumptions  and  data  requirements, 
the  number  of  estimates  can  vary  across  years  for  each  bank.  We  made  sure  that 
estimates  for  at  least  two  of  these  measures  were  available  before  including  in  our 

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The data for this analysis, with the exception of the disclosure quality score, is sourced 
from  Thomson  Reuters.  We  take  an  annual  average  of  the  monthly  data  for  each  of 
these variables in our analysis. 

Table  3  reports  the  summary  statistics  for  the  independent  and  dependent  variables 
included in our cost of equity capital specification.  

Table 3: Summary statistics for variables used in the cost of equity model  

Mean Median Min  Max  Standard deviation 

Cost of Equity 

Disclosure Score 

0.146

0.126 

0.040  1.265

42.168 42.000  20.000 61.000

Log of Market Capitalisation  10.411 10.475  4.656  12.418

MTBV 

Beta 

Source: PwC analysis 

1.533

1.388 

0.023  6.001

1.302

1.230 

-0.807 3.202

0.092 

8.255 

0.985 

0.890 

0.487 

The cost of equity capital for the banks in our sample is around 15% on average, but 
this masks significant variation across time. Similarly, although the average disclosure 
score is around 42, it demonstrates significant variation across banks and also across 
time.  

Table 4: Correlation between independent and dependent variables 

Cost of 
Equity 

Disclosure 
Score 

Log of Market 
Capitalisation 

MTBV 

Beta 

Cost of Equity 

Disclosure Score 

1.000 

0.175 

- 

1.000 

- 

- 

Log  of  Market 
Capitalisation 

MTBV 

Beta 

Source: PwC analysis 

-0.321 

0.061 

1.000 

-0.363 

-0.312 

0.178 

0.117 

0.183 

0.164 

- 

- 

- 

1.000 

- 

- 

- 

- 

-0.211 

1.000 

The  correlation  coefficients  do  not  appear  to  indicate  any  issues  of  multi-collinearity, 
with the pairwise correlations of most variables remaining between -0.3 and 0.3. The 
data  shows  that  disclosure  quality  score  and  the  cost  of  equity  capital  are  positively 
correlated,  which  is  contrary  to  our  expectations.  The  other  explanatory  variables 
included in our specification have the expected correlation with cost of equity capital, 
i.e.  both  the  log  of  market  capitalisation  and  MTBV  have  a  negative  correlation  with 
cost  of  equity  capital,  whereas  beta  has  a  positive  correlation  with  cost  of  equity 
capital. 

analysis. We restrict the implied cost of equity capital estimates to be in the range of 
0% to 150% to remove the presence of outliers in the data. 

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Figure 6: Scatter plot between the cost of equity capital and total disclosure score  

Source: PwC analysis  

The above scatter plot shows weak to no correlation between the cost of equity capital 
and disclosure score for our sample of banks, therefore it is not immediately obvious 
that a higher disclosure quality score leads to a lower cost of equity capital. However, 
it  should  be  noted  that  neither  the  correlation  coefficients,  nor  a  simple  scatter  plot, 
are  as  informative  as  performing  an  econometric  analysis  using  a  dynamic  system 
GMM model. 

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Results 

Overall our regression results suggest that increasing the quality of disclosures lowers 
the  effective  cost  of  equity  capital  for  banks;  specifically,  regional  breakdown  scores 
appear to be the driver of this relationship. Our results are shown in Table 5. 

Table 5: Results for the impact of disclosure quality on cost of equity capital using the 
total disclosure score and regional breakdown score 

Cost of equity capital 

Total disclosure score Regional Breakdown score

Total disclosure Score 

-0.0017* 
(0.07) 

Regional breakdown score 

-  

Lag of cost of equity 

Beta 

Log of market capitalisation 

MTBV 

2008 Dummy 

Constant 

Firm-year 

# of instruments 

F-stat 

Sargan p-value 

Hansen p-value 

AR(1) test p-value 

AR(2) test p-value 

0.3277*** 
(0.002) 

0.0235* 
(0.07) 

-0.0079 
(0.42) 

-0.0378*** 
(0.000) 

0.0252*** 
(0.000) 

0.2778*** 
(0.005) 

493 

52 

 282.78 

0.000 

0.514 

0.006 

0.137 

 - 

-0.018* 
(0.079) 

0.2725*** 
(0.001) 

0.0328*** 
(0.001) 

-0.0083 
(0.175) 

-0.029*** 
(0.000) 

0.0187*** 
(0.001) 

0.2509*** 
(0.002) 

493 

37 

 316.90 

0.013 

0.542 

0.007 

0.064 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis 

There  is  a  dynamic  positive  relationship  between  the  lag  of the  cost  of  equity  capital 
and the current period’s cost of equity. The Fama-French variables, with the exception 
of the log of market capitalisation, are statistically significant, and are in the predicted 
signs:  an  increase  in  beta  has  a  significant  positive  impact  on  the  cost  of  equity 
capital. A low market-to-book value ratio, which is an indication of distress, results in 
a  higher  cost  of  equity  capital,  and  conversely,  a  high  market-to-book  value  puts 
downward pressure on the cost of equity capital. 

The impact of an improvement in disclosure quality on the cost of equity capital could 
also  be  large.  The  modelling  results  show  that  an  increase  in  the  disclosure  quality 
score  by  1  lowers  the  cost  of  equity  capital  by  0.2  percentage  points  on  average  for 
our  sample  of  banks.  This  relationship  is  statistically  significant  at  the  10%  level. 

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Market-to-book value and market capitalisation also have a negative effect on the cost 
of equity capital. Beta and the lag of the cost of equity have a positive impact, all in 
the expected signs.  

However, the log of market capitalisation is insignificant with the inclusion of the 2008 
dummy,  which  could  be  due  to  multi-collinearity64;  the  financial  crisis  had  a 
considerable  negative  impact  on  market  capitalisation,  meaning  the  two  variables 
would  both  work  to  increase  the  cost  of  equity  capital  for  observations  in  2008.  The 
2008  dummy,  which  is  highly  significant,  tells  us  that  the  cost  of  equity  capital  was 
3.2 percentage points higher in 2008 than it was for other years in our sample.  

We  also  test  whether  the  score  for  regional  breakdown  has  an  impact  on  the  cost  of 
equity  capital.  We  observe  that  the  coefficients  for  beta  and  MTBV  are  significant, 
whereas  for  the  coefficient  for  the  log  of  market  capitalisation  is  insignificant.  The 
regional  breakdown  score  has  a  significant  impact  on  the  effective  cost  of  equity, 
consistent  with  the  literature  that  information  asymmetries  are  mitigated  more 
effectively  when  investors  have  a  more  comprehensive  and  granular  overview  of  a 
bank’s  geographic  operations,  improving  knowledge,  confidence  and  liquidity  (Pelaez 
et al., 2009; Saini and Herrmann, 2012). The regional breakdown coefficient was of a 
much  greater  magnitude  than  that  for  the  total  disclosure  score,  decreasing  the  cost 
of equity capital by 1.8 percentage points when the score increases by 1. This shows 
how  important  the  regional  breakdown  of  disclosures  is  in  driving  the  relationship 
between disclosure quality and the cost of equity capital.  

We proceeded to test the specific components of disclosure score individually, running 
six  additional  regressions.  This  was  aimed  at  identifying  which  particular  aspect  of 
bank’s disclosures is the driver of the significant relationship between disclosure score 
and  the  cost  of  equity  capital.  This  allows  us  to  develop  a  more  comprehensive 
understanding  of  the  relationship  and  how  these  findings  can  be  applied  to  CBCR. 
These results are provided in Table 6.  

The  coefficients  of  the  Fama-French  variables  appear  to  be  consistently  significant, 
with the exception of a loss of significance of the log of market capitalisation with the 
non-financials  regression.  We  might  have  expected  to  see  some  significance  of  the 
shareholder  returns,  market  share,  targets  and  risk  management  scores,  as  it  is 
intuitive  to  assume  that  investors  would  place  great  emphasis  on  historical  returns, 
the bank’s share of the market relative to its peers and how various types of risk are 
controlled for. In light of the recent financial crisis, it is reasonable to hypothesise that 
the  risk  management  element  of  disclosures  would  especially  be  a  driver  of  lowering 
the cost of equity capital.  

A possible explanation for this lack of relationship may be due to the fact that banks 
have  also  provided  increased  disclosures  on  risk  management  controls  and  risk 
performance  via  other  means,  such  as  regulatory  submissions,  which  reduces  the 
importance  of  annual  reports  as  the  main  source  of  information  for  investors  about 
these issues.  

It  is  perhaps  understandable  that  the  corporate  governance  and  the  non-financials 
component are insignificant. In general, the primary concern of a potential investor is 
the  profitability  of  a  firm  and  the  financial  returns  they  will  make  on  purchasing 
shares.  Therefore,  disclosure  aspects,  such  as  corporate  responsibility  and 
sustainability, are unlikely to be an important driver in capital market outcomes.  

64 Collinearity arises when two or more explanatory variables are strongly correlated, 
exhibiting a linear relationship with each other. This causes bias of the coefficients and 
generates inefficiency of the estimator due to the fact the limited variation in the two 
explanatory  variables  is  not  providing  unique  information  to  explain  the  variation  in 
the dependent variable.  

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

The  Hansen  J  test  performed  for  all  model  specifications  shows  that  the  instruments 
used in our model are valid. The null hypothesis of instrument validity is unable to be 
rejected at the 5% level, with a p-value of 0.316 for the disclosure score model.  

Regarding  the  Arellano-Bond  test,  the  AR  (1)  tests  were  rejected  across  all 
specifications. This implies that the first lag of the dependent variable, in this case the 
cost  of  equity,  is  highly  correlated  with  its  current  value,  which  justifies  the  use of  a 
dynamic specification. The AR(2) test is unable to be reject the null hypothesis of no 
correlation  between  the  second  lag  of  the  dependent  variable,  meaning  that  serial 
correlation of order 2 is not an issue in our model specifications. 

Before running the system GMM regressions, we tested for endogeneity in our model 
using  Stata’s  “ivreg2”  command,  individually  testing  each  explanatory  variable  for 
instrument validity  and  relevance.  For  validity,  we  used the  endogeneity  test  and  for 
relevance  the  Cragg-Donald  Wald  and  Kleibergen  and  Schaffer  tests  are  used.  For 
many  of  the  variables,  we  had  to  increase  the  lags  used  on  the  individual  “ivreg2” 
tests,  providing  evidence  to  suggest  that  we  should  be  using  combinations  of  lags 
which are slightly higher for the overall GMM model, such as (7 1) and (8 1). 

We  conclude  that  increasing  the  quality  of  disclosures,  specifically  the  geographic 
granularity  of  reports,  has  a  significantly  negative  impact  on  the  effective  cost  of 
equity  capital,  providing  an  empirical  basis  for  the  theory  outlined  previously.  The 
disclosure  requirement  under  CBCR  is  most  closely  captured  by  the  regional 
breakdown  component  of  our  scoring  index.  This  suggests  the  implementation  of 
CBCR could lower the effective cost of equity capital in a similar manner.65 However, 
as  banks  have  already  reported  segmental  information,  it  is  uncertain  whether 
incremental  disclosures  at  the  country  level  as  required  by  CBCR  will  have  similarly 
significant effects. 

Robustness and sensitivity tests 

Initially we augmented the basic specification to include an indicator variable equal to 
1 if for company i at time t if it uses IFRS and equal to 0 if otherwise. The inclusion of 
the IFRS dummy did not alter the significance of the results, neither did the coefficient 
on the IFRS dummy appear to be significant. This is perhaps unsurprising, as most of 
the banks in our sample would have adopted other international accounting standards 
such  as  the  US  GAAP,  towards  which  the  IFRS  standards  are  gradually  converging. 
Therefore,  introducing  an  IFRS  dummy  is  unlikely  to  be  sufficient  to  explain  the 
variation across banks. There is also likely to be significant collinearity between IFRS 
adoption and disclosure quality, as the IFRS aims to increase the quality of disclosures 
through  international  harmonisation  and  the  increased  granularity  of  reporting. 
Therefore, this variable was excluded from our model. 

We also included a dummy equal to 1 if the bank is headquartered in an EU or EFTA 
country  to  test  whether  non-EU/EFTA  banks  are  affecting  the  significance  of  the 
results. The coefficient for this dummy did not appear to be statistically significant in 
our  specification,  which  suggests  that  non-EU/EFTA  banks  are  not  affecting  the 
statistical  significance  of  the  results.  The  system  GMM  approach  also  takes  into 
account  banks’  fixed  effects,  which  also  includes  the  countries  in  which  they  are 
headquartered. 

We  also  tested  the  impact  of  disclosure  quality  on  the  cost  of  equity  capital, 
conditional on the state of the existing information environment as in Eugster (2014). 

65 Previous evidence from Fama Jr. (2006) show that the ‘three-factor model’ explains, 
on  average,  95%  of  an  asset’s  returns,  which  suggest  that  these  factors  could 
dominate the effects on cost of equity. 

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CRD IV 

Specifically,  we  tested  for  the  opaqueness  hypothesis,  i.e.  whether  the  impact  of 
disclosure  quality  on  the  cost  of  equity  capital  is  limited  to  firms  with  a  low  analyst 
following. If this were true, for firms in a high information environment, an increase in 
the  level  of  disclosure  would  be  of  limited  value  to  investors.  We  used  analyst 
coverage as a proxy for the information environment, specifically by using the number 
of  forecasts  available  for  each  bank;  this  is  included  as  an  additional  explanatory 
variable  in  our  basic  specification.  We  expect  that  banks  in  a  low  information 
environment with a high level of disclosure quality would have a lower cost of equity 
capital.  We  found  that  the  significance  of  the  overall  disclosure  quality  score  was 
robust to the inclusion of the analyst coverage variable, which suggests that firms in 
both  a  low-  and  high-information  environment  benefit  from  increased  disclosure 
quality. 

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 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Table 6: Results for the impact of disclosure quality on cost of equity capital using individual disclosure scoring components 

Cost of equity capital 

Risk Management 
score 

Corporate Governance 
score 

Non-Financials 
score 

Targets score  Market Share 

score 

Shareholder 
Returns score 

Risk management score 

Corporate governance score 

-0.0011 
(0.738) 

Non-financials score 

Targets score 

Market share score 

Shareholder Returns score 

Lag of cost of equity 

Beta 

Log of market capitalisation 

Market to book value 

2008 Dummy 

Constant 

Firm-year 

# of instruments 

F-stat 

Sargan p-value 

Hansen p-value 

AR(1) test p-value 

AR(2) test p-value 

0.2483** 
(0.012) 

0.0226* 
(0.079) 

-0.0195** 
(0.043) 

-0.0316*** 
(0.000) 

0.0223*** 
(0.000) 

0.3384*** 
(0.001) 

493.000 

47 

 278.47 

0.000 

0.423 

0.010 

0.105 

-0.0006 
(0.889) 

0.257*** 
(0.000) 

0.0318*** 
(0.001) 

-0.011* 
(0.086) 

-0.025*** 
(0.000) 

0.0226*** 
(0.000) 

0.2175*** 
(0.005) 

493.000 

42 

 172.40 

0.000 

0.418 

0.008 

0.090 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level  

Source: PwC analysis 

September 2014   

56 

-0.0022 
(0.272) 

0.2563*** 
(0.000) 

0.0286*** 
(0.003) 

-0.001 
(0.872) 

-0.0296*** 
(0.000) 

0.0209*** 
(0.000) 

0.1415** 
(0.049) 

493.000 

42 

 173.23 

0.000 

0.384 

0.007 

0.060 

-0.0021 
(0.583) 

0.2918*** 
(0.000) 

0.0208** 
(0.016) 

-0.0153** 
(0.016) 

-0.0247*** 
(0.000) 

0.0177*** 
(0.002) 

0.273*** 
(0.000) 

493.000 

37 

 268.74 

0.012 

0.544 

0.007 

0.107 

0.0022 
(0.739) 

0.2614*** 
(0.003) 

0.0204* 
(0.073) 

-0.016* 
(0.074) 

-0.0265*** 
(0.000) 

0.0166** 
(0.015) 

0.2749** 
(0.012) 

493.000 

37 

 163.51 

0.002 

0.462 

0.011 

0.101 

-0.0001 
(0.993) 

0.2757*** 
(0.000) 

0.0226** 
(0.026) 

-0.0173** 
(0.025) 

-0.0244*** 
(0.000) 

0.021*** 
(0.000) 

0.2868*** 
(0.000) 

493.000 

37 

 333.42 

0.006 

0.400 

0.008 

0.120 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Impact of disclosure quality on bid-ask spreads 

Section summary 

We  hypothesise  that  improved  disclosure  scores  will  reduce  bid-ask  spreads  due  to 
improved  intermediation  for  a  firm’s  stock  as  a  result  of  reduced  information 
asymmetries  between  management  and  outside  investors  (Healy  et  al.,  1999;  Leuz 
and Verrecchia, 2000).  

We  use  a  dynamic  system  GMM  model  to  estimate  this  relationship  to  overcome 
possible estimation problems such as endogeneity within the regression.  

Our findings suggest there is no statistically significant relationship between disclosure 
quality  and  bid-ask  spreads.  The  lack  of  a  relationship  could  be  due  to  the  fact  that 
spreads  tend  to  be  driven  by  short-term  changes  in  the  trading  environment  and 
market  factors,  and  less  so  by  longer-term,  structural  factors  such  as  disclosure 
quality.  

Modelling approach 

Information  asymmetries  can  create  costs  by  introducing  adverse  selection  into 
transactions between buyers and sellers of shares. This typically manifests in reduced 
levels of liquidity for shares or large bid-ask spreads (Leuz and Verrecchia, 2000).  

High  bid-ask  spreads  can  thus  indicate  the  presence  of  information  asymmetry,  with 
market  makers  widening  bid-ask  spreads  in  order  to  protect  themselves  against 
making losses when transacting with better informed traders and to be compensated 
for  bearing  greater  risk  (Kyle,  1985;  Glosten  and  Milgrom,  1985;  Amihud  and 
Mendelson, 1988; Diamond and Verrecchia, 1991; Leuz and Verrecchia, 2000). 

We  use  the  specification  outlined  in  Espinosa,  Tapia  and  Trombetta  (2008).  Prior 
research  further  supports  the  use  of  our  controls  (Hanley,  Kumar  and  Seguin,  1993; 
Welker,  1995;  Brockman  and  Chung,  1999; Healy  et  al.,  1999;  Corwin,  1999;  Heflin 
and Shaw, 2000, 2001). We estimate the following using a dynamic GMM approach: 

(2) 

As with our cost of equity regressions, we include the lag of the dependent variable to 
account  for  the  historical  feedback  between  past  and  current  bid-ask  spreads.  High 
bid-ask spreads could incentivise banks to lower these in the next period by increasing 
the quality of their disclosures to lower information asymmetries. For this reason, and 
for the reasons set out in our methodology section, we use a system GMM approach in 
order to overcome potential estimation problems. The system GMM approach uses an 
instrumental  variable  based  approach  where  higher  lag  values  of  the  lagged 
dependent variable are used as instruments. First differencing also allows us to control 
for firms’ fixed effects, i.e. time-invariant unobserved heterogeneity. 

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Table 7: List of variables used for econometric analysis 

Variable 

Expected 
Relationship 

Description 

Spreadit 

Yearly  average  of  daily  relative  bid-ask  spreads  for 
company i at time t 

Spreadit-1 

+ 

Lag of bid-ask spreads for company i at time t-1 

Disclosure 
Scoreit 

Log of market 
capitalisationit 

Log 
turnoverit 

of 

Betait 

Year10 

- 

- 

- 

+ 

~ 

Total  disclosure  quality  score,  out  of  75,  for  company  i
at time t 

Natural log of the equity market value for company i at 
time t 

The log of turnover value is the natural log of the annual 
average  of  the  daily  number  of  shares  times  the 
transaction price for company i at time t 

Measure  of  an  asset’s  risk  in  relation  to  the  market  for 
company i at time t  

A  binary  variable  equal  to  1  if  year  equals  2010  and  0 
otherwise 

We hypothesise that an increase in disclosure quality leads to a reduction in the bid-
ask spread. We include other explanatory variables that are likely to influence the bid-
ask spread. These include the market value of a company, which we expect to have a 
negative impact on the spread. Larger firms often exhibit smaller spreads as there is 
more  information  available  about  them  for  investors,  reducing  the  information 
asymmetries  that  can  cause  the  bid-ask  spread  to  widen.  Liquid  assets  pose  lower 
risks to investors of not being able to turn their holdings into cash, so a higher market 
capitalisation  that  is  associated  with  lower  information  asymmetries  and  increased 
liquidity should reduce the risk of investing, and hence, the bid-ask spread. 

The spread may also be influenced by other factors of liquidity, such as the share price 
of the company and the volume of shares traded in a given day. Banks that are traded 
at  a  higher  volume  and  higher  price  (more  valuable  shares)  are  likely  to  have  a 
narrower  spread.  Firms  that  are  traded  in  lower  volumes  and  at  low  prices  are 
considered to be more illiquid, such that the broker needs to be compensated for the 
liquidity risk in carrying out the transaction, introducing a spread during the execution 
of the trade. Thus we expect a negative relationship between the spread and the log 
of  turnover  value  and  a  positive  relationship  between  the  spread  and  the  inverse  of 
the share price.  

We also included beta as an additional control variable in our specification. Beta is the 
CAPM measure of risk, specifically the volatility of stock returns. Banks that are more 
volatile tend to be associated with higher risks and are less liquid, and as a result will 
be  more  likely  to  face  larger  bid-ask  spreads.  We  included  the  2010  dummy  in  our 
specification by testing several model specifications with year dummies, in which 2010 
consistently appeared to be significant. 

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Data and summary statistics 

The  bid-ask  spread  is  measured  as  the  yearly  average  of  daily  relative  bid-ask 
spreads.66  The  data  for  this  measure  is  obtained  from  S&P  Capital  IQ,  while  the 
remaining variables have been collected from Thomson Reuters on an annual basis.  

Table 8: Summary statistics for variables used in the spreads model  

Mean  Median 

Min 

Max 

Standard deviation 

Spread 
Disclosure Score 
of 
Log 
Capitalisation 
Log of Turnover 
Beta 

Market 

Source: PwC analysis 

0.002 
42.518 

0.001 
43.000 

0.000 
19.000

0.047 
70.000 

10.369 

10.444 

6.276 

12.418 

4.723 
1.316 

4.849 
1.236 

-0.047 
-0.807 

8.213 
3.202 

0.003 
8.700 

1.003 

1.524 
0.504 

The  standard  deviation  of  the  bid-ask  spread  is  almost  three  times  the  size  of  the 
mean,  suggesting  it  is  highly  volatile.  The  volatility  stems  from  the  large  range  of 
factors  that  affect  the  spread,  particularly  the  array  of  macroeconomic  factors  that 
affect  investor  knowledge.  Beta  is  also  a  relatively  volatile  component  of  the 
regression,  which  is  consistent  with  the  fact  that  banks  have  undergone  a  significant 
amount of volatility, particularly in recent years. 

Table 9 shows the correlation matrix for bid-ask spread and the control variables used 
in our model specification. It provides limited evidence of strong multi-collinearity with 
most correlations coefficients remaining within -0.3 and 0.3. It also shows that there 
is  not  a  strong  correlation  between  disclosure  score  and  spread,  however,  we  do 
observe  a  negative  relationship.  The  log  of  turnover  does  have  a  significant  positive 
correlation with the log of market capitalisation. Similarly, Table 7 shows a scatter plot 
between total disclosure score and spread, which does not indicate a strong negative 
relationship between disclosure score and the spread. 

Spread  seems  to  be  correlated  most  strongly  with  market  capitalisation,  with  the 
negative correlation implying that a greater market capitalisation reduces the bid-ask 
spread, which is consistent with the existing evidence that suggests bigger firms have 
a  lower  bid-ask  spread.  Spread  is  also  negatively  correlated  with  the  log  of  turnover 
(with  higher  values  of  turnover  indicating  higher  liquidity  levels),  however  it  is 
negatively correlated with beta, although this correlation is weaker.  

Table 9: Correlation matrix for bid-ask spread 

Spread 

1.000 
-0.209 
-0.375 

-0.251 
-0.029 

Disclosure 
Score 

- 
1.000 
0.092 

-0.026 
0.176 

Log of 
Market 
Capitalisation
- 
- 
1.000 

Log of 
Turnover 

Beta 

- 
- 
- 

- 
- 
- 

0.704 
0.164 

1.000 
0.194 

- 
1.000 

Spread 

Disclosure Score 

Log  of  Market 
Capitalisation 

Log of Turnover 

Beta 
Source: PwC analysis 

66 This is the difference between the bid and ask prices, scaled by the midpoint of the 
bid and ask prices. 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Figure 7: Scatter plot between total disclosure score and bid ask spreads 

Source: PwC analysis 

Results 

Our results from the preferred model revealed that increasing the quality of disclosure 
does not have a significant effect on the bid-ask spreads, which may be because other 
short-term factors affect bid-ask spreads. 

The  results  in  Table  10  show  that  the  lag  of  disclosure  score  does  not  have  a 
statistically significant impact on bid-ask spreads (the coefficient is in the wrong sign 
but  is  insignificant).  The  lag  of  spread  has  a  statistically  significant  (at  1%)  and 
positive  relationship  with  spread,  as  expected.  Similarly  the  log  of  market 
capitalisation  is  significant  at  the  10%  level,  providing  the  relationship  we  expected. 
The  log  of  turnover  value  has  its  expected  sign,  though  it  is  not  significant,  whereas 
beta has the opposite sign but again is insignificant. 

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Table 10: Results for the impact of disclosure quality on spreads using disclosure 
score and the regional breakdown score 

Spreads 

Total disclosure 
score 

Regional Breakdown 
score 

Lag of Total disclosure score 

Lag  of  Regional  breakdown 
score 

Lag of spread 

Beta 

Log of market capitalisation 

Log of turnover 

2010 dummy 

Constant 

Firm-year 

# of instruments 

F-stat 

Sargan p-value 

Hansen p-value 

AR(1) test p-value 

AR(2) test p-value 

0.0001 
(0.558) 

-  

0.5777*** 
(0.000) 

-0.0005 
(0.459) 

-0.0013* 
(0.054) 

-0.0001 
(0.542) 

-0.0006*** 
(0.000) 

0.013** 
(0.027) 

506 

37 

 193.21 

0.000 

0.460 

0.004 

0.225 

-  

0.0001 
(0.796) 

0.4841*** 
(0.000) 

0.0001 
(0.878) 

-0.0012** 
(0.037) 

-0.0002 
(0.425) 

-0.0006*** 
(0.000) 

0.0145** 
(0.017) 

506 

37 

 124.88 

0.000 

0.292 

0.002 

0.175 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis 

The sensitivity of bid-ask spreads to the macroeconomic environment can be captured 
in  year  dummies,  with  bad  industry  years  having  a  positive  correlation  with  bid-ask 
spreads.  We  ran  the  regression  with  all  years  and  found  2010  to  be  consistently 
significant.  We  therefore  included  a  dummy  for  2010  in  the  specification.67  The 
dummy for 2010 is negative and highly significant at 1%.  

We  also  test  whether  the  regional  breakdown  score  has  an  impact  on  the  spread 
measure, and similarly, found no statistically significant relationship. 

We  proceeded  to  test  the  other  specific  components  of  disclosure  score  individually, 
running  six  additional  regressions.  These  results  are  provided  in  Table  11.  The 
coefficients of the individual scoring components have the opposite sign, to the one we 
would expect; however none of these are significant.  

67 Removing the year dummies from the specification does not change the significance of any of the other 
variables.  

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CRD IV 

We test the validity of these results using the Hansen J test. The p-values for all our 
model  specifications  are  greater  than  0.05,  which  means  that  the  null  hypothesis  of 
instrument  exogeneity  cannot  be  rejected.  The  p-value  is  0.460  for  the  specification 
for total disclosure score. Our specifications that test the impact of individual scoring 
components also pass the Hansen J test.  

The null hypothesis was rejected in the AR (1) test, with a p-value of 0.004 which is 
well below 0.05 for the specification for total disclosure score. This suggests that the 
first lag of the dependent variable, in this case bid-ask spreads, is strongly correlated 
with its current value, justifying the use of a dynamic model in this case. For the AR 
(2)  test  we  fail  to  reject  the  null  of  no  correlation  between  the  second  lag  of  the 
dependent  variable  and  the  current  value.  Thus  the  serial  correlation  of  order  2, 
between the current value of dependent variable and the value of its second lag, is not 
an issue in our model and does not need to be accounted for.  

Before  running  the  system  GMM  regressions  we  individually  tested  whether  each 
explanatory variable was endogenous using Stata’s “ivreg2” command and whether its 
instruments were both valid and relevant. For validity we used the endogeneity tests 
and for relevance we made sure that both the Cragg-Donald Wald and Kleibergen and 
Schaffer  tests  were  satisfied.  As  in  the  cost  of  equity  capital  modelling,  the  Stata 
“ivreg2”  test  for  instrument  validity  and  relevance  suggests  that  the  optimal  GMM 
model should have higher combinations of lags. 

We  conclude  that  increasing  the  quality  of  disclosures  has  little  effect  on  the  bid-ask 
spread. This seems surprising, given the significant results obtained for the impact of 
disclosure quality on cost of equity capital. Various studies have also documented the 
relationship  between  market  liquidity  and  the  effective  cost  of  equity  capital  –  a 
reduction in the bid-ask spread should be associated with a reduction in the effective 
cost  of  equity  capital  as  investors  require  less  compensation  for  being  subject  to 
liquidity risks. This suggests that the degree of influence of disclosure quality over the 
effective  cost  of  equity  capital  is  stronger  than  for  bid-ask  spreads,  which  may  be 
more driven by short-term changes in the trading factors and other transient market 
factors. 

Robustness and sensitivity tests 

Similar  to  cost  of  equity,  we  included  the  IFRS  dummy  initially  in  our  model 
specification.  However,  the  IFRS  dummy  was  not  significant  and  its  inclusion  did  not 
alter  any  of  the  results  qualitatively.  As  explained  in  the  previous  section,  it  is 
unsurprising  to  observe  a  statistically  insignificant  coefficient  on  this  variable,  due  to 
the  growing  similarities  between  IFRS  and  US  GAAP.  Due  to  this,  as  well  as  the 
potential risk of collinearity between disclosure score and IFRS, we decided to exclude 
the IFRS dummy from the regression.  

We also included a dummy equal to 1 if the bank is headquartered in an EU or EFTA 
country  to  test  whether  non-EU/EFTA  banks  are  affecting  the  significance  of  the 
results. The coefficient for this dummy did not appear to be statistically significant in 
our  specification,  which  suggests  that  non-EU/EFTA  banks  are  not  affecting  the 
statistical significance of the results.  

We  test  the  robustness  of  our  results  by  using  an  alternative  measure  of  liquidity  as 
,  which  is  frequently  used  as  a  measure  of 
outlined  in  Amihud  (2002),  called 
illiquidity in the literature. The higher the value of ILLIQ, the lower the level of market 
liquidity.  When  a  stock  has  a  high  value  of  ILLIQ,  it  suggests  that  the  price  moves 
quite a lot in response to trading volume, and thus the stock is considered illiquid. This 
involves calculating the annual average of daily stock returns divided by daily turnover 
value for each bank. This is set out as follows: 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

 is the number of trading days for firm i in year t, 

 is the daily stock return for firm 

i on day j, and 

 is the dollar daily volume of stock traded for firm i on day j.  

This measure therefore replaced the bid-ask spread as the dependent variable in our 
specification, and was regressed against the same set of explanatory variables as set 
out  in  Table  7.  We  also  used  the  system  GMM  approach.  We  found  that  there  is  no 
change  qualitatively  to  the  results  we  obtained  using  bid-ask  spreads.  This  provides 
support  for  the  lack  of  evidence  linking  an  improvement  in  disclosure  quality  with 
improved market liquidity. 

September 2014   

63 

 
 
 
 
 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Table 11: Results for the impact of disclosure quality on spreads using the individual disclosure scoring components 

Spreads 

Lag of Risk management score 

Lag  of  Corporate  governance 
score 

Lag of Non-financials score 

Lag of Targets score 

Lag of Market share score 

Lag of Shareholder returns score 

Lag of spread 

Beta 

Log of market capitalisation 

Log of turnover value 

2010 dummy 

Constant 

Firm-year 

# of instruments 
F-stat 
Sargan p-value 
Hansen p-value 
AR(1) test p-value 
AR(2) test p-value 

Risk management 
score 
0 
(0.799) 

Corporate 
Governance score 

Non-Financials 
score 

Targets 
Score 

Market Share 
score 

Shareholders 
Return score 

0.0002 
(0.417) 

0.3431** 
(0.042) 
-0.0007 
(0.369) 
-0.0029** 
(0.013) 
-0.0007 
(0.174) 
-0.0004** 
(0.027) 
0.0351*** 
(0.007) 
506 

42 

 120.69 
0.000 
0.291 
0.603 
0.603 

0.0001 
(0.411) 

0.5341*** 
(0.000) 
-0.0004 
(0.192) 
-0.0015** 
(0.036) 
-0.0001 
(0.776) 
-0.0006*** 
(0.000) 
0.0159*** 
(0.009) 
506 

37 

 286.74 
0.000 
0.539 
0.003 
0.293 

0.0006 
(0.183) 

0.5671*** 
(0.000) 
-0.0002 
(0.489) 
-0.0015** 
(0.023) 
-0.0002 
(0.396) 
-0.0006***
(0.01) 
0.0152** 
(0.021) 
506 

32 

 177.68 
----- 
nts.) 
----- 
0.001 

-0.0003 
(0.62) 

0.4581*** 
(0.000) 
0.0002 
(0.609) 
-0.0011* 
(0.094) 
-0.0002 
(0.275) 
-0.0005*** 
(0.003) 
0.0138** 
(0.019) 
506 

22 

 130.22 
0.000 
0.246 
0.006 
0.119 

0.0003 
(0.32) 

0.4645*** 
(0.000) 
0 
(0.927) 
-0.0014** 
(0.045) 
-0.0001 
(0.607) 
-0.0005*** 
(0.000) 
0.0151** 
(0.025) 
506 

37 

 149.95 
0.000 
0.346 
0.003 
0.207 

0.4941*** 
(0.000) 
0.0001 
(0.867) 
-0.001* 
(0.084) 
-0.0002 
(0.35) 
-0.0007*** 
(0.000) 
0.0121* 
(0.061) 
506 

37 

 103.39 
0.000 
0.385 
0.003 
0.152 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis 

September 2014   

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Impact of disclosure quality on transparency 

Section summary 

This  regression  is  based  on  the  theoretical  idea  that  through  being  more  transparent 
and  providing  more  information  to  the  general  public,  banks  can  reduce  investor 
uncertainty about their future earnings, increasing the accuracy of analysts’ forecasts. 
We  hypothesise  that  an  increase  in  disclosure  quality  is  associated  with  improved 
accuracy of analysts’ earnings forecasts.  

Again,  we  use  the  dynamic  system  GMM  approach  to  this  model,  due  to  potential 
estimation problems, such as endogeneity.  

We  find  some  empirical  evidence  to  support  this  hypothesis,  as  we  observe  a 
significant positive relationship between our disclosure scoring index and the accuracy 
of analysts’ earnings forecasts: an increase in disclosure score by 1 increases forecast 
accuracy  by  0.49  percentage  points.  We  find  that  the  driver  of  this  relationship  is 
disclosures  relating  to  corporate  governance  and  non-financial  disclosures.  However, 
our  results  provide  limited  support  for  the  potential  impacts  of  CBCR  on  forecast 
accuracy,  as  we  find  the  impact  of  regional  breakdown  scores  on  accuracy  to  be 
insignificant.  

Modelling approach 

We use a model specification based on De Franco et al. (2009) to study the impact of 
higher  quality  disclosures  on  the  accuracy  of  analysts’  earnings  forecasts,  which 
serves as a proxy for the information environment. We hypothesise that an increase in 
disclosure quality is associated with an increase in analyst forecast accuracy. We use 
the following model specification: 

(3) 

Accuracyit in this context is defined as the absolute value of the forecast error, or the 
absolute  difference  between  firm  i’s  actual  earnings  and  the  mean  of  analysts’ 
earnings forecasts for firm i that is published in December each year for the following 
financial  year.  This  is  scaled  by  price  and  multiplied  by  -1,  so  that  a  higher  value 
indicates increased accuracy and a lower value indicates lower accuracy. 

We  control  for  other  determinants  of  accuracy  which  are  commonly  used  in  the 
literature  (Heflin  et  al.,  2003;  De  Franco  et  al.,  2009).  Firms  which experience  more 
volatile earnings, earnings below last year’s earnings (negative earnings) or earnings 
below  zero  (loss  earnings)  are  likely  to  cause  analysts’  difficulty  in  forecasting  as 
earnings  do  not  demonstrate  stability  or  predictability.  The  earnings  predictability 
variable captures the extent to which historical earnings have exhibited a pattern over 
time  –  the  higher  the  degree  of  explanatory  power  of  previous  years’  earnings  over 
current  earnings,  the  more  predictable  earnings  become.  This  enables  analysts  to 
forecast  earnings  accurately  (Kross,  Ro  and  Schroeder,  1990;  Lang  and  Lundholm, 
1996).  The  greater  the  number  of  days  between  the  forecast  being  made  and  the 
earnings  announcement  date,  the more  likely it  is  for  accuracy  to  decrease,  as  more 
recent  forecasts  have  a  greater  chance  of  capturing  new  industry  or  market 
information that may affect earnings (Sinha et al., 1997; Clement, 1999; Brown and 

September 2014   

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Mohd, 2003; Karamanou and Vafeas, 2005; De Franco et al., 2009). We also control 
for  banks’  market  capitalisation,  as  size  is  positively  related  to  earnings  stability, 
thereby improving forecast accuracy (Jelic et al., 1998), leading to greater consensus 
among analysts (Beekes et al., 2012).  

We  use  a  dynamic  system  GMM  approach  to  test  our  hypothesis.  This  is  due  to 
potential  estimation  problems  such  as  reverse  causality:  past  values  of  forecast 
accuracy  could  influence  firms’  decisions  over  the  current  period’s  disclosure  score. 
Banks for whom earnings forecasts are consistently inaccurate may have an incentive 
to  increase  the  quality  of  their  disclosure  to  reduce  the  likelihood  of  inaccurate 
forecasts. This is because inaccurate forecasts may give investors the perception that 
the bank’s earnings are volatile or that the bank’s disclosures are not transparent.  

Table 12: List of variables used in the accuracy regression 

Variable 

Expected 
Relationship 

Description 

Accuracyit 

Accuracyit-1 

Disclosure 
Scoreit 

Unexpected 
Earningsit 

Negative 
Earningsit 

Loss 
Earningsit 

Earnings 
Volatilityit 

Earnings 
Predictabilityit 

Log  of  Market 
Capitalisationit 

Daysit 

+ 

+ 

- 

- 

- 

- 

+ 

+ 

- 

The absolute value of the forecast error, or the absolute 
difference  between  firm  i’s  actual  earnings  and  the 
mean  of  analysts’  earnings  forecasts  for  firm  i  that  is 
published  in  December  each  year  for  the  time  t (the 
following  financial  year).  This  is  scaled  by  price  and 
multiplied by -1. 

Lag  of  the  absolute  value  of  the  analyst  December 
forecast error for company i at time t 

Disclosure score, out of 75, using PwC disclosure quality 
scoring index for company i at time t 

Absolute  value  of  unexpected  earnings,  scaled  by  the 
stock  price  at  the  end  of  the  prior  year,  where 
unexpected earnings is actual earnings less the previous 
year’s earnings for company i at time t 

Indicator variable that equals one if firm i’s earnings are 
below the reported earnings a year ago, and equals zero 
otherwise for company i at time t 

Indicator  variable  that  equals  one  if  the  current 
earnings is less than zero, and equals zero otherwise for 
company i at time t  

Standard deviation of the sixteen most recent quarterly 
earnings for company i at time t 

The R2 of a regression of annual earnings on prior-year 
annual earnings for the same firm for company i at time 
t 

Natural log of the equity market value for company i at 
time t 

Number of days from the forecast date to the December 
earnings announcement date for company i at time t 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

IFRSit 

- 

A  binary  variable  equal  to  1  if  the  bank  used  IFRS 
accounting standards at time t or equal to 0 if otherwise 
for company i at time t 

We use a dynamic approach to account for autocorrelation in the relationship between 
forecast  accuracy  in  the  current  period  and  in  the  last  period.  The  more  accurate  a 
forecast  was  in  the  previous  period,  the  more  likely  it  is  to  be  accurate  in  the  next 
period  due  to  the  analyst  becoming  more  familiar  with  the  bank  and  adept  at 
interpreting  their  disclosures.  Furthermore,  there  may  also  be  reverse  causation 
occurring in the model, with less accurate forecasts encouraging firms to increase the 
quality  of  their  disclosures  in  order  to  aid  analysts  in  their  predictions  and  increase 
investor confidence and liquidity. Therefore, we use a dynamic system GMM approach, 
as outlined in the earlier methodology sections, to account for endogeneity. 

Data and summary statistics 

We measure accuracy as the absolute value of the forecast error, multiplied by -1 and 
scaled by the stock price, so that a higher value implies higher levels of accuracy (De 
Franco  et  al.,  2009).  Earnings  announcements  are  typically  made  a  few  months 
following  the  end  of  the  financial  year  and  all  the  banks  in  our  sample  have  a 
December financial year end. To construct the accuracy variable, we took the mean of 
I/B/E/S  analysts’  earnings  forecasts  that  are  published  in  December.  The  forecast 
error  is  the  difference  between  the  December  forecasts  and  actual  earnings 
subsequently announced by the bank. 

The earnings predictability variable was constructed by regressing current earnings on 
lagged  earnings  (Lipe,  1990;  De  Franco  et  al.,  2009).  A  higher  R2  indicates  that 
current  earnings  are  somewhat  explained  by  lagged  earnings,  suggesting  earnings 
growth exhibits some trend or predictability.  

Table 13: Summary statistics of analyst accuracy regression 

Mean  Median Minimum Maximum 

-0.083 
Accuracy 
42.723 
Disclosure Score 
-0.010 
Unexpected Earnings 
0.320 
Negative Earnings 
0.087 
Loss Earnings 
0.561 
Earnings Volatility 
Earnings Predictability 
0.637 
Log of Market Capitalisation  10.449 
Days 
IFRS dummy 

-0.036 
43.000 
0.003 
0.000 
0.000 
0.156 
0.681 
10.496 
415.132 413.000
1.000 

0.574 

-0.986 
19.000 
-2.523 
0.000 
0.000 
0.000 
0.016 
7.257 
346.000 
0.000 

0.000 
70.000 
0.878 
1.000 
1.000 
10.372 
0.973 
12.418 
537.000 
1.000 

Standard 
Deviation 
0.145 
8.529 
0.200 
0.467 
0.283 
1.169 
0.234 
0.937 
26.459 
0.495 

Source: PwC analysis 

The  variable  ‘days’  has  the  largest  dispersion.  The  negative  earnings  variable  is  also 
very  volatile,  with  a  standard  deviation  greater  than  the  mean.  There  is  also  a 
relatively  large  dispersion  of  accuracy,  the  absolute  value  of  the  forecast  error,  and 
the loss earnings.  

Table  14  shows  the  correlation  matrix  for  the  disclosure  quality  score  and  other 
variables included in our model specification. Most of the pairwise correlations indicate 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

that  the  risks  of  multi-collinearity  are  minimal.  There  is  a  negative,  but  weak, 
relationship  between  disclosure  scores  and  accuracy.  Earnings  predictability  has  a 
negative relationship with accuracy, which is surprising as it indicates that an increase 
in  earnings  predictability  is  associated  with  decreased  forecast  accuracy,  while  the 
volatility  of  earnings  is  positively  correlated  with  accuracy.  We  observe  a  weak 
negative  correlation  between  the  number  of  days  between  the  forecast  date  and  the 
earnings announcement date, which is as expected. The log of market capitalisation is 
also positively correlated with accuracy. 

There appears to be a moderate correlation between the IFRS dummy and disclosure 
score, which suggests that IFRS adoption is associated with better disclosure scores. 

Table 14: Correlation matrix between variables in the accuracy regression 

Accuracy

Disclosu
re Score 

Unexpec
ted 
Earnings

Negative 
Earnings

Loss 
Earnings

Earnings 
Volatility

Earnings 
Predicta
bility 

Log of 
Market 
Capitalis
ation 

IFRS 

Days 

Accuracy 

1.000 

- 

-0.160 

1.000 

0.094 

-0.088 

1.000 

- 

- 

- 

- 

- 

-0.044 

0.126 

-0.322 

1.000 

Loss Earnings  -0.265 

0.178 

-0.255 

0.313 

1.000 

- 

- 

- 

- 

- 

- 

- 

- 

- 

Disclosure 
Score 

Unexpected 
Earnings 

Negative 
Earnings 

Earnings 
Volatility 

Earnings 
Predictability 

Log of Market 
Capitalisation 

0.013 

-0.032 

-0.014 

0.098 

0.261 

1.000 

-0.027 

0.087 

0.022 

-0.095 

0.078 

0.106 

1.000 

0.203 

-0.096 

-0.070 

-0.024 

-0.140 

-0.008 

-0.075 

1.000 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

Days 

-0.105 

0.134 

-0.049 

-0.054 

0.129 

-0.161 

-0.003 

-0.254 

1.000 

IFRS dummy 

-0.166 

0.484 

-0.059 

0.021 

0.146 

-0.097 

0.023 

-0.240 

0.592 

1.000 

Source: PwC analysis 

September 2014   

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Results  

Our  econometric  modelling  reveals  that  the  quality  of  disclosures  has  a  significantly 
positive  impact  on  the  accuracy  of  analyst’s  earnings  forecasts;  this  relationship  is 
driven  by  the  corporate  governance  and  non-financial  elements  of  our  disclosure 
scoring index.  

The  results  in  Table  15  show  that  the  relationship  between  disclosure  quality  and 
accuracy  is  significant  at  the  5%  level,  with  an  increase  of  disclosure  score  by  1 
reducing the absolute value of the forecast error by 0.49 percentage points, increasing 
accuracy.  

Table 15: Results for the impact of disclosure quality on accuracy using disclosure 
score and regional breakdown score 

Forecast Accuracy 

Total disclosure Score 

Regional Breakdown score 

Lag of Earnings Accuracy 

Total disclosure score 

Regional breakdown score 

Unexpected Earnings 

Negative Earnings 

Loss Earnings 

Earnings Volatility 

Earnings Predictability 

Days 

Log of market capitalisation 

IFRS dummy 

Constant 

Firm-year 

# of instruments 

F-stat 

Sargan p-value 

Hansen p-value 

AR(1) test p-value 

AR(2) test p-value 

0.3405*** 
(0.001) 

0.0049** 
(0.04) 

 - 

0.1499 
(0.374) 

0.0229 
(0.203) 

-0.0797** 
(0.048) 

0.0074 
(0.517) 

0.019 
(0.582) 

-0.001 
(0.285) 

0.0899** 
(0.035) 

-0.1187* 
(0.079) 

-0.7358 
(0.183) 

375 

51 

  28.30 

0.000 

0.643 

0.109 

0.138 

0.2599** 
(0.021) 

 - 

0.0364 
(0.36) 

0.1653 
(0.242) 

0.0293* 
(0.099) 

-0.0655** 
(0.05) 

0.0134 
(0.306) 

0.0341 
(0.265) 

-0.0021 
(0.106) 

0.1091** 
(0.013) 

-0.1362* 
(0.078) 

-0.434 
(0.468) 

375 

51 

  31.87 

0.524 

0.596 

0.127 

0.138 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis 

The  lag  of  accuracy  has  a  positive  and  highly  significant  impact  on  current  levels  of 
accuracy,  which  provides  support  for  our  dynamic  model  specification.  We  also 
observe  that,  of  our  control  variables,  loss  earnings  and  the  log  of  market 

September 2014   

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

capitalisation exhibit consistent significance throughout our model specifications, both 
of which are in the expected signs; accuracy is lower for banks whose current earnings 
are  negative,  relative  to  those  who  had  positive  earnings.  Forecasts  for  larger  firms 
(as reflected in the log of market capitalisation) are also likely to be more accurate.  

Unexpected  earnings,  negative  earnings  and  earnings  volatility  are  in  the  opposite 
signs,  but  are  insignificant.  The  variable  days  is  negative,  i.e.  the  greater  the  gap 
between  when  the  forecast  is  made  and  the  earnings  announcement  date,  the  less 
accurate the forecast; however, this is also insignificant. 

We  also  test  whether  the  regional  breakdown  score  has  an  impact  on  the  forecast 
accuracy measure, and found no statistically significant relationship. 

We proceeded to test the other individual components of disclosure score, again aimed 
at identifying the underlying reason for the significant relationship between disclosure 
score  and  forecast  accuracy.  Of  the  six  individual  components,  the  coefficient  on 
corporate governance and non-financial disclosure scores are significant and positive. 
Corporate  governance  refers  to  the  structures  and  processes  in  place  aimed  at 
reducing  the  agency  problem  and  aligning  manager  and  shareholder  interests 
(Armstrong, Guay and Weber, 2010). As mentioned in the literature review, Beekes et 
al.  (2012)  explain  how  the  transparency  of  disclosures  regarding  the  corporate 
structure of a firm is related to the credibility of a firm’s overall disclosures, meaning 
that  analysts  will  place  greater  reliance  on  disclosures  when  forecasting.  It  is 
important  to  note  that  the  significance  of  corporate  governance  scores  is  slightly 
higher than the disclosure score, providing further empirical evidence that the quality 
of  corporate  governance  disclosures  are  crucial  to  the  relationship  with  forecast 
accuracy. This finding for non-financial disclosure scores is perhaps surprising, as we 
would not necessarily expect an increase in the quality of non-financial information to 
have  a  significant  positive  association  with  forecast  accuracy.  These  findings  are 
consistent with Dhaliwal et al. (2012), and suggest that non-financial disclosures play 
a complementary role to financial disclosure and are informative to analysts. 

As  outlined  in  previous  sections,  to  ensure  the  robustness  of  our  model,  the 
specification  must  meet  several  requirements.  The  lag  combination  of  our  chosen 
models  met  the  Blundell-Bond  plausibility  check  and  specifies  the  highest  Wald 
statistic. For the basic specification, and with the 2008 year dummy, we are unable to 
reject the Hansen J test’s null hypothesis of exogeneity, supporting the validity of our 
instruments.  This  is  also  the  case  for  the  individual  component  regressions.  Further, 
we reject the AR (1) test of autocorrelation of order 1, which indicates that there is a 
correlation between accuracy and its value in the previous period; but the results for 
the  AR  (2)  test  reveal  we  cannot  reject  the  null  of  no  autocorrelation,  thus  implying 
that the model does not suffer from autocorrelation of order two.68 

Before  running  the  system  GMM  regressions  we  individually  tested  whether  each 
explanatory variable was endogenous using Stata’s “ivreg2” command and whether its 
instruments were both valid and relevant. For validity we used the endogeneity tests 
and for relevance we made sure that both the Cragg-Donald Wald and Kleibergen and 
Schaffer  tests  were  satisfied.  As  in  the  cost  of  equity  capital  modelling,  the  Stata 
“ivreg2”  test  for  instrument  validity  and  relevance  suggests  that  the  optimal  GMM 
model should have higher combinations of lags. 

Our  results  reveal  that  there  is  a  significant  relationship  between  higher  quality 
disclosures  and  the  accuracy  of  analysts’  forecasts  and  it  is  the  quality  of  the 
disclosures  relating  to  corporate  governance,  market  share  and  shareholder  returns 
that  drive  this  relationship.  We  can  only  draw  limited  conclusions  on  the  impact  of 

68  Again,  heteroskedasticity  was  present  in  this  model,  so  we  chose  to  focus  on  the 
results of the Hansen tests, as opposed to the Sargan test 

September 2014   

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

CBCR on analyst forecast accuracy, as our results do not provide any evidence linking 
the  score  for  regional  breakdown  and  forecast  accuracy.  On  this  basis,  we  may 
conclude  that  is  it  unlikely  that  CBCR  will  drive  further  improvements  in  forecast 
accuracy.  

Robustness and sensitivity tests 

We  found  a  significant  relationship  between  the  quality  of  disclosure  score  and  the 
accuracy  of  analyst’s  forecasts,  supporting  the  theory  and  the  literature.  In  reality, 
analysts are likely to consider a much wider range of materials and sources than just 
annual statements released by the firm itself. Further, forecasts are also susceptible to 
market  shocks  and  general  economic  trends.  As  our  results  suggest,  analysts  will 
place  more  weight  on  disclosures  the  more  transparent  and  credible  a  bank’s 
corporate governance structure is revealed to be. Similarly, information on the firm’s 
market  share  in  each  business  segment  and  shareholder  returns  also  provide 
additional  valuable  information  to  analysts.  It  is  the  lag  of  accuracy  which  has  the 
largest impact, of the significant variables, on the current period’s accuracy, which is 
also  intuitive  as  this  variable  captures  the  intrinsic  abilities  of  analysts  and  how 
successfully they have understood the underlying potential of that individual bank. 

We  also  tested  for  the  exclusion  of  the  IFRS  dummy  in  our  model  specification.  This 
did  not  alter  the  significance  of  the  coefficients  of  the  total  disclosure  score  variable 
and the corporate governance score variable.  

We also included a dummy equal to 1 if the bank is headquartered in an EU or EFTA 
country  to  test  whether  non-EU/EFTA  banks  are  affecting  the  significance  of  the 
results. The coefficient for this dummy did not appear to be statistically significant in 
our  specification,  which  suggests  that  non-EU/EFTA  banks  are  not  affecting  the 
statistical  significance  of  the  results.  The  system  GMM  approach  also  takes  into 
account  banks’  fixed  effects,  which  also  includes  the  countries  in  which  they  are 
headquartered. 

We  also  tested  the  inclusion  of  year  dummies  in  our  model,  specifically  for  2008,  in 
order to take into account the potential impacts of the financial crisis that could have 
impacted forecast accuracy. However, the 2008 indicator variable was insignificant in 
this  specification,  which  ultimately  led  to  its  exclusion  in  our  final  specification.  This 
might be explained by the fact that analysts had already anticipated the impacts of the 
crisis, and adjusted their earnings expectations accordingly. 

September 2014   

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 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Table 16: Results for the impact of disclosure quality on analysts’ earnings forecast accuracy using individual disclosure scoring 
components 

Forecast Accuracy 

Corporate Governance 
score 

Risk management 
score 

Non-Financials 
score 

Targets 
Score 

Market Share 
score 

Shareholders Return 
score 

Lag of Earnings Accuracy 

Corporate 
score 

governance 

Risk management score 

Non-financials score 

Targets score 

Market share score 

Shareholder returns score 

Unexpected Earnings 

Negative Earnings 

Loss Earnings 

Earnings Volatility 

Earnings Predictability 

Days 

0.2931*** 
(0.001) 

0.024** 
(0.042) 

0.1469 
(0.36) 

0.0275 
(0.236) 

-0.0981** 
(0.023) 

0.0048 
(0.639) 

0.0444 
(0.233) 

-0.0016 
(0.125) 

Log 
of 
capitalisation 

market 

0.0791** 
(0.045) 

September 2014   

72 

0.2846*** 
(0.005) 

0.2881*** 
(0.01) 

0.2915*** 
(0.002) 

0.2894*** 
(0.002) 

0.2624*** 
(0.002) 

0.0021 
(0.781) 

0.1341 
(0.453) 

0.0183 
(0.417) 

-0.0698** 
(0.043) 

0.0111 
(0.389) 

0.0365 
(0.295) 

-0.0015 
(0.22) 

0.0956** 
(0.026) 

0.0128** 
(0.017) 

0.1512 
(0.451) 

0.0248 
(0.286) 

-0.0617 
(0.163) 

0.0115 
(0.386) 

0.0203 
(0.644) 

-0.0016 
(0.189) 

0.1115** 
(0.034) 

0.0097 
(0.206) 

0.1517 
(0.387) 

0.0195 
(0.371) 

-0.061* 
(0.087) 

0.0101 
(0.435) 

0.0243 
(0.44) 

-0.0024** 
(0.043) 

0.1082** 
(0.029) 

-0.0118 
(0.593) 

0.1515 
(0.362) 

0.0208 
(0.364) 

-0.0747* 
(0.076) 

0.0059 
(0.642) 

0.0167 
(0.599) 

-0.0021* 
(0.092) 

0.0914* 
(0.078) 

-0.0195 
(0.306) 

0.1346 
(0.435) 

0.0252 
(0.281) 

-0.0669* 
(0.061) 

0.0098 
(0.462) 

0.0447 
(0.178) 

-0.002 
(0.108) 

0.116** 
(0.019) 

 
 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Forecast Accuracy 

Corporate Governance 
score 

Risk management 
score 

Non-Financials 
score 

Market Share 
score 

Shareholders Return 
score 

IFRS dummy 

Constant 

Firm-year 

# of instruments 

F-stat 

Sargan p-value 

Hansen p-value 

AR(1) test p-value 

AR(2) test p-value 

-0.0981* 
(0.085) 

-0.369 
(0.507) 

375 

51 

  33.24 

0.372 

0.592 

0.110 

0.107 

-0.0843 
(0.201) 

-0.4596 
(0.447) 

375 

51 

-0.1186** 
(0.045) 

-0.6538 
(0.36) 

375 

61 

Targets 
Score 

-0.0888 
(0.116) 

-0.2403 
(0.679) 

375 

51 

-0.0583 
(0.4) 

-0.1298 
(0.866) 

375 

51 

  33.17 

  31.67 

  32.59 

  32.26 

0.330 

0.859 

0.110 

0.157 

0.478 

1.000 

0.104 

0.123 

0.358 

0.806 

0.101 

0.153 

0.284 

0.775 

0.107 

0.150 

-0.0727 
(0.236) 

-0.3835 
(0.542) 

375 

51 

  28.79 

0.000 

0.460 

0.098 

0.161 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis 

September 2014   

73 

 
 
 
 
 
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Impact of disclosure quality on earnings management 

Section summary 

We  hypothesise  that  increased  disclosure  scores  reduce  the  likelihood  of  managing 
earnings as they reduce the possibility of using accounting mechanisms to manipulate 
earnings.  

We  use  a  logistic  model  to  estimate  the  relationship  between  disclosure  quality  and 
the likelihood of earnings management, due to the binary form the dependent variable 
takes.  

Our  results  suggest  that  an  increase  in  the  disclosure  score  of  1  decreases  the 
probability  of  managing  earnings  by  3.5%  on  average  for  our  sample  of  banks.  The 
drivers  behind  this  seem  to  be  regional  breakdown  scores  and  corporate  governance 
scores.  

Modelling approach 

One of the measures used for earnings management in the literature is management 
application  of  accounting  discretion  to  present  small,  positive  earnings  in  financial 
reporting  to  avoid  reporting  negative  ones.  The  presence  of  such  ‘small’  positive 
earnings  is  considered  to  be  indicative  of  the  presence  of  earnings  management.  In 
our  study,  we  use  a  dummy  variable  (Positive  Earnings)  which  equals  one  if  net 
income  scaled  by  total  assets  is  between  0  and  0.01.69  This  is  underpinned  by 
empirical research that is established in the literature, namely Burgstahler and Dichev 
(1997),  which  show  that  firms  with  the  ratio  net  income  to  total  assets  lying  within 
this interval are statistically more likely to be engaging in earnings management.70 

This  concept  of  earnings  management  has  also  been  used  in  Leuz  (2003),  which 
investigated  the  relationship  between  investor  protection  and  earnings  management. 
Lang, Raedy and Yetman (2002), use the same measure of earnings management to 
investigate  the  impact  of  accounting  differences  between  firms  cross-listing  on  US 
exchanges, along with the previously mentioned Chen et al. (2010), Christensen et al. 
(2008) and Barth et al. (2007).  

Because  the  dependent  variable,  Positive  Earnings,  is  a  dummy  variable,  a  logistic 
regression  is  used  to  model  the  relationship  between  disclosure  quality  and  earnings 
management. A logistic regression estimates the probability of an event occurring, in 
this case the probability of Positive Earnings, taking the value of one. We can interpret 
the  coefficients  given  in  a  logistic  regression  as  the  log  of  the  odds  ratio.71  Thus  the 

69 0.01 is the upper limit that indicates the presence of small, positive earnings. 
70  Based  on  an  analysis  of  firms’  distribution  of  earnings,  Burgstahler  and  Dichev 
(1997)  analyse  the  statistical  distribution  of  earnings  scaled  by  assets  and  find  that 
earnings  slightly  less  than  zero  occur  much  less  frequently  than  would  be  expected 
given the smoothness of the remainder of the distribution, and earnings slightly more 
than  zero  occurs  much  more  frequently  than  expected.  This  irregularity  near  zero  is 
statistically significant, specifically in the interval between 0 and 0.01. 
71 The odds ratio, or the probability of a “success” outcome (in this context, where the 
dependent variable is 1, indicating the presence of earnings management) divided by 
the  probability  of  a  “failure”  outcome  (where  the  dependent  variable  is  0,  indicating 
the absence of earnings management).  

September 2014   

74 

 
 
 
 
 
 
                                          
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

exponential  function  of  the  regression  coefficient  is  the  odds  ratio  associated  with  a 
one-unit increase in disclosure quality.  

We use a random effects approach in our logistic model. Unlike the fixed effects (FE) 
approach  it  assumes  that  the  individual-specific  effect  is  correlated  with  independent 
variables,  the  random  effects  (RE)  approach  assumes  that  individual-specific  effects 
are  uncorrelated  with  independent  variables.72  Under  the  RE  approach,  rather  than 
thinking  of  each  unit  as  having  its  own  systematic  baseline  (as  in  under  FE),  the 
intercept is the result of a random deviation from some mean intercept. We employed 
the  RE  approach  as  we  have  reason  to  believe  that  differences  across  entities  have 
some influence on the dependent variable in our model. In order to test whether an FE 
or RE model is appropriate in this context, we use the Hausman test which compares 
the two models with a null hypothesis that the random effects model is preferred. We 
consistently get a p-value greater than 0.05, which suggests that the random effects 
model is preferred to fixed effects.  

As  we  are  using  RE  we  need  to  control  for  the  time-invariant  heterogeneity  across 
banks’  countries  of  headquarters,  hence  the  use  of  country  dummies  in  our  model. 
This  heterogeneity  includes  specific  domestic  regulatory  policies,  legal  systems,  as 
well  as  institutional  structures  and  socio-economic  environments,  which  can  also 
influence  the  likelihood  of  earnings  management  (Leuz  et  al.,  2003;  and  Burgstahler 
et al., 2006). 

Our  specification  is  based  on  Chen,  Tang  and  Jiang  (2010),  which  uses  Positive 
Earnings  as  the  dependent  variable,  which  equals  one  if  net  income  scaled  by  total 
assets is between 0 and 0.01. In our specification we also include  a dummy variable 
IFRS for IFRS adoption, and other controls for log of sales, growth, leverage and other 
variables  which  have  been  shown  to  influence  the  likelihood  of  managing  earnings 
towards target (Lang et al., 2003, 2006; Christensen, 2008; Barth et al., 2008; Chen 
et al., 2010). Table 17 sets out the variables used in more detail. 

(4) 

72 A fixed-effects analysis can only support inference about the sample upon which we 
conduct  the  analysis,  whereas  a  random-effects  analysis  allows  the  inference  of  the 
population from which the sample was drawn. 

September 2014   

75 

 
 
 
 
 
 
                                          
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Table 17: List of variables used for econometric analysis 

Variable 

Expected 
Relationship 

Description 

Positive 
Earningsit 

Disclosure 
Scoreit 

Log of salesit

Sales growthit 

Stock growthit 

Leverageit 

Liabilities 
growthit 

Sales/assetsit 

Cash 
operationsit 

flow 

No. 
exchangesit 

of 

US listingit 

Close Sharesit 

IFRSit 

- 

- 

- 

- 

+ 

+ 

- 

- 

- 

- 

- 

- 

A  binary  variable  equal  to  one  if  the  annual  net 
income scaled by lagged total assets is between 0 and 
0.01 for company i at time t 

Disclosure  score,  out  of  75,  using  PwC  disclosure 
quality scoring index for company i at time t 

Natural  log  of  sales  in  millions  of  US  dollars  for 
company i at time t 

Annual  percentage  change  in  sales  for  company  i at 
time t 

Annual  percentage  change  in  common  stock  for 
company i at time t 

End  of  year  total  liabilities  divided  by  total  assets  for 
company i at time t 

Annual  percentage  change  in  total  liabilities  for 
company i at time t 

Sales divided by lagged total assets for company i at 
time t 

Annual  net  cash  flow  from  operations  scaled  by 
lagged total assets for company i at time t 

Number of exchanges on which a firm’s stock is listed 
for company i at time t 

A binary variable equal to one if the bank is also listed 
on any US stock exchange for company i at time t 

Percentage  of  closely  held  shares  of  firm  as  reported 
by Worldscope for company i at time t 

A  binary  variable  equal  to  1  if  the  bank  used  IFRS 
accounting  standards  at  time  t  or  equal  to  0  if 
otherwise for company i at time t 

Log of sales is expected to be negatively related to Positive Earnings, as larger firms 
are  expected  to  manage  earnings  towards  a  small  positive  target  to  a  lesser  extent. 
This could be due to the fact that larger firms are placed under more scrutiny, not only 
from  shareholders,  but  also  regulators  and  are  subject  to  more  rigorous  auditing 
processes. The credibility of larger firms – which are often more well-known – is also 
at  stake,  so  there  are  larger  costs  involved  with  manipulating  earnings  (Lemma, 
Negash  and  Mlilo,  2013).  Similarly,  stock  growth  has  a  negative  relationship  with 

September 2014   

76 

 
 
 
 
 
 
 
 
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Positive  Earnings,  as  firms  with  greater common  stock  are  more  liquid  and  therefore 
have less incentive to manage earnings (Fang, 2012). Similarly, cash flow operations 
and  turnover  follow  the  same  relationship  and  can  be  seen  as  proxies  of  size  and 
liquidity.  

Sales growth and Positive Earnings are also negatively associated, as firms with slow 
growth are more likely to manage earnings. Leverage on the other hand has a positive 
relationship  with  Positive  Earnings.  Although  having  greater  leverage  can  increase 
potential  returns,  it  also  raises  the  possibility  of  disproportionate  losses.  As  such, 
banks with greater leverage could be perceived as riskier, and may be more likely to 
manage earnings as they face losses. This is similar for liabilities growth, as firms with 
greater liabilities have a greater incentive to manage earnings.  

We expect the coefficient for US listing to be negative. This is because firms that are 
listed on any US stock exchange are subject to the US GAAP and the SEC’s disclosure 
rules, which tend to be relatively more stringent than for firms headquartered in other 
countries contained within our sample. Thus firms listed  on a US stock exchange are 
likely  to  have  fewer  opportunities  to  manipulate  their  negative  earnings  into  small 
positive ones (Lang, Raedy and Yetman, 2002). 

A  firm  with  more  closely  held  shares  –  has  more  shares  held  by  affiliates  of  the 
company  or  its  management  –  is  considered  to  be  less  likely  to  manage  earnings. 
Firms with more shares held by the company have less external shareholder pressure 
to meet earnings targets, so could have less of an incentive to manage earnings.  

Our  regression  approach  also  accounts  for  the  presence  of  country  fixed  effects  by 
including  country  dummies,  which  take  into  account  country-specific  characteristics 
that are time-invariant, e.g. legal institutions affecting firms headquartered in different 
countries. We also include a dummy for IFRS adoption, which was made mandatory in 
the  EU  in  2005,  but  had  been  gradually  adopted  by  some  banks  prior  to  this  date. 
IFRS  adoption  is  likely  to  reduce  the  likelihood  of  earnings  management  due  to  the 
decline  in  areas  where  managers  could  exercise  discretion,  thereby  reducing  the 
likelihood of small, positive earnings being present.  

We  note  that  national  accounting  standards  such  as  local  Generally  Accepted 
Accounting  Principles  (GAAP)  have  been  on  a  long-term  pattern  of  convergence 
towards  IFRS  to  smooth  out  the marginal  costs  of  compliance  in  anticipation  of  IFRS 
adoption  in  the  EU,  which  limits  the  explanatory  powers  of  IFRS,  and  there  is  some 
variation  across  countries  on  the  scope  of  IFRS  adoption,  which  provides  further 
support  for the  use  of country  dummies  to  control  for  these  effects.  We  do  not  have 
prior expectations over the signs of individual country dummies, as different legal and 
institutional  environments  could  cause  different  incentives  and  attitudes  towards 
earnings management.  

September 2014   

77 

 
 
 
 
 
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Data and summary statistics 

Table  18  presents  the  key  summary  statistics  of  the  main  variables  that  are  used  in 
the  regression.  The  leverage  variable  is  the  most  volatile  of  the  variables,  as  can  be 
seen  from  the  wide  minimum  and  maximum  differential.  Companies  in  the  banking 
industry  naturally  operate  with  a  higher  leverage  as  their  assets  are  easily 
collateralized. The big variation in leverage is not unusual given the different economic 
climates and countries included in this analysis.  

Table 18: Summary statistics of earnings management regression 

Positive Earnings 

Disclosure Score 

Log of sales 

Sales growth 

Stock growth 

Leverage 

Mean  Median Minimum Maximum

0.604 

1.000 

0.000 

41.558  42.000 

15.000 

17.168  17.263 

13.680 

0.119 

0.087 

-0.555 

1.000 

70.000 

18.929 

2.842 

Standard 
Deviation 
0.490 

9.152 

0.994 

0.289 

5.501 

0.047 

-0.999 

3158.714 

129.077 

7.217 

6.203 

-93.577 

99.737 

Liabilities growth 

0.156 

0.127 

-0.453 

0.069 
Sales/assets 
Cash flow operations  0.009 
3.639 
No. of exchanges 

0.061 

0.011 

4.000 

US listing 

Close Shares 

IFRS 
Source: PwC analysis 

0.574 

1.000 

0.278 

0.223 

0.568 

1.000 

0.017 

-0.265 

0.000 

0.000 

0.000 

0.000 

5.971 

0.298 

0.136 

12.000 

1.000 

0.969 

1.000 

8.091 

0.341 

0.038 

0.031 

2.430 

0.495 

0.261 

0.496 

Table 19 shows the correlation matrix for the variables in our specification. It provides 
little  evidence  of  multi-collinearity,  with  the  majority  of  the  correlation  coefficients 
lying between -0.3 and 0.3. This means that the variables can be used together in the 
model specification. 

The  correlation  between  Positive  Earnings  and  disclosure  score  suggests  a  positive 
relationship,  which  runs  counter  to  our  expectations  that  disclosure  quality  should 
reduce  the  likelihood  of  earnings  management.  As  expected,  we  observe  a  negative 
relationship  with  sales  growth,  stock  growth,  Sales/assets,  cash  flow  operations  and 
Close shares. For the variables log of sales, leverage, number of stock exchanges and 
US stock exchanges we find a correlation opposite to what we would normally expect. 
There appears to be moderate correlation between the number of exchanges and log 
of  sales,  which  is  perhaps  unsurprising  as  larger  firms  with  larger  sales  values  are 
more likely to have multiple listings globally.  

September 2014   

78 

 
 
 
 
 
  
 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Table 19: Correlation matrix between the variables in the earnings management regression 

Positive 
Earnings 

Disclosure 
score 

Log of 
sales 

Sales 
growth

Stock 
growth

Leverage

Liabilities 
growth 

Sales/ 
assets 

Cash flow 
Operations 

No. of 
exchanges

US 
listing 

Close 
Shares

IFRS 

Positive 
Earnings 

Disclosure 
Score 

1.000 

- 

0.150 

1.000 

- 

- 

Log of sales 

0.019 

0.206 

1.000 

- 

- 

- 

-0.118 

-0.158 

-0.033 

1.000 

-0.055 

0.009 

0.034 

0.035 

1.000 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

Leverage 

0.179 

0.109 

0.040 

0.020 

-0.022 

1.000 

Liabilities 
growth 

-0.124 

-0.142 

-0.086 

0.435 

0.040 

0.002 

1.000 

Sales/assets

-0.296 

-0.310 

0.041 

0.429 

0.030 

0.024 

0.434 

1.000 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

-0.015 

-0.071 

-0.016 

0.122 

-0.022 

-0.121 

-0.053 

0.141 

1.000 

Sales 
growth 

Stock 
growth 

Cash flow 
operations 

No. of 
exchanges 

- 

- 

- 

- 

- 

- 

- 

- 

- 

0.290 

0.230 

0.484 

-0.111 

0.002 

0.165 

-0.095 

-0.107 

0.005 

1.000 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

US listing 

0.227 

0.042 

0.310 

-0.208 

0.033 

0.065 

-0.111 

-0.202 

-0.033 

0.576 

1.000 

Close Shares

-0.254 

-0.061 

-0.168 

0.075 

0.014 

-0.033 

0.092 

0.074 

-0.037 

-0.343 

-0.249 

1.000 

IFRS 

0.001 

0.371 

-0.023 

0.065 

-0.062 

0.069 

0.007 

-0.267 

-0.009 

-0.009 

-0.121 

0.115 

1.000 

Source: PwC analysis 

September 2014   

79 

 
 
 
 
 
 
 
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

Results 

Based  on  our  preferred  model  specification  which  was  drawn  from  our  literature 
review, our econometric results show that: 

• 

• 

Increasing the disclosure quality score reduces the likelihood of earnings 
management. 
Corporate governance and regional breakdown disclosures underpin the 
relationship between disclosure quality and earnings management. 

Table  20  shows  the  results  for  the  random  effects  logistic  regression,  which  also 
controls for country fixed effects through the use of country dummies. 

Table 20: Results for the impact of disclosure quality on earnings management using 
disclosure score 

Positive Earnings 

Total disclosure Score 

Regional Breakdown score 

Coefficient 

Odds ratio 

Coefficient 

Odds ratio 

Total disclosure score 

-0.0353* 
(0.087) 

0.9653* 
(0.087) 

-  

 - 

Regional breakdown score 

 - 

-  

Log of sales 

Sales growth 

Stock growth 

Leverage 

Liabilities growth 

Sales/assets 

Cash flow operations 

No. of exchanges 

US listing 

Close shares 

IFRS dummy 

Constant 

Number of obs 

Country fixed-effects 

Wald chi2(27) 

Prob > chi2 

0.1211 
(0.527) 

1.2289** 
(0.032) 

-0.3135 
(0.246) 

0.0201 
(0.22) 

0.4056 
(0.456) 

-31.6411*** 
(0.000) 

4.8487 
(0.277) 

0.0102 
(0.921) 

-0.188 
(0.693) 

-2.324*** 
(0.000) 

-1.0484** 
(0.022) 

1.8907 
(0.558) 

503 

Yes 

92.02 

0 

1.1288 
(0.527) 

3.4175** 
(0.032) 

0.7309 
(0.246) 

1.0203 
(0.22) 

1.5002 
(0.456) 

0*** 
(0.000) 

127.5806 
(0.277) 

1.0103 
(0.921) 

0.8286 
(0.693) 

0.0979*** 
(0.000) 

0.3505** 
(0.022) 

6.6241 
(0.558) 

503 

Yes 

92.02 

0 

-0.3148* 
(0.069) 

0.0211 
(0.907) 

1.2183** 
(0.031) 

-0.2794 
(0.301) 

0.0203 
(0.231) 

0.4029 
(0.45) 

-29.661*** 
(0.000) 

5.4815 
(0.228) 

0.0686 
(0.527) 

-0.2557 
(0.6) 

-2.6298*** 
(0.000) 

-1.0251** 
(0.027) 

2.7052 
(0.404) 

503 

Yes 

88.71 

0 

0.7299* 
(0.069) 

1.0213 
(0.907) 

3.3814** 
(0.031) 

0.7562 
(0.301) 

1.0205 
(0.231) 

1.4961 
(0.45) 

0*** 
(0.000) 

240.2022 
(0.228) 

1.071 
(0.527) 

0.7743 
(0.6) 

0.0721*** 
(0.000) 

0.3588** 
(0.027) 

14.958 
(0.404) 

503 

Yes 

88.71 

0 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis 

September 2014   

80 

 
 
 
 
 
 
 
  
 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

These coefficients need careful interpretation due to the nature of the logistic model.73 
We can interpret the signs on the coefficients to mean an increase (+) or decrease (-) 
in the likelihood of earnings management. We observe an increase in disclosure score 
is  associated  with  a  decrease  in  the  likelihood  of  earnings  management;  and  this  is 
significant at 10%.  

The  magnitude  of  the  coefficients  is  not  particularly  meaningful  in  its  original  form. 
The  transformation  of  these  values  into  odds  ratios  provides  for  a  more  intuitive 
interpretation.  As  explained  before,  the  exponential  of  the  coefficient  needs  to  be 
taken in order to transform the values into odds ratios. The odds ratio represents the 
relative  odds  that  earnings  management  is  present,  i.e.  Positive  Earnings  equal  to 
one. The odds ratio of 0.97 for total disclosure score means that a one unit increase in 
disclosure score will mean banks are 0.97 times as likely to manage earnings, or 3% 
(1-0.97=3%) less likely to manage earnings on average for our sample of banks. The 
Close shares variable is significant at 1% level and as predicted has a negative impact 
on  earnings  management,  with  a  1%  increase  in  Close  shares  causing  a  0.9% 
decrease in likelihood of managing earnings. The IFRS dummy is significant at the 5% 
level  and  negative,  confirming  previous  results  that  show  IFRS  adoption  reduces  the 
likelihood  of  earnings  management.  The  adoption  of  IFRS  by  banks  reduces  the 
likelihood of banks managing earnings in our sample by 65%. The coefficient of sales 
growth,  which  is  significant  at  the  5%  level,  suggests  that  a  1  percentage  point 
increase in the growth of sales increases the likelihood of managing earnings by 2.4%. 

The  coefficient  on  sales/assets  is  negative  and  significant  at  the  1%  level,  which 
confirms  our  expectations  that  bigger  firms  are  less  likely  to  manage  earnings. 
However,  when  converted  into  odds  ratios,  a  1  unit  change  in  the  sales/assets  ratio 
almost eliminates the likelihood of earnings management (almost 100%, or 1-0), i.e. 
it has a very big effect. Although this is a correct interpretation of the results, it is a 
misleading  one.  This  is  mainly  because  of  the  scaling  effect,  therefore  for  variables 
with  very  small  values  (such  as  ratios  with  a  mean  smaller  than  1),  a  1  unit  change 
can  have  extremely  large  impacts.  The  sales/assets  variable  is  the  ratio  of  sales  to 
assets.  For  banks  in  particular,  which  have  large  amounts  of  assets,  this  variable 
tends to be fairly small, with a mean of 0.0996. Therefore a 1 unit change is unlikely 
to  occur  and  is  less  meaningful  for  interpretation.  We  can  get  a  more  meaningful 
interpretation  of  the  odds  ratio  by  scaling  down  the  unit  increase  to  0.01,  which 
results  in  a  change  in  the  likelihood  of  earnings  management  of  1%.  Similarly,  the 
mean  value  for  cash  flow  operations  is  0.01, which  means  an  increase  of  0.001  may 
be more intuitive, i.e. a 0.001 unit increase in the ratio of cash flow scaled by assets 
increases  the  likelihood  of  earnings  management  by  12.7%,  although  this  impact  is 
insignificant.  

Breaking  down  the  disclosure  scores  into  its  individual  components  enables  us  to 
understand  the  main  drivers  of  the  effect  of  total  disclosure  score  on  earnings 
management.  Specifically,  the  regional  breakdown  score  is  significant  at  the  10% 
level.  This  may  be  because  the  disclosure  of  more  granular  data  makes  it  harder  to 
mask  small  negative  earnings.  Increasing  regional  breakdown  scores  by  one  reduces 
the likelihood of managing earnings by 27%.  

The  coefficient  on  the  corporate  governance  disclosure  score  appears  to  be  negative 
and the most statistically significant, i.e. at the 1% level. This could be due to the fact 
that more transparent disclosures over corporate governance disclosures reflect better 
monitoring and management accountability, which reduces the incentive for managers 
to manage earnings. Improving the corporate governance disclosure score by one unit 

73 As explained in the methodology, we cannot interpret the coefficients of the logistic 
model  as  an  increase  in  the  value  of  the  dependent  variable  given  a  single  unit 
increase in the explanatory variable 

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 General  assessment  of  potential  economic  consequences  of  country-by-country  reporting  under 
CRD IV 

reduces  the  likelihood  of  managing  earnings  by  23%.  None  of  the  other  individual 
disclosure  areas  have  a  statistically  significant  relationship  with  the  likelihood  of 
earnings management. 

We conclude that increasing the disclosure quality results in a significant reduction in 
the  likelihood  of  earnings  management,  providing  empirical  support  for  our 
hypotheses.  This  appears  to  be  driven  by  regional  breakdown  and  corporate 
governance  disclosures.  The  disclosure  requirement  under  CBCR  is  most  closely 
captured  by  the  regional  breakdown  component  of  our  scoring  index.  Therefore  the 
implication  for  CBCR  is  that  if  CBCR  leads  to  an  increase  in  the  granularity  of 
disclosure, it could lead to a statistically significant improvement in accounting quality 
and  in  the  credibility  of  financial  results  by  reducing  the  likelihood  earnings 
management.  However,  as  banks  have  already  reported  segmental  information,  it  is 
uncertain  whether  incremental  disclosures  at  the  country  level  as  required  by  CBCR 
will have similarly significant effects. 

Robustness and sensitivity tests 

As  previously  explained,  we  use  the  RE  approach  rather  than  FE  in  our  logistic 
regression  on  the  basis  of  the  Hausman  test,  which  suggests  that  the  RE  model  is 
preferred.  

To  make  sure  the  standard  errors  are  robust  to  the  relatively  small  sample  log  of 
sales, we used the “vce (bootstrap)” option offered in Stata. We also conduct a formal 
test of specification to ensure that our model is correctly specified. The likelihood ratio 
test  can  be  used  to  see  if  the  inclusion  of  an  explanatory  variable  in  a  model  has 
greater explanatory power over the outcome variable than a model without it. To test 
the significance of country dummies in the regression we carried out a likelihood ratio 
test  which  compares  a  restricted  model  (without  country  dummies)  and  the 
unrestricted model (including country dummies). The null hypothesis is that the joint 
significance  of  the  coefficients  of  the  country  dummies  is  equal  to  zero.  A  p-value  of 
less than 0.05 suggests that the joint significance of the coefficients of the additional 
explanatory  variables  (in  this  case,  the  country  dummies)  is  significantly  different 
from zero. The p-value for this test was 0.000, so we reject the null meaning that the 
country dummies have significant explanatory power over the dependent variable. On 
this  basis,  we  included  the  country  dummies  in  our  specification,  which  controls  for 
country-specific characteristics. 

We also applied the likelihood ratio test to test whether to include the IFRS dummy in 
our specification. The p-value of this test is 0.0176, i.e. the null hypothesis is rejected 
at  the  5%  level,  and  therefore  the  coefficient  on  IFRS  is  significantly  different  from 
zero. On this basis, we included the IFRS dummy in our model specification. However, 
excluding the IFRS dummy does not change the significance of the coefficients on the 
disclosure quality scores. 

We  also  considered  the  use  of  year  dummies  in  our  specification  to  control  for  time-
specific factors, e.g. poor performance across the industry under weak macroeconomic 
conditions  in  certain  years  could  have  had  an  influence  on  the  likelihood  of  earnings 
management.  In  order  to  test  whether  the  year  dummies  should  be  added  in  our 
specification, we carried out a likelihood ratio test to compare the performance of the 
restricted  model  (no  year  dummies)  against  the  unrestricted  model  (with  time 
dummies).  We  fail  to  reject  the  null  hypothesis  which  indicates  that  the  joint 
significance of the coefficients of the year dummies are not significantly different from 
zero. We therefore excluded the dummies on this basis.  

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Table 21: Results for the impact of disclosure quality on earnings management using individual disclosure scoring components 

Earnings Management 

Corporate Governance 
score 

Risk management 
score 

Non-Financials 
score 

Targets 
Score 

Market Share 
score 

Shareholders 
Return score 

Corporate governance score 

Risk management score 

Non-financials score 

Targets score 

Market share score 

Shareholder returns score 

Log of sales 

Sales growth 

Stock growth 

Leverage 

Liabilities growth 

Sales/assets 

Cash flow operations 

No. of exchanges 

US listing 

Close shares 

-0.2639*** 
(0.008) 

0.1143 
(0.527) 

1.2747** 
(0.024) 

-0.3085 
(0.262) 

0.0225 
(0.175) 

0.2585 
(0.654) 

0.0127 
(0.792) 

-0.0256 
(0.892) 

1.214** 
(0.029) 

-0.2677 
(0.32) 

0.0217 
(0.204) 

0.3921 
(0.456) 

-0.0777 
(0.111) 

0.067 
(0.712) 

1.2145** 
(0.032) 

-0.2987 
(0.26) 

0.0184 
(0.243) 

0.3834 
(0.471) 

-0.0581 
(0.505) 

-0.0027 
(0.988) 

1.224** 
(0.028) 

-0.2712 
(0.313) 

0.0218 
(0.203) 

0.3846 
(0.471) 

0.0221 
(0.876) 

-0.0145 
(0.936) 

1.216** 
(0.029) 

-0.268 
(0.321) 

0.0222 
(0.205) 

0.398 
(0.45) 

-0.0686 
(0.591) 

0.0084 
(0.964) 

1.2114** 
(0.031) 

-0.2843 
(0.293) 

0.0221 
(0.207) 

0.4078 
(0.439) 

-30.436*** 
(0.000) 

-28.374*** 
(0.001) 

-29.5019*** 
(0.000) 

-29.5854***
(0.000) 

-28.8274*** 
(0.000) 

-29.1991*** 
(0.000) 

5.3104 
(0.247) 

-0.01 
(0.923) 

-0.1525 
(0.745) 

4.9211 
(0.274) 

0.0172 
(0.867) 

-0.207 
(0.665) 

4.7952 
(0.286) 

-0.01 
(0.922) 

-0.1384 
(0.769) 

4.8389 
(0.279) 

0.0191 
(0.852) 

-0.2078 
(0.662) 

4.9358 
(0.272) 

0.019 
(0.853) 

-0.2031 
(0.672) 

5.0033 
(0.267) 

0.0185 
(0.858) 

-0.2309 
(0.634) 

-2.3191*** 
(0.000) 

-2.2487*** 
(0.000) 

-2.3945*** 
(0.000) 

-2.1423***
(0.001) 

-2.2216*** 
(0.001) 

-2.2951*** 
(0.000) 

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 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Earnings Management 

Corporate Governance 
score 

Risk management 
score 

Non-Financials 
score 

Targets 
Score 

Market Share 
score 

Shareholders 
Return score 

IFRS dummy 

Constant 

Number of obs 

Country fixed-effects 

Wald chi2(27) 

Prob > chi2 

-1.0012** 
(0.028) 

-1.1693*** 
(0.01) 

-1.0676** 
(0.018) 

-1.1257** 
(0.013) 

-1.1555** 
(0.012) 

-1.1508** 
(0.011) 

2.407 
(0.449) 

503 

Yes 

95.39 

0 

2.7083 
(0.404) 

503 

Yes 

89.48 

0 

1.9291 
(0.548) 

503 

Yes 

93.07 

0 

2.7047 
(0.4) 

503 

Yes 

91.32 

0 

2.6329 
(0.415) 

503 

Yes 

89.28 

0 

2.4661 
(0.449) 

503 

Yes 

88.72 

0 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis

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under CRD IV 

Summary and conclusions 
The  results  from  our  analysis  provide  some  evidence  that  disclosure  quality  has  a 
positive  impact  on  capital  market  outcomes  (by  lowering  a  firm’s  effective  cost  of 
equity  capital),  improves  transparency  (by  improving  the  accuracy  of  analysts’ 
forecasts)  and  reduces  the  likelihood  of  earnings  management,  thereby  improving 
accounting  quality.  There  is  also  some  evidence  to  suggest  that  the  public 
availability and granularity of financial information reduces a firm’s effective cost of 
equity  capital,  which  provides  support  for  CBCR  to  lead  to  beneficial  outcomes  for 
banks. However, it should be noted that the magnitude of the potential impacts are 
likely to be small. 

These impacts could affect the wider economy through the following channels: 

• 

• 

• 

• 

Competitiveness: The evidence from our econometric analysis suggests that 
an improvement in disclosure quality, which is a key objective of CBCR, is 
associated with a reduction in earnings management by reducing the ability of 
firms to mask their true performance, which could have small but positive 
impacts on firms’ competitiveness. Although we have not captured the 
impacts on competitiveness directly, our review of the literature suggests that 
greater openness could enable banks to become more competitive and our 
results suggest that CBCR is unlikely to lead to adverse effects on 
competition.  

Credit availability: Our econometric results suggest that CBCR is unlikely to 
have any negative impact on banks’ ability to access capital markets. The 
improvement in disclosure quality as perceived by capital markets as a result 
of CBCR could have a small impact on reducing banks’ cost of equity capital, 
and these benefits could be passed on to non-financial sector firms and 
households in the form of lower lending rates. 

Investment: Related to the point on credit availability, our econometric 
results suggest that CBCR is unlikely to have a negative impact on 
investment. The improvement in disclosure quality as perceived by capital 
markets as a result of CBCR could lead to a lower cost of equity capital for 
banks, which may translate into lower lending rates and enable firms to invest 
in their business and expand. However, these impacts are likely to be small. 

Stability of the financial system: The evidence from our econometric 
analysis suggests that an increase in disclosure quality, which is a key 
objective of CBCR, could have a small but positive impact on accounting 
quality. This means that following the implementation of CBCR, the 
information provided by banks could become more informative for external 
stakeholders, and better reflects the true economic condition of the bank. This 
could result in lower volatility and increased financial stability. 

Overall, our analysis suggests that CBCR could have small but positive impacts on 
banks’  outcomes  and  is  unlikely  to  have  negative  effects  on  capital  market 
outcomes, transparency and accounting quality. 

However,  as  CBCR  is  yet  to  be  implemented,  we  do  not  as  yet,  have  the 
opportunity to conduct an ex-post “event study”, i.e. a study where we are able to 
compare  the  differences  in  outcomes  between  the  pre-  and  post-implementation 
period  to  understand  the  impacts  of  introducing  the  disclosure  requirement. 
Therefore,  we  necessarily  need  to  infer  from  the  historical  relationships  between 
disclosure  quality  and  the  outcomes  of  interest  to  draw  possible  conclusions  for 
CBCR.  It  is  therefore  important  to  be  cautious  when  interpreting  the  results  and 

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under CRD IV 

conclusions from our study and their applicability to CBCR, for the reasons outlined 
below. 

First, although our results can be a useful proxy for what might happen with CBCR, 
the differences between the incentives that have driven current reporting practices 
and behavioural changes likely to be induced by CBCR need to be considered when 
interpreting  these  results.  Following  the  implementation  of  CBCR,  firms  will  be 
required to report certain key metrics, which have hitherto been largely provided on 
a  voluntary  basis.  Voluntary  disclosures  and  mandatory  disclosure  regimes  can 
result  in  quite  different  impacts.  Voluntary  disclosures  are  largely  the  result  of  a 
strategic choice driven  by other factors such as management incentives and other 
signalling effects, whereas under a mandatory regime, firms have less control over 
their  disclosure  choices.  For  example,  Hail  and  Leuz  (2007)  note  that  firms  that 
adopted IFRS voluntarily or ahead of the EU requirement experience larger capital 
market benefits than those who adopted the IFRS following its mandatory adoption.  

However, it could be argued that mandatory reporting could have stronger impacts 
because  possible  spillovers  or  market-wide  impacts  are  now  internalised,  such  as 
enhancing  the  comparability  of  disclosures  and  increasing  transparency  across  the 
sector.  Therefore  it  is  unclear  how  the  magnitude  of  the  impacts  would  differ 
between voluntary and mandatory disclosure regimes with respect to CBCR. 

Second,  although  our  analysis  points  to  positive  impacts  that  could  arise  from 
CBCR, it is unclear whether this could be subject to diminishing returns. Banks are 
already subject to a high disclosure requirement relative to other sectors, and it is 
unclear  whether  the  increase  in  disclosures  will  amount  to  additional  valuable 
information for investors and the general public. The highly-regulated nature of the 
financial services sector means that banks are already providing a lot of information 
to regulators, e.g. capital and liquidity requirements, transactions reporting, MiFID 
II/EMIR, money laundering etc. The large banks which will be affected by Article 89 
rules  also  tend  to  be  heavily  covered  by  information  intermediaries  such  as 
analysts, and it is unclear how much more this new information will add to analysts’ 
existing information environment. 

Finally,  while  the  CBCR  is  likely  to  help  improve  the  comparability  of  financial 
reporting at the country-by-country level, there are several reasons why the impact 
of  such  comparability  could  be  limited.  This  is  because  different  countries  have 
different  sets  of  rules  and  interpretations  of  the  disclosure  items,  as  indicated  by 
the  results  of  our  legal  questionnaire  on  the  implementation  status  of  Article  89 
across  the  EU.  Also,  there  is  no  requirement  to  provide  granular  reporting  on 
individual  business  units  within  each  country,  which  limits  the  ability  of  investors 
and analysts to make informed comparisons across banks. 

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Section four – Stakeholder survey 

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Overview of the stakeholder survey 
While the econometric study seeks to look at some potentially measurable impacts of Article 89, 
we  recognise  that  it  has  limitations.  Because CBCR  is  yet  to  be  implemented,  the  econometrics 
relies  on  using  historical  evidence  of  earlier  improvements  in  disclosure  quality  to  infer  what 
might happen as a result of CBCR. It is difficult to make such inferences – not only is it difficult 
to  quantify  the  effects  of  CBCR  on  disclosure,  but  it  is  uncertain  whether  the  historical 
relationships  will  be  repeated  in  the  future  given  the  relatively  high  level  of  financial  reporting 
disclosure before CBCR. Furthermore, many of the potential economic consequences of Article 89 
are  either  intrinsically  difficult  to  measure,  or  could  only  reasonably  be  measured  once  the 
legislation has been in effect for some time.  

We therefore devised a questionnaire to obtain the views of stakeholders in three main areas: 

1.  Respondents were asked to rate the economic impact that they expected Article 89 to 
have  on  a  range  of  areas  as  very  positive,  positive,  no  impact,  negative  or  very 
negative. 

2.  Respondents  were  asked  to  provide  comments  on  certain  matters  of  interpretation 

relating to the Article 89 requirements. 

3.  Views were sought on the location of the CBCR disclosure and on the requirement that 

the disclosure has to be audited. 

The survey responses to part one are summarised in this section of the report and the detailed 
results  by  question  are  included  in  Appendix  2.  The  responses  to  parts  two  and  three  are 
incorporated into section 5 and into Appendix 3 which look at the issues with implementation and 
interpretation.   

We  sent  questionnaires  to  156  organisations  covering  all  the  EU  Member  States,  the  US  and 
Switzerland.  The  organisations  included  the  GSIBs,  other  reporting  institutions,  CSOs,  financial 
regulators, central banks, governments, trade associations and credit agencies. 35 organisations 
responded to the questionnaire. 

The  list  of  stakeholders  was  developed  in  consultation  with  DG  MARKT  and  sought  to  cover  all 
those with an interest in Article 89 and to be representative of the different stakeholder groups. 
The  geographic  location  of  the  stakeholders  focussed  on  the  Member  States  with  the  largest 
financial  services  sectors  –  the  UK,  Germany,  France,  Spain,  Italy  and  the  Netherlands,  though 
views were sought from organisation in all Member States, including Scandinavia and Poland and 
from organisations such as trade associations and CSOs that operate on a Europe wide basis. 

From the responses received we concluded that stakeholders were broadly of the view that: 

(cid:131)  Article  89  was  expected  to  improve  transparency,  accountability  and  public  confidence  in  the 

financial  services sector 

(cid:131)  Any impact on competitiveness, investment, credit availability, stability of the financial system 

would be limited 

(cid:131)  Improvements  to  the  implementation  and  interpretation  of  Article  89  would  enhance  its 
usefulness in terms of clarity and comparability and without such improvements there is a risk 
that the benefits arising from the disclosures could be undermined. 

(cid:131)  The  cost  of  complying  with  Article  89  was  not  significant  compared  to  other  regulatory 

compliance burdens on the sector 

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Survey participants 

We  asked  156  organisations  to  provide  their  views  on  their  expectations  of  the  likely 
economic impact of Article 89  

As  shown  below,  these  stakeholders  were  drawn  from  a  range  of  organisations.  While  we 
surveyed regulators and central banks from all the Member States, for the reporting institutions 
we  concentrated  on  the  EU  countries  with  the  largest  financial  services  sectors  (the  UK, 
Germany,  France,  Spain,  Italy,  and  the  Netherlands).  All  but  one  of  the  GSIBs,  Nordea,  are 
located in these countries. We also sought to include a smaller number of reporting institutions 
from other Member States to participate in our study, in particular from Poland and Scandinavia. 

Excluding the multinational companies that were asked to participate, 20% of the organisations 
asked to complete the survey have a cross-EU remit. These include trade associations, European 
regulators and CSOs. 

For comparison purposes, FS institutions headquartered in the US and in Switzerland were also 
asked to take part. 

The full detail of the responses is included in Appendix 2. 

Source: PwC analysis 

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 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

35  organisations  responded  to  our  opinion  survey,  with  an  equal  split  between 
business and non-business organisations  

We received 35 responses with 18 coming from businesses, trade associations and advisers and 
14  from  governments,  regulators  and  central  banks.  We  received  three  responses  from  civil 
society organisations. 

Within this section, credit institutions, business associations and professional advisers are classed 
as  business  organisations  while  central  banks,  regulators  and  civil  society  organisations  are 
referred to collectively as non-business organisations. 

The questionnaire and the list of stakeholders were reviewed by DG MARKT. 

Source: PwC analysis 

We had responses from organisations in 15 Member States, with the most responses from the UK 
followed by the Netherlands.  

The  overall  geographical  spread  of  responses  is  good  and  it  is  not  surprising  that  we  received 
most  responses  from  organisations  with  a  pan-EU  remit  and,  given  the  size  and  importance  of 
the FS sector to the UK economy, from UK based organisations. 

The  responses  that  we  received  from  the  smaller  Member  States  came  largely  from  financial 
regulators  and  from  central  banks,  which  again  is  not  surprising  given  that  very  few  credit 
institutions with sizeable cross border operations are headquartered in these smaller territories. 

We  received  25  separate  responses  from  investment  firms  in  Greece  that  are  members  of  the 
Hellenic  Capital  Markets  Committee.  For  the  purposes  of  our  analysis  these  have  been 
consolidated into one response (using the most common answer to each question) so as not to 
give the responses disproportionate weight when compared to the responses from other bodies 
which provided one view taking into account the views of all of their members.  

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Source: PwC analysis 

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Views on transparency, accountability and public confidence 

On balance, the stakeholders that responded to our survey expect Article 89 to have a 
broadly positive impact on the transparency and accountability of reporting institutions 
and on public confidence in the FS sector  

58%  of  respondents  felt  that  Article  89  would  improve  the  transparency  and  accountability  of 
reporting  institutions,  with  a  further  33%  expecting  there  to  be  no  impact.  A  negative  impact 
was anticipated by 9% of respondents. 

In  general,  business  organisations  were  less  positive  about  the  impact  than  non-business 
organisations. 

Few  respondents  provided  detailed  reasons  for  their  responses,  but  there  was  a  general  view 
among those expressing a positive view that providing the information required by Article 89 was 
transparent behaviour of itself.  

Some  stakeholders  with  a  positive  view  felt  that  the  disclosure  would  put  information  into  the 
public  domain  for  the  first  time  and  that  this  information  was  being  sought  by  investors  and 
other stakeholders. 

A view expressed by several stakeholders who anticipated no impact, and by one that anticipated 
a  negative  impact,  was  that  for  the  full  benefit  of  transparency  to  be  obtained  from  the 
disclosure requirements it was necessary for the requirements to be more clearly interpreted so 
that  more  meaningful  and  more  comparable  data  would  be  disclosed.  The  other  organisations 
expressing a negative view did not comment on the reasons behind their view. 

45%  of  respondents  felt  that  Article  89  would  lead  to  greater  public  confidence  in  the  financial 
services  sector.  A  further  42%  felt  there  would  be  no  impact  with  13%  anticipating  a  negative 
impact. 

The  views  on  increased  public  confidence  were  more  mixed  than  those  on  transparency  and 
accountability, with non-business organisations again expressing more positive views than those 
of the reporting institutions and other business organisations. 

Similarly  to  the  views  on  transparency  and  accountability,  stakeholders  with  positive  views 
commented  that  greater  transparency  would  lead  to  greater  public  confidence  and  that  it  was 
desired  by  some  investors.  One  organisation  with  a  positive  view  felt  that  transparency  alone 
would  not  be  sufficient  to  increase  public  confidence,  but  factors  such  as  business  results  and 
other disclosures would need to be considered. 

Again, a lack of clarity as to the reporting requirements was felt by many to have the potential to 
reduce  any  positive  impact  that  the  disclosure  might  have.  In  particular,  two  of  the  four 
organisations  that  predicted  a  negative  impact  cited  the  lack  of  clarity  and  potential  for 
misinterpretation of the disclosures as the reason for their negative view. The other two provided 
no comments as to the reasons for their view. 

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Views on the economic impact 

Stakeholders broadly expect Article 89 to have limited impact on competitiveness, 
investment, credit availability and stability of the financial system  

Whilst stakeholders expected a broadly positive effect on the accountability and transparency of 
reporting institutions and on public confidence in the financial system, the overall view was that 
there  would  be  no  impact  on  the  specific  criteria  of  competitiveness,  investment,  credit 
availability or stability of the financial system. 

A view expressed by a number of stakeholders was that while increased transparency may have 
an economic impact, it was likely to be incremental, coming on top of other changes in regulation 
and that there were many other factors that would have a far greater economic impact. 

It was also noted by some stakeholders that while any economic effects were likely to be small 
when  looking  at  the  financial  services  sector  as  a  whole,  there  may  be  significant  effects  for 
individual companies. 

A recurring theme throughout the responses from the stakeholders was that the current range of 
interpretations  and  the  different  statuses  of  Member  States’  implementation  of  Article  89  have 
resulted in considerable uncertainty as to how institutions should comply with the requirements. 
This was expected to lead to different institutions using different bases of preparation resulting in 
disclosures that would not be comparable and which could be prone to misinterpretation. 

Generally,  it  was  felt  that  the  impact  of  Article  89  would  be  improved  if  the  interpretation  of 
requirements  was  clearer,  more  detailed  and  more  consistent  so  as  to  allow  for  meaningful 
disclosure, including the disclosure of the basis of preparation and assumptions used, and if the 
requirements were implemented in the same way by all Member States. 

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The wider economic impact 

Some  stakeholders  expect  the  Article  89  disclosure  to  affect  the  management  of 
companies’ tax affairs  

Some  stakeholders,  including  businesses,  expect  CBCR  to  change  how  some  reporting 
institutions manage their tax affairs. 

One  reporting  institution  commented  that  “the  outlying  [tax]  positions  (i.e.  more  aggressive 
[tax] positions) will be abolished under public scrutiny. “ 

One CSO noted that 

“CBCR will increase awareness of financial institutions' tax management practices leading to 
greater  reluctance  to  operate  in  low  tax  jurisdictions  …  CBCR  will  lead  to  greater  public 
awareness  of  corporate  tax  payments.  This  might  ultimately  lead  to  an  environment  of 
greater  tax  compliance  which  will  increase  public  money  available  for  economic 
development.” 

While one regulator felt that CBCR would result in a reduced incentive for tax avoidance another 
expressed the view that  

“we  doubt  that  tax  minimisation  strategies  will  diminish  due  to  enhanced  reporting 
requirements  as  these  strategies  are  mainly  based  on  the  legal  exploitation  of  gaps  and 
loopholes in national and international tax law.”  

These  comments  indicate  that  CBCR  may  have  an  effect  that  goes  beyond  the  impact  on 
reporting entities themselves. Given the range of views, it is not possible at this stage to know if 
CBCR will cause reporting institutions to adopt a more cautious approach to tax risk, but if such 
an approach were adopted, future increases in the effective tax rates of some institutions could 
be expected, with a consequent reduction in banks’ capital base that supports lending. 

CBCR is a transparency initiative intended to give a clearer picture of a company’s corporate tax 
footprint across the world. Similar initiatives to improve tax transparency have been introduced, 
e.g. the OECD’s “Base erosion and profit shifting” (BEPS) initiative74. However, once a company’s 
corporate tax footprint is made public, the possible reactions are wide-ranging, uncertain and are 
highly dependent on stakeholders’ understanding of the reasons for the amount and geographical 
distribution of the taxes paid by the CBCR reporting entities. A wider economic impact could be 
generated if there were a change in a reporting entity’s effective tax rate as an indirect result of 
CBCR – for example if it felt forced to change its tax policies, taking all things into consideration, 
as  a  result  of  stakeholder  pressure  that  it  was  not  paying,  in  the  view  of  the  stakeholders,  the 
“right amount” of tax.  

Large-scale economic models are commonly used to analyse the impacts of changes in effective 
tax rates or changes in taxes on the FS sector (HMRC, 2013, EC, 2011 and 2013) on the wider 
economy.75 While PwC has the capacity to undertake modelling of this type, following discussion 

74 BEPS data are not to be made publicly-available but are to be provided to tax authorities for 
risk assessment purposes. 
75 For instance, HM Revenue and Customs (2013) analysed the effects of corporate tax cuts on 
the UK economy using a Computable General Equilibrium model, while the EC (2011 and 2013) 
commissioned analysis using a Dynamic Stochastic General Equilibrium model to examine the 
effects of the Financial Transaction Tax proposals. Such models are commonly used by 
governments and institutions to examine the effects of changes in effective tax rates.  

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with DG Markt it was felt that, given the uncertainty about the possible scenarios through which 
changes  in  effective  tax  rates  might  occur,  this  approach  might  over  or  under  estimate  a 
particular outcome. In particular the magnitude of any changes in effective tax rates can be very 
difficult to predict. On this basis our analysis is restricted to the following qualitative discussion of 
the potential impacts of CBCR on the wider economy that is focussed on the scope of stakeholder 
reactions that might lead to a change in the effective tax rate and subsequent economic effects.  

The importance of stakeholder reactions 

A wide range of stakeholders might be expected to be interested in and to react to the   CBCR 
disclosures  of  reporting  entities.  These  include  governments,  CSOs,  customers,  investors, 
employees and the general public. The perceptions of these stakeholders will, in part, depend on 
the following factors: 

(cid:131)  The  reporting  entity’s  performance  during  the  financial  crisis.  Some  of  the  reporting 
entities  will  have  received  state  support  during  the  crisis  and  it  may  be  deemed  that  these 
institutions  are  not  “paying  enough  back”.  Within  the  countries  where  the  group  is 
headquartered,  information  relating  to  corporate  tax  payments  will  be  published  as  part  of  a 
company’s  annual  accounts.  However,  the  introduction  of  CBCR  will  increase  the  amount  of 
detailed  information  available  and  could  therefore  raise  the  level  of  stakeholders’  interest  in 
these figures.  

The  FS  sector  has  faced  considerable  scrutiny  both  during  and  after  the  financial  crisis.  The 
sector  facilitates  the  flow  of  capital  around  the  economy,  and  provides  financial  products  to 
households, businesses, investors and the government. A well-functioning banking sector can 
improve  both  capital  efficiency  and  productivity  in  the  economy.  However,  the  sector  has 
inevitably  been  affected  by  the  knock-on  negative  economic  consequences  of  the  financial 
crisis  and  this  may  lead  stakeholders  to  form  more  negative  perceptions  relating  to  levels  of 
tax payments. 

(cid:131)  The ratio of economic activity generated by the reporting entity to taxes paid. Some 
reporting entities may have significant operations in a particular country, but, because of how 
the local tax rules apply to the profits of that operation or because of its financial performance, 
the proportion of taxes paid may not match the corresponding proportion of economic activity. 
Prior to the recent financial crisis, the financial services sector contributed a significant amount 
of  corporate  taxes,  accounting  for  around  18%  of  total  corporation  taxes  paid  in  the  G20 
economies76  .  However,  extensive  tax  losses  and  declining  profitability  will  place  downward 
pressure on the level of taxes paid for some years to come. 

As  shown  by  the  stakeholder  comments,  the stakeholder  reactions  to  CBCR  reporting  will  vary. 
The amount of tax levied on CBCR reporting entities is a governmental policy decision and again 
is influenced by public perception and also political will, not economic considerations alone. The 
political stance of some governments may lead them to seek to raise further tax revenues from 
CBCR  reporting  entities  –  the  amount  of  tax  paid  could  be  relatively  high  in  the  view  of  some 
stakeholders,  but  could  at  the  same  time  be  perceived  as  not  being  “enough”  in  the  view  of 
others.  This  decision  will  also  be  affected  by  economic  realities  such  as  fiscal  deficits  and  the 
circumstances and strength of likely stakeholder reactions.  

•  HM Revenue and Customs (2013) “Analysis of the dynamic effects of Corporation Tax 

reductions”, joint report by HMRC and HMT, 5 December 2013  

•  European Commission (2011) 1st impact assessment on the financial transaction tax 
(SEC/2011/1102), Brussels: Taxation and Customs Union, European Commission 
•  European Commission (2013) 2nd impact assessment on the financial transaction tax 
(SWD/2013/28), Brussels: Taxation and Customs Union, European Commission 

76  IMF  (2010)  “A  fair  and  substantial  contribution  by  the  financial  sector:  final  report  for  the 
G20”, June 2010 

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The  scope  of  any  government  policy  response  to these  reactions  could  fall  within  the  corporate 
income tax system, or outside it, e.g. through the use of bank levies. However, there is a distinct 
risk  that  any  stakeholder  reaction  will  only  be  based  on  partial  information.  CBCR  under  Article 
89 only relates to corporate income tax payments, but this represents only a portion of the taxes 
borne  by  the  reporting  entities  (e.g.  taxes  such  as  employer  social  security  contributions, 
irrecoverable  VAT  and  bank  levies)  and  the  taxes  they  collect,  which  are  generated  by  the 
economic activity they create (e.g. personal income taxes paid by employees and withheld by the 
companies, employee social security contributions).  

Impacts of a change in effective tax rates 

As we have mentioned above, some respondents to the stakeholder survey have indicated  that 
CBCR may lead to a change in effective tax rates of some reporting institutions. The probability 
and  magnitude  of  any  such  change  are  however  impossible  to  predict  as  this  stage  given  the 
different  mechanisms  through  which  change  could  occur  and  the  fact  that  change  could  affect 
only single entities or the sector more broadly. 

Possible  changes,  for  example  include  a  direct  change  in  existing  tax  rates  or  allowances,  new 
taxes  or  a  self-imposed  reduction  in  planning  that  increases  tax  cost  efficiency.  If  any  such 
change were to occur then the following effects could potentially arise: 

(cid:131)  A  corresponding  reduction  in  economic  activity  in  the  particular  entity.  Economic 
theory  would  dictate  that  an  increase  in  taxation  leads  to  a  “deadweight  loss”  i.e.  a  loss  of 
economic  output.  The  concept  of  deadweight  loss  is  explained  in  more  detail  in  Appendix  4. 
The scale and magnitude of any reduction in economic activity will depend on the type of taxes 
raised and their economic efficiency.  
The  OECD  (2010)77  ranks  capital  based  taxes  at  the  more distortive  end  of the tax  spectrum 
(taxes  on  consumption  are  considered  to  be  more  efficient).  Capital  taxes  (e.g.  corporate 
income taxes and bank levies) reduce the profits of firms, inhibiting both domestic and foreign 
direct  investment  and  reducing  the  rate  of  capital  accumulation  and  lending  in  the  economy. 
Corporate  income  taxes  also  hinder  productivity  through  a  number  of  channels,  including 
distorting  relative  factor  prices,  causing  high  compliance  costs  and  hindering  technology 
transfers and knowledge spillovers. Most importantly, taxes that relate to business inputs are 
particularly distortive as they affect the allocation of productive inputs within an economy. By 
increasing the price of the product involved in the transaction, market participants adjust their 
behaviour to economise on the more expensive products. 

(cid:131)  An offsetting benefit through governments spending any additional taxes raised. Any 
additional  tax  payments  to  the  government  could  be  used  to  provide  benefits  to  society  and 
the  wider  economy.  The  government  could  use  additional  tax  receipts  generated  from  CBCR 
reporting  entities  to  fund  public  services  or  reduce  existing  fiscal  deficits  or  levels  of  national 
debt. These benefits will offset, either partially or in full, the economic costs of additional tax 
payments.  The  extent  of  this  offset  is  dependent  on  how  effectively  any  additional  taxes 
generated are spent – unproductive and inefficient spending would do very little to provide an 
offset, highly productive and efficient spending could more than offset the deadweight loss.  

(cid:131)  Corresponding  competition  effects  amongst  reporting  entities.  If  the  average  effective 
tax for a particular reporting entity does increase in a particular country, then this could have 
pro-  or  anti-competitive  effects.  For  instance,  if  a  particular  entity  was  forced  into  paying 
additional  tax  after  pursuing  highly  efficient  tax  planning,  then  this  could  benefit  entities 
operating  in  the  same  country  that  have  not  pursued  such  planning.  However,  the 
corresponding circumstances are key to the outcome. For instance, an entity might only decide 
to pursue more efficient tax planning if it is struggling to preserve capital to comply with other 
FS sector regulations (e.g. Basel III or capital ratios set by CRD IV). In such circumstances the 
consequences of an increase in effective tax rates could be quite severe.  

77 OECD (2010) OECD Tax Policy Studies: Tax Policy Reform an Economic Growth, OECD, 2010. 

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Alternatively,  situations  may  arise  whereby  domestically-headquartered  entities  could  be 
favoured  over  foreign  entities  or  vice-versa.  Or  an  entity  that  has  engaged  in  tax  efficient 
planning  could  be  treated  in  the  same  way  as  an  entity  that  has  not  e.g.  through  a  policy 
change that affects the whole of the sector. 

(cid:131)  Increases in public confidence. If transparency results in the amount of tax paid by the FS 
sector  being  viewed  by  the  public  as  “fairer”,  there  could  be  a  benefit  in  the  form  of  public 
confidence  in  the  tax  system  in  general  and  in  the  FS  sector  specifically.  This  could  have 
benefits  that  outweigh  the  economic  consequences  of  the  higher  effective  taxes  in  the  FS 
sector  that  might  be  required  to  obtain  such  a  view.    If  effective  tax  rates  rise  due  to  a 
reduction  in  tax  planning  that  the  relevant  tax  authority  or  Government  perceives  to  be 
unacceptable,  then  this  could  be  viewed  as  the  tax  system  functioning  better.    This  could  be 
distinguished from situations where institutions choose, for fear of adverse public opinion, in a 
situation where public opinion may not be well informed, to adopt a potentially overly-cautious 
approach to tax thereby unnecessarily and inefficiently increasing their effective tax costs.   

Again,  these  outcomes  are  not  easily  predicted,  nor  is  it  straightforward  to  predict  their 
likelihood.  Their  scope  and  magnitude  will  ultimately  be  dictated  by  subsequent  stakeholder 
reactions  to  the  published  CBCR  data  and  the  balancing  by  companies  of  differing  stakeholder 
reactions.  

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Compliance costs 

The  costs  of  complying  with  Article  89  are  expected  to  be  limited  compared  to  other 
regulatory burdens  

In addition to the questions asking for the views of stakeholders on Article 89, we also asked the 
GSIBs and some other reporting institutions for their estimate of the incremental costs incurred 
in preparing their disclosures. 

Only two banks provided any quantitative estimate of the cost with a number of other institutions 
commenting  that  either  they  were  unable  to  accurately  estimate  the  cost,  or  that  the  cost  was 
not  significant  when  compared  with  the  other  regulatory  compliance  burdens  that  the  business 
faced. 

The two banks that provided a quantification of the cost are both GSIBs operating across a range 
of territories. The cost estimate provided was for the central headquarter costs, but there may be 
additional  costs  incurred  by  subsidiaries.  One  bank  estimated  the  annual  recurring  cost  of 
complying with Article 89 to be in the region of €50,000 including external audit costs, while the 
other estimated the cost to be around €20,000 excluding external costs. 

The one-off costs for the first year of the reporting were estimated by both banks to be around 
€10,000  excluding  external  costs.  Only  one  of  the  two  banks  provided  information  on  the 
external  costs  which  it  estimated  at  €200,000  of  initial  one-off  costs  and  €40,000  of  annually 
recurring  costs.  As  only  two  banks  provided  quantitative  data,  this  cannot  be  taken  as  being 
representative of the sector as a whole and cannot be extrapolated.  

The cost of complying with Article 89 is expected to be inherently proportional to the size of the 
business  with  smaller  institutions  operating  across  only  a  few  territories  needing  to  collect  and 
disclose far less data than large businesses operating across many jurisdictions. 

While  a  number  of  stakeholders  expected  the  cost  not  to  be  significant  compared  to  other 
regulatory costs, it should be noted that this is in the context of a highly regulated industry that 
is likely to have already invested significantly in reporting systems. 

Many of the financial institutions that have to report under Article 89 are likely to be affected by 
the  country-by-country  reporting  template  that  has  been  developed  by  the  OECD  as  part  of  its 
work on BEPS78. While the disclosures under Article 89 are to be public, the disclosures under the 
proposed  BEPS CBCR  template  are  to  be  made  in  confidence  to  tax  authorities  and  the  OECD’s 
CBCR template is designed to serve as a high level risk assessment tool for the tax authorities.  
In  view  of  this  purpose,  the  BEPS  template  includes  extra  items  of  information  not  required  by 
Article 89. The compliance cost for companies that are subject to both regimes could be reduced 
if,  for  those  items  which  have  to  be  reported  under  both  Article  89  and  under  the  BEPS  CBCR 
template, the Article 89 and the BEPS requirements could be made equivalent.  

Many groups that are headquartered outside the EU, and which have no, or only partial reporting 
under Article 89, will have to make data available to tax authorities under the OECD provisions. 
Although  the  OECD  reporting  requirements  are  expected  to  apply  equally  to  groups 
headquartered  in  OECD  countries  inside  and  outside  the  EU,  there  will  still  be  an  additional 
burden  and  additional  impacts  on  the  groups  that  are  also  required  to  report  publically  under 
Article 89. 

78  
OECD/G20 Base Erosion and Profit Shifting Project Guidance on Transfer Pricing Documentation 
and Country-by-Country Reporting ACTION 13: 2014 Deliverable, September 2014 

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Section  five  -  Key  challenges  with  the  implementation  of  Art. 
89 

This section explains a range of approaches that have been taken by Member States and by 
reporting entities to the interpretation and implementation of Article 89 as identified by our legal 
analysis, our stakeholder survey and our review of the initial disclosures by reporting institutions. 

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Overview 

Despite the requirement for CRD IV to be implemented by 31 December 2013, and the first year 
reporting  deadline  of  1  July  2014  set  out  in  Article  89,  only  thirteen  Member  States  had  fully 
implemented  Article  89  as  at  30  June  2014,  with  a  further  four  having  implemented  it  only  for 
either credit institutions or investment firms. 

Of the jurisdictions that have implemented the requirements, the majority have provided little or 
no  guidance  as  to  how  institutions  should  apply  the  regulations,  leaving  uncertainty  for  many 
organisations that are required to comply. Further, the first year disclosures submitted privately 
to  the  European  Commission  illustrate  a  number  of  areas  where  there  has  been  a  lack  of 
guidance from Member States leading to inconsistent interpretation by institutions. 

Although most jurisdictions have provided little clarity on many of the requirements, where they 
have, a number of inconsistencies have been identified.  

(cid:131)  The  objective  of  Article  89,  as  set  out  in  recital  (52)  to  CRD  IV,  is  to  increase  transparency 

which “is essential for regaining the trust of citizens of the Union in the financial sector”.  

(cid:131)  To  the  extent  that  a  lack  of  clarity  leads  to  inconsistency  in  how  institutions  meet  their 

obligations under Article 89, it is likely to undermine the success in meeting that objective. 

(cid:131)  The  key  areas  of  uncertainty  are  summarised  on  the  following  pages  and  more  detail  is 

provided in Appendix 3. These are: 

o  Uncertainty as to which entities within a group are within the scope of Article 89 

o  Lack of coherence between the interpretation of terms used in CRD IV and terms 

used in financial accounting 

o  Use of different methods of consolidation 

o  Member States having different views on whether tax on profit or loss should be an 

accounting or a cash measure 

o  Lack of clarity as to how amounts should be treated where the taxing jurisdiction 

and the location of an activity are different 

o  Lack  of  legislation  to  prevent  double  reporting  by  subsidiaries  whose  parent 

companies have reported in a different Member State 

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Initial disclosures 

A  number  of  GSIBs  have  publically  disclosed  the  items  required  by  parts  d)  to  f)  of 
Article 89 (1)  

Of the fourteen GSIBs required to report privately items (d), (e) and (f) of article 89 (1) to the 
European Commission, at least three (Royal Bank of Scotland, Barclays and Standard Chartered) 
have reported this information publically. In addition, two of these GSIBs have reported 
significant amounts of additional voluntary information, primarily around taxes paid other than 
corporate income taxes. 

The publication of this information suggests that these organisations are not overly concerned 
about the potential consequences of the data being in the public domain. The publication of 
additional information to support the disclosures does however suggest there is a concern that 
data could be misinterpreted in the absence of additional contextual data and explanations. 

Furthermore, we note that since the publication of first year disclosures, there has been limited 
public interest with, as far as we are aware, significant comments appearing in the media in 
respect of only one GSIB's disclosures.  

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The reporting ‘institution’ 

Placing  the  reporting  requirement  on  ‘institutions’  can  lead  to  disclosures  that  cover 
only part of a group and are difficult to reconcile to consolidated accounting data  

Article  89  places  the  reporting  obligation  on  the  ‘institution’.  The  implication  of  this  is  that  for 
most  (but  not  all)  banking  groups,  the  ultimate  parent  will  be  required  to  comply  with  the 
reporting requirement. In the case of almost all non-banking groups and groups headquartered 
outside the EU, the ‘institution(s)’ are typically embedded within the group structure.  

Where  the  ultimate  parent  is  not  an  ‘institution’,  a  group  may  have  multiple  reporting 
obligations, one for each of its institutions with each representing only a portion of the group. 

In light of this, one credit institution highlighted the disparity between how the regime applies to 
groups with headquarters inside the EU compared to those with headquarters in third countries:  

“we consider it is important to maintain the level playing field for all financial institutions.  
As far as non EU parent institutions are exempted from this report they will not be subject 
to the market discipline as EU parent institutions.  Moreover these institutions will not 
suffer the potential adverse consequences of publishing this information (e.g. eventual 
misinterpretation of the reported information by the media or the public).” 

From  an  analysis  of  the  disclosures  produced  by  the  GSIBs  and  submitted  to  the  European 
Commission,  it  appears  that  the  majority  have  reported  at  the  ultimate  parent  company  level, 
thereby  covering  their  entire  worldwide  group.  In  some  cases  this  may  include  entities  that 
would not be included within the prudential consolidation required by CRD IV more generally.  

That  said,  there  is  at  least  one  organisation  whose  disclosure  is  not  easy  to  reconcile  to  the 
financial statements of their ultimate parent company and therefore their worldwide group.  

Whilst  all  territories  have  so  far  maintained  the  reporting  obligation  on  the  ‘institution’,  the  UK 
has implemented an option for groups only partially within the scope of the regulations to report 
at a parent or sub-parent level rather than the ‘institution’ level.  

This is intended to provide flexibility and empower organisations to choose the most appropriate 
level at which to report. 

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Another consideration in respect of the reporting ‘institution’ is whether or not branches of third 
country institutions are within the scope of the regime. We recognise that this is a wider issue for 
CRD IV as a whole; particularly where provisions which would not normally apply to branches can 
be deemed to do so if not applying the provisions would confer an advantage on those entities 
that are headquartered outside the EU.  

In some territories, the position of branches in respect of Article 89 is unclear, whilst in others, 
such as the UK, Denmark, Austria, Finland and Malta they have been specifically excluded.  

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Consolidation 

Different  consolidation  approaches  have  been  followed  by  different  countries  and 
businesses. Many Member States have no provisions to prevent double reporting.  

Article  89  includes  the  requirement  to  report  ‘on  a  consolidated  basis’.  This  term  has  not  been 
defined  in  any  level  of  detail  by  any  territory.  In  the  majority  of  cases,  this  wording  has  been 
implemented  without  modification.  An  exception  to  this  approach  is  the  UK,  which  has 
implemented the requirement to report ‘in accordance with accepted accounting standards on a 
consolidated basis’. The Austrian regulators have adopted a similar approach.  

The  lack  of  any  detailed  framework  creates  challenges  for  those  institutions  required  to  report 
under  the  regime.  Not  only  does  it  leave  questions  about  whether  an  accounting  or  prudential 
based consolidation approach should be adopted, but it also leaves uncertainties as to how intra-
group items should be accounted for.  

The  first  year  GSIB  disclosures  highlight  the  lack  of  clarity  around  consolidations,  with  several 
disclosures including a ‘consolidation adjustments’ row while others do not.  

Exemption to prevent double reporting 

To date, only Germany, France and the UK have implemented an exemption to prevent double 
reporting. The implication of this is that many organisations will be subject to a double reporting 
requirement where an institution has an establishment which also meets the definition of an 
institution, but which is established in a different jurisdiction.  

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Name, nature of activities and geographical location 

There  is  considerable  variation  in  how  GSIBs  have  described  the  name  and  nature  of 
their activities and how amounts have been allocated to territories  

The  requirement  to  report  ‘name,  nature  of  activities  and  geographical  location’  has  not  been 
prescribed in detail by any jurisdiction. Although the opinion survey results suggest this creates 
very  little  uncertainty,  a  review  of  the  GSIB  disclosures  suggests  it  has  been  interpreted  very 
differently.  

Of  the  disclosures  reported  on  1  July  2014,  there  is  a  large  variation  in  the  level  of  detail 
reported,  from  those  who  have  reported  every  single  legal  entity  within  the  scope  of  the 
requirements, to those who have reported only principal trading entities and those who have not 
reported the names of any legal entities.  

There is a similar variety of approaches to reporting the nature of activities, with the majority of 
organisations  disclosing  a  high  level  description,  such  as  ‘financial  services’  or  ‘commercial 
banking’,  however  a  number  of  organisations  have  provided  substantially  more  descriptive 
narratives of their operations in each territory.  

Geographical  location  is  an  area  that  has  not  been  addressed  in  any  level  of  detail  by  any 
jurisdiction, and is an area that is particularly subjective. Areas of particular subjectivity include 
entities  incorporated  in  one  territory  but  which  operate  in  a  different  jurisdiction.  Other 
subjective areas include branch top up taxes that are payable in a parent jurisdiction, or tax paid 
in respect of a controlled foreign company but which is charged on a parent company.  

From  the  data  provided  it  is  not  possible  to  interpret  on  what  basis  the  GSIB  disclosures  have 
allocated activities and data to each jurisdiction.  

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Turnover 

There  is  some  variation  in  stakeholders’  preferred  interpretations  of  ‘turnover’  and 
‘employment’  

Although turnover is not a commonly used term in the financial services industry, most territories 
have not included a prescriptive definition. That said, the first year disclosures do not appear to 
be creating particular challenges for institutions.  

The  results  of  the  opinion  survey  suggest  a  broad  consensus  for  a  requirement  that  amounts 
disclosed as turnover should agree to the institutions’ financial statements.  

Despite  this  consensus,  stakeholders  remain  divided  as  to  whether  the  term  should  mean  total 
gross income, or net income before certain expenses.  

It  is  also  noted  that  many  stakeholders  recognise  the  difficulties  in  providing  a  rigid  definition 
given that the ‘turnover’ reflected in the financial statements of credit institutions and investment 
firms is often displayed in very different ways.  

Employees 

In territories such as Denmark and the UK it is clear that the requirement is to report employees 
based  on  contractual  employment.  Other  territories  have  remained  silent  on  the  point  and 
therefore there is a level of uncertainty around how employees should be reported.  

The  results  of  the  opinion  survey  highlighted  some  possible  alternative  approaches,  with  some 
stakeholders favouring a strict definition based on contractual employment which would be in line 
with  other  reporting  requirements,  whereas  others  expressed  a  preference  for  flexibility  to 
incorporate the effect of secondees and sub-contractors.  

From  reviewing  the  GSIB  disclosures,  it  appears  that  differing  approaches  have  been  taken  to 
reporting  employees.  In  particular,  it  is  noted  that  the  disclosures  include  the  following  terms: 
‘average full time equivalent employees’, ‘financial headcount’, ‘no. employees’ and ‘average FTE 
including temporary staff’. 

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Tax on profit or loss 

The term “tax on profit or loss” has been taken as meaning tax paid by some Member 
States, but others have applied an accruals based definition  

Member  States  have  interpreted  the  term  ‘tax  on  profit  or  loss’  in  different  ways.  There  are  a 
number of territories such as the UK and Belgium that have defined the term as cash tax paid, 
whilst  others,  such  as  France,  Austria,  and  Malta  have  defined  the  term  as  taxes  accrued. 
Despite  the  clarity  in  these  territories,  many  others  have  not  provided  any  guidance  and 
therefore institutions must themselves interpret the local regulations to determine how the term 
should be applied. 

An  analysis  of  the  GSIB  disclosures  highlights  the  inconsistent  interpretations  which  are  as  a 
result  of  the  inconsistent  implementation  of  Article  89  amongst  Member  States  combined  with 
the lack of implementation in others.  

Of  the  disclosures  reviewed,  a  number  of  different  terms  are  used  in  place  of  the  Article  89 
requirement, including: 

(cid:131)   

(cid:131)   

(cid:131)   

(cid:131)   

‘tax on profit or loss’ 

‘current tax’ and ‘deferred tax’ 

‘tax paid / (received)’ 

‘corporation tax paid’ 

While some of the disclosures make it clear that the tax figures are limited to corporate income 
taxes  only  (e.g.  UK  GSIBs  applying  the  UK  regulations)  other  disclosures  do  not  make  it  clear, 
although where an accounts based tax charge is disclosed, it is likely that withholding taxes are 
also included within the figures.   

In addition, one GSIB disclosure includes a note that their numbers include withholding taxes as 
well as corporate income taxes.  

Of the stakeholders surveyed as part of the opinion survey, 17 of the respondents expressed a 
view that the term should be interpreted as an accounting based tax charge (6 credit institutions, 
4  FS  trade  associations,  7  regulators/  government  bodies),  while  4  were  in  favour  of  cash  tax 
paid  (2  business  and  2  non-business  organisations)  and  the  remaining  respondents  did  not 
answer the question. 

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Public subsidies received 

There is a difference of views as to how broad the scope of “public subsidies received” 
should be.  

The term ‘public subsidies’ has not been defined by most jurisdictions, although a number have 
included  guidance.  Given  the  limited  number  of  territories  that  have  addressed  the 
interpretation,  two  key  uncertainties  remain.  The  first  is  the  scope  of  the  term  and  whether  it 
should be limited to direct taxpayer support or whether the scope should be widened to include 
implicit support, such as that provided by central banks. The second key question is whether the 
requirement should be to report on a cash basis or an accruals basis. 

Of  the  territories  that  have  implemented  Article  89  to  date,  Finland  has  adopted  a  definition 
which covers both capital grants and also government guarantees.  

Another  territory  that  has  implemented  the  requirement  (the  UK) has  excluded  implicit  support 
provided by central banks and governments.  

The  results  of  the  opinion  survey  indicate  a  division  of  opinion  between  business  and  non-
business  organisations,  with  business  organisations  favouring  a  limited  scope  based  on  cash 
support, compared to non-business organisations favouring a broader definition. 

Some  stakeholders  have  commented  on  the  practical  difficulties  associated  with  quantifying  a 
figure that includes amounts other than direct taxpayer support.  

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Location of disclosures 

Reporting  institutions  have  used  a  variety  of  formats  for  their  disclosures  and 
disclosure on websites appears popular  

With the exception of the UK, Member States have not included any guidance on how the term 
‘where possible, as an annex to the annual financial statements’ should be interpreted.  

The  guidance  provided  by  the  UK  is  that  disclosures  should  be  publicly  available  and  therefore 
reported in either the financial statements or on the company web site.  

Of  the  respondents  to  the  opinion  survey,  only  fourteen  answered  the  question  as  to  where 
institutions  should  report,  with  views  fairly  evenly  spread  between  disclosure  in  the  annual 
accounts and disclosures on company websites. Six reporting institutions favoured disclosure  in 
the  annual  accounts,  five  reporting  institutions  or  trade  associations  favoured  disclosure  on 
websites and three organisations opting for disclosure on websites and in annual reports. 

Format of disclosures 

The first year disclosures submitted to the European Commission highlight the different formats 
and levels of detail included by each organisation. Key observations include the varying level of 
detail included within the disclosures, including the varying levels of explanation of the context, 
approach and framework applied to comply with the regulations, and the differences in additional 
disclosures around other taxes paid, and footnotes to explain certain numbers. 

The other key difference was the presentation of consolidation adjustments by some institutions 
compared to others who did not explicitly report such items. 

No strong opinions were expressed by stakeholders as to the desirability of a standard template 
for  CBCR.    The  concerns  raised  relate  mainly  to  inconsistencies  in  the  implementation  and 
interpretation  of  Article  89,  rather  than  from  the  lack  of  a  template.  Indeed  a  number  of 
stakeholders have expressed a wish for flexibility in the application of Article 89 and a template 
may make such flexibility more difficult to achieve. 

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Interactions between Article 89 and other CBCR regimes 

Country-by-country  reporting  under  CRD  IV  creates  a  new  financial  reporting 
requirement for most institutions 

Although the requirements to report employees, turnover, profits and taxes are, to some extent 
consistent  with  existing  reporting  obligations  across  the  European  Union,  the  requirement  to 
report such information on a country-by-country basis is new, and requires much more granular 
reporting than any existing obligations. 

Some  groups  may  include  some  of  the  data  within  their  geographic  segmental  reporting,  most 
commonly  for  net  income  disclosures.  The  level  of  the  reporting  is  however  a  matter  for  each 
group  based  on  its  own  materiality  considerations  and  so  reporting  is  often  done  at  a  regional 
rather than a country level. The reporting of tax data and profits, even by region, is uncommon 
and we are not aware of any example of the reporting of public subsidies by region under IFRS. 

The use of detailed reporting by geography is perhaps more common in sustainability reporting 
than  in  financial  reporting.  The  Global  Reporting  Initiative  (GRI)  has  developed  a  reporting 
framework  for  sustainability  reporting  which,  although  not  mandatory,  is  well  recognised  and 
increasingly used by multinational companies. 

All topics listed in the Article are included in the GRI sustainability reporting framework.  To be 
considered  ‘in  accordance’  with  the  GRI  Guidelines,  an  entity  is  required  to  report  on  the  same 
topics as for (a), (b), and (c) of Article 89. Items (d), (e), and (f) are to be reported under the 
economic  category  of  the  guidelines  (G4  -  EC  1-4)  but  the  reporting  is  not  required  to  be  ‘in 
accordance’, provided that the aspects have not been identified as material to the organisation.   

Organisations that have adopted the GRI framework may therefore already be reporting some of 
the  data  required  by  Article  89,  but  the  extent  of  the  report  and  the  level  at  which  the  data  is 
disclosed will be determined by the reporting organisation based on its materiality considerations 
and on what it views as important to its stakeholders. 

From the responses that we received to our stakeholder survey we noted a difference of views as 
to whether the data required to be disclosed under Article 89 was already in the public domain.  

A number of respondents were of the view that the information was available, albeit not in such 
a convenient form, while others felt it was a new requirement which placed an additional burden 
on reporting institutions. 

For many large and complex groups, however, the information required by Article 89 is unlikely 
to  be  in  the  public  domain.  The  information  is  not  required  for  consolidated  accounts  prepared 
under  IFRS  and  even  if  every  subsidiary  of  a  group  prepared  publically  available  accounts,  the 
data would still need consolidating at a country level to produce the Article 89 disclosures. 

The  Article  89  reporting  is  therefore  likely  to  be  a  new  requirement  for  most  multinational 
groups, unless they already perform detailed and comprehensive CBCR reporting under the GRI 
or another voluntary framework.  

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CBCR regimes have historically focussed on the extractive industry, though BEPS CBCR 
will affect all industries 

CBCR was first applied to the extractive industry as a way of alleviating the “resource curse” of 
poverty in nations that are rich in mineral wealth79. The first reporting regime for the extractive 
sector  was  the  Extractive  Industries  Transparency  Initiative  (EITI).  While  arguably  not  a  CBCR 
regime  in  the  truest  sense,  given  that  each  country  has  to  adopt  the  EITI  separately  and  the 
reporting  is  only  for  that  country,  the  EITI  has  influenced  the  US  Dodd-Frank  and  the  EU 
Accounting and Transparency Directive CBCR regimes that have followed.  

EITI,  Chapter  10  of  the  EU  Accounting  Directive  and  section  1504  of  the  US  Dodd-Frank  rules 
apply only to the extractive sector and include payments to governments, but not disclosure of 
number  of  employees,  turnover,  profits,  public  subsidies  or  nature  and  location  of  activities.  In 
addition,  these  regimes  include  not  just  corporation  tax,  but  other  payments  to  governments 
such  as  mining  royalties,  license  fees  and  bonus  payments.  These  regimes  aim  to  inform  local 
communities  of  the  amounts  that  are  paid  by  extractive  companies  working  in  their  region  to 
allow local communities to hold their governments to account. This would seem to be a different 
aim from that set out for Article 89. 

CBCR  under  CRD  IV  differs  from  the  extractive  regimes  as  it  includes  non-tax  financial  data 
which may allow stakeholders to assess in some measure whether the “right amount” of tax has 
been paid.  

The draft transfer pricing documentation rules issued on 30 January 2014 by the OECD as part of 
its programme to address Base Erosion and Profit Shifting include a requirement for multinational 
companies  to  prepare  a  CBCR  template  which  is  intended  to  serve  as  a  high-level  risk 
assessment tool for tax authorities.  

The draft rules include provisions for the disclosure of a number of the non-tax items that have 
given  rise  to  many  of  the  practical  challenges  with  interpreting  and  implementing  Article  89  of 
CRD IV.  

The  final  version  of  the  BEPS  requirements  was  made  public  in  September  2014  and  items 
similar  to  those  in  parts  a)  to  e)  of  paragraph  (1)  of  Article  89  are  included  in  the  BEPS  CBCR 
template. In view of its purpose to act as high level risk assessment tool for tax authorities, the 
BEPS  template  includes  further  items  of  information  not  required  by  CRD  IV,  and  further 
information will need to be included in transfer pricing documentation. The reporting burden on 
companies could be reduced if, for those items which have to be reported under both Article 89 
and  under  the  BEPS  CBCR  template,  the  Article  89  and  the  BEPS  requirements  could  be  made 
equivalent.  

As part of our work, we also considered whether other financial centres, specifically the US and 
Switzerland, imposed disclosure requirements similar to Article 89. 

We  found  no  evidence  of  similar  reporting  obligations  in  either  Switzerland  or  the  US.  We  note 
however  the  existence  in  the  US  of  CBCR  for  the  extractive  sector  under  section  1504  of  the 
Dodd-Frank Act and also note the various difficulties in the implementation of section 1504 which 
means that the regime is not yet active in the US, despite originally being added to the statute 
books in August 2010.  

79 http://eiti.org/eiti/history 

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Appendix 1 – Detailed reference material for the econometric 
study

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Appendix 1.1 Other country-by-country reporting initiatives 
The  table  below  sets  out  more  detail  the  various  country-by-country  reporting  initiatives  that 
have been implemented worldwide. 

Table 22: Extractives industry country-by-country reporting initiatives 

Reporting 
initiative 

Who does it 
cover? 

Key objectives 

Reporting requirements 

Extractive 
Industries 
Transparency 
Initiative 
(EITI) 

Street 
and 

Dodd-Frank 
Wall 
Reform 
Consumer 
Protection 
Act 

All 
companies 
extracting  natural 
resources 
operating 
country 
implementing EITI. 

in 

a 

EITI  aims  to  improve 
the  transparency  and 
accountability 
of 
extractives  regimes  in 
natural 
resource-rich 
countries  with  a  view 
to 
strengthening 
governance. 

requires 

EITI 
extractives 
companies  to  disclose  payments 
to governments. It also requires 
the 
governments 
payments  they  received  from 
extractives  companies.  The  two 
sets 
then 
are 
figures 
independently reconciled 

to  disclose 

of 

All  SEC  registered 
extractives 
companies 
upstream 
downstream). 

(both 
and 

The  Dodd-Frank  Act 
aims to promote better 
and 
governance 
accountability 
of 
extractives regimes. 

registered 

SEC 
extractives 
companies  are  required  to  file 
an  annual  SEC  report  disclosing 
payments  made 
the 
company, 
its  subsidiaries  or 
entities  under  its  control  to  the 
foreign 
US  government  and 
governments  for  the  purpose  of 
extracting natural resources. 

by 

EU  Directives 
on 
Accounting 
and 
Transparency 

EU  public  interest 
(notably 
entities 
listed  entities)  and 
EU 
large 
undertakings 
in 
extractives 
the 
industry. 

EU  Directives  aim  to 
promote  transparency 
and  accountability  of 
the 
extractives 
industry  and  national 
governments  to  local 
communities. 

EU  Directives  require  disclosure 
of  payments  over  €100,000 
made  to  governments  on  a 
country-by-country  basis,  or 
where possible, on a project-by-
project basis. 

Source: PwC analysis 

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Appendix 1.2 List of banks included in our analysis 

Bank name 

Bank of America 

Bank of China 

Bank of New York Mellon 

Barclays 

BBVA 

BNP Paribas 

Citigroup 

Credit Suisse 

Deutsche Bank 

Goldman Sachs 

Group Crédit Agricole 

HSBC 

Headquarter country 

United states 

China 

United states 

United kingdom 

Spain 

France 

United states 

Switzerland 

Germany 

United states 

France 

United kingdom 

Industrial and Commercial Bank of China Limited 

China 

ING Bank 

JP Morgan Chase 

Morgan Stanley 

Nordea 

Royal Bank of Scotland 

Santander 

Société Générale 

Standard Chartered 

State Street 

UBS 

Unicredit Group 

Wells Fargo 

Lloyds Banking Group 

Commerzbank 

Intesa 

Danske Bank 

KBC 

Handelsbanken 

SEB 

Banca Monte dei Paschi Siena 

Erste Bank 

Swedbank 

UBI 

Agricultural Bank of China Limited 

Bank of Communications Co. Ltd 

Natixis 

CITIC Group 

Banco do Brasil S.A. 

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114 

Netherlands 

United states 

United states 

Sweden 

United kingdom 

Spain 

France 

United kingdom 

United states 

Switzerland 

Italy 

United states 

United kingdom 

Germany 

Italy 

Denmark 

Belgium 

Sweden 

Sweden 

Italy 

Austria 

Sweden 

Italy 

China 

China 

France 

China 

Brazil 

 
 
 
 
 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

China Merchants Bank Co Ltd 

Industrial Bank Co Ltd 

China Minsheng Banking Corporation 

Shanghai Pudong Development Bank 

Sberbank of Russia 

Dexia 

Itau Unibanco Holdings 

Caixabank, S.A. 

DnB ASA 

Banco Financiero y de Ahorros SA-Bankia 

Source: PwC analysis 

China 

China 

China 

China 

Russian federation 

Belgium 

Brazil 

Spain 

Norway 

Spain 

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Appendix 1.3 Disclosure quality scoring framework 

This  section  sets  out  our  disclosure  scoring framework  in  more  detail,  with  information  on  the  criteria  for  each  of  the  seven  individual 
components.  

Reporting Area 

Notes for scoring 

Score scale 

Risk 
Management

Discussion of 
risk 
management 
strategy  and 
objectives 

Best practice would be a good discussion of the 
company's strategy for dealing with risk and the 
objectives  for  the  company's  risk  strategy. 
Information  is  usually  at  the  start  of  a  Risk 
section of the report although summaries at the 
start of a report may also mention this area. 

of 

Details 
risk 
management 
in  the  past 
year 

Again this is usually found in the risk section of 
the  report.  Best  practice  would  be  a  good 
description  of  risk  management  procedures  or 
activities within the company over the past year 
with  some  discussion  or  examples  perhaps  of 
how  that  has  fitted  in  with  the  overall  strategy 
or objectives. 

Quantitative 
data 
reported 

Best  practice  would  be  some  data  or  statistics 
that  detail  risk.  Again  usually  found  in  the  Risk 
section of reports. 

5 = a very detailed discussion of both strategy and 
objective 
4= a detailed discussion of both 
3= detailed but maybe missing discussion on strategy 
or objectives 
2 = lacking detail 
1= little or no discussion 

5 = a very detailed discussion of previous years’ risk 
management 
4= a detailed discussion  
3= detailed but maybe missing some specifics 
2 = lacking detail 
1= little or no detail 

5 = very detailed data covering a wide range of areas 
4= detailed data covering some areas 
3= detailed data but missing some areas 
2 = some data 
1= little or no data 

Corporate 
Governance 

Board 
Structure 
and 
members 

Board 

Best  practice  would  be  an  outline  of  the 
structure of the board and its committees. Also 
a  detailed  biography  of  each  board  member.  A 
record  of  attendance  of  board  members  at 
meetings  is  also  a  plus.  Information  usually 
found in a Corporate governance section or in a 
summary at the start of a report. 

5 = a very detailed description of the board structure 
and board members 
4= a detailed discussion and some biographies of 
board members 
3= detailed but maybe missing some specifics 
2 = lacking detail 
1= little or no detail 

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Reporting Area 

Notes for scoring 

Score scale 

Discussion of 
corporate 
strategy 

Non-
Financials 

Discussion of 
future 
or 
planned 
investments 

Best practice would be a detailed description of 
the overall strategy for the company in years to 
come.  Usually  outlined  in  the  Chief  executive's 
Summary or Chairman's Report. May also be in 
a separate section dedicated to a discussion on 
overall strategy. 

Best practice would be a discussion on areas or 
markets  that  the  bank  is  looking  to  invest  into 
in  future  years.  Also,  more  specific  discussions 
of  investments  here  rather  than  an  overall 
strategy  (that  is  covered  by  the  corporate 
strategy  metric).  Future  investments  may  be 
mentioned  in  chief  exec  reports  or  in  financial 
review sections when looking at business units. 
May also be scattered throughout the report. 

5 = a very detailed description of corporate strategy 
4= a detailed discussion  
3= detailed but maybe missing some specifics 
2 = lacking detail 
1= little or no detail 

5 = a very detailed description of planned investments 
4= a detailed discussion  
3= detailed but maybe missing some specifics 
2 = lacking detail 
1= little or no detail 

Employee 
satisfaction 

Best  practice  would  be  a  discussion  of  some 
measure  of  how  well  employees  view  the 
business. Perhaps survey results or a discussion 
on  how  to  improve  employee  opinions  of  the 
business etc. 

5 = a very detailed review of employee opinion 
4= a detailed discussion of employee opinion 
3= some discussion  
2 = mentions employees but no real detail 
1= very little or no detail 

Customer 
satisfaction 

Similar  to  above  except  for  customers.  For 
example, survey results or a discussion on how 
they are looking to improve public image etc. 

5 = a very detailed review of customer opinion 
4= a detailed discussion of customer opinion 
3= some discussion  
2 = mentions customers but no real detail 
1= very little or no detail 

Discussion of 
corporate 
responsibility 
/ 
sustainability 
/ 
environment 

Best practice would be a detailed discussion on 
these  areas.  Can  be  mentioned 
in  Chief 
Executive  report  or  there  may  be  a  section 
dedicated  to  looking  at  these  sorts  of  areas. 
More detail and looking at more areas should be 
marked higher here.  

5 = detailed look at all these issues 
4= a detailed look at two of these issues or very 
detailed of one at least 
3= some discussion of one or two of the issues 
2 = brief mentions 
1= no real discussion 

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Reporting Area 

Notes for scoring 

Score scale 

Market 
Share 

Market share 
data 

Regional 
Breakdown 

Regional 
Breakdown 
data 

Shareholder 
Returns 

Shareholder 
returns data 

Best practice would be a detailed explanation of 
the  company's  market  share  in  different  areas, 
either  geographical  or  business  unit.  Can  be 
mentioned  sporadically  throughout  the  report. 
Sometimes  if  there  are  reviews  by  heads  of 
business  units  then  they  may  discuss  market 
share.  Also  there  should  be  as  much  data  as 
possible rather than just a vague discussion. 

In the financial review section the results will be 
segmented  to  a  certain  degree  but  it  can  vary. 
Some  will  break  down  and  discuss  results  by 
business  unit,  others  will  do  by  a  broad 
geographic unit (e.g. Europe), some may break 
down  results  by  individual  countries.  Best 
practice  would  be  granular  data  at  the  country 
level;  additional  business  unit  information  is  a 
plus. 

5 = broken down into individual countries and 
business units 
4= broken down into geographical region 
3= broken down by business unit 
2 =some mention of market share 
1= very little or no mention of market share 

5 = broken down into individual countries and 
business units 
4= broken down into geographical region 
3= broken down by business unit 
2 = broken down into broad business 
1=not broken down 

returns.  Usually 

The  report  should  include  information  about 
in  a 
shareholder 
summary  at  start  or  in  the  financial  review 
section.  Can  also  give  comparisons  against 
other companies and how returns have changed 
over time.  

found 

5 = very detailed and some form of comparisons 
4= detailed and maybe some comparisons 
3= discussed in some detail 
2 = some/little discussion 
1= not discussed 

Growth 
Targets 

Specific 
targets 
out 

set 

Best  practice  would  be  a  clear  exposition  of 
specific  targets  that  the  company  is  looking  to 
hit in the years ahead. May be key performance 
indicators or something similar. Could be found 
in financial review, summary section at start or 
Chief  execs  review  or  may  even  have  a 
separate section.  

5 = key targets laid out clearly and in detail 
4= key targets laid out clearly 
3= some targets laid out 
2 = targets briefly discussed 
1= no targets laid out 

September 2014   

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General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Reporting Area 

Notes for scoring 

Score scale 

Discussion of 
how 
to 
achieve 
targets 

Best  practice  would  be  a  discussion  of  how  the 
business has tried to achieve the targets in the 
past  year  or  how  they  will  try  to  achieve  them 
in future years 

Overall  

General 
Presentation 
and  ease  of 
use 

Best  practice  would  be  a  report  that  is  easy  to 
navigate  around  and  find  information.  Also 
looking for good use of graphics and charts that 
highlight key information.  

5 = a very detailed and specific description of how 
targets will be achieved  
4= a detailed discussion  
3= some detail but maybe missing some areas 
2 = lacking detail but some sort of discussion 
1= little or no discussion 

5 = Excellent graphics, easy to navigate 
4= some good graphics, quite easy to navigate 
3= decent graphics, can navigate ok 
2 = lacking graphics and not easy to navigate 
1=poor use of graphics and hard to find information 

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 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Appendix 1.4 Disclosure quality score summary statistics 
Table 23 shows the descriptive statistics for the disclosure quality scores each year from 2000 to 
2013.  

Table 23: Descriptive statistics of total disclosure quality scores over time 

Mean 

Median 

2000 

2001 

2002 

2003 

2004 

2005 

2006 

2007 

2008 

2009 

2010 

2011 

2012 

2013 

31.68 

34.84 

35.30 

36.33 

37.46 

38.38 

40.53 

42.52 

43.36 

44.04 

44.62 

45.32 

45.96 

47.06 

Source: PwC analysis

32.00 

34.00 

36.00 

37.00 

39.00 

40.00 

42.00 

42.00 

42.00 

43.00 

46.00 

46.50 

45.50 

47.00 

Min 

15.00 

17.00 

20.00 

22.00 

20.00 

22.00 

22.00 

23.00 

28.00 

29.00 

16.00 

26.00 

30.00 

29.00 

Max 

46.00 

51.00 

50.00 

46.00 

50.00 

49.00 

52.00 

59.00 

58.00 

58.00 

60.00 

70.00 

69.00 

69.00 

Standard Deviation 

9.43 

9.92 

9.15 

8.46 

9.35 

9.09 

9.34 

10.11 

8.92 

9.43 

9.85 

10.00 

10.29 

10.19 

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 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Appendix 1.5 GMM methodology tests 
In general, to ensure that our findings do not suffer from endogeneity, we use two different tests 
on whether a possibly endogenous regressor can be treated as exogenous. We use the statistical 
software  Stata  to  conduct  our  econometric  analysis  and  explain  these  issues  with  reference  to 
the commands in Stata that can be used to carry out relevant tests. 

The  first  test  of  exogeneity  we  use  is  by  Davidson  and  MacKinnon  (1993)  which  has  been 
adapted  for  use  in  a  panel  data  context  by  Baum  and  Sillman  (1999),  through  the  “dmexogxt” 
procedure  following  Stata’s  “xtivreg”.  A  key  issue  with  this  method  is  that  the  fixed  effects 
instrumental  variable  (IV)  estimator  available  from  Stata’s  “xtivreg”  imposes  the  constraint  of 
constant correlation of individual observations within group (Baum, Shaffer and Stillman, 2003). 
As Hoxby and Paserman (1998) demonstrate, however, the presence of intra-cluster correlation 
can readily cause a standard over-identification statistic to over-reject the null.  

We also use a second test based on the endogenous option of Stata’s “ivreg2” procedure which 
can  report  test  statistics  that  are  robust  to  various  violations  of  conditional  homoscedasticity. 
Each  model  is  then  specified  accordingly  based  on  both  evidence  gathered  from  our  literature 
review and on our endogeneity test results.  

Using two distinct tests for endogeneity in our analysis does come at a cost. In some cases, we 
obtain  conflicting  results  between  the  two  tests  as  a  given  explanatory  variable  is  found  to  be 
endogenous  or  exogenous  depending  on  the  test  we  use.  In  such  a  situation,  we  adopt  the 
following approach: 

• 

• 

• 

We first treat the variable as exogenous, and change our estimator and model specification 
accordingly. 
We next treat the variable as endogenous and use the IV estimator depending on our 
modelling context. 
We then use a number of key diagnostic statistics to choose, where possible, the most 
robust model. 

There  is  an  argument  that  there  might  be  forward  looking  expectations  within  the  aviation 
industry. If this is true, such forward looking expectation will be detected by our endogeneity test 
and  subsequently  dealt  with.  Although  the  endogeneity  tests  cannot  tell  us  what  is  causing  the 
observed endogeneity problem, they can nevertheless identify any endogeneity caused. 

September 2014   

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 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Appendix 1.6 Cost of equity estimation methods 
The table below sets out the four implied cost of equity capital methods used in our approach to estimate the impact of disclosure quality 
on the cost of equity capital: 

Method 

Description 

Advantages 

Disadvantages 

Claus  and  Thomas 
(2001) 

This  model  is  based  upon  the  residual  income  valuation  model, 
which  derives  the  expected  future  residual  income  series. 
Residual  income  is  forecasted  earnings  per  share  up  to  5  years 
ahead, minus a cost of capital charge for book value of equity per 
share  at  the  beginning  of  the  fiscal  year.  After  the  fifth  time 
period,  the  model  assumes  that  residual  income  grows  at  a  rate 
equal  to  expected  inflation,  g;  a  proxy  of  median,  country-
specific,  one-year  ahead  realised  monthly  inflation  rates  is  used. 
is 
A 
clean 
assumed, 
whereby 
future  book  values  are 
from  current 
imputed 
book  values,  forecasted  earnings  and  dividends.  (Daske  et  al., 
2007).  

surplus 

Time-varying  discount 
rates  can  be  calculated 
by splitting the discount 
factor 
risk 
premium  and  risk-free 
rate (Schroder, 2007) 

into 

the 

Confusing  results  are 
generated  if  the  book 
value  of  equity  exceeds 
its market capitalisation 
(Schroder, 2007) 

and 

Ohlson 
Juettner-
Nauroth 
(2005)/Gode 
and  Mohanram 
(2003) 

This model is based upon the abnormal earnings growth valuation 
model  and  uses  one-year  ahead  forecasted  earnings  and 
dividends  per  share  to  determine  the  expected  price.  To  yield  a 
logical numerical solution, the change in forecasted earnings must 
be  positive;  this  permits  zero  expected  dividends  for  any  period. 
It  is  assumed  that  the  growth  of  abnormal  earnings  per  share, 
beyond  the  first  year,  is  equal  to  the  expected  rate  of  inflation, 
which  is  calculated  as  the  country-specific  median  of  one-year-
ahead realised monthly inflation rates; this sets a lower bound to 
the cost of equity capital estimates. (Daske et al., 2007). 

Does  not  rely  on  a 
dividend 
pay-out 
parameter. Permits zero 
expected  dividends  for 
any  number  of  future 
periods.  Provides  risk 
premium  estimates  that 
the  market’s 
reflect 
perception 
risks 
(Ohlson and Gao, 2006) 

of 

the 

in 
Usefulness 
measuring 
risk 
premium  is  empirically 
debatable  (Gode  and 
Mohanram, 2003) 

September 2014   

122 

 
 
 
 
  
 
 
 
 
 
 
 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Method 

Description 

Advantages 

Disadvantages 

Easton (2004) 

This model is based upon the abnormal earnings growth valuation 
model.  Abnormal  earnings  growth  is  calculated  using  one-  and 
two-year  ahead  earnings  per  share  forecasts  and  expected 
dividends per share. The model assumes that growth in abnormal 
earnings  continues  infinitely  after  the  initial  period.  Again,  this 
model  requires  the  change  in  forecasted  earnings  to  be  positive. 
(Daske  et  al.,  2007).  This  method  simultaneously  estimates  the 
implied  market  expectation  of  the  rate  of  return  and  the  implied 
market expectation of the long-run change in abnormal growth in 
earnings.  

growth 

Isolates  the  respective 
roles of: forecasts of the 
next period’s accounting 
forecasts  of 
earnings, 
short-run 
in 
accounting earnings and 
expected 
in 
earnings 
accounting 
beyond 
short 
forecast 
horizon 
(Easton, 2004). 

growth 

the 

expected 
PE 
ratio, 
abnormal  growth 
in 
earnings  and  expected 
in 
change 
long-run 
in 
abnormal  growth 
earnings 
all 
are 
interdependent, 
in 
resulting 
(Easton, 2004). 

bias 

Where,  

= Market price of a firm’s stock at date t 

= Book value per share at the beginning of the fiscal year 

= Expected future book value per share at date t + τ, where 

 = 

 + 

 - 

= Expected future earnings per share for period (t + τ-1, t + τ) using wither explicit analyst forecasts or future earnings 

derived from growth forecasts, 

 respectively 

= Expected future net dividends per share for period (t + τ-1, t + τ), derived from the dividend pay-out ratio times the 

earnings per share forecast, 

= Expected (perpetual, short-term or long-term) future growth rate 

=  Implied  cost  of  capital  estimates,  calculated  as  the  internal  rate  of  return  solving  the  above  valuation  equations 
respectively 

September 2014   

123 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Appendix 1.7 Logistic regression interpretation and results using odd ratios 
The table below sets out odd ratios for the individual specifications.  

Table 24: Results for individual the impact of disclosure quality on earnings management using individual disclosure scoring 
components (coefficients presented as odds ratios) 

Earnings 
Management 

Total disclosure 
Score 

Regional 
Breakdown 
score 

Corporate 
Governance 
score 

Risk 
management 
score 

Non-Financials 
score 

Targets Score  Market Share 

score 

Shareholders 
Return score 

Total disclosure score 

Regional 
score 

breakdown 

Corporate  governance 
score 

Risk 
score 

management 

Non-financials score 

Targets score 

Market share score 

Shareholder 
score 

returns 

Log of sales 

Sales growth 

Stock growth 

Leverage 

Liabilities growth 

Sales/assets 

-0.0353* 
(0.087) 

-0.3148* 
(0.069) 

-0.2639*** 
(0.008) 

0.0127 
(0.792) 

-0.0777 
(0.111) 

0.1211 
(0.527) 

1.2289** 
(0.032) 

-0.3135 
(0.246) 

0.0201 
(0.22) 

0.4056 
(0.456) 

0.0211 
(0.907) 

1.2183** 
(0.031) 

-0.2794 
(0.301) 

0.0203 
(0.231) 

0.4029 
(0.45) 

0.1143 
(0.527) 

1.2747** 
(0.024) 

-0.3085 
(0.262) 

0.0225 
(0.175) 

0.2585 
(0.654) 

-0.0256 
(0.892) 

1.214** 
(0.029) 

-0.2677 
(0.32) 

0.0217 
(0.204) 

0.3921 
(0.456) 

0.067 
(0.712) 

1.2145** 
(0.032) 

-0.2987 
(0.26) 

0.0184 
(0.243) 

0.3834 
(0.471) 

-0.0581 
(0.505) 

-0.0027 
(0.988) 

1.224** 
(0.028) 

-0.2712 
(0.313) 

0.0218 
(0.203) 

0.3846 
(0.471) 

0.0221 
(0.876) 

-0.0145 
(0.936) 

1.216** 
(0.029) 

-0.268 
(0.321) 

0.0222 
(0.205) 

0.398 
(0.45) 

-0.0686 
(0.591) 

0.0084 
(0.964) 

1.2114** 
(0.031) 

-0.2843 
(0.293) 

0.0221 
(0.207) 

0.4078 
(0.439) 

-31.6411*** 
(0.000) 

-29.661*** 
(0.000) 

-30.436*** 
(0.000) 

-28.374*** 
(0.001) 

-29.5019*** 
(0.000) 

-29.5854*** 
(0.000) 

-28.8274*** 
(0.000) 

-29.1991*** 
(0.000) 

September 2014   

124 

 
 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 General assessment of potential economic consequences of country-by-country reporting under CRD IV 

Earnings 
Management 

Total disclosure 
Score 

Regional 
Breakdown 
score 

Corporate 
Governance 
score 

Risk 
management 
score 

Non-Financials 
score 

Cash flow operations 

No. of exchanges 

US listing 

Close shares 

IFRS dummy 

Constant 

Number of obs 

Country fixed-effects 

Wald chi2(27) 

Prob > chi2 

4.8487 
(0.277) 

0.0102 
(0.921) 

-0.188 
(0.693) 

-2.324*** 
(0.000) 

-1.0484** 
(0.022) 

1.8907 
(0.558) 

503 

Yes 

92.02 

0 

5.4815 
(0.228) 

0.0686 
(0.527) 

-0.2557 
(0.6) 

5.3104 
(0.247) 

-0.01 
(0.923) 

-0.1525 
(0.745) 

4.9211 
(0.274) 

0.0172 
(0.867) 

-0.207 
(0.665) 

4.7952 
(0.286) 

-0.01 
(0.922) 

-0.1384 
(0.769) 

4.8389 
(0.279) 

0.0191 
(0.852) 

-0.2078 
(0.662) 

Targets Score  Market Share 

score 

4.9358 
(0.272) 

0.019 
(0.853) 

-0.2031 
(0.672) 

Shareholders 
Return score 

5.0033 
(0.267) 

0.0185 
(0.858) 

-0.2309 
(0.634) 

-2.6298*** 
(0.000) 

-2.3191*** 
(0.000) 

-1.0251** 
(0.027) 

-1.0012** 
(0.028) 

-2.2487*** 
(0.000) 

-1.1693*** 
(0.01) 

-2.3945*** 
(0.000) 

-2.1423*** 
(0.001) 

-2.2216*** 
(0.001) 

-2.2951*** 
(0.000) 

-1.0676** 
(0.018) 

-1.1257** 
(0.013) 

-1.1555** 
(0.012) 

-1.1508** 
(0.011) 

2.7052 
(0.404) 

503 

Yes 

88.71 

0 

2.407 
(0.449) 

503 

Yes 

95.39 

0 

2.7083 
(0.404) 

503 

Yes 

89.48 

0 

1.9291 
(0.548) 

503 

Yes 

93.07 

0 

2.7047 
(0.4) 

503 

Yes 

91.32 

0 

2.6329 
(0.415) 

503 

Yes 

89.28 

0 

2.4661 
(0.449) 

503 

Yes 

88.72 

0 

*** Significant at the 1% level; ** Significant at the 5% level; *Significant at the 10% level 

Source: PwC analysis  

The  odds  ratio  indicates  the  probability  of  a  “success”  outcome  (in  this  context,  where  the  dependent  variable  is  1,  indicating  the 
presence of earnings management) divided by the probability of a “failure” outcome (where the dependent variable is 0, indicating the 
absence of earnings management). A coefficient value of less than 1 indicates that an increase in the explanatory variable it is less likely 
for earnings management to occur, and a value exceeding 1 indicates that it is more likely to occur. For example, the coefficient on the 
regional  breakdown  score  indicates  that  an  increase  in  the  score  of  one  unit  means  that  earnings  management  is  0.73  times  likely  to 
occur, meaning that it is less likely to occur. This could also be interpreted to mean that an increase in the score of one unit means that 
banks are 27% (1-0.73=27%) less likely to manage earnings. 

September 2014   

125 

 
 
 
 
 
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CRD IV 

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Appendix  2  –  Detailed  results  from  the  stakeholder 
survey 

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CRD IV 

How  strongly  do  you  agree  that  Article  89  is  justified  as  a  reporting 
requirement and serves a legitimate public interest? 

32 out of 35 respondents answered the question 

Non-business  respondents  were  more  positive  than  business  respondents  that  Article 
89 is in the public interest 

While  three  quarters  of  respondents  either  agreed,  or  neither  agreed  nor  disagreed, 
with  the  statement,  there  was  a  split  between  business  and  non-business,  with  non-
business respondents more likely to agree with the statement. 

Of the non-business respondents, two strongly agreed with the statement, ten agreed 
with the statement, three neither agreed nor disagreed and one disagreed. 

There was a wider range of views among the business respondents with one strongly 
agreeing  with  the  statement,  two  agreeing,  three  disagreeing,  one  strongly 
disagreeing and the remaining nine neither agreeing nor disagreeing. 

A number of contributors felt that the public interest would be better served by having 
legislation  that  could  be  consistently  applied  across  all  Member  States  and  business 
contributors  expressed  concerns  that  the  data  to  be  provided  would  not  be  easily 
understood by the general public. One trade association regretted that there had not 
been time for a full consultation including preparers and auditors of the information to 
create effective legislation. 

A couple of contributors were of the view that while the concept of transparency was a 
positive  one,  they  were  not  convinced  that this  measure  helped  to  achieve  it.  It  was 
also  noted  that  in  some  Member  States  the  legislation  would  only  apply  to  a  small 
number of institutions. 

Only one bank expressed concerns around the confidential nature of some of the data 
to be made public, particularly with regard to the disclosure of profit or loss before tax 
and  of  public  subsidies  received.  The  bank  noted  that  the  required  form  of  the 
disclosure  was  not  in  line  with  those  required  under  its  accounting  policies  and  so 
would  not  reflect  the  view  of  management.  The  bank  was  therefore  concerned  about 
full  public  disclosure  and  recommended  that  the  Commission  allow  reporting  entities 
to include information on how the disclosure would differ from figures reported in the 
consolidated financial statements. 

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One  CSO  expressed  a  clear  view  that  the  reporting  was  in  the  public  interest  as  the 
disclosures  would  “enable  the  public  to  make  an  informed  judgement  about  a 
company’s  contribution  to  the  society  in  which  it  operates.  They  can  help  flag  up 
corruption  risks  by  shedding  light  on  any  special  arrangements  between  companies 
and  governments.  They  can  improve  the  oversight  exercised  by  authorities.  They 
allow  investors  to  gain  an  insight  into  the  political  risks  a  company  faces  and  the 
sustainability  of  its  tax  strategy”.  The  concerns  raised  by  many  about  the  lack  of 
consistency  in  the  implementation  of  the  regulations  and  the  consequent  risk  of 
misinterpretation of the data would seem to put at risk the usefulness of the data for 
the purposes outlined by this CSO 

One  bank  felt  that  the  public  interest  was  not  best  served  by  having  the  disclosure 
requirement  included  within  CRD  IV  which  is  primarily  focussed  on  prudential 
regulation.  Indeed,  the  confusion  between  prudential  and  accounting  bases  of 
preparation of the data gives rise to some of the confusion described elsewhere in this 
report.  The  bank  was  of  the  view  that  the  public  interest  would  be  better  served  by 
extending  the  disclosure  requirements  to  all  public  companies  and  not  just  those  in 
the FS sector. 

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CRD IV 

What  sort  of  impact  will  Article  89  have  on  the  willingness  of  institutions  to 
be (or to stay) established within the EU? 

32 out of 35 respondents answered the question 

78% of respondents were of the view that Article 89 would not affect the willingness 
of reporting institutions to remain in the EU 

Several of those who felt that there would be no impact in this regard noted that while 
Article 89 created an extra burden for companies, it would not be significant enough to 
affect the willingness of businesses to remain in the EU. It was felt that other factors 
were far more important for businesses when determining where to locate. 

One regulator felt that additional transparency would increase public confidence in the 
financial  sector  thereby  making  the  EU  a  more  attractive  place  for  companies. 
Similarly,  one  CSO  felt  that  the  additional  disclosure  would  increase  investor 
confidence, 
increase  the  attractiveness  and 
competitiveness of EU banks. 

lower  the  cost  of  capital  and 

One business organisation noted that non-EU headquartered groups would be affected 
differently  from  EU  headquartered  groups  and  that  the  structure  of  groups  would 
affect  the  extent  to  which  they  were  affected  by  the  legislation.  The  impact  of  the 
legislation  was  however  unlikely  to  cause  companies  to  cease  doing  business  in  the 
EU. 

Of  the  four  organisations  predicting  a  negative  impact,  one  was  a  financial  regulator 
and the other three were financial institutions. One of these financial institutions was 
concerned  that  the  information  would  be  misunderstood  as  there  were  likely  to  be 
inconsistencies with the group accounts and with the local statutory accounts on which 
tax calculations are based. 

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What sort of impact will Article 89 have on the competitiveness of reporting 
institutions,  particularly  as  against  non  EU  parented  groups,  who  may  be 
wholly or partially exempt from the requirement? 

30 out of 35 respondents answered the question  

53% of respondents felt that Article 89 would have no impact on the competitiveness 
of EU institutions, over a quarter felt it would be negative. 

The  majority  of  respondents  felt  that  Article  89  would  have  no  impact  on  the 
competitiveness  of  EU  institutions.  Seven  business  organisations  and  one  financial 
regulator thought the impact would be negative, while two regulators, two CSOs and 
one trade association felt it would be positive. 

Those  with  a  negative  view  were  mainly  concerned  the  legislation  would  mean  that 
there was no level global playing field given the absence of similar regulations in other 
financial centres. 

One  of  those  with  a  negative  view  referred  to  current  global  initiatives,  a  view  that 
was shared by another respondent who felt that the OECD’s BEPS project would have 
a greater effect.   

Other  contributors  with  a  negative  view  noted  that  non-EU  institutions  could  face 
problems  with  applying  the  legislation.  This  view  was  shared  by  another  business 
organisation  which  noted  that  it  would  expect  the  cost  to  be  proportionately  greater 
for non-EU institutions reporting on their EU operations. 

One  CSO  expressing  a  positive  view  noted  that  a  number  of  companies  are  already 
making  CBCR  disclosures  and  that  it  was  hard  to  see  that  their  competitiveness  had 
been eroded.  It also commented that the need to disclose would encourage banks to 
consider political risk more carefully thereby increasing competitiveness and reducing 
corruption.

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What  sort  of  impact  will  Article  89  have  on  the  investment  in  reporting 
institutions,  e.g.  the  availability  of  capital  markets  funding,  and  decisions 
whether or not to invest in institutions in the EU? 

32 out of 35 respondents answered the question. 

62%  of  respondents  felt  that  Article  89  would  have  no  impact  on  investments  into 
reporting institutions. 

The majority of respondents felt that Article 89 would have no impact on the decisions 
of  investors  whether  or  not  to  invest  in  reporting  institutions,  while  three  business 
organisations and five non-business organisations felt the impact would be positive. 

The one CSO with a strongly positive view felt the disclosure would allow investors to 
understand  where  businesses  operate  and  the  associated  political  risks.  This  would 
lead to better risk management by institutions. 

Two  organisations  with  a  positive  view  noted  that  investors  are  increasingly 
considering factors such as sustainability and transparency in investment decisions. 

Of  those  expecting  no  impact,  it  was  noted  that  the  disclosure  may  attract  more 
investment  from  socially  responsible  investors,  but  the  effect  was  expected  to  be 
minimal.  Another  view  was  that  negatively  perceived  disclosures  could  lead  to 
customer  revolt,  making  investment  less  attractive;  this  was  not  expected  to  have  a 
significant impact. A general view was that investment decisions were based on other 
factors other than the data to be disclosed under Article 89. 

Finally, it was noted that institutions applying for funding on the capital markets have 
already to provide more information than is required by Article 89. 

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What  sort  of  impact  will  Article  89  have  on  the  investment  by  reporting 
institutions, and decisions as to whether to invest in the EU or not?  

31 out of 35 respondents answered the question 

81%  of  respondents  felt  that  Article  89  would  have  no  impact  on  investments  by 
reporting institutions 

The  vast  majority  of  respondents  felt  that  Article  89  would  have  no  impact  on  the 
investment  decisions  of  institutions  and  in  particular  whether  or  not  to  invest  in  the 
EU. 

Two  non-business  organisations  and  one  business  organisation  felt  there  might  be  a 
positive  impact  with  one  of  them  expressing  the  view  that  the  increased  information 
could aid investment decisions. 

A couple of those who felt there would be no impact commented that there were other 
more important factors in investment decisions. One trade association noted that the 
lack  of  a  level  playing  field  could  make  the  EU  less  attractive,  but  nevertheless  no 
impact was foreseen. 

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What sort of impact will Article 89 have on the provision of credit to reporting 
institutions,  e.g.  the  effect  on  the  cost  of  debt/equity,  cost  of  obtaining 
wholesale loan finance? 

30 out of 35 respondents answered the question  

73  %  of  respondents  felt  that  Article  89  would  have  no  impact  on  the  availability  of 
credit to reporting institutions 

Five  non-business  organisations  felt  that  there  would  be  a  positive  impact.    One 
commented  that  the  increased  transparency  could  improve  confidence  in  reporting 
institutions,  while  another  pointed  to  transparency  leading  to  a  better  understanding 
of company risk and therefore better risk management and lower levels of risk in the 
longer term. 

One credit institution felt that there may be a negative effect as the disclosures were 
likely  to  be  misunderstood  by  many  readers  of  the  disclosures  potentially  leading  to 
negative sentiments. 

One regulator noted that far more information than is required by Article 89 is usually 
provided by institutions seeking loan finance. 

One  business  organisation  commented  that  the  information  on  public  subsidies  could 
lead  to  a  perception  of  a  bank  being  “propped  up”,  leading  to  increased  costs  of 
wholesale funding. Overall however the organisation felt there would be no impact. 

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What  sort  of  impact  will  Article  89  have  on  the  provision  of  credit  by 
reporting  institutions  considering  the  level  of  financial  services  provided,  as 
well  as  the  price  and  quantity  of  credit  available  to  businesses  and 
households? 

30 out of 35 respondents answered the question 

90%  of  respondents  felt  that  Article  89  would  have  no  impact  on  the  provision  of 
credit by reporting institutions 

The  vast  majority  of  respondents  felt  that  Article  89  would  have  no  impact  on  the 
provision of credit by reporting institutions while two non-business organisations felt it 
would have a positive impact and one business organisation felt that there would be a 
negative impact. 

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CRD IV 

What    sort    of  impact  will  Article  89  have  on  the  stability  of  the  financial 
services sector in the EU e.g. any effect on financial market volatility from the 
change in disclosure requirements 

33 out of 35 respondents answered the question. 

76 % of respondents felt that Article 89 would have no impact on the stability of the 
financial services sector. 

Two  credit  institutions  felt  that  there  would  be  a  negative  impact  with  one  of  them 
mentioning that the availability of detailed information could affect interbank lending. 

One  business  and  five  non-business  organisations  expect  a  positive  impact,  with  one 
commenting  that  increased  disclosure  would  increase  confidence  and  reduce  market 
volatility. One CSO expected a positive impact as they felt the disclosures respond to 
the  demands  of  investors  and  CSOs,  while  another  CSO  felt  that  there  would  be 
increased  trust  in  the  market  as  more  transparency  would  lead  to  better 
understanding and better management of risks. 

One  comment  from  those  expecting  no  impact  was  that  while  individual  businesses 
may experience volatility, this would not affect the sector as a whole.  Another noted 
that volatility was due to a number of causes and it would not be possible to identify 
volatility arising solely from Article 89 disclosures. 

Finally, one business association noted that there may be some risk of the disclosures 
affecting the perception of the sector, but they still did not expect a noticeable impact. 

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CRD IV 

What  sort  of  impact  will  Article  89  have  on  the  transparency  and 
accountability  of  reporting 
institutions  towards  their  consumers  and 
investors? 

33 out of 35 respondents answered the question 

55%  of  respondents  felt  that  Article  89  would  improve  the  transparency  and 
accountability of reporting institutions 

One CSO thought Article 89 would have  a strongly positive impact as “CBCR enables 
investors  to  know  which  corporations  operate  in  tax  havens  and  in  highly  corrupt 
environments,  politically  unstable  regimes,  conflict  zones  and  other  sensitive  areas 
enabling  them  to  assess  their  political  and  other  risks  and  potential  return  on 
investment.”  

Thirteen  non-business  and  five  business  organisations  expect  a  positive  impact  on 
transparency  and  accountability.  Their  comments  included  views  that  it  would  be 
easier to obtain and compare data, that some stakeholders were requesting this data 
and that it would mean companies having to take more account of public opinion when 
considering their tax policies. 

Two non-business organisations and nine business organisations felt that there would 
be no impact on transparency and accountability. One of these business organisations 
commented: 

“We hope that the reporting will have a positive impact on the perceived transparency 
and accountability of relevant institutions but note that this will be hard to capture and 
measure  in  the  early  reporting.    Review  and  consideration  of  the  cost/benefit  of 
reporting  will  be  needed.  We  further  note  that  lack  of  proper  due  process  in  the 
development of the disclosure makes it difficult to establish if users' needs will be met, 
whether they will examine, and indeed understand, the information and therefore the 
benefits in terms of transparency and accountability will be limited.”  

Another  business  organisation  that  expected  no  impact  commented  that  flexibility 
should  be  given  to  institutions  in  preparing  their  disclosures  so  that  they  can  reflect 
the fiscal reality of the business and be transparent about the definitions and criteria 

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used.  Overly prescriptive criteria were thought likely to result in disclosures that were 
misleading and would generate meaningless “noise”. 

One regulator that expected no impact noted that this was because it “saw no merit in 
the CBCR requirements.” 

Another  business  organisation  felt  that  the  regulation  was  unlikely  to  lead  to 
transparency  as  it  did  not  provide  a  complete  picture  of  an  institution’s  activities, 
particularly  for  non-EU  headed  groups  and  could  lead  to  voluntary  reporting  to 
contextualise the required disclosures. 

The one business organisation that expected a negative impact referred to the lack of 
clarity around the requirements, the likely lack of consistency in implementation which 
could lead to negative perceptions of institutions and of the reporting system itself. 

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What sort of impact will Article 89 have on public confidence in the financial 
services  sector  in  the  EU  e.g.  the  effect  on  public  image  of  the  sector,  the 
demand for financial services, the trust that the public has in the sector? 

33 out of 35 respondents answered the question. 

42% of respondents felt that Article 89 would lead to greater public confidence in the 
financial services sector. A further 42% felt there would be no impact. 

Views  on  whether  Article  89  would  lead  to  increased  public  confidence  were  more 
mixed than those on whether it would improve transparency. 

Those  expecting  no  impact  were  largely  business  organisations,  with  four  business 
organisations  expecting  a  negative  impact.    Three  business  organisations,  and  all 
except one non-business organisation, expected a positive impact. 

Those  predicting  a  negative  impact  were  concerned  that  the  lack  of  clarity  in  the 
regulations, its potential to be implemented differently in different Member States and 
the  fact  that  it  may  not  present  a  complete  picture  would  lead  to  misunderstanding 
and misinterpretation of the data. This could lead to a reduction in public confidence. 

Others, some of whom felt the impact would be positive and some of whom expect no 
impact,  felt  that  of  itself  Article  89  would  have  little  impact,  but  it  might  have  an 
incremental  positive  effect  when  considered  alongside  other  changes  in  the  financial 
services  sector.  One  credit  institution  was  of  the  view  that  the  impact  would  be 
positive as CBCR data is requested by a number of stakeholders. Again, the risk that 
disclosures would be misunderstood was highlighted as a key risk. 

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What  sort  of  impact  will  Article  89  have  on  the  cohesion  of  the  EU’s  tax 
regimes  as  a  result  of  potentially  highlighting  the  practical  impact  of  tax 
competition between states? 

30 out of 35 respondents answered the question 

57 % of respondents felt that Article 89 would have no impact on the cohesion of the 
EU’s tax regimes 

A  number  of  respondents  had  a  similar  view  that  Article  89  might  highlight  some  of 
the differences between tax regimes in the EU, but that the lack of clarity in the rules 
and  inconsistent  application  of  the  rules  could  mean  that  the  differences  highlighted 
are meaningless, confusing or inappropriate.  

The  different  respondents  had  varying  views  as  to  the  strength  and  nature  of  the 
resultant  impact  with  one  non-business  organisation  thinking  it  might  lead  to 
harmonisation  while  another  non-business  organisation  felt  that  tax  competition 
between Member States was desirable. 

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Respondents  were  asked  to  comment  on  any  other  impacts  that  they 
expected  to  arise  from  Article  89.  Below  are  three  detailed  comments 
provided by business organisations. 

Respondents  from  business  are  concerned  that  the  lack  of  clarity  and  consistency 
around the regime will lead to confusion and misunderstanding  

“The  lack  of  consistency  across  country-by-country  reporting  initiatives  is  bad  for 
investors  and  stakeholders.    We  would  encourage  the  pursuit  of  regimes  that  are 
internationally consistent as well as consistent across sectors. “ 

“…due  to  the  lack  of  clarity  in  the  requirements  and  the  resulting  likelihood  of 
inconsistent application there is risk of increasing public misunderstanding or that the 
disclosures will be disregarded resulting in costs but no benefit. Given that there was 
not a proper impact study before the requirements were introduced or a due process 
to  ensure  that  the  requirements  themselves  were  understandable  and  worked  within 
the existing reporting regimes where, for example, sub-consolidations are not required 
if  the  group  consolidation  is  publicly  available,  it  seems  likely  that  the  administrative 
burden  will  outweigh  any  benefits  from  the  disclosures.  In  addition,  we  believe  that 
the question of whether the disclosure of public subsidies is in the wider public interest 
should be carefully considered since such disclosure could prove counterproductive in 
the event of a banking crisis.” 

“I believe that the rules will lead to greater confusion over the contribution a financial 
institution  makes  in  a  jurisdiction.    Disclosures  such  as  tax  paid  for  some  financial 
institutions  that  are  still  carrying  tax  losses  may  lead  to  a  zero  disclosure  whilst 
showing significant profits.  In addition where an institution has overpaid taxes in one 
year  and  receives  a  refund  in  the  subsequent  year  this  may  deliver  an  inaccurate 
message  to  the  reader.    This  is  likely  to  lead  to  a  misinterpretation  of  a  financial 
institutions  contribution  to  the  exchequer  and  therefore  further  disillusionment  with 
the financial sector.  

Whilst  compliance  with  Article  89  on  its  own  is  unlikely  to  be  excessively  onerous  on 
most financial institutions that are impacted, there is likely to be wider implications of 
compliance  for  example  a  financial  institution  may  be  cornered  into  making  further 
voluntary disclosures to prevent public misinterpretation, further institutions may need 
to provide reconciliations to other tax transparency agenda's such as the BEPS Action 
Plan - Action 13. Further where voluntary disclosures are made, this may led to new 
data  sets  being  collated  and  therefore  an  increase  in  costs  in  investing  into  systems 
and  reporting  capabilities.    From  a  social  perspective  the  disclosures  are  likely  to 
increase  confusion  over  the  way  financial  institutions  operate  and  the  tax  laws  that 
govern a financial institutions requirement to pay taxes, this again is likely to increase 
the lack of trust the public have in financial institutions.” 

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Respondents  were  asked  to  comment  on  any  other  impacts  that  they 
expected to arise from Article 89.  

One CSO believes that CBCR will lead to better risk management, less corruption and 
potentially greater tax compliance, commenting: 

“Country-by-country reporting of key financial information such as that listed in Article 
89  is  a  good  measure  of  a  multinational  company’s  commitment  to  a  culture  of 
transparency  and  dialogue  with  its  stakeholders.  In  addition,  these  disclosures  can 
deliver  real  benefits  for  citizens,  investors  and  governments  around  the  globe.  They 
enable the public to make an informed judgement about a company’s contribution to 
the  society  in  which  it  operates.  They  can  help  flag  up  corruption  risks  by  shedding 
light  on  any  special  arrangements  between  companies  and  governments.  They  can 
improve the oversight exercised by authorities. They allow investors to gain an insight 
into the political risks a company faces and the sustainability of its tax strategy. Such 
disclosures  also  have  a  deterrent  effect  on  tax  avoidance  The  benefits  of  a  detailed 
disclosure  regime  of  corporate  tax  payments  are  corroborated  by  an  analysis  of  US 
companies  that  shows  that  lowering  corporate  disclosure  requirements  directly 
prompts  companies  to  practice  more  tax  avoidance  and  reduce  their  tax  burden 
further, on average by an additional significant 4.8 percentage points (O. Hope, M. Ma 
et  al.  (2013):  “Tax  Avoidance  and  Geographic  Earnings  Disclosure”,  working  paper 
available at SSRN.com, May 28, 2013)” 

“CBCR  will  increase  awareness  of  financial  institutions'  tax  management  practices 
leading  to  greater  reluctance  to  operate  in  low  tax  jurisdictions  (see  also  recent 
research  cited  above).  CBCR  will  lead  to  greater  public  awareness  of  corporate  tax 
payments.  This  might  ultimately  lead  to  an  environment  of  greater  tax  compliance 
which  will  increase  public  money  available  for  economic  development.  Greater 
transparency  will  help  reduce  the  potential  for  corruption.  Key  financial  data  gives 
citizens the possibility to understand the activities of a particular financial institution in 
their country and to monitor the appropriateness of payments to governments.” 

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Respondents  were  asked  to  comment  on  any  other  impacts  that  they 
expected to arise from Article 89.  

Some  expect  the  disclosures  to  increase  public  pressure  on  business’s  tax 
arrangements, while others think it is too early to tell 

One business and one non-business organisation expected that there could be some 
effect on how businesses organise their tax affairs if the disclosures lead to increased 
public scrutiny and increased pressure from the public and shareholders. 

One regulator commented that it was too early to tell what the impact of Article 89 
would be.  

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Appendix 3 – Detailed issues arising from the 
transposition, implementation and interpretation of 
Article 89 

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Only half of Member States had implemented Article 89 by 30 June 
2014 

(cid:131)  Thirteen Member States had transposed Article 89 into domestic law as at 30 June 
2014.  A further four had partially transposed the law with it applying to either 
credit institutions or investment firms. 

(cid:131)  Of the remaining Member States, there is a mixture between those who have clearly 
indicated when Article 89 will be implemented and those where the authorities have 
given no indication of the timeframe. 

(cid:131)  In respect of the jurisdictions that have implemented the requirements, the 
common approach has been to copy and paste the wording of Article 89.  

(cid:131)  Despite this approach, there are a number of areas where member states have 

departed from the wording of Article 89 and implemented their own interpretation or 
altered the scope of the regime.  

(cid:131)  Only a limited number of territories have implemented local requirements that 

include additional detail beyond the wording of Article 89. 

(cid:131)  We set out on the following pages the key differences that we see in the 

interpretation and application of Article 89 across the EU. The differences arise 
through differences in transposition, differences in interpretation that have been 
noted by respondents to our surveys, differences that we have noted from public 
disclosures made by reporting institutions and from the confidential disclosures 
submitted by the 14 GSIBs to DG MARKT. 

Placing the reporting obligation on “institutions” means that the 
extent of reporting can be affected by group structures 

(cid:131)  Article 89 places the reporting obligation on the CRD IV regulated ‘institution’. At 

times this therefore results in groups being partially within the scope of the 
regulations and also often results in multiple reporting entities within the same 
‘group’.  

(cid:131)  In France, the regulations have broadened the scope to include not only institutions, 

but also non-institution holding companies, whilst the UK has also widened the 
scope of the regime to include optional reporting at a parent level. 

(cid:131)  Although most banking groups are regulated at the top holding company, and 

therefore are only required to report once for the worldwide group, not all banking 
groups are structured in this way.  

(cid:131)  The CBCR disclosure produced by [one GSIB] includes four separate tables, 
presumably representing four separate sub groups within the [GSIB] group. 

There remains uncertainty as to whether branches of third country 
institutions are within scope 

(cid:131)  EU branches of third country institutions are ordinarily outside the scope of CRD IV 
and therefore CBCR, although in some territories, branches are expected to comply 
with their jurisdiction’s CBCR requirements.  

(cid:131)  In some territories, the position remains unclear, however certain territories such as 
the UK, Denmark, Austria, Finland, Malta and Croatia have clarified that they remain 
outside the scope. 

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The audit requirement has been relaxed in some Member States for 
first year reports, but maintained for subsequent years 

(cid:131)  The audit requirement has not been applied to first year disclosures in a number of 

territories. 

(cid:131)  In many jurisdictions, it was unclear whether the requirement applied. 

(cid:131)  All territories that have implemented Article 89 have maintained the audit 

requirement for all subsequent reporting periods. 

There is a division in interpretation amongst Member States in respect 
of ‘tax on profit or loss’ 

(cid:131)  The interpretation of ‘tax on profit or loss’ has been interpreted inconsistently by 

Member States.  

(cid:131)  At one end of the spectrum, the UK and Belgium have defined the term as meaning 

corporate income taxes paid during the accounting period. At the opposite end, 
territories such as France, Austria and Malta have interpreted the term as meaning 
taxes accrued.  

(cid:131)  Of the territories that have not provided any guidance or clarity on how the term 

should be interpreted such as Denmark, Croatia and Finland, the consensus appears 
to be that the local regulations should be interpreted as meaning taxes accrued.  

(cid:131)  In addition, draft regulations in the Netherlands adopt an accruals based approach.   

(cid:131)  From some of the disclosures privately submitted by GSIBs to the European 

Commission, it is also noted that some disclosures simply include the term ‘tax on 
profit or loss’ but do not include an indication as to whether the disclosures are 
based on cash payments of tax or taxes accrued. 

(cid:131)  It is also noted that the GSIB disclosures include all of the examples below: 

⎯ ‘Tax on profit or loss’ 

⎯ ‘Current tax’ and ‘deferred tax’ 

⎯ ‘Tax paid / (received)’ 

⎯ ‘Tax on profit before tax’ 

⎯ ‘Corporation tax paid’ 

(cid:131)  20 of the respondents to our opinion survey expressed a view as to how the term 
‘tax on profit or loss’ should be interpreted. 16 organisations (5 credit institutions/ 
investment firms, 3 FS trade associations and 8 non-business organisations) 
indicated that the term should mean tax on an accruals basis and several mentioned 
it should be in line with the accounts. 4 organisations were in favour of cash tax (2 
business and 2 non-business organisations). 

(cid:131)  One business organisation felt that there were issues with both cash tax and an 

accruals basis approach, noting that cash tax does not always relate to the year in 
question and that the accrued tax charge included deferred tax which should 
perhaps be eliminated.  

(cid:131)  One non-business organisation expressed a wish for a cash basis, but without 

providing further detail while one regulator felt that it should be as defined by the 
local legislation. 

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Consolidation is an issue most Member States have not addressed, 
with most businesses and regulators preferring an accounting based 
approach 

(cid:131)  The term ‘on a consolidated basis’ has not been clearly defined by any of the 
territories who have implemented Article 89 to date and only a couple have 
explicitly relied on the definition in Article 3 (1) of CRR. 

(cid:131)  Without any further framework or guidance, there is uncertainty as to how intra-

group transactions should be accounted for when producing CBCR disclosures. For 
example, whether intra-group transactions should be consolidated on a group basis 
or on a country wide basis. 

(cid:131)  The UK regulations include the requirement to report ‘in accordance with accepted 
accounting standards on a consolidated basis’, while Austrian regulations adopt a 
similar approach.  

(cid:131)  Despite this, all other territories simply include the requirement to report ‘on a 

consolidated basis’.  

(cid:131)  The lack of any detailed framework creates challenges for institutions who are 

required to comply with the regime, and this can be illustrated by referring to the 
disclosures by the GSIBs which in some cases include consolidation adjustments and 
in others do not:  

⎯ [One GSIB] includes [amount] of consolidation adjustments, [one GSIB] 
includes [amount] and [one GSIB] includes [amount] of turnover within 
consolidation adjustments. 

⎯ [Seven GSIBs] do not separately disclose consolidation adjustments 

⎯ [One GSIB that included consolidation adjustments to turnover] also 

included consolidation adjustments to profit before tax of [amount] 
although no other submission included any such adjustments to profit before 
tax 

(cid:131)  Seven of the business organisations and three of the non-business organisations 

expressed a desire that consolidation should follow accounting rules whether those 
were local or international rules depending on which applied to the institution in 
question, 

(cid:131)  Three regulators were of the view that consolidation for these purposes should be 

read in the light of the definitions in CRR.  

(cid:131)  One respondent’s answer did not specifically address this point and the others 

provided no comment on the interpretation of the term. 

(cid:131)  One of the business organisations commented that as there were no clear guidelines 

as to how to deal with intra-group and intra-country transactions, there may be 
diversity in practice. 

In practice, most GSIBs have made their Article 89 disclosures on 
their websites, while legislation replicates the wording in the 
Directive. 

(cid:131)  Although many territories have not included any further guidance on the term 

‘where possible as an annex to the annual financial statements’, most have adopted 
the same wording in their local implementation.  

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(cid:131)  The exception is the UK, which has instead included the requirement that the 

disclosure be made publicly available. In practice, this allows institutions to either 
publish disclosures on a website or include within their financial statements. 

(cid:131)  There is however a distinction to be made between first year reporting, which was 
subject to a fixed reporting deadline, and subsequent reporting, which could be 
expected to align with existing financial reporting obligations. 

(cid:131)  Only four business and one non-business organisation responded to our survey 
questions on the location of disclosures. Three business organisations favoured 
disclosure on a website, while one intended to include it in its annual report. The 
one non-business organisation that expressed a view felt that the disclosure should 
be in the annual report and on a website. 

(cid:131)  It should also be noted that the location of the disclosure could affect the type of 
audit to which the data is subject. If it is included within the annual report then it 
could be included in the statutory audit report. If it is disclosed separately then it 
would have to be subject to a separate form of audit procedure. 

There is a difference of view as to how ‘public subsidies’ reportable 
under Article 89 should be defined 

(cid:131)  The definition of subsidies is not defined by most jurisdictions. However some 

territories have included guidance on this. The key questions which remain unclear 
in most territories are: 

⎯ Should the definition be limited to direct taxpayer support or should it 

include implicit support provided by central banks and other government 
bodies. 

⎯ Should public subsidies be reported on a cash or an accruals basis. 

(cid:131)  For example, in Finland, the definition adopted covers the total amount of capital 

grants received and loans as well as guarantees given by public entities.  

(cid:131)  In the UK, the government has included guidance that the definition should be 

limited to direct support by the government and should not include central bank 
interventions. 

(cid:131)  Of the GSIB disclosures, only [two GSIBs] have included any public subsidies. 

(cid:131)  [One GSIB] has included [amount] in respect of [country] 

(cid:131)  [One GSIB] has included [amount] the majority of which relates to [a guarantee 

provided by a city within an EU country].  

(cid:131)  There is a clear division in our opinion survey between business and non-business 

organisations as to how ‘public subsidies’ should be interpreted. 

(cid:131)  Five business organisations and one regulator preferred a limited definition based on 

cash support received, with another business preferring a definition of direct 
support. 

(cid:131)  Six non-business organisations preferred a broader definition that would reflect 

implicit government support. 

(cid:131)  One business organisation expressed the view that a wide definition including 

implicit support seemed unlikely to be workable in practice. 

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Some survey respondents have questioned whether ‘establishment’ 
refers to legal incorporation or location of activity 

(cid:131)  Where a definition of ‘establishment’ has been provided, it seems to have 

consistently been interpreted as meaning branch or subsidiary and there does not 
appear to be any inconsistent application by any particular jurisdiction.  

(cid:131)  A number of questions have however arisen in practice as can be seen from the 

responses to our opinion survey, 

(cid:131)  There appear to be a number of considerations as to how the term should be 

interpreted: 

⎯ Limited to subsidiaries and branches 

⎯ Based solely on legal incorporation 

⎯ Based on location of actual activity 

⎯ Based on taxable presence similar to a definition of permanent 

establishment 

(cid:131)  Most non-business organisations and some business organisations prefer a more 
legal definition based on the inclusion of companies and branches and looking at 
legal incorporation. 

(cid:131)  A number of business organisations would favour a definition that took into account 

the actual location of activities. One business organisation expresses the issues 
succinctly by saying: 

“We believe disclosure which allows entities to present the geographical substance 
of their business, not necessarily based on where they are legally incorporated, will 
be more useful, but may also be more ambiguous. Where there is not an alignment 
in the location of incorporate and economic activity, an explanatory narrative will 
certainly be required.” 

No definition of employees has been provided by most Member 
States, though survey respondents have expressed slightly differing 
views 

(cid:131)  Most territories have not provided any definition beyond the wording of Article 89. 

(cid:131)  Other territories such as the UK and Denmark have specified that employees should 

be reported with reference to contractual employment. This therefore excludes 
contractors and would ignore the effect of employees employed in one country, but 
who work in other countries. 

(cid:131)  Seven of the respondents favoured a strict definition based on contractual 

employment and potentially in line with other reporting requirements around 
headcount. A couple of these noted that a definition based on actually location of 
employment might present a more accurate picture of an institution’s activity, but 
felt it would be too complex to implement in practice. 

(cid:131)  Five business organisations expressed a wish that the requirement should be based 
on, or at least have flexibility to take account of, the location in which employees 
actually work. 

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Turnover is not a widely used term within the financial services 
industry, contributors prefer reporting in line with accounting 
standards 

(cid:131)  Although ‘turnover’ is not a widely used term in the financial services industry, most 

territories have not provided a detailed definition. 

(cid:131)  In the UK, the regulations and guidance provide that turnover should be consistent 
with that disclosed in financial statements. The UK Government has also stated that 
the general principle is that turnover should broadly represent net interest income, 
net fee income and other income, net of impairments. 

(cid:131)  In Austria the term ‘turnover’ has been defined and replaced in the local regulations 

as the term ‘net income from interest plus operating revenues’. 

(cid:131)  The total turnover figures included within the GSIB disclosures agree to those 

included within consolidated financial statements. 

(cid:131)  From the responses to our survey, there seems to be broad consensus that the term 
should be interpreted in line with an institution’s financial statements, though there 
seems to be some difference as to exactly which line in the financial statements 
should be used. 

(cid:131)  One regulator was of the view that ‘turnover’ should mean total revenue, while most 
others took the view that it should be net income before certain expenses, but it 
was not universally agreed which expenses should be included or excluded. 

(cid:131)  In contrast, profit or loss before tax appears to be a commonly understood term 

within the financial services sector that can, and should be, taken directly from an 
institution’s financial statements. 

Only a limited number of territories have included an exemption to 
prevent double reporting 

(cid:131)  The UK, France and Germany have all implemented an exemption to prevent 

institutions established in their territories that are themselves subsidiaries of other 
EU based institutions from having to report twice, provided the parent institution 
has complied with the regulations in their home territory.   

(cid:131)  All other territories have remained silent on this point, creating the possibility that 

institutions will be required to duplicate their reporting. 

(cid:131)  We note that Chapter 10 of the EU Accounting Directive on reports of payments to 
governments by the extractive and logging sectors has a provision that precludes 
double reporting and which could be used as a template. 

Name, nature of activities and geographical location has been 
interpreted differently by each of the GSIBs 

(cid:131)  The requirement to report ‘name, nature of activities and geographical location’ has 

not been prescribed in any additional detail in any jurisdiction. 

(cid:131)  Respondents to our survey were of the view that there should be little difficulty in 
interpreting this requirement, but we have seen that GSIBs have interpreted the 
requirement inconsistently in practice. 

(cid:131)  Whilst some GSIBs have included the ‘name’ of every legal entity in the disclosure, 
others have limited the disclosure to principal trading companies, whereas others 
have not named any legal entities 

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(cid:131)  In terms of the ‘nature of activities’, GSIBs have varied the level of detail they 

provide. On the one hand, some groups have included minimal descriptions, using 
terms such as ‘commercial banking’ and ‘retail banking’, whereas at the other end of 
the spectrum, Barclays included a more detailed description of their operations. 

(cid:131)  Jurisdictional location is not addressed by any of the Member States that have 

implemented the requirements so far.  

(cid:131)  It is not clear, without further discussion with GSIBs as to how they have assigned 
data, such as turnover, profits and taxes to jurisdictions. For example, where a 
branch is subject to tax locally and in its parent jurisdiction, how the tax is included 
in the CBCR disclosure is unclear. 

There is no consistent format or template for institutions to use 

(cid:131)  From the first year submissions made to the European Commission, and also from 

the publication of disclosures by other non-GSIB institutions across the EU, there is 
a large difference in the format and content of the publications.  

(cid:131)  Key differences include the level of detail, the context provided and the inclusion, or 

not, of additional voluntary disclosures.  

(cid:131)  Some organisations have provided context to their disclosures whereas others have 

simply reported the basic numbers and included no further information. 

(cid:131)  Another anomaly that is apparent from the first year disclosures, as well as from 
one survey respondent, is whether it is necessary to consolidate all the different 
activities into one disclosure or whether it is permissible to report by business unit. 

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Appendix  4  –  The  concept  of  deadweight  loss  from  a 
tax perspective 

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In basic economic terms, the equilibrium price and quantity that prevails in the market 
for  a  product,  including  a  banking  product,  is  determined  by  the  intersection  of  the 
market demand and market supply curves. We illustrate this graphically in below. 

Before the application of a tax, the quantity consumed in the market is shown as Q0 
and the equilibrium price as P0. Once a tax is applied, the market supply curve shifts 
upwards  by  the  amount  of  the  tax  (i.e.  suppliers  are  only  willing  to  supply  a  given 
quantity at a price which is higher by the amount of the tax). The equilibrium price for 
consumers (the market participants who buy the product) is now higher (P1), so they 
demand less of the product (Q1).  

As a result, consumer surplus (a measure of consumers’ welfare associated with trade 
in  this  product,  being  the  difference  between  what  they  are  prepared  to  pay  for  the 
product and what they actually pay) falls from the amount represented by areas 1, 2 
and 3 at equilibrium before the tax was imposed, to the amount represented by area 1 
only at the new equilibrium.  

At  the  same  time,  the  price  received  by  the  producer  (the  market  participants  that 
originate  or  sell  products)  falls  from  P0  to  ‘P1-tax’  and  therefore,  producer  surplus 
(the  counterpart  to  consumer  surplus,  and  hence  a  measure  of  producers’  welfare) 
falls from areas 4, 5 and 6 at the original equilibrium to area 6 at the new equilibrium. 

The government captures a portion of the consumer and producer surplus lost through 
tax receipts (areas 2 and 4) – this is essentially a transfer of welfare from producers 
and  consumers  in  this  market  to  government  or  taxpayers.  However,  some  of  the 
original  surplus  in  the  market  is  lost  entirely  –  represented  by  areas  3  and  5. 
Economists refer to this as a ‘deadweight loss’ – a loss of welfare to society, or a loss 
of economic output, caused by ‘distorting’ the market outcome through the imposition 
of a tax, and reducing the benefits of trade. 

Figure 8: Deadweight loss caused through application of indirect tax 

Price

P1

P0

P1 - tax

1

2

4

Producer surplus

6

3

5

Supply curve (with tax)

Amount of tax 

Supply curve (no tax)

Demand curve

Q1

Q0

Quantity consumed

Source: Varian (2010), PwC analysis 

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Of  course,  this  analysis  does  not  take  into  account  the  outcomes  that  tax  revenue 
helps  achieve  in  the  economy.  Governments  use  the  proceeds  of  taxation  to  provide 
goods  and  services  that  would  otherwise  be  underprovided  by  a  free  market  and  to 
correct  other  market  failures.  The  money  raised  from  taxation  is  spent  by 
governments, bringing about a positive multiplier effect and higher economic activity. 
However,  the  most  important  question  for  policymakers  is  the  ‘net’  effect  to  society 
which results from the balance between the deadweight loss created by taxation and 
the stimulus created from government spending.  

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Appendix 5 – Text of Article 89 

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Article  89  of  Directive  2013/36/EU  on  access  to  the  activity  of  credit 
institutions  and  the  prudential  supervision  of  credit 
institutions  and 
investment (CRD IV) 

Article 89  

Country-by-country reporting  

1.    From 1 January 2015 Member States shall require each institution to disclose 
annually, specifying, by Member State and by third country in which it has an 
establishment, the following information on a consolidated basis for the financial year:  

(a) name(s), nature of activities  
(b) turnover;  
(c) number of employees on a full time equivalent basis;  
(d) profit or loss before tax;  
(e) tax on profit or loss;  
(f)  public subsidies received. and geographical location; 

2. Notwithstanding paragraph 1, Member States shall require institutions to disclose 
the information referred to in paragraph 1(a), (b) and (c) for the first time on 1 July 
2014.  

3. By 1 July 2014, all global systemically important institutions authorised within the 
Union, as identified internationally, shall submit to the Commission the information 
referred to in paragraph 1(d), (e) and (f) on a confidential basis. The Commission, 
after consulting EBA, EIOPA and ESMA, as appropriate, shall conduct a general 
assessment as regards potential negative economic consequences of the public 
disclosure of such information, including the impact on competitiveness, investment 
and credit availability and the stability of the financial system. The Commission shall 
submit its report to the European Parliament and to the Council by 31 December 
2014.  

In the event that the Commission report identifies significant negative effects, the 
Commission shall consider making an appropriate legislative proposal for an 
amendment of the disclosure obligations set out in paragraph 1 and may, in 
accordance with point (h) of Article 145, decide to defer those obligations. The 
Commission shall review the necessity to extend deferral annually.  

4. The information referred to in paragraph 1 shall be audited in accordance with 
Directive 2006/43/EC and shall be published, where possible, as an annex to the 
annual financial statements or, where applicable, to the consolidated financial 
statements of the institution concerned.  

5. To the extent that future Union legislative acts for disclosure obligations go beyond 
those laid down in this Article, this Article shall cease to apply and shall be deleted 
accordingly.  

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DOI : 10.2780/53352 

ISBN : 978-92-79-38488-2