According to the disclosure requests of IAS 23 Borrowing Costs, companies areto include the following elements within their annual reports: accounting policies adopted bythe firms, value of capitalization for borrowing costs and capitalization rate. This paperinvolves an empirical research, presenting the correlation that might exist at the level ofcompliance with IAS 23 and specific variables that characterize the activity of a company.The purpose of our investigation is to estimate and determine a statistic function that shouldconnect disclosure index measured for IAS 23 requests and a series of elements, namely:country of origin, total assets, turnover, ROA, ROE, debt rate and solvency. The researchmethodology assumes disclosure index determination and SPSS analysis. The findings suggestevidence of correlation with respect to the level of compliance in information disclosure andthe mentioned variables.information, disclosure, compliance, correlation

Adriana Tiron Tudor

Ioana-Maria Dragu

English

Research Papers in Economics

Annales Universitatis Apulensis Series Oeconomica, 13(2), 2011 
 
  254 
DEVELOPING AN ECONOMETRIC MODEL FOR MEASURING THE 
EVOLUTION OF INFORMATION DISCLOSURE - IAS 23 BORROWING 
COSTS – 
 
 
Ioana-Maria Dragu
1 
Adriana Tiron Tudor
2 
 
 
ABSTRACT: According to the disclosure requests of IAS 23 Borrowing Costs, companies are to 
include the following  elements  within their annual reports: accounting policies adopted by the 
firms, value of capitalization for borrowing costs and capitalization rate. This paper involves an 
empirical research, presenting the correlation that might exist at the level of compliance with IAS 
23  and  specific  variables  that  characterize  the  activity  of  a  company.  The  purpose  of  our 
investigation is to estimate and determine a statistic function that should connect disclosure index 
measured for IAS 23 requests and a series of elements, namely: country of origin, total assets, 
turnover, ROA, ROE, debt rate and solvency. The research methodology assumes disclosure index 
determination and SPSS analysis. The findings suggest evidence of correlation with respect to the 
level of compliance in information disclosure and the mentioned variables. 
 
Key words: information, disclosure, compliance, correlation 
 
JEL Codes: M41   
 
 
Introduction   
The contribution of this research for international literature relies in studying the disclosure 
process  regarding  the  IAS  23  disclosure  requirements  in  correlation  to  specific  variables  that 
describe  the  profile  and  operations  of  an  entity.  Having  an  empirical  character, the  paper  also 
involves accounting practices, assuming real data for a set of 91 companies and their consolidated 
financial reports. The motivation for writing this article comes from the necessity of establishing an 
IFRS compliance  level, as  both IAS recognition and appliance represent essential steps  for the 
process of accounting development. 
This research concentrates on information disclosed by companies regarding their borrowing 
costs. According to the checklists presented by KPMG, PwC, Delloite, Ernst&Young and to IAS 23 
disclosure requests, companies are to include the following elements within their annual reports: 
accounting  policies  adopted  by  the  firms,  value  of  capitalization  for  borrowing  costs  and 
capitalization rate.  
The literature review is meant to bring evidence and arguments for the selection criteria used 
in  this  study,  as  well  as  the  methodology  through  which  the  research  is  implemented.  The 
originality approach or the authors’ contribution comes from the diversity of countries implied in 
the study, the areas of activity for companies, the large sample of 91 firms, and also the fact of 
considering market capitalization in allocating the number of entities. All these have been made in 
an attempt to determine IFRS compliance for disclosure of borrowing cost information, this field 
being very much affected by the financial crisis that created a general economic disequilibrium.   
 
                                                 
1  Babes-Bolyai  University,  Faculty  of  Economical  Sciences  and  Administration,  Cluj-Napoca,  Romania,  e-mail: 
ioanadragu@yahoo.com 
2  Babes-Bolyai  University,  Faculty  of  Economical  Sciences  and  Administration,  Cluj-Napoca,    Romania,  e-mail: 
adriana.tiron@econ.ubbcluj.ro Annales Universitatis Apulensis Series Oeconomica, 13(2), 2011 
 
  255 
Research Methodology 
As an empirical research, this article focuses on a sample of 92 companies that develop 
activities in 10 European countries and it uses a database of their consolidated financial reports for a 
period of 5 years (2005-2009). 
Data gathering assumed selecting firms according to some criteria, such as industry, headquarter, or 
market capitalization- the last one being the main issue in allocating the number of companies for 
each one of the 10 countries (France, Germany, Spain, Italy, Austria, Poland, Romania, Hungary, 
Ukraine and Bulgaria). The methodology implies disclosure index determination, being computed 
as follows: 
 
DI = Σ(di effectively disclosed) / Σ(di all possible cases of disclosure)  (1) 
The purpose of this research is to estimate an empirical model that should best describe the 
correlation  between  disclosure  index  of  borrowing  costs  information  and  turnover,  total  assets, 
solvency, debt rate, ROE, ROA and country of origin, the econometric function being presented 
below: 
 
DIt = ∂0 + ∂1 Turnover + ∂2 Total Assets + ∂3 Debt Ratio + ∂4 Solvency Rate + ∂5 Return on Assets 
+ ∂6 Return on Equity + ∂7 Country of headquarter  (2) 
 
where t represents the year of study. 
 
Another important step in research methodology assumes SPSS processing and regression 
analysis. This stage consists in determining the econometric models, by considering one dependent 
variable DI-, and other independent ones- turnover, total assets, solvency, debt rate, ROE, ROA and 
country  of  origin-.  Furthermore,  this  study  concentrates  a  multiple  linear  regression,  in  which 
linearity results from coefficients, not from variables. In addition, the model is estimated through 
enter  method,  all  variables  being  introduced  simultaneously  in  the  regression.  Practically,  this 
method  is  used  for  theoretical  or  empirical  models,  as  the  one  in  our  case,  and  its  main 
characteristic is the set of predictive variables, the results showing how the exogenous variables 
explain the endogen ones. 
 
Literature Overview 
International accounting literature provides evidence on the fact that information disclosure 
is becoming more and more important for both producers and users of information. Further on, 
companies  are  interested  in  providing  their  reports  with  transparency,  especially  if  they  need 
external  funds  to  sustain  their  operations  and  investments.  On  the  other  side,  there  are  the 
shareholders, investors and other stakeholders that rely on the information disclosed by firms, and a 
high disclosure level would make the respective company more trustworthy.     
When considering mandatory and voluntary disclosure, most seem to believe that firms that present 
information  in  low  amounts  might  have  something  to  hide  (Fishman  and  Hagerty,  2007),  and 
generally stakeholders become suspicious with them. Therefore, disclosure should be a matter of 
voluntary choice, and entities are to present the requested information according to their own will, 
not just because regulatory organisms require them.  
According to Hossain (Hossain, 2008), the disclosure process can be characterized as being 
economically efficient, as an influencing factor for the behavior of the economic agent, a strong 
fundament for any decision. Studies on corporate disclosure measurement (Hossain et al. 2009) 
imply analysis criteria, such as: turnover, ROE, ROA, industry, activity field, country of origin, and 
assets. This type of research involves scoring the disclosure degree, by allocating 0 points to non 
disclosed and 1 for the presented elements.  Annales Universitatis Apulensis Series Oeconomica, 13(2), 2011 
 
  256 
Non-compliance factors have been correlated to the disclosure trend (Street, 2001), while 
certain  economic  ratios,  namely  return  on  assets  and  return  on  equity  are  subject  to   detailed 
analysis in connection to borrowing costs (Bohusova and Nerudova, 2009). A study on disclosure 
concerning borrowing costs capitalization involving the oil and gas field reveal that borrowing costs 
are either expensed, or capitalized (Chung et al., 1993)  
Kueppers and Sullivan identify a common point of the policies adopted by companies in 
practice  that  can  lead  to  a  ’real-time  reporting’  (Kueppers  and  Sullivan,  2010).  In  addition, 
international literature (Lang and Lundholm, 1993), mentions that improved disclosure incorporates 
a set of   benefits for firms, as debt and equity financing rely heavily on the intensity of disclosure 
efforts (Barry et al., 1991). 
 
Discussion on Results  
The SPSS analysis has generated a series of Pearson’s’ Coefficients and Un- standardized 
Beta Coefficients on which our discussion of results is funded. Pearson Coefficients were used to 
determine and express the correlation level between the main (dependent) variable one, namely 
disclosure index for information on borrowing costs, and the independent ones, in the form of sales, 
total assets, ROA, ROE, solvency, debt rate and country. The Un-standardized Coefficients are also 
useful when  estimating the trend of the econometric  model and thus, the statistic  function that 
results for each one of the five analyzed years. Table no.1 shows the values obtained for Pearson 
Coefficients and Un-standardized Beta Coefficients, by applying the enter method during SPSS data 
processing. 
In the first year of analysis the variables that have a strong influence on disclosure index are 
Sales, Total Assets, ROE and ROA. This means that those companies that register a high score  for 
turnover or sales are also the ones that seem to publish more information. Further on, as the assets 
value increases, the firm is more likely to disclose a higher quantity of information. ROE and ROA 
are also positively correlated to disclosure index. An analysis on debt rate and solvency shows that 
there is negative correlation on behalf of disclosure, indicating that an increase negative correlation 
on behalf of disclosure, indicating that an increase in debt rate would generate a lower level of 
information published by firms. Regarding the country of origin, it seems that for both Romania and 
Italy there is low amount of disclosed information, while Hungary and Germany maintain a high 
level  of  publishing.  According  to  our  model,  the  econometric  function  for  2005  presents  the 
following trend: 
 
DI2005 = 0,279 + 5,9709 x Sales + 5,3549 x Total Assets + 3,9492 x Debt Rate + 3,2602 x 
Solvency + 0,110 x ROA - 1,3092 x ROE – 0,324 x Ro + 1,2692 x Bg + 0,138 x Hu – 8,9603 x Pl + 
1,7782 x Ur + 1,4032 x Sp – 5,6652 x It + 7,4092 x Ge + 1,4592 x Au 
 
The following year shows that sales and total assets do not have a significant influence on 
disclosure index, while debt rate and ROE register a negative correlation regarding DI, solvency 
being an important influencing factor in contrast to the low correlated variable, ROA. On the whole, 
we noticed that an increase in solvency could generate a greater amount of published information, 
while a higher debt rate results in decreasing the disclosure level. If we analyze the country of 
origin criteria, it seems that Romania, Italy and Germany have negative correlation with respect to 
DI.  However,  Hungary  and  France  appear  to  be  highly  positive  correlated  to  disclosure.  The 
regression model for year 2006 involves the following trend: 
 
DI2006 = 0.406 + 3.4239 x Sales + 9.2549 x Total Assets – 5.766 x Debt Rate + 5.8132 x Solvency 
-2.3752 x ROA + 4.2313 x ROE – 0,435 x Ro – 9.7562 x Bg + 0,118 x Hu – 9.4892 x Pl – 7.1512 x 
Ur – 5.2562 x Sp – 0.143 x It – 5.5502 x Ge – 6.8652 x Au 
 Annales Universitatis Apulensis Series Oeconomica, 13(2), 2011 
 
  257
 
 
 
 
Table no.1.  
Correlation and model determination-SPSS data processing and analysis 
 
Pearson’s Correlation Coefficient  Un-standardised Beta Coefficient                  Year 
Variables   2005  2006  2007  2008  2009  2005  2006  2007  2008  2009 
Significance   *, for Sig  ≤ 0,10   **, for  Sig  ≤ 0,05  ***, for  Sig  ≤ 0,01  ,279  ,406  ,381  9,474E-02  ,518 
Sales  0,102  0,076  0,073  0,132  0,076  5,970E-09  3.42E-06  3,099E-08  3,983E-07  1,183E-07 
Total Assets   0,105  0,093  0,051  0,091  0,070  5,354E-09  9.25E-06  -1,750E-08  -3,702E-07  -8,611E-08 
Debt Rate  -0,058  -0,185 **  -0,214 **  0,062  0,159 *  3,949E-02  -5.77E-02  -1,845E-02  ,235    -,101 
Solvency  0,075  0,187 **  0,211 **  -0.073  -0,181 **  3,260E-02  5.81E+01  6,058E-02  ,331  -8,861E-02 
ROA  0,224 **  0,024  0,115  0,003  -0,031  ,110  -2.38E-02  -1,403E-02  5,622E-03  -,443 
ROE  0,216 **  -0,005  -0,027  0,009  -0,011  -1.309E-02  -4.23E+00  3,767E-03  -5,951E-04  9,498E-02 
Romania (Ro)  -0,545 ***  -0,529 ***  -0,564 ***  -0,450 ***  -0,432***  -,324  -,435  -,419  -,413  -,413 
Bulgaria (Bg)  0,025  0,007  0,011  0,003  -0,034  1,269E-02  9.76E-02  -8,288E-02  1,609E-02  -,109 
Hungary (Hu)  0,255 *  0,305 **  0,229 **  0,170 *  0,147 *  ,138  ,118  5,577E-02  4,135E-02  ,11 
Poland (Pl)  0,056  0,0015   0,024  0,006  -0,075  -8.960E-03  -9.49E-02  -9,031E-02  -4,705E-02  -8,185E-02 
Ukraine (Ur)  0,031  0,008  0,013  0,003  0,130  1,778E-02  -7.15E-02  -6,698E-02  -3,669E-02  ,134 
Spain (Sp)  0,066  0,017  0,028  0,007  -0,089  1,403E-02  -5.26E-02  -5,271E-02  -2,841E-02  -8,765E-02 
France (Fr)  0,042  0,231 **  0,263 *  0,097  0,079           
Italy (It)  -0,175 **  0,127  0,129  -0,114  -0,080  -5.665E-02  -,143  -,137  -,107  -9,158E-02 
Germany (Ge)  0,139 *  0,043  0,036  0,060  0,201  7,409E-02  -5.55E-02  -5,867E-02  -3,097E-03  4,688E-02 
Austria (Au)  0,052  0,014  0,022  0,139  0,092  1,459E-02  -6.87E-02  -6,711E-02  6,163E-02  4,002E-02 
(Source: SPSS data processing) 
 Annales Universitatis Apulensis Series Oeconomica, 13(2), 2011 
 
  258 
The correlation coefficients obtained for year 2007 demonstrate that as solvency increases in 
value, the company tends to supply more information about borrowing costs. Hence, a higher debt 
rate  involves  less  information  disclosed  in  consolidated  financial  statements.  Regarding  the 
analyzed countries, Hungary performs with a high correlation to DI, accompanied by France. On 
the other side, there are the negative correlations of Italy and Romania, these countries maintaining 
a  low amount of published  information. Therefore, the representative  function  for 2007 can  be 
described as follows: 
 
DI2007 = 0,381 + 3,0998 x Sales – 1,758 x Total Assets – 1,8452 x Debt Rate + 6,0582 x Solvency 
- 1,4032 x ROA + 3,7673 x ROE – 0,419 x Ro – 8,2882 x Bg + 5,5772 x Hu – 9.0132 x Pl – 6,6982 
x Ur – 5,2712 x Sp – 0,137 x It – 5,8672 x Ge – 6,7112 x Au 
 
In 2008, there is evidence for the fact that the higher the turnover, the most likely for the 
firm to become more careful with the information they disclose, and to publish more as to fulfil the 
needs  of  the  users  of  accounting  information.  The  ROE  and  ROA  do  not  represent  significant 
factors for DI during this specific period. The same for total assets and debt rate, which show low 
correlation levels. When considering the countries included in this study, coefficients still have a 
negative sign for Romania, leading to the same conclusions as in previous cases. The econometric 
function is defined by a new regression model: 
 
DI2008 = 9,4742 + 3,9837 x Sales – 3,7027 x Total Assets + 0,235 x Debt Rate + 0,331 x Solvency 
+ 5,6223 x ROA – 5,9514 x ROE – 0,413 x Ro + Debt Rate + 0,331 x Solvency + 5,6223 x ROA – 
5,9514 x ROE – 0,413 x Ro + 1,6092 x Bg + 4,1352 x Hu – 4,7052 x Pl – 3,6692 x Ur – 2,8412 x 
Sp – 0,107 x It – 3,0973 x Ge + 6,1632 x Au 
 
Regarding the last period of analysis, in 2009 we notice that an increase in debt rate would 
generate  increased  disclosure,  while  turnover  and  total  assets  do  not  represent  a  significant 
influence. Higher values for solvency, ROE and ROA would mean lower quantities of disclosed 
information. Ukraine, Hungary and Germany have significant and positive correlations with DI. 
The explanation is that companies with headquarters in these three countries maintain a high level 
of information disclosure regarding IAS 23. The model can be described below: 
 
DI2009 = 0,518 + 1,1837 x Sales – 8,6118 x Total Assets – 0,101 x Debt Rate – 8,8612 x Solvency 
– 0,443 x ROA + 9,4982 x ROE – 0,413 x Ro – 0,019 x Bg + 0,112 x Hu – 8,1852 x Pl + 0,134 x 
Ur – 8,7652 x Sp – 9,1582 x It + 4,6882 x Ge + 4,0022 x Au 
 
Conclusions 
This paper presents the correlation at the  level  of compliance with IAS 23 and specific 
variables that characterize the activity of a company. The purpose of this research is to estimate and 
determine a statistic function that should connect disclosure index measured for IAS 23 requests 
and a series of elements, namely: country of origin, total assets, turnover, ROA, ROE, debt rate and 
solvency. 
As  research  perspective,  we  are  aiming  to test the  model  on  a  larger  sample,  and  first 
conducting a study on Romanian companies, to expand afterwards the study at European level. 
Another research discussion could focus on the criteria of economic development of the selected 
countries, and grouping them into well-developed and under-developed. We also intend to perform 
an analysis on financial reporting trends in  years 2010 and to perform an analysis on financial 
reporting trends in years 2010 and 2011. 
Finally, we have to add that the study has some limitations, in the form of the finite number 
of selected companies and countries. If the database assumed more than 10 states or 92 firms, it Annales Universitatis Apulensis Series Oeconomica, 13(2), 2011 
 
  259 
would have been possible for the correlation to be different. In other words, the model should be 
continuously tested in order to verify its validity and relevance at the level of the whole population. 
Also, there are several criteria that should be met by an econometric model so as to be declared as 
valid. In what concerns this research, the validity is representative for the chosen sample, of the 92 
companies,  and  their  corresponding  countries.  Furthermore,  this  paper  concentrates  on  the 
correlation between the dependent variable- information disclosure for borrowing costs -, and the 
independent ones - country of origin, turnover, total assets, debt rate, solvency, ROA and ROE -, or 
the connection between elements, not aiming to demonstrate that the model is valid for the entire 
population, which could be a challenge for future manuscripts. 
 
 
References 
 
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Financial Disclosure on Governmental Borrowing Costs, Journal of Accounting, Auditing, 
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The Extent of Disclosure in Annual Reports of Banking Companies: The Case of India,

DEVELOPING AN ECONOMETRIC MODEL FOR MEASURING THE EVOLUTION OF INFORMATION DISCLOSURE - IAS 23 BORROWING COSTS -

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DEVELOPING AN ECONOMETRIC MODEL FOR MEASURING THE EVOLUTION OF INFORMATION DISCLOSURE - IAS 23 BORROWING COSTS -

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