Transcript XBRL development in Europe

Academic Track
XBRL development in Europe: identifying explanatory factors
Ignacio Boixo and Enrique Bonsón, XBRL Spain
April 21st, 2010
• Level of development of XBRL
• Hypotheses and explanatory variables
• The model
XBRL development
The following 6 sequential steps of XBRL jurisdiction development
can be identified:
• Without formal structure: step 0
• Provisional Jurisdiction: step 1
• Permanent Jurisdiction: step 2
• National Taxonomies: step 3
• Public XBRL reports available: step 4
• Public XBRL reports successfully exploited: step 5
Dummy
Yes =0
No =1
This allows each country
to be classified from Y=0
to Y=5
Additional information for
the analysis
Explanatory variables
Some of the explanatory factors, at the country level, that can be
explored:
•
•
•
•
Economic wealth
Level of education
Level of usage of ICTs
Style of government/administration
Listing of Hypotheses
•
H1: Economic wealth of a country positively influence XBRL development
since more resources are available for the implementation of the jurisdiction.
•
H2 + H3: Levels of education and usage of ICTs positively influence XBRL
development through the availability of more and better qualified human
resources for the implementation of the jurisdiction.
•
H4: The country’s category, within the EU, that reflects a particular
differentiated style of public administration in its governmental agencies,
makes the country’s level of XBRL development significantly different.
Hypothesized relationships
b
a
GDP per capita
+
+
XBRL
development
Style of administration
region
EDUCATION
+
ICTs USAGE
c
a)
As stated by Siau and Long, 2006, the economic situation of a country can
influence its ability to adopt particular e-government initiatives.
b)
Kim, 2007,explains that prior technological and educational development is
a prerequisite for the implementation of IT.
c)
Pina et al. (2009 divided the EU-15 into categories defined by a specific
style of administration. In our opinion, this framework can be applied to the
EU-27 grouping as an additional explanatory factor to be explored, by
adding a new category for eastern countries.
Explanatory variables operationalization
Data provided by EUROSTAT
• Country GDP per capita
• GDP per capita (purchasing parity power) for the year 2009,
• Levels of education
• Tertiary/further education graduates (per 1 000 of population aged 20-29).
• Level of usage of ICTs
• Measured using Gross domestic expenditure on R&D (%) as a proxy
Styles of public administration
Anglo-Saxon
• Managerial approach
• Efficiency in terms of economic values
• Likely to introduce market mechanisms
Anglo-Saxon
Ireland
UK
Nordic
Germanic
Denmark
• Bureaucratic system
Finland
• Complex relationships among federal
Sweden
institutions
• Strong regulation
Netherland
Southern European
Nordic
Belgium
• Unified, not federal states
• Decisions by negotiation and consultation France
• Efficiency in terms of users´ satisfaction Greece
Italy
Southern European
Luxembourg
• Influenced strongly by French legal style
• Some degree of decentralization but with Portugal
a powerful central government that collects Spain
most taxes
Germanic
Austria
Germany
Other styles
Bulgaria
Cyprus
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Malta
Poland
Romania
Slovak Republic
Slovenia
Administration
styles
Nordic
Anglo-Saxon
Germanic
Southern
European
Other
Presenting the model
If the variable to be explained, the level of development of XBRL, presents only
a positive value (0 to 5), then the appropriate statistical technique for analyzing
the data and the hypotheses is the TOBIT regression model, proposed by
James Tobin (1958), also called “censored data regression”.
Feature of Model:
• Left censored 0, right censored 5.
XBRL use
Nordic
Anglo-Saxon
Germanic
Southern
European
Other
XBRL GAAP
Nordic
Anglo-Saxon
Germanic
Southern
European
Other
Banking
Nordic
Anglo-Saxon
Germanic
Southern
European
Other
Jurisdictions
Nordic
Anglo-Saxon
Germanic
Southern
European
Other
Public
reports
Nordic
Anglo-Saxon
Germanic
Southern
European
Other
Countries ordered by
XBRL evolution
Countries ordered by
GDP per capita
Countries ordered by
Tertiary education
Countries ordered by
Research & Develop.
Nordic
+
+
% of GDP in
R&D
+
+
GDP per
capita
-
Other
Your suggestions are more than welcome.
Many thanks for your attention.
[email protected]
[email protected]
References
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•
•
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EUROSTAT, (2010): http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/
http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database
KIM Ch.K. (2007): “A cross-national analysis of global E-government”, Public Organization Review, vol. 7: 317-329.
Pina et al. (2009): “E-government evolution in EU local governments: a comparative perspective” Online Information
Review, 33,6.
SIAU, K.; LONG, Y. (2006): “Using social development lenses to understand E-government development”, Journal of
Global Information Management, vol. 14, n. 1: 47-62.
Tobin, James (1958), "Estimation for relationships with limited dependent variables", Econometrica 26 (1).