Academic Track XBRL development in Europe: identifying explanatory factors Ignacio Boixo and Enrique Bonsón, XBRL Spain April 21 st, 2010

Level of development of XBRL Hypotheses and explanatory variables The model

XBRLdevelopment 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

Explanatoryvariables 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

ListingofHypotheses 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 countrys category, within the EU, that reflects a particular differentiated style of public administration in its governmental agencies, makes the countrys level of XBRL development significantly different.

Hypothesizedrelationships Hypothesized relationships 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. XBRL development EDUCATION ICTs USAGE GDP per capita a b Style of administration - region c

Explanatoryvariablesoperationalization 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 of population aged 20-29). Level of usage of ICTs Measured using Gross domestic expenditure on R&D (%) as a proxy

Stylesofpublicadministration Styles of public administration Anglo-Saxon Managerial approach Efficiency in terms of economic values Likely to introduce market mechanisms Germanic Bureaucratic system Complex relationships among federal institutions Strong regulation Nordic Unified, not federal states Decisions by negotiation and consultation Efficiency in terms of users´ satisfaction Southern European Influenced strongly by French legal style Some degree of decentralization but with a powerful central government that collects most taxes Anglo-SaxonGermanic IrelandAustria UKGermany NordicOther styles DenmarkBulgaria FinlandCyprus SwedenCzech Republic NetherlandEstonia Southern EuropeanHungary BelgiumLatvia FranceLithuania GreeceMalta ItalyPoland LuxembourgRomania PortugalSlovak Republic SpainSlovenia

Administrationstyles Anglo-Saxon Southern European Nordic Germanic Other

Presentingthemodel 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 Anglo-Saxon Southern European Nordic Germanic Other

XBRL GAAP Anglo-Saxon Southern European Nordic Germanic Other

Banking Anglo-Saxon Southern European Nordic Germanic Other

Jurisdictions Anglo-Saxon Southern European Nordic Germanic Other

Publicreports Anglo-Saxon Southern European Nordic Germanic Other

Countries ordered by XBRL evolution

Countries ordered by GDP per capita

Countries ordered by Tertiary education

Countries ordered by Research & Develop.

Nordic - Other GDP per capita + + % of GDP in R&D + + -

Your suggestions are more than welcome. Many thanks for your attention. References EUROSTAT, (2010): KIM Ch.K. (2007): A cross-national analysis of global E-government, Public Organization Review, vol. 7: 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: Tobin, James (1958), "Estimation for relationships with limited dependent variables", Econometrica 26 (1).