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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 • • • • • 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).