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SICENTER Ljubljana, Slovenia Time is not on our side Time Distance – A New View of the Position of Europe Lisbon Agenda and Technomics – The Dramatic Implications for Professional Competence Building, Brussels, Fondation universitaire, October 5, 2006 Professor Pavle Sicherl SICENTER and University of Ljubljana Email: [email protected]; www.sicenter.si Copyright © 1995-2006 P. Sicherl All rights reserved Example: A Comparison of European and US Economies Based on Time Distances US-EU gaps in GDP per capita: static index and time distance 100 US GDP per capita (2003=100) 95 90 85 Index 141 80 75 70 S-time-distance 18 years US 65 60 55 50 EU15 45 EU15 40 US 35 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 Time Source: P. Sicherl, A Comparison of European and US Economies Based on Time Distances, EUROCHAMBRES, Brussels, March 2005 The fact that comparisons should be made in two dimensions has been verified by the worldwide media interest in my analysis for the EUROCHAMBRES Spring Business Forum. The static ratio of 1.41 does not catch much attention, while the time gap of about two decades obviously produced a different perception of reality. The same will be true for comparing within the EU. Static measure and time distance show two very different messages about importance of different components EU15-US - Static Disparities (2003) 30 150 145 Time distance between the EU15 and the US (years) 25 141 25 23 Index EU15=100 135 130 125 120 115 111 113 114 EU15 time lag in years 140 20 18 15 10 110 5 5 105 100 GDP per capita Employment Rate Annual Hours Worked Productivity (GDP per hour) Percentage differences between US and EU15 for employment rate, annual hours worked and productivity per hour are very similar. It seems as if the difficulty of catching up would be similar in the analysed components. 0 GDP per capita Employment Rate Annual Hours Worked Productivity (GDP per hour) S-time-distances are very different, for productivity per hour only 5 years, while for employment rate and annual hours worked are about a quarter of a century. Policy analysis should expect different difficulties of catching up in these fields. Comparisons over many indicators can show characteristic profiles across countries, regions, socio-economic groups, firms, etc. Time distances in years between the USA and EU15 average for selected indicators for 2003 (- time lead, + time lag for the USA) -30 S-time-distance in years -25 -20 -15 -10 -5 -18 -25 -23 -5 -23 0 10 10 Life expectancy females Infant survival rate 5 10 15 GDP per capita Employment Rate Annual Hours GDP per hour Worked R&D per capita economic indicators © P. Sicherl 2005 Source: Interview with P.Sicherl - Semanario Economico, Lisbon, March 18, 2005 social indicators EU catching-up: year in which EU catches up with the US under various assumptions 2130 R&D Investment (R&D per capita) 2120 Income (GDP per capita) 2110 Productivity (GDP per employed) Productivity (GDP per hour) 2100 Employment Rate Year of catch up 2090 2080 2070 2060 2050 2040 2030 2020 2010 2000 0.5% 1% 1.5% 2% 2.5% 3% 3.5% 4% 4.5% Assumed positive difference of EU15 growth rate over the US Source: P. Sicherl, A Comparison of European and US Economies Based on Time Distances, EUROCHAMBRES, Brussels, March 2005 5% The generic idea for many other applications of S-time-distance S-time-distance adds a second dimension to comparing actual value with estimated value, forecast, budget, plan, target, etc. and to evaluating goodness-of-fit in regressions, models, forecasting and monitoring e5 Variable X S4 S5 e4 S2 e2 S3 S1 e1 Time e3 What would be deviations in two dimensions from the original Barcelona target if the new Lisbon 2 targets for EU15 countries would be reached? Share of R&D in GDP (%) Monitoring deviations of actual from path to target in two dimensions Implied path 1 to target 3% Actual EU15 and new target 2 Percentage deviation of actual from path to target S-time-distance deviation of actual from path to target (in years) 2000 1.94 1.94 0.0% 0.0 years 2001 2.05 1.98 -2.7% 0.5 years 2002 2.15 1.98 -7.5% 1.5 years 2003 2.26 1.97 -12.3% 2.6 years 2004 2.36 1.95 -17.5% 3.9 years 2005 2.47 2.06 -16.7% 3.9 years 2006 2.58 2.17 -15.9% 3.9 years 2007 2.68 2.28 -15.2% 3.8 years 2008 2.79 2.38 -14.5% 3.8 years 2009 2.89 2.49 -13.9% 3.8 years 2010 3.00 2.60 -13.3% 3.8 years S-time-distance in years: - actual ahead of path to target, + actual behind the path to target Benchmarking and Monitoring of the Barcelona Target for GERD as % of GDP 3.5 Japan Path to Target 1 3% Share of R&D in GDP (percent) 3 USA 2.6% 2.5 EU15 2 Path to Target 2 EU25 1.5 China 1 0.5 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Time Barcelona target EU25 EU15 US JP CH Lisbon 2 target S-time-distance between EU15 average and selected countries for R&D per capita 2004 LU SE FR DE FI DK AT BE EU15 NL UK IE SI IT Time series data too short ES 40 CZ SK PT PL MT HU LT LV CY GR EE 35 © P. Sicherl 2006 more than 34 years more than 34 years more than 34 years more than 34 years more than 34 years more than 34 years more than 34 years more than 34 years more than 34 years more than 34 years 30 25 20 15 10 5 0 -5 -10 -15 S-time-distance (years): - time lead, + time lag -20 -25 -30 -35 -40 General conclusions on time distance measure Time distance concept and statistical measure S-time-distance is: - theoretically universal - intuitively understandable - immanently practical “The usual matrix for comparing two lines involves differences along the vertical axis. This can be a poor way of measuring how these trends vary in terms of time which is on the horizontal axis… Sicherl’s several works have presented a non-technical discussion of the theory of time distance… As Sicherl (1973, 1993) proposes… observed time distance is a dynamic measure of temporal disparity between the two series, intuitively clear, readily measurable, and in transparent units….. ” C.W.J. Granger and Y. Jeon, University of California at San Diego “Time distance is a generic concept. That means that, as it has been the case e.g. with spreadsheet, one cannot in advance specify all the uses to which a generic framework can be put by imaginative users in numerous fields.” J. Backhouse, Information Science Dpt., London School of Economics SUMMARY: Benefits of immediate operational uses of time distance • 2.1 A new view in competitiveness issues, benchmarking, target setting and monitoring for economic, employment, social, R&D and environment indicators at the world, EU, country, regional, city, project, socio-economic groups, company, household and individual levels • 2.2 A broader dynamic framework for interrelating Lisbon strategy issues of growth, efficiency, inequality and convergence • 2.3 Enhanced semantics for policy analysis and public debate • 2.4 Additional exploitation of databases and indicator systems • - 2.5 An excellent presentation and communication tool among different levels of decision makers and interest groups for describing of the situations, challenges and scenarios for proactive discussion and presentation of policy alternatives to policy makers, media, the general public and mobilizing those participating in or being affected by the programs for communicating the urgent need for change and reforms - Development is first and foremost a process of learning: • We should learn from others in and outside the EU – set high benchmarks • Time distance analysis presents an additional view, the gaps may be very different in static measures and in time, an important consideration for the Lisbon Strategy • Namely, greater efficiency leading to greater dynamics could also contribute to greater cohesion and to alleviating the time distance dimension of inequality • Knowledge based society needs reintegration of strategies of firms, social partners and policies in different fields (Lundvall 2000)