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S-T-D Monitoring Tool PDF Print E-mail
Tuesday, 27 November 2007

FREE WEB MONITORING TOOL FOR LISBON, NRP, MILLENNIUM DEVELOPMENT GOALS AND OTHER TARGETS WITH S-TIME-DISTANCE MEASURE



      FUNCTION

  • To calculate the lead or lag in time for tracking implementation of targets at the world, regional, national, sub-national or business levels, e.g.
  • Lisbon, NRP and Sustainable Development targets in the case of EU
  • UN Millennium Development Goals
  • or other planned, budgeted, or aid disbursement targets




PURPOSE

To empower a broad range of stakeholders in Europe and in the world with an excellent presentation and communication tool that is easily understood by policy makers, experts, managers, media and general public, it can support decision-making as well as influence public opinion.

POTENTIAL USERS

All stakeholders who would like to take advantage of this complementary statistical measure for analysis and policy debate at various levels, e.g.: international and national organizations, NGOs, experts, businesses, managers, educators, students, interest groups, media and the general public

 


WHY TRACKING THE IMPLEMENTATION OF LISBON STRATEGY WITH THE S-TIME-DISTANCE MEASURE


   1. The time distance information is at least as helpful for a proper perception of the progress in implementation or the lack of it as is the percentage difference
   2. It complements rather than replaces other methods
   3. It is comparable across variables, fields of concern and units of comparison
   4. This innovation provides simultaneous two-dimensional comparisons of time series data: vertically (standard measures of static difference) as well as horizontally (Sicherl time distance)
   5. Empirically, the perceptions of the degree of disparity may be very different in static terms and in time distance
   6. Thus the broader conceptual and analytical framework leads to new conclusions and richer semantics important for policy considerations

DO IT YOURSELF

Use the tool to track the implementation by using your choice of data and assumptions

 
 
 
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