shadow_left
Logo
Shadow_R

Graphs & Tables

MDG Graphs

Login Form






Lost Password?

Subscribe to News

Search on Gaptimer.eu
 
   


Innovative framework for dynamic indicator analysis of Beyond GDP initiatives
Friday, 14 August 2015

How well are EU28 countries progressing towards their targets for EU2020


The high-level expert EU conference “Moving ‘beyond GDP’ in European economic governance”, Brussels (October 10, 2014) was intended to discuss recent technical advances in measuring well-being, their current policy implications and how to translate this into EU-level and national policy-making in the future. These issues are discussed in three sections: 

1. Broadened theoretical concept of measuring inequalities and in evaluating the magnitude of inequality. Time, besides money, is one of the most important reference frameworks in a modern society. People have memories of the past and expectations about the future; they compare over many dimensions and over time. The observed distance in time (the number of years, quarters, months, etc.) for given levels of the indicator is used as a temporal measure of disparity between the two series, in the same way that the observed difference (absolute or relative) at a given point in time is used as a static measure of disparity. This innovation opens the possibility for simultaneous two-dimensional comparisons of time series data in two specified dimensions: vertically (standard measures of static difference) as well as horizontally (Sicherl time distance). In the information age this new view of the existing databases should be evaluated as an important contribution to a more efficient utilisation of the existing data. 

2. Time matrix presentation format indicates at a glance that GDP underestimated the scale of damage of the financial crisis, showing the importance of ‘beyond GDP’ initiatives for policy debate. Time matrix organises the same data from Eurostat databases in a way that data are arranged by selected levels of indicators showing in which year these levels of the indicators were achieved by given country. The result is a LEVEL-TIME MATRIX, which is easily understood by everybody. This presents a first level visualisation that usefully complements the details in the original database by showing the easily understandable summary dynamic overview. The study ‘European Union at a Glance’ allows for a quick level comparison for time matrices for 30 selected indicators for 28 countries.

3. Time distance measurement for monitoring of implementation of targets and for goodness-of-fit. It provides new parallel system of monitoring implementation of targets based on deviations in time of actual values from the time on line to the target, complementing (not replacing) the existing mostly static measures of inequality and of implementation of targets. Expressed in time units, S-time-distance is easily understood by policy makers, managers, media and general public, thus being an excellent presentation tool for policy analysis and debate. 

Empirical part shows time distance deviations for implementation of five selected headline indicators towards the EU2020 EU and national targets. The Gaptimer progress chart is a clear example of simplicity with the summary story of about 150 cases of EU2020 targets. The additional time distance monitoring supervision can be a standard procedure also in numerous other activities of the Commission and of the national and local levels in hundreds of cases like monitoring and evaluation implementation of budgets, plans, projects, structural funds, etc. 

This presents a complementary possibility to look at indicator differences in the parallel universe of time, adding new vocabulary in the semantics of discussing and analysing differences in the real world.


 
SYSTEM FOR MONITORING IMPLEMENTATION OF TARGETS: Present MDGs and Post-2015 SDGs
Tuesday, 14 July 2015

Results for 10 selected MDG indicators for Developing Regions, 7 world regions, China and India, and for 125-154 countries for four selected indicators


The Millennium Development Goals (MDGs) are coming towards conclusion and the international community is deciding on the scope and the timetable for a set of Sustainable Development Goals (SDGs). The study “SYSTEM FOR MONITORING IMPLEMENTATION OF TARGETS: Present MDGs and Post-2015 SDGs” includes three main parts:

1. Outline of time distance methodology, with S-time-matrix format to present data over many units and over time, two generic statistical measures S-time-distance and S-time-step. The new generic time distance approach, which is easy to understand and to communicate, offers a new view of reality that significantly complements existing mostly static measures of inequality in many domains. In the information age this new view of the existing databases should be evaluated as an important contribution to a more efficient utilisation of the existing data.

2. Empirical part uses the most recent data from the UN 2015 MDG Report Statistical annex and MDG database updated on July 6, 2015 and shows implementation of MDG targets for 

a) 10 selected MDG indicators for Developing Regions, 7 world regions, China and India
b) details for implementation of four MDG indicators for 125-154 countries, year by year. 

It provides new parallel system of monitoring implementation of targets based on deviations of actual values from the line to the target, thus complementing (not replacing) the existing mostly static measures of inequality and of implementation of targets. Expressed in time units, S-time-distance is easily understood by policy makers, managers, media and general public, thus being an excellent presentation tool for policy analysis and debate. It can help us to form a new perception of the magnitude of the gap between the implementation and proclaimed targets for a given indicator as well as across more indicators. 

3. This study offers a system for time distance monitoring implementation of targets for many domains and levels (global, regional, national, local, business). The detailed application to current MDGs could be immediately applied for the post-2015 SDGs targets when they are determined. It can be with the help of Sustainable Development Solutions Network facilities further refined and distributed to complement existing methods of monitoring implementation.

We added complementary possibility to look at indicator differences in the parallel universe of time, adding new vocabulary in the semantics of discussing and analysing differences in the real world. Free web monitoring tool is provided. SDG initiative is an important field where this additional dimension could be fruitfully applied making some aspects more transparent and understandable to people as the main potential beneficiaries and participants in the implementation. 

Printed version is available on Amazon.com 

FULL TEXT: 

 
Time distance monitoring of implementation of targets
Wednesday, 18 June 2014

Test application for EU2020 targets by countries and free software tool

Monitoring implementation of targets is an integral part of policy making at many levels and in many domains. The innovation is that implementation of targets is described in two dimensions: static deviation from the line to target at a given point in time and S-time-deviation at a given level of the indicator. Describing the implementation of targets as leading or lagging in time against the line to well-known targets is a very useful application in the policy debate that enhances knowledge, giving data a value beyond spreadsheets. Expressed in time units, S-time-distance is easily understood by policy makers, managers, media and general public thus being an excellent presentation tool for policy analysis and debate. It can help us to form a new perception of the magnitude of the gap between the implementation and proclaimed targets for a given indicator as well as across more indicators.


We measure deviations in two dimensions. Firstly, one can measure the difference in variables at a given point in time. And secondly, discrepancies in time (either time lead or time lag) are measured. Monitoring implementation in time is like comparing train or bus arrivals with the timetable provided for each mode of transport. The statistical chart uses the same identifiers as Formula 1 on TV: drivers who score a minus at time distance are shown in green to signify that they are ahead in time. 

The table for EU 28 countries for 2013 (or 2012) shows the results from 2010 on. Yet the summary results confirm the earlier conclusions. For the headline indicator employment rate 20 countries are behind the schedule, 11 of them had in 2013 values below those in 2010 starting year. For 11 countries there was no progress in the 2010-2013 period for employment rate. The earlier graph that contained also the worse years of the financial crisis showed even a more serious situation. The time distance method, either for monitoring or for benchmarking in the time perspective, brings the second dimension of deviations or disparities that the present state-of-the-art is neglecting. 

For early leavers nine countries were in 2013 already better than their 2020 targets, this holds true for tertiary attainment for 10 countries; with only six countries being behind the schedule for both indicators. The headline indicator renewable energy also more countries are ahead of schedule than behind it, but with fewer cases that already reached the 2020 targets. R&D in GDP indicates a different picture, with 9 countries ahead and 16 countries behind the schedule; overall it is closer with the employment rate situation than with the other three indicators. 

The average for EU28 S-time-distance deviations express the situation with being ahead or behind the track to 2020 targets in simple terms: employment rate is more than 3 years behind, R&D 1.2 years behind, renewably energy 0.6 years, early leavers 2.1 years and tertiary attainment 2.4 years, ahead of  the line to the 2020 target.   

Software for time distance monitoring of targets from your own data: 

For time distance monitoring of implementation of targets, as shown for examples of indicators for EU2020 and UN Millennium Development Goals, SICENTER developed on www.gaptimer.eu a software tool to facilitate interested users to use the method for their own data. The tool can be accessed on http://www.gaptimer.eu/s-t-d_monitoring_tool.html


 
<< Start < Prev 1 2 3 4 5 Next > End >>

Results 1 - 13 of 62