Innovative framework for dynamic indicator analysis beyond GDP
Monday, 25 September 2017

Summary and conclusions


Well-being and development embody multidimensional and long-term experience, going much beyond the GDP. The focus in the media is especially in GDP growth rates. Over time, UNDP, OECD, and European Commission have participated in the conferences, indicator developments, and policy discussions of 'Beyond GDP Initiatives'. In the article, the analyses of beyond the GDP indicators are enriched by the application of the dynamic time distance methodology to complement the results of the usual mostly static tools. 

With time distance methodology, a new perspective related to time does not replace but rather adds a new dimension to existing analysis across many variables, fields of concern, and units of comparison. Section 3 deals with the broadened concept of measuring and evaluating the magnitude of inequalities in two dimensions. LEVEL-TIME matrix in section 4 is an additional option of visualisation of time series data which helped to establish that GDP underestimated the scale of damage of the financial crisis in the EU for selected indicators. Section 5 emphasises the function of the time distance tool for monitoring implementation of targets parallel to other methods, with application to about 150 cases of EU2020 targets; as well as to measuring implementation of the UN Millennium Developments Goals that can be used also for the UN initiative of the 2030 Agenda for Sustainable Development. This transparent and innovative method for monitoring implementation of targets at all levels is available but not yet utilised. It can bring a new easily understandable perception of the magnitude of the gap between the actual implementation and proclaimed targets at many levels: it can help governments, the civil society, and businesses in a broader understanding of continuous policy debate and necessary adjustments. The free software tool is available.

The empirical study exposes that GDP underestimated the scale of damage of the financial crisis as selected time matrices showed deterioration in many indicators:
  • Employment rate fell in 20 EU countries (71% of countries);
  • Risk of poverty as percent of total population increased in 24 EU countries (86%);
  • Income distribution worsened as Gini coefficient and income quartile share ratio increased in 25 EU countries (89% of countries);
  • The most shocking conclusion is that the value of the share of growth fixed capital formation in GDP decreased in all 28 EU countries (100%!). This negatively affected the medium/long-term rate of growth of GDP.

Table 2 shows possible scheme and numerical values for analysing time distance deviations for implementation of five selected headline indicators towards the EU2020 for the entire EU and national targets. It is a clear example of simplicity with an overview of about 150 cases of EU2020 targets, showing the results of 5 selected EU2020 indicators, 28 countries, and the EU aggregate in one single table. Such time distance monitoring supervision could become a standard procedure in numerous other activities of the Commission on the national and local levels, e.g. monitoring and evaluation implementation of budgets, plans, projects, structural funds, etc.


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