shadow_left
Logo
Shadow_R
   


Benchmarking comparison in the time dimension
Sex Differences around the World in Time Distance Watch PDF Print E-mail
Thursday, 21 July 2016

Life Expectancy, Obesity, Mean Body Mass Index, and Diabetes for about 200 Countries

The Gaptimer Report No. 5 offers new insights by analysing gender differences in life expectancy, mean body mass index, obesity and diabetes by using the novel time distance methodology. It combines two developments: firstly, recent availability of gender disaggregated longer time series by NCD Risk Factor Collaboration, 2016 on trends in body mass index and diabetes in 200 countries over 40 (35) years combined with  the UN long time series on life expectancy for about 60 years. As the focus we selected the gender difference in these indicators which can be attractive from both the medical and social standpoint and can be further elaborated with additional studies.    

Secondly, such longer time series make possible creative application of S-time- distance methodology for describing and analyzing indicator differences in the parallel dimension of time. Methodological innovations: parallel additional generic statistical measures S-time- distance, S-time- step and Level-Time Matrix as presentation and visualization tool. Expressed in time units they are comparable across variables, fields of concern and units of comparison. This makes S-time- distance an excellent complementary analytical and presentation tool offering additional insights, intuitive understanding, simplicity, and new semantics to many indicators and issues.  

In the gender difference for life expectancy one can address the question ‘How many years ago did the current level of the male value attained the same level in the past trend for women?’ This makes it possible to describe the gender differences in many indicators in the time distance dimension simultaneously with the static measures, leading to different perception of the extent of disparity than the conventional static measures alone.  

For life expectancy the time distance dimension of the diversion increases the perception of the degree of magnitude of sex difference in the indicator. In percentage terms in 2015 the range for 200 countries varied to about 15 percent for Belarus. The perception of the magnitude of sex differences is very different, as S-time- distances of women being ahead of men ranges up to about 60 years! in Belarus.   

Time lag for males behind the time when female life expectancy already achieved that level is on the world level about 14 years, about 38 years for more developed regions in UN definition and about 11 years for the less developed regions. USA and EU28 are both showing very substantial and persuading differences in favour of women, also at the regional NUTS levels in the EU and for the average of more than 3000 USA counties.   

The analysis of gender differences for the three more indicators, mean body mass index, obesity and diabetes, again shows that there were many cases where the time lead or time lag of one gender were larger than 20 years, which was taken as indication that such gender differences prevailed over longer periods of time (in either direction). For life expectancy and obesity about 100 countries show such female predominance. S-time- distance values range from more than 40 years of mean BMI values for males being ahead of mean BMI for females for Switzerland and Japan to more than 40 years of time lag in the opposite direction for five countries. Gender differences in obesity prevalence are strongly tilted in the female predominance. For Egypt, Turkey and South Africa the gender time distances show large time differences of 28, 24 and more than 40 years, respectively. For USA and for the UK the obesity prevalence is high also for men so that gender time distances are only few years. For diabetes there is predominance of cases for men in two high income regions; it was shown that for 26 countries (out of 27 countries) in the region High Income Western Countries the male values were for more than 20 years ahead of those for women.   

Time distances offer very different perception of the gender disparities as those of percentage differences at given point in time. We need both measures to understand the reality.

 
European Union at a Glance PDF Print E-mail
Thursday, 08 May 2014

Statistical portrait with innovative table-graphs for 30 selected indicators over 28 countries in time perspective


European Union at a Glance presents an easily understandable overview of 30 selected indicators over 28 EU countries in time, which is probably the most condensed current summary picture of dynamics and disparities in the EU over many domains over time.

The Gaptimer Report No. 3 is timely publication very useful for discussion of the situation in the EU in light of the forthcoming new European Commission and European Parliament and at the occasion of the 10th Anniversary of the largest EU expansion in 2004.

List of 30 selected indicators

 

Indicators

Data range

Top country (last year)

1

Life expectancy at birth

1960-2012

Spain

2

Human Development Index

1980-2012

Netherlands

3

GDP per capita in PPS

1995-2012

Luxembourg

4

Median income in PPS

1995-2013

Luxembourg

5

Employment rate (15 to 64 years)

1992-2012

Netherlands

6

Activity rate (15 to 64 years)

1992-2012

Sweden

7

Share of gross fixed investment in GDP

1954-2013

Estonia

8

R&D expenditure (GERD), percent of GDP

1981-2012

Finland

9

Summary Innovation Index

2008-2012

Sweden

10

Tertiary attainment for age group 15-64

2000-2013

Ireland

11

Proportion of population aged 65 years and more

1961-2013

Italy

12

Old age dependency ratio, projections 2013-2080

2013-2080

Slovakia

13

Population growth rates, total

1961-2013

Luxembourg

14

Persons killed in road accidents per million inhabitants

1990-2012

United Kingdom

15

Death due to homicide, standardised death rate by 100 000 inh.

1994-2010

United Kingdom

16

Infant mortality rate

1960-2012

Slovenia

17

At-risk-of-poverty (percent of total population)

1995-2012

Czech Republic

18

At-risk-of-poverty (percent of elderly population)

1995-2013

Hungary

19

Income quintile share ratio S80/S20

1995-2013

Slovenia

20

GINI coefficient

1995-2013

Slovenia

21

Early leavers from education and training

1992-2013

Croatia

22

Healthy life years at birth - females

1995-2012

Malta

23

Healthy life years at birth - males

1999-2012

Malta

24

Households with broadband access

2003-2013

Finland

25

Regular Internet use

2003-2013

Luxembourg

26

Share of energy from renewable sources

2004-2012

Sweden

27

Urban population exposure to air pollution by particulate matter PM10

1997-2011

Denmark

28

Publications per million inhabitants

1994-2010

Denmark

29

Proportion of seats in national parliaments held by women

2000-2013

Sweden

30

Current account balance in % of GDP

1975-2013

Netherlands



AN ADDITIONAL WAY OF PRESENTATION ACROSS MANY UNITS AND MANY YEARS

It uses innovative time matrix presentation format that enables such condensed summary visual presentation over many countries and over time. Secondly, 30 selected indicators from many Eurostat indicators systems like Quality of life; Sustainable Development Indicators, Digital Agenda, Headline Indicators, etc. follow the orientation of Beyond GDP. Annex A1 provides Time Matrix Calculator to calculate time matrix for your own data. 

The 30 time matrices give rich food for thought and imagination of readers can find numerous comparisons and stories in the material. One of them is that the damage done to countries by the world financial crisis is seen in a much greater scale when we look for 28 countries beyond GDP and look at employment, investment share, risk of poverty, income distribution, health, etc.

While media and also official organizations are focusing on discussion of GDP growth rate, such orientation understated the severity of the crisis.

Other domains showed a more difficult situation:

  •  employment rate fell in 20 EU countries;
  •  in all 28 EU countries without exception share of gross investment in GDP decreased;
  •  risk of poverty as percent of total population increased in 24 EU countries;
  •  income distribution worsened as Gini coefficient and income quartile share ratio increased in 25 EU countries;
  •  healthy life years at birth decreased for males and females in 15-18 EU countries.

The voyage through 30 time matrices for 28 countries compressed a very large amount of data, expressing multidimensional nature of development and well-being, indicating both visually and in numbers that very large differences exist between EU countries with respects to levels and dynamics. Using the innovative approach of time distance methodology the telling power of S-time-matrix provided a good summary overview at-a-glance over many domains with clear understanding to decision-makers as well as to the general public. Seeing with new eyes creates new knowledge and better understanding.

FULL TEXT: 

 
Astonishing Differences in Gender Disparity in Life Expectancy between Countries PDF Print E-mail
Wednesday, 07 May 2014

How much longer live women than men around the globe?

Gender disparities in life expectancy are analysed in Gaptimer Report No. 2 ‘How much longer live women than men around the globe?’ World inequalities are studied by combining two sets of statistical measures: static gap at a given point in time and gap in time for a given level of the indicator, providing a broader picture.

Firstly, it offers an innovative approach for looking at disparities over many units and over time. The new time distance measure, expressed in time units, is easy to understand by everybody and offers a novel way to compare situations in economics, politics, business and statistics. The time distance concept can influence the perception and decisions of people when they are assessing their relative position in their surroundings, in the society and across countries over time.

‘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. It is suggested that one should complement conventional measures with horizontal measures.’ (Granger and Jeon, 1997)
C.W.J. Granger and Y. Jeon, University of California at San Diego 

Secondly, the empirical results concentrate on gender disparity in life expectancy around the globe (at the world level for 196 countries and some aggregates; for EU27 countries with 269 NUTS2 regions). While female life expectancy at birth is higher than that for males for 99.5 percent of the world population, there are astonishing differences among countries. For example, Estonia occupied rank 51 the world for females and 110 for males. On the other extreme, e.g. the rank for Qatar was 65 for females and only 12 for males.

The time distance measure shows the reality with new eyes. The overall life expectancy the static difference between China and Sweden was less than 10 percent (which may appear to be small) while the S-time-distance was 51 years, (which gives a very different perception of the magnitude of the gap). For gender disparity in life expectancy S-time-distance for the world average, i.e. the horizontal time gap between trends of female and male life expectancy amounted to 20 years, 28 years for the EU27 and 35 years for the USA, showing a large and persistent gap in favour of women.   

 
World Inequalities in Human Development Index (1980-2012) PDF Print E-mail
Tuesday, 04 February 2014

Time Distance Approach

Gaptimer Report No. 1 ‘World Inequalities in Human Development Index’ presents a new way of understanding and discussing development and world inequalities in a new dynamic framework. This manuscript can expand knowledge in two ways. 

Firstly, it offers an innovative approach for looking at disparities over many units and over time. The new time distance measure, expressed in time units, is easy to understand by everybody and offers a novel way to compare situations in economics, politics, business and statistics. The time distance concept can influence the perception and decisions of people when they are assessing their relative position in their surroundings, in the society and across countries over time.

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. It is suggested that one should complement conventional measures with horizontal measures.’ (Granger and Jeon, 1997)
C.W.J. Granger and Y. Jeon, University of California at San Diego 

Secondly, the empirical results for the Human Development Index over the three decades (1980-2012) provide new insights for the post-2015 agenda. S-time-distance measure (calculations based on official UNDP data) estimates HDI inequalities for each of 187 countries within their peer group. Telling new stories includes inequalities within EU27, BRICS countries, and Gulf Coordination Council countries.

These additional insights provide a transparent matter-of-fact message to politicians and the international community about the degree of urgency to tackle wide inequalities between and within countries in formulating and deciding on the post-2015 agenda. 

FULL TEXT: 


 
The Global eGovernment Experts Workshop in Bahrain PDF Print E-mail
Wednesday, 05 December 2012

Professor Pavle Sicherl prepared a presentation on eGovernment measurement - The role and the time perspective on indicators


United Nation Public Administration Network published under UN E-Government Survey in the News on November 7, 2012 the news – ‘17 Nations Discusses the UN eGovernment Indexes in Bahrain’:

“For the first time in the world, a Global Expert Workshop was organized by the eGovernment Authority (eGA) in order to discuss all the United Nations eGovernment indexes, with the participation of elite countries, the United Nations, International Telecommunication Union (ITU) and ICT experts. Pavle Sicherl, Professor in Economics at the University of Ljubljana in Slovenia presented the first paper of the workshop entitled 'eGovernment Measurement - The role and the Time Perspective on Indicators'. He highlighted the key findings from the 2012 survey which include eGovernment survey rankings by countries and regions, the steady improvement in all the indicators of the eGovernment development index and an imbalance remains in the digital divide between developed and the developing countries.”

Professor Sicherl suggested several points for discussion:
1. Sustainable development requires that the analysis is broadened.
2. Static measures alone are inadequate.
3. To enable the dynamic comparability of the composite indices it would be advisable to make a change in the standardization process.
4. Absolute values of original data and indicators should be analysed in addition to the static comparison and composite indicators, at regional and at the country level.
5. Open data access to selected original data and indicators would be an important help to the countries for comparing the evolution over time.

 
<< Start < Prev 1 2 3 Next > End >>

Results 1 - 15 of 32
 
 
Related Items