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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: 


 
Just published: New book on time distance by Professor Pavle Sicherl PDF Print E-mail
Thursday, 01 March 2012

Book: Time Distance in Economics and Statistics - New Insights from Existing Data


The book on time distance methodology by Professor Pavle Sicherl was published in Vienna. The time perspective, which no doubt exists in human perception when comparing different situations, is systematically introduced in comparative analysis both as a concept and as a quantifiable measure. Time distance is an innovative approach for looking at time-series data, it offers two improvements in the present state-of-the-art of comparative analysis.

The first one is analytical and statistical – two novel generic statistical measures S-time-distance and S-time-step are generalised to complement conventional measures in time series comparisons, regressions, models, forecasting and monitoring, and to provide from existing data new insights due to an added dimension of analysis. Expressed in time units they are intuitively understandable; they can be compared across variables, fields of concern, and units of comparison.

The second component is normative and theoretical, related to subjective perceptions, policy and welfare issues. Time distance concept can influence the perception and decisions of people when they are assessing their relative position in the society and across countries over time. Concept of the ‘overall degree of disparity’ combines static and time distance measures of disparity with the potential to bring new understanding in economics, management, research and statistics. Empirical applications analyse time distance differences between countries in the world, OECD and EU, regional disparities, transition depression, ICT and digital divide, and monitoring implementation of UN MDGs and Lisbon strategy in the EU.


 
50 years of OECD countries at a glance PDF Print E-mail
Monday, 07 February 2011

A visual overview of 50 years in OECD countries with time distance methodology


At the occasion of the 50th Anniversary of the OECD SICENTER presents a visual overview across several decades of the development for all present OECD countries for selected indicators based on the time distance methodology.

Time distance concept arranges the same data from the OECD Factbook 2010 in an additional way so that data are arranged by selected levels of indicators showing in which year these levels of the indicators were achieved by given country. The level-time matrix compresses original data from the usual time series table in the Factbook 2010 in a new easily understandable way while still containing the most important information. The table-graph in yellow colour shows the range of values achieved for a given country over the period from available data. This allows for a quick level comparison of the situation across the whole set of OECD countries and individual countries as well as of how many steps over levels of indicators was achieved a given country.

The selected indicators are: life expectancy at birth, infant mortality, road fatalities, projections of population growth rates and of elderly population until 2050, employment rates, tertiary attainment, gross domestic expenditures on R&D, telecommunication access paths, gross domestic product per capita, international trade in goods and services, current account balance, and general government expenditures as percent of GDP. This additional way of presentation over many countries and many years provides a much better summary and understanding.




The level-time table-graph for share of elderly population covers the period of 100 years (1951-2050). It is difficult to imagine that the usual table of 34 countries across 100 years with 3400 entries would allow such a compressed essence of the long-term information and visualisation for a relevant perception of the situation. 

For the majority of the selected indicators it is obvious at a glance that the differences between OECD countries are large. For instance, for gross domestic expenditures on R&D, GDP per capita and tertiary attainment the indicator values for the best countries are 4 to 5 times higher than for the lowest countries. While best practices are of interest it is obvious that policies have to be differentiated and adjusted to such wide differences in the circumstances. There is a wealth of information and possible comparisons in the tables; the comments provided are just some examples of such interpretations. ‘Seeing with new eyes’, to borrow the phrase from Marcel Proust, creates new knowledge, better understanding and material for telling new development stories.    
 
Annex 1 shows using the example for life expectancy how the level-time matrix can lead further to derivation of two novel statistical measures: S-time-distance and S-time-step.  All three look easily understandable and are bringing even to general public additional understanding of the situation to build their perception about the disparities involved. S-time-step shows how many years were needed in the past to increase one year in life expectancy, thsi indication of dynamics depends only on the developments in the given country. The values of S-time-distance in the table compare the value for a country to the benchmark OECD average, showing the lead (-) or lag (+) in time against the OECD average.

 
S-time-distance perspective on the current crisis in CIRET conference New York PDF Print E-mail
Thursday, 25 November 2010

Providing new insights from Business Tendency Surveys and GDP data


The paper ‘S-time-distance perspective: providing new insights of the current crisis from BTS
and GDP data’ prepared by P. Sicherl, J. Cirjaković, M. Remec was presented in the session
New Methods at the 30th CIRET Conference, New York, October 2010. The time distance
methodology deals here with the description of the current economic crisis with selected
indicators from the Business Tendency Surveys and GDP for EU and selected countries. This
makes it possible to analyse the severity of the crisis in the two dimensions: decrease in
the static index from the peak in 2008 and the S-time-distance lag indicating how many
years earlier the same levels of GDP were already achieved in the past.

The latter indicates that e.g. for EU27 this would amount to 3.3 years for 2009, 3.9 years
for 2010 and to 4.4 years for 2011. Alternatively, this means that the forecast level for 2011
would be lower than that achieved in 2007. On the other hand, S-time-distance measure
clearly shows how debt crisis has weakened the possibility of higher growth rate in the near
future. In 2011 the investment rate for EU27 would still be around 10% below 2008 value and
about at the level attained 14 years ago (about 1997 level). For the USA the investment rate in
2011 is expected to be about 13% below the 2008 value at a level before 1994 resulting in S-
time-distance of about 17 years. For investment rate Triad countries are expected to fall
back to the levels in past century which could not be perceived by looking only at the static
indexes.


Comparing maximum and minimum values of ESI and GDP in the period 2007-2009 shows
different development in the declining and recovery phases. ESI for EU27 started to decline
after June 2007, while GDP started to decline after first quarter of 2008, this means
8 months later than ESI. In the declining phase ESI offered a leading warning of about 8
months, showed a fall of about 21 months from the maximum in June 2007 to the minimum
levels in March 2009, while the fall in quarterly GDP from first quarter of 2008 lasted about
15 months. In the current crisis ESI showed much higher volatility than GDP. As mentioned
before, this may indicate that much greater decline of ESI than of GDP might be a sign
that the economic sentiment goes considerably beyond GDP and include also problems
related to the decrease in the investment rate, employment and other conditions.

The examples show that more attention needs to be paid to levels and time, which means
that S-time-distance can bring about additional information for a more thorough analysis and
understanding of the situation. An obvious extension would be to repeat such analysis for
the ESI components and also on types of indicators like OECD composite leading indicators.
There are lessons that can be learned with the new methodology from comparisons
across indicators and countries and lessons from a more detailed analysis within a given
country.

 
 
 
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