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Recession in USA, EU, Japan - China became the Largest Economy PDF Print E-mail
Monday, 04 September 2017

Overview of the decade of financial crisis in the world

1. The damage of the world financial crisis needs to be studied in the broader perspective of beyond GDP framework. The fall in GDP underestimated the extent of damage of the financial crisis in the Triad (USA, EU, and Japan), as the greater part of the developed world. The deterioration of the employment rate and especially the fall in the share of the capital formation in GDP seriously hindered the medium to long-term capabilities of these economies, not to mention the worsening of inequalities.


Source: own calculations based on OECD (2017a, 2017b) and World Bank data (2017c)

The detrimental effect of the world financial crisis beyond that on the GDP level and on the GDP growth rate has been felt with even greater intensity in the deterioration of employment rates, investment share in the GDP, in the increasing risk of poverty, and increasing income inequality. This has diminished the welfare and growth capabilities of these economies during the decade.

2. For the overall magnitude of GDP in constant prices China surpassed EU28 in 2015 and the USA in 2013; for the overall gross capital formation China surpassed EU28 in 2012 and the USA in 2010. The two opposing directions: the decline in the Triad and the high growth rate in China, changed the ranking between them, currently being 1. China, 2. EU28, 3. USA. 

However, one should add that the level of GDP per capita (as distinct from the overall GDP level) in the Triad is still much higher than in China. Yet, as an effective developing country, China is progressing fast also in this respect.

3. In addition to the usual statistical measures, such as percentages and growth rates, we shall describe the severity of the great recession with statistical measure S-time- distance, which measures distance in time (e.g. years) when the same level of the indicator has been reached. The time distance methodology is available in the large study (Sicherl, 2011a) and on www.gaptimer.eu. The paper (Sicherl, 2011b) published by the OECD Statistics Directorate can be freely downloaded from OECD at http://dx.doi.org/10.1787/5kg1zpzzl1tg-en. It can show how much time has been needed for the indicator to recover to the level before the crisis. The results are: to regain the 2007 level of GDP per capita, Japan needed 6 years, the USA 7 years and EU28 8 years; for the employment rate EU28 needed 8 years, while in 2015 the USA is still below its 2007 level; for the investment effort as the share in GDP the 2006 level has not been yet recovered in Triad: a delay of more than 10 years. This gives politicians and especially the general public unambiguous message that the financial crisis resulted in lost growth potential in this field for more than a decade. 

4. While the 2015 and 2016 values of GDP per capita were in all three economies higher than the pre-crisis levels, the situation on the of investment effort is completely different; the investment shares in GDP were distinctly below their respective pre-crisis levels. It seems that the damage done by the financial crisis has in this respect meant a delay of a decade or more.

The speed of change was swift. For gross capital formation in constant prices China surpassed the value of the USA in 2010 and the value of EU28 in 2012. In 2006 the magnitude of investment in China was still more than 50% lower than in the USA and EU28. In terms of time distance the 2006 value for China was reached in Japan 10 years earlier, 18 years earlier in the USA and more than 30 years earlier EU28. With great speed China reached the value of the USA in only 3 years and that of EU28 in 6 years.

Closing remarks

After slow recovery, growth may be picking up but we need to know where we start from. The fundamentals need to be improved. As the quality of financial regulation has not improved substantially on either side of the Atlantic, these domains are prone to further deterioration anywhere in the world. Even more so, possible further financial crisis could come around if these financial institutions are not properly regulated.

FULL TEXT: 

 
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.

 
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.


 
 
 
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