Part 1 of 2
1. ESCAP’s Inclusive Growth Index
In line with the ESCAP’s mandate to bring 743 millions of poor people in Asia and the Pacific region into the economic mainstream, ESCAP’s recently launched 2015 survey report creatively and innovatively proposes a composite index of 15 separate indicators to measure inclusive growth for sustainable development.
This is the first time where inclusiveness has been defined technically and quantitatively.
There are five indicators or variables for economic opportunities, five for environmental sustainability and five for social opportunities. Averaging the five subcomponents under each dimension and arriving at a subtotal, it would be possible to rank the performance of countries separately by economic inclusiveness, social inclusiveness or environmental sustainability, or any combination of two or all three.
Two of the five social opportunities, and one of the five economic opportunities variables or indicators are gender sensitive. Therefore, about 20% of the total weight in ESCAP’s inclusiveness growth index is inclined towards gender balance. The index is sensitive to gender issues in those specific sense.
Among the selected countries, adopting this composite indicator of inclusiveness puts Kazakhstan on the top of the list of 16 countries, which had uniform data for 2000-2012 period. Kazakhstan is a nation of 27M people with a GDP of $ 420B. Russian Federation is number two and Thailand is number three. Among the 16 countries, Cambodia, Nepal, India and Pakistan are among the last. Bhutan is not part of this ranking because it could not supply data for the required period.
The range of variables included in the ESCAP inclusiveness indicators and the UN’s “List of Proposed Preliminary Indicators (February 2015)” for SDGs have much in common. The UN’s document is a compilation of the indicators proposed for discussion, though the UN document did not indicate which indicators were going to be selected. It also included GNH index as a possible indicator for alternative progress, though due to lack of advocacy from Bhutan’s side, it appears that it may not last through further rounds of selection.
But the originality of ESCAP’s approach is that, after careful selection of the variables, the constituent variables are neatly grouped and then aggregated into a single number. ESCAP’s 2015 survey report uses data from the last 23 years – from 1990 to 2012- to assess the trend of inclusive growth in the Asia Pacific region. As the report mentions, the variables used should the output variables, as opposed to input or process variables.
2. Bhutan’s Inclusive Growth Performance
How has the trend of inclusive growth, defined economically, socially and environmentally, been in Bhutan? This was not answered at all in ESCAP 2015 survey report because the trend data since 1990 for Bhutan has not been supplied to ESCAP, as it does not exist for the entire period. But as regards selected variables for a certain year that can generate cross-country comparisons, Bhutan’s performance is shown sporadically in many cross-country comparative charts. In this article, an attempt is made to fish out or calculate data for the missing information for Bhutan.
5 Variables or Indicators of Economic Opportunities
Variable 1: Gini coefficient was 0.416 in 2003 and 0.352 in 2007. It increased slightly to 0.36 in 2012. Social development and per capita income can be adjusted by inequality to show inclusiveness foregone.
Among the bigger nations, South Africa has supposedly the highest income gini at 0.62. Gini measures relative, not absolute, income. Higher inequality can also be due to structural change in population. However, “Inequality remained stable, allowing the full effect on poverty reduction”. What has been not measured is asset, especially household land ownership gini. Such gini coefficient can be lower and decreasing than income gini coefficient because of poverty focused land distribution by His Majesty the King.
Variable 2. Ratio of income share of the highest quintile to the lowest quintile was 7.3 in 2012. Ratio of highest to lowest quintile was 7.47 in 2003, 4.01 in 2007. This ratio is also known as ratio 20:20 and measures concentration of consumption between the two groups. “The 20:20 ratio for example shows that Japan and Sweden have a low equality gap, where the richest 20% only earn 4 times the poorest 20%, whereas in the UK the ratio is 7 times and in the US 8 times.”
In 2012, average consumption expenditure of a Bhutanese was Nu 48,418 per year. The monthly per capita consumption expenditure (Nu 10,765) of the top 20% of the Bhutanese people in 2012 was 7.3 times higher than the lowest 20% (Nu 1,471). The difference had not narrowed down much since 2003. The distribution of consumption expenditure is static. Ratio 20:20, as it is also known, has not decreased.
Variable 3. Poverty headcount ratio of those below $1.25 per day in PPP was 2% in 2012, or in absolute size about 14,000 people. Extreme poverty has ended except for the 14,000 or so people.
Poverty rate by our Bhutan’s own threshold was 12% in 2012. Consumption expenditure poverty line is primarily made up of food poverty line estimated at Nu. 1,154 per person per month. Thus it is food component that will exert influence on poverty line. Non-food poverty line is defined to be Nu. 550 per person per month. For 2012, the expenditure poverty line (also called the poverty line) composed of food + non-food = Nu. 1,704 per person per month in Bhutan.
Variable 4. Ratio of female to male labour force participation was 96.2 in 2012. It was 51.1% in 2001.
Variable 5. Unemployment rate was 2.1 in 2012. It rose to 2.9 in 2013. These percentages are viewed as full-employment state in any countries such as China, South Korea or Hongkong. But the Bhutanese numbers are deceptive.
According to Bhutan Living Standard Survey (BLSS) 2012, which is similar to Labour Force Survey (LFS) in findings, the employed number in 2012 is 239, 049. Unemployed number was 6,727 (2.7% unemployment rate, which is slightly higher than LFS figure). The breakdown of the employed number gives a sobering picture of the situation. “Unpaid family workers make up the largest proportion of all employed persons, at 44%.” The size of unpaid family workers is marginal in industrialized nations. So is agricultural labour.
The method and definition is suitable for industrialized nations where there is clear demarcation of being employed or unemployed along the lines of being regularly paid or unpaid. Agriculture absorbs below 5% of labour in industrialized countries whereas it forms almost majority (over 60%) in Bhutan. But Bhutan’s agriculture labour is not full time; there is huge underemployment. So the same methods of classification and definition are not suitable in the context of Bhutan.
ESCAP’s 2015 survey report points out that in the Asia Pacific region, 54.7% of the employed are what it calls “vulnerable employment, consisting of own-account and contributing family workers” (p. 29). 44% of employed in Bhutan can be termed vulnerable employment.
Unemployment is quite high among the youth. Perhaps it might be worrisome if the definition of unemployed is changed. Unless a new strategy is promoted, Bhutan may find demographic disappointment instead of a demographic dividend.
To be continued
Contributed by Karma Ura