WWDR: Development Index
Draft of December 2 2001
An Indicator for Human Development
Hadi Dowlatabadi
Introduction
The goal here is to devise an indicator for development. This indicator is being sought in
addition to more conventional measures of water infrastructure in a region and the
region’s formal measures of economic performance. Defining such a metric can take
many approaches, such as a focus on institutions for human cooperation and resource
management. I have adopted a different path in order avoid the challenge of formal vs.
informal institutions and also to try to get to the heart of the question rather than play at
its periphery. In doing so, I may have become too much of a functionalist, but that is the
bias in my training and how I frame problems.
Here are the basic challenges inherent in defining an indicator of Human Dimensions of
Development, as I see them:
1) What is meant by "human dimensions"?
2) What are the ways in which this can be measured?
3) Where are the measures most useful?
In the text that follows, I offer a first attempt at an answer. I welcome critiques of both
the framing and the answer.
What is meant by Human Dimensions of development?
I think that extracting services from our environment and coping with natural hazards are
both features that we share with other living entities.1 What makes us "human" is perhaps
to be found where other living beings play a less active role "against the tendencies of
nature."
If you believe in Darwin, the most important tendency in biology is selection pressure
based on fitness for an environmental condition. I think the defining feature of humanity
is how we expend resources to keep a wider spectrum of fitness alive. This wider
spectrum has both our youth and our old. The young carry the new genes from which our
stock will grow. The elderly carry the memories and experiences that define us. The
latter group has lost its relative importance since the advent of literacy.
In addition to cheating "natural selection" we have the capacity (not always exercised) to
balance how we allocate our resources to capital formation vs. operation and maintenance
of the system that extracts services from nature.2 Social organizations (specifically the
confidence to pool resources and lend capital) are key to economic development. The
1
I interpret one the scientific definitions of life is “a local fold in entropy.” In other words, life performs
the miracle of rearranging resources and energy into a more ordered state in a spatially and temporally
bounded package. Once its gone, the inevitable physical diffusion of energy and loss of order resume.
2
This is where the link between David Major's piece on economic performance, Tol and Yohe paper on
adaptation, and my piece can be made.
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WWDR: Development Index
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roots of credit unions can be found in Quakers history. Much of what we take for granted
as part of the formal economy came about because social organizations grew so well
established that the institutions could act in place of a personal network of social
contacts.
What can be measures of Human Dimensions of Development?
Humans cheat natural selection through adaptation. Various modes of adaptation are
often combined to make the environment inhabited by humans a hospitable one. Water,
shelter, fire, food and waste disposal are all inanimate essentials to survival. Dealing with
animals, coping with neighbors, surviving diseases and parasites are the animate side of
the same coin. Knowledge gathering and transfer and genetic drift are the two
mechanisms for enhanced adaptation and survival skills through time.
Children are how new genetics enter the population3 and how we pass on knowledge.
Their preparations and life experience are how we develop new skills and knowledge.
The elderly are where much of the knowledge resides (in pre-literate societies). Thus, a
healthy population and any form of education/apprenticeship are critical to cheating
natural selection. Where the world is changing, this knowledgebase also needs to change.
Some social organizations do not encourage this process. Clearly, a mismatch between
knowledge and environmental conditions will lead to dysfunctional adaptive practices.
Possible Metrics
Given the importance of children, a natural indicator of development is child mortality.
This metric is strongly modulated by vaccination, a relatively easy intervention that can
be provided by outside entities. In fact, the worse the raw values for this indicator, the
more likely that the attention of outside agencies are raised. The efforts of these groups
will be accepted in all but the most isolationist regions and hence a “J-curve” of
achievement will be evident where the bottom of the “J” will often be a true measure of
local capabilities, while the truly desperate regions will have a higher level of
achievement – achieved as a consequence of outside interventions.
Another measure would be malnutrition among children. Malnutrition is an outcome of a
number of factors:
selective allocation of food among offspring,
household level inadequacy of food,
poor hygiene, and
poor water quality.
All of these are related to different facets of the human dimensions of development.
Water quality and quantity are critical to good nutrition and health. In order for children
not to suffer malnutrition, society must solve a number of social issues related to
management of water resources. In a sense, where water stress is greatest, the
achievement of the same level of nutrition is a testament to local success in developing
this critical resource more effectively. Therefore, the proposed indicator would be based
3
With advances in genomic technologies, we are on the threshold of an era when this statement will no
longer be true.
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on malnutrition among children after accounting for income and water availability. The
correction for these two factors is an attempt to tease out what the local social
organization has achieved given the local context.
Desirable Features of Indicators
There are as many ideas about good indicator designs as there are indicators. I see no
reason why I should abandon this great tradition. Therefore, staying true to a functionalist
approach, I assert that an indicator is useful when it has been designed with three criteria
in mind:
have a range that reflects what is locally possible (e.g., water availability);
focus attention on achievable objectives (i.e., have an upper bound that can be
achieved given the resources that are locally available);
have resolution about the system conditions where it matters (i.e., use the
majority of a 5 point scale indicating different identifiable stages of achievable
conditions).
Constructing a fair indicator for human dimensions of
development
A fair indicator should recognize that economic power can be a substitute for social
organization and development. As proof let me offer a simple comparison of life
expectancy in centrally planned Asian countries versus other Asian nations – see table 1.
Table 1, Comparing the impact of social institutions with wealth †
National Group
Centrally
Intercept
Coefficient for increase in
(i.e., life expectancy
life expectancy with wealth
at no income)
(natural log of GDP/cap.)
Adjusted R2
25.1
5.9
0.53
34.9
4.2
0.80
planned Asia
Other Asian
nations
Note: † Based on World Bank data on life expectancy and raw GDP per capita.
The figures in Table 1 reveal that such simple models can have surprising explanatory
power with Adjusted R2 of over 0.5. They also attest to the power of wealth when starting
from a low income – i.e., the logarithmic relationship between income and life
expectancy. The estimated model parameters also suggest that by the time a community
reaches an income of $320 per capita, the centrally planned communities (here taken as
being equivalent to having social development programs) will deliver a higher life
expectancy than market based economies of similar per capita income. The life
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Draft of December 2 2001
expectancy achieved by a centrally planned economy with GDP per capita of $1000 is
equal to a nation with GDP per capita twice that level (i.e., $2000/capita) if based on a
market economy.
The general idea presented above will be refined further and applied to childhood
malnourishment. The reason I am choosing malnourishment rather than mortality is that
mortality rates can be changed dramatically through vaccination programs. These require
less persistent effort than feeding and nurturing children a healthy environment.
Malnourishment can also be a consequence of frequent gastro-intestinal diseases, often
associated with water-born pathogens. Therefore, malnourishment is an endpoint for
both persistent effort to maintain children’s health and local water quality.
Table 2, Correlation between measures of income (GDP/cap (ppp corrected)
Water Availability (m3/cap) and Childhood malnourishment rate (%).†
% of Children under
GDP per capita (ppp
Water
age 5 malnourished
corrected)
availability
% of Children
under age 5
malnourished
1.000
GDP per capita
(ppp corrected)
-0.441
1.000
Water availability
-0.135
0.038
1.000
Note: † Based on World Bank data on water availability, and purchasing power parity corrected GDP per
capita, and % of children younger than 5 who are malnourished.
This simple correlation reproduced in Table 2 presents evidence of the strong negative
relationship between income and childhood malnourishment. A simple indicator of water
availability does not have a strong correlation with malnourishment. Furthermore, there
seems little relationship between GDP per capita and water availability. Thus, I used
GDP/capita and water availability as independent variables that may be used to estimate
malnourishment in different countries.
Data availability limited the calculation of a 5 point indicator to 81 nations and territories.
In many instances, there is little data on level of malnutrition. In a minority, the missing
data are economic measures of GDP/cap and water availability. Nonetheless, the
approach adopted here may be applied to as many complete datasets as can be assembled
for an chosen scale of analysis.
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WWDR: Development Index
Draft of December 2 2001
The first step is to define a simple linear regression model relating malnourishment (as
the dependent variable) to GDP/capita and Water availability per capita (as the
independent variables). The residuals of this regression equation are insensitive to scale
when log of GDP/capita are used as the independent variable. A summary of the
regression results are presented in Table 3.
Table 3, Regression Result Summary†
Model
Intercept
Coefficient for
Coefficient for
Adjusted
(i.e., %
malnutrition with
malnutrition with
R2
Malnutrition at
wealth
water availability
no income)
(log of GDP/cap.)
(m3/cap.)
Income only
76.33
-17.04
Income &
76.02
-16.78
…
-53.25 e-6
0.298
0.293
water
The regression models explored above can only explain about 30% of the variability in
observations. Something beyond water availability and economic power is responsible
for the level of malnourishment. Thus, the residual of this model, i.e., what is not
explained by economic and water availability is a measure of the human dimensions of
development. Normalized residuals from the model can thus be used to construct a 5
point indicator.
The normalized residuals span a ±2 sigma range from a mean of zero. A one sigma
positive residual indicates that the above model under-estimates the extent of
malnutrition. Thus, a region where such condition prevails has failed to attain the global
norm of human dimensions of development. The reverse is true for a region where
malnourishment is significantly above zero. By reversing the sign of the normalized
residuals and shifting their mean to 2.5, a five point scale can be constructed where a
score above 5 indicates a high level of development. Table 4 summarizes the indicator
values for the observations used to generate this scale. A histogram of the scores is
presented in Figure 1.
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WWDR: Development Index
Draft of December 2 2001
Table 4: Development Index
(1-5 Scale, with 5 being high)
Region/Nation
Score
Region/Nation
Score
Region/Nation
Score
Algeria
2.8
Georgia
4.2
Nicaragua
3.2
Angola
0.9
Ghana
2.4
Niger
0.6
Argentina
3.3
Guatemala
1.8
Nigeria
1.5
Armenia
4.1
Haiti
2.5
Oman
1.4
Australia
2.9
Honduras
2.1
Pakistan
1.3
Austria
2.9
India
0.7
Peru
3.0
Azerbaijan
3.8
Indonesia
1.1
Philippines
1.5
Russian
Bangladesh
0.0
Iran, Islamic Rep
2.9
Federation
3.6
Belgium
2.9
Jamaica
3.7
Rwanda
2.7
Benin
2.2
Jordan
3.8
Saudi Arabia
1.5
Bolivia
3.4
Kazakhstan
3.4
Slovenia
2.5
Botswana
2.1
Kenya
2.9
Spain
0.3
Brazil
3.1
Kuwait
2.7
Sri Lanka
1.4
Burkina Faso
2.1
Kyrgyzstan
3.5
Switzerland
1.7
Cameroon
2.5
Lao PDR
1.1
Tajikistan
2.3
C. African Rep
2.5
Lebanon
3.3
Tanzania
3.5
Chad
1.6
Lesotho 13
3.1
Thailand
1.5
Chile
3.0
Madagascar
1.4
Tunisia
3.2
China
3.4
Malawi
2.5
Turkmenistan
2.2
Colombia
2.7
Malaysia
1.5
Ukraine
3.8
Congo, D. Rep
1.9
Mali
2.8
United Kingdom
2.9
Costa Rica
3.2
Mauritania
2.5
United States
2.4
Côte d'Ivoire
2.4
Mauritius
2.2
Uruguay
1.9
Dominican Rep
3.4
Mexico
2.9
Uzbekistan
3.6
Egypt
3.4
Mongolia
3.4
Venezuela
0.2
El Salvador
3.2
Mozambique
3.0
Yemen
4.8
Gambia
2.5
Nepal
0.7
Zambia
3.5
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WWDR: Development Index
Draft of December 2 2001
Histogram of Indicators for
Human Development
35
30
25
20
15
10
5
0
1
2
3
4
5
Bins
Figure 1: Presents a frequency histogram of the development scores estimated using the
approach presented here. Nations/regions scoring below 3 are less developed than the rest
of the regions used to estimate this indicator if the approach proposed here has validity.
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