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Human Development Indicators. Human Development Community of Practice Meeting Bratislava, 19 May 2008. What is HDI?. Paradigm shift: people as mean of development vs people as end of development Simple and straightforward summary measure of development to replace GDP HDI

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Human development indicators l.jpg

Human Development Indicators

Human Development Community of Practice Meeting

Bratislava, 19 May 2008

What is hdi l.jpg
What is HDI?

  • Paradigm shift: people as mean of development vs people as end of development

  • Simple and straightforward summary measure of development to replace GDP

  • HDI

    • a composite index, from 0 to 1

    • mix both input and output indicators

    • three major areas of development—health, knowledge and decent standards of living

    • not comprehensive measure of development

    • relevant for both developing and developed countries

    • adequate quality of data, for cross-country comparisons

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Composite indices

  • Aggregate information from different (incomparable directly) areas

  • Indexing absolute values

  • Issues of discretionary choice:

    • Approaches to aggregation of individual components

    • Weights of individual components

    • Min/max values

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Human Development Index

Human Development Index (HDI)


Long and healthy life


Descent standard of living



Life expectancy index

Education index

GDP index


Life expectancy at birth

Adult literacy rate

GDP per capita (PPP US$)

Gross enrollment ratio

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Other Human Development Indices

  • GDI - Gender-related development index

    • average achievement adjusted to gender inequalities

    • focus of ‘functionings’ not opportunities

  • GEM - Gender empowerment measure

    • gender inequality in three dimensions

    • focus on opportunities, not ‘functionings’

  • HPI - Human Poverty Index

    • deprivations in the basic dimensions of human development

    • HPI1 - for developing countries

    • HPI2 - for developed countries

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GDI - Gender-related development index

  • average achievement adjusted to gender inequalities

  • ε—aversion to inequality

  • Estimating female and male earned incomes

    • Total GDP (PPP US$)

    • Ratio female to male non-agriculture wage

    • Female and male share of economically active population

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GEM - Gender empowerment measure

  • Gender inequality in three dimensions

    • economic participation and decision-making

    • political participation, and decision making; and

    • power over economic resources

  • Indicators

    • Women’s and men’s share of parliamentary seats

    • Women’s and men’s percentage shares of positions as legislators, senior officials and managers

    • Women’s and men’s percentage shares of professional and technical positions.

    • Estimated female and male earned incomes

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Human Poverty Index

  • Human Poverty Index 1

    • People not expected to survive to age 40

    • Adult illiteracy rate (% age 15 and above)

    • Population without access to safe water

    • Share of under-weight children under age five

  • Human Poverty Index 2

    • People not expected to survive to age 60

    • Share of people who are functionally illiterate

    • Long-term unemployment (as % of labour force)

    • Population below income poverty line

  • α is ‘attention to deprivation’—the higher is α, the greater weight of dimension with higher deprivation

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Problems with composite indices

  • Bringing together “apples and oranges”

  • Indexing absolute values – choice of min and max thresholds

  • Reliability of data inputs

    • GDP value fluctuates depending on PPP

    • Literacy – from census to census

    • Enrollment – different meaning for different educational levels

  • Depends on the analytical interpretation

    • What does an “HDI value” mean?

    • What does a rank mean?

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Data and indicators

  • Data

    • the status of given phenomenon

    • reflected in number

    • does not mean much out of a context

    • example: number of unemployed; income earned by person; household expenses for food; number of people with flu

  • Indicator

    • instruments that show the status and tendency of a given phenomenon

    • puts data in a context and extracts out of it its meaning

    • used to show progress or regress vis-à-vis certain targets

    • combination of at least two sets of data

    • example: unemployment rate; increase in income earned; share of food in household expenditures; morbidity rate

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Indicators based monitoring chains

Plus sustainability and positive externalities







Financial, physical resources

Goods and services produced by inputs (classrooms built, textbooks provided)

Access to, use of, and satisfaction with services (enrolment, repetition, dropout rates)

Effect on dimension of well-being (literacy)

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Sources of data

  • Administrative or routine data

  • Census data

  • Survey data

  • Surveillance data

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Administrative (or routine) data

  • Generated as a byproduct of events and processes

  • Primary purpose is management of processes

  • Event triggers data production

  • Summary and/or dissemination occurs later (but usually within one or two years)


  • Registration of birth

  • Immunization

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Administrative sources

  • Vital registration (births, deaths, etc)

  • Health systems (immunization rates, mortality rates, maternal health data, etc.)

  • Education registries (Enrollment and completion data, student-teacher ratio, etc.)

  • Employment registries (numbers employed, industry, level of participation)

  • Business (Industry, sector, size)

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Administrative sources: advantages

  • Less expensive than surveys, censuses (provided it already exists and they usually don’t in areas or countries that most need them)

  • Relatively up to date (usually available within one to two years after event)

  • Useful for short to medium term policy development

  • Often produced by agencies who are stakeholders in the policy process, e.g., health providers, schools, industry bodies, so incentive to participate

  • Good source for small-area disaggregated data

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Administrative sources: disadvantages

  • Very expensive to set up

  • Coverage may be insufficient or biased

  • Limited set of information collected

  • Put in one basket input and output indicators (some data may depend upon uptake of services)

  • May measure service provision rather than demand, and uptake rather than impact

  • Numbers may be inflated or missing in some areas (female infant mortality, custom marriages)

  • People may be reluctant to register

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  • Collect data from every unit in the population

  • 100% coverage (in theory)

  • Expensive

  • Time consuming

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Population census

  • Identify each member of the population

  • Collect certain basic data about them

    • age, gender, location, etc.

  • Modules to collect data on specific topics may be added

  • Normally about every 10 years

  • Modeling methods used to generate population estimates between censuses

  • Good for small-area poverty mapping

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Population census data

  • Advantage

    • Excellent coverage

    • Creates sampling frame for household surveys

  • Disadvantage

    • Potential for some bias – for example, could miss nomadic groups or homeless

    • May be inaccurate due to infrequency

    • Limited data collected

    • Lag before data produced

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Establishments censuses

  • Censuses of businesses, hospitals, other organisations

  • Provide a frame for later surveys

  • Collect basic data, as for population census

  • Problems:

    • Smaller or informal establishments often excluded

    • Establishments may change more frequently than households

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Sample survey data

  • Advantages

    • Cheaper and quicker than census, conducted more frequent than census, though usually only every 3 to 5 years

    • Can collect wider range of data than census and administrative systems

    • Reduced potential for bias than administrative data

  • Disadvantages

    • Sampling error since coverage < 100%

    • Requires more sophisticated design to ensure consistency and accuracy

  • Major types

    • Household surveys

    • Labor force surveys

    • Perception surveys

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Household surveys

  • Usually carried out every 3 to 5 months

  • Reporting usually takes about 1 year after completion of data collection

  • Sample of households drawn, and data collected about each member of the household

  • Focus is on socio-economic and health issues

  • Examples:

    • Multi Indicator Cluster Surveys (MICS)

    • Demographic and Health Surveys (DHS)

    • Living Standards Measurement Study Surveys (LSMS)

    • World Health Surveys (WHS)

    • Core Welfare Indicators Questionnaires (CWIQ)

    • Household budget surveys (HBS)

    • Household income and expenditure surveys

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Demographic Surveillance Systems (DSS)

  • Longitudinal monitoring of sentinel populations (60,000 to 100,000)

    • Follow same people every year through life of survey

    • 100% event registration

  • Advantages

    • Coverage of sentinel pop = 100%

    • Rapid data availability

    • Facilitates targeting and short term monitoring

  • Disadvantages

    • Few large clusters – potential for serious bias

    • Expensive to include many clusters

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When data is not there… Proxy indicators

  • Every indicator is a “proxy” of something. In current context, proxy indicators :

    • Reflect those aspects indirectly (its “face value” may mean different things)

    • Are contextually linked to certain aspects of reality

    • Highly dependent on contextual interpretation, need broader background

    • Can be used for estimates, perhaps for indices

    • Have advantages and problems that should be clearly stated

  • Both quantitative (“hard statistics”) and qualitative (“soft” data but also quantifiable)

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Examples of proxies – poverty

  • Quantitative:

    • Food share of household expenditures

    • Level of outstanding payments per category per household (HH member)

    • Eligibility for bank loan (share of approved loan applications of all submitted)

    • Usage of dental services (per capita in municipality)

  • Qualitative (perception based)

    • Can you afford…

    • Where spend vacations

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Metadata – data on data

  • Provides info on how data were collected, when, by whom

  • Give a clue on potential for bias

  • Assessment of quality of data

  • Tells how data items are defined, what methodology was used

  • Confirm definitions, facilitate decisions about compatibility of data from different sources

  • Guides and validates the interpretation of data and their indicators

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Abuse of indicators

  • Wrong indicator

  • Wrong interpretation

  • Comparing unlike scales (for example, comparing CPI of two countries which use different consumer baskets)

  • Errors in data or analysis methods

  • Using out of date values

  • Inappropriate extrapolation

  • Ignoring variability