Human Development Measurement Francesco Burchi Francesco burchi die-gdi de

Human Development Measurement Francesco Burchi Francesco. burchi@die-gdi. de Master HDFS 1

Table of Contents n n n Measuring Human Development dimensions Human Development Index: goal, components and aggregation procedure New HDI Inequality-adjusted HDI Gender Inequality Index Master HDFS 2

How to measure HD? n n Education is a core dimension Educational indicators should be divided in: 1. Input indicators (quantity and quality) 2. Output indicators (quantity and quality) 3. Outcome indicators (education-related functionings) which are result of both qualitative and quantitative educational inputs and outputs 4. Impact indicators Master HDFS 3

Input indicators n n n n Public expenditure in education; Private expenditure in education; School resources; Teachers/students ratio, Class size and instruction Teaching material; Quality and adequacy of curriculum Master HDFS 4

Output indicators Measures of ACCESS: n Enrolment rate; n Attendance rate; n Dropout rate, n Repetition rate Master HDFS 5

Outcome indicators (functionings) functionings n n Completion rates (in between output and outcome indicator); Expected number of completed years of schooling Literacy rates; Standardized test measures of student and adult achievement in terms of literacy and numeracy Master HDFS 6

Impact indicators Effects on other capabilities such as nutrition and health? n Effects on economic production, personal earnings or economic growth? n Master HDFS 7

The Human Development Index (1990) n n It was elaborated following strong criticisms towards GDP growth “Any measure that values a gun several hundred times more than a bottle of milk is bound to raise serious questions about its relevance for human progress” (ul Haq 1995, p. 46). Master HDFS 8

Old and New HDI n n It is a composite indicator that cannot reflect the whole Human Development Approach It has the main objective to shift the focus from the means of development to the ends. The HDI was introduced to cover both social and economic choices. A composite index was constructed rather than a plethora of separate indices. Master HDFS 9

Old and New HDI (2) n n One of the most important decisions was to keep the coverage and methodology of HDI quite flexible – subject to gradual refinements as analytical critiques merged and better data became available. The old HDI is available for 177 countries, the new HDI 187. Master HDFS 10

HDI: Which components? n n n Components should reflect basic capabilities, capabilities which are those universally accepted and without which people are harmed (Fukuda Parr 2003, 97 -99). Problem of operationalization: only functionings How many components? Problem of multicorrelation, double-counting and simplicity. Master HDFS 11

HDI: Components (2) n n Final components: 1. Long and healthy life 2. Knowledge 3. Decent standard of living The first two are ends, the third is a means. It is a proxy for all other variables not reflected in the first two components. Master HDFS 12

HDI: Components (3) n n Other components? Long debate…environment, mortality rates, political freedom… The index should be taken with caution: choice of dimensions is also based on data availability (Sen). Master HDFS 13

The OLD HDI Master HDFS 14

Units of Measurement n n Each component is measured by one or more variables, which have different units of measurement. Standardization: Evolution over time: before the minimum was the existing minimum value, now most extreme result in the previous 3 decades or forecasted in next 3 decades. Each component has a value >=0 and <=1. Master HDFS 15

Component 1: Long and healthy life n n n Variable: life expectancy at birth Unit of measurement: years. Standardization: Life Expectancy Index= Max= 85 Min=25 Master HDFS 16

Component 2: Knowledge The dimension “knowledge” is measured by a weighted mean of the following variables: - Adult literacy rate (weight 2/3) - Combined gross enrolment rate (weight 1/3). It was added later. n The GER is calculated by expressing the number of students enrolled in primary, secondary and tertiary levels of education, regardless of age, as a percentage of the population of official school age for the three levels. n Master HDFS 17

An example Albania 2002 Adult Literacy Rate Gross Enrolment Index Education Index = 2/3 (0. 853) + 1/3 (0. 69) = 0. 798 Minimum = 0 Maximum = 100 Master HDFS 18

Component 3: Decent standard of living n n GDP per capita is adjusted with PPP (purchasing power parity) and with the logarithm because achieving a decent standard of living does not require unlimited income It is measured in USD Minimum=100 Maximum=40, 000 Master HDFS 19

Aggregation n Weights: there is no evidence regarding which capability is more important, thus each of the three dimensions has a weight equal to 1/3. Aggregation procedure: simple mean. HDI=1/3(Life Expectancy Index)+ 1/3(Education Index)+ 1/3(GDPIndex) Master HDFS 20

HDI tables n n n HDI Value (between 0 and 1) HDI Ranking Division of countries in 3 groups: - High Human Development Countries (HDI>= 0. 800) - Medium Human Development Countries (0. 800>HDI>=0. 500) - Low Human Development Countries (HDI<0. 500) Master HDFS 21

Proposals of alternative HDI n n n Standard of Living: “median income” in place of “log per capita GDP” (Brazilian HDR) Knowledge: school attendance rate instead of enrolment rate (American HDR) Inclusion of inequality-adjusted functionings (Hicks, 1997; Foster et al, 2005). Aggregation methods different from simple arithmetic mean. Context-based indicators Master HDFS 22

The NEW HDI Master HDFS 23

HDR 2010 & 2014: changes in the HDI (http: //hdr. undp. org/sites/default/files/hdr 14_tec hnical_notes. pdf ) Goalposts are changed: max and min are not observed, but set on a theoretical basis. Min. mean years of schooling =0 (societies can subsist without formal education), max. =15 (projected maximum of this indicator for 2025. 2. The Knowledge Component is now measured by two variables (with equal weight): A) Mean years of schooling; B) Expected years of schooling - Critique to the binary nature of adult literacy 1. Master HDFS 24

HDR 2010 & 2014: changes in the HDI (2) n n Mean years of schooling of adults (years) = average number of years of education received by people aged 25 and older in their lifetime based on education attainment levels of the population converted into years of schooling based on theoretical durations of each level of education attended (Barro and Lee, 2010) Expected Years of schooling of children (years) = number of years of schooling that a child of school entrance age can expect to receive if prevailing patterns of age-specific enrolment rates were to stay the same throughout the child’s life (UNESCO Institute for Statistics, 2010). Master HDFS 25

HDR 2010 & 2014: changes in the HDI (3) 3. PPP-adjusted per capita GNI replaces PPPadjusted per capita GDP in the component “decent standard of living”: this is because GDP is the monetary value of goods and services produced in a country, GNI is the income accrued to residents of a country, including international flows such as remittances and aid, and excluding income generated in the country but repatriated abroad. - Moreover, natural logarithm replaces that with the base of 10. Master HDFS 26

HDR 2010 & 2014: changes in the HDI (4) 4. Geometric rather than arithmetic mean as aggregation method for the final HDI. Poor performance in any dimension is now directly reflected in the new HDI, which captures how well a country’s performance is across the 3 dimensions. No longer perfect substitutability across the dimensions: a low achievement in one dimension is not anymore linearly compensated for by high achievement in another dimension. Penalizes countries with uneven development across dimensions! Master HDFS 27

The New HDI Master HDFS 28

Formula for the new HDI (see technical notes HDR 2014) Education Index = (Mean years of schooling + Exp. years of schooling)/2 New HDI = Indexlife 1/3 · Index. Education Master HDFS 1/3 · Index. Income 1/3 29

HDI Vs. GDP n n n GDP focuses on the average income owned, while HDI tells us also about the DISTRIBUTION and the USE of income for valuable purposes. GDP cannot be adjusted following people’s diversity (disability, age, sex, metabolism = conversion factors). E. g. having weapons is much more valued than having milk due to monetary terms using only GDP. HDI shows directly the areas where performances are eventually low, thus where interventions should be made. HDI can be disaggregated, by gender, ethnicity, region …. HDI can also tell us about future economic growth because having accumulated human capital (education and health) can lead in the future to the enlargement of economic possibilities. Master HDFS 30

HDR 2015 HDI 2015 Table 1: http: //hdr. undp. org/en/composite/HDI n n Master HDFS 31

The Inequality-adjusted HDI Master HDFS 32

Inequality-adjusted HDI (2010) (see notes HDR 2014 and http: //hdr. undp. org/en/faq-page/inequalityadjusted-human-development-index-ihdi#t 293 n 91 ) n n n The IHDI adjust the HDI for inequality in the distribution of each dimension across the population IHDI=HDI if there is no inequality in all the dimensions (thus, IHDI<=HDI) Data source different from HDI data source because we need information on the distribution of life expectancy, schooling, and disposable income/consumption. Master HDFS 33

IHDI: Step 1 n Measuring inequality in each of the 3 dimensions Geometric mean of the distribution Arithmetic mean of the distribution n n Ax >=0 because geometric mean cannot be higher than arithmetic mean The higher the difference between the two means, the higher inequality is. Master HDFS 34

IHDI: Step 2 n Adjusting the dimension indices for inequality Inequality measure Dimension Index n The inequality-adjusted income index, I*IIncome, is based on the unlogged gross national income (GNI) index, I*Income. Master HDFS 35

IHDI: Step 3 n Aggregation through geometric mean Master HDFS 36

The Gender Inequality Index (2010) n n Replaces the Gender-related Development Index and the Gender Empowerment Measure Main drawbacks of past indicators: n n Unreliable data especially for genderdisaggregated income Mix of absolute and relative variables Main focus on gender bias in elites and urban areas (in the case of GEM) Computed for 140 countries Master HDFS 37

GII: main purpose To highlight women’s disadvantage in 3 dimensions: 1. Reproductive health 2. Empowerment 3. Access to labour market Master HDFS 38

GII: Variables (http: //hdrstats. undp. org/en/indicators/24806. html) n n n Reproductive health: maternal mortality ratio and adolescent fertility rate (number of births per 1, 000 women age 15 -19 years) Empowerment: share of parliamentary seats by sex and attainment at secondary or higher levels Labour market: labour market participation rate (Percentage of the working-age population (ages 15– 64) that actively engages in the labour market, by either working or actively looking for work) Master HDFS 39

GII calculation n n see technical notes HDR 2010: http: //hdr. undp. org/en/media/HDR_2010_EN _Tech. Notes_reprint. pdf and http: //hdr. undp. org/en/statistics/gii/ Master HDFS 40

Policy use of indicators n n GDP Index, HDI, IHDI, GII (and previous GEM and GDI) should be analyzed together and in a historical perspective in order to understand overall characteristics of a country and to come out with better development policies. Comparison across indicators is of easier interpretation with rankings. A good tool is calculating the difference in a country’s rankings in two different indicators. E. g. Support-led or growth-led approach? Sustainable HD or not? Gender biased policies? Some cultural or religious aspects are a constraint or a positive engine for HD? Geographical uniformity? Regions reflect similar human development levels and trends? Master HDFS 41

Further tools n n HDI Rank – IHDI Rank to measure the loss of position of a country with the inclusion of inequality in the 3 dimensions in the measure of development. (HDI* – IHDI)/HDI* to measure the percentage reduction of the IHDI from the HDI* (i. e, the HDI without logarith of GNI). Master HDFS 42

PPP Purchasing power parity in US$ The purchasing power of a country’s currency, defined as the number of units of that currency required to purchase the same (or very similar) representative basket of goods and services that a US dollar (the reference currency) would buy in the United States. Master HDFS 43