PERCENT OF POPULATION LIVING BELOW POVERTY LINE

Social

Equity

Poverty

1.                Indicator

(a)      Name:  Percent of Population Living Below Poverty Line.

(b)      Brief Definition:  The proportion of the population with a standard of living below the poverty line.

(c)      Unit of Measurement:  %.

(d)      Placement in the CSD Indicator Set:  Social/Equity/Poverty.

 2.       Policy Relevance

 (a)      Purpose:  The most important purpose of a poverty measure is to enable poverty comparisons.  These are required for an overall assessment of a country's progress in poverty alleviation and/or the evaluation of specific policies or projects.  An important case of a poverty comparison is the poverty profile which shows how the aggregate poverty measure can be decomposed into poverty measures for various sub‑groups of the population, such as by gender region of residence, employment sector, education level, or ethnic group.  A good poverty profile can help reveal a number of aspects of poverty‑reduction policies, such as the regional or sectoral priorities for public spending.  Poverty comparisons are also made over time, in assessing overall performance from the point of view of the poor.

 (b)      Relevance to Sustainable/Unsustainable Development (theme/sub-theme):  Measures of poverty are a very significant consideration of sustainable development.  The eradication of poverty remains a major challenge for policy decision makers.  Furthermore, an integrative viewpoint which simultaneously takes account of development issues, resource use and environmental quality, and human welfare must be taken if sustainable progress is to be achieved.

 The % Population Living Below Poverty Line captures the prevalence of poverty by measuring the proportion of population for whom consumption (or any other suitable measure of living standard) is below the poverty line.  An increase in this indicator implies a worsening of the poverty situation with a greater proportion of the population falling below the poverty line.

 (c)      International Conventions and Agreements:  Not available.

 (d)      International Targets/Recommended Standards:  To reduce income poverty by half by 2015.

 (e)      Linkages to Other Indicators:  In general, this indicator is linked to many other sustainable development measures, for example, net migration rate, adult literacy rate, Gross Domestic Product per capita, and population living below the poverty line in dryland areas.  In particular, the  % Population Living Below Poverty Line is closely associated to the Poverty Gap Index and the Squared Poverty Gap Index which capture successively more detailed aspects of the poverty situation.  The  % Population Living Below Poverty Line measures how widespread poverty is, the Poverty Gap Index measures how poor the poor are, and the Squared Poverty Gap Index measures the severity of poverty by giving more weight to the poorest of the poor.

3.       Methodological Description  

(a)      Underlying Definitions and Concepts:  A poverty measure is a summary statistic on the economic welfare of the poor in a society.  There is no one universally accepted single measure of poverty.  A number of different approaches exist (see, for example, the methodology sheets for the Poverty Gap Index and the Squared Poverty Gap Index).  This methodology sheet guides the reader along certain key issues, such as the different approaches to measuring individual welfare, without prescribing decisions.  Consequently, it is directed at comparability over time within a given country, as it helps national practitioners specify poverty indicators that match their specific situation and preferred approach.  However, this is at the expense of international comparability.

 To compute poverty measures, the following questions related to identifying and defining the poor must be addressed first:

        i)   How do we measure an individual's economic welfare?

ii)  At what level of measured welfare is a person considered poor?

 (b)  Measurement Methods:  The  % Population Living Below Poverty Line (H) is the proportion of the population whose economic welfare (y) is less than the poverty line (z).  If q people are deemed to be poor in a population of size n then H=q/n. For computing the  % Population Living Below Poverty Line, estimates of individual economic welfare and the poverty line are required.

i)  Measuring Individual Welfare:  There are a number of different approaches to measuring welfare.  The approaches differ in terms of the importance attached to the individual's own judgment of well‑being versus a concept of welfare decided upon by somebody else.  The former would focus on measuring an individual's consumption of a bundle of goods and services.  An example of the latter would be defining welfare by the level of nutritional intake, even though people do not live on food alone, or make food choices solely on the basis of nutrition. Approaches in practice also differ according to how difficult it is to obtain certain types of data in specific settings.

  Typically one finds that poverty comparisons in developing countries put a high weight on nutritional attainments, consistent with the behaviour of poor people in a specific society.  A comprehensive measure of consumption (for example, total expenditure on all goods and services consumed, including non‑market goods, such as consumption from a farmer's own product) has been more popular than using current income in the development literature. This is due in part to the fact that incomes are harder to measure accurately.  Current consumption is also likely to give a better indication than current income of a household's typical, long‑term, economic welfare; income may fluctuate greatly over time, particularly in rural economies (see Ravallion reference in section 6a below).

  The following methods can be used for measuring individual standards of living:

       --Consumption per equivalent male adult: Since households differ in size and composition, a simple comparison of aggregate household consumption can be misleading about the welfare of individual members of the household.  Therefore, for any given household, an equivalence scale is used to approximate the number of single adults, based on observed consumption behaviour. There are a number of value judgments embedded in this practice; for example, differences in needs are reflected in differences in consumption.  Adult females and children are assigned a male equivalence of less than one since they typically consume less; however, that may not mean that they have lower "needs" but rather have less power within the household.  The existence of size economies in consumption may also mean that two people can live more cheaply together than apart (for a further discussion of these issues, see Ravallion reference in section 6 below).

       --Undernutrition: This is a distinct concept, although closely associated with poverty.  Undernutrition can be viewed as a specific type of poverty, namely food energy poverty.  There are a number of arguments for and against using this as a measure of well‑being.  A practical advantage is that this measure does not have to be adjusted for inflation and would not be constrained by any inadequacy of price data.  Measures of child nutritional status can help capture aspects of welfare, such as distribution within the household which are not adequately reflected in other indicators.  However, nutrition is not the only aspect that matters to the well‑being of people, including the poor.  Thus, poverty comparisons based solely on nutrition alone may be limited and deceptive.

  ii)  Defining the Poverty Line:  In practice, there are a number of alternative approaches to defining poverty lines:

       --Absolute poverty lines: An absolute poverty line is one which is fixed in terms of the living standard indicator being used (consumption, nutrition).  It is fixed over the entire domain of comparison, that is, a poverty line which assures the same level of economic welfare would be used to measure and compare poverty across provinces or different situations.  The poverty line may still vary, but only so as to measure the differences in the cost of a given level of welfare.  Absolute poverty lines are more common in developing country literature.

  The most common approach to defining absolute poverty lines is to estimate the cost in each region or at each date of a certain bundle of goods necessary to attain basic consumption needs (this is called the basic needs approach).  The most important component of basic needs is a recommended food energy intake, supplemented by essential non‑food goods.  To measure food energy requirements, one needs to make an assumption about activity levels which in turn determine energy requirements to maintain the body's metabolic rate at rest.  Once the food energy intake has been determined, and its cost has been calculated, an allowance for non‑food spending can be added by finding the total expenditure level at which a person typically attains the food component of the poverty line.  An alternative (lower) allowance for non‑food goods is to use the average non‑food spending of people who can just afford the food component of the poverty line: it can be argued that this is a reasonable lower bound for the non‑food component of the poverty line (see Ravallion reference in section 6a below).

       --Relative poverty lines: These have dominated developed country literature where many studies have used a poverty line which is set at, for example, 50% of the national mean income.  When the poverty line is fixed as a proportion of the national mean, if all incomes increase by the same proportion, there would be no change in relative inequalities and the poverty line would simply increase by the same proportion; that is, the poverty measure will not change.  This can make such poverty lines deceptive for some purposes, such as assessing whether poor people are better or worse off.

  A cross‑country comparison of 36 countries, both developed and developing, revealed that real poverty lines will tend to increase with economic growth, but they will do so slowly for the poorest countries.  Therefore, the concept of absolute poverty appears to be more relevant to low income countries, while relative poverty is of more relevance to high-income countries.

(c)      Limitations of the Indicator:  In practice, most applications in developing countries have used consumption per person.  This probably overstates the extent to which poverty is associated with larger family sizes.  But other aspects of the poverty profile (such as assessments of the regional or sectoral poverty profiles) tend to be more robust as a measurement choice.

It is important to note that a certain amount of arbitrariness and value judgement are unavoidable in defining individual welfare and any poverty line.  Therefore, the overall assessment of the poverty situation should pay particularly attention to how the choices made affect poverty comparisons, since these are generally what matter most to policy implications.  An increasingly common practice is to recalculate the poverty measures using various poverty lines, and to test whether the qualitative poverty comparisons are robust to the choice.

It should be noted that there are several comparability problems across countries in the use of data from household surveys (see section 4 below).  In addition, definitions of poverty are lacking in some countries or vary from country to country.  These problems are diminishing over time as survey methodologies are improving and becoming more standardized, but they remain.

(d)        Status of the Methodology:  Not Available.

 (e)      Alternative Definitions/Indicators:  The Poverty Gap Index and the Squared Poverty Gap Index represent alternative definitions for a poverty indicator (see section 2e above).

 4.                Assessment OF DATA

(a)        Data Needed to Compile the Indicator:  The most important source of data on living standards is household surveys.

(b)        National and International Data Availability and Sources:  The results of household surveys can be obtained from government statistical agencies, often via published reports.  About two thirds of the developing countries have done sample household surveys which are representative nationally, and some (but certainly not all) of these provide high‑quality data on living standards.

Data can also be obtained from international agencies such as The World Bank (mostly data for low and middle income countries emerging from the Living Standards Measurement Study and Social Dimensions of Adjustment Project for Sub Saharan Africa).  Data for developed countries can be obtained from the Statistical Office of the European Union (Eurostat), the Luxembourg Income Study, or the Organisation for Economic Co-operation and Development (OECD).

(c)        Data References:  Not Available.

5.         Agencies Involved in the Development of the Indicator

(a)        Lead Agency:  The lead agency is the World Bank (WB). The contact point is the Chief, Indicators and Environmental Valuation Unit, Environment Department, WB; fax no. (202) 477 0968.

(b)       Other Contributing Organizations:  None.

6.        References

(a)       Readings:

Ravallion, M. Poverty Comparisons. Fundamentals in Pure and Applied Economics, Volume 56, Harwood Academic Press, Switzerland. 1994.

Shaohua, C. and Ravallion, M. Global Poverty Measure 1987-98 and Projections for the Future. World Bank, Development Research Group, Washington, D. C. Forthcoming.

(b)       Internet site:  www.worldbank.org/data

GINI INDEX OF INCOME INEQUALITY

Social

Equity

Poverty

 

1.         Indicator

(a)        Name:  Gini Index of Income Inequality.

(b)        Brief Definition:  A summary measure of the extent to which the actual distribution of income, consumption expenditure, or a related variable, differs from a hypothetical distribution in which each person receives an identical share.

(c)        Unit of Measurement:  A dimensionless index scaled to vary from a minimum of zero to a maximum of one; zero representing no inequality and one representing the maximum possible degree of inequality.

(d)        Placement in the CSD Indicator Set:  Social/Equity/Poverty. 

2.         Policy Relevance

(a)        Purpose:  The Gini Index provides a measure of income or resource inequality within a population.  It is the most popular measure of income inequality.

(b)        Relevance to Sustainable/Unsustainable Development (theme/sub-theme): This indicator is particularly relevant to the equity component of sustainable development. Income or resource distribution has direct consequences on the poverty rate of a country or region. Broadly speaking, average material welfare can be defined by the per capita Gross Domestic Product (GDP).  However, statistical averages can mask the diversity that exists within any country.  Therefore, from a sustainable development perspective, it is informative to examine income and wealth distribution throughout a population.  A country can, for example, have a high per capita GDP figure, but its income distribution so skewed that the majority of people are poor. This indicator is useful both to measure changes in income inequality over time and for international comparisons.

(c)        International Conventions and Agreements:  None.

(d)        International Targets/ Recommended Standards:  None.

(e)        Linkages to Other Indicators:  This indicator is linked to several other sustainable development measures, including the Poverty and Gender Equality Indicators as well as Economic Indicators to include GDP per capita among others, and sustainable development strategies.

3.         Methodological Description 

(a)        Underlying Definitions and Concepts:  The concept and definition of this indicator are well understood and readily available.  The Gini Index measures the area between the Lorenz Curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line of perfect equality (see Figure 1 in section 3b below).  The Gini Index is defined as one half of the average value of the absolute differences between all possible pairs of "incomes".

 b)        Measurement Methods:  The Lorenz Curve plots the cumulative percentages of total income received (on the vertical axis) against the cumulative percentage of recipients, starting with the poorest individual or household (see Figure 1).  

Figure 1: The Lorenz Curve and Gini Index of Income

 

There are a number of choices about data, which can influence the precise value of the Gini Index obtained.  For example, a Gini Index for consumption expenditure will typically be lower in value than one for income, even within the same population.  This is because households smooth their consumption over time in response to income changes.  At any one date, there will be some households with unusually low incomes and others with unusually high ones; with some opportunities for saving and/or borrowing.  Thus, household consumption will be less unequal.

It is important how "income" is measured, for example whether it is total household income or per capita household income, or income per equivalent adult. In addition, it matters whether or not the incomes are weighted by household size, since households with lower income per person tend to be larger.  Thus, the income share of the poorest 20% of households will be higher than the income share of the poorest 20% of persons.

The World Bank, for example, prefers to weight by household size and calculate the shares held by persons rather than households for most purposes.  As a general rule, the Bank also considers consumption expenditure to be the more reliable indicator of welfare than income, which can be excessively variable over time, and is also more difficult to measure accurately, particularly in developing countries.  Looking at the sample of 112 countries for which Gini indices of income are reported in the World Bank's 2000 World Development Indicators, this coefficient ranges from a low of 19.5% to a high value of 62.9%.

There are a number of ways of estimating the Gini Index of income, and the choice depends in part on the type of data available.  Distributional data are often available in grouped form, such as the income share of the lowest decile of households, where households are ranked by income per person.  To estimate the Lorenz Curve, and thus the Gini Index, from such data, the World Bank often uses a software package called POVCAL.  Having specified the type of data, the program calculates both the General Quadratic specification for the Lorenz Curve and the Beta specification. It then calculates the Gini Index and various other statistics, including poverty measures for each Lorenz Curve.  The program also advises which is the better specification for the Lorenz Curve for the specific data used. 

(c)       Limitations of the Indicator:  The Gini Index is not a very discriminating indicator.  Two very different distributions‑‑one having more inequality amongst the poor, the other having more amongst the rich‑‑can have exactly the same Gini Index.

Measurement errors in data sets are thought to be greater for incomes compared to consumption expenditure, which will add to measured inequality (see section 3b above).  Differences between countries in the measured Gini index may thus reflect in part differences in the welfare measures used.

While the Gini Index of income (in common with most other measures of inequality) captures information on the pattern of relative levels of wellbeing in the population, it is independent of any considerations of absolute living standards.  So, there is nothing to guarantee that a lower Gini Index of income entails higher social welfare in any agreed sense, since the mean income may have also fallen.  The Gini Index is at best a partial indicator, and other measures will be needed to complete the picture of how levels of economic welfare are evolving in a society.

It should be noted that there are several comparability problems across countries in the use of data from household surveys (see section 4 below).  These problems are diminishing over time as survey methodologies are improving and becoming more standardized, but they remain.

(d)        Status of Methodology:  Not Available.

(e)        Alternative Definitions/Indicators:  There are many other measures of inequality, with various strengths and weaknesses.  These are discussed in Sen (1973) (see section 6a below). 

4.         Assessment OF DATA  

(a)        Data Needed to Compile the Indicator:  See 3(b) above. 

(b)        National and International Data Availability and Sources:  The most important source of data on living standards is household surveys.  The results of these surveys can be obtained from government statistical agencies, often via published reports.  About two thirds of the developing countries have done sample household surveys which are representative nationally, and some (but certainly not all) of these provide high‑quality data on living standards.

Data can also be obtained from international agencies such as The World Bank (mostly data for low and middle-income countries emerging from the Living Standards Measurement Study and Social Dimensions of Adjustment Project for Sub Saharan Africa).  Data for developed countries can be obtained from the Statistical Office of the European Union (Eurostat), the Luxembourg Income Study, or the Organisation for Economic Co-operation and Development (OECD).

(c)       Data References:  Not Available.

5.        Agencies Involved in the Development of the Indicator

(a)       Lead Agency:  The lead agency is the World Bank (WB).  The contact point is the World Development Indicators Team, Development Data Group, the World Bank; fax no. (1 202) 522-1785.

(b)       Other Contributing Organizations:  None.

6.        References

(a)       Readings:

Chen, S., G. Datt, M. Ravallion. POVCAL: A Program for Calculating Poverty Measures from Grouped Data. Poverty and Human Resources Division, Policy Research Department, Washington DC: World Bank. 1992.

Ravallion, M., and S. Chen. What Can New Survey Data Tell Us About Recent Changes in Living Standards in Developing and Transitional Economies?. Working Paper 1. Research Project on Social and Environmental Consequences of Growth‑Oriented Policies, Washington DC: World Bank.

Sen, A.  On Economic Inequality. Oxford: Oxford University Press. 1973.

The World Bank.  2000 World Development Indicators. 2000.

(b)              Internet site:  www.worldbank.org/data

 

 


UNEMPLOYMENT RATE

Social

Equity

Poverty

1.       INDICATOR

 (a)      Name:  Unemployment Rate.

 (b)           Brief Definition:  Unemployment rate is the ratio of unemployed people to the labour force. 

 (c)      Unit of Measurement:  %. 

 (d)      Placement in the CSD Indicator Set:  Social/Equity/Poverty.

 2.       POLICY RELEVANCE

 (a)      Purpose:  The unemployment rate is a measure of the unutilized labour supply of a country.  If employment is viewed as the desired portion of the economically active population (labour force), unemployment can been seen as, for the most part, the undesirable portion (although some short-term unemployment can be both desirable and necessary).  Unemployment rates by specific groups- such as by age, sex, occupation or industry- are also useful statistics in identifying groups of workers and sectors most vulnerable to joblessness. 

 (b)      Relevance to Sustainable/Unsustainable Development (theme/sub-theme):  Unemployment is useful and relevant to measuring sustainable development, especially if uniformly measured over time, and considered with other socioeconomic indicators.  It is one of the main reasons for poverty in rich and medium income countries and among persons with high education in low income countries (no work, no income but compensation from insurance schemes or other welfare state systems whenever they exist).  It should be noted, however, that it is common to find people working full‑time but remaining poor due to the particular social conditions and type of industrial relations prevalent in their country, industry, or occupation.    

 (c)      International Conventions and Agreements:  The measurements of unemployment and the labour force are defined in the International Labour Office (ILO): Resolution concerning statistics of the economically active population, employment, unemployment and underemployment, 13th International Conference of Labour Statisticians, Geneva, 1982.

 (d)      International Targets/Recommended Standards:  There are no international targets regarding the rate of unemployment.

 (e)      Linkages to Other Indicators:  The indicator is one among many that measure utilization or underutilization of the labour market.  Other measurements focus on parts of the unemployment experience: youth unemployment, long-term unemployment, unemployment by educational attainment, time-related underemployment and the inactivity rate.

 3.       METHODOLOGICAL DESCRIPTION

 (a)      Underlying Definitions and Concepts:  The definitions for labour force, employed population, and unemployed population are well established by international agreements (see section 6 below).    

i)  Labour Force:  The current economically active population or labour force has two components: the employed and the unemployed population.  The international standard definition of labour force established by the Thirteen International Conference of Labour Statisticians (International Labour Office (ILO), 1982) is based on the following elements:

 -- The survey population: All usual residents (de jure population) or all persons present in the country at the time of the survey (de facto population).  Some particular groups, such as the armed forces or other populations living in institutions, nomadic people, etc., may be excluded.

 -- An age limit:  In countries where compulsory schooling and legislation on the minimum age for admission to employment have broad coverage and are widely respected, the age specified in these regulations may be used as a basis for determining an appropriate minimum age limit for measuring the economically active population. 

 In other countries, the minimum age limit should be determined empirically on the basis of (i) the extent and intensity of participation in economic activities by young people, and (ii) the feasibility and cost of measuring such participation with acceptable accuracy.  Some countries also determine a maximum age for inclusion in the labour force.

 -- The involvement in economic activities during the survey reference period: The concept of economic activity adopted by the Thirteenth International Conference of Labour Statisticians (1982) is defined in terms of production of goods and services as set forth by the United Nations System of National Accounts, (revised in 1993). 

 --  A short reference period:  For example, one week or a day.

 ii)  Employed population:  According to the 1982 international definition of employment (ILO, 1983) the  employed  comprise all persons above the age specified for measuring the labour force, who were in the following categories:        

 -- Paid employment: (i) at work: persons who, during the reference period, performed some work (at least one hour) for wage or salary, in cash or in kind; (ii) with a job but not at work: persons who, having already worked in their present job, were temporarily not at work during the reference period but had a formal attachment to their job;

 -- Self‑employment:  (i) at work: persons who, during the reference period, performed some work (at least one hour) for profit or family gain, in cash or in kind;    (ii) with an enterprise but not at work: persons with an enterprise, which may be a business enterprise, a farm or a service undertaking, who were temporarily not at work during the reference period for some specific reason. 

 iii) Unemployed population: According to the 1982 international definition of employment (ILO, 1983) the unemployed comprise all persons above the age specified for measuring the labour force, who during the survey reference period were at the same time: (i) not in paid employment or self‑employment, not even for an hour; (ii) available for work; and (iii) seeking work.

(b)      Measurement Methods:  Household or labour force surveys are generally the most comprehensive and comparable sources for unemployment statistics.  Other sources include population censuses, “employment office records” and “official estimates”.  Data based on registration at employment offices tend to understate unemployment, in comparison with household or labour force surveys, because not all persons who are looking for work will register on account of eligibility requirements which may exclude those who have never worked or have not worked in a recent period.  (In some countries, registration data can overstate unemployment, largely because of double-counting and failure to track persons registering, not all of whom, in any case, may be job-seekers).  Official estimates are often based on a combination of sources. Population censuses generally do not probe very deeply into labour force status, resulting in magnitudes of unemployment that differ substantially (either higher or lower) from those obtained from household surveys where more questions are asked.  

(c)      Limitations of the Indicator:  As important as the unemployment rate is, it should not be interpreted as a measure of economic hardship.  Doing so can produce some unfortunate results, giving unemployment a greater degree of significance than it deserves. The unemployment rate, if based on the internationally recommended standards, simply tells us the proportion of the labour force that does not have a job but is available and actively looking for work.  It says nothing about the economic resources of the unemployed worker or the worker’s family.  The scope of unemployment should therefore be limited to its use as a measurement of the utilization of labour, and should not be extended to other spheres of the economy of a country.  Broader measures, including income-related indicators, are needed to evaluate economic hardship. 

Paradoxically, low unemployment rates may well disguise substantial poverty in a country, whereas high unemployment rates can occur in countries with significant economic development and low incidences of poverty.  In countries without a safety net of unemployment insurance and welfare benefits, many individuals simply cannot afford to be unemployed.  Instead they eke out a living in the informal sector.  In countries with well-developed social protection schemes, workers can better afford to take the time to find desirable jobs.

(d)      Status of the Methodology:  Well developed and employed although discrepancies do occur.

In an effort to resolve the international comparability issue for its member-countries and building on work carried out by the United States Bureau of Labour Statistics in the 1960’s, the Organization for Economic Co-operation and Development (OECD) initiated research on and has published “standardized unemployment rates” adjusted to the International Labour Office (ILO) concepts.  The ILO extended the process even further, beginning in 1990.  The ILO-comparable unemployment rates show historical data for 25 of the ILO member States based on the ILO-comparable series (produced in ILO: 1999 Key Indicators of the Labour Market, Geneva, 1999).  This table represents unemployment rates from national labour force surveys that have been reconciled with and adjusted to make the estimates conceptually consistent, with the strictest application of the ILO statistical standards. This implies that participating countries must be able to provide detailed information on the composite elements of their labour forces.  At the same time, the unemployment rates obtained are in conformity with the OECD’s programme of standardized rates, which itself is based on the ILO standards.  This avoids a proliferation of “international” estimates, which might not be the same.  Further, all the data are expressed in terms of annual averages (or a period that is currently found to be the most representative over the year), thereby avoiding the variances that would occur if different reference periods were observed.  These estimates, based on official national data, should provide the best basis currently available for making reasonable international comparisons and assumptions, although they may still contain very minor discrepancies.

(e)      Alternative Definitions/Indicators:  Underemployment rate; discouraged workers rate.

4.       ASSESSMENT OF DATA

(a)      Data Needed to Compile the Indicator:  Labour force (total number of persons) and total number of unemployed persons, derived from the same survey. 

(b)      National and International Data Availability and Sources:  Unemployment rate data are available for a total of 113 countries, all of which are broken down by gender, in the 1999 KILM with the majority of data resulting from household or labour force surveys with the remainder from employment office records, official estimates or population censuses.

(c)      Data References:  The data repositories used are International Labour Office (ILO) Yearbook of Labour Statistics, OECD Labour Force Statistics, and ILO Digest of Caribbean Labour. For seven countries, data were taken from national sources. 

5.       AGENCIES INVOLVED WITH THE DEVELOPMENT OF THE INDICATOR

(a)      Lead Agency:  The lead agency is the International Labour Office (ILO) of the United Nations, located in Geneva.  The contact point is the Focal Point for Environment and Sustainable Development, ILO; fax no.  (41‑22) 798 8685.

(b)           Other Contributing Organizations:  None.

6.       REFERENCES

(a)      Readings:

Yearbook of Labour Statistics, ILO, Geneva; 

Bulletin of Labour Statistics (quarterly) and its Supplement (January/February, April/May, July/August and October/November), ILO, Geneva;

Statistical yearbooks and other publications issued by the national statistical offices.

Surveys of Economically Active Population, Employment, Unemployment and Underemployment ‑An ILO Manual on Concepts and Methods, ILO, Geneva, 1992.

Sources and Methods: Labour Statistics, Volumes 3 and 5, ILO, Geneva, 1991 and 1990, currently updated.

System of National Accounts 1993, Commission of the European Communities, International Monetary Fund, Organisation for Economic Co‑operation and Development, United Nations, World Bank, Brussels/Luxembourg, New York, Paris, Washington, D.C., 1993;

Current international recommendations on labour statistics, ILO, Geneva, 1988. See particularly the Resolution Concerning Statistics of the Economically Active Population, Employment, Unemployment and Underemployment, adopted by the Thirteenth International Conference of Labour Statisticians (October 1982).

(b)               Internet sites:

For 1999 Key Indicators of the Labour Market, Geneva, 1999:

http://www.ilo.org/public/english/employment/strat/polemp/kilm/

For the text of the resolution concerning statistics of the economically active population, employment, unemployment and underemployment see:

http://www.ilo.org/public/english/bureau/stat/res/ecacpop.htm

For the ILO database on labour statistics, see http://laborsta.ilo.org

   

RATIO OF AVERAGE FEMALE WAGE TO MALE WAGE

Social

Equity

Gender Equality

1.         INDICATOR

(a)                Name:  Ratio of average female wage to male wage.

(b)            Brief Definition:  Obtained as the quotient of average wage rates paid to female and male employees at regular intervals for time worked or work done for particular occupations.

(c)                Unit of Measurement:  %.

(d)               Placement in the CSD Indicator Set:  Social/Equity/Gender Equality.

2.         POLICY RELEVANCE

(a)                Purpose:  To assess the remuneration offered women vis-a-vis their male counterpart to ultimately determine the level of women's participation in the economy.

(b)               Relevance to Sustainable/Unsustainable Development (theme/sub-theme):  The lower the ratio of wages offered to women, the less the attraction for women to join the labor force, which in turn deprives the economy of a vital component of development.  This disadvantage could also be attributed to inequalities in educational opportunities for women and the need for policy makers to correct this inequity.  It is generally acknowledged that if women are more educated, they are more likely to contribute to the broader productivity of society while enhancing child and maternal health and welfare.

(c)                International Conventions and Agreements:  None.

(d)               International Targets/Recommended Standards:  Eliminate discriminatory practices in employment (Beijing).

(e)                Linkages to Other Indicators:  The indicator has close linkages with the unemployment rate indicator because both deal with employment as a principal generator of production.  It is also closely linked to indicators pertaining to education and poverty.

3.         METHODOLOGICAL DESCRIPTION

(a)                Underlying Definitions and Concepts: There are two international sources of definitions and concepts: 

(i)      The concept of earnings, as applied in wages statistics, relate to remuneration in cash and in kind paid to employees, usually at regular intervals, for time worked; or work done together with remuneration for time not worked, such as for annual vacation, other paid leave or holidays.  Wage rates, as part of earnings, include basic wages, cost-of-living allowances and other guaranteed and regularly paid allowances, but exclude overtime payments, bonuses and gratuities, family allowances and other social security payments made by employers. Ex gratia payments in kind, supplementary to normal wage rates are also excluded (UN International Labor Office). 

(ii) Wages and salaries, as part of compensation to employees, are payable in cash or in kind and include the values of any social contributions, such as income taxes, payable by the employee even if they are actually withheld by the employer for administrative convenience or other reasons and paid directly to social insurance schemes, tax authorities, etc. on behalf of the employee.  Wages and salaries in cash include payments at regular intervals, supplementary allowances payable regularly, payments to employees away from work for short periods such as holidays, and ad hoc bonuses linked to performance, commissions, gratuities and tips (UN System of National Accounts SNA).

(b)               Measurement Methods: The indicator is measured by taking the average wage rates per day, week or month received by female employees as a ratio of the corresponding average wage rates for males.  It could be classified further according to major divisions of economic activity, for example, agriculture, mining and quarrying, etc., to facilitate measurement of sectoral impact on the development process.  Similarly, breakdowns according to age classes would provide additional information related to sustainable development trends.

(c)                Limitations of the Indicator: A serious limitation is the reliability and comprehensiveness of wage rate data paid to female labor.  Although data is available for many countries, the quality varies significantly among countries. Wage rates determine total remuneration and measure women's contribution to total production.  However, since most of the basic remuneration for women's economic and social activities remain unreported or unrecorded--and even if reported, are grossly undervalued--only imputations are possible in many countries.  The indicator will be greatly influenced by the selection of wage sectors, and type and level of job.  The cost of collecting the data from questionnaires and surveys can be significant. Another limitation is that female wage rates do not tell the whole story.  Wages, particularly for females, may reflect under-employment.  Women, especially in developing countries, may participate in informal activities where they are not classified as wage earners.  The household work is outside of the production boundary in the SNA therefore these activities are not covered by this indicator.

(d)               Status of the Methodology:  The resolution covering the institution of an integrated system of wages statistics, including defined earnings and wage rates, was adopted by the Twelfth International Conference of Labor Statisticians in Geneva in 1973.

(e)                Alternative Definitions/Indicators:  An alternative indicator to the male-female wage would be the percentage contribution of women to GDP which measures activities in the production boundary that incorporate the contribution of women in the economic process as proposed in the 1993 SNA.  Another alternative indicator would be the employment distribution per gender (source: labor statistics) that measures the share of women in employment.  An additional alternative indicator could be the number of elected women in positions in government as % of total elected, which measures gender equality through female participation in the government (Source: national election statistics). 

4.         ASSESSMENT OF DATA  

(a)                Data Needed to Compile the Indicator:  The average wage rates paid to female and male employees provide the basic information to compile this indicator.  

(b)               National and International Data Availability and Sources:  The data are mainly reported by departments or ministries of labor in most countries.  It is obtained either through questionnaires or surveys from the different economic sectors of the economy.  Average earnings are usually derived from payroll data supplied by a sample of establishments together with data on hours of work and on employment.  Occasionally, wage indices are reported in the absence of absolute wage data.  In some other cases, information is compiled on the basis of social insurance statistics. 

(c)                Data References:  Data are published by the ILO in the Yearbook of Labor Statistics. 

5.         AGENCIES INVOLVED IN THE DEVELOPMENT OF THE INDICATOR  

(a)              Lead Agency: The lead agency is the International Labor Office (ILO).  The contact point is the Focal Point for Environment and Sustainable Development; fax no. (41 22) 798 8685.

(b)             Other Contributing Organizations:  None.

6.         REFERENCES         

(a)                Readings: The full text of the resolution listed in section 3e above can be found in Current International Recommendations on Labor Statistics (Geneva 1988). 

Further information can be obtained from other ILO publications: An Integrated System of Wages Statistics: A Manual on Methods (Geneva 1979).

Statistical Sources and Methods; Vol. 2  Employment, Wages and Hours of Work (Establishment Surveys) (Geneva 1987); Vol. 4 Employment, Unemployment, Wages and Hours of Work (Administrative Records and Related Sources) (Geneva 1989).

(b)               Internet site:  International Labor Office:  http://www.ilo.org


NUTRITIONAL STATUS OF CHILDREN

Social

Health

Nutritional Status

1.         INDICATOR

(a)        Name:  Nutritional Status of Children.

(b)        Brief Definition:  Children under age five whose weight-for-age and height-for-age is between either 80% and 120% of the reference value of the country, or within two standard deviations of this value.

(c)        Unit of Measurement:  %.

(d)        Placement in the CSD Indicator Set:  Social/Health/Nutritional Status.

2.         POLICY RELEVANCE

(a)        Purpose:  The purpose of this indicator is to measure long term nutritional imbalance and malnutrition, as well as current under-nutrition.

(b)        Relevance to Sustainable/Unsustainable Development (theme/sub-theme): Health and development are intimately interconnected.  Meeting primary health care needs and the nutritional requirement of children are fundamental to the achievement of sustainable development. Anthropometric measurements to assess growth and development, particularly in young children, are the most widely used indicators of nutritional status in a community.  The percentage of low height-for-age reflects the cumulative effects of under-nutrition and infections since birth, and even before birth.  This measure, therefore, should be interpreted as an indication of poor environmental conditions and/or early malnutrition.  The percentage of low weight-for-age reflects both the cumulative effects of episodes of malnutrition or chronic under-nutrition since birth and current under-nutrition.  Thus, it is a composite indicator which is more difficult to interpret.

(c)        International Conventions and Agreements:  The WHO Global Strategy for Health for All by the Year 2000 and its Ninth General Programme of Work, together with the United Nations World Summit for Children represent international agreements relevant to this indicator.

(d)        International Targets/Recommended Standards:  At least 90% of children within a population should have a weight-for-age that corresponds to the reference values given in section 1b above by the year 2000.  This target has been established by the World Health Organization's (WHO) Global Strategy for Health for All by the Year 2000.

(e)        Linkages to Other Indicators:  This indicator is closely linked with adequate birth weight. It is also associated with such socioeconomic and environmental indicators as squared poverty gap index, access to safe drinking water, infant mortality rate, life expectancy at birth, national health expenditure devoted to local health care, Gross Domestic Product (GDP) per capita, environmental protection expenditures as a percent of GDP, and waste water treatment coverage.

3.         METHODOLOGICAL DESCRIPTION

(a)        Underlying Definitions and Concepts:  A national or international reference population is used to calculate the indicators for weight-for-age and height-for-age.  A WHO Working Group has recommended that the best available data for this has been established by the United States National Center for Health Statistics (see references in section 6 below).  This data may be used for children up to five years of age, since the influence of ethnic or genetic factors on young children is considered insignificant.

Low weight and low height are defined as less than the value corresponding to two standard deviations below the median of the respective frequency distributions for healthy children (see WHO, 1981 in section 6 below).

(b)        Measurement Methods:  The proportion of children under five with acceptable weight-for-age (or height-for-age) can be calculated by using the following formula:

            Numerator:  number of children under five with weight-for-age (or height-for-age) acceptable x 100.

            Denominator:  total number of children under five weighed.

For height, supine length is measured in children under two, and stature height in older children.

(c)        Limitations of the Indicator:  Available data may be outdated, site-specific, and lack a time series perspective.  In some countries, the age of children is difficult to determine.  It is also difficult to measure the height of children under two with accuracy and consistency.

(d)        Status of the Methodology:  Not Available.

(e)        Alternative Definitions/Indicators:  Not Available.

4.         ASSESSMENT OF DATA

(a)        Data Needed to Compile the Indicator:  The data needed to compile this indicator are the number of children under five weighed; and the number of children under five with weight-for-age or height-for-age within the national reference values.

(b)        National and International Data Availability and Sources:  The data are routinely collected by ministries of health at the national and subnational levels for most countries. The primary national sources of data are the ministries of health.

(c)        Data References:  Not Available.

5.         AGENCIES INVOLVED IN THE DEVELOPMENT OF THE INDICATOR

(a)        Lead Agency:  The lead agency is the World Health Organization (WHO).  At WHO, the contact point is the Director, Department of Nutrition for Health and Development; fax no. (41 22) 791 3111.

(b)        Other Contributing Organizations:  None.

 6.         REFERENCES

(a)        Readings:

WHO Working on Infant Growth. An evaluation of infant growth: the use and interpretation of anthropometry in infants. Bulletin of the World Health Organization, 1995, 73(2): 165-174.

An Evaluation of Infant Growth. WHO Working Group on Infant Growth (WHO/NUT/94.8). Geneva, World Health Organization, 1994.

Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee. Geneva, World Health Organization, 1995 (WHO Technical Report Series, No. 854).

The Growth Chart. A Tool for Use in Infant and Child Health Care. Geneva, World Health Organization, 1986.

WHO Global Database on Child Growth and Malnutrition (WHO/NUT/97.4). Geneva, World Health Organization, 1997.

A Guide to Nutritional Assessment. Geneva, World Health Organization, 1988.

(b)             Internet site:  World Health Organization.  http://www.who.org

 

MORTALITY RATE UNDER 5 YEARS OLD

Social

Health

Nutritional Status

1.         INDICATOR

(a)        Name:  Mortality Rate Under 5 Years Old.

(b)        Brief Definition:  Under-5 mortality refers to the probability of dying before age 5, per 1,000 newborns.

(c)        Unit of Measurement:  Per thousand live births.

(d)        Placement in the CSD Indicator Set:  Social/Health/Mortality.  

2.         POLICY RELEVANCE

(a)        Purpose:  This indicator measures the risk of dying in infancy and early childhood.

(b)        Relevance to Sustainable/Unsustainable Development (theme/sub-theme):  The reduction of childhood mortality is one of the most strongly and universally supported development goals.  In high-mortality settings, a large fraction of all deaths occur at ages under 5 years.  Despite considerable progress in reducing child mortality, there remains a large gap between more- and less-developed countries in risks of dying before the age of 5 years:  for instance, during 1995-2000, under-5 mortality stood at 11 per thousand in the more developed regions but at 156 per thousand in the least developed countries (DESA, World Population Prospects:  The 1998 Revision).  The gap between more- and less- developed countries is larger in proportional terms for death rates in early childhood than during the adult ages.  Under-5 mortality levels are influenced by poverty; education, particularly of mothers; the availability, accessibility and quality of health services; health risks in the environment, such as access to safe water and sanitation; and nutrition, among other factors. 

(c)        International Conventions and Agreements:  The 1990 World Summit for Children Programme of Action adopted a target of reducing the 1990 under-5 mortality rates by one third, or to 70 per 1,000 live births, whichever is less, by the year 2000.  The Programme of Action of the International Conference on Population and Development further encouraged countries with intermediate mortality levels to achieve an under-5 mortality rate below 60 deaths per 1,000 births by the year 2005, and all countries to achieve an under-5 mortality rate below 45 per 1,000 live births by 2015.  It is currently one of the indicators included in the Augmented Physical Quality of Life Index, which is among the quantitative criteria for the identification of least developed countries within the United Nations.  Many other international agreements, including Agenda 21, also refer to the general goal of reducing childhood mortality.

(d)        International Targets/Recommended Standards:  In addition to the quantitative goals mentioned in section 2(c) above, the World Health Organization’s Ninth General Programme of Work includes the goal of reducing the under-5 mortality rate by one third or to 70 per 1,000 live births, whichever is less, between the years 1990 and 2000.

(e)        Linkages to Other Indicators:  This indicator is closely related to life expectancy at birth.  It is more generally connected to many other social and economic indicators, including those listed in section 3b above.

3.         METHODOLOGICAL DESCRIPTION

(a)        Underlying Definitions and Concepts:  Standard statistical definitions of the terms “live birth” and “death” are put forth in the United Nations Principles and Recommendations for a Vital Statistics System (para. 46):

LIVE BIRTH is the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of pregnancy, which after such separation breathes or shows any other evidence of life such as beating of the heart, pulsation of the umbilical cord, of definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached; each product of such a birth is considered live-born regardless of gestational age.

DEATH is the permanent disappearance of all evidence of life at any time after live birth has taken place (post-natal cessation of vital functions without capability of resuscitation).

(b)        Measurement Methods:       The under-5 mortality rate is derived from estimates of births and deaths gathered in vital statistical systems, censuses and surveys.  Where data on deaths and births are complete, or adjustments for age misstatement and incompleteness can be made, the under-5 mortality rate can be calculated directly.  The details can be found in demographic or actuarial references that describe construction of life tables, for example, Pressat (1972) or Shryock and Siegel (1980).  When such data are unavailable from registration systems or maternity history data in sample surveys, the under-5 mortality rate can be calculated through indirect or modelling methods based on special questions asked in censuses or demographic surveys.  For information on these estimates see the Manual X and MORTPAK-LITE references listed in section 6 below.

(c)        Limitations of the Indicator:  There are often problems in collecting the information required for calculating the under-5 mortality rate in less developed countries where routine data collection in the health services may omit many infant and child deaths.  Some countries do not follow the standard definition, given above, of “live birth”.  However, adjustments can sometimes be made for incomplete registration and age misstatement, and in many developing countries maternity-history data gathered in nationally representative sample surveys provide a sound basis for estimating levels and trends of under-5 mortality.  Sample surveys have been more successful at obtaining estimates of under-5 mortality than of adult mortality, and because of this, information about mortality of young children is currently substantially more complete and more timely than is information about the mortality of adults.

If the necessary data are available, the rate can be calculated separately for boys and girls, and for geographic and social subgroups (based on parents’ characteristics).  It is also useful to disaggregate the under-5 period into separate rates for under age one (infant mortality rate) and for ages 1-4 years.

(d)        Status of the Methodology:  Well developed and widely employed.

(e)        Alternative Definitions/Indicators:  The infant mortality rate is another indicator of early child mortality for which quantitative goals have been set forth at recent international conferences.  The infant mortality rate is the number of deaths under 1 year of age during a period of time per 1000 live-births during the same period.

4.         ASSESSMENT OF DATA

(a)        Data Needed to Compile the Indicator:  The under-5 mortality rate is derived from data on births and deaths occurring under the age of 5 years, as described in section 3(b) above. 

(b)        National and International Data Availability and Sources:  Data are now available for most countries thanks to special surveys of representative samples of the population whenever vital registration systems are not available.  Surveys that rely on maternity histories, in which women are asked to give the date of birth and age of death (if applicable) of each live-born child, are used in many household surveys, but care must be taken to avoid age misreporting and to ensure that there is a complete report of deaths.  Retrospective questions about the survival of all children born included in censuses and surveys, and analyses using indirect estimation procedures, are also considered to be reliable sources.

(c)        Data References:  Original data sources include vital registration, sample registration systems, surveillance systems, censuses, and demographic surveys.  Information needed for this indicator is collected by the United Nations on a regular basis.  For all countries, survey and registration data are evaluated and, if necessary, adjusted for incompleteness by the Population Division, Department of Economic and Social Affairs (DESA) as part of its preparations of the official United Nations population estimates and projections.  Past, current and projected estimates of infant mortality are prepared for all countries by the Population Division; DESA and appear in the United Nations publication, World Population Prospects:  The 1998 Revision.  Demographic monitoring done by government statistical offices often allows desegregation of information to show differences within countries.  Surveys are generally designed to provide estimates for major regions within countries as well as at the national level.

5.         AGENCIES INVOLVED IN THE DEVELOPMENT OF THE INDICATOR

(a)        Lead Agency:  The lead agency is the United Nations Department of Economic and Social Affairs.  The contact point is the Director, Population Division, fax no. (1 212) 963 2147. 

(b)        Other Contributing Organizations:  The United Nations Statistics Division/ DESA; and the United Nations Children’s Fund (UNICEF); and the World Health Organization (WHO).

6.         REFERENCES

(a)        Readings:

Pressat, R.  Demographic Analysis: Methods, Results, Applications.  London, Edward Arnold; Chicago, Aldine Atherton.  1972.

Shryock, H.S, and J.S.Siegel.  The Methods and Materials of Demography.  U.S. Government Printing Office,  Washington, D.C.  1980.

WHO. Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.  Geneva,  1981, p. 69.

WHO. Global Health for All Data Base.  Geneva, 1994.

WHO. Global Strategy for Health for All by the Year 2000.  Geneva,  1981.

DESA. Manual X:  Indirect Techniques for Demographic Estimation. Population Division.  United Nations Sales No. E. 83.XIII.2, New York, 1983.

DESA. MORTPAK-LITE - The United Nations Software Package for Mortality Measurement. Population Division.  United Nations, New York, 1988.

DESA. World Population Prospects: The 1994 Revision. Population Division.  United Nations Sales No. E.95.XIII.16, New York, 1995.

Hill K. Approaches to the measurement of childhood mortality:  A comparative review.  Population Index 57(3):368-382, Fall, 1991.

United Nations. Report of the International Conference on Population and Development, Programme of Action of the International Conference on Population and Development, Cairo, Egypt, September 5-13, 1994.  United Nations Document A/CONF. 171/13.

United Nations.  Principles and Recommendations for a Vital Statistics System.  United Nations publication, Sales No. E.73.XVII.9.

UNICEF.  The State of the World’s Children.  2000.

WHO and UNICEF. Measurement of overall and cause-specific mortality in infants and children.  Report of a Joint WHO/UNICEF Consultation, 15-17 December 1992. Unpublished document WHO/ESM/UNICEF/CONS/92.5.

DESA. Demographic Yearbook 1997. Statistics Division. United Nations Sales No. E/F.99.XIII.1, 1999.

(b)        Internet sites:

Statistics are available at:

http://www.undp.org/popin/wdtrends/wdtrends.htm

http://www.un.org/Depts/unsd/social/health.htm

 

LIFE EXPECTANCY AT BIRTH

Social

Health

Nutritional Status

1.         INDICATOR

(a)        Name:  Life Expectancy at Birth.

(b)        Brief Definition:  The average number of years that a newborn could expect to live, if he or she were to pass through life subject to the age-specific death rates of a given period.

(c)        Unit of Measurement:  Years of life.

(d)        Placement in the CSD Indicator Set:  Social/Health/Mortality.

2.         POLICY RELEVANCE

(a)        Purpose:  Measures how many years on average a new-born baby is expected to live, given current age-specific mortality risks.  Life expectancy at birth is an indicator of mortality conditions and, by proxy, of health conditions.

(b)        Relevance to Sustainable/Unsustainable Development (theme/sub-theme):  Mortality, with fertility and migration, determines the size of human populations, their composition by age, sex, and ethnicity, and their potential for future growth.  Life expectancy, a basic indicator, is closely connected with health conditions, which are in turn an integral part of development.  The International Conference on Population and Development (ICPD) Programme of Action notes that the unprecedented increase in human longevity reflects gains in public health and in access to primary health-care services (paragraphs 8.1 and 8.2), which Agenda 21 recognizes as an integral part of sustainable development and primary environmental care (paragraph 6.1).  The ICPD Programme of Action highlights the need to reduce disparities in mortality and morbidity among countries and between socio-economic and ethnic groups.  It identifies the health effects of environmental degradation and exposure to hazardous substances in the work-place as issues of increasing concern.  Life expectancy is included as a basic indicator of health and social development in, among others, the Minimum National Social Data Set endorsed by the United Nations Statistical Commission at its 29th session in 1997, the UNDG-CCA indicator set and the OECD/DAC core indicators. 

(c)        International Conventions and Agreements:  The Declaration of Alma Ata (1978) set a target of life expectancy greater than 60 years by the year 2000; the World Summit for Social Development (WSSD) also included this goal.  The ICPD Programme of Action specified that: life expectancy should be greater than 65 years by 2005 and 70 years by 2015 for countries that currently have the highest levels of mortality; and 70 years and 75 years, respectively, for the other countries (ICPD Programme of Action, paragraph 8.5).

(d)        International Targets/Recommended Standards:  See above.

(e)        Linkages to Other Indicators:  This indicator reflects many social, economic, and environmental influences.  It is closely related to other demographic variables, and it is related to human health and the environment as well as economic indicators.

3.         METHODOLOGICAL DESCRIPTION

(a)        Underlying Definitions and Concepts:  Calculation of life expectancy at birth is based on age-specific death rates for a particular calendar period. The death rates are commonly tabulated for ages 0 to1 years, 1 to 5 years, and for 5-year age groups for ages 5 and above.

(b)        Measurement Methods:  Several steps are needed to derive life expectancy from age-specific death rates; the details can be found in demographic or actuarial references that describe construction of life tables, for example, Pressat (1972) or Shryock and Siegel (1980).  For a description of the methodology that is linked to computer routines to aid in the calculation, see MORTPAK-LITE (section 6, below).

(c)        Limitations of the Indicator:  Where data on deaths by age are of good quality, or adjustments for age misstatement and incompleteness can be made, the life expectancy at birth can be calculated directly from registered deaths and population counts, which are usually based on census enumerations, evaluated and, if necessary, adjusted.  When data on deaths by age are unavailable from registration systems or sample surveys, the life expectancy at birth can be calculated through "indirect" methods based on special questions asked in censuses or demographic surveys.  For information on these indirect estimates, see Manual X and MORTPAK-LITE (section 6, below).

(d)              Status of the Methodology:  Not available.

(e)        Alternative Definitions/ Indicators:  Another indicator of general mortality in common use is the Crude Death Rate (CDR), which is the number of deaths in a period (commonly a one-year period) divided by the mid-period population; it is usually expressed in units of deaths per 1,000 population.  The CDR requires less detailed data for its calculation than does life expectancy at birth, but it has the drawback of being influenced to a substantial degree by population age structure:  two populations with the same CDR could have markedly different mortality risks, age by age.

Life expectancy may be calculated separately for males and females, or for both sexes combined.  If the underlying data permit, life expectancy may also be calculated for subnational regions, or for other population subgroups.  Life expectancy can also be presented for particular ages after birth.  For instance, life expectancy at age 60 represents the number of additional years an individual who has just reached age 60 can expect to live, given current age-specific mortality rates for older ages.

4.         ASSESSMENT OF DATA

(a)        Data Needed to Compile the Indicator:  Some data sources yield estimates of age-specific mortality for only some age groups, so that it may be necessary to employ separate adjustments to data from different sources in order to arrive at a complete and consistent set of rates for a given period of time.  Most countries tabulate data from death registration systems at the sub-national level. The under-5 mortality rate and the crude death rate are more readily available for sub-national units than is life expectancy at birth.

(b)        National and International Data Availability and Sources:  Data are collected by the United Nations on a regular basis and are available for most countries from vital registration systems or surveys. For all countries, census and registration data are evaluated and, if necessary, adjusted for incompleteness by the Population Division, United Nations Department of Economic and Social Affairs (DESA) as part of its preparations of the official United Nations population estimates and projections. 

(c)        Data References:  Past, current and projected estimates of life expectancy at birth are prepared for all countries by the Population Division, DESA and appear in the United Nations publication, World Population Prospects: The 1998 Revision (see section 6, below).

5.         AGENCIES INVOLVED IN THE DEVELOPMENT OF THE INDICATOR

(a)        Lead Agency:  The lead agency is the United Nations Department of Economic and Social Affairs (UN/DESA).  The contact point is the Director, Population Division, fax no. (1 212) 963 2147. 

(b)        Other Contributing Organizations:  The United Nations Statistics Division/DESA; and the United Nations Children’s Fund (UNICEF); and the World Health Organization (WHO).

6.         REFERENCES

(a)        Readings:

DESA. World Population Prospects: The 1998 Revision. Vol. I Comprehensive Tables Population Division. United Nations Sales No. E.99.XIII.9, New York, 1999.

DESA. World Population Prospects: The 1998 Revision. Vol. III Analytical Report.  Population Division. United Nations, ESA/P/WP.156, New York, 1999.

DESA. Manual X: Indirect Techniques for Demographic Estimation. Population Division United Nations Sales No. E.83.XIII.2, New York, 1983.

DESA. MORTPAK-LITE: The United Nations Software Package for Mortality Measurement.  Population Division.  United Nations,  New York, 1988.

DESA. Demographic Yearbook. Statistical Division. United Nations Sales No.E/F.95.XIII.1,1995.  1993.

Pressat, R.  Demographic Analysis: Methods, Results, Applications.  London, Edward Arnold; Chicago, Aldine Atherton.  1972.

United Nations.  Report of the International Conference on Population and Development. Programme of Action of the International Conference on Population and Development.  United Nations Document A/CONF. 171/13.  Cairo, Egypt, September 5-13, 1994. 

Shryock, H.S, and J.S.Siegel.  The Methods and Materials of Demography.  U.S. Government Printing Office,  Washington, D.C.  1980.

(b)        Internet sites:

Statistics are available at:

http://www.undp.org/popin/wdtrends/wdtrends.htm

http://www.un.org/Depts/unsd/social/health.htm

 

PRIVATE PERCENT OF POPULATION WITH ADEQUATE SEWAGE DISPOSAL FACILITIES

Social

Health

Sanitation

1.         INDICATOR

(a)        Name:  Percent of Population with Adequate Sewage Disposal Facilities.

(b)        Brief Definition:  Proportion of population with access to a sanitary facility for human excreta disposal in the dwelling or immediate vicinity.

(c)        Unit of Measurement:  %.

(d)        Placement in the CSD Indicator Set:  Social/Health/Sanitation.

2.         POLICY RELEVANCE

(a)        Purpose:  To monitor progress in the accessibility of the population to sanitation facilities.

(b)        Relevance to Sustainable/Unsustainable Development (theme/sub-theme):  This represents a basic indicator useful for assessing sustainable development, especially human health.  Accessibility to adequate excreta disposal facilities is fundamental to decrease the faecal risk and the frequency of associated diseases.  Its association with other socioeconomic characteristics (education, income) and its contribution to general hygiene and quality of life also make it a good universal indicator of human development.  When broken down by geographic (such as rural/urban zones) or social or economic criteria, it also provides tangible evidence of inequities.

(c)        International Conventions and Agreements:  Agenda 21 UNCED (1992) indicates the need for universal coverage and the Second World Water Forum and Ministerial Conference, The Hague, March 2000 established the target of universal coverage by the year 2025.

(d)        International Targets/Recommended Standards:  International targets for this indicator have been established under the auspices of the World Health Organization (WHO).  The Vision 21 of the Water Supply and Sanitation Collaborative Council provides targets of 100% coverage by the year 2025.

(e)        Linkages to Other Indicators:  The indicator is closely associated with other socioeconomic indicators (see section 2(b) above), particularly the proportion of population with access to improved water sources.  The indicator represents two of the eight elements of primary health care.

3.         METHODOLOGICAL DESCRIPTION

(a)        Underlying Definitions and Concepts:  Definitions for sanitary facility and population covered are required.

i)   Sanitary facility:  "A sanitary facility is a unit for disposal of human excreta which isolates faeces from contact with people, animals, crops and water sources.  Suitable facilities range from simple but protected pit latrines to flush toilets with sewerage.  All facilities, to be effective, must be correctly constructed and properly maintained".

ii) Population covered:  This includes the urban and rural population served by connections to public sewers; (pit privies, pour-flush latrines, septic tank, etc.)

(b)        Measurement Methods:  This indicator may be calculated as follows:  The numerator is the number of people with improved excreta-disposal facilities available multiplied by 100.  The denominator is the total population.

(c)        Limitations of the Indicator:  The availability of facilities does not always translate into their utilization.

(d)        Status of the Methodology:  Not Available.

(e)        Alternative Definitions/Indicators:  This indicator could also be expressed as the percent of people without access to improved excreta disposal facilities.  The population that must be used in the numerator is the number of people without access to improved excreta disposal facilities.  If the data available are in terms of proportion of households for which sanitation is available, it should be possible to convert this into a percentage of population, using average figures for household size.  Also see section 3(c) above.

4.         ASSESSMENT OF DATA

(a)        Data Needed to Compile the Indicator:  The number of people with access to improved  excreta disposal facilities, and the total population.

(b)        National and International Data Availability and Sources:  Routinely collected at the national and sub‑national levels in most countries using censuses and surveys. In order to arrive at more robust estimates of sanitation coverage, two main data source types are required.  First, administrative or infrastructure data which report on new and existing facilities.  Second, population-based data derived from some form of national household survey.

(c)        Data References:  Not Available.

5.         AGENCIES INVOLVED IN THE DEVELOPMENT OF THE INDICATOR

(a)        Lead Agency:  The lead agency is the World Health Organization (WHO).  The contact point is the Coordinator, Water, Sanitation and Health, WHO; fax no. (41 22) 791 4159.

(b)        Other Contributing Organizations:  None.

6.         REFERENCES

(a)        Readings:

WHO, Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.  Geneva, WHO, 1981, p. 29.

WHO, Global Strategy for Health for All by the Year 2000.  Geneva, WHO, 1981.

WHO, Ninth General Programme of Work Covering the Period 1996-2001.  Geneva, WHO, 1994.

World Health Organization, Division of Operational Support in Environmental Health, October 1995.

World Health Organization. National and Global Monitoring of Water Supply and Sanitation.  CWS Series of Cooperative Action for the Decade, No. 2, 1982.

World Health Organization.  Water Supply and Sanitation Sector Monitoring Report (WSSSMR), 1990.

(b)               Internet site: World Health Organization.  http://www.who.org

 

POPULATION WITH ACCESS TO SAFE DRINKING WATER

Social

Health

Drinking Water

1.         INDICATOR

(a)        Name:  Population with Access to Safe Drinking Water.

(b)        Brief Definition:  Proportion of population with access to an improved water source in a dwelling or located within a convenient distance from the user's dwelling.

(c)        Unit of Measurement:  %.

(d)        Placement in the CSD Indicator Set:  Social/Health/Drinking Water.

2.         POLICY RELEVANCE

(a)        Purpose:  To monitor progress in the accessibility of the population to improved water sources.

(b)        Relevance to Sustainable/Unsustainable Development (theme/sub-theme):  Accessibility to improved water sources is of fundamental significance to lowering the faecal risk and frequency of associated diseases.  Its association with other socioeconomic characteristics, including education and income, which also makes it a good universal indicator of human development.  When broken down by geographic (such as rural/urban zones), or social or economic criteria, it provides useful information on equity issues.

(c)        International Conventions and Agreements:  Agenda 21 of UNCED (1992) indicates the need for universal coverage and the Second World Water Forum and Ministerial Conference, The Hague, March 2000 established the target of universal coverage by the year 2025.

(d)        International Targets/Recommended Standards:  International targets for this indicator have been established under the auspices of the World Health Organization (WHO).  The Vision 21 of the Water Supply and Sanitation Collaborative Council provides targets of 100% coverage by the year 2025.

(e)        Linkages to Other Indicators:  This indicator is closely associated with other socioeconomic indicators on the proportion of people covered by adequate sanitation.  These indicators are among the eight elements of primary health care.  It also has close links to other water indicators such as withdrawals, reserves, consumption, or quality.  (See section 2(b) above.)

3.         METHODOLOGICAL DESCRIPTION

(a)        Underlying Definitions and Concepts:  This indicator requires definitions for several elements.

i)   Population covered:  This includes urban and rural population served by house connections, or without house connections but with reasonable access to other sources.

ii)  Reasonable access to water:  In urban areas, a distance of not more than 200 metres from a house to a public stand post or any other adequate point source may be considered reasonable access.  In rural areas, reasonable access implies that people do not have to spend a disproportionate part of the day fetching water for the family's needs.

iii) Minimum amount of water:  The amount of water needed to satisfy metabolic, hygienic, and domestic requirements. This is usually defined as twenty litres of safe water per person per day.

iv) Safe water:  The water does not contain biological or chemical agents at concentration levels directly detrimental to health. It is likely that treated surface waters, and water such as that from protected boreholes, springs, and sanitary wells are safe. Untreated surface waters, such as streams and lakes, should be considered safe only if the water quality is regularly monitored and considered acceptable by public health officials.

(b)        Measurement Methods:  This indicator may be calculated as follows:  The numerator is the number of persons with access to an adequate amount of safe drinking water in a dwelling or located within a convenient distance from the user's dwelling multiplied by 100.  The denominator is the total population.

(c)        Limitations of the Indicator:  The existence of a water outlet within reasonable distance is often used as a proxy for availability of safe water.  The existence of a water outlet, however, is no guarantee in itself that water will always be available or safe, or that people always use such sources.

(d)        Status of the Methodology:  Not Available.

(e)        Alternative Definitions/Indicators:  This indicator may be also expressed as the percent of population without access to improved water sources. Thus the population indicated in the numerator would be those who do not have access to improved water sources.  If these data are available in terms of the proportion of households, it should be possible to convert this into a percentage of the population, using average figures for household size.

4.         ASSESSMENT OF DATA

(a)        Data Needed to Compile the Indicator:  The number of people with access to improved water sources, and the total population.  Data on the source of water, for example, house tap or yard pipe, would provide additional meaning to this indicator.

(b)        National and International Data Availability and Sources:  Routinely collected at the national and sub‑national levels in most countries using censuses and surveys. Two data sources are common: administrative data that report on new and existing facilities, and population data derived from some form of household survey or census.

(c)        Data References:  Not Available.

5.         AGENCIES INVOLVED IN THE DEVELOPMENT OF THE INDICATOR

(a)        Lead Agency:  The lead agency is the World Health Organization (WHO).  The contact point is the Coordinator, Water, Sanitation and Health, WHO; fax no. (41 22) 791 4159.

(b)        Other Contributing Organizations:  None.

6.         REFERENCES

(a)        Readings:

WHO, Global Strategy for Health for All by the Year 2000.  Geneva, WHO, 1981.

WHO, Ninth General Programme of Work Covering the Period 1996-2001.  Geneva, WHO, 1994.

WHO,  Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.  Geneva, WHO, 1981, p. 40.

World Health Organization.  National and Global Monitoring of Water Supply and Sanitation.  CWS Series of Cooperative Action for the Decade, No. 2, 1982.

World Health Organization.  Water Supply and Sanitation Sector Monitoring Report (WSSSMR), 1990.

Program of Action of the Ministerial Drinking Water Conference, 1994.

(b)               Internet site:  World Health Organization.  http://www.who.org