The Alkire Foster (AF) method developed by Sabina Alkire and James Foster at the Oxford Poverty and Human Development Initiative (OPHI) is a flexible poverty or welfare calculation technique. These calculations can combine different dimensions and indicators to make the calculations adaptable to more specific contexts. This means that this method can be used in different ways.
- Poverty and Welfare Measurement. The Alkire Foster method can be used to measure poverty or welfare at the national, regional or international level by combining dimensions and indicators according to the relevant context. For example, Alkire Foster's method was used to construct a global multidimensional poverty index in collaboration with the United Nations Development Program's and is considered a flagship report on human development. This method has also been adapted by several countries in four or five regions of the world to create national poverty measures.
- Monitoring and evaluating. The Alkire Foster method can be used to carry out effective monitoring of the programs being carried out. For example, Alkire Foster's method supports the Women in Agriculture Empowerment Index, which measures women's empowerment, agency, and inclusion in the agricultural sector. This index is used to help evaluate the performance of United States agricultural assistance programs.
- Targeting the poor as service beneficiaries or conditional cash assistance recipients. The Alkire Foster method can also be used to determine individual criteria for recipients of public service programs or conditional cash transfers (BTB).
Advantages of using the Alkire Foster method for policy makers?
This method can be used by NGOs, governments, institutions, and the private sector to make measurements that have uses, among others:
- Effectiveness of allocation of funding sources. This method can help policy makers identify the poorest communities and the most deprived indicators. This information can be used to invest resources that work to reduce poverty.
- Policy design. Stakeholders can identify the deprivations that are the most common causes of poverty among the poor, so that policies can be designed to address specific needs and reduce poverty more effectively.
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Identify the relationship between deprived indicators. This method is used to integrate many different aspects of poverty into a single measure, which reflects the interconnections between deprivations and helps identify the factors that lead to people being trapped in poverty.
- Shows changes over time. The Alkire Foster method can more quickly reflect the impact of policy changes than using income measurements alone. For example, if there is a new program that aims to improve education in an area, it will take a long time for the impact of education to be seen when using income measurements. In contrast, multidimensional poverty measures that include school attendance and achievement in education can reveal the outcomes of policies aimed at improving education and measure the contribution of education to multidimensional poverty as a whole.
- Different dimensions, indicators and cut offs can be used to make measurements according to usage, situation and context. The selection of these indicators and dimensions can be done using a participatory process.
- Completing the poverty matrix. The multidimensional poverty index can help complement information from other poverty calculation matrices such as: poverty measurement based on income and consumption.
Global Multidimensional Poverty Index
IKM has been used by more than 50 countries that are members of the Forum Multidimensional Poverty Peer Network (MPPN). The following are several countries in the world that have used multidimensional poverty calculations with various multidimensional poverty measurement indicators adapted to national conditions and situations:
| Dimensions and Indicators | kolombia | India | south Africa | Thailand |
| Education | school achievement | Old school | Old school | Old school |
| Literacy | school participation | school participation | being late for school | |
| school participation | ||||
| being late for school | ||||
| Childcare access | ||||
| child labour | ||||
| standard of living | Access to water sources | Cooking fuel | Lighting fuel | Disposal of household waste |
| Waste disposal | Sanitation | Space heating fuel | Internet access | |
| House floor | Drinking water | Cooking fuel | Asset ownership | |
| House wall | Electricity | Water access | ||
| house density | House materials | Sanitation | ||
| Aset | occupancy type | |||
| bank account | Asset ownership | |||
| Health | Health Insurance | Nutrition | Child death | Drinking water |
| Health access | Mortality of children and adolescents | Self care | ||
| Care after delivery | Production of food nutrients | |||
| Work | Long time unemployed | Unemployment | ||
| formal job | ||||
| Financial access | Savings | |||
| Financial burden | ||||
| Pension security ownership |
In compiling global SMIs, OPHI uses three dimensions of measurement namely health, education, and standard of living with 10 indicators. This standardized global IKM is intended to compare multidimensional poverty across countries by adjusting the SDGs and data availability. Whereas in this study, the National IKM was compiled through several adjustments to dimensions and indicators that still refer to the standard OPHI methodology.
Dimensions of IKM 2012-2014
The calculation of IKM in Indonesia uses three dimensions, namely the dimensions of health, education, and quality of life standards, and there are a total of 11 indicators. In accordance with the Alkire-Foster method which frees the use of indicators, we adjust data availability with indicators that can be representative in Indonesia.
Dimensions of IKM 2015-2018
The 2015–2018 Indonesia IKM calculation uses the same methodology as the 2012–2014 Indonesia IKM calculation, but there are slight changes to the composition of the indicators in each dimension in order to adjust to the latest development trends and better reflect the actual conditions of poverty. Unlike the 2012–2014 Indonesian IKM which has 11 indicators, the 2015–2018 Indonesian IKM consists of 8 indicators.
Dimensions of IKM 2019-2021
Indonesia's national IKM is adjusted into five dimensions, namely the dimensions of health, education, housing, basic needs, and social protection & participation. The determination of the dimensions in this study was carried out based on considerations for global SMEs, data availability, and study relevance. The preparation of IKM also considers input from experts and key stakeholders. This is done to adapt to the context of poverty in Indonesia.
The 2012-2014 IKM calculation uses 11 indicators which are adjusted to the availability of data and needs in Indonesia. As mentioned in the Alkire-Foster method, the selection of indicators is adjusted to the needs and urgency of each country. Some of the indicators in the first calculation include: sanitation, clean water, access to maternal health services, nutritional intake for children under five, access to education services, literacy, access to preschool education services, sources of lighting, fuel/energy for cooking, floor conditions roofs and walls, and ownership of assets.
Multidimensional Poverty Indicators 2015-2018
The PRAKARSA in the second calculation period eliminates one indicator each in each dimension. In the 2015–2018 Indonesian IKM, we removed the indicator for birth attendants in the health dimension, the literacy indicator in the education dimension, and the asset ownership indicator in the quality of life standard dimension.
The omission of the indicator for birth attendants is because now Indonesia has implemented national health insurance and people are starting to become aware of checking the conditions of pregnancy and delivery at health facilities with the assistance of health workers.
In addition, with the implementation of the national health insurance, all delivery costs have been borne and the poor are assisted by the government in paying their premiums. The literacy indicator was omitted because in 2015 Indonesia's literacy rate had reached above 95 percent so that it was no longer relevant to represent the condition of poverty.
The omission of the housing asset ownership indicator is due to the fact that in recent years most of the young adult age group considers ownership of home asset status to not reflect the level of welfare. Therefore, distinguishing between the poor and non-poor is increasingly biased when measured in terms of housing asset ownership.
In addition to removing these 3 indicators, in the 2015-2018 Indonesian IKM we revised the measurements on the light source indicator. In the 2012-2014 Indonesian IKM, the light source indicator refers to poor people as people who do not use the State Electricity Company (PLN) and people who use PLN but are subsidized with a value of 450 and 900 watts. However, because since 2015 the questions related to sources of lighting in Susenas have changed, the measurement of indicators for sources of lighting in the 2015-2018 Indonesian IKM has also changed.
Multidimensional Poverty Indicators 2019-2021
The calculation of the 2019-2021 IKM eliminates several indicators that have been used in calculating the 2015-2018 IKM. This change is based on socio-economic changes in Indonesia which affect the relevance of using an indicator. For example, indicators for early childhood education in the 2015-2018 IKM were not reused because the calculation results for the 2015-2018 IKM showed a continuous downward trend and the research team decided to explore the issue of enrollment and length of schooling more deeply. In the 2019-2021 IKM there are 11 indicators, namely: under-five nutrition, morbidity, school participation, length of schooling, quality of roof floors and walls, density in housing, proper drinking water, cooking fuel, sanitation, birth certificates, and the internet.
In summary, calculating multidimensional poverty using the Alkire Foster method is carried out in 12 main steps. Complete training on calculating multidimensional poverty can be seen on the following training portal. Following are the six calculation steps according to the Alkire Foster method:
- Stage 1: Selecting the Unit of Analysis
The selected analysis can be in various units, such as individual, household, province, district/city, gender, and village-urban.
- Stage 2: Selecting Dimensions
The choice of dimensions is very important to see what dimensions you want to see. The OPHI standard uses three dimensions, namely the dimensions of health, education, and quality of life standards. Meanwhile, Indonesia's IKM uses three dimensions in the first period (2012-2014) and second period (2015-2018) calculations. Meanwhile, for the calculation of the third period, we break down the 3 dimensions of the OPHI standard into 5 dimensions, namely: health, education, housing, basic service standards, and social protection & participation. The determination of the 2019-2021 IKM dimensions also takes into account input from experts and key stakeholders. This is done to adapt to the context of poverty in Indonesia.
- Stage 3: Selecting Indicators
Indicators will be selected from each dimension by principle accuracy (to make data more accurate, you can use various kinds of indicators needed so that you have various kinds of analysis to make policy making better) and parsimony (using as few indicators as possible to facilitate policy analysis and transparency). In order to determine a good indicator, statistical rules must be observed, namely if the determination of indicators does not have a high correlation between indicators. which indicator PRAKARSA Select has gone through several consultation stages, including with a number of experts who are familiar with the problem of poverty in Indonesia.
- Stage 4: Weighting Dimensions and Indicators
Each dimension and indicator will be given a certain weight. The weighting method is used to average each dimension and indicator. There are five dimensions in the calculation of the 2019-2021 IKM. The five dimensions are weighted equally at 0,2 or 20%, respectively. Then, the five dimensions are given a second screening in determining the weight of the indicators. Indicator weights are divided proportionally according to the number of indicators in one dimension.
- Stage 5: Determining the Poverty Line
Need to set poverty cut-off for each dimension. The first step is to create cut-off for the methodology in which one can say deprive or non-deprived from every dimension. For example: someone is said to be poor based on educational indicators if that person has dropped out of school or has never attended school even though they are in the school age range. Beyond that, one cannot be said to be poor.
- Stage 6: Poverty Line Application
This step replaces a person's attainment with the status experienced at each cut-off or threshold of the existing multidimensional poverty line. For example, the limit of the poverty line for SMEs is 0,333. If a person experiences deprivation on several poverty indicators with a total value of more than 0,333, then he is classified as multidimensionally poor, while if it is below 0,333, then that person cannot be said to be multidimensionally poor. So, if someone does not go to school (experiencing poverty from the educational dimension), but is still below the multidimensional poverty line, then he is not categorized as poor.
- Step 7: Calculating Deprivation Based on Number of Persons
After obtaining the poverty line boundary, the next step is to calculate the amount of poverty. The Alkire-Foster method makes a requirement that people who cross the 0,333 threshold are considered to be affected by multidimensional poverty, however cut-off This can be adjusted depending on the needs of each region.
- Stage 8: Determine Cut-off second
The assumption of this determination is to set the appropriate weight. This will give a number from each dimension in the indicator he is experiencing poverty. Someone who is said to experience multidimensional poverty, if he is affected in several relevant dimensions, according to the weight value of each indicator.
- Stage 9: Applying Cut-off
The focus is to provide a profile of the poor and the dimensions given when they are deprived. All information stating that he is not poor will be all zeroed out, so that it is not included in the calculation for his deprivation. IKM is calculated using the weight of each dimension and indicator. The five dimensions used in calculating multidimensional poverty are weighted equally, namely 1/5 or 20% of each dimension. Then, the five dimensions are given a second screening in determining the weight of the indicators. Indicator weights are divided proportionally according to the number of indicators in one dimension.
For example, in calculating the 2019-2021 IKM, the following indicator weights will be obtained: the indicator weights on the dimensions of health, health, housing, and protection & participation each get a weight of 1/10 because each of these dimensions consists of 2 indicators. As for the basic needs dimension, the weight of each indicator is 1/15 because there are three indicators in this dimension.
Everyone who is assessed in the IKM is seen based on the indicators being assessed. The score consists of a range of 0-1. When a person fulfills the poverty assessment according to the IKM indicator, he is given point 1. Assessment will continue to be carried out for each indicator. The following is the formula for calculating cut-off for each multidimensional poverty indicator:
a. Toddler Nutrition Indicators
Information:
RTMI: Household Multidimensional Poverty Index
(sigma symbol) RT: Number of households
The cut-off for the calculation of the under-five nutrition indicator is that households that fall into the poor category on the under-five nutrition indicator are individuals aged between 0-4 years (0
b. Morbidity Indicator
Information:
(sigma symbol) RT: Number of households
The cut-off for calculating morbidity indicators is for individuals who fall into the category of those affected by the IKM indicators for morbidity as follows: (1) if the individual has health complaints (for example: fever, cough, runny nose, diarrhea, dizziness, chronic illness, etc.) (2) due to health complaints resulting in disruption of work, school or daily activities.
c. School participation indicators
Information:
SMI: Multidimensional Poverty Index
(sigma symbol) RT: Number of households
The cut-off for calculating the school enrollment indicator is if there are individuals aged 7-18 years, individuals who have not completed at least high school, and individuals who have never attended school.
d. Old School Indicator
Information:
SMI: Multidimensional Poverty Index
(sigma symbol) RT: Number of households
The cut-off for calculating the length of school indicator is if an individual is 19-30 years old, does not have a diploma, and the last diploma is package A, special elementary school, elementary school, primary school.
e. Decent Home Indicator
The cut-off for calculating a decent house indicator is if 1 out of 3 (roof, floor and walls) part of the house does not meet the proper criteria.
Information:
SMI: Multidimensional Poverty Index
(sigma symbol) RT: Number of households
f. House Density Indicator
Information:
SMI: Multidimensional Poverty Index
RT: Household
The cut-off indicator for inadequate housing density is a house with a floor area per household member below 7,2 meters2.
g. Adequate Drinking Water Indicator
Information:
SMI: Multidimensional Poverty Index
(sigma symbol) RT: Number of households
The cut-off for calculating drinking water indicators is categorized based on the source of drinking water used by households as follows: (1) unprotected wells, (2) unprotected springs, (3) surface water (rivers/lakes/reservoirs/ponds/irrigation ), (4) rainwater, (5) wells with a septic tank <10 meters distance, (6) pumps with <10 meters distance from a septic tank, and (7) springs with <10 meters distance from a septic tank.
h. Cooking Fuel Indicator
Information:
SMI: Multidimensional poverty index
(sigma symbol) RT: Number of households
The cut-off for calculating the indicator for cooking fuel is calculated based on the criteria for using the main cooking fuel in a household, namely kerosene, briquettes, charcoal, firewood and other materials that are not suitable.
i. Sanitation Indicator
Information:
SMI: Multidimensional poverty index
(sigma symbol) RT: Number of households
The cut-off for calculating the sanitation indicator is the category of using the type of bathroom in the household as follows: (1) there is a communal toilet washing bathroom, (2) there is a public toilet washing bathroom/whoever uses it, (3) there are household members who do not use , and (4) has no facilities.
j. Birth Certificate Indicator
Information:
SMI: Multidimensional poverty index
The cut-off calculation on the birth certificate indicator is for individuals aged 0-17 years who do not have or do not know that they have a birth certificate or cannot show their birth certificate documents.
k. Internet indicator
Information:
SMI: Multidimensional poverty index
(sigma symbol) RT: Number of households
RT: Household
The cut-off for calculating internet indicators is if in one family no one has accessed the internet and used the internet (including social media) in the last 3 months.
- Stage 10: Calculating Poverty headcount
Poverty head count will provide an overview of who is experiencing multidimensional poverty. At least in this case, each individual will know what kind of poverty they experience, q is the number of individuals who are categorized as poor multidimensionally, while n is the total population.
- Stage 11: Calculating Poverty Household
In accordance with the Alkire-Foster method, individual poverty must be applied to household by mapping each individual in a family experiencing multidimensional poverty.
- Stage 12: Split the Group and Breakdown of Dimensions
The groups created can be based on gender, village, city, age, and others. The poverty rate can increase if a person experiences poverty with additional dimensions, so this individual is sensitive to the multiplication of poverty. This poverty will adjust to the calculated group and can also be an international comparison between different countries.
This group breakdown aims to make it easier for local governments to determine how many (population or households are poor), where (poor areas), why (causes of poverty), and how (poverty alleviation).
In calculating the deprivation rate of each SMI indicator, a study has the choice to focus on all or part of the sample individual or household scope. If the study focuses on all individuals or households in the population then the headcount ratio (H) uses the uncensored type (not censored - the entire population is included in the calculation). However, if the study only focuses on deprived individuals or households, then the headcount ratio uses the censored type (censored - not all populations are included in the calculation).
According to OPHI, the use of uncensored or censored is adjusted to the needs of the study. In general, IKM studies use the censored type (so that the results of calculating the poor population can be used directly in policy formulation. Therefore, this study uses the censored headcount ratio type. This ratio is often also defined as the Multidimensional Poverty Rate (AKM). In In the initial stage, the study needs to calculate each indicator based on the cut-off point of the lower poverty line. After weighting based on all indicators, we can identify multidimensionally deprived households with a cut-off limit of 1/3. If an individual has a poverty indicator with a total value of more than 1/3 means the individual is multidimensionally poor. And if it is below 1/3, then the individual is not multidimensionally poor. In the censored headcount ratio type, only individuals who are multidimensionally poor are used as the basis for calculating the level of deprivation for each indicator.
On the other hand, multidimensional poverty intensity (A) calculates the average percentage of indicators by which poor people are deprived in the five dimensions of poverty. This intensity is calculated from individuals who are included in the deprivation category uncensored and accumulated at the population level. The higher the individual or population intensity value, the more severe the multidimensional level of poverty that is being experienced. The Multidimensional Poverty Index (IKM) integrates two factors of poverty, namely the AKM which is the percentage of poor people and intensity (A) which is the percentage of severity of the poor. The index value is calculated by multiplying the poverty rate by the poverty intensity.
Multidimensional Poverty Index (IKM) = AKM x A
The higher the IKM value, the higher the number and severity of individual poverty in households in a region.