Impacts of social protection on poverty reduction

Impacts of social protection on poverty reduction
Social Security Summer School, ILO-ITC Turin Elective Course 13 Week 2, Monday to Wednesday 3-5 October 2011, 14:00-17:00 Florence Bonnet and Christina Behrendt ILO Social Security Department, Geneva

A. Introduction 0. Quick overview Objectives and structure of the seminar

Impact of cash transfers on the reduction of poverty: A quick overview
Objectives Overview of the potential and limitations of micro-simulations in the assessment of the possible impact of social transfers on poverty reduction Includes some conceptual thinking behind (poverty concepts and measurement etc.) In practice... Requirements: data needs (which survey types usually contain the necessary information; how to find them; and how to use them?) Assessment of possible impacts principles, steps, hypotheses, interpretation, limitations

Outline of the course Introduction Some basics
0. Quick overview: objectives and structure of the seminar Linking poverty outcomes to policies: Social security programmes and poverty reduction Elements of a wider process: country-level rapid assessment Some basics Poverty and inequality: concepts and measurement Preparatory work for hands-on session Simulating the possible impact of cash transfer programmes Hands-on exercises and discussion Scenarios and group work Presentations of group work results and discussion Presentation of more examples and discussion Working with survey data and other useful sources Day 1 Day 2 Day 3

A. Introduction 1. Linking poverty outcomes to policies: Social protection programmes and poverty reduction

1.1 Evaluating the effects of social transfers on living standards
Ex-post assessment: Analysis of existing programmes or social security systems Effectiveness: Does the programme reach its objectives? Efficiency: Does the programme achieve its objectives in an optimal way? Ex-ante assessment: Preparing future reforms Adjusting parameters of existing programmes Designing new social security benefits/schemes Enhancing the coordination between different schemes within a social security system

1.2 Evaluating the effects of social transfers on living standards: Ex-post assessment (1)
Ex-post assessment: Analysis of existing programmes Effectiveness: Does the programme reach its objectives? Coverage: e.g. which proportion of elderly receives an old age pension? Benefit levels and effects: e.g. effects of old age pensions on living standards of pensioners; effects of social assistance on overall poverty reduction

1.3 Evaluating the effects of social transfers on living standards: Ex-post assessment (2)
Efficiency: Does the programme achieve its objectives in an optimal way? Coverage: Are benefits going to those who should receive them? (inclusion/exclusion errors) Benefit levels and effects: Are benefit levels adequate to reach objectives? Costs: Does the programme reach its objectives in a cost-effective way?

1.4 Evaluating the effects of social transfers on living standards: Ex-ante assessment (1)
Ex-ante assessment: Preparing for future reforms Adjusting parameters of existing programmes How can the coverage of a social insurance scheme can be extended to still uncovered groups of workers? Which benefit levels should be provided in order to effectively prevent poverty? Designing new social security benefits/schemes How could a new social pension programme be designed? What is the most effective way to introduce child benefits? Enhancing the coordination between different benefits within a social security system Identifying undue cumulation of benefits and coverage gaps

1.5 Evaluating the effects of social transfers on living standards: Ex-ante assessment (2)
Relevance of ex-ante assessments for establishing national social protection floors Identifying effective ways to close coverage gaps Assessing the possible impacts of a set of basic social security guarantees on poverty reduction Assessing the interplay between different programmes and identifying gaps Assessing several options for benefit levels and their impact on poverty reduction Assessing the cost of a proposed reform and its possible impact

1.6 Ex-ante assessment of impacts (1)
Ex-ante assessment of the impact of cash transfers on the reduction of poverty is.... a static micro-simulation of the (direct) impact of transfers on individual/household income/expenditure and poverty status And is not.... a full assessment of the impact which would take into account changes in people’s behaviour and further socio-economic effects a Poverty Impact Assessment / Poverty and Social Impact Assessment (WB, OECD and others)

Example: Tanzania Source: Gassmann, F. and Behrendt, C., 2006: Cash benefits in low-income countries: Simulating the effects on poverty reduction for Senegal and Tanzania, Issues in Social Protection Discussion Paper (Geneva: International Labour Office).

The basic idea income post-reform income minimum income threshold
pre-reform income households

1.7 Ex-ante assessment of impacts (2)
Why conducting ex-ante assessments of impacts? Estimating the likely effects of future reforms on people’s incomes Testing different reform options ... without hurting anyone... Reflecting the interplay of different programmes with household structures, employment, wages etc. Enhancing the effectiveness of future reforms Preconditions Know how.... Availability of good survey data (see next section...)

Introduction 2. Element of a wider process
Rapid assessment at the country level

Poverty impact | The process
The impact assessment is one element of a wider process Identification of coverage gaps and needs Costing exercise to close the coverage gap Assessment of the potential impact of different options on the reduction of poverty Feeds into national discussions National dialogue including social partners and other stakeholders Leading to a national social security extension strategy Aiming at building a national social protection floor… …progressively extending social security in line with national conditions Iterative process Sequential adaptation of assessment during the dialogue process to take into account new options considered

Assessment Matrix: structure
SPF objectives Existing SP provision What is foreseen in the SP Strategy Gaps Agencies involved Priorities Design gaps Implemen-tation gaps Health Children Working age Elderly Social Protection Floor template: guarantees and objectives Describe the present and planned social protection situation, taking into account SP strategy objectives Identify design gaps (population not covered due to the lack of SP policy / legislation Identify implementation gaps: dysfunction in existing policy and schemes (entitlements not meet, unavailability or lack of access to services Basis for the preliminary costing and thr analysis of potential impacts on poverty reduuction A consistent framework where all schemes and UN agencies support interventions can fit. Mapping & sharing of responsibilities and activities among actors and more specifically One UN Priority policy options to be decided through national dialogue on assessment results

The purpose of the assessment
Key questions Is there a SPF or some elements of the SPF in this country?  1. Inventory of schemes for the four guarantees: health, children, working age, elderly & disabled How far has a country advanced in the implementation of the floor?  2. Analysis & identification of gaps If the government plans to further develop its SPF, what should be done?  3. Recommendations How much would it cost and what would be the impact in terms of the reduction of poverty and inequality?  4. Scenarios, costing and respective impacts

Vietnam Assessment Matrix

Vietnam Assessment Matrix Main results (1)
Health for all Policy fully developed to achieve population coverage until 2014 No design gap as far as policy is concerned But some implementation gaps: At present 60% covered but no clear solution for the implementation the remaining 40% uncovered; lack of comprehensive analysis of the delivery or supply of services (quality, availability and geographical access); and need for a proper registration, data collection and monitoring system Income security for children Higher poverty rate than the overall poverty rate (22% against 14.5% on average) Provision of various benefits: Under regular social assistance schemes and the National Targeted Programme for Poverty Reduction (NTP-PR) few beneficiaries and low resources Specific programmes such as school fee exemptions and reductions for poor students. Over 10 per cent of children attending school benefiting Loans for food for students living in poor households Support for minority children for food, textbooks, notebooks Health coverage under 6 years (included under health) … but no general child benefit

Vietnam Assessment Matrix Main results (2)
Income security for the elderly Some benefits provided through: Contributory pension covering 18% of the working age 20% of the 55/60+ receive an old age pension) Targeted social assistance for the 80+ Some design gaps for the persons aged not covered by the contributory pension and the various targeted programmes groups under the NTPs Some implementation gaps Non contributory pension: closed to 40% of entitled beneficiaries not covered and Low level of benefit = 2/3 of the poverty line Under-declaration of wage level among formal workers Income security for people in working age Some design gaps Unemployment insurance covering 10% of the labour force (limited to formal employment in enterprises of 10 or +) maternity protection: 18% of the labour force (not all workers in formal employment) Social assistance for the disabled and single parents: low coverage and minimal benefit (only 32,5% of the poverty line) Some targeted programmes: housing and food support for minorities; and Benefits to people with national merit But no general income support for workers in informal employment Recommends to study the experience of India (100 days employment scheme)

B. Some basics 3. Poverty and inequality: Concepts and measurements

3.1 Income and poverty | Definitions
Poverty measures can be grouped into four major categories: Economic: mainly monetary indicators of household well-being, particularly food and non-food consumption or expenditure and income. Social: Other non-monetary indicators of household well-being such as quality and access to education, health, other basic services, nutrition and social capital. Demographic: These indicators focus on the gender and age structure of households, as well as household size Vulnerability: focus on the level of household exposure to shocks that can affect poverty status, such as environmental endowment and hazard, physical insecurity, political change and the diversification and riskiness of alternative livelihood strategies. Focus

3.1 Income and poverty How to measure poverty?
What are the respective advantages and disadvantages of different poverty concepts? Which resources are assessed? Consumption Income Assets Multidimensional deprivation How are they assessed? Objective measures Subjective measures How to draw the line? Absolute poverty line Relative poverty line

3.1 Income and poverty Examples of indicators and tools
Income and consumption expenditure level and distribution: Quintiles, deciles, etc Gini coefficient Poverty monetary main indicators Poverty headcount (poverty rate) Percentage of population below food poverty line Percentage of the population below the basic needs poverty line Poverty gap Poverty squared gap

Typical income distribution

3.2 Income & Poverty | Indicator of distribution Expenditure or Income quintiles / quartiles /deciles “Quantiles” are a set of 'cut points' that divide a sample of data into groups containing (as far as possible) equal numbers of observations. Main steps Divide population into ‘groups’ ranked from ‘poorest’ to ‘richest’ based on expenditure (or income) Divide into 4 groups (25% of the population each): quartiles Divide into 5 groups (20% of the population each): quintiles Divide into 10 groups (10% of the population each): deciles Sum for each group (equal proportion of the population) the total consumption (or income) Calculate the share of the consumption expenditure for each specific group (quintile, quartile or decile) to the total consumption expenditure or income Usual indicators Last quintile/decile - richest fifth/tenth of the population First quintile/decile - poorest fifth/tenth of the population Ratio Q5:Q1 for quintiles or Q4:Q1 for Quartiles

3.2 Income & Poverty | Indicator of distribution. Example of quintiles
Income / expenditure distribution: Share of Poorest Quintile Total consumption/income of the poorest quintile (20%), as a share of total consumption/income of the population. . Where yi is per capita consumption/income N is the total population m is the number of individuals in the lowest x %. Income / expenditure distribution: Share of Richest Quintile Total consumption/income of the richest quintile, as a share of total consumption/income of the population. .

3.2 Income & Poverty | Expenditure per capita by Quintile
Zanzibar and Tanzania mainland: Distribution of consumption expenditure (28 Days) by quintile and areas In Tanzania mainland the poorest 20 percent spent 7.2 percent of total expenditure In Zanzibar, the richest 20% spent on average nearly 40% of total consumption expenditure The 20 percent richest spent 42 percent of total expenditure This is 6 times more than the poorest

3.2 Income & Poverty | Gini Coefficient Definition
Gini coefficient or gini index The Gini index summarizes how equal or unequal income or expenditure distribution is. Gini index is calculated on a per capita basis Higher values indicate greater inequality. A Gini index of zero represents perfect equality and 1, perfect inequality. The Gini index measures the area between the Lorenz curve and the hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Cumulative share of income earned (or expenditure) (Yi) G = 1 – 2B 10% Cumulative share of people from lowest to highest incomes (Xi) 30

3.2 Income & Poverty | Gini Coefficient Calculation
Yi+1 Yi Yi-1 . Y1 Y0 Gini coefficient or gini index where fi = proportion of the population in classe i also equals to (Xi – Xi-1) with Xi = Cumulative share of people from lowest to highest incomes p = Nber of classes or observations Yi = Cumulative share of income earned (or expenditure) (Yi + Yi-1) X X1…. . Xi-1 Xi Xi+1 ƒi = Xi - Xi-1 31

3.2 Income & Poverty | Gini Coefficient
Urban versus rural Inequality is highest in urban areas, lowest in rural areas While poverty rates decrease notably in rural areas, inequalities increase over time

3.3 Income & Poverty | Poverty monetary indicators Definitions
Poverty headcount index (or poverty rate) the headcount index estimates the percentage of the population living in households with per capita consumption expenditure (or per equivalent adult) below the poverty line. it measures the incidence of poverty Poverty gap The Poverty Gap Index expresses the total amount of money which would be needed to raise the poor from their present incomes (c) to the poverty line (z), as a proportion of the poverty line, and averaged over the total population, which measures the depth of poverty The aggregate poverty gap shows the cost of eliminating poverty by making perfectly targeted transfers to the poor. This total cost can be related to GDP. The squared poverty gap measures the severity of poverty as the poorest households are given a greater weight in the equation.

3.3 Income & Poverty | Poverty monetory indicators Calculation
Poverty rates, poverty gap and squared poverty gap formulae can be represented as follows: Poverty rate = Q/N With Q = total number of poor Poverty gap index = 1/n* [(z-c)/z] Squared Poverty gap = 1/n* [(z-c)/z]2 q c<z  where n represents the total population, q the poor z the poverty line and c consumption expenditure If the parameter α = 0, then the equation is simply the headcount index. With α = 1, the equation measures the poverty gap, which is the average income / expenditure shortfall of the poor with respect to the poverty line. When α = 2, the equation represents a measure for the severity of poverty Foster-Greer-Thorbecke (FGT) indices where n is population size, q number of people below poverty line, yi is income, z is the poverty threshold. Poverty threshold is equal to the food threshold plus the non-food threshold, where threshold refers to the cost of basic food and non-food requirements. The parameter ¦Á can have three values, each one indicating a measure of poverty. The headcount index of poverty has ¦Á = 0. This is the common index of poverty, which measures the proportion of the population whose income (or consumption) falls below the poverty threshold. The poverty gap index has ¦Á = 1. This measures the depth of poverty in the sense that it indicates how far below on average the poor are from the poverty threshold. The poverty severity index has ¦Á = 2. This measure is sensitive to the distribution among the poor as more weight is given to the poorest below the poverty threshold. This is because the poverty severity index corresponds to the squared average distance of income of the poor from the poverty line, hence gives more weight to the poorest of the poor in the population.

3.3. Poverty | Poverty rates in Viet Nam (1)
Poverty rate by urban rural and region calculated by income (Government poverty line) 2002 2004 2006 2008 Food poverty lines (in thousands per capita and per month) Rural 112 124 200 290 Urban 146 163 260 370 Poverty rates Food poverty line 11,9 8,1 New government poverty line 21,2 18 16,1 3,9 3,3 8,6 7,7 6,7 Total 9,9 6,9 18,1 15,5 13,4 Food poverty line New Government poverty line adopted in 2006 and reported in 2004 for poverty rate calculation

3.3. Poverty | Poverty rates in Viet Nam (2)
General poverty rate by urban rural and region calculated by expenditure 2002 2004 2006 2008 Rural 35,6 25 20,4 18,7 Urban 6,6 3,6 3,9 3,3 Total 28,9 19,5 16 14,5 Exercise based on this one

Equivalence scales How to account for economies of scale?
Household income Equivalized income (how?) Per capita income Choice of scale may have strong effects on measured poverty, especially for sub-groups of the population Examples of equivalence scales: “classical OECD scale”: head: 1, other adults: 0.7, children: 0.5 “modified OECD scale”: head: 1, other adults: 0.5, children: 0.3 square root scale: (number of hh members)0.5 More general: income / (hhsize)e

Equivalence scales: Effects on measured poverty rates
Source: Behrendt, C., 2002: At the Margins of the Welfare State: Social Assistance and the Alleviation of Poverty in Germany, Sweden and the United Kingdom (Aldershot: Ashgate).

Poverty gaps | Vietnam General poverty gaps (calculated by expenditure)

Poverty profile Objectives
Analysing the relationship between poverty rates and household’s or individual’s characteristics Demographic and composition of the household Situation in the labour market Housing conditions and access to basic services Developing a picture of who are the most exposed to poverty Comparison of poverty rates and poverty gaps between different groups of the population

Poverty profile | Poverty rates & socio-demo characteristics – Vietnam
Poverty rates by age range: highest poverty rates among children (especially <6) Poverty rates in the population aged 6+ working: higher general poverty rate than the non working Highest poverty rates among the self employed in non registered enterprise (65% of total employment, 72% in rural areas) and people working for other households (16%) Poverty rates in the population aged 6+ not working: highest risk of poverty among disabled

Poverty profile | Poverty rates by age and area of residence Vietnam
Higher poverty rates in rural areas: between 5 to 7 times higher than in urban areas Typical U curve with higher poverty rates among children and elderly

B. Some basics 4. Preparatory work for hands-on session: How to become familiar with Excel formulas

Click session | Quiz Question 1 | Would you say that Excel is
Your favourite software… and has no secret for you Some horizontal and vertical lines Nice to do tables… possibly with one or two “=“ or “+” …. ?? Is it a new Hollywood master production? Question 2 | Definition of a formula A formula is a mathematical equation used to calculate a value Can be conditional Can be used to aggregate or redistribute values A formula can be ... magic None of the above 4 of the above

Quick exercice (1) | Context
We — the happy participants to the course n°13 — have the pleasure to celebrate our new ability to measure impact on poverty reduction of social security benefits and enjoy a delicious dinner Antipasti, Primi Piatti, Secondi Piatti and Dolci della Casa in Turnino… Difficult to resist! Result: an impressive bill …. far too big to be paid by a single person and still many participants do not have Euros (not yet or not any more) Solution by “speciality”: the bill is split between 3 persons by type of dishes José Manuel covers all Antipasti (1) Jane Chantal the Primi Piatti (2) Secondi Piatti (3) and…… Chico the Dolci della casa (4) and drinks (5)….

Quick exercice (2) | Context
Please go into Excel file….. It is just training in prevision of tomorrow session The bill, basis of the exercise has Five different colours = five codes Antipasti in blue Primi Piatti in red Secondi Piatti in green Dolci della casa in purple Drinks in orange The Menu …… purely informative

Quick exercice (3) | Questions
=SUM(C6:C50) Yesterday night unfortunately the restaurant’ cash register has been stolen…. there is a computer with Excel but the owner of the restaurant was not available to participate in this course… so no total bill is provided but only the detailed dishes prices… Question 1 Please calculate the sum of the total bill

Quick exercice (2) | Questions
=IF(E6=1,1,0) and =IF(AND($E6=2,$E6=3),1,0) =IF(OR($E6=4,$E6=5),1,0) Alternative not used here =IF(OR($E6=2,$E6=3),1,0) Question 2 Based on the codes indicated in the excel file, identify the respective “dishes” to be paid respectively by José Manuel (1), Jane Chantal (2) & (3) and Chico (4) et (5) = “simple formula” = $C6*F6 Question 3 After identification in question 2, allocate the amount by dish to the three “payers” … to sum the total amount to be paid respectively by José Manuel, Jane Chantal and Chico

Quick exercice (4) | Useful formula SUMIF
Question 4: Calculate the total amount to be paid respectively by José Manuel, Jane Chantal and Chico How to? In Excel, the SumIf function adds all numbers in a range of cells, based on a given criteria. Generic syntax: SumIf ( range, criteria, sum_range) range is the range of cells that you want to apply the criteria against (e.g code of type of dishes or code of household associated to each dish) criteria is used to determine which cells to add (e.g. list of codes for type of dishes). sum_range are the cells to sum (amount per dish)

Quick exercice (5) | Useful formula SUMIF
Applications: 2 options …. both will be used tomorrow Option 1 [in Bill (original)] =SUMIF(F6:F43,"=1",$C$6:$C$43) Sum the amount of dishes allocated to each of the 3 people in question 2 by column Option 2 [in Dishes category (original)] =SUMIF ('Bill (original)'!$E$6:$E$43,$C$6:$C$10,'Bill (original)'!$C$6:$C$43) 'Bill (original)'!$E$6:$E$43: column of codes for each types of dishes (from 1 to 5) in ‘Bill (Original)’ sheet $C$6:$C$10 Column with 5 values = list of individual codes for types of dishes in ‘Dishes category (original)’ $C$6:$C$43 Column of respective prices for dishes

Quick exercice (6) | Question 5 — redistribution
VLOOKUP Situation Italy just wins the football world cup and to celebrate this great news, the Ristorante Il Leccio offers a percentage reduction by type of dishes Question 5 Reallocate for each dish the percentage reduction applied depending to the category it belongs to

VLOOKUP | Redistribution of per capita value of benefit to each individual HH member (1)
Objective Searches for a value in the first column of a table array and returns a value in the same row from another column in the table array. The V in VLOOKUP stands for vertical. Use VLOOKUP instead of HLOOKUP when your comparison values are located in a column to the left of the data that you want to find. Syntax: =VLOOKUP(lookup_value,table_array,col_index_num,range_lookup) Lookup_value The value to search in the first column of the table array Table_array Two or more columns of data. Use a reference to a range or a range name. The values in the first column of table_array are the values searched by lookup_value. These values can be text, numbers, or logical values. Col_index_num The column number in table_array from which the matching value must be returned Range_lookup A logical value that specifies whether you want VLOOKUP to find an exact match or an approximate match (use FALSE)

C. Simulating the possible impact of cash transfer programmes
5. Hands-on exercises and discussion

Total poverty gap ratio
Poverty impact | Overview Initial situation Total population (42) Non poor (30) Poverty line = 500 Gap Indi = 270 Poor (12) Poverty rate 12/(30+12) = 29% 400 200 420 180 230 250 300 220 450 Total poverty gap ratio (2510/500)/42 =11.9% Total poverty gap c<z  Gap Indi = 2510

Poverty impact | Overview Initial situation
Total population (42) Non poor (30) 400 200 180 230 250 300 220 420 620 650 Non poor (32) Social cash benefit provided: targeted benefit of 200 to all poor people enable to work ….. and living alone Poverty line = 500 Poor (12) Poor (10) Poverty rate 10/42 = 24% New 400 200 420 180 230 250 300 220 450 Total poverty gap c<z  Gap Indi = 2180 New Total poverty gap ratio (2180/500)/42 =10.3% Simplified example of people living alone .... With no redistribution of benefit among household members

Poverty impact analysis | Steps
Pre-requisite Data file ready for use and key variables identified Analysis of the initial situation « ex-ante » Define and identify target groups for the new benefit (s) Define benefit(s): type and amount Add the new benefit amount to the income or consumption expenditure ex-ante Aggregation of individual (or equivalent) income or consumption expenditure « ex-post » at the household level Redistribution of this amount (per capita or per equivalent adult) among household members Calculation of distribution and poverty indicators « ex-post »    Individual level Household level

Pre-requisite | Ready to use data file (1)
Micro data file Microdata is data on the characteristics of units of a population, such as individuals, households, or establishments collected by a census, a survey, or experiment Dealing with microdata requires good knowledge of statistics and statistical software packages (SPSS, SAS, Stata, etc.).

Pre-requisite | Ready to use data file (1)
A micro data file is A « flat file», a table with: in columns: variables in lines: individuals, households or any other unit of observation In case of survey, this is associated with a questionnaire Basis for variable creation and essential for the understanding of possible filters and reference population for each question a variable dictionary (code book) Ideally a survey methodology (description of sampling, the weighting variable, etc..) & measurement of poverty if familiar ... a source of freedom … it is not … A black box Necessarily transparent not always one single file but a collection of files .... to merge not always in line with official results presented in national reports .. So it is sometimes … a puzzle in Vietnamese or Nepalese to “reconstruct” on the basis of associated documents … to come to this stage of « ready for use » can sometimes be the hardest and longest part of the process

Step 1 | SPSS file … in 2-3 pictures (± Stata)
Vietnam Household Living Standards Survey | VHLSS 2008 Variables view or variable dictionary Each column = one variable A question (typical questionnaire) = one or several variables according to the type of questions (single or multiple answers notably) Variables are defined by: a type of variable, a labels, some codes for pre-coded answers and corresponding labels A typical data file in SPSS or SAS or STATA is Some variables: the translation of the questionnaire Some data: answers of individuals to each variable Each line = Unit of observation - in the present case, an individual. Can be an household, an enterprise, etc. The total number of lines = sample size The weight variable assigns to each individual a certain weight acting as a “multiplicator” Each individual is identified by a single ID number or a combination of variables (region, district, commune, household_ID, individual ID) Each household should also be identified by a single ID (individuals from a same households will have the same HH_ID) Each variable is defined by A variable name A variable type (numerical, textual, date, etc.) A variable label Value labels of codes used for variable answers Defining missing values for certain modalities of answer not to be taken into account for analysis

Hands on | Excel files Excel files for exercises Groups Excel file
Several groups working on the same Excel file but testing various benefits Excel file One file with mainly two sheets Household level sheet Individual level sheet Built from the Viet Nam Living Standard Survey 2008 (sub-sample)

Step 1 | … the excel file a quick guided tour
Main parameters: poverty line, benefit amount, etc. Main results Main formula: explanation and applied formula Reminder of main steps and questions as well as references to useful formulas Quick access to all other sheets in the Excel file..... An overview 61

Step 1 | Excel file — File 1 at the individual level
The individual datafile Total annual consumption expenditure per capita in thousands of VND  Poverty rates and gaps, quintiles and gini are calculated on an individual basis One line = one individual Random sampling from the VHLSS 2008 (10% of the original datafile) for training purposes (DON’T DO THAT FOR A REAL ANALYSIS) Original sample size: 38,253 (total population: 86,312,257) Selected subsample for the exercise: 3,878 (10%) Total number households in the original sample: 9,189 (20,960,121 households at the national level) #H: Household size: total number of household members Per capita basis calculation No equivalent scale used in Viet Nam for poverty analysis #I – M: basic socio-demo characteristics Variables to identify individuals and households # Ind_ID Unique ID for each individual # HH_ID Unique Household ID Link with the HH datasheet for the aggregation of each individual income/expenditure at the household level From the sample to the total population WEIGHT Adjusting for non-response Adjusting for external information notably some proportions known in the total population for key variables selected when defining the sampling (e.g distribution of the population by region, district obtained from a recent census or an extrapolation of the most recent one HH

Pre-requisite | Excel file | File 2 at the household level
The household datafile One line = 1 household # HH_ID Unique Household ID / identifiant unique de chaque ménage Link with the Individual datasheet for the aggregation of each individual income/expenditure at the household level #C: Household size: total number of household members Per capita basis calculation #D: Total consumption expenditure at the household level = SUM of individual per capita expenditure pre-benefit for all household members From the sample to the total population WEIGHTHH for household WEIGHTHH= WEIGHTIND * HHSIZE

Click session | Quiz 2 Question 3 | First impression
Super, the steps are clear and I am fully ready to jump in to step 2 Well, why do we have two separate sheets??? From which one should I start? Break! I need a break Question 4 | Which are the essential variables to carry out an impact analysis on poverty reduction? Identification variables: individual and household id Weight variable Size of household Some individual characteristics: Sex, age, depending on the eligibility criteria used for the benefits The income or consumption expenditure variable used to determine poverty status All of the above All minus one of the above

Click session | Quiz 2 Question 5 | Structure of the individual level table In the individual table, each row represents an individual who can initially be poor or not, and who can potentially be a future beneficiary In the individual table, each column provides some information about the personal characteristic of all the individuals included in the sub-sample One of several lines of the individual tables correspond to one row of the household table (individuals who live in the same household) All of the above Question 6 | Working with a Sample survey means that Each line in the individual file represents one person at the national level Each line in the household file represents an household level Each line in the individual file is representative of a number of individuals at the national level equals to the value of the WEIGHT variable (for this individual/line) None of the above

Click session | Quizz 2 Question 7| What is the next step?
Calculate the initial poverty rate and eventually some poverty distribution indicators from the individual table Discuss parameters of possible benefit to provide to defined target groups Look for resources to finance the future benefit or change in existing programme Think of arguments to convince relevant ministries about the need of a new social protection benefit Question 8 | How do I go from the individual to the household level and vice-versa The individual_id is the key variable The household_id is the key variable The household size is the key variable All of the above

Click session | Quizz 2 Question 9 | Why do I have to deal with both individual and household levels? Because of the redistribution effect Benefit are provided to individuals, and poverty is calculated at the individual level => I do not need to deal with household level Because it makes the whole process more complicated Question 10 | The analysis of Impacts of social protection on poverty reduction can be appropriate to Adjust parameters of existing programmes Design new social security benefits/schemes Determine exactly what benefit will be able to eliminate poverty at the lower cost All of the above 2 of the above

Poverty impact analysis | Step 2
Data file ready for use and key variables identified Analysis of the initial situation « ex-ante » Define and identify target groups for the new benefit (s) Define benefit(s): type and amount Add the new benefit amount to the income or consumption expenditure ex-ante Aggregation of individual (or equivalent) income or consumption expenditure « ex-post » at the household level Redistribution of this total amount among household members (per capita or per equivalent adult) Calculation of distribution and poverty indicators « ex-post » Individual level

Step 2 | Simple analysis of the initial situation “ex-ante” (1)
Poverty line Viet Nam national poverty line in national currency in Viet Nam VND per month 3360 thousands VND per year (consumption expenditure in the excel file are annual) Calculation on a per capita basis

Objective: Calculate the initial poverty rate (before benefit) for the total population and by main age groups Identification of children, working age and elderly and quantification of these groups Identification of the poor Sum of poor population (do not forget the weight) Summary of initial poverty rates by group

How to? Identification of main age groups In Excel file columns S to AD (can concentrate on main groups for children) Formula: =IF($K6> Parameters!$C$28,1,0) With $K6: absolute address of age column in individual file Parameters!$C$28: maximum age of the working age in “parameters”. Any age superior to this value is part of the elderly group Allocate 1 for elderly, 0 otherwise Quantification of main age groups (e.g. Quantification of the elderly) Formula: = $S6*$F6 With $S6 : identification of elderly $F6 Weight variable = representation of this individual in the sample to the all population

Step 2 | Identified poor individuals. Useful formula (3) reminder
Useful formula IF Syntax: IF(logical_test,value_if_true,value_if_false) Example: identification of individuals whose consumption expenditure are inferior to the poverty line =IF($P6<Parameters!$C$54,1,0) =IF($P6<3360,1,0) With $P6 = variable « consumption expenditure per capita » Parameters!$C$54: value of the poverty line in the parameters sheet (pay attention to unit of reference – currency and time period used)

Step 2 | Identified poor individuals. Useful formula (3) reminder
Useful formula: IF AND/OR Example of syntax Identification of individuals between 16 and 64 =IF(AND($K6>Parameters!$C$22, $K6<Parameters!$C$21),1,0) With $K = Age variable (by fixing the column « $ » but not the line) Parameters!$C$22: 15 years old Parameters!$C$22: 65 years old

Step 2 |. Income & Poverty | Poverty monetory
Step 2 | Income & Poverty | Poverty monetory indicators Calculation (6) (reminder) Poverty rates, poverty gap and squared poverty gap formulae can be represented as follows: Poverty rate = Q/N With Q = total number of poor Poverty gap index = 1/n* [(z-c)/z] Squared Poverty gap = 1/n* [(z-c)/z]2 q c<z  where n represents the total population, q the poor z the poverty line and c consumption expenditure If the parameter α = 0, then the equation is simply the headcount index. With α = 1, the equation measures the poverty gap, which is the average income / expenditure shortfall of the poor with respect to the poverty line. When α = 2, the equation represents a measure for the severity of poverty Foster-Greer-Thorbecke (FGT) indices where n is population size, q number of people below poverty line, yi is income, z is the poverty threshold. Poverty threshold is equal to the food threshold plus the non-food threshold, where threshold refers to the cost of basic food and non-food requirements. The parameter ¦Á can have three values, each one indicating a measure of poverty. The headcount index of poverty has ¦Á = 0. This is the common index of poverty, which measures the proportion of the population whose income (or consumption) falls below the poverty threshold. The poverty gap index has ¦Á = 1. This measures the depth of poverty in the sense that it indicates how far below on average the poor are from the poverty threshold. The poverty severity index has ¦Á = 2. This measure is sensitive to the distribution among the poor as more weight is given to the poorest below the poverty threshold. This is because the poverty severity index corresponds to the squared average distance of income of the poor from the poverty line, hence gives more weight to the poorest of the poor in the population. 74

How to? Identification and quantification of the poor Columns AF (identification) and AG (quantification) in excel Formula: =IF($P6<Parameters!$C$54,1,0) With $P6: absolute address of consumption expenditure per capita Annual consumption expenditure per capita in thousands VND in Vietnam Parameters!$C$54: Poverty line in the corresponding unit in the parameters sheet Allocate 1 for poor, 0 otherwise Quantification of total number of poor Formula: = $AF6*$F6 With $AF6 : identification of the poor *$F6 Weight variable = extrapolation to the all population

How to? Calculation of the poverty rate for the population and for sub age groups Numerator: number of poor For total number of poor: Simple SUM at the end of column AG =SUM($AG$6:$AG$3883) For total number of poor by main age group =SUMIF('Raw data Individuals'!$W$6:$W$3883,"=1”,'Raw data Individuals'!$AG$6:$AG$3883) eg : sum the poor only for children Denominator: total population (F), total number of elderly (T), working age (W) Sum of the respective columns

Step 2 | Simple analysis of the initial situation “ex-ante” (8) | Poverty gap
Reminder ! Poverty gap The Poverty Gap Index expresses the total amount of money which would be needed to raise the poor from their present incomes (c) to the poverty line (z), as a proportion of the poverty line, and averaged over the total population, which measures the depth of poverty The aggregate poverty gap shows the cost of eliminating poverty by making perfectly targeted transfers to the poor. This total cost can be related to GDP. The squared poverty gap measures the severity of poverty as the poorest households are given a greater weight in the equation.

Step 2 | Simple analysis of the initial situation “ex-ante” (9) | Poverty gap
How to: Main steps For the poor Calculate the difference between the consumption expenditure per capita and the poverty line (column AI for total population) Formula: =IF($AF6=1,(Parameters!$C$54-'Raw data Individuals'!$P6),0) With $AF6=1 : identification of the poor Parameters!$C$54-'Raw data Individuals'!$P6: difference to reach the poverty line The sum of this column = The total aggregate poverty gap ; i.e. the cost of eliminating poverty by making perfectly targeted transfers to the poor

Calculate the poverty gap ratio
Step 2 | Simple analysis of the initial situation “ex-ante” (10) | Poverty gap Calculate the poverty gap ratio Calculate the poverty gap ratio for each individual by dividing the  by the poverty line (Column AR in excel file) Formula: =AI6/Parameters!$C$54 AI = Difference between individual consumption expenditure and poverty line () Parameters!$C$54 : poverty line Sum (taking into account the weight variable) column AI for all individual and divide by total population Formula: SUMPRODUCT and simple division

Step 2 | Simple analysis of the initial
Step 2 | Simple analysis of the initial situation “ex-ante” (11) | Poverty gap Useful formula SUMPRODUCT Take into account the « WEIGHT » variable Total poverty gap =SUMPRODUCT($AI$6:$AI$3883,$F$6:$F$3883) / $F$3885*100 With $AI$6:$AI$3883 = sum of all poor of the difference betweenn consumption expenditure and poverty line. $F$6:$F$3883 : weight variable to extrapolate to the total population / $F$3885*100 : divided by total population

6. Scenarios for group work

Which benefits could contribute to close coverage gaps as part of the SPF? Group work: National task force You are: National Social Protection Task Force for the Reduction of Poverty Composed of 1-2 national experts (quantitative analyses) 1-2 representatives of the Ministry of Labour and Social Affairs 1-2 representatives of the Ministry of Finance 1-2 representatives of the Ministry of Planning Representatives of social partners and other stakeholders as appropriate Task force elects spokesperson responsible for the presentation to Cabinet

Which benefits could contribute to close coverage gaps as part of the SPF? Group work: National task force ToRs for the Tasks Force: Provide an ex-ante assessment of one of the following reform options: Income security for the elderly Group 1 Non-contributory pension for all elderly (universal social pension) Group 2 Non-contributory pension for all poor elderly (targeted old age pension) Income security for children Group 3 Child benefits to all children (universal benefits) Group 4 Child benefits to poor children (targeted child benefits) Note: The exact specification of each benefit may be adapted as appropriate if there are good reasons to do so (explain!).

Which benefits could contribute to close coverage gaps as part of the SPF? Group work: National task force Your tasks Depending on the benefit scenario chosen, define an initial set of parameters (selection of beneficiaries, benefit levels, etc.) and justify why you have chosen these parameters Simulate “your” benefit and assess the impact on poverty reduction for the whole population and specific subgroups Discuss the design of “your” benefit within the Task Force taking into account considerations from different perspectives. If necessary, adjust your initial set of parameters and recalculate until you have reached an acceptable solution. Your presentation (max. 5 minutes) Explain the design of “your” benefit (selection of beneficiaries, benefit levels etc.) and your reasoning behind this choice. Present the results of your simulation. Provide recommendations with regard to the implementation of “your” benefit as part of a national social protection floor.

Poverty impact analysis | Step 3, 4 & 5
Data file ready for use and key variables identified Analysis of the initial situation « ex-ante » Define and identify target groups for the new benefit (s) Define benefit(s): type and amount Add the new benefit amount to the income or consumption expenditure ex-ante Aggregation of individual (or equivalent) income or consumption expenditure « ex-post » at the household level Redistribution of this total amount among household members (per capita or per equivalent adult) Calculation of distribution and poverty indicators « ex-post » Individual level

Steps 3&4 | Define and identify target groups and the benefit(s) provided (1)
Question : Which benefit(s) for who? Define and identify target groups Individuals or household By age group, situation on the labour market or status in employment, ability to work or not, etc Define benefit or benefits Type of benefit and amount Cash or in in-kind Estimate of corresponding cash value of a benefit in-kind Relative or absolute value If relative value: expressed as a proportion of the poverty line; of minimum wage or any other value of reference Value depending on household structure? Means-tested, targeted or universal If means-tested: perfect targeting of poor population or simulation of an imperfect targeting more close to reality such proxy means-tests (suppose availability of appropriate indicators) Individual level

Steps 3&4 | Simple examples of benefits
How to fix eligible age? For pension Legal retirement age for existing contributory pension Based on detailed analysis of poverty profile among elderly Cost versus impact on poverty reduction Any other? For Child benefit Based on detailed analysis of poverty profile among children, cost versus impact on poverty reduction Various benefits for different ages according to schooling age or not, any other?

Universal versus perfect targeted old age pension Pro and coins?

Steps 3&4 | Define and identify target groups and the benefit(s) provided (2)
Some particular cases … Change in an existing benefit Identification of actual beneficiaries for this benefit: Option 1: the identification variable is available in the survey (rare) Option 2: usually, find some proxy variables to identify this group of the population Calculation of the additional cost resulting from the change in the benefit level Example: Viet Nam: increase in the level of the contributory pension Benefit for the populations not yet covered Important in countries where the proportion of the population covered by existing social security provision represents a significant proportion (more than 10 per cent). Identification of actual beneficiaries in order to exclude them from the target group of the new benefit (simulated) Or provide them with a lower level of benefit (for the new benefit) Individuual level

Universal versus perfect targeted old age pension Columns BK (universal) and BL (perfect targeting) in Excel In case of universal pension Principle: a benefit of a given amount (to be fixed – parameters sheet) provided to all elderly (60+ or 65+ or any other age limit to be defined) =Parameters!$E$94*$S6 =Parameters!$E$94 : level of benefit for the elderly pension $S6: identification of the elderly (1 if elderly, 0 otherwise) In case of means-tested pension (perfect targeting….. Theory!) =Parameters!$E$94*$AF6*$S6 The only difference if the selection of the poor only (AF6)

Data file ready for use and key variables identified Analysis of the initial situation « ex-ante » Define and identify target groups for the new benefit (s) Define benefit(s): type and amount Add the new benefit amount to the income or consumption expenditure ex-ante Aggregation of individual (or equivalent) income or consumption expenditure « ex-post » at the household level Redistribution of this total amount among household members (per capita or per equivalent adult) Calculation of distribution and poverty indicators « ex-post » Household level Aggregation of individual (or equivalent) income or consumption expenditure « ex-post » at the household level

Step 6 | Aggregation of individual (or equivalent) consumption expenditure « ex-post » - household level Aggregation of ex-post consumption expenditure at the household level Household level From individual consumption to household aggregate consumption Hypothesis 3: distribution of the individual benefit for a shared and equal consumption among all household members Aggregation of new individual consumption expenditure (INDexp_post1 = INDexp_0 + Benef1) at the household level For each household = HHexp = ∑ INDexp_post1 (of each household member) Calculate consumption expenditure post benefit per capita (or equivalent adult) New consumption expenditure per capita = ∑ INDexp_post1 / household size (or sum equivalent adult values)

Step 6 | Aggregation of individual (or equivalent) consumption expenditure « ex-post » - household level Household level Aggregation of consumption expenditure at the household level. How to? < Household level (“HHBasis”) < Raw data Individuals = sum of individual consumption expenditure in the household HHId « 118 » 67221 =

Poverty impact | Step 6 household level useful formula (2)
Useful formula SUMIF Syntax SUMIF (HH_ID in individual file, HH_ID in HH file, Expenditure in individual file) SUMIF (range,criteria, sum_range) With Range: the range of cells that you want to apply the criteria against (e.g household id code in the Individual sheet | Column D) criteria: used to determine which cells to add (e.g. corresponding HH_Id in the household basis sheet “HHBasis” column B Sum_range: are the cells to sum (amount of ex-post individual consumption expenditure in individual basis sheet column BN)

Poverty impact | Step 6 household level useful formula (2)
Useful formula| application =SUMIF('Raw data Individuals'!$D$6:$D$3883,"="&HHbasis!$A7,'Raw data Individuals'!$BN$6:$BN$3883) 'Raw data Individuals'!$D$6:$D$3883: HH_ID at the individual level (same value for all household members (for a given household) "="&HHbasis!$A7: = HH_ID at the household level (household sheet “HHbasis” where one line = 1 household) 'Raw data Individuals'!$BN$6:$BN$3883: Column/ expenditure variable post benefit Result: sum for each household of consumption expenditure post benefit Last step: Calculate the new per capita (or equivalent adult) value (Columns I and J in the case of the elderly universal or means tested old age pension)

Data file ready for use and key variables identified Analysis of the initial situation « ex-ante » Define and identify target groups for the new benefit (s) Define benefit(s): type and amount Add the new benefit amount to the income or consumption expenditure ex-ante Aggregation of individual (or equivalent) income or consumption expenditure « ex-post » at the household level Redistribution of this total amount (per capita or per equivalent adult) among household members Calculation of distribution and poverty indicators « ex-post » Individual level

Step 7 | Redistribution of this total amount among household members
< Raw data Individuals Redistribution of consumption expenditure post benefit per capita (calculated for each household) to each household member (in the individual sheet). New basis for the calculation of poverty indicators post benefit < Household level (“HHBasis”)

Step 7 | From households to individuals Useful formula: VLOOKUP (1)
Syntax VLOOKUP(lookup_value,table_array,col_index_num,range_lookup) With Lookup_value : The value to search in the first column of the table array Table_array: Two or more columns of data. Use a reference to a range or a range name. The values in the first column of table_array are the values searched by lookup_value. These values can be text, numbers, or logical values. Col_index_num: The column number in table_array from which the matching value must be returned. Range_lookup: A logical value that specifies whether you want VLOOKUP to find an exact match or an approximate match (use FALSE)

Step 7 | From households to individuals Useful formula: VLOOKUP (2)
VLOOKUP | application =VLOOKUP($D$6:$D$3883,HHbasis!$B$7:$I$933,HHbasis!$I$2, FALSE) ($D$6:$D$ Column HH_ID at the individual level (the same for all household members of a given household) HHbasis!$B$7:$I$933 Table with as a first column (reference) the HH_id at the household level (Hhbasis) and the last column the one with per capita consumption expenditure post benefit to realocate to each household member of a given household (HH_ID) HHbasis!$I$2 = nième column in the table indicated above. 9 if column 9. FALSE Take into account the exact value in the cell ... It is much easier in SPSS or STATA!

Poverty impact | Step 8 Go! « ex post » Individuual level
Data file ready for use and key variables identified Analysis of the initial situation « ex-ante » Define and identify target groups for the new benefit (s) Define benefit(s): type and amount Add the new benefit amount to the income or consumption expenditure ex-ante Aggregation of individual (or equivalent) income or consumption expenditure « ex-post » at the household level Redistribution of this total amount among household members (per capita or per equivalent adult) Calculation of distribution and poverty indicators « ex-post » « « ex post » Individuual level

7. Presentation of results of group work

Which benefits could contribute to close coverage gaps as part of the SPF? Group work: National task force Your tasks Depending on the benefit scenario chosen, define an initial set of parameters (selection of beneficiaries, benefit levels, etc.) and justify why you have chosen these parameters Simulate “your” benefit and assess the impact on poverty reduction for the whole population and specific subgroups Discuss the design of “your” benefit within the Task Force taking into account considerations from different perspectives. If necessary, adjust your initial set of parameters and recalculate until you have reached an acceptable solution. Your presentation (max. 5 minutes) Explain the design of “your” benefit (selection of beneficiaries, benefit levels etc.) and your reasoning behind this choice. Present the results of your simulation. Provide recommendations with regard to the implementation of “your” benefit as part of a national social protection floor.

8. Presentation of more examples and discussion

Viet Nam: Simulating the cost of closing the Gap: The elderly
Income security for the elderly: 2 scenarios Pension benefit at the level of the poverty line for all uncovered elderly Changes recommended (vis-à-vis existing schemes) Lower the age (from 80 to 65) with progressive implementation until 2020 Increase the level of benefit: from 270 to poverty line level (500 thousands dongs per month in urban areas in 2011 and 400 thousands dongs per month in rural areas) Scenario 2 = Scenario 1 50 percent of the poverty line level for elderly benefiting from the contributory pension  

Viet Nam: Simulating the cost of closing the Gap: the elderly (scenario 2)
Alternative scenario: Elderly universal pension at the level of the poverty line for ALL elderly with reduced level for pensioners of the contributory scheme and progressive reduction of eligible age to reach 65+ in 2020 Additional cost as percentage of GDP Additional cost as percentage of general government expenditure

Viet Nam: Simulating the cost of closing the Gap: The working-age population
Income security and return to employment for working age population Comprehensive benefit package for the working age for workers in informal employment and disabled Employment guarantee scheme of 100 days per household per year Benefit level: minimum wage for 100 days / 220 working days per household (2 adults on average per household) Employment & training service available including training allowances to facilitate return to employment and creation of micro-enterprises Estimate of the cost of employment & training service: 2 staff per county & urban district (682) + non-staff costs Social assistance for those who are unable to work (3,7% of population has a severe disability): Benefit level: Increase in the level of existing benefits for people with disabilities to the level of the poverty line and cover those who are not covered at present Implemented gradually over a period of 4 years

Viet Nam: Simulating the cost of closing the Gap: working-age population
Employment guarantee scheme of 100 days per household per year and social assistance for those who are unable to work Additional cost as percentage of GDP Additional cost as percentage of general government expenditure

Viet Nam: Simulating the cost of closing the Gap: Children (Scenario 2)
Income security for Children | targeted scenario Comprehensive benefit package targeted at POOR children aged 0-15 (based on child poverty line = 22 percent) Child allowance for all children aged 0-15 years old: Benefit level: between 30-50% of minimum wage depending on age group (0-5/ 6- 10/ 11-15) as an incentive against child labour Additional education services for children in communities that are lacking schools or kinder-gardens Education services: 1 additional teacher per 20 children + non-staff costs One meal + take-home ration for all poor children in school (aged 5-15 yrs old) 50% of poverty line per child Scenario 2 = Scenario 1 but limited to 2 children per poor households Implemented gradually over a period of 5 years (20 % coverage each year)  

Viet Nam: Simulating the cost of closing the Gap: Children (Scenario 2)
Child allowance and benefits in kind for all poor children aged 0-15 years old (scenario 1) Additional cost as percentage of GDP Additional cost as percentage of general government expenditure

Viet Nam: Closing the gap Total cost of the benefit package
As a percentage of Government expenditure As a percentage of GDP

Viet Nam: The impact of filling the SPF gap on the general government deficit
Impact on general government deficit

Poverty impact | Impact on poverty rates Viet Nam
Base: SPSS data file | total sample and simulation of impact of the detailed benetits as presented in the costing exercise Reduction in the poverty rate Post 100 days guarantee for the working age Post Means tested for all poor children Initial poverty rate Post Elderly universal pension

Poverty impact | Impact on poverty gaps Viet Nam

Poverty impact | Useful indicators
Some useful indicators Total aggregate poverty gap Shows the cost of eliminating poverty by making perfectly targeted transfers to the poor. Indicators This total cost can be related to GDP Broken down in sub-poverty gaps (e.g.; by age groups) to analyse the composition of total poverty gap Comparison between expenditure to provide the benefit and the reduction of poverty gap Total COSTS (benefit + admin costs) Ratio = Poverty gap reduction (initial poverty gap – new poverty gap)

Viet Nam: Poverty impact Cost versus reduction of total poverty gap
Initial aggregate poverty gap Aggregate poverty gap post universal elderly benefit Aggregate poverty gap post means tested child benefit

Zambia Impact on poverty reduction Initial situation [1]
On a household basis in 2010, 36% of the households are in extreme poverty and 54% are considered as poor (combining extreme and moderate poverty). Among the most critical situations are the households headed by elderly people in rural areas or households composed only of elderly people. In both cases more than 50 percent are in extreme poverty and around three quarters are poor (considering both extreme and moderate poor).

Zambia Impact on poverty reduction Initial situation [2]
On an individual basis 67% of ederly aged 60+ are poor (46% in extreme poverty) This proportion reaches 77% among elderly in rural areas (55% of extreme poverty)

Zambia Impact on poverty reduction Initial situation: where do elderly live?
The majority of the elderly are living within their extended family either with the younger generation of working age (61 percent) or within a three generations household (22 percent). Only 6 percent of the elderly live in household composed exclusively of people aged 60 and over

Zambia Impacts of universal old age pension on poverty reduction | Options for static micro simulation Eligible age for the pension 60+ years 65+ years 70+ years Levels of monthly benefits Kwacha per month benefit level for the the elderly pension Katete pension Kwacha per month extreme poverty line in 2010 Kwacha per month Total poverty line 2010 Source: LCMS data

Zambia | Impacts of universal old age pension
Zambia | Impacts of universal old age pension on extreme poverty reduction

Zambia | Impacts of universal old age pension on
Zambia | Impacts of universal old age pension on extreme poverty gap reduction

Zambia | Impacts of universal old age pension on poverty rates by age range

Policy implications for building national social protection floors
Assessments are a useful tool to feed in the national dialogue on the extension of social security and on building national social protection floors Reflect the combined effects of a set of benefits on the realities of households Allow for interaction with household structures and employment patterns But: need to be aware of its limitations Possibility of transforming assessment methodology into policy monitoring tools to support implementation Extremely useful if done seriously

9. Working with survey data (2) and other useful sources and references

Microdata | Sources: which surveys?
Do not look for ONE data file and ANY variable on expenditure or income, but for THE data file used at the national level to carry out the poverty analysis and the variable(s) used to determine the poverty rate at the national level Application-oriented and not (purely academic) research Work with national data and initial statistics that are used at the national level Population: level and distribution by age and geographic areas Initial poverty rate and other related indicators used and shared in the country Types of surveys Income and expenditure surveys or equivalent

Microdata | Some examples of typical surveys to
Microdata | Some examples of typical surveys to be used for impact analysis

Microdata | Where to find them? (1)
National institute of statistics More and more countries developed a data catalog with sometimes a direct access to micro data in SPSS or STATA format Links to national statistical offices: International sources (1) ISHN | International Household Survey Network Survey catalog ( Survey questionnnaires ( Recently: Household survey data catalog ( )

Microdata | Where to find them? (2)
International sources (2) World Bank Central Microdata Catalog The Central Microdata Catalog is a portal for all datasets held in catalogs maintained by the World Bank and a number of contributing external repositories Europe: Luxembourg Income Study LIS is home to the Luxembourg Income Study Database and the Luxembourg Wealth Study Database: harmonised microdata from high- and middle-income countries around the world. ( ) From GESS | Statistics page Social protection in regular national household surveys: questionnaires, types of questions and links to resources (including microdata when possible) ttp://

GESS | Social protection in regular national household surveys:
GESS | Social protection in regular national household surveys: questionnaires, types of questions and links to resources Information organized by region country Access to main resources questionnaires survey reports microdata when available webspace dedicated to the survey updated on a regular basis

Assessing impact on poverty reduction | some references (1)
ILO studies ILO: Viet Nam. Compatibility analysis of the national Social Protection Strategy and the UN Social Protection Floor Initiative, Costing and financial projections to implement social protection policies , draft report. ILO: Zambia. Introduction of a Universal Pension Scheme . Section 5. Impact of the universal old age pension on poverty reduction Gassmann, F. and Behrendt, C., 2006: Cash benefits in low-income countries: Simulating the effects on poverty reduction for Senegal and Tanzania, Issues in Social Protection Discussion Paper (Geneva: ILO), Broader Poverty impact assessment (PIA) Promoting Pro-Poor growth: A Practical Guide to ex-ante Poverty Impact Assessment | Access to resources / download guide

Assessing impact on poverty reduction | some references (2)
The Poverty impact “webspace” (Gess) Access to main resources associated to this course: Excel files, documents, guides and examples Page.do?pid=1235

GESS | Social transfers matrix
Social transfers impact web space A matrix presents available evidence on the effects of different social transfers programs around the world a desk review on the social transfers domain which consists of quotes extracted directly from the literature reviewed No restriction was applied but the Matrix does not pretend to be exhaustive A search engine by type of effects, specific groups, main target groups (children, working age, elderly),country or region A List of Social Transfers Programs: snapshot of a significant number of social transfer initiatives around the world An extensive list of Bibliographical Resources on social transfers programs (available for download)

presents available evidence on the effects of different social transfers programs around the world

Impacts classified by effects (poverty impact, health, education, participation on the labour market, etc.) Specific groups Main target groups (children, working age elderly) Category of programmes

Examples Income level and stimulation of consumption Bolsa Familia As a result, the program has also demonstrated a significant impact on poverty (...) Results of the annual household survey (PNAD 2004) show that the BFP accounted for (...) 16% of the recent fall in extreme poverty'. (Lindert et al, 2007, p. 116). The nuts and bolts of Brazilian Bolsa Família programme: Implementing conditional cash transfers in a decentralized context Lindert, K. - Linder, A. - Hobbs, J. - Brière, B effects (poverty impact, health, education, participation on the labour market, etc.) Progresa (Programa de Educacion, Salud y Alimentacion) | Oportunidades" The conditional cash transfers [Bolsa Família, Oportunidades and Chile Solidario] proved to be an important inequality-reducing factor in all three countries. With a share of about 0.5 per cent of total income in Brazil and Mexico and much less in Chile, the CCTs were responsible for 21 per cent of inequality reduction in Brazil and Mexico and 15 per cent in Chile. (Soares et al, 2007: 17). Conditional cash transfers in Brazil, Chile and Mexico: Impacts upon inequality "Soares, S. - Osório, R. - Soares, F. - Medeiros, M. - Zepeda, E. "

Child Support Grant `In the absence of the CSG, but after taking account of the SOAP, 42.7% of children would be in poverty and 13.1% would be in ultra-poverty. As previously explained, 33.1% of individuals are poor after taking account of SOAP. Assuming that all the eligible (under the age of 7) register for the CSG, household poverty would fall to 28.9%. Even more strikingly, poverty among children (under 7) falls from 42.7% to 34.3% and ultra poverty falls from 13.1% to 4.2%¿. (Woolard, 2003: 9). Social assistance grants: Impact of government programmes using administrative data sets Woolard, I. – 2003 Social Pension The social pension [in South Africa] reduces the number of people living below the poverty line by 2.24 million. It increases the income of the poorest 5% of the population by 50%'. (HelpAge International, 2009). Social Pensions in South Africa HelpAge International – 2009

Impacts of social protection on poverty reduction

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