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Ben E. Aigbokhan, Ph.D Department of Economics Ambrose Alli University Ekpoma, Nigeria. UNSD Capacity Building Workshop For LISGIS Staff, Monrovia, Liberia.

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Presentation on theme: "Ben E. Aigbokhan, Ph.D Department of Economics Ambrose Alli University Ekpoma, Nigeria. UNSD Capacity Building Workshop For LISGIS Staff, Monrovia, Liberia."— Presentation transcript:

1 Ben E. Aigbokhan, Ph.D Department of Economics Ambrose Alli University Ekpoma, Nigeria. UNSD Capacity Building Workshop For LISGIS Staff, Monrovia, Liberia 12-16 December 2011.

2  To acquaint participatants with working definition of poverty and the justification for measuring poverty.  Poverty may be defined on the basis of monetary dimension or non-monetary dimension: Either dimension views poverty as a manifestation of pronounced deprivation of well being.  Well being is conventionally linked to command over consumption.  The poor are therefore those who lack enough income or consumption to place them above some defined minimum level. This is the monetary dimension of poverty.  The broader approach to well being focuses on the capabilities of individuals to function in society.  Lack of capabilities is reflected in inadequate income, education, health, political freedom, or powerlessness.  1.2Why Measure Poverty  -To be able to identify the poor.  -To be able to target appropriate interventions.  -To be able to monitor and evaluate projects and policies targeted at the poor.  -To be able to evaluate the effectiveness of institutions whose mandate is to help the poor. 

3  Define an Indicator of Welfare.  Most measures of welfare are based on household consumption expenditure or income. In developing countries preference is for current consumption rather than current income, for the following reasons:  In the short run it reflects more accurately the resources that households control. Income tends to be understated (table 1).  Over the long run, it reveals information about incomes at other dates; in the past and future.  In poor countries, income is particularly difficult to measure accurately, especially in agriculture.  Establish a minimum acceptable standard of the indicator to separate the poor from the non-poor.  Generate a summary statistic or index to aggregate the information from the distribution of the welfare indicator relative to the poverty line.  Comparisons across households at similar consumption level is meaningful when adjustments are made for differences in household size, age composition, the prices they face, the publicly provided goods to which they have access.  When divided by the number of household members, this gives per capita measure of household consumption expenditure or income.  When adjusted for age composition, and therefore household consumption needs, it gives adult equivalence scales.  An adult equivalence scale typically measures the number of adult males to which that household is deemed to be equivalent. Each member of the household counts as some fraction of an adult male. Effectively, household size is the sum of these fractions. It is not measured in members but in numbers of adult equivalence.  Both fall under the welfarist approach to measuring well being.  A non-welfarist approach would focus on whether households have attained certain minimum levels of, say, nutrition or health. In this case, indicators would include caloric intake, proportion of income/expenditure devoted to food, housing conditions, child schooling, and infant mortality rate.

4 LowestLower-midMiddleMid-upperHighestOverall Income/capita4946949561,1912,1901,105 Expenditure/capit a 5187569841,3382,5401,227 Food spending /capita 3785266438071,382747 Food as % expenditure 737065605461 Source: Haughton and Khandker (2009) P.23. Income tends to be understated for the following reasons: Recall problem. Intent to limit tax burden. Reluctance to report income from illegal sources. Some parts of income are difficult to calculate accurately. The understatement of both income and expenditure means that poverty rates are overstated. It also means that the estimates of income and expenditure that are based on sample survey data invariably fall short of the levels observed in national accounts data.

5  Objectives of the session:  To acquaint participants with what a poverty line is and why is it needed.  To enable participant develop the skill required for constructing poverty lines.  3.1Defining a poverty line  -The poverty line defines the level of consumption or income needed for a household to escape poverty.  -The poverty line is obtained by specifying a consumption bundle considered adequate for basic consumption needs, then estimating the cost of those basic food and non food needs.  -Another approach is to determine a food poverty line, based on some notion of the minimum caloric intake required to stay healthy and productive. The income required to purchase these basic needs food bundle is computed.  -If the cost of basic nonfood needs is estimated, this added to the nonfood basic needs will equal the overall poverty line.  3.2Approaches to Constructing a Poverty Line: Cost of basic needs approach:  (i)One approach is to compute a poverty line for each household, adjusting it from household to household to take account of differences in the prices they face and their demographic composition. This gives different poverty line for each household.  (ii)A second approach is to construct one per capita poverty line for all individuals, but to adjust per capita expenditure / income for differences in prices and composition. The adjusted per capita expenditure/income is then compared with the poverty line to determine whether the individual is living below the poverty line. This approach gives a single poverty line.  (iii)A third approach is to construct poverty lines by region. Separate poverty line is constructed for each region, based on the prices prevailing in each region. Each household in a region is then assessed to be poor if its per capita expenditure / income is below the regional poverty line. (Table 2)  -Over time, nominal poverty lines do change for a population;  (i)Due to change in price over time, and  (ii) If the real poverty threshold is revised over time (Table 2).

6 RegionFood Poverty LinePoverty LineFood Poverty LinePoverty Line Phnom Penh1,1851,5781,7372,470 Other Urban9951,2641,5832,093 Rural8811,1171,3791,777 Example: Table 2: Summary of Poverty Lines for Cambodia: riels Per Person Per Day 1993/94SESC 1999CSES Source: Haughton and Khandker (2009) P.42 3.3Relative and Absolute Poverty Lines - Generally, the choice of poverty line depends largely on the intended use of the poverty rates. -Sometimes we are interested in identifying the poorest segment of the population for purposes of policy intervention. We may want to identify the poorest one-fifth or two- fifths or one- third. These are the relatively poor. -Poverty line may in such cases be defined as some percentage, say, two-thirds, of the mean income / expenditure. -Were the objective is to identify and target today’s poor, a relative poverty line is appropriate, if it is tailored to the overall level of development. -Absolute poverty line, on the other hand, is fixed in terms of the standard indicator being used, and fixed over the entire geographical space of the poverty comparison. The poverty line is set so that it represents the same purchasing power year after year, but this line may differ from region to region or country to country. -An absolute poverty line is essential if one in concerned to judge the effect of antipoverty policies over time. -Legitimate comparisons of poverty rates between one region and another, or between one country and another can only be made if the same absolute poverty line is used in both regions or countries. -The World Bank/UN needs absolute poverty lines to be able to compare poverty rates across countries: US$1/day, revised in 2008 to US$1.25 a day is commonly used ( Table 3). The poverty line refers to the poverty line used by the 15 poorest countries in their sample, converted to US dollars, using the most recent measures of purchasing power parity.

7 CountryYear % of population living on less than $1/day CountryYear % of population living on less than $1.25/day Indonesia, rural200524China, rural200526 Indonesia, urban200519China, urban20052 Philipines200623India, rural2004/0544 Vietriam200850India, urban2004/0536 Vietriam200622Nigeria200364 Region % of Population Living on less than $1/day in 1998 % of population living on less than one- third of average national consumption for 1993 (in 1998) East Asia & Pacific15.319.6 East Asia & Pacifie Excluding China11.324.6 Europe & Central Asia5.125.6 Latin America & the Caribbean15.651.4 Middle East of North Africa1.910.8 South Asia40.040.2 Sub-saharan African46.350.5 Total24.032.1 Total excluding china26.232.0 Table 4:Absolute and Relative Poverty Rates Table 3:$1/day Absolute Poverty Lines Source: Haughton and Khandker (2009) P.49

8  3.4Objective Poverty Lines  The Cost of Basic Needs method  This method requires composing a consumption bundle that is deemed to be adequate, with both food and nonfood components, and then estimate the cost of the bundle for each subgroup.  The process is as follows:  Pick a nutritional requirement for good health. The standard value widely used, which has been proposed by the FAO, is 2,100 calories per person per day.  Estimate the cost of meeting this food energy requirement, using a diet that reflects the habits of households close to the poverty line. Let this food component be Z f.  Add a nonfood component, Z nf.  Sum up both to derive the basic needs poverty line, Z bn = Z f + Z nf  Table 5: Illustration of construction of cost of food component of poverty line for Nigeria.  Table 5.1: Monthly per capital food poverty line-national urban average, 1996 Food items Monthly Consumption (kg) Calories Per kg Total calories Per month Unit required Prices N/kg 1996 Food Expenditure Poverty line Cassava2.6435109,266.42.64103.30272.71 Beans 2.46 3,4208,413.22.46134.77313.53 Rice2.20364.08,008.02.20123.06270.73 Maize2.283.5708,139.62.2844.95102.49 Millet0.383,3301,265.40.3832.0012.16 Yam3.291,2354,063.23.29143.72472.84 Meat1.632,5004,075.01.63129.87211.69 Fish(dried)1.902,8905,491.01.90360.43684.82 Eggs0.441,400616.00.4442.11118.53 Palm oil0.528,7504,5500.52186.1596.80 Tomatoes2.58220567.62.58131.01338.01 Pepper0.8794087180.8728.3724.68 Vegetables1.28250320 1.28 35.5845.54 Fruits0.34430146.20.3424.88.43 Onions0.57410233.70.5747.2626.94 Sugar0.224,000880.00.2243.239.51 56,853.12,928.93

9 1985/861992/931996/97 National776.27723.771,169.18 Urban808.34742.061,278.25 Rural742.68737.961,179.76 Gender Male-headed770.52833.931,237.59 Female-headed760.18711.821,154.23 Regions : Northeast736.64795.161,169.72 Northwest827.641,181.951,169.92 North central795.55725.771,149.25 Southeast800.93807.851,379.39 Southwest764.69739.181,235.88 South south781.31824.291,156.61 Table 5.2: Food poverty lines Source: Aigbokhan (2000) p. 15. 3.5Subjective Poverty Lines -This approach relies on self-rated or self-assessment poverty lines. It involves asking people simple questions such as; (i)What income level do you personally consider to be absolutely minimal; that is, below which you could not make ends meet? (ii)Do you consider your current consumption to be adequate to make ends meet? -The answers provided, e.g. in (i) could be plotted, and a line fitted through the points to obtain a subjective poverty line, z*. Example: x x x x x x x x x x x x x x x x x Z*Y (actual income) subjective minimum income


11 Expenditure in country100110150160 Poverty Gap251500 G i /Z0.200.12000.08(=0.32/4) Expenditure for each household Poverty gap index (P I ) The index does not reflect changes in inequality among the poor. 4.3Poverty Severity (Squared Poverty Gap) Index -The measure is a weighted average of poverty gaps as a proportion of the poverty gap. -The weights are the proportionate poverty gaps themselves. That is, where the poverty gap is, say 10%, of the poverty line, it is given a weight of 10%; for a poverty gap of 50%, it is given a weight of 50% -By squaring the poverty gap index, the measure implicitly puts more weight on observations that fall well below the poverty line. Example: Calculating Squared Poverty Gap Index Assume Z = $125 Square Poverty Gap Index (P 2 ) Expenditure in the country100110150160 Poverty Gap251500 G/Z0.200.1200 (G/Z) 2 0.040.0144000.0136(=0.0544/4) -The three indexes of poverty form what has been termed a family of poverty measures proposed by Foster, Greer, and Thorbecke (1984), which is written as: P α =I (Y i ) α ………………. (6) N Z Where α is a measure of the sensitivity of the index to poverty when the parameter α = 0, P 0 is simply the headcount index; when α = I, the index is poverty gap, and when α = 2, the index is poverty severity index. 4.4Checking for Robustness of Poverty Lines -There are four main reasons why measures of poverty may not be robust. (i)Sampling error, which is due to the fact that poverty rate for the entire population of a country is based on sample data which captures only a modest number of household. (ii)Measurement error, which is due say to underreporting. This tends to overstate the degree of poverty. Unknown differences in needs between households at similar levels of income / consumption, even when adult equivalence scale is used. Uncertainty and imprecision due to choice of poverty line.

12  Objective of the session:  To expose participants to what a poverty profile is and why it is useful, particularly in mapping the various dimensions of poverty.  5.1What is a Poverty Profile?  -A poverty profile sets out the major dimensions of poverty.  -It shows how the pattern of poverty varies by demographic characteristics and geographical location of individuals or households.  -Thus, a poverty profile is useful for comprehensive poverty comparison across sub- groups of a country. Box 2: Key Questions to Guide in Preparing a Poverty Profile. 1.-Does poverty vary widely between different areas in the country? 2.-Are the most populated area also the areas where most of the poor live? 3.-How is income poverty correlated with gender, age, urban and rural, racial or ethnic characteristics? 4.-What are the main sources of income for the poor? 5.-On what sectors do the poor depend for their livelihoods? 6.-What products or services-tradables and montradables-do the poor sell? A tradable good is one that is, or easily might be, imported or exported. The prices of such goods are influenced by changes in the world price and the exchange rate. 7.-To what extent are the rural poor engaged in agriculture? In off-farm employment? 8.-How large a factor is unemployment? Underemployment? 9.-What are the important goods in the consumption basket of the poor? How large are the shares of tradables and nontradable? 10.-How is income poverty linked to malnutrition or educational outcomes? 11.-What are the fertility characteristics of the poor? 12.-To what public services do the poor have access? What is the quality of these services? -How important are private costs of education and health for the poor? 1.-Can the poor access formal or informal credit market? 2.-What assets-land, housing, and financial-do the poor own? Do properly rights over such assets exist? 3.-How secure is their access to, and tenure over, natural resources?

13  5.2Poverty Profile Presentation  There are two main ways of presenting a poverty profile.  By poverty status: Poor versus nonpoor, or by expenditure per capita quintile. Then summarize the incidence of characteristics, e.g. educational level of each group.  By some characteristics, e.g. age, educational level, occupation of household head, region of residence. Then report the poverty rate for each components.  Examples on Nigeria and Indonesia  5.3Poverty comparisons over Time  To enable comparison of poverty oven time, based on more than one round of household survey, certain steps are necessary.  Use data from highly comparable questionnaires with respect to sampling frame and definitions of income or consumption; otherwise, adjust the definition of income por consumption aggregates over time to ensure that similar definitions are used.  Adjust for price changes over time. Use temporal or regional price indexes to ensure similar definition of the poverty line over time and across regions to measure real income or expenditure over time. Principal Sector of Employment Population Share, 1984 (percent) Contribution of sectoral change (x 100) Headcount Index Poverty gap index Poverty Severity Index (p o )(percent) (p 1 ) (percent) (p 2 ), Farming Self-employed Laborer 45.0 9.0 49.8 11.2 54.6 14.8 57.4 16.5 Industry Urban Rural 2.6 3.3 4.1 0.8 2.8 3.2 0.4 3.1 2.6 0.3 2.7 2.2 construction trade Urban Rural 5.4 6.6 3.8 2.2 7.2 3.6 1.6 5.6 2.7 1.4 4.7 2.2 Transport services Rural Urban Total sector effect (including omitted sectors) Contribution of population shifts Interaction effects 6.5 5.8 n.a. 1.0 2.9 89.3 13.2 - 2.6 1.0 2.4 93.8 10.4 -4.3 0.9 2.0 95.1 9.4 - 4.5 Total 100.0

14 Principal Sector of Employment Population Share (percent) Headcount Index (p o ) (percent) Poverty gap index (p 1 ) (percent) Poverty severity Farming Self-employed Laborer Industry Urban Rural construction trade Urban Rural Transport services Rural Urban Other total 41.1 8.6 3.0 3.4 4.3 6.3 7.6 4.1 7.6 7.3 6.7 100.0 3.11 38.1 8.1 19.4 17.4 5.0 14.7 10.7 4.2 11.6 17. 21.7 6.42 7.62 1.26 3.00 2.92 0.71 2.42 1.53 0.61 1.84 3.55 4.22 1.97 2.21 0.32 0.76 0.80 0.17 0.61 0.34 0.14 0.49 1.03 1.24 Head count Index (P o ) Poverty gap Index (P 1 ) Poverty severity c Index (P 2 ), x100 Index (percent) Contribution To total (percent) Contribution To total (percent) index Contribution To total (percent) Share of Total Population (percent) 35.9100.06.5100.02.0100.0 Age of head 18-30 years36.710. 31-35 years35.410. 36-40 years43.621. 41-45 years40.315.77.315.82.215.314.0 46-50 years36.514.47.716.92.416.914.2 51-60 years28.315.85.316.31.716.820.0 61 and above32.011.35.611.11.811.327.7 Male36.484.46.684. Female33.615.

15  Objective of the session: To enable participants identify main causes of poverty and understand how regression technique could be used to identify the immediate main causes of poverty, for purposes of identifying necessary policy interventions.  6.1Causes of Poverty  The main causes of poverty may be classified by certain characteristics;  Household and individual characteristics, the most important of these are;  Demographic characteristics, such as household size, age structure, gender of head, dependency ratio.  Economic, such as employment status, occupation, hours worked, property owned.  Social, such as health and nutritional status, shelter, education of head.  Regional level characteristics, which include availability of infrastructure, proximity to markets, quality of governance, property rights and their enforcement, and vulnerability to weather conditions.  6.2Analyzing the Determinants of Poverty  -The most widely used technique to identify the contribution of different variables or indicators to poverty is regression analysis.  -There are two main types of analysis;  (i)Attempts to explain the level of expenditure per capita (an indicator for living standard or welfare) as a function of a variety of variables or indicators, typically those discussed in 6.1 above.  (ii)Attempts to explain whether the household is poor, using a probit or logit regression. In this case, the independent variables are as in 6.1, but the dependent variable is binary, taking the value of 1 if the household or individual is poor and zero otherwise.  -A regression estimate shows how closely each independent variable is related to the dependent variable, holding all other influences constant.  A typical multiple regression equation as applied in poverty analysis is  Log (Y i ) =a 0 +a 1 X i1 +a 2 X i2 +a 3 X i3 +…..+a n X in  Z

16  Where z is the poverty line, y i is per capita expenditure or income, X i are respective explanatory variables, and a j are the coefficients to be estimated.  -Level of significance: As a rule of thumb, t-statistic of less than 2, p-value of 0.05 and above, suggests that estimated coefficient is not statistically significant from zero.  6.3:Interpreting Regression Results on Determinants of Poverty  Examples:  Table 6.1: Determinant of household welfare in Ivory Coast, 1993 Dept. variable: lag(per capital) Urban Coeff: t-statistic Rural Coeff: t-statistic Educ. Level of most Educated male Elementary Junior secondary Senior secondary University 0.38 5.3 0.62 8.6 0.80 9.6 0.93 9.4 0.08 0.9 0.05 0.4 Educ. Level of most Educated female Elementary Junior secondary Senior secondary University 0.11 1.7 0.24 3.1 0.34 4.1 0.52 4.1 0.07 1.0 0.27 2.2 Value of selected house Hold assets Home Business assets Savings 0.06 5.3 0.04 3.3 0.08 4.7 0.16 4.9 Hectares of agric. Land Cocoa trees Coffee trees 0.17 4.3 0.04 1.3 Distance to nearest paved road -0.04 -2.0 Distance to nearest market -0.09 -3.3 Unskilled wage 0.37 0.4

17 ConstantAge of headAge 2 Sex of headEdu. Of head Household size Household Size 2 Adj. R 2 Middle Belt Rural 8.73 (57.68) -0.002 (0.33) -0.00001 (0.19) -0.64** (13.29) 0.03 (1.46) -0.31** (22.23) 0.01** (13.18) 0.31 Urban 7.49 (22.63) 0.02 (0.99) -0.0001 (0.89) -0.29** (3.15) 0.17** (6.11) -0.25** (13.49) 0.006** (7.63) 0.32 North-East Rural 7.49 (42.63) 0.01* (1.59) -0.0001* (1.70) -0.12 (1.46) 0.09* (3.61) -0.32** (20.10) 0.01**0.29 Urban 7.26 (11.99) 0.01 (0.51) -0.0002 (0.69) 0.14 (1.14) 0.19** (4.44) -0.26** (6.64) 0.009** (3.75) 0.35 North-West Rural 7.60 (41.58) -0.02** (2.62) 0.0002* 0.14 (1.18) 0.14** (4.10) -0.29** (16.65) 0.01** (9.40) 0.28 Urban 8.63 (12.82) -0.05* (1.77) 0.0004 (1.45) 0.12 (0.58) 0.05 (0.92) -0.20** (5.81) 0.004** (2.38) 0.38 South-East Rural 8.10 (36.35) 0.01 (0.63) -0.0001 (0.55) -0.16** (3.55) 0.12** (4.81) -0.35** (18.10) 0.01** (10.34) 0.31 Urban7.92 (11.39) 0.03 (1.01) -0.0003 (1.11) 0.06 (0.24) 0.18** (2.62) -0.58** (7.46) 0.03** (4.76) 0.49 Source: Aigbokhan (2000) Lecture 7:Poverty Analysis based on Census data Objective of session: To acquaint participants with basic methodologies useful in computing and analyzing poverty estimates, based on national population census data.

18  7.1Poverty Mapping  Governments are often interested in more detailed poverty rates for relatively small geographical units.  Often in a given region there are typically wide divergence in standards of living  Detailed poverty maps cannot be generated from household survey data alone.  If one tries to use survey data to measure poverty in each district or region, such estimates would be based on just a few observations, and would as such be imprecise.  One solution is to use population census data.  Census data are more available for all households and can provide reliable estimates at highly disaggregated levels, such as small municipalities, towns and villages.  Census do not contain the income or consumption information necessary to yield reliable indicators of welfare or standard of living, such as poverty and inequality measures.  7.2Methodology  One approach involves estimations of measures of poverty based on the access and quality of service. One such measure is the Living Conditions Index, (LCI). This index:  Summarizes access and quality of household source of water  Source of drinking water  Type of toilet facility  The main method of garbage collection.  The extent of crowding in the household (number of people divided by the number of bedrooms in the dwelling).  This approach involves classifying responses into Level 1 ( high quality) through Level 5 ( low quality).  Then assign a number of points to each level, say, 100,75,50,25, and 0 to the respective level.  Let us specify h000=y, to denote the relevant question number in the census questionnaire, where y denotes the code for the answer; e.g: water supply: level 1=if h17=1/h17=4; level 2= if h17=3/ h17=5; level 3=if h17=6/h17=7; level4= if h17=2; level 5 =if h17=8/h17=9.  Crowding Index: level 1= one person to a bedroom, level 2= 1 or 2 persons, Level 3 = 2 or 3 persons, Level 4 = 3 or 4 persons, Level 5= 4 persons or more.  For each household in the census, the value of LCI is constructed as the simple sum of points across the six variables.  The lower the sum, the poorer the household.  The house-specific index is then averaged by enumeration district, villages or region to yield a picture of the relative quality of service by geographical location.  Another measure is the Enumeration District Marginality Index (E  DMI) Variables included are:  Proportion of adults in the district/ county who have either had no education at all or did not complete primary schooling.  Proportion of adults ( 15 years plus) in the primary sector.  Proportion of children (6-14 years) who do not attend school full time.  Proportion of dwellings without piped-water.  Proportion of dwellings without W.C. linked to sewer.  Proportion of dwellings without electricity supply.  Proportion of dwellings who do not have garbage collection service for refuse disposal.  Average number of family members per bedroom.  After constructing these variables at the district/county level, the EDMI is constructed using the method of “principal component”, a statistical technique for forming new variables which are linear combination of the original variables.  STATA is a useful software  The new variables are referred to as the principal components. The first principal component accounts for the maximum variance in the data, the second principal component accounts for the maximum variance that has not been accounted for by the first principal component, and so on.  The EDMI is the first principal component which is the weighed sum of the variables considered. High values of the EDMI denote more marginal ED.  Examples of the application of both measures to Guyana

19 Poverty score Based on LC11 Poverty score based on EDMI Rural3410.333 Urban426-0.782 Based on LCI Rank (poorest on top less poor at bottom)Based on EDMI Region 81621Region 12.125 Region91842Region 92.049 Region 12073Region 81.982 Region 72594Region 71.023 Region 22785Region 20.583 Region 33526Region 50.303 Region 53557Region 30.234 Region 103648Region 60.188 Region 63739Region 4-0.137

20  7.3Combining Household Survey and Census Data.  An alternative approach is to combine survey data with census data to create more detailed poverty maps.  The basic idea is to use more detailed survey data to construct household or individual level indicators of welfare as a function of variables that are common to both survey and census data.. In(y ί )X 1 ί β+U ί ………………….(1)  The second step is to use estimates from equation (1) along with census data on the X i variables, to get predicted values of Y i for every household in the country.  These predicted values can then be used to measure poverty to a more disaggregated level.  Total poverty gap (TPG) in each district/ county can be estimated as TPG i =P 1i x Z i x N i ……………(2)  Where P 1i is poverty gap in location i, Z i is poverty line in location i, N i is total population in location i.  The share (W i ) of the total poverty gap of location i among k locations within a county is calculated as:  ∑TPG i-i k W i = TPG i.................................(3)  Inequality measures:  Useful to examine the relation between poverty and inequality.  Correlation estimation between FTG poverty indices and inequality indices:  May be positive or negative in survey data.  More likely to be negative in census data. This is because being a larger population than sample data, the larger the proportion of the population below the poverty line, the less scope there is for variance in the per capita consumption measure, and therefore the less inequality likely to be.  7.4Exercises  1. Identify questions from National Census Questionnaire to construct the following variables:  EDMI VARIABLES  -Proportion of households in the district who do not have electricity supply (H08-H09)  -Proportion of household who do not have piped water supply (H07)  -Proportion of households who do not have W.C. toilet system (H10)  -Proportion of households who do not have basic durable goods (Q1-Q8)  -Proportion of adults (15 years and above) who have either no education at all or did not complete primary education (P20)  -Proportion of adults who work in agriculture sector (P22, A01-A13)  -Proportion of adults who work in the informal sector (P22)  -proportion of children (6-14 years) who do not attend school full time (P19)  -Proportion of adults who were unemployed in the past 7 days (P21)  -Proportion of adults who are paid unskilled worker (P24)  -Proportion of households with child death in the past 12 months (P34-P37)

21  -Proportion of dwellings built with mud/stick/reed/bamboo/thatch/mat/grass ( H04-H06)  -Average number of household members per bedroom (H03)  LCI VARIABLES  -Number and quality of rooms the household occupy (H03-H06)  -Main source of water supply : L1 Pipe or pump indoors;L2 Pipe or pump outdoors/Public tap; L3 Close well or protected spring;L4 Open well;L5 River/Lake/Spring/Vendors (H07)  -Mai n source of fuel used for lighting/cooking : L1 Electricity own generator, L2 Electricity power supply, L3 Gas/Kerosine, L4 Palm oil lamp/charcoal, L5 wood (H08-H09)  -Type of human waste disposal system used by household: L1Flush toilet for household alone, L2 Flush toilet shared with other households, L3 Covered pit latrine, L4 Open pit latrine, L5 Bush/Beach (H10)  -Distance from nearest facilities (H11-H13): L1 Less than 20 mins, L2 20-39 mins, L3 40-59 mins, L4 60-79 mins, L5 80 mins and more (H11-H13)  -Construction materials of housing unit (H04-H06):  Outer walls—L1 cement blocks, L2 Mud blocks, L3 zinc and iron, L4 mud and sticks, L5 bamboo/reed/grass/mat  Roof---L1 concrete/tiles, L2 Asbestos, L3 Zinc, L4 Tapaulin, L5 Bamboo/thatch.  Floor---L1 Tiles, L2 cement, L3 mud, L4 wood, L5 others. 


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