A Simple Poverty Scorecard for the Philippines

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For the Philippines, Haslett and Jones’ 21 indicators are:• Demographics:— Household size (and its mean-adjusted square)— Proportion of household members who are children of the head— Proportion of household members who are 61-years-old or older• Proportion of household members 10-years-old or older with only:• Elementary education• High-school education• College education• Education level for households in ARMM• Residence:— Type of house— Type of roof— Type of wall— Floor area• Presence of domestic help• Urban/rural area by region• Municipality characteristics (percentages):— Dwellings built in 1996–2000— Heads who are Muslim— Residents 5-years-old or older who speak English— Households who use electricity of LPG for cooking— Households who have a refrigerator— Households who have a telephone— Persons who work for a private household— Persons employed in retail tradeWhile Haslett and Jones report standard errors for estimated poverty rates, theydo not report standard-error formula nor enough information to enable the derivation ofa standard-error formula, so the precision of their poverty mapping cannot be comparedto that of the poverty scoring here.11
3.3 Gwatkin et al.Gwatkin et al. (2000) apply Principal Components Analysis to make a “wealthindex” from simple, low-cost indicators available for the 62,932 households in thePhilippines’ 1998 DHS. This same approach is used by USAID in 56 countries withDemographic and Health Surveys (Rutstein and Johnson, 2004).Gwatkin et al.’s PCA-based index is close kin to the poverty scorecard hereexcept that, because the DHS does not measure expenditure, the index can only beassumed to be correlated with socio-economic status. 13 Examples of the PCA-indexapproach are Stifel and Christiaensen (2007), Zeller et al. (2006), Sahn and Stifle (2003and 2000), and Filmer and Pritchett (2001).A strength of PCA-based indices is that, because they do not require incomedata, they can be applied to a wide array of “light” surveys such as censuses,Demographic and Health Surveys, Welfare Monitoring Surveys, and Core WelfareIndicator Questionnaires. Of course, the flip side is that, without expenditure data, theycan only rank households and thus provide only relative—not absolute—measures ofpoverty. Thus, while PCA-based indices can be used for targeting, they cannot estimatehouseholds’ poverty likelihoods or groups’ poverty rates.13Still, because their indicators are so similar, the PCA-based index and income-basedpoverty scorecards probably pick up the same underlying construct (such as “permanentincome”, see Bollen, Glanville, and Stecklov, 2007) and rank households much the same.Filmer and Pritchett (2001) and Montgomery et al. (2000) test how well PCA-basedindices predict expenditure.12
Page 1 and 2: A Simple Poverty Scorecard for the
Page 3 and 4: comparable across organizations nor
Page 5 and 6: Poverty scoring can also be used fo
Page 7 and 8: points or less for estimates of cha
Page 9 and 10: counted as if it had only one perso
Page 11 and 12: derived from the 2000 FIES by the N
Page 13 and 14: Given this, the USD1.25/day 2005 PP
Page 15 and 16: Reyes builds a scorecard using the
Page 17: that quickly show how estimated pov
Page 21 and 22: includes income, the PCA index cann
Page 23 and 24: One of these one-indicator scorecar
Page 25 and 26: The scorecard in Figure 1 is ready
Page 27 and 28: If not determined by other factors,
Page 29 and 30: 6.1 Calibrating scores with poverty
Page 31 and 32: 6.2 Accuracy of estimates of househ
Page 33 and 34: The 90-percent confidence interval
Page 35 and 36: 7. Estimates of a group’s poverty
Page 37 and 38: To derive a sample-size formula (or
Page 39 and 40: 21.64n = 0. 55 ⋅⎛ ⎞⎜ ⎟
Page 41 and 42: 8. Estimates of changes in group po
Page 43 and 44: 2002 in the Philippines is the diff
Page 45 and 46: from 0.63 to 0.77 (Figure 10), sugg
Page 47 and 48: To illustrate the use of (8), suppo
Page 49 and 50: the four possible targeting outcome
Page 51 and 52: As an alternative to assigning bene
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Page 55 and 56: ReferencesAdams, N.M.; and D.J. Han
Page 57 and 58: Hentschel, Jesko; Lanjouw, Jean Ols
Page 59 and 60: Onwujekwe, Obinna; Hanson, Kara; an
Page 61 and 62: Stillwell, William G.; Barron, F. H
Page 63 and 64: Figure 1: A simple poverty scorecar
Page 65 and 66: Figure 3: Poverty indicators by unc
Page 67 and 68: Figure 3 (cont.): Poverty indicator
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National Poverty Line Tables(and Ta
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Figure 5 (National poverty line): D
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Figure 7 (National poverty line): B
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Figure 9 (National poverty line): D
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Figure 11 (All poverty lines): Poss
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Figure 13 (National poverty line):
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Figure 4 (National food poverty lin
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Figure 7 (National food poverty lin
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Figure 12 (National food poverty li
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USAID “Extreme” Poverty Line Ta
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Figure 5 (USAID “Extreme” pover
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Figure 9 (USAID “Extreme” pover
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Figure 13 (USAID “Extreme” pove
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Figure 4 (USD1.25/day 2005 PPP line
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Figure 12 (USD1.25/day 2005 PPP lin
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USD2.50/Day 2005 PPP Poverty Line T
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USD5.00/Day 2005 PPP Poverty Line T
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National Poverty Line Tablesfor 200
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Figure 9 (National line): Differenc
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Figure 13 (National line): For a gi
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Figure 7 (Food line): Bootstrapped
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Figure 12 (Food line): Households b
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USAID “Extreme” Poverty Line Ta
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Figure 9 (USAID “extreme” line)
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Figure 13 (USAID “extreme” line
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USD2.50/day 2005 PPP Poverty Line T
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USD5.00/day 2005 PPP Poverty Line T
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Poverty Lines and Poverty Rates,by
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Figure A2: All-urban Philippines an
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Figure A4: Agusan del Norte, povert
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Figure A6: Aklan, poverty lines and
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Figure A8: Antique, poverty lines a
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Figure A10: Bataan, poverty lines a
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Figure A12: Batangas, poverty lines
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Figure A14: Bohol, poverty lines an
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Figure A16: Bulacan, poverty lines
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Figure A18: Camarines Norte, povert
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Figure A20: Camiguin, poverty lines
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Figure A22: Catanduanes, poverty li
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Figure A24: Cebu, poverty lines and
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Figure A26: Davao del Sur, poverty
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Figure A28: Eastern Samar, poverty
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Figure A30: Ilocos Norte, poverty l
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Figure A32: Iloilo, poverty lines a
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Figure A34: Kalinga, poverty lines
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Figure A36: Laguna, poverty lines a
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Figure A38: Lanao del Sur, poverty
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Figure A40: Maguindanao, poverty li
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Figure A42: Marinduque, poverty lin
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Figure A44: Misamis Occidental, pov
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Figure A46: Mountain Province, pove
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Figure A48: Negros Oriental, povert
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Figure A50: Northern Samar, poverty
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Figure A52: Nueva Vizcaya, poverty
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Figure A54: Oriental Mindoro, pover
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Figure A56: Pampanga, poverty lines
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Figure A58: Quezon, poverty lines a
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Figure A60: Rizal, poverty lines an
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Figure A62: Western Samar, poverty
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Figure A64: Sorsogon, poverty lines
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Figure A66: Southern Leyte, poverty
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Figure A68: Sulu, poverty lines and
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Figure A70: Surigao del Sur, povert
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Figure A72: Tawi-tawi, poverty line
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Figure A74: Zamboanga del Norte, po
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Figure A76: 2nd District, poverty l
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Figure A78: 4th District, poverty l
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Figure A80: Biliran, poverty lines
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Figure A82: Saranggani, poverty lin
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Figure A84: Compostela Valley, pove
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Figure A86: Shariff Kabunsuan, pove
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Figure A88: Isabela City, poverty l
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A Simple Poverty Scorecard for the Philippines

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