A Simple Poverty Scorecard for the Philippines

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interval of +/–0.44 percentage points (Figure 9). 22 Plugging these into the directmeasurementsample-size formula (1) above gives not n = 16,384 but rathern=⎛ 1.64 ⎞⎜ ⎟⎝ 0.0044 ⎠2⋅ 0.313 ⋅ ( 1 − 0.313)= 29,874. The ratio of the sample size for scoring(derived empirically) to the sample size for direct measurement (derived from theory) is16,384 ÷ 29,874 = 0.55.Applying the same method to n = 8,192 (confidence interval of +/–0.6221.64percentage points) gives n =⎛ ⎞⎜ ⎟ ⋅ 0.313 ⋅ ( 1 − 0.313)= 15,046. This time, the⎝ 0.0062 ⎠ratio of the sample size using scoring to the sample size using direct measurement is8,192 ÷ 15,046 = 0.54. This ratio for n = 8,192 is close to that for n = 16,384. Indeed,applying this same procedure for all n ≥ 256 in Figure 9 gives ratios that average to0.55.This approach can be used to define a sample-size formula for the povertyscorecard applied to the population in the validation sample:n2z= α ⋅⎛ ⎞⎜ ⎟ ⋅ pˆ⋅ ( 1 − pˆ), (2)⎝ c ⎠where α = 0.55 and z, c, and pˆ are defined as in (1) above. It is this α that appears inFigure 8 as “α for sample size”.To illustrate the use of (2), suppose c = 0.0359 (confidence interval of +/–3.59percentage points) and z = 1.64 (90-percent confidence). Then (2) gives22Due to rounding, Figure 9 displays 0.4, not 0.44.31
21.64n = 0. 55 ⋅⎛ ⎞⎜ ⎟ ⋅ 0.313 ⋅ ( 1 − 0.313)= 247, which is close to the sample size of 256⎝ 0.0359 ⎠for these parameters in Figure 9.When the sample-size factor α is less than 1.0, it means that the scorecard ismore precise than direct measurement. This occurs for all of eight poverty lines inFigure 8.Of course, the sample-size formulas here are specific to the Philippines, itspoverty lines, its poverty rates, and this scorecard. The derivation method, however, isvalid for any poverty scorecard following the approach in this paper.In practice after July 2004 (the end date of the 2004 APIS), an organizationwould select a poverty line (say, the national line), select a desired confidence level(say, 90 percent, or z = 1.64), select a desired confidence interval (say, +/–2.0percentage points, or c = 0.02), make an assumption about pˆ (perhaps based on aprevious measurement such as the 31.4 percent national average for the 2004 APIS inFigure 2), look up α (here, 0.55 for the national line), assume that the scorecard willstill work in the future and/or for non-nationally representative sub-groups, 23 and thencompute the required sample size. In this illustration,21.64n = 0. 55 ⋅⎛ ⎞⎜ ⎟ 0.314 ⋅ ( 1 − 0.314)= 797.⎝ 0.02 ⎠23The next sub-section discusses accuracy when applied out-of-sample and out-of-timeto the 2002 APIS. In general, performance after the 2004 APIS will probably resemblethat in the 2004 APIS, with some deterioration as time passes.32
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 and 18: that quickly show how estimated pov
Page 19 and 20: 3.3 Gwatkin et al.Gwatkin et al. (2
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: To derive a sample-size formula (or
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
Page 53 and 54: at a point in time is always less t
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
Page 69 and 70: National Poverty Line Tables(and Ta
Page 71 and 72: Figure 5 (National poverty line): D
Page 73 and 74: Figure 7 (National poverty line): B
Page 75 and 76: Figure 9 (National poverty line): D
Page 77 and 78: Figure 11 (All poverty lines): Poss
Page 79 and 80: Figure 13 (National poverty line):
Page 81 and 82: Figure 4 (National food poverty lin
Page 83 and 84: Figure 7 (National food poverty lin
Page 85 and 86: Figure 12 (National food poverty li
Page 87 and 88: 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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