A Simple Poverty Scorecard for the Philippines

More documents

Recommendations

Info

A Simple Poverty Scorecard for the Philippines1. IntroductionThis paper presents an easy-to-use poverty scorecard that pro-poor programs inthe Philippines can use to estimate the likelihood that a household has income below agiven poverty line, to monitor groups’ poverty rates at a point in time, to track changesin groups’ poverty rates between two points in time, and to target services tohouseholds.The direct approach to poverty measurement via surveys is difficult and costly,asking households about a lengthy list of income categories. In contrast, the indirectapproach via poverty scoring is simple, quick, and inexpensive. It uses ten verifiableindicators (such as “What is the house’s roof made out of?” or “What type of toiletfacility does the family have?”) to get a score that is highly correlated with povertystatus as measured by the exhaustive survey.The poverty scorecard here differs from “proxy means tests” (Coady, Grosh, andHoddinott, 2002) in that it is tailored to the capabilities and purposes not of nationalgovernments but rather of local, pro-poor organizations. The feasible povertymeasurementoptions for these organizations are typically subjective and relative (suchas participatory wealth ranking by skilled field workers) or blunt (such as rules basedon land-ownership or housing quality). Results from these approaches are not1
comparable across organizations nor across countries, they may be costly, and theiraccuracy and precision are unknown.If an organization wants to know what share of its participants are below apoverty line (say, USD1.25/day at 2005 purchase-power parity for the MillenniumDevelopment Goals, or the poorest half of people below the national poverty line asrequired of USAID microenterprise partners), or if it wants to measure movementacross a poverty line (for example, to report to the Microcredit Summit Campaign),then it needs an income-based, objective tool with known accuracy. While incomesurveys are costly even for governments, many small, local organizations can implementan inexpensive scorecard that can serve for monitoring, management, and targeting.The statistical approach here aims to be understood by non-specialists. After all,if managers are to adopt poverty scoring on their own and apply it to inform theirdecisions, they must first trust that it works. Transparency and simplicity build trust.Getting “buy-in” matters; proxy means tests and regressions on the “determinants ofpoverty” have been around for three decades, but they are rarely used to informdecisions, not because they do not work, but because they are presented (when they arepresented at all) as tables of regression coefficients incomprehensible to lay people (withcryptic indicator names such as “HHSIZE_2”, negative values, many decimal places, andstandard errors). Thanks to the predictive-modeling phenomenon known as the “flatmax”, simple scorecards are about accurate as complex ones.2
Page 1: A Simple Poverty Scorecard for the
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 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
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
Page 89 and 90:
Figure 5 (USAID “Extreme” pover
Page 91 and 92:
Figure 9 (USAID “Extreme” pover
Page 93 and 94:
Figure 13 (USAID “Extreme” pove
Page 95 and 96:
Figure 4 (USD1.25/day 2005 PPP line
Page 97 and 98:
Page 99 and 100:
Figure 12 (USD1.25/day 2005 PPP lin
Page 101 and 102:
USD2.50/Day 2005 PPP Poverty Line T
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
USD5.00/Day 2005 PPP Poverty Line T
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
National Poverty Line Tablesfor 200
Page 131 and 132:
Figure 9 (National line): Differenc
Page 133 and 134:
Figure 13 (National line): For a gi
Page 135 and 136:
Figure 7 (Food line): Bootstrapped
Page 137 and 138:
Figure 12 (Food line): Households b
Page 139 and 140:
USAID “Extreme” Poverty Line Ta
Page 141 and 142:
Figure 9 (USAID “extreme” line)
Page 143 and 144:
Figure 13 (USAID “extreme” line
Page 145 and 146:
Page 147 and 148:
Page 149 and 150:
USD2.50/day 2005 PPP Poverty Line T
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Page 159 and 160:
USD5.00/day 2005 PPP Poverty Line T
Page 161 and 162:
Page 163 and 164:
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
Poverty Lines and Poverty Rates,by
Page 171 and 172:
Figure A2: All-urban Philippines an
Page 173 and 174:
Figure A4: Agusan del Norte, povert
Page 175 and 176:
Figure A6: Aklan, poverty lines and
Page 177 and 178:
Figure A8: Antique, poverty lines a
Page 179 and 180:
Figure A10: Bataan, poverty lines a
Page 181 and 182:
Figure A12: Batangas, poverty lines
Page 183 and 184:
Figure A14: Bohol, poverty lines an
Page 185 and 186:
Figure A16: Bulacan, poverty lines
Page 187 and 188:
Figure A18: Camarines Norte, povert
Page 189 and 190:
Figure A20: Camiguin, poverty lines
Page 191 and 192:
Figure A22: Catanduanes, poverty li
Page 193 and 194:
Figure A24: Cebu, poverty lines and
Page 195 and 196:
Figure A26: Davao del Sur, poverty
Page 197 and 198:
Figure A28: Eastern Samar, poverty
Page 199 and 200:
Figure A30: Ilocos Norte, poverty l
Page 201 and 202:
Figure A32: Iloilo, poverty lines a
Page 203 and 204:
Figure A34: Kalinga, poverty lines
Page 205 and 206:
Figure A36: Laguna, poverty lines a
Page 207 and 208:
Figure A38: Lanao del Sur, poverty
Page 209 and 210:
Figure A40: Maguindanao, poverty li
Page 211 and 212:
Figure A42: Marinduque, poverty lin
Page 213 and 214:
Figure A44: Misamis Occidental, pov
Page 215 and 216:
Figure A46: Mountain Province, pove
Page 217 and 218:
Figure A48: Negros Oriental, povert
Page 219 and 220:
Figure A50: Northern Samar, poverty
Page 221 and 222:
Figure A52: Nueva Vizcaya, poverty
Page 223 and 224:
Figure A54: Oriental Mindoro, pover
Page 225 and 226:
Figure A56: Pampanga, poverty lines
Page 227 and 228:
Figure A58: Quezon, poverty lines a
Page 229 and 230:
Figure A60: Rizal, poverty lines an
Page 231 and 232:
Figure A62: Western Samar, poverty
Page 233 and 234:
Figure A64: Sorsogon, poverty lines
Page 235 and 236:
Figure A66: Southern Leyte, poverty
Page 237 and 238:
Figure A68: Sulu, poverty lines and
Page 239 and 240:
Figure A70: Surigao del Sur, povert
Page 241 and 242:
Figure A72: Tawi-tawi, poverty line
Page 243 and 244:
Figure A74: Zamboanga del Norte, po
Page 245 and 246:
Figure A76: 2nd District, poverty l
Page 247 and 248:
Figure A78: 4th District, poverty l
Page 249 and 250:
Figure A80: Biliran, poverty lines
Page 251 and 252:
Figure A82: Saranggani, poverty lin
Page 253 and 254:
Figure A84: Compostela Valley, pove
Page 255 and 256:
Figure A86: Shariff Kabunsuan, pove
Page 257 and 258:
Figure A88: Isabela City, poverty l
show all

A Simple Poverty Scorecard for the Philippines

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?