Index
life expectancy, as indicator of welfare, 34t lifecycle hypothesis for income and consumption expenditure, 24f Lithuania, 332t, 333 Litvack, Jennie, 56 living standards. See standard of living Living Standards Measurement Surveys (LSMSs), 18–20 Lloyd George, David, xvii Loefgren, H., 269 logistic regression, 287–89, 287f, 289t Lorenz curve inequality, measuring, 104–6, 105f, 391 poverty indexes, 77, 88 tax incidence analysis, 296, 298f Lustig, Nora, 115–16, 169
412
Madagascar, 73t, 167t, 168, 310t Malawi, 124t, 201n2, 310t, 321–22, 321t Malaysia, 90, 91t, 206 Mali, 201n2, 308 malnutrition as indicator of welfare, 33. See also food and nutrition Mangahas, Mahar, 60 mapping poverty, 136–40, 139–40t MARS models (multiple-adaptive regression splines), 156 matching comparisons, 260–61 MDGs (Millennium Development Goals), 181, 182, 194, 251, 252–53t mean log deviation measure of inequality, 106 measurement error, 87–89, 89f, 241, 279–80, 386–87 measuring inequality. See inequality measuring institutional effectiveness, 5–6 measuring poverty aggregate welfare and its distribution. See poverty indexes exercises, 369–76 household survey data. See household survey data international poverty comparisons and, 183–84 learning objectives, 10 reasons for, 3–6 review questions, 17 robustness of. See robustness of poverty indexes steps required in, 10–11. See also indicators of welfare, defining; poverty indexes; poverty lines time, changes over. See time, measuring poverty over
time taken to exit, 78–80, 79f vulnerability, measuring, 236–43, 237–38f, 240t, 398–401 Metcalf, Gilbert, 311 Mexico, 78t Michigan Panel Survey on Income Dynamics (PSID), 207, 211 microfinance, 264–66b Middle East and North Africa, 49t, 185t. See also specific countries Millennium Development Goals (MDGs), 181, 182, 194, 251, 252–53t Minoiu, Carnelia, 196, 199 Minten, Bart, 148 MKUKUTA (Tanzanian poverty reduction plan), 175–78, 176t, 177f model error, 138 Moldova, 166, 167t, 331, 332t monitoring and evaluation systems, 249–72 cost-benefit and cost-effectiveness analysis, 251 goals, identifying, 251, 252–53t impact evaluations. See impact evaluations indicators, selecting, 251, 254 learning objectives, 250 measurement of poverty, reasons for, 5 process evaluation, 251 review questions, 255–56, 267, 270 targets, setting, 251, 254–55 Mookherjee, Dilip, 172 Morduch, Jonathan, 78, 242, 265b mortality rates, as indicator of welfare, 34t Moulin, Sylvie, 258 Mozambique, 201n2 multicolinearity, 283 multiple-adaptive regression splines (MARS models), 156 national accounts and HBS data, discrepancies between, 191–94, 193t national or regional level characteristics associated with poverty, 147–48 Nead, Kimberly, 307 Nepal, 201n2 the never poor, 214 Nicaragua, 197, 198t, 201n4 Niger, 201n2 Nigeria, 46b, 78t, 167t nonparametric regression, 156 nonresponse bias, 12 adjusting for, 329–30, 330t, 331f international poverty comparisons, 191–92, 193t