Household Income and Expenditure Survey;small number of household;metropolitan area;law of large number;poverty does;inefficient allocation of resource;household-level ...  See More + per capita consumption;consumption level per household;choice of poverty line;cost of living;small area estimation;smaller towns;cumulative distribution function;spatial price index;difference in poverty;poverty mapping methodology;national poverty line;access network;access to network;Access to Electricity;per capita expenditure;regional price index;large metropolitan areas;estimates of poverty;measure of poverty;incidence of poverty;inequality within country;monte carlo simulation;medium sized cities;Population and Development;large urban centers;allocation of capital;public health service;terms of trade;distribution-sensitive poverty measure;coefficient on population;extent of poverty;infant mortality rate;constant poverty line;standard of living;development research group;height for age;weight for age;index of inequality;Poverty & Inequality;access to water;health outcome indicators;urban poverty reduction;dimensions of poverty;local public good;access to sewerage;types of city;child health outcomes;small size cities;household survey data;distribution of poverty;poverty line one;high poverty line;census enumeration area;population census;rural area;urban poor;large town;robustness check;urban bias;income poverty;parameter estimate;poverty incidence;local inequality;child malnutrition;small cities;consumption poverty;inverse relationship;global poverty;living standard;anthropometric outcomes;estimation technique;equivalence scale;population share;poverty estimate;median poverty;piped water;slum dweller;medium towns;slum resident;urban inequality;relative income;slum area;price variation;Poverty measures;household level;small sample;richer countries;inequality measure;consumption pattern;consumption expenditure;consumption model;national currency;explanatory variable;Public Services;basic infrastructure;infrastructure service;preceding section;urban population;extreme poverty;connected household;children of ages;Exchange Rates;household expenditure;income share;between-group components;unequal inequality;poor community;empirical method;disturbance term;smaller share;poverty-reduction effort;socio-economic survey;garbage collection;electric heating;price difference;sewerage service;sewerage facilities;broad consensus;living condition;household weight;cluster-level effect;stunted child;malnourished child;regional coverage;urban child;simulation approach;Poverty Analysis;Child Mortality;Poverty Measurement;detail level;statistical technique;sample survey;estimation procedure;housing price;data availability;urban food;relative price;stochastic dominance;rural population;rural phenomenon;price regulation;poverty ranking;marketing board;urban growth;infant industry;open access;development policy;regression coefficient;standard error;negative relationship;urban activity;individual welfare;urbanized countries;demographic characteristic;public domain;future research;urban setting;transitory shock;measurement error;poverty drive;internationally comparable;size distribution;infrastructure access;missing data;urban slum;violent crime;international level;measured poverty;welfare indicator;census data;spatial correlation;disaggregated analysis;sanitation problem;substantial variation;service availability;large population;hedonic model;population size;coverage rate;sampling error;rural counterpart;empirical model;estimation method;household consumption;multiple dimension;family size;poverty profile;transfer resource;negative correlation;relative earnings;primary healthcare;aggregate inequality;economics research;fighting poverty;anecdotal evidence;  See Less -