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Updating Poverty Estimates at Frequent Intervals in the Absence of Consumption Data : Methods and Illustration with Reference to a Middle-Income Country

AGRICULTURAL WAGES CELL PHONE CELL PHONES CHANGES IN POVERTY COMMODITY CONFIDENCE INTERVALS CONSUMER PRICE INDEX CONSUMPTION DATA DATA AVAILABILITY DECLINE IN POVERTY DEPENDENT VARIABLE DEVELOPING COUNTRIES DEVELOPMENT ECONOMICS DEVELOPMENT POLICY DEVELOPMENT RESEARCH DIMENSIONS OF POVERTY DRINKING WATER DUMMY VARIABLES ECONOMETRIC ISSUES ECONOMETRICS ECONOMIC ACTIVITIES ECONOMIC LITERATURE ECONOMIC REFORMS ECONOMIC STUDIES ECONOMICS ECONOMICS LETTERS ECONOMICS LITERATURE ELDERLY PEOPLE EMPIRICAL APPLICATION EMPIRICAL EVIDENCE EMPIRICAL RESULTS EMPLOYMENT INCOME EMPLOYMENT STATUS ENUMERATION EQUATIONS ERROR TERMS ESTIMATED COEFFICIENTS ESTIMATES OF POVERTY ESTIMATION RESULTS ESTIMATION TECHNIQUES EXPLANATORY VARIABLES EXTREME POVERTY FEMALE HOUSEHOLD MEMBERS FINANCIAL RESOURCES FOOD BASKET FOOD CONSUMPTION FUNCTIONAL FORM GLOBAL POVERTY GOVERNMENT AGENCIES GROWTH RATES HEADCOUNT POVERTY HOUSEHOLD CONSUMPTION HOUSEHOLD DATA HOUSEHOLD DEMOGRAPHICS HOUSEHOLD HEAD HOUSEHOLD HEADS HOUSEHOLD SIZE HOUSEHOLD SURVEY HOUSEHOLD SURVEYS HOUSEHOLD WELFARE HOUSING HUMAN RESOURCES IMPUTATION IMPUTATION METHOD IMPUTATION METHODS IMPUTATIONS INCOME INCOME GROUPS INEQUALITY LABOR FORCE LABOR MARKET LINEAR REGRESSION MEASUREMENT ERRORS MEASURING POVERTY MISSING DATA MISSING VALUES MODEL SPECIFICATIONS MULTIPLE IMPUTATION MULTIPLE IMPUTATIONS NET CHANGES NORMAL DISTRIBUTION NORMAL DISTRIBUTIONS OPEN ACCESS PER CAPITA CONSUMPTION PER CAPITA INCOME PHONE POINT DECLINE POINT ESTIMATES POLICY INTERVENTIONS POLICY MAKERS POLICY RESEARCH POOR POOR HOUSEHOLDS POPULATION GROUP POVERTY ANALYSIS POVERTY ASSESSMENT POVERTY CHANGE POVERTY COMPARISONS POVERTY DATA POVERTY DEBATE POVERTY DECLINE POVERTY DYNAMICS POVERTY ERADICATION POVERTY ESTIMATES POVERTY LINE POVERTY LINES POVERTY MEASUREMENT POVERTY RATE POVERTY RATES POVERTY REDUCTION POVERTY REDUCTION STRATEGY POVERTY STATUS PRECISION PREDICTION PREDICTIONS PROBABILITY RADIO RAPID GROWTH RESEARCH METHODS RESULT RURAL RURAL AREAS SAMPLE SIZE SAMPLE SURVEYS SAMPLING FRAMES SATELLITE SCHOOLING SOFTWARE PACKAGES STANDARD DEVIATION STANDARD DEVIATIONS STANDARD ERRORS STANDARDIZATION STATA STATISTICAL ANALYSIS STATISTICAL INFERENCE STATISTICAL THEORY STATISTICIANS TARGETS TECHNICAL EXPERTISE TELEVISION TIME PERIOD TIME PERIODS TIME SERIES UNEMPLOYMENT URBAN AREAS USER USES VALIDITY WAGE DIFFERENTIALS
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World Bank Group, Washington, DC
Middle East and North Africa | Jordan
2014-10-06T20:36:13Z | 2014-10-06T20:36:13Z | 2014-09

Obtaining consistent estimates on poverty over time as well as monitoring poverty trends on a timely basis is a priority concern for policy makers. However, these objectives are not readily achieved in practice when household consumption data are neither frequently collected, nor constructed using consistent and transparent criteria. This paper develops a formal framework for survey-to-survey poverty imputation in an attempt to overcome these obstacles, and to elevate the discussion of these methods beyond the largely ad-hoc efforts in the existing literature. The framework introduced here imposes few restrictive assumptions, works with simple variance formulas, provides guidance on the selection of control variables for model building, and can be generally applied to imputation either from one survey to another survey with the same design, or to another survey with a different design. Empirical results analyzing the Household Expenditure and Income Survey and the Unemployment and Employment Survey in Jordan are quite encouraging, with imputation-based poverty estimates closely tracking the direct estimates of poverty.

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