Estimating Quarterly Poverty Rates Using Labor Force Surveys : A Primer
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World Bank, Washington, DC
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The paper shows how Labor Force Surveys
can be used effectively to estimate poverty rates using
Household Expenditure Surveys and cross-survey imputation
methods. With only two rounds of Household Expenditure
Survey data for Morocco (2001 and 2007), the paper estimates
quarterly poverty rates for the period 2001-2010 by imputing
household expenditures into the Labor Force Surveys. The
results are encouraging. The methodology is able to
accurately reproduce official poverty statistics by
combining current Labor Force Surveys with previous period
Household Expenditure Surveys, and vice versa. Although the
focus is on head-count poverty, the method can be applied to
any welfare indicator that is a function of household income
or expenditure, such as the poverty gap or the Gini index of
inequality. The newly produced time-series of poverty rates
can help researchers and policy makers to: (a) study the
determinants of poverty reduction or use poverty as an
explanatory factor in cross-section and panel models; (b)
forecast poverty rates based on a time-series model fitted
to the data; and (c) explore the linkages between labor
market conditions and poverty and simulate the effects of
policy reforms or economic shocks. This is a promising
research agenda that can expand significantly the tool-kit
of the welfare economist.
Palabras clave
ACCESS TO SERVICES, AGRICULTURAL OUTPUT, AGRICULTURAL PERFORMANCE, AGRICULTURAL PRODUCTION, AGRICULTURAL SECTOR, AVERAGE GROWTH, AVERAGE INCOME, CAP, CLEAN DRINKING WATER, CONFLICT, CONSUMPTION DATA, CONSUMPTION GROWTH, CONSUMPTION POVERTY, DATA SETS, DECLINE IN POVERTY, DEPENDENT VARIABLE, DESCRIPTIVE STATISTICS, DETERMINANTS OF POVERTY, DEVELOPED COUNTRIES, DEVELOPMENT POLICY, DISTRIBUTION FUNCTION, DYNAMIC PANEL, ECONOMIC ACTIVITIES, ECONOMIC GROWTH, ECONOMIC SHOCKS, ECONOMICS, EMPIRICAL MODEL, EMPIRICAL RESULTS, EMPIRICAL SECTION, EMPIRICAL WORK, EMPLOYMENT IN AGRICULTURE, ERROR TERM, ERROR TERMS, ESTIMATES OF POVERTY, EXPLANATORY VARIABLES, FINANCIAL CRISES, FINANCIAL CRISIS, FINANCIAL SECTOR, FIXED EFFECTS, GINI INDEX, GLOBAL ECONOMY, GROWTH RATE, GROWTH RATES, HEADCOUNT POVERTY, HOUSEHOLD CONSUMPTION, HOUSEHOLD EXPENDITURE SURVEYS, HOUSEHOLD INCOME, HOUSEHOLD INCOMES, HOUSEHOLD SIZE, HOUSEHOLD SURVEY, HOUSEHOLD SURVEYS, HOUSING, HUMAN DEVELOPMENT, IMPACT ON POVERTY, INCOME DATA, INCOME DISTRIBUTION, INCOME POVERTY, INDEPENDENT VARIABLE, INDEPENDENT VARIABLES, INEQUALITY, LABOR FORCE, LABOR MARKET, LIVING STANDARDS, MACROECONOMIC POLICIES, MACROECONOMIC SHOCKS, MARGINAL EFFECT, MEASUREMENT OF POVERTY, MEASURING POVERTY, MICRO DATA, NATIONAL ACCOUNTS, 0 HYPOTHESIS, NUTRITION, PER CAPITA EXPENDITURE, POLICY MAKERS, POLICY REFORMS, POLICY RESEARCH, POOR, POVERTY ASSESSMENTS, POVERTY DATA, POVERTY DEBATE, POVERTY ESTIMATES, POVERTY GAP, POVERTY LEVELS, POVERTY LINE, POVERTY MAPPING, POVERTY RATE, POVERTY RATES, POVERTY REDUCTION, POVERTY SERIES, PRIMARY EDUCATION, PRO-POOR, PROGRAMS, PUBLIC POLICIES, PUBLIC SECTOR, RANDOM VARIABLES, REDUCING POVERTY, REDUCTION IN POVERTY, REGIONAL DUMMY, REGIONAL GROUP, REGIONAL LEVEL, REGIONAL PERSPECTIVE, REGIONAL POVERTY, REGRESSION ANALYSIS, REMOTE AREAS, RURAL, RURAL AREAS, RURAL DIVIDE, RURAL GAP, RURAL POVERTY, RURAL STANDARDS, SAMPLE SIZE, SELF-EMPLOYMENT, SIGNIFICANT IMPACT, STABILIZATION POLICIES, SUB-REGION, SUB-REGIONS, SUBREGIONS, UNEMPLOYMENT, URBAN AREAS, URBAN POVERTY, WELFARE INDICATOR, WELFARE MEASURE, WELFARE MEASURES