Rapid Consumption Method and Poverty and Inequality Estimation in Somalia Revisited
This paper presents updated poverty and inequality estimates from the Somalia High Frequency Survey. This survey used the Rapid Consumption Method to collect consumption data quickly in an environment of high insecurity. Its poverty estimation, therefore, requires imputation of skipped consumption modules. Previous poverty estimates did not properly impute consumption, resulting in the imputation of negative total consumption values for some households. This paper uses the Two-Part Multiple Imputation method to address this issue. The assessment of module-level prediction performance demonstrates that the Two-Part Multiple Imputation handles this issue effectively. In addition, this paper adopts the newly updated 2011 purchasing power parities to convert the High Frequency Survey consumption data for global poverty measurement purposes. Lastly, this paper provides new inequality measures to address issues with the previous exercise. The paper finds that new poverty rates are slightly lower than those using the previous method while inequality is higher with the new method.
Main Authors: | , , |
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Format: | Working Paper biblioteca |
Language: | English |
Published: |
Washington, DC: World Bank
2022-03
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Subjects: | CONSUMPTION MEASUREMENT, TWO-PART MODELS, POVERTY AND INEQUALITY PREDICTION, POVERTY AND INEQUALITY MEASUREMENT, SURVEY METHODS, MULTIPLE IMPUTATION, MISSING DATA, HIGH-FREQUENCY DATA, RAPID CONSUMPTION METHOD, HIGH INSECURITY, UPDATED (PURCHASING POWER PARITIES (PPP), INEQUALITY MEASUREMENT, |
Online Access: | http://documents.worldbank.org/curated/en/099538303302234339/IDU0f3e6ea4209840041f5091ce02a420950f318 http://hdl.handle.net/10986/37583 |
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Summary: | This paper presents updated poverty
and inequality estimates from the Somalia High Frequency
Survey. This survey used the Rapid Consumption Method to
collect consumption data quickly in an environment of high
insecurity. Its poverty estimation, therefore, requires
imputation of skipped consumption modules. Previous poverty
estimates did not properly impute consumption, resulting in
the imputation of negative total consumption values for some
households. This paper uses the Two-Part Multiple
Imputation method to address this issue. The assessment of
module-level prediction performance demonstrates that the
Two-Part Multiple Imputation handles this issue effectively.
In addition, this paper adopts the newly updated 2011
purchasing power parities to convert the High Frequency
Survey consumption data for global poverty measurement
purposes. Lastly, this paper provides new inequality
measures to address issues with the previous exercise. The
paper finds that new poverty rates are slightly lower than
those using the previous method while inequality is higher
with the new method. |
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