Updating Poverty in Afghanistan Using the SWIFT-Plus Methodology
Close to half of the population of Afghanistan was living below the national poverty line prior to the regime change in August 2021, with no additional information on poverty collected in the country since the last official household survey in 2019/20. This paper fills this knowledge gap through survey-to-survey imputation using a SWIFT-plus methodology. The analysis trains a predictive model on data from the 2019/20 Expenditure and Labor Force survey and imputes poverty in the latest Afghanistan Welfare Monitoring Survey. The analysis accounts for seasonality in welfare patterns and implements several tests to assess the model’s predictive capacity. The results show that 48.3 percent of the Afghan population was poor as of April–June 2023, a relative decline of 4 percentage points compared to poverty levels observed over the same months in 2020. The reduction in poverty was concentrated among rural households, with a decline from 51 to 44 percent, while it stagnated in urban areas at around 58 percent. Although no poverty data exists since 2020, the evolution of self-reported welfare and food security makes it reasonable to conclude that poverty first increased during the immediate economic contraction following the regime change and has progressively declined since then.
| Main Authors: | , , , |
|---|---|
| Format: | Working Paper biblioteca |
| Language: | English English |
| Published: |
World Bank, Washington, DC
2023-11-29
|
| Subjects: | POVERTY MEASUREMENT, SURVEY-T0-SURVEY IMPUTATION, SHORT TERM POVERTY MONITORING, POVERTY ESTIMATION METHODOLOGY, |
| Online Access: | http://documents.worldbank.org/curated/en/099439111272329963/IDU0ed4d6e61077f404936080040a13f92c09683 https://openknowledge.worldbank.org/handle/10986/40660 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Close to half of the population of
Afghanistan was living below the national poverty line prior
to the regime change in August 2021, with no additional
information on poverty collected in the country since the
last official household survey in 2019/20. This paper fills
this knowledge gap through survey-to-survey imputation using
a SWIFT-plus methodology. The analysis trains a predictive
model on data from the 2019/20 Expenditure and Labor Force
survey and imputes poverty in the latest Afghanistan Welfare
Monitoring Survey. The analysis accounts for seasonality in
welfare patterns and implements several tests to assess the
model’s predictive capacity. The results show that 48.3
percent of the Afghan population was poor as of April–June
2023, a relative decline of 4 percentage points compared to
poverty levels observed over the same months in 2020. The
reduction in poverty was concentrated among rural
households, with a decline from 51 to 44 percent, while it
stagnated in urban areas at around 58 percent. Although no
poverty data exists since 2020, the evolution of
self-reported welfare and food security makes it reasonable
to conclude that poverty first increased during the
immediate economic contraction following the regime change
and has progressively declined since then. |
|---|