Different Dreams, Same Bed : Collecting, Using, and Interpreting Employment Statistics in Sub-Saharan Africa--The Case of Uganda
Employment and earnings statistics are the key link between the size and structure of economic growth and the welfare of households, which is the ultimate goal of development policy, so it is important to monitor employment outcomes consistently. A...
| Main Authors: | , |
|---|---|
| Format: | Policy Research Working Paper |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2013
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2013/05/17680193/different-dreams-same-bed-collecting-using-interpreting-employment-statistics-sub-saharan-africa-case-uganda http://hdl.handle.net/10986/15577 |
| Summary: | Employment and earnings statistics are
the key link between the size and structure of economic
growth and the welfare of households, which is the ultimate
goal of development policy, so it is important to monitor
employment outcomes consistently. A cursory review of
employment data for low-income Sub-Saharan African countries
shows both large gaps and improbable variation within
countries over time and among countries, suggesting that low
quality data are routinely reported by national statistics
offices. Unfortunately, policies are formed and projects
developed and implemented on the basis of these statistics.
Therefore, errors of measurement could be having profound
implications on the strategic priorities and policies of a
country. This paper explains the improbable results observed
by using data from Uganda, where the labor module contains
variation both within and across surveys, to show the
sensitivity of employment outcomes to survey methodology. It
finds that estimates of employment outcomes are unreliable
if the questionnaire did not use screening questions, as
labor force participation will be underestimated. Likewise,
surveys that use a seven-day recall period underestimate or
potentially misrepresent employment outcomes, owing to
seasonality and multiple jobs. Common multivariate analysis
applied on household survey data will be affected, as the
errors in measurement in the dependent and independent
variables will be correlated. Corrections to reduce
measurement bias in existing data are tested with the survey
data; none are found to be completely satisfactory. The
paper concludes that there is a knowledge gap about
employment outcomes in Sub-Saharan Africa that will continue
unless collection techniques improve. |
|---|