Tracking Results in Agriculture and Rural Development in Less-Than-Ideal Conditions : A Sourcebook of Indicators for Monitoring and Evaluation
The demand for verifiable evidence of results and impacts of development agricultural programs and projects is growing. However, most of the indicators that development practitioners have traditionally used in tracking progress toward achieving pro...
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| Format: | Brief |
| Language: | English |
| Published: |
World Bank, Washington, DC
2012
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| Online Access: | http://documents.worldbank.org/curated/en/2009/03/11913409/tracking-results-agriculture-rural-development-less-than-ideal-conditions-sourcebook-indicators-monitoring-evaluation http://hdl.handle.net/10986/9497 |
| Summary: | The demand for verifiable evidence of
results and impacts of development agricultural programs and
projects is growing. However, most of the indicators that
development practitioners have traditionally used in
tracking progress toward achieving projects' objectives
focus on the workings of the development operation itself.
These performance indicators relate mainly to lower-level
inputs and outputs and are used to populate management
information systems. Higher-level indicators are used to
measure progress in achieving the ultimate objectives of
projects, and in bringing about larger outcomes and impacts.
The ability to measure and demonstrate outcomes and impacts
relies on the use of indicators that are based on reliable
data and on the capacity to systematically collect and
analyze that information. The conditions in which monitoring
and evaluation (M&E) are carried out vary widely,
depending on the demand for information, the extent to which
it is used to inform decision-making, and the reliability of
the systems that are in place to capture and convey that
information. Throughout much of the developing world these
conditions are "less-than-ideal," and information
is irregular and often lacking altogether. In these
conditions there is a lack of effective demand for
information on the part of policy makers. The conditions are
often especially pronounced for data related to rural areas,
where the costs of data collection are high and the quality
of existing data is particularly low. Building data systems
and developing and supporting capacity for M&E in these
conditions is, therefore, a pressing imperative for
interventions in the agriculture and rural development
sector. Strengthening capacity for M&E begins at the
national and sub-national levels, where addressing the
weaknesses of national statistical systems is a common
priority. The data collected and reported within countries
must not only be of sufficient quality to inform planning
and policy formulation but must also be consistent between countries. |
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