Basic Impact Assessment At Project Level Page 30
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36As mentioned in Section1, IA methods fall into three broad categories: qualitative,
quantitative, and participatory. Techniques from each of these categories can be combined
in any one IA, always bearing in mind the purpose of the IA.
Quantitative approach
This most closely resembles a 'scientific method', but even with careful design is still
subject to problems such as:
• sample selection bias
• mis-specification of underlying causal relationships, and
• respondent motivation
Selection bias may occur because of:
i. difficulties in finding a location at which the control group’s economic, physical and
social environment matches that of the treatment group
ii. the treatment group systematically possessing an ‘invisible’ attribute which the control
group lacks (most commonly identified as entrepreneurial drive and ability)
iii. receiving any form of intervention may result in a short-term positive response from the
treatment group
iv. the control group may become contaminated by contact with the treatment group.
Problems (i) and (iv) can be tackled by more careful selection of the control group. This
applies particularly to controlling for access to infrastructure (which has a key influence on
input and output prices as well as other variables) and ensuring that the control group is
located far away from the treatment group. Problems (ii) and (iii) are more intractable, but
in many cases they can be tackled by using program-accepted ‘clients-to-be’, who have
not yet received the services, as the control group. It must be noted, however, that this
approach will not be valid when the take up of services is based on diffusion through a
heterogeneous population.
The mis-specification of underlying causal relationships arises most commonly
because of the assumption that causality is a one-way process. Overcoming this can be
enormously demanding in terms of data requirements, technical expertise and costs, and
is often only feasible on very rare occasions. The main means of dealing with it are (i)
tracing dropouts from both the treated and control groups; (ii) only conducting IAs on
relatively mature programs; (iii) interim impact monitoring activities to gather qualitative
information about the complexity of causality; and (iv) retrospective. in-depth interviews
with clients.
Respondent motivation operates at two levels. Firstly, the people who take up the
services may be more strongly motivated to participate in the intervention than those in the
control group (similar to 'the entrepreneurial factor' referred to above). Secondly, their
motivation when taking part in the IA, whether it be completion of a survey form or in the
conduct of an interview, may be influenced by their desire to say what they think the
interviewer wants to hear, or how they relate to the interviewer, or the time they are able to
give to completion of the form, and so on. Training of interviewers to ask questions in a
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