[EQ] Conducting Quality Impact Evaluations Under Budget, Time and Data Constraints

Conducting Quality Impact Evaluations Under Budget, Time and Data
Constraints

World Bank's Independent Evaluation Group (IEG) and the Poverty Analysis
Monitoring and Impact Evaluation Thematic Group (PREM Network) 2006

Available online as PDF file [35p]

            English Version:

http://lnweb18.worldbank.org/oed/oeddoclib.nsf/DocUNIDViewForJavaSearch/757A
5CC0BAE22558852571770059D89C/$file/conduct_qual_impact.pdf

Spanish Version:

http://lnweb18.worldbank.org/oed/oeddoclib.nsf/DocUNIDViewForJavaSearch/4EE5
AA007401147C8525717700650954/$file/conduct_qual_impact_spanish.pdf

"... The purpose of this booklet is to provide advice to those planning an
impact evaluation, so that they can select the most rigorous methods
available within the constraints they face. The booklet is also intended to
clarify the nature of the trade-offs between evaluation rigor and the
budget, time and data which are available for an evaluation. It is hoped
that this booklet will encourage managers to conduct impact evaluations when
they might otherwise have viewed them as too expensive or time-consuming to
be conducted to a high standard. Thus the desired outcome is an increase in
the quality and quantity of rigorous impact evaluations which are conducted.

An extensive literature is now available on appropriate methodologies for
evaluating the impacts of development projects and programs. This booklet
applies these methodologies to the real-world situations and constraints
faced by task managers and researchers..."

TABLE OF CONTENTS

1 Overview

2 Simplifying the evaluation design

Case study 1: Reducing costs through a post-project cross-sectional design -
gender and time-use impacts of the Ecuador cut-flower industry

3 Working with comparison group designs

Case study 2: Using propensity scores to produce a matched comparison
group - the Viet Nam Rural Roads Project

4 Working with secondary data

Case study 3: Using multiple sources of secondary data - the Bangladesh
Integrated Nutrition Project

5 Reconstructing baseline data

Case study 4: Reconstructing baseline data - the Nicaragua Social Fund

6 Reducing the costs of data collection

Case study 5: Using PRA techniques to reduce data collection costs - the
Flores, Indonesia Village Water Supply and

Sanitation Project

7 Strengthening evaluation designs when working under budget, time and data
constraints

Tables

* * * *

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Received on Wed Aug 23 11:50:53 2006