Quantitative methods & analysis

How do we know if a program made a difference? A guide to statistical methods for program impact evaluation

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Authors: Peter M. Lance,  David K. Guilkey, Aiko Hattori & Gustavo Angeles (for MEASURE Evaluation)
Publication date: 2014

There is a long-running, vigorous and evolving methodological debate about the appropriate or optimal way to evaluate the impact of a program. This manual strives not to convince readers of the merits of one particular alternative or another, but instead simply to present the various options in as approachable a fashion as possible and then let them decide for themselves where they stand. In other words, it strives to be impartial.

FANTA: Sampling Guide (with 2012 Addendum)

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Authors: Robert Magnini (1999) and Diane Stukel & Megan Deitchler (2012) (for FANTA)
Publication date: Sampling Guide (1999) and Addendum (2012)

These materials provide sampling guidance for baseline and final performance evaluation surveys in the context of USAID Food for Peace Title II development food assistance programs. The guide provides methods and instructions for developing the design of a population-based household survey and provides information on how to randomly select samples of communities, households, and/or individuals for such surveys. It emphasizes the use of probability sampling methods, which are essential to ensure that the survey represents the target population. In the addendum, an updated approach for sample size calculation is provided, which will result in a household sample size that is more likely to achieve the required sample size of children for child-level indicators.

Mapping village variability in Afghanistan: The use of cluster analysis to construct village typologies

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Authors: Adam Pain and Georgina Sturge 

Publication date: May 18, 2015

This working paper investigates whether or not village typologies can be constructed with respect to the behaviour of village elites in Afghanistan.

Creating an Analysis Plan

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Author: Centers for Disease Control and Prevention (CDC)

Publication date: 2013

The Creating an Analysis Plan training module is one of three modules that will provide you with the skills needed to analyze and interpret quantitative 1 noncommunicable disease (NCD) data. When you apply these quantitative analysis skills, you will turn data into information that can be used to make informed decisions on public health program and policy recommendations.

Patterns of progress on the MDGs and implications for target setting post-2015

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Authors: Rodriguez Tacheuki, L., Samman, E. with Steer, L.
Publication date: 2015

To examine the true patterns of progress on the MDGs, this paper explores seven indicators – one representing each of the first seven MDGs. For all indicators but extreme poverty, we find that typically, progress is easiest to attain for countries that are relatively deprived (or further from the target), though there are important differences between indicators.

Indicators. A working aid

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Author: Hunter, J. (for GIZ)
Publication date: 2014

This document serves as a guide that aids in selecting and formulating indicators.

CLEAR M&E Roundtable Series # 2 - Theory of Change

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This roundtable was the second in a series of M&E roundtables organised by CLEAR South Asia on Best Practices in Data Collection. It provided an introduction to of experimental evaluation and quasi-experimental methods.

Systems Dynamics Modelling in Industrial Development Evaluation

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Authors: Derwisch, S. & Löwe, P.
Publication date: 2015

The complexity of development processes makes it difficult to observe and interpret the impacts of policies. The authors demonstrate the use and benefits of system dynamics modelling (SDM) in impact evaluation of private sector development programmes.

Dynamics of Rural Innovation - a primer for emerging professionals

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Authors: Pyburn, R. & Woodhill, J. (eds.)
Publication date: 2014

Dynamics of Rural Innovation – a primer for emerging professionals is a co-publication of KIT and Wageningen University’s Centre for Development Innovation (CDI) that brings together the experiences of over 40 conceptual thinkers and development practitioners to articulate lessons on agricultural innovation processes and social learning.

What is the future of official statistics in the Big Data era?

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Digital data are increasingly changing the shape of our world. At the same time, attention is also being paid to the woeful state of development data. 

This public event brought together leading experts who explored the potential of Big Data to transform national statistical systems as well as concerns about the reliability and representativeness of these data, and over ethics, privacy, and the blurring of lines between formal and informal data sources.