Difference between revisions of "Secondary Data Sources"
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== Guidelines == | == Guidelines == | ||
=== Administrative and Monitoring Data === | === [[Administrative and Monitoring Data]] === | ||
Administrative data includes all data collected through existing government Ministries, programs and projects. It is a potentially rich source of data for an impact evaluation. Key challenges are: data is in paper format only (needs to be digitized), restricted access, lack of numeric identifier (or lack of common identifier with other key datasets). | Administrative data includes all data collected through existing government Ministries, programs and projects. It is a potentially rich source of data for an impact evaluation. Key challenges are: data is in paper format only (needs to be digitized), restricted access, lack of numeric identifier (or lack of common identifier with other key datasets). | ||
[https://www.povertyactionlab.org/ JPAL] provides a [https://www.povertyactionlab.org/na/administrative-data-and-evaluation-guides useful guide to using administrative data for impact evaluations]. | [https://www.povertyactionlab.org/ JPAL] provides a [https://www.povertyactionlab.org/na/administrative-data-and-evaluation-guides useful guide to using administrative data for impact evaluations]. | ||
=== Survey Data === | === [[Survey Data]] === | ||
The bread and butter of most impact evaluations is primary data collection; enumerators conducting personal interviews with respondents. These can be in the form of household surveys, firm surveys, school surveys, health facility surveys, etc. They can take place in-person, by telephone, or online. | The bread and butter of most impact evaluations is primary data collection; enumerators conducting personal interviews with respondents. These can be in the form of household surveys, firm surveys, school surveys, health facility surveys, etc. They can take place in-person, by telephone, or online. | ||
=== Geospatial Data === | === [[Geospatial Data]] === | ||
This includes data from | This includes data from traditional satellites, micro- and nano-satellites, and unaccompanied aerial vehicles (UAVs, e.g. drones). | ||
=== | === [[Remote Sensing]] === | ||
This includes all data collected by sensors, and through IoT. | This includes all data collected by sensors, and through the Internet of Things (IoT). | ||
=== Telecomms Data === | === [[Telecomms Data]] === | ||
This includes [[call detail records]], | This includes [[call detail records]], social media data, web scraping. | ||
=== Crowd-sourced Data === | === [[Crowd-sourced Data]] === | ||
This includes all data collected by crowd-sourcing, often through social media or mobile apps. | This includes all data collected by crowd-sourcing, often through social media or mobile apps. | ||
Revision as of 20:23, 26 October 2017
Impact Evaluations rely on many different sources of data: administrative, survey, geospatial, sensors, telecomms, and crowd-sourcing. An important step in designing an impact evaluation is to evaluate what data sources are best suited (and which are available, given the context).
Guidelines
Administrative and Monitoring Data
Administrative data includes all data collected through existing government Ministries, programs and projects. It is a potentially rich source of data for an impact evaluation. Key challenges are: data is in paper format only (needs to be digitized), restricted access, lack of numeric identifier (or lack of common identifier with other key datasets).
JPAL provides a useful guide to using administrative data for impact evaluations.
Survey Data
The bread and butter of most impact evaluations is primary data collection; enumerators conducting personal interviews with respondents. These can be in the form of household surveys, firm surveys, school surveys, health facility surveys, etc. They can take place in-person, by telephone, or online.
Geospatial Data
This includes data from traditional satellites, micro- and nano-satellites, and unaccompanied aerial vehicles (UAVs, e.g. drones).
Remote Sensing
This includes all data collected by sensors, and through the Internet of Things (IoT).
Telecomms Data
This includes call detail records, social media data, web scraping.
Crowd-sourced Data
This includes all data collected by crowd-sourcing, often through social media or mobile apps.
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This article is part of the topic Data Sources