Secondary Data Sources

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Secondary data is data collected by any party other than the researcher, including administrative data from programs, geodata from specialized sources, and census or other population data from governments. Secondary data provides important context for any investigation, and in some cases (such as administrative program data), it is the only source which covers the full population needed to conduct a research project.

Read First

  • Research teams usually rely on two broad categories of data - primary data, and secondary data.
  • Impact evaluations rely on many different sources of secondary data, such as: administrative, geospatial, sensor, telecom, and crowd-sourcing.
  • Research teams should decide on the kind of data they want to use, based on context and project-needs.

Types of Secondary 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. Some of the key challenges with administrative data include:

  • Digitization. In a lot of cases, the data is in paper format only.
  • Restricted access. It is also difficult to get access to certain data because it contains sensitive information.
  • Lack of unique ID. In some cases, administrative datasets might be missing a numeric ID variable.

National Survey Data

Existing survey data may be of use depending on the sampling frame for the impact evaluation, level of representativity of the existing data, and availability of disaggregated data. National Statistics Office typically collect a wide array of nationally-representative data, such as Living Standards Measurement Surveys and censuses. International survey efforts such as the Demographic and Health Surveys [1] and Enterprise Surveys [2] are also good sources.

Geo Spatial 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).

Telecom 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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