Difference between revisions of "Primary Data Collection"

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This article is part of the topic [[Primary Data Collection|primary data collection]]
This article is part of [[Primary Data Collection]]

== Additional Resources ==
== Additional Resources ==

Revision as of 20:19, 19 March 2020

Primary data collection is the process of gathering data through surveys, interviews or experiments. A typical example of primary data is household surveys. In this form of data collection, researchers can personally ensure that primary data meets the standards of quality, availability, statistical power and sampling required for a particular research question. With globally increasing access to specialized survey tools, survey firms, and field manuals, primary data has become the dominant source for empirical inquiry in development economics.

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  • The DIME Research Standards provide a comprehensive checklist to ensure that collection and handling of research data is in line with global best-practices.
  • Personal interviews are the most effective medium for primary data collection. Depending on the research question, these interviews may take the form of household surveys, business (firm) surveys, or agricultural (farm) surveys.
  • iefieldkit is a Stata package that aids primary data collection. It currently supports three major components of that workflow: survey design; survey completion; and data-cleaning and survey harmonization.


While impact evaluations often benefit from secondary sources of data like administrative data, census data, or household data, these sources may not always be available. In such cases, researchers need to collect data directly through a series of well-designed interviews and surveys. The process of collecting primary data requires a great deal of foresight, planning and coordination. Listed below are the crucial steps involved the in preparation and collection of primary data:

Pre-register research

Pre-register and consider producing a pre-analysis plan.

Acquire approval from human subjects

Acquire human subjects approval and get set up with the proper tools for encryption and de-identification.

Compile the survey budget

Compile the survey budget

Determine and set the relevant sampling parameters.

Determine the sampling frame, calculate sample size, conduct sampling and power calculations, and randomize treatment.

Desing and translate the survey instrument

Design and translate the survey instrument

Program the instrument

Program the instrument f data is being collected electronically via a Computer-Assisted Personal Interviews (CAPI) or Computer-Assisted Field Entry (CAFE) survey.

Establish survey protocols

Establish survey protocols.

Pilot the survey instrument

Pilot the survey instrument–both the content and protocols.

Procure a survey firm

Procure a survey firm, taking care to prepare detailed Terms of Reference.

Train enumerators

Train enumerators

Monitor data quality

Monitor data quality can be done through back-checks, high frequency checks, and other methods.

Maintain an organized data folder

via iefolder.

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This article is part of Primary Data Collection

Additional Resources

  • Oxfam provides a detailed case study of how to use electronic data collection (SurveyCTO) combined with Stata code to improve data quality in the field.