Primary Data Collection

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.

Read First

• The DIME Research Standards provide a comprehensive checklist to ensure that collection and handling of research data is in line with global best practices.
• Field surveys are one of 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.
• The research team must plan and prepare for primary data collection in advance.
• iefieldkit is a Stata package that aids primary data collection. It currently supports three major components of this process: testing survey instruments; survey completion; and data-cleaning and survey harmonization.

Overview

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, the research team will need to collect data directly using well-designed interviews and surveys, and the research team typically owns the data that it collects. However, even then, the research team must keep in mind certain ethical concerns related to owning and handling sensitive, or personally identifiable information (PII).

Before moving on to the discussion of concerns about ownership and handling, however, it is important to understand the process of collecting primary data. The process of primary data collection consists of several steps, from questionnaire development, to enumerator training. Each of these steps are listed below, and require detailed planning, and coordination among the members of the research team.

Develop Questionnaire

The first step of primary data collection is to design a survey instrument (or questionnaire). It is important to remember that drafting a questionnaire from scratch can be a time-consuming process, so the research team should try to use existing resources as far as possible. While developing the questionnaire, keep the following things in mind:

• Modules. Divide the questionnaire into individual modules, each with a group of questions that are related to one aspect of the survey. Unless the context of the study is entirely new, perform a literature review of existing well-tested and reliable surveys to prepare the general structure of the questionnaire. One example of a resource for past studies and questionnaires is the World Bank Microdata Library.

• Measurement challenges.' Often, research teams face challenges in measuring certain outcomes, for instance, abstract concepts (like empowerment), or socially sensitive topics that people do not wish to talk about (like drug abuse). In such cases, try to use indicators that are easy to identify, or build a level of comfort with respondents before moving to the sensitive topics.

• Translation. Translating the questionnaire is a very important step. The research team must hire only professional translators to translate the questionnaire into all local languages that are spoken in the study location.

Pilot Questionnaire

The first stage of the survey pilot, the pre-pilot involves two things: piloting content and piloting protocols. Clear protocols allow researchers to ensure that field collection is carried out consistently across teams and/or regions, and ensure that published research is reproducible.

TOR and Procurement

Researchers must prepare a survey budget before procuring a survey firm. This step allows researchers to calculate expected costs of conducting a study, and compare these with the proposals of firms that submit an expression of interest (EOI).

Determine relevant parameters of a study

After agreeing upon a budget, researchers then decide upon factors like the adequate sampling frame (which is a list of individuals or units in a population from which a sample can be drawn), sample size, and statistical power based on which they can then randomize treatment.

Procure a survey firm

The next step is to procure a survey firm after issuing detailed terms of reference (TOR), and performing due diligence among local research firm options.

Obtain Ethical Approval

There are strict rules about acquiring approval from human subjects. Researchers must understand the ethics and rules for security of sensitive data, and should use proper tools for encryption and de-identification of personally identifiable information (PII).

Train Enumerators

After validating the programming of the questionnaire, the researchers train enumerators and monitor data quality to generate a final draft of the instrument. Monitoring can be done in the form of back checks, high frequency checks, as well as other methods.

DIME Analytics has created a Stata command, iefolder. Part of the DIME Analytics Stata packageietoolkit , it helps increase project efficiency, and reduces the risk of error in a study.

Related Pages

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Additional Resources

• Oxfam, Brief on Planning Survey Research
• DIME (World Bank), Guide on Planning, Preparing & Monitoring Household Surveys
• DIME Analytics (World Bank), Guidelines on Preparing for Data Collection
• Oxfam, Case study on using electronic data collection (SurveyCTO) and Stata to improve data quality in the field