iefieldkit: Stata commands for primary data collection and cleaning

Data collection and cleaning workflows use highly repetitive but extremely important processes. -iefieldkit- was developed to standardize and simplify best practices for high-quality primary data collection across the 100+ members of the World Bank's Development Research Group, Impact Evaluations team (DIME). It automates: error-checking for electronic ODK-based survey modules such as those implemented in SurveyCTO; duplicate checking and resolution; data cleaning including renaming, labeling, recoding, and survey harmonization; and codebook creation. The presentation will outline how the -iefieldkit- package is intended to provide a data collection workflow skeleton for nearly any type of primary data collection, from questionnaire design to data import. One feature of many -iefieldkit- commands is their utilization of spreadsheet-based workflows, which reduce repetitive coding in Stata and document corrections and cleaning in a human-readable format. This enables rapid review of data quality in a standardized process, with the goal of producing maximally clean primary data for the downstream data construction and analysis phases in a transparent and accessible manner. These tools are developed open-source on GitHub and available publicly.