Abstract Child care and early education plays a vital role in the lives of young children and the social infrastructure of the United States. Extensive and emerging research to understand the accessibility of child care in the United States has focused more on the supply side of the industry than the demand side; there lacks reliable, accessible data regarding parents’ need or desire for child care across time and space. This study proposes using Google Trends data as an ancillary source for understanding child care demand across diverse temporal and spatial contexts because of the dataset’s free and accessible nature. The methods build on a growing body of literature examining best practices of using Google Trends for research, especially in harnessing geographic insights for the spatial components of the data. It contributes to this literature methodologically by demonstrating the usefulness of comprehensive replicate sampling in presenting Google Trends data and how what is considered “comprehensive” depends on the scale of the spatial unit being studied. This case study demonstrates that while Google Trends is a subtly complex data source that should be used judiciously, it is a particularly valuable surrogate for geographers and social scientists to use when no other viable datasets exist. The results reaffirm the need for multiple samples of the same Google Trends query over many days for accurate research insights, and it builds upon recent literature by exploring the use of bias-correcting techniques at different geographic scales. Furthermore, caution is warranted when using Google Trends to study search interest in precise geographies where there is little stability in the data.
Cooper et al. (Mon,) studied this question.