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Data Visualization in Applied Economics Instruction and Outreach

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  • Hutchins, Jared
  • Van Leuven, Andrew J.

Abstract

This article highlights the critical role of data visualization in applied economics education and outreach. We first outline some general principles for teaching graph literacy and data visualization principles in and out of the classroom. We then discuss the mechanics of visualizing data—collection, preparation, and visualization—with an emphasis on how instructors can teach each step using the R and/or Python statistical environments. We ultimately contend that the requisite skills for successful data visualization are indispensable for students trained in today’s agricultural and applied economics programs to communicate their research effectively.

Suggested Citation

  • Hutchins, Jared & Van Leuven, Andrew J., 2025. "Data Visualization in Applied Economics Instruction and Outreach," Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 7(5), October.
    • Handle: RePEc:ags:aaeatr:384745
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    File URL: https://ageconsearch.umn.edu/record/384745/files/AETR_2025_0237%20Full.pdf
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    References listed on IDEAS

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    4. Maximilian Auffhammer & Solomon M. Hsiang & Wolfram Schlenker & Adam Sobel, 2013. "Using Weather Data and Climate Model Output in Economic Analyses of Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 7(2), pages 181-198, July.
    5. Elliott, Matthew S. & Elliott, Lisa M., 2020. "Developing R Shiny Web Applications for Extension Education," Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 2(4), October.
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    7. Indaco, Agustín, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).
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