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This is a group project created for Introductory Econometrics (ECON*3740) which analyzes how the gender wage gap has changed over the pandemic.

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Isss11/Pandemic-Gender-Wage-Gap-Statistical-Inference

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Pandemic-Gender-Wage-Gap-Statistical-Inference

This was a group project created in ECON*3740 (Introductory Econometrics) at the University of Guelph. I created it alongside my group members, Yushan Xie, Jack Ronson, and another group member.

I used R programming to perform varying statistical tests on LFS data from December 2019 and December 2022 and determined with a 1% level of significance that the gender hourly wage gap has closed over the course of the pandemic. While we cannot derive fully causal effects of the pandemic's impact on the gender pay gap, we found that women did disproportionately better with increases in hourly wages in comparison to men. We also found that holding numerous factors constant, women earned less 9.6% in hourly earnings than men, as reported in December 2022. Once again, there could be other unexplained factors that produce downward/upward bias on this coefficient, but we did find a reduction in wages for women even after holding multiple independent variables constant.

Datasets to Download:

  1. December 2019 Labour Force Survey
  2. December 2022 Labour Force Survey

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This is a group project created for Introductory Econometrics (ECON*3740) which analyzes how the gender wage gap has changed over the pandemic.

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