Introduction to Data Analysis and Applied
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ECO220Y5Y: Introduction to Data Analysis and Applied
Econometrics
Data Project Two
Is COVID-19 likely to increase educational inequality amongst less de-
veloped countries? Does cross-country evidence indicate some countries
are at greater risk of an educational crisis?
0.1 Project Overview
Your goal is to describe the variation in COVID-19 related educational inequality and risks facing the
education sector across countries. You should comment on the articles which discuss the severity of
the situation for many countries and what COVID-19 might mean for educational vulnerabilities. You
will do this using the ‘projectdata Fall2020.xlsx’ file provided. Continuing from your previous analysis
you will produce additional evidence using your knowledge from linear regression. You must now
include and discuss results using multivariate regression techniques, for example: output
tables, interpretation of coefficients, goodness of fit statistics, plots of residuals, etc. You should
consider carefully the best specification and provide evidence (formal testing or analysis of plots) to
support your model selection. You should consider creating indicator variables that might be used
to impact the intercept or as interaction terms. You should look for common violations of the OLS
assumptions in your regressions such as heteroskedasticity, serial correlation and non-normality. You
should conclude using your model to determine whether COVID has increased educational inequality
for developing countries. You should comment on how significant your variables of interest are
and what economic significance you can uncover relating COVID to educational outcomes amongst
different countries.