FIN41920 R

Java Python FIN41920 Sustainable Finance Group Project
2025
The purpose of this project is to evaluate the ability of applying US toxic emission data
and accounting data to analyse the effect of toxic emissions on firms’ financial
performance. Here are the recommended instructions:
➢ Each group should decide whether to use Stata or R to complete the work.
➢ You are required to download the Toxics Release Inventory (TRI) Basic Data from
1987 to 2010. The US accounting data and linktable have been provided on
Brightspace for your use. Both files are in .csv format.
➢ Use the linktable to merge TRI data and US accounting data. Both data files have
the same company ID and year information which shall be used.
➢ Calculate the variables of firm size, operating leverage, tangibility, investment rate,
return on equity (ROE), total emissions and emission intensity. For the variable
definitions, please check the pollution premium paper for reference.
➢ Perform the summary statistics for the above variables, i.e., the number of
observations, mean, standard deviation, minimum value, median, and maximum
value.
➢ Use OLS analyses to regress financial performance (ROE) on emission intensity
and control for the variables of firm size, operating leverage, tangibility, investment
rate, year anddai 写FIN41920、R firm fixed effects.
➢ Output the regression table and identify the relationship between emission
intensity and financial performance. Discuss the statistical significance of
estimated coefficient of emission intensity in the context.
➢ Write a comprehensive report documenting each step, from data curation to the
final model analysis. Include R or Stata code snippets, figures, tables, and a
discussion of results and diagnostics. Conclude with reflections on main findings
and any limitations encountered. The word limit is 1,500 (-/+10%) that excludes
code snippets, figures, tables and references.
➢ During the 15-minute presentation, you should walk through all the steps, the
corresponding codes and findings. The report, final dataset and coding files must
be submitted to Brightspace before the deadline.
➢ Only one member of the group shall make the submission to Brightspace.
➢ During the presentation, three random questions will be asked that must be
answered. Please ensure that every member is thoroughly familiar with the work.
Failure to answer any question will result in the deduction of one mark per missed
question.
➢ Submission Deadline is 21st March 11:00 pm. All group presentations will take
place in the class in 27th March