Assignment 1
Description
Since 1997, Quebec has offered regulated child care at a low fixed daily fee, while until 2021 parents in the rest of Canada mostly paid market prices. In this assignment you will use data from the Labour Force Survey to compare the labour force participation of mothers of young children in Quebec and the rest of Canada, and to think about whether the difference tells us what cheap child care does to mothers’ labour supply.
The assignment is designed to give you practice analysing data in R and writing up your results in Quarto, and to show how economists use data to test a prediction of the labour supply model.
Due: Friday, October 9, 2026 at 9:00pm.
ec306assign1.qmd — the assignment questions, as a Quarto document you write your answers into
ec306assign1.csv — the data
Instructions
The questions are in the Quarto document above. Open it in RStudio and press Render before you change anything: it should produce a PDF. If it does not, fix that first, using the Introduction to R and Quarto page.
Then work through the questions, writing your R code in the chunks provided and your answers in the text below each question. The hints under each question point to sections of the Introduction to R and Quarto page, which has a worked example of each step. Wherever a written answer is needed, the question has a Comment on the results prompt, just above the answer space, that says what to cover. Tables must be made with modelsummary(), datasummary() or datasummary_df(), and graphs must have readable axis labels. Do not print a data frame as a table, and do not copy and paste, or screenshot, console output.
Several questions ask you to store a result under a particular name, such as q2 or gap_u6. Those objects are checked automatically, so:
- use exactly the names given in the question;
- do not change the code in the
setupandload-datachunks; - do not round the numbers you store (round only when displaying them).
The last chunk in the document tells you whether any of the required objects are missing.
The data
The data come from the Labour Force Survey public use microdata file for March 2019. The sample is everyone aged 25 to 54, which is 46,808 people. The data are from 2019 because in 2021 the other provinces began cutting their child care fees toward Quebec’s level, which makes later comparisons harder to interpret.
| Variable | Description |
|---|---|
id |
Person identifier |
province |
Province of residence |
gender |
“Women+” or “Men+”. Statistics Canada uses these labels because the small number of non-binary respondents are distributed between the two categories to protect confidentiality. |
agegroup |
Five-year age group |
educ |
Highest level of education |
lfsstat |
Labour force status: “Employed, at work”, “Employed, absent from work”, “Unemployed”, or “Not in labour force” |
kidage |
Age of the person’s youngest child living with them: “Under 6”, “6 to 12”, “13 to 17”, “18 to 24”, or “None under 25” |
hours |
Usual weekly hours at all jobs. Missing for people who are not employed. |
Submission
Submit two files on Gradescope, both by the due date:
- Your
.qmdfile, to the assignment called Assignment 1 - Code. This is the file that is marked by computer. - The PDF produced by rendering it, to the assignment called Assignment 1 - Written. When you upload it, match each question to the page it is on. Your tables, graphs, and written answers are marked from this file.
Results from the computer marking are released after the due date, not when you submit, so use the check at the end of the document before you submit.
A document that does not render cannot produce a PDF, so render after every question, not only at the end.
Marking
The assignment is marked out of 30.
- Each of the five questions is marked out of 5 from your PDF, using the rubric below. The mark reflects the whole answer: code, tables, graphs, and writing.
- Your code is marked out of 5 by computer, from how many of the objects you were asked to create are correct.
| Points | Rubric |
|---|---|
| 5 | Fully correct |
| 4 | Mostly correct with a minor mistake, or slightly lacking detail |
| 3 | Mostly correct with multiple minor mistakes, a more substantial mistake, or a more significant lack of detail |
| 2 | Mostly incorrect with a major mistake or several minor mistakes |
| 1 | Mostly incorrect with multiple major and minor mistakes |
| 0 | Blank or entirely incorrect |
Generative AI
You may use generative AI for this assignment, but you must say how you used it. The document has a section at the end for this. Failing to disclose its use is academic misconduct.
Plagiarism
This is an independent assignment, which I expect you to complete on your own. It is plagiarism to copy someone else’s work verbatim, which includes R code. Any work you submit should be yours only. However, you are encouraged to talk to each other to try to figure out how to do the assignment.