DACM Assignment #2 for ECO220Y1Y (weight: 4% of course grade)
Due: Before noon on Thursday, April 6, 2023, and submitted via Quercus

Purpose of this Assignment and What You Gain from Working on It
Analysts, researchers, economists, and anyone laboring to make sense of data, must communicate what they
have discovered. Figures, tables, and writing help readers get the message. This assignment gives you a chance
to further your skills in communicating empirical results using a table and writing. In addition, by working to
construct a table yourself and reviewing tables constructed by economists, you deepen your ability as a reader
to understand how economists communicate analyses – employing our course concepts and skills – in academic
journals. This assignment is your opportunity to:
1) Enhance your fluency in applying course concepts to real data and contexts.
2) Showcase your Excel analysis abilities.
3) Sharpen your skills in comprehending tables created by economists.
4) Boost your own ability to communicate via a table and capitalize on readers’ natural attraction to
anything that helps visualize empirical results.
5) Elevate your writing skills. Be clear, correct, concise, and coherent.
These are key skills for your other courses and future careers. More immediately, during our final exam you will
draw especially heavily on your skills with 1), 3), and 5) above.
How is the DACM Assignment #2 Different from DACM Assignment #1?
The two DACM assignments are similar in structure. However, unlike Assignment #1, for Assignment #2 you
must include inferential statistics. But, before you get carried away with excessive discussion of P-values and
statistical significance, remember that economists focus the most meaningful discussion on point estimates and
economic significance. Further, after Assignment #1 we studied multiple regression, differences in means, and
differences in proportions. We expect your Assignment #2 to include at least one of these more recent topics.
Your Objectives and Expectations for Your Effort
Using an approved dataset from DACM – on Quercus marked by *** – and methods from ECO220Y and DACM,
do a data analysis. Your analysis must be something that you can capture with a table and discuss. Also, your
analysis must be at least a twist on what appears already in DACM or elsewhere in our course and not simply a
replication of what has already been done. You may use more than one of the approved datasets if that makes
sense. You do not need to use the same data for Assignments #1 and #2. Your empirical analysis must be
presentable in a well-constructed table. This assignment ends with sample tables to help you gets some ideas.
To earn good marks, your analysis must be sufficiently complex so you can demonstrate the requisite mastery.
Sufficiently complex means using inferential statistics and at least one of these: multiple regression, difference
in means, and/or difference in proportions, as already mentioned above. When appropriate and meaningful,
panels for heterogeneity analysis or multiple ways to measure an effect can also add useful complexity. Of
course, complicating things unnecessarily and without a clear purpose is not helpful to your assignment.
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In several short paragraphs, offer a clear explanation of what we can learn from your analysis and table. Give the
necessary context and correctly apply relevant course concepts.
Imagine your audience is your peers who have some training in economics and statistics. You are expected to
clearly explain your analysis, table, and take-away message and not put the burden on the reader.
Create a great title – like a headline it should succinctly convey your findings – and title your table too. Your
primary submission – the title, writing, and table – must fit on one side of one page. On the second page, itemize
the steps in Excel to replicate your findings and list the tables that inspired you.
Spend about eight to ten hours on this assignment. This gives time to read and review this assignment and
sample tables, do your analysis, construct your table, write a discussion, revise both, and itemize the replication
steps in Excel and the inspiring tables. This is a mini project, and it is not expected to take days of your time.
Formatting Requirements for Your Assignment
 From your first to final draft, use Microsoft Word with file type .docx and portrait orientation, not
landscape. The table and text must be created in Word: do not use images or screenshots.
 The first page has your title, paragraphs, and table. All should comfortably fit on one side of one page.
We do not dictate fonts, margins, and spacing, but it must comfortably fit and be visually appealing.
 The second page gives succinct, yet clear, bullet lists of replication steps and tables. For replication, the
first step is: open tba.xlsx, where “tba” is the selected DACM dataset marked by *** in Quercus. For
inspiring tables, list clearly. For example, from Denning et al. (2022): “Table 6 – GPA Differences.”
 Do NOT include a cover page. Do NOT write your name and student number.
 For how to be concise, and not wordy, see https://advice.writing.utoronto.ca/revising/wordiness/.
Your Steps to Complete this Assignment
To help break down this assignment into doable steps, you may find this helpful:
1) Carefully read this assignment: it is five pages and is packed with critical information for your success.
2) Browse through all the sample tables at the end of this assignment – they are on Quercus.
o Jot down your ideas.
3) Browse through the approved (***) DACM data sets on Quercus.
o Jot down your ideas.
4) Pick a data set and try doing some analysis in Excel with it.
5) On a piece of paper using pencil and an eraser or on your tablet, sketch out a table you have in mind.
6) Revise your analysis and revise your sketch of a table.
7) Repeat step 1). Now that you have done some hard work, questions will occur to you. They are likely
answered in this assignment. A second read is helpful at this point.
8) Create a Microsoft Word document.
9) Write your replication steps and double-check your analysis for correctness and any further revisions.
10) Construct your table in Microsoft Word.
11) Write your discussion.
12) Write your title.
13) Revise your table to improve its ability to communicate.
14) Revise your discussion and title to improve clarity, correctness, conciseness, and coherence.
15) Submit to Quercus well before the deadline and make sure your assignment looks as intended. If not, fix
formatting issues and resubmit before the deadline.
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How We Mark Your Assignment: The Rubrics
There are 20 points possible. A second table explains “Excellent,” “Good,” “Adequate,” “Flawed,” and “Fail.”1
CATEGORY: Criteria Mark
TABLE: Conveys a correct message/analysis that is sufficiently
complex. Is well labelled and is clear on its own. Overall, adheres to
the norms of substantive tables in academic research. Is well
constructed and communicates effectively.
6.0
Excellent
4.8
Good
3.6
Adequate
3.0
Flawed
1.8
Fail
DISCUSSION: Correct and substantive discussion of the findings and
table. Gives needed context. Correctly applies relevant course
concepts. Supports the message with thorough and insightful
supporting evidence.
6.0
Excellent
4.8
Good
3.6
Adequate
3.0
Flawed
1.8
Fail
OVERALL PRESENTATION: Gives a clear and coherent message that
the reader easily understands. Uses effective titles. Writing is
concise and not wordy. Is visually appealing. Is free of typos and
formatting issues. Follows all instructions.
4.0
Excellent
3.2
Good
2.4
Adequate
2.0
Flawed
1.2
Fail
REPLICATION: Clear, accurate, complete, and succinct replication
steps for a substantive analysis in Excel. Lists inspiring tables.
4.0
Excellent
3.2
Good
2.4
Adequate
2.0
Flawed
1.2
Fail

Mark: Meaning Short Meaning Long
Excellent: Clearly meets, or
exceeds, all criteria.
Demonstrates a thorough understanding of relevant concepts and mastery of relevant
analysis skills. Application of knowledge and skills is highly effective and any minor errors
and/or omissions do not detract from the overall impact.
Good: Meets important
criteria.
Demonstrates considerable understanding of relevant concepts and good proficiency with
relevant analysis skills. Application of knowledge and skills is considerably effective.
Adequate: Approaches
meeting important criteria.
Demonstrates some understanding of relevant concepts and some proficiency with
relevant analysis skills. Application of knowledge and skills is moderately effective.
Flawed: Falls short of
important criteria but shows
progress towards them.
Demonstrates limited understanding of relevant concepts and limited proficiency with
relevant analysis skills. Application of knowledge and skills is slightly effective. There is
evidence of progress towards understanding and proficiency, but overall falls short.
Fail: Insufficient progress
towards important criteria.
Demonstrates insufficient understanding of relevant concepts and insufficient proficiency
with relevant analysis skills. Application of knowledge and skills is ineffective.
Uphold Your Academic Integrity
Submit your own work. Collaboration is not allowed. While you may use services provided by University of
Toronto, you may not use tutoring, editing, or other services of individuals or other organizations. You may not
use generative artificial intelligence, such as chat bots, or any tool that produces writing that is not yours.
Ouriginal – a plagiarism detection tool – assesses your submission. Avoid plagiarism:
https://advice.writing.utoronto.ca/using-sources/how-not-to-plagiarize/. TAs also assess integrity. If it appears
that any empirical results are made up (i.e. fake), beyond a mark of zero for failing to meet the assignment
expectations, we alert Student Academic Integrity (SAI) https://www.artsci.utoronto.ca/current/academic-
advising-and-support/student-academic-integrity. Similarly, we alert SAI of all academic integrity concerns.

1 Adapted from the “Generic Rubric – Mathematics – Open Response (Grade 9)” from the Education Quality and
Accountability Office, retrieved from https://www.eqao.com/the-assessments/math-open-response-g9/ on July 27, 2022.
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Your Submission Window and Penalties for Lateness
You receive this assignment at 11am on Thursday, March 9, 2023. It is due before noon on Thursday, April 6,
2023. The four-week submission window for this short two-page assignment accommodates all issues. Do not
wait until near the end of the window to finish, leaving no time for unexpected situations affecting your ability
to finish. There are no extensions. A late penalty of 1 percent (of the maximum possible points) per hour is
automatically applied by Quercus. Submit your assignment at least a week before the deadline. We set Quercus
to allow you to resubmit. Hence, before the deadline, you can upload a revised and refined version. We only
mark (or even look at) the most recent submission. If you resubmit after the deadline, late penalties apply.
Some Advice for You
Do something that interests you. You may think of this as a mini-mini research paper. If that is daunting rather
than exciting, tackle a concept/skill that has challenged you and create a primer demonstrating your mastery.
You have some flexibility in your use of space. You may create a large table (e.g. two-thirds of a page) that is so
well-designed that it almost explains it all with shorter paragraphs underscoring the conclusions. Alternatively,
you may create a small table (e.g. one-third of a page) with more extensive paragraphs.
Exceeding the length parameters will substantially worsen your assignment, not make it better. Make strategic
decisions about where to focus the reader’s attention. Long research papers are routinely distilled to one page
in the NBER Digest. It is an important skill to be concise and judicious. Do not use small fonts and tight margins.
For tables with multiple panels or variations on a theme, researchers often explain one set of results in detail. Do
not plod through results in your table: if the writing is repetitive and tedious, it needs revision. If the take-away
is similar, just say that. In contrast, if results are notably different, it is important to point out those differences.
Make your table sing! Seasoned researchers often first read the title and abstract of an empirical paper and then
skip ahead to the tables. While you are not off the hook for supporting text, the table itself should tell a story. It
is an important opportunity to communicate your message.
Get started! A first draft is often too long, lacking coherence, and riddled with errors. That is OK if you leave time
to revise and refine. The act of writing and preparing a table helps you think. Start your first draft now!
Some More Advice for You: Mistakes to Avoid
 Do not include raw output from Excel and do not follow the output format from Excel.
o Instead, follow norms of substantive tables in economics. Sample tables end this assignment.
 Do not be shy about rounding numbers in your table.
o Instead, round to an appropriate decimal place and remember that excessive precision often
distracts readers and makes tables visually unappealing.
o For example, do not type 0.0541936711 for a P-value. Round and type 0.054.
 Do not insufficiently label your table so the reader is unsure of the units or the meaning of the numbers.
o Instead, revise your table with row and column labels that help clarify what it shows.
 Do not use variable names from the original data.
o Instead, use helpful, clear, and, still concise, labels.
o For example, “Number of residents” instead of “num_res.”
 Do not be vague about the dependent and independent variables for tables with regressions.
o Instead, clearly indicate the y variable and explanatory variables and any natural log
transformations or other transformations that you have used.
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 Do not forget about key instructions.
o Remember to give just one table.
o Remember to exclude any figures and that no figures are allowed for this assignment.
o Remember to check that Quercus shows your discussion and table as one page.
 Do not prepare a table and discussion that are too long and cram them into one page with small font,
little spacing, and/or narrow margins yielding a visually unappealing assignment that is tiresome to read.
o Instead, revise your table and discussion to fit comfortably on one page.
 In the discussion, do not overemphasize inferential statistics at the expense of the point estimates.
 Do not insufficiently interpret results. Do not offer generic discussion of course concepts.
o Instead, revise any sentences that could be cut-and-paste to another context to directly apply
course concepts and skills to the context of the selected data.
o For example, this sentence is generic and not concise: “The P-value is very small at 0.0042421
and hence, we can conclude that the results are statistically significant at a 1% significance
level.” Instead, this sentence is more effective: “There is overwhelming evidence that happiness
and income are related even after controlling for health and age differences across countries.”
 Do not jump to conclusions about causality with an analysis of observational data with endogeneity bias.
 Do not leave it to the reader to figure out your main message.
o Instead, your title, table, and discussion should work together to deliver a clear message.
 Do not use a separate introduction section.
o Instead, put any background in the body of this short assignment.
 Do not list vague and/or unclear replication steps on the second page and do not forget to list them.
o Instead, list replication steps that clearly demonstrate your fluency in how do analysis in Excel.
 Do not forget to list the tables serving as inspiration on the second page.
 Do not create drafts outside of Word (e.g. Google docs): this causes formatting issues in conversion.
 Do not wait until the deadline before attempting to submit the assignment to Quercus, encountering
unexpected problems, and then asking us to intervene (the answer is no).
o Instead, remember that you can resubmit as many times as you want before the deadline, and
we only mark the most recent version. After the deadline, late penalties apply automatically.
Some Sample Tables to Start the Inspiration
Review all the sample tables below. You can mix-and-match ideas, when sensible, not rigidly follow a template.
Many things with rows and columns do NOT adhere to the norms of substantive tables in academic research.
This list has helpful samples but is not exhaustive. Also, some tables could use revisions to improve clarity and
visual appeal: while researchers may take short-cuts, you cannot. The DACM page in Quercus gives links to each.
 April 2022 Exam, Questions (4), (6): “Women’s Downhill Skiing Final: 2022 Beijing Olympics” and “Table
4. OLS regression results, with dummy variables for blue and red states” from Bachmann et al. (2021)
 Denning et al. (2022): “Table 6 – GPA Differences”
 Karlan and List (2007): “Table 2A – Mean Responses” and “Table 2B – Mean Responses”
 Taubman et al. (2013): “Table 2: Emergency-Department Use”
 Zheng and Kahn (2017): “Table 1. Correlates of Urban Air Pollution in China”
 April 2017 Exam, Question (3): “Table 1: Estimates of Learning by Doing” from Levitt et al. (2013)
 April 2013 Exam, Questions (20) – (26) “Table 2: OLS regression models of subjective well-being” from
Steele and Lynch (2013)
 2022 World Happiness Report: “Table 2.1: Regressions to Explain Average Happiness across Countries
(Pooled OLS)” and “Table 2.5: COVID-19 deaths in 2020 and 2021 per 100,000 population”