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ECO220Y1Y, Short Writing Assignment #3, March 2021

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ECO220Y1Y, Short Writing Assignment #3, March 2021
ECO220Y1Y, Short Writing Assignment #3, March 2021 Overview Economists conduct quantitative analyses to obtain key numbers, tables, and figures and explain in words what these results mean. These short writing assignments help you build an essential academic and workplace skill: writing. In 200 to 300 words, you will answer questions about an excerpt from current research. This is a short writing assignment and is not much longer than the writing students have done in timed term tests and final examinations over the last five years. The substance of the questions in this assignment is very similar to test and exam questions. Similarly, you are not expected to conduct research nor to use software to analyze a data set. Everything needed to answer is within this assignment and our regular course materials. Similarly, we give links to the original research papers (and copies are in Quercus: https://q.utoronto.ca/courses/183576/pages/perusall-andreadings#other), but you can successfully answer without reading beyond what is given in this assignment. A key difference is that we expect you to engage in significant revision, which is essential to effective writing: good writing involves rewriting. A timed test/exam setting affords too little opportunity because of the timer and because answers are handwritten. This assignment avoids those limitations and gives you more flexibility: you have two weeks and you type your submission in Microsoft Word in Office 365 ProPlus. Give yourself ample time to revise your first draft, not only so that it meets length expectations, but also for substance, clarity, precision, concision, and coherence. A good suggestion would be to start by taking 30 minutes to type your first draft, as if you had a timer and it were a test or exam question. Step away. Reread this entire assignment, including the marking rubric, and then read your first draft with a critical eye and start revising. Come back multiple times to revise your writing and refine your thinking, studying the related course concepts where necessary. This assignment should take you roughly 4 to 6 hours overall. See Section 12.4 of our syllabus. How to Submit You must type your submission using Microsoft Word in Office 365 ProPlus, which produces a .docx file type. Recall https://onesearch.library.utoronto.ca/ic-faq-categories/office-365-proplus.  Upload your .docx file to our Quercus site under Assignments: Short Writing Assignment 3. We use Turnitin.  Upload your .pdf copy to Crowdmark. PDF export is built into all the O365 apps. Either under “File -> Save As Copy” and specifying the file type as .PDF or via “File -> Export -> Create PDF/XPS File.” Both submissions are required: failure to submit either or discrepancies between the .docx and .pdf files will result in an automatic mark of 0. Do not include a title page and do not include your name or student number. Deadlines You must complete your submission – both to Quercus and to Crowdmark – by NOON on Friday, March 26. You can earn a small early bird bonus for completing both of your final submissions more than 24 hours before the deadline, which means before noon on Thursday, March 25. There is a short grace period of 5 hours after the deadline but beyond that we do not accept late submissions: an automatic mark of zero. There are no make-ups and no extensions for any reason. No Collaboration, No Plagiarism There is absolutely no collaboration allowed for any short writing assignments. There is not an academic integrity statement for this short writing assignment, but academic integrity remains critical. Also, make sure not to plagiarize. An excellent resource is the U of T Writing Advice page titled “How Not to Plagiarize” by Margaret Procter. See https://advice.writing.utoronto.ca/using-sources/how-not-to-plagiarize/. Questions for You to Address Your short writing assignment should address the questions listed next. Review your research excerpts in the last section. DO NOT offer a general discussion of the research excerpts, but rather DO address all of the specific questions asked. Where questions are somewhat distinct (perhaps about a quite different aspects of the research and/or results), make each answer internally coherent and separate your answers to distinct questions with paragraphs. As you see from the excerpts, the authors have already introduced the research, drew some conclusions, and discussed the tables and figures. (Read those first.) Your job is to answer these specific follow-up questions.  This sentence from the page 73 excerpts – “We find that December approvals account for over 15.07 percent of all approvals, or about 7.35 percent (t = 5.26) more than the average in other months” – should say percentage points, not percent. Using the information in that sentence, how is 7.35 computed? Why is it important to be careful whether you write “percent more” or “percentage points more”? Explain in this specific context, using the relevant numbers.  In the excerpts from page 74, the researchers state “Similarly, we see no evidence of elevated adverse effects for drugs approved the week before Lunar New Year in either the United States or the European Union.” Explain the simple regression that could be run to suggest this conclusion for the European Union. Explain what the y variable and x variable would be and how the researcher would create each. Make sure to specify how many observations would be in the data and what the unit of observation is.  In Column (1) of Table A1, what is the correct one-sentence-long interpretation of 2.317? (Note: The “YES” indicated for “Year FE” would add “controlling for differences in the number of approvals across years” to the interpretation. However, leave that part out of your interpretation for this assignment.) What do the regression results suggest for the last 10 days of December? If the researchers had a Column (0) that was like Column (1) but excluded “Last 10 Days,” what would that likely mean for the coefficient on “December”? Why? Marking Rubric Marking TAs will assess how well you answer your assigned questions. While many factors contribute to effective writing, here are three guideposts. The second point is the most important, but they are all interconnected. 1. Identification and understanding of relevant course concepts: How well are relevant concepts identified and explained? 2. Precise application and integration of relevant course concepts: How well have the relevant concepts been applied to the specific context? Are the concepts clearly applied (well-integrated) or are they discussed in a more generic manner with only superficial connections to the issue and context? Are the sentences precise in their meaning or somewhat vague or lacking in relevant numeric details? 3. Effective communication: How easy is it for the reader to understand the ideas and train of thought? To what extent are the answers expressed in clear, complete, and concise sentences? Are ideas explained or is jargon overused? Is the discussion logically ordered? Are paragraphs well-structured with a clear topic sentence for each? Understanding Word Counts There is no fixed numeric deduction for being outside the word count requirement of between 200 and 300 words. However, submissions shorter than 200 words will almost surely lack depth and inadequately address the questions asked. Submissions exceeding 300 words are more challenging to read and comprehend and are less likely to be effective. The word count is the total for all questions and subparts: your entire submission should be within that range. Research Excerpts Consider a 2021 academic article “Internal Deadlines, Drug Approvals, and Safety Problems” in the American Economic Review: Insights. (https://doi.org/10.1257/aeri.20200086) Next are the abstract and selected excerpts from the article. Abstract: Absent explicit quotas, incentives, reporting, or fiscal year-end motives, drug approvals around the world surge in December, at month-ends, and before respective major national holidays. Drugs approved before these informal deadlines are associated with significantly more adverse effects, including more hospitalizations, life-threatening incidents, and deaths—particularly, drugs most rushed through the approval process. These patterns are consistent with a model in which regulators rush to meet internal production benchmarks associated with salient calendar periods: this “desk-clearing” behavior results in more lax review, leading both to increased output and increased safety issues at particular—and predictable—periodicities over the year. Excerpts (pp. 67-68, Introduction): The approval patterns we observe exist at periodicities consistent with regulators rushing to meet internally imposed benchmarks associated with calendar events such as year-ends, month-ends, and holidays. In particular, while Carpenter, Zucker, and Avorn (2008) have shown that drug regulators rush to meet formal deadlines in the United States, we identify a distinct behavioral phenomenon that persists across different formal regulatory regimes in many countries. For example, drug regulators are not formally evaluated on their year-end output in any country that we are aware of; rather, they are typically given target times for processing applicants and evaluated in part based on the percentage of applications that receive a timely review. These specific targets differ across regulators in different countries (within 300 days in the United States versus 210 days in the European Union, for instance). Rushing to comply with these formal policies would not generate the pattern of year-end, month-end, and holiday surges that we document. Excerpts (p. 73, Section III. Main Results, A. Analysis of Number of Approvals): [NOTE: There are some errors: where the authors say percent more, they mean percentage points more.] Panels A and B of Figure 1 illustrate our first key finding: across the world, more drugs are approved in December than in any other month. Panel A illustrates results from the United States and plots the total number of drug approvals in our sample period by month and, within a month, by whether they are approved in the first, middle, or last ten days of the month. We find that December approvals account for over 15.07 percent of all approvals, or about 7.35 percent (t = 5.26) more than the average in other months. Similarly, panel B presents results from our international sample, which includes the European Union, United Kingdom, Japan, China, and South Korea. December approvals account for 21.06 percent of all approvals in this sample, or 13.89 percent (t = 7.41) more than the average in other months. Panels A and B of Figure 1 also show that there are more approvals during another natural desk-clearing window: month-ends. In the United States, 45.50 percent more drugs are approved on days that fall in the last 10 days of a month than in any other given period (t = 9.36). In our international sample, this ratio is 50.50 percent (t = 6.17). Online Appendix Table A1 presents the accompanying regression results, which show that these output surges are statistically significant and robust to inclusion of a variety of controls. If our results are driven by the idea that such dates serve as natural psychological markers of production period-ends, then we may expect to see similar behavior associated with holiday breaks. In the United States, Thanksgiving is the most celebrated holiday outside of Christmas and is associated with a long travel weekend. Panel C of Figure 1 confirms this fact: on average, more drugs are approved the week before Thanksgiving than in any other (non-December) week in the United States. This pattern, however, does not hold outside the United States, where the week before Thanksgiving has, if anything, slightly fewer approvals than other nonDecember weeks. Similarly, panel D shows that the same idea holds for Lunar New Year, which is widely celebrated in China, Japan, and South Korea but not in the United States or European Union. Here, we see a spike in approvals the week before Lunar New Year only in Asian countries and not in the United States or European Union

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