pereiragc / sper-spring24

Spring 2024 - Special Projects in Econ Researh

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Syllabus

Logistics

• Class meets Tuesdays 6:20pm - 8:20pm

• How to contact me:

  • ID is gap7077
  • Also surname + gdc at gmail dot com

• Groups:

  • Groups size is 2, 3 or 4.
  • There will be one final submission per group

• Main deadlines:

  1. Group formation: Friday, February 2nd
  2. Project plan: end of February
  3. Preliminary draft: April 26th May 3rd
  4. Final submission: May 14th, 2024

• Late submissions for the final project will not be accepted.

• Evaluation:

  • Class participation (30%)
  • Final submission (70%)

Class plan

• Each class will feature presentations from groups.
• The natural progression is to start presenting the existing literature related to your topic of interest, and gradually transition to your own research idea and what you have done so far to addres it.
• Details on presentations, such as how long each one will be, and how frequently each group will present, will depend on the final number of groups. Please be patient while I finalize this.

Project discussion

The final deliverable for this course is a write-up of your project. A submission will:

• identify a research question in Economics
• review the literature around that research question
• specify a method to address that question and apply it
• report the results and explain how they connect to extant literature

Let's dissect these steps.

• More often than not, identifying a topic involves starting with a broad theme and reviewing the literature around that, and narrowing down from there.
• Reading papers and not making notes is as good as not reading them. Having notes will not only help you absorb the content, but will also help reviewing it later. And your literature review could be a summary of these notes.
• Most students end up doing empirical work, although it is not a requirement.
  • Assembling and cleaning data to tackle a research question is cumbersome, so the earlier you start, the better.
  • NYU has fantastic data avaialble. Please check out the library's catalog. If thinking of using financial data, I'd recommend you familiarize yourself with the Bloomberg terminal, and also have a look at the WRDS database.
  • You shouldn't use the most sophisticated statistical method for sophistication's sake; rather, the simplest possible method that helps you answer your question is likely the best
• Results sometimes are inconsistent with your prior. In fact, most of the time, you'll get a "null result" (especially if you don't p-hack or data mine)). Although it's better to find something interesting, null results are acceptable given the time constraints.

One important note. Getting a project ready in ~13 weeks is difficult, and you won't be able to "wing it". Please reach out to me if you're experiencing roadblocks. The earlier you do this, the more time we'll have to troubleshoot.

Final submission format

I would expect the average project to be 20-30 pages, but there is no strict requirement. Brevity is appreciated. I strongly advise against writing redundant content for the sake of adding pages.

There is also no strict requirement for the structure, but I recommend following some variation of the below:

1. An introduction outling: motivation, research question, data, methodology, results, etc.

• the main objective is to communicate the message of your project in a concise, yet sufficiently detailed way.
• It should be appealing to a non-technical/non-expert reader.

2. A literature review, explaining how your approach and results connect with prior findings, and what's your specific contribution.

• This section should be a "big picture" review, and not about specific numbers. Leave that to the discussion of your results.
• There is no preferred citation format, but be consistent.

3. A description of your analysis

• In the case of empirical work, this should contain some information of the data you use. How did you collect it? Is it publicly available? Show some descriptive stats, tables, charts, etc.
• You can get as technical as you want here, but if you prefer, you can also leave more technical parts to an appendix.

4. A discussion of the results and interpretation of your analysis. Ideally, you will connect your findings to the extant literature.

You can include a conclusion if you want. Sometimes it feels a bit like boilerplate (like the "this paper is structured as follows..." part), but it's ok to have it since some people seem to expect that.

Again, this is all about having a compelling write-up: if you think following a different structure may communicate your work better, by all means, do that!

Some topics of interest

This list is supposed to expand as I think of things. It is not exhaustive. Students can pick any topic in Economics of their choosing.

Reach out to me if you want literature recommendations on any of the below.

• The 2010s era of low interest rates and its aftermath
  • Between 2010-2021, most developed economies had generally low risk-free rates. States and large corporations with "good credit" were able to issue debt (even long-term) at very little cost.
  • Central banks worldwide set short rates close to zero (some even negative) to try to stimulate economic activity; simultaneously, most of them expanded their balance sheets
  • The post-covid inflation led many central banks to raise rates and shrink balance sheets
  • This is a fertile ground for research ideas. A few questions that people are interested in:
    • Was there a structural reason for rates to be low between 2010-2021?
    • Have these structural forces changed in any way?
    • Why did investors accept such low compensation for long-term debt?
    • Are we out of the low rates world for good, or are rates going to converge back to low levels seen before?
• The post-covid inflation itself. What explains it?
  • A few views:
    • supply shocks was main driver
    • excessively stimulative fiscal/monetary policy => too much aggregate demand
    • "greedflation": abuse of market power
  • It would be interesting to unpack some of these channels and try to assess their quantitative importance. Note that those who like microeconomics and industrial organization may find this appealing as well.

List of tools/resources

Reference managers

Reference managers are a centralized database to which you save papers, organize them into categories. There are typically note-taking options as well. They also allow you to quickly create a bibliography afterwards, and produce ready-to-use citations.

The two big names here are Mendeley and Zotero. The latter is free software, less commercial and powerful, although it has a less fancy looking interface.

Podcasts

• Econtalk. This podcast features interviews with most big names in Economics, and goes back almost two decades (hence the period surrounding the 07-09 GFC/great recession). Given the enormous number of episodes, I suggested going to the list of guests and searching for some names you may be familiar with (e.g., Piketty, Chetty, Saez, Friedman, Lucas, etc.). Just so you're aware: there's a bit of a libertarian/free-market advocacy subtext to the podcast.

• Macro musings. More "technical", focused on macroeconomics and featuring many episodes on Fed policy, recent financial crises, the "plumbing" of the financial system. Most episodes will be linked to specific reports and research pieces and can be a good source for presentation topics.

• Odd lots. More of a finance/actualities kind of podcast, but discusses many topics of interest to economists.

Finding research papers

• NBER working paper series. This is a good way to be on top of how academics are thinking of current issues. Many of these papers end up published in top academic journals. I sign up for weekly emails and I recommend all of you do it as well.

• Google scholar. This is a great resource. Especially the "cited by" feature. Please familiarize yourself with google scholar if you haven't yet.

AI guidelines

TBA