The course"s topic is unemployment. The course presents facts about the labor market and unemployment, models to describe unemployment, and policies to tackle unemployment. The course addresses several questions:

• Why do we care about unemployment?
• Why does unemployment exist?
• Why does unemployment vary over the business cycle?
• What is the socially efficient rate of unemployment?
• How should policies respond to fluctuations in unemployment?

• Course material
• Course portal
• Discussion forum

• Tuesday–Thursday, 3:20pm–4:55pm
• Cowell Academic Building, room 131

• Section A: Wednesday, 1:20pm–2:25pm, in Merrill Academic Building, room 132
• Section B: Friday, 2:40pm–3:45pm, in Baskin Engineering Building, room 165

• Pascal Michaillat
• Associate Professor of Economics, UCSC

• Ananyo Brahma
• PhD student in Economics, UCSC

Office hours are conducted in-person. Office hours are first-come-first-served: there is no need to sign up. Feel free to come to office hours to discuss concepts covered in the lectures and readings, discuss your research project, or talk about any other course-related matters:

• Professor office hours: Wednesday, 4:00pm-5:00pm, in Engineering 2 Building, room 437
• TA office hours: Monday, 2:00pm–4:00pm, in Engineering 2 Building, room 403B

In addition to office hours, we will communicate using GitHub Discussions. This collaborative discussion forum is designed to get you help quickly and efficiently. To take full advantage of this communication channel, make sure to:

• Create a free GitHub account. Several GitHub services are available to students for free, so sign up with your UCSC email address to benefit from those.
• Watch the course repository on GitHub to be notified when any new material is uploaded, new discussions are started, and new contributions are made to ongoing discussions. To watch the repository, click on the Notifications button at the top of the GitHub repository, sign in, and select All Activity.
• Rather than sending emails, please post your questions and queries on GitHub, and participate whenever you can: ask and answer questions, share updates, have open-ended conversations, and follow along on decisions affecting the course.

This is a flipped course, so at home you will watch lecture videos and read articles. Class time will be used to discuss the course material and to work on the research projects.

At home, you will have to watch the following lecture videos:

• Before Thursday 9 January: videos in Introduction
• Before Thursday 16 January: videos in Labor market facts and matching function
• Before Thursday 23 January: videos in Matching model of the labor market
• Before Thursday 30 January: videos in Wage functions
• Before Thursday 6 February: videos in Unemployment fluctuations
• Before Thursday 13 February: videos in Frictional and rationing unemployment
• Before Thursday 20 February: videos in Efficient unemployment and unemployment gap
• Before Thursday 27 February: videos in Labor-demand policies
• Before Thursday 6 March: videos in Unemployment insurance

At home, you will also have to go over the following readings:

• Before Tuesday 14 January: main readings in Introduction
• Before Tuesday 21 January: main readings in Labor market facts and matching function
• Before Tuesday 28 January: main readings in Matching model of the labor market
• Before Tuesday 4 February: main readings in Wage functions
• Before Tuesday 11 February: main readings in Unemployment fluctuations
• Before Tuesday 18 February: main readings in Frictional and rationing unemployment
• Before Tuesday 25 February: main readings in Efficient unemployment and unemployment gap
• Before Tuesday 4 March: main readings in Labor-demand policies
• Before Tuesday 11 March: main readings in Unemployment insurance

The main readings cover important material on which the lectures are based. You should read them from beginning to end, attempt to reproduce the key steps of the derivations, and remember the key results. Additional readings are also be provided in each section. These readings provide additional theoretical results, empirical evidence, some background, and may provide inspiration for your research. If you plan to do a PhD in economics, you are encouraged to go over the additional readings as well.

Sections will be devoted to solving multiple-choice quizzes based on lecture material. The quizzes will put the material from lecture into practice. Sections will cover the following material:

• Wednesday 8 January & Friday 10 January : no section
• Wednesday 15 January & Friday 17 January: introduction to research tools (GitHub, LaTeX, MATLAB, R, Python)
• Wednesday 22 January & Friday 24 January: quizzes on Labor market and Matching function
• Wednesday 29 January & Friday 31 January: quizzes on Matching model of the labor market
• Wednesday 5 February & Friday 7 February: quizzes on Wage functions
• Wednesday 12 February & Friday 14 February: quizzes on Unemployment fluctuations
• Wednesday 19 February & Friday 21 February: quizzes on Frictional and rationing unemployment
• Wednesday 26 February & Friday 28 February: quizzes on Efficient unemployment and unemployment gap
• Wednesday 5 March & Friday 7 March: quizzes on Labor-demand policies
• Wednesday 12 March & Friday 14 March: quizzes on Unemployment insurance

The section quizzes are designed to help review and assimilate the content from lecture. This content provides the building blocks that you will use in your research project. As such, mastering the lecture content is key, and the section quizzes are here to help you do that.

Most Tuesday class meetings will be devoted to discussing readings.

To lead the discussion, students will give 10-minute presentations that summarize the readings for the week. Each student will give several presentations during the quarter (the exact number of presentations will depend on the enrollment). The presentations will be scheduled in advance.

Each presentation should have 6 slides addressing the following questions:

1. CONTEXT: How does the paper relate to the lecture material? How does it contribute to the course material?
2. QUESTION: What is the research question addressed by the paper?
3. ANSWER: What are the main elements of the answer to the research question?
4. ILLUSTRATION: Illustrate graphically the answer to the research question or an interesting mechanism discussed in the paper.
5. POSITIONING: How does the material in the paper contribute to the previous literature?
6. CONCLUSION: What are the limitations of the answer provided in the paper? How could the answer be improved? What else would you have liked to know or learn on the topic?

Presentation slides must be written in LaTeX and compiled to a PDF. Slides should be submitted to Ananyo by email before noon on the day of the presentation.

Most Thursday class meetings will be devoted to research. Indeed, this is a research-intensive course, which will serve as good preparation for students interested in pursuing further studies in macroeconomics, especially a PhD.

In this course you will shift away from learning the results of other peoples" research into learning how to conduct your own research. You will therefore devote a good part of the course to active research. You will learn:

• How to select a research question
• How to develop and refine the answer to your research question
• How to position your paper in the literature

By the end of the course, you will have experienced all the stages of a research project and completed a short research paper on a topic related to unemployment.

One of the main objectives of the course is to complete a short research paper. A good research paper should do the following:

1. Develop a well-posed, original research question
2. Answer the research question using a combination of theory, simulations, and empirical analysis
3. Position the paper in the prior literature

Your research paper will be evaluated based on how well it accomplishes these three tasks.

More specifically, a good research paper should adhere to the following guidelines:

1. It should describe in details the research question you are answering, and explain why it is an original and interesting question.
2. It should provide a thorough review of the prior literature, and it should explain how the paper advances that literature.
3. It should describe the model, data, empirical strategy, and computational method used to answer the questions.
4. It should describe the results obtained in the analysis using diagrams, tables, and figures.
5. It should discuss the limitations of the current analysis, and how the limitations could be addressed in the future.

You should work on your research project on your own. However, you should feel free to discuss methods and literature, and to elicit feedback, from your peers.

Any research question related to unemployment is acceptable for the research paper. The research question could involve unemployment directly or related labor-market phenomena (nonparticipation, part-time employment, underemployment, job vacancies, unemployment insurance, etc.). The question can look at the US labor market, at national labor markets abroad, or at local labor markets (in a specific US states, specific commuting zones, or specific industries).

You are welcome to work on any research question that you would like. If you are looking for some inspiration, I would encourage you to look at the readings for the course. There are several ways to write research papers based on any of the papers assigned as reading:

• Reproduce the empirical or numerical results of the paper
• Extend the empirical or numerical results of the paper by looking at different outcomes or implications of framework
• Extend the empirical or numerical results of the paper, using more recent data or data for different countries
• Modify the empirical or numerical results of the paper, using different assumptions or different computational or statistical methods

In one of the course readings, Shimer (2005) estimates the fluctuations in unemployment and vacancies in the US, and simulates the fluctuations in a DMP model. In your research paper, you could:

• Reproduce the estimation
• Reproduce the simulations
• Redo the estimation or simulation using newer US data (Shimer stops in 2003) or older US data (Shimer starts in 1951, but data are now available from 1930)
• Redo the estimation in a different country
• Redo the simulation by calibrating the DMP model for a different country
• Redo the simulation by using a different matching model, such as a model with wage rigidity or job rationing

• Thursday 6 February: presentations of project outlines in class
• Thursday 20 February: presentations of early results in class
• Tuesday 11 March & Thursday 13 March: presentations of final results in class
• Thursday 20 March at noon: final paper due by email

The project outline should be presented in 10 minutes with 5 slides.

• Slide 1 – Research question: what are you asking in the project & why that matters
• Slide 2 – Positioning: what we already know & what we do not yet know
• Slide 3 – Research methodology: how you will address the research question
• Slide 4 – Overview of what you have so far: data & model & code & other ideas
• Slide 5 – Existing & projected hurdles & next steps

It is fine to propose several possible research questions if you are unsure. Presentation slides must be written in LaTeX and compiled to a PDF. Slides should be submitted to Ananyo by email before noon on the day of the presentation.

Early results should be presented in 10 minutes with 6 slides.

• Slide 1 – Rapid review the research question & project positioning
• Slides 2 + 3 – Detailed presentation of the research methodology, including data & model
• Slides 4 + 5 – Detailed presentation of the early results, with tables & graphs
• Slide 6 – Existing research hurdles & next steps

Presentation slides must be written in LaTeX and compiled to a PDF. Slides should be submitted to Ananyo by email before noon on the day of the presentation.

Final results should be presented in 10 minutes with 6 slides.

• Slide 1 – Review the research question & project positioning
• Slide 2 – Review of the methodology, including data & model
• Slides 3 + 4 + 5 – Detailed presentation of final theoretical & empirical & computational results, with tables & graphs
• Slide 6 – Implications of the results, for instance for policy, & limitations

Presentation slides must be written in LaTeX and compiled to a PDF. Slides should be submitted to Ananyo by email before noon on the day of the presentation.

Your research paper should be short and follow the guidelines:

• Manuscripts must be less than 6,000 words. The wordcount applies to the main body of the text and title page but excludes the reference list.
• Manuscripts should contain no more than 5 exhibits (tables and figures). Individual exhibits are limited to one page each.
• Manuscripts must include an abstract of 150 or fewer words.
• Papers must be self-contained. Specifically, a reader should be able follow the analysis in the paper and be convinced it is correct and coherent from the main text alone, without consulting the appendix. For empirical work, the main text should include relevant information about data sources, variable definitions and construction, the estimating equations, and any other information needed to understand and assess each exhibit in the main text. For theoretical work, proofs should typically be contained in the paper. This is the case when the proof itself provides insight into the paper"s argument or when the method of proof is innovative.

The research paper must be written in LaTeX, compiled to a PDF, and submitted to Ananyo by email before noon on the due date.

Any code and data used in the analysis must be submitted with the paper. This applies both to code used to simulate models and to code used to analyse data. The easiest way to submit the code is to create a public GitHub repository, upload code and data there, and share the link with Ananyo. Another way is to place all code and data to a folder, zip it, and email it to Ananyo. The code should be commented so that a reader can understand how to code works. The code should also work out of the box, so that the entire analysis can be reproduced with one prompt. Please include a README file describing all files and explaining how to run the code and obtain the results. Please use the following code & data repository as a template: https://github.com/pmichaillat/feru.

Your grade will be based on the quality of the research project and your participation in various course activities. The contribution to the total grade of 100 points is as follows:

• Participation and general community building: 10 points
• Answers to section quizzes: 10 points
• Presentations of course readings: 30 points
• Presentation of project outline: 10 points
• Presentation of early results: 10 points
• Presentation of final results: 10 points
• Final paper (including code & data): 20 points

Letter grades will be computed based on your total grade using a standard curve.

The course relies on basic mathematical methods such as unconstrained and constrained optimization, and linear and nonlinear differential equations—including phase diagrams.

So you are expected to have good command of this material. Appropriate courses in the department of Applied Mathematics will provide a great preparation for the course. In additional, a good reference for the material used in the course is Essential Mathematics for Economic Analysis, by K. Sydsaeter, P. Hammond, A. Strom, and A. Carvajal.

See also these lecture notes for a review of the material—although not everything covered in these notes is required for the course.

There is no textbook for this course, but several books might be helpful to write your research paper.

First and foremost, a good research paper needs to have a good structure. A good reference on how to structure your paper is The Little Book of Research Writing by V. Chaubey.

Scientific papers involve an elements that does not appear in other writings but is fundamental to communicate scientific ideas: graphs. It is important to make clear, clean, and meaningful graphs. A great reference on how to create compelling graphs is The Visual Display of Quantitative Information by E.R. Tufte.

Once your paper has a good structure and good graphs, it does not hurt to have a decent style—to help readers go through the paper. The canonical reference on style is The Elements of Style by W. Strunk and E. B. White.

Whatever you write, it is important to follow the rules and conventions of the English language. The canonical manual—followed by most US journals—is the Chicago Manual of Style. You should consult it if you have any question about English writing, rules, conventions, and style.

LaTeX is the best system to typeset scientific research. In particular, it allows to typeset mathematical expressions, insert tables and figures with results, and manage scientific references. This is why you are asked to write your presentation slides and research paper in LaTeX. If you continue on a research path, you will need to use LaTeX, so it is good to learn how to use it now.

LaTeX templates are available on GitHub to help you write your presentations and research paper:

• LaTeX template for research paper
• LaTeX template for research presentations

These templates follow typographical best practices and have a minimalist design. You can also use these LaTeX commands in conjunction with the templates to obtain mathematical expressions that are more legible and easier to manipulate.

If you are new to LaTeX, feel free to use Overleaf, for which UCSC supplies professional accounts. Overleaf makes it easy to produce research paper and research presentations in LaTeX directly from your web browser. You can use the above templates with Overleaf.