Ph.D. Students

Since I started in Tilburg in 2007, I have been advising a number of Ph.D. students. I always found it particularly rewarding to see students grow during those years. Below you find a list of names.

A remarkable thing about doing a Ph.D. is that we normally don't teach students in a structured way how to perform certain tasks, like writing a paper, communicating, and many other things. Therefore, I collected a few links that Ph.D. students in economics and related fields may find helpful.

There is a lot of great stuff out there, here I'm trying to give you a starting point for your own journey. Please send me an email if you come across something that I may want to include.

Academic writing

A topic that comes up all the time is how to write a good paper. What I like about the first video on the left is that it conveys an important message: it does not have to take ages to write a first draft of a paper, one just has to get started and do it.

The book How to write a lot by Silva makes a similar point and gives some very useful advice on how one should organize the process of writing to be productive.

The second video is also great. Also there one important topic that is discussed is that one has to write for the reader, in a way the reader likes. Only in that way one can be effective.

Here are some other resources for academic writing that I find useful:

Besides, a few years ago I have written some blog posts:

Communication

A second related topic that is quite important is communication. It seems to me that Ph.D. students and junior researchers often feel that it expected to "be" technical and communicate using "the right jargon".

In the video on the left, Paul Krugman makes the point that it's not only harder, but also more effective to use simple language. I think this is to some extent also true for writing papers.

Somebody once told me that in the beginning a paper is often very simple and straightforward, because it consists of the main idea. Then it becomes all very complex, when lots of bells and whistles are added (and robustness checks, etc.). Ideally, it them becomes less complex again, but this is a lot of work. Distilling and communicating the essence of an argument and making it easy to understand is hard work. But I think it's time well-spent.

There is a whole website devoted to communicating economics. You can find it here.

Besides, you can check out:

Publishing

In the end of the day, it's all about publications.

Being economists, let's do a little bit of backward recursion. One thing that may be useful is to learn a bit more about the editorial process before even starting to write. In that respect, I really like the book Secrets of economics editors. It makes you realize that it's a messy process and that it pays off to write a paper as clearly and to the point as possible. Reviewers and editors are often extremely smart, but also extremely time-constrained. One should take that into account when writing.

The picture on the left is taken from the American Economic Association website. There is a very insightful post on The tyranny of the top five. It's really helpful to have a top 5 publication, over even better multiple ones, but in the end of the day journal space is scare, so let's not be obsessed about it. The related article raises some very good related points.

This is not the only thing one can see critically. Recently, the editors of Econometrica, Quantitative Economics, and Theoretical Economics have issued a statement in which they make some remarks and suggestions. I am very sympathetic.

But, ultimately, the publication culture and the norms are a given. So, in the end of the day, we have to do our best to be successful within that culture and given those norms. For this, there is a lot of advice out there, for instance:

Coding and workflows

I'm enthusiastic about our Tilburg Science Hub initiative because I think that there we give advice that is also particularly useful for Ph.D. students. It explains

  • how to code like a pro

  • how to set up a work flow for empirical project and automate things to save time

Other resources that are similar or complementary:

This connects nicely to the topics of reproducibility and, related, open science. Reproducibility means that part of a publication of empirical work or work that involves some form of computation is a replication package. This ultimately helps the "market for ideas" to work, as other researchers can see how things were done and can therefore assess it and see whether findings are robust, and also creates the right incentives to do things well in the first place. So, I'm all in favor.

We have made great progress as a profession in that respect. But it does mean that when we do empirical work, we should already take into account what is later required. The AEA Data and Code Availability Policy will probably become a de facto standard. So, it's a good idea to read it before even starting a new empirical project. I've been involved in designing replication packages checks for the Royal Economic Society. "Our" policy for The Econometrics Journal can be found here.

Professional advice and finding a job

The picture on the left is taken from the American Economic Association website with job listings for economists. I've participated in the job market to find my first job and then many times on the hiring side. Somehow it never looked like this ;)

Jokes aside, if you're up for a fun way of learning about all kinds of topics related to doing an (econ) Ph.D., check out

More professional advice:

  • Chris Blattman's advice in the bottom-right of his homepage

  • The Tilburg Science Hub page on how to work in teams using Scrum

There is a ton of advice out there on the academic job market, see for instance

Economics content-related resources

Then, there is a ton of material on doing research that is more content-related. I quite like:

There are some blog posts of mine and some material in my econometrics lecture notes that Ph.D. students may still find useful:

More links

There are many great link collections if you are hungry for more:

Past students of mine

1. Patrick Hullegie (joint supervision with Peter Kooreman), 2007-2012 (placement: VU Amsterdam)

2. Yufeng Huang (joint supervision with Bart Bronnenberg), 2011-2015 (placement: Rochester)

3. Noelia Bernal (joint supervision with Frederic Vermeulen), 2013-2014 (placement: University of Piura)

4. Yan Xu (joint supervision with Bart Bronnenberg), 2013-2017 (placement: Hong Kong Polytechnic University)

5. Roxana Fernandez (joint supervision with Jan Boone and Catherine Schaumans), 2013-2017 (placement: CREST)

6. Emre Koc (joint supervision with Eline van der Heijden and Lex Meijdam), 2013-2015 (placement: private sector)

7. Chen He (joint supervision with Bart Bronnenberg), 2014-2018 (placement: Shanghai Tech)

8. Laura Capera Romero (joint supervision with Jaap Abbring), 2015-2020 (placement: VU Amsterdam)

Current students

9. Ittai Shacham (joint supervision with Jaap Abbring), 2017-

10. Suraj Upadhyay (joint supervision with Martin Salm), 2017-

11. Rafael Greminger (joint supervision with Jaap Abbring), 2018- (233KUR 4-year research talent grant)

12. Maciej Husiatyński (joint supervision with Misja Mikkers), 2018-

13. Michela Bonani (as official promotor, the main advisors are Christoph Walsh and Florian Schütt), 2018-

14. Kadircan Çakmak (joint supervision with Bart Bronnenberg), 2019-

15. Jan Svitak (external, joint supervision with Jan Boone), 2020-

16. Tinghan Zhang (joint supervision with Christoph Walsh), 2020-

Future students

If you're currently in the CentER research master program in economics and interested in working on a topic that is related to my research interests, feel free to get in touch.

The best time to do that is sometime in your second year, but feel free to contact me earlier. Usually, you would write your research master thesis with me, maybe also your term paper, and then a revised version of that thesis would become the first paper of your thesis.