This page is for both prospective students thinking about working with me and current advisees who want to understand how I like to operate. My goal is to help you become an independent researcher who produces rigorous, policy-relevant work.

1. Advising philosophy

I think of advising as a collaborative process of turning ideas into research. If you come with your own question, I will help you refine it, anchor it in the literature, and develop it into a feasible research design. If you prefer structure, I can also involve you in ongoing projects where the question is already defined and the task is execution. Both paths are valid — what matters is that you are motivated and moving forward.

That said, the ideas, the ownership, and the momentum need to come from you. I am here to shape and challenge your thinking, not to drive your research for you. With the rise of AI tools, simply writing code and running regressions is no longer enough. What distinguishes good research is the ability to evaluate results critically, interpret findings honestly, and communicate them clearly. That is what we work on together.

2. Meetings

I am flexible on frequency. We can meet weekly if that is what you need, or less often if you are in a productive stretch. What matters is that our time together is useful.

Schedule yourself. Send me a calendar invite — that is the most reliable way to guarantee I am available and prepared. Do not rely on informal agreements.

Come prepared. Before each meeting, distill your progress and open questions into a short set of slides — two to five is usually plenty. We will not run code together or work through model output in real time. The slides help me understand where you are, and force you to clarify what you actually found and where you are stuck.

Take notes and follow through. Keep a record of what we discussed and what you committed to. At the next meeting, those items should have moved — or you should be able to explain why. Progress means not revisiting the same open questions every time we meet.

3. Co-authorship

I am happy to co-author with students, but it is not a given. I equally support solo-authored work, and I will not claim a byline unless I feel I have made a substantial contribution beyond advising and commenting on drafts. If the research develops into something strong enough for journal submission and there is a genuine case for joining forces, I am glad to do that.

That said, I do not publish at all costs. Quality and integrity matter more to me than output. If maximizing the number of publications is your primary goal, please bring that up early so we can make sure our expectations are aligned.

4. On artificial intelligence

AI tools can be useful in research, and I have no objection to you using them. But be transparent about it, and never lose sight of the fact that you are responsible for everything that carries your name. If your analysis turns out to be wrong — or reflects sloppy practice — that is your problem, not the tool’s. Always understand what AI is doing on your behalf, and always verify the output.

On written communication: please write your own emails to me. If your English is not perfect, that is not a problem — mine was not always either. But writing through the imperfection is how you develop a voice, learn to communicate with peers, and build a genuine working relationship with your advisor. I will not respond to emails I believe were written by AI. No tool can substitute for that back-and-forth, and I am not interested in corresponding with one.

5. Letters of recommendation

I write many letters each year and am glad to support your applications. To make this manageable and give your letters the attention they deserve, please follow these guidelines:

  • Give me at least two weeks before your earliest deadline.
  • Send me one single email with all programs listed in order of your priority, with deadlines. If the list changes, send one updated email clearly marked as a revision.
  • No attachments, no spreadsheets — just the list in the body of the email, formatted like this:
1. University of X — PhD in Economics — Dec 15
2. Z State University — PhD in Agricultural Economics — Dec 20
3. ...