Economic Research: Creating, Writing, Presenting

1. Economic Research: Creating, Writing, Presenting Maarten C.W. Janssen

2. Aim, Background of the Course • Assumption 1: You want to become known for your research in the international scene • Assumption 2: You have the necessary skills and knowledge to do research in your field • But this is by far not enough (only 50% of work) • You have to do your own marketing • Competition for attention • Backward induction

3. You can be very smart, but… • You are (very) unlikely to be in the position to create a new line of research • Research is building on others, linking to others, get feedback from others • Network is important, internally in the school (among PhD students), externally in your field • Collaboration can be inspiring • Being recognized is about how you connect to others; others will help you by giving their feedback

4. What is my message and for who? • Why is my work important? • Do I contribute to existing literature? If so, what? And why is this literature important? • Do I have a methodological contribution? What are the (potential) applications? • Do I contribute to an understanding of some real world issues? What other contributions are there? Are they complementary? Is my contributions better, more plausible, why? • Which people would be most interested in my work? Do I have different lessons for different audiences?

5. Lessons to be Learnt from JET editorial report #1 • Does my paper really matter? • There is some literature (quality chosen, price signals quality?) Is my modeling more appropriate? • What is wrong with previous papers? Do I have evidence of this? • If it is a theory paper, it should have useful machinery • Presentation is way too awkward • Equations too dense • Not adequate notation • What is a real result, what just some technical lemma?

6. Creating • Start naively: • I have a data set • I saw some paper and checked whether results hold under alternative assumption (robust) • I was struck with a newspaper article, everyday life • In the US without US adaptor • Taxi driver does not want to take you • Sitting with wife in the car, to buy gasoline or not? • Adverse selection is not a problem (bachelor student) • Anything is good, but soon you have to ask: what is my message and for who? • You may change the answer all the time, but you need to know where you intend to go to direct your research efforts • Remain open to alternative messages, interpretations • Read nontechnical, non economic literature; institutional detail • Can I publish about Russian economy in international journals?

7. During research • Think about what are the possible outcomes? • Theoretical research: Any equilibrium has certain properties? Or, there is an equilibrium with certain properties? • Empirical research: economic and statistical (in)significance? • Very different things • Is any outcome interesting? But for different reasons? • Expected cost/benefit analysis

8. Start simple • Theoretical research: what is the simplest model that you can think of that captures the phenomenon you want address? • What is essence? • US Electricity adaptor • Adverse selection • Empirical research: look at the data, do also simple descriptive statistics. • Helps enormously to focus main message, get it across. • Research is then mainly a robustness check (helping you to sharpen and deepen main results) • Adverse selection

9. What if you get the opposite result of what you expected? • Ask yourself always why you get a certain result? • Can I explain the result without going into technical details? • Is the result correct? (often, when you cannot explain there is a mistake—simulations?) • If so, what causes this unexpected result? • Is it an unimportant assumption that can be replaced by another one? • Or does my intuitive result only hold under some conditions (and can I understand these conditions intuitively) • Learn from intermediate results you get, relate back to main message? Should it be reformulated? • What are the crucial assumptions, what not?

10. Role of Simulations, Numerical results • Depend on area • Computational heavy (dynamic macro, or not) • But generally, • It is not considered as a substitute for a proof • It is nevertheless increasingly useful • Plot f(x) < 0, but not for f(x; α,β,γ) < 0 • Get an idea whether your intuitive result is correct or whether there are counterexamples • Aid understanding by giving a flavour of magnitude of effect (economic significance) • Draw pictures • Check robustness (where model is analytically untractable) • Be open and honest about which results are analytic and which you obtained with simulations • Do not hide unclear numerical analysis in proof in appendix, (especially not if you do not have clear intuitive explanation for your claim)

11. Read, but not too much • You have to be able to relate what you have been doing to what others have done • You have to know that • Especially in an oral presentation you cannot hide behind others “this is a crazy assumption, but others also make it” • Reading too much may prevent you to be original (as you tend to copy things you have read) • People do not want to hear (or read) endless literature review (Murayev; Boulatov, finance presentation) • Read at different stages differently • In beginning: did someone do what I intend to do • Later: how exactly do I differ? Which crucial assumptions, timing of events? What if I incorporate some of their assumption in my model? • You should be able to defend your crucial departures from the literature • Yankelevich presentation: behaviour of shoppers

12. Talking, talking, talking • You only understand your own research when you can explain it. • When you have to explain to someone else, you have to distinguish between main and side issues. • Often prevents loopholes in argumentation. • Talk during lunch, come to the office • Organize your own (brown bag) PhD research seminars where you discuss among each other!

13. Presenting, Writing • Rule 1: (almost) never follow the line of research that lead to the results • Rule 2: be enthousiastic about your results • If you say “I did some exercise and this is the result”…… you do not motivate people to pay attention to you. • Be honest: if there is a critical assumption, you cannot get rid of, or if you do not know what happens if you change it, say so • But give it a positive turn (future research, I would be a hero in this branch of literature if I could)

14. Presenting, Writing • Learn from others • Why did I like this paper, presentation? • Why did I get board? • How do I read other people’s work? • When do I loose concentration during a presentation? • Develop your own style

15. People’s time span of attention • 1 minute: people want to know whether it is worthwhile to listen, read further • What is the topic, what can they gain? • Title (abstract) is very important • 5-10 minutes: which main results do you have, what do you add to what is known • Introduction should contain this • 1-2 hours: get into more details, how do you get these results, which methodology, which data, model?

16. Titles • Do they attract attention? • Convey topic of the paper, main result? • Examples: • Going where the Ad Leads you • Do Auctions Select Efficient Firms? • Can we Rationally Learn to Coordinate? • Non-exclusive Conventions and Social Coordination • Signaling Quality Through Prices under Oligopoly • Job market papers at HSE • Can you trust your broker? • If you pose a question, • It should be attracting attention • You should answer it clearly, and it should have element of surprise

17. Introductions I • Most critical part of a paper, usually rejection is based on Introduction only • Requires writing, rewriting, ….., 5-6 times • How to start, where to explain your insights • Get as quickly as possible to your results • Start with the most key papers and what they lack if you have a pure theory, methodology contribution • Start with describing real world issue and what you aid in our understanding of it (do literature review then afterwards, and sometimes even before the conclusions—if your breakthrough can only be really described after you have presented it) • Adverse selection paper as example

18. Introductions II • Describe main features of your set-up concisely • Describe your main results • Why they are interesting (adds to methodology, adds to understanding)? • Why you get it (you should be able to explain the main mechanism(s), not I worked hard to crack the math puzzle and this is the answer • Only a few readers will ever go through all your proofs (even referees seldom do): you have to write so that people understand it and believe result once you have made them think about it. • Relate to several literatures (if possible), to show breadth.

19. What comes next? • Model? • Often yes, but try to be creative: • A simple 2x2 example capturing the main features of paper (Kandori, Malaith, Rob, 1993 Ectrica; 2010 EJ paper)? • Extensive Literature Review? • Description Institutional Context or Data? • Literature review should not be a list of short statements about other papers. • Make a story with your paper and results as the central theme. Start with fundamental papers, say how other papers have built on it and how you continue (or break with that line)

20. Once you get to a formal model • Take the lessons of Thompson to heart • (Here is one example where an oral presentation is different from a written one) • Notation • Follow existing literature as much as possible (f = ma) • Use natural symbols • Is notation essential (if used only once or twice……) • Explain assumptions and their interpretation (are they usually met? What is their role ….) • And if you can do without the word assumption, it is better. • We assume there are two periods. In each of these periods, individuals are assumed to work and we introduce the assumption that the utility function is concave…. Or • Consider a two-period economy where individuals have a concave utility function and work in every period.

21. Present Formal Results • In main body of the text, people want to see things that stick out (propositions, hypotheses, results, statements) • Indicate them as such (with open space) • Take care these are very precisely formulated • Make sure that they correspond to the main results of the paper as explained in the Intro. Déjà vu, but in a more formalized manner • I have seen main results being presented somewhere in a footnote (and vice versa) • And spend at last one paragraph introducing the propositions and (after stating them) explaining them. • Think about proofs in appendix, properly bordered in the text, or informally presented as part of the flow of the text (what is audience, what is purpose of proof?)