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Tilburg大學(xué)教授給自己博士生整理的一些寶貝!開(kāi)啟自己學(xué)術(shù)旅程!

 skysun000001 2022-04-25

稿件:econometrics666@126.com

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以下內(nèi)容真的非常有用,可以到文后進(jìn)入原文下載鏈接里的內(nèi)容。
大家一定熟悉,荷蘭蒂爾堡大學(xué)“全球經(jīng)濟(jì)學(xué)研究機(jī)構(gòu)排名”(Tilburg University Economics Ranking)。下面就是該大學(xué)計(jì)量經(jīng)濟(jì)學(xué)教授Tobias Klein整理的。

博士學(xué)位的一個(gè)顯著特點(diǎn)是,我們通常不會(huì)以結(jié)構(gòu)化的方式教學(xué)生如何完成某些任務(wù),比如寫(xiě)論文、學(xué)術(shù)交流以及其他許多事情。因此,丁伯根大學(xué)Tobias Klein教授收集了一些經(jīng)濟(jì)學(xué)和相關(guān)領(lǐng)域的博士生可能覺(jué)得有用的鏈接。

這里有很多很棒的東西,Tobias Klein教授想給你們一個(gè)開(kāi)啟自己學(xué)術(shù)旅程的起點(diǎn)。

學(xué)術(shù)寫(xiě)作
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:
  • John Cochrane's Writing tips for Ph.D. students
  • McCloskey: Economical writing (there is also a related freely available article)
  • Donald E. Knuth, Tracy Larrabee, and Paul M. Roberts  advice on Mathematical writing
  • Strunk and White: The elements of Style
  • Nikolov's Writing tips for economics research papers
  • Amanda Y. Agans's website with writing and presentation advice links
  • Bellemare's paper on academic writing (this will be part of the book Doing research: What you should have learned in grad school-but didn't)
  • Jesse Shapiro's Four steps to an applied micro paper
  • The Tilburg Science Hub pages on writing an academic paper, and on using the LaTeX front end LyX to be more productive (including a template for a paper)
Besides, a few years ago I have written some blog posts:
  • the challenge of writing
  • starting to work on a Ph.D. thesis
  • writing papers and theses
學(xué)術(shù)交流
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:
  • How to present your job market paper by Eliana La Ferrara
  • The ten commandments for how to give a seminar by Kjetil Storesletten
學(xué)術(shù)發(fā)表
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:
  • Nezih Guner: Getting your work published
  • Imran Rasul: Advice on the publishing process
編碼和工作流程
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:
  • the online version of the book Gabor's analysis
  • The Turing way
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.
專業(yè)建議和找工作
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
  • The hidden curriculum podcast
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
  • The European Economic Association job market guide
  • The American Economic Association website on the topic has a lot of useful material
經(jīng)濟(jì)學(xué)內(nèi)容相關(guān)資源
Then, there is a ton of material on doing research that is more content-related. I quite like:
  • Varian: How to build an economic model in your spare time
There are some blog posts of mine and some material in my econometrics lecture notes that Ph.D. students may still find useful:
  • econometrics, economic theory, and reduced forms
  • correct and incorrect models
  • Chapter 2 of my econometrics lecture notes for Ph.D. students on 'the big picture'
更多的鏈接
There are many great link collections if you are hungry for more:
  • Christoph Kronenberg's resource page on academic writing, citizenship, econometrics, coding, teaching, similar lists by others
  • Julian Reif's link collection on his Stata coding guide page
  • Alex Ebele's advice page
  • Jonathan Benchimol's link collection
  • Vikesh Koul's website on economics and data science
  • Marc Bellemare's suggested readings
  • Pietro Biroli's resources

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