Most of the paper I’ll assign this term are in a standard format. Once you learn that format, you’ll be able to “read” a paper quickly (indeed, potentially more quickly than me because you’ll learn how to skip technical material and so so, whereas sometimes I’ll go through those details).
- Read the conclusion and then the introduction (doing it the other way around is OK, too). Sometimes they’ll be the same, wasting space and the reader’s energy (hey, in a short paper do you really need to repeat things?). The better written the paper, the easier it is to skim.
- Next — and I will take you through the process — scan the tables. This won’t always be helpful — the variable names may be computer-generated gibberish, which I find inexcusable in the days of ready editing. And it may not be clear what the tables are trying to convey — the title may be clear, but you won’t know which variables are central, and which are there as controls.
- Then … there will be a literature survey, something that will place the paper in context. Sometimes it will be terse, assuming you’re generally familiar with the field, and hence not very helpful. But try…
- Then comes stuff on methodology — what is the model, and perhaps details of what they’ll do in terms of statistical tests. If the paper is well-written, you can still read the first and last paragraphs, and (sometimes) the first and last paragraphs of sub-sections.
- You will find a description of data, typically with a table of sample means and so on. Always worth scanning.
- The penultimate section (or two ) will be the results. You really ought to skim. When there are two sections, one will be the main results, the other will consist of robustness checks.
The goal? — reading a paper in 5 minutes. Hard to achieve, but you may be able to approach that for your term paper, when you’re reading [scanning!] multiple papers on the same topic.
Addendum: you need to learn how to read tables, not a problem if you’ve had Econ 203 (econometrics), and comparatively easy when they use asterisks to denote statistical significance, harder when you only get a standard error. As noted above, I’ll take you through examples in class.