Writing Tips for Ph. D. Students
John H. Cochrane1,2
Graduate School of Business
University of Chicago
5807 S. Woodlawn
Chicago IL 60637.
773 702 3059.
john.cochrane@gsb.uchicago.edu
http://gsbwww.uchicago.edu/fac/john.cochrane/research/Papers/
June 8, 2005
1 Always
put your contact info on the front page so that people can find your paper and send
you comments! It’s the 21st century — get a web page. If your paper is ready for a faculty member
to read it, it should be on your webpage. Put the date on the paper so people know if they are
reading a new version.
2 I thank Toby Moskowitz for helpful comments.
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Organization
Figure out the one central and novel contribution of your paper. Write this down in one
paragraph. As with all your writing, this must be concrete. Don’t write “I analyzed data
on executive compensation and found many interesting results.” Explain what the central
results are. For example, Fama and French 1992 start their abstract with: “Two easily
measured variables, size and book-to-market equity, combine to capture the cross-sectional
variation in average stock returns associated with market β, size, leverage, book-to-market
equity, and earnings-price ratios.”
Distilling your one central contribution will take some thought. It will cause some pain,
because you will start to realize how much you’re going to have to throw out. Once you do
it, though, you’re in a much better position to focus the paper on that one contribution, and
help readers to get it quickly.
Your readers are busy and impatient. No reader will ever read the whole thing from start
to finish. Readers skim. You have to make it easy for them to skim. Most readers want to
know your basic result. Only a few care how it is different from others. Only a few care if
it holds up with different variable definitions, different instrument sets, etc.
Organize the paper in “triangular” or “newspaper” style, not in “joke” or “novel” style.
Notice how newspapers start with the most important part, then fill in background later for
the readers who kept going and want more details. A good joke or a mystery novel has a
long windup to the final punchline. Don’t write papers like that — put the punchline right
up front and then slowly explain the joke. Readers don’t stick around to find the punchline
in Table 12.
The vast majority of Ph.D. student papers and workshop presentations (not all by students!) get this exactly wrong, and we never really find out what the contribution of the
paper is until the last page, the last table, and the last 5 minutes of the seminar.
A good paper is not a travelogue of your search process. We don’t care how you came to
figure out the right answer. We don’t care about the hundreds of things you tried that did
not work. Save it for your memoirs.
Abstract
Most journals allow 100-150 words. Obey this limit now. The main function of the
abstract is to communicate the one central and novel contribution, which you just figured
out. You should not mention other literature in the abstract. Like everything else, the
abstract must be concrete. Say what you find, not what you look for. Here too, don’t write
“data are analyzed, theorems are proved, discussion is made..”
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Introduction
The introduction should start with what you do in this paper, the major contribution.
You must explain that contribution so that people can understand it. Don’t just state your
conclusion: “My results show that the pecking-order theory is rejected.” Give the fact behind
that result. “In a regression of x on y, controlling for z, the coefficient is q.”
The first sentence is the hardest. Do not start with philosophy, “Financial economists
have long wondered if markets are efficient.” Do not start with “The finance literature has
long been interested in x.” Your paper must be interesting on its own, and not just because
lots of other people wasted space on the subject. Do not start with a long motivation of
how important the issue is to public policy. All of this is known to writers as “clearing your
throat.” It’s a waste of space. Start with your central contribution.
Three pages is a good upper limit for the introduction.
I don’t write a “roadmap” paragraph: “Section 2 sets out the model, section 3 discusses
identification, section 4 gives the main results, section 5 checks for robustness, section 6
concludes.” It seems a waste of space; readers will figure it out when they get there and
I save a paragraph against the editor’s page count. Make your own mind up about this
question; but realize it’s not mandatory.
Literature review
Do not start your introduction with a page and a half of other literature. First, your
readers are most interested in just figuring out what you do. They can’t start wondering if
it’s better than what others have done until they understand what you do. Second, most
readers do not know the literature. It’s going to be hard enough to explain your paper in
simple terms; good luck explaining everyone else’s too.
After you’ve explained your contribution, then you can write a brief literature review.
Make it a separate section of otherwise set it off so people can skip it who aren’t interested.
Remember, it will be very hard for people to understand how your paper is different from
others’ given that they don’t understand your paper yet, and most of them have not read
the other papers.
Be generous in your citations. You do not have to say that everyone else did it all wrong
for your approach and improvements to be interesting.
Literature reviews have gotten way out of hand. It is not necessary to cite every single
paper in the literature or to write a Journal of Economic Literature style review. The main
point of the literature review should be to set your paper off against the 2 or 3 closest
current papers, and to give proper credit to people who deserve priority for things that
might otherwise seem new in your paper. Some people worry a lot about strategic citations;
choosing citations to hint to editors who they should assign as referees and adding loads of
citations to make sure referees see themselves. Whatever one thinks of these practices, we
can agree you should get rid of all the fluff in the final version.
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Body of the paper
Your task now is to get to the central result as fast as possible. Most papers do precisely
the opposite: They have a long motivation, a long literature review, a big complex model
that then gets ignored, descriptive statistics, preliminary results, a side discussion or two
and then finally Table 12 of “main estimates.” By then we’re all asleep.
Here’s the rule: There should be nothing before the main result that a reader does not
need to know in order to understand the main result.
Theory
In most papers, the “main result” is empirical. There may be some theory or a model,
but if you (or the editor!) ask “does this paper expand our knowledge of economic theory?,”
the answer is “no.” The theory is there to help understand the empirical work. Following
the rule, then, the theory must be the minimum required for the reader to understand the
empirical results.
Do not write a “general” model and then “for the empirical work, we now specialize the
general shock process to an AR(1), we use only 2 firms rather than a continuum, we assume
agents have quadratic utility,” etc. Work out only the specialized model that you actually
take to data.
Empirical work
Start with the main result. Do not do warmup exercises, extensive data description
(especially of well-known datasets), preliminary estimates, replication of others’ work. Do
not motivate the specification that worked with all your failures. If any of this is really
important, it can come afterwards or in an appendix.
You will mightily resist this advice. If you can’t follow it, at least do not put anything
before the main result that a reader does not need to know in order to understand the main
result.
Follow the main result with graphs and tables that give intuition, showing how the main
result is a robust feature of compelling stylized facts in the data. Follow that with limited
responses to potential criticisms and robustness checks. Most of those should end up in your
web appendix.
Conclusions
Really, a conclusions section should not be necessary. If you did a good job of explaining
your contribution in understandable prose in the introduction, and then documenting those
claims in the body of the paper, (writing in good triangular style), then saying it all over
again is pointless. I tried omitting the conclusions section a few times, though, and this was
too radical for editors and referees. It is true that some people skip to the conclusion to
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look for the main result, but that’s because they are used to authors who don’t explain it
well enough in the introduction.
Thus, conclusions should be short and sweet. Do not restate all of your findings. One
statement in the abstract, one in the introduction and once more in the body of the text
should be enough! You can include a short paragraph or two acknowledging limitations,
suggesting implications beyond those in the paper. Keep it short though — don’t write your
grant application here outlining all of your plans for future research. And don’t speculate;
the reader wants to know your facts not your opinions.
Appendices
Appendices are a great tool. Take that delicious section that has so many insightful
comments on the literature, the general version of the model, the 57 robustness exercises
that you did, and dump them in to an appendix. This is a good way to get them out of the
paper. Eventually you’ll dump them out of the appendix too.
Seriously, careful authors, referees and critics often want to document that the main result
is robust to various other ways of doing things. You have to do that, but once you’ve verified
that it does not make that much difference and you’ve found the one best way of doing
things in your main result, it isn’t worth space in the paper to present all the checks and
variations. Appendices are a great way to solve this problem, and you can just summarize
all the things you did in the paper. You can put the appendix on your and the journal’s
website. (“Bond risk premia” with Monika Piazzesi is an example of a web-appendix gone
wild.)
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Writing
Keep it short
Keep the paper as short as possible. Every word must count. As you edit the paper ask
yourself constantly, “can I make the same point in less space?” and “Do I really have to say
this?” Final papers should be no more than 40 pages. Drafts should be shorter. (Do as I
say, not as I do!) Shorter is better.
Don’t repeat things. In other words, if you’ve said it once, you don’t have to say it again.
Most of all, it uses up extra space and reader’s patience to have to see the same point made
over and over again. So, once again, repetition is really a bad idea. (Get the picture?!) “In
other words” is a sign of trouble. Go back and say it once, right.
General points
Follow the rule “first describe what you do, then explain it, compare it to alternatives,
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and compare it to others’ procedures” at the micro level as well as the macro level. For
example, in describing a data transformation, just start with, say, “I adjust income by the
square root of household size”. Then tell us why adjusting is important, and then talk about
different adjustment functions. Most writers do all this in the reverse order.
Previews and recalls are a good sign of poor organization. “As we will see in Table 6”
“Recall from section 2” “this result previews the extra analysis of section 4” all often mean
you didn’t put things in the right order.
Strive for precision. Read each sentence carefully. Does each sentence say something,
and does it mean what it says?
Document your work. A fellow graduate student must be able to sit down with your
paper and all alone reproduce every number in it from instructions given in the paper, and
any print or web appendices. The usual student paper falls short here. There is a sea of
verbiage, but I can’t figure out how the central table of results was computed, how standard
errors were computed, how a simulation was conducted, etc.
Simple is better. Most students think they have to dress up a paper to look impressive.
The exact opposite is true: The less math used, the better. The simpler the estimation
technique, the better.
Footnotes
Don’t use footnotes for parenthetical comments. If it’s important, put it in the text. If
it’s not important, delete it. Parenthetical comments in footnotes usually mean you haven’t
organized your ideas; you haven’t figured out where to put this thought in a proper linear
sequence. Do you really want the reader to stop and read this? Then it should be in the
text. Do you think the average reader should not stop? Then delete the footnote. Obviously,
lots of parentheses are just as bad as lots of footnotes.
Use footnotes only for things that the typical reader genuinely can skip, but a few readers
might want to have attached to the current point. Long lists of references, simple bits of
algebra, or other documentation are good candidates for footnotes.
Tables
Each table should have a self-contained caption so that a skimming reader can understand
the fact presented without having to go searching through the text for things like the definitions of Greek letters. Don’t go nuts here; some captions are longer than the paper. In my
opinion, you can leave out details of variable construction and similar items. “Book/market
ratio” is fine; you don’t have to tell me that you got book values in June from Compustat.
The goal is to allow a skimming reader to understand the table, not to substitute for the
detailed documentation that must be in the paper somewhere.
The caption of a regression table should have the regression equation and the name of
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the variables, especially the left hand variable.
No number should appear in a table that is not discussed in the text. You don’t have to
mention each number separately; “Row 1 of Table 3 shows a u-shaped pattern” is ok. “Table
5 shows summary statistics” (period) is not ok. If it’s not worth writing about in the text,
it’s not worth putting in the table.
Use the correct number of significant digits, not whatever the program spits out. 4.56783
with a standard error of 0.6789 should be 4.6 with a standard error of 0.7. Two to three
significant digits are plenty for almost all economics and finance applications.
Use sensible units. Percentages are good. If you can report a number as 2.3 rather than
0.0000023, that’s usually easier to understand.
Figures
Good figures really make a paper come alive, and they communicate patterns in the data
much better than big tables of numbers. Bad or poorly chosen figures waste a lot of space.
Again, give a self-contained caption, including a verbal definition of each symbol on the
graphs. Label the axes. Use sensible units. Don’t use dotted line types that are invisible
when reproduced. Don’t use dashes for very volatile series.
Writing tips
The most important thing in writing is to keep track of what your reader knows and
doesn’t know. Most Ph.D. students assume far too much. No, we do not have the details
of every paper ever written in our heads. Keep in mind what you have explained and what
you have not.
The reader usually wants most of all to understand your basic point, and won’t start
criticizing it before he or she understands it. That’s behind my advice to first state and
explain what you do, and save defending it and comparing it to other approaches until much
later.
Use active tense. Not: “it is assumed that τ = 3”, “data were constructed as follows..”
Gee, I wonder who did that assuming and constructing? Search for “is” and “are” in the
document to root out every single passive sentence.
“I” is fine. Don’t use the royal “we” on a sole-authored paper. “I assume that τ = 3.” “I
construct the data as follows.” If it seems like too much “I,” you can often avoid the article
altogether. For example, I think it’s ok to write “Table 5 presents estimates” rather than “I
present estimates in Table 5”, though a purist might object to making a Table the subject of
a sentence. I use “we” to mean “you (the reader) and I,” and “you” for the reader. “We can
see the u-shaped coefficients in Table 5” or “You can see the u-shaped coefficients” is much
better than “The u-shaped coefficients can be seen” (passive) or “one can see the u-shaped
coefficients” (who, exactly?)
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Much bad writing comes down to trying to avoid responsibility for what you’re saying.
That’s why people resort to passive sentences, “it should be noted that”, poor organization
with literature first and your idea last, and so on. Take a deep breath, and take responsibility
for what you’re writing.
Present tense is usually best. You can say “Fama and French 1993 find that” even though
1993 was a while ago. The same goes for your own paper; describe what you find in Table
5 not what you will find in Table 5. Most importantly, though, keep the tense consistent.
Don’t start a paragraph in past tense and finish it in the future.
Use the normal sentence structure: subject, verb, object. Not: “The insurance mechanisms that agents utilize to smooth consumption in the face of transitory earnings fluctuations are diverse” Instead: “People use a variety of insurance mechanisms to smooth
consumption..” (I also changed the starchy “agents” to the concrete “people,” and the simple “variety” rather than the fancy “diverse.” Actually, this whole sentence probably should
be dumped; it was introducing a paragraph that described the mechanisms. It’s a throatclearing sentence that violates the rule that every sentence should mean something. The fact
that people use a variety of mechanisms is not big news, the news is what the mechanisms
are.)
Avoid technical jargon wherever possible.
Writing should be concrete, not abstract. (Insert concrete examples.)
Little writing tips
Don’t use adjectives to describe your work: “striking results” “very significant” coefficients, etc. If the work merits adjectives, the world will give them to you.
If you must use adjectives, don’t use double adjectives. Results are certainly not “very
novel.”
Use simple short words not big fancy words. “Use” not “utilize.” “several” not “diverse”.
It is usually the case that most good writers find that everything before the “that” should
be deleted from a sentence. Read that sentence again starting at “Everything”: it’s true,
isn’t it? “It should be noted that” is particularly obnoxious. Just say what you want to say.
“It is easy to show that” means that it isn’t. Search for “that” in the document to get rid
of these. Similarly, strike “A comment is in order at this point.” Just make the comment.
These phrases also violate the rule that each sentence should mean what it says. Is the point
of the sentence really that “it should be noted?” Or is this just a wimpy way to bring up
the topic?
Clothe the naked “this.” “This shows that markets really are irrational...” This what?
“This” should always have something following it. “This regression shows that....” is fine.
More generally, this helps (no, that should be “this rule helps,” right?) you to avoid an
unclear antecedent to the “this.” Often there are three or more things in recent memory
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that “this” could point to.
Hyphens are widely misused. Here’s the rule from the JFE style sheet: “Hyphens are
used for true compound modifiers before the noun (e.g., after-tax income, risk-free rate,
two-day return, three-digit SIC code, value-weighted index) unless part of the compound
modifier is an adverb ending in ‘ly’ (e.g., previously acquired subsidiary, equally weighted
index, publicly traded stock). When there is no risk of misinterpretation, the hyphen can be
omitted, but the treatment must be consistent throughout the paper.” Note the hyphen is
optional, so you don’t have to construct monstrosities like “continually-rebalanced-equallyweighted portfolio.” Don’t use hyphens in other circumstances, e.g. “The paper focuses on
small-stocks.”
People forget Greek letter definitions. If you define them once in an obscure part of the
text and then use naked references (“θ = 3 gives the best fit”) no one will know what you’re
talking about. Define them clearly in an easy-to-find place. It’s best to give them a name
too, and then remind people of the name and the number (“I find the best fit when the
elasticity of substitution θ equals 3.”) This is the one place where a little repetition isn’t
bad. If you’ve reminded them of the name in the last paragraph or two, however, you can
use the naked letter.
Strike “I leave x for future research.” We’re less interested in your plans and excuses than
we are in your memoirs.
Never use the words “illustrative test” or “illustrative empirical work.” Never do illustrative work. Do real empirical work or don’t do any at all. Illustrating technique with
empirical work you don’t believe in is a waste of space. Even if you do it, there is no faster
way to get readers to fall asleep than to tell them that what you’re doing doesn’t really
matter.
You don’t need to “assume” things about a model. Don’t write “I assume that consumers
have power utility” (And, of course, don’t write “it is assumed that utility is power,” right?)
You are describing a model, not reality, so you can just state the model structure. “Consumers have power utility.” (“In this model” is understood.) Save “assumptions” for things
that really do modify the real world, “I assume there are no shifts in the demand curve so
that the regression of price on quantity identifies the supply curve.”
Keep down the number of clauses in your sentences, and the number of things kept
hanging.
“Where” refers to a place. “In which” refers to a model. Don’t write “models where consumers have uninsured shocks,” write “models in which consumers have uninsured shocks.”
Don’t abbreviate authors’ names, “FF show that size really does matter.” There is always
enough space to spell out people’s names. You’d want them to write out yours, no?
It is appropriate to thank people who have helped you in the author footnote. I don’t
add the qualifier about not blaming people I thank for comments for mistakes. It goes
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without saying. I don’t list every single place I’ve given the workshop in the thanks. I’m
not ungrateful, but the long list can get out of hand.
Don’t start your paper with a cute quotation.
Don’t overuse italics. (I use them far too much.) It’s best to use them only when the
emphasis in a sentence would otherwise not be clear — but maybe then you should rewrite
the sentence so that the emphasis really is clear. (Who is that shouting in here?)
When describing the sign of a casual link, one direction is enough. “When Jane goes
up (down) on the teeter-totter, Billy goes down (up) on the other side,” the stuff in the
parentheses is distracting. Add “and vice versa” if you must.
Every sentence should have a subject, verb and object. No sentences like “No sentences
like this.”
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Tips for empirical work
These tips verge on “how to do empirical work” rather than just “how to write empirical
work,” but in the larger picture “doing” and “writing” are not that different.
What are the three most important things for empirical work? Identification, Identification, Identification. Describe your identification strategy clearly. (Understand what it is,
first!) Much empirical work boils down to a claim that “A causes B,” usually documented
by some sort of regression. Explain how the causal effect you think you see in the data is
identified.
1. Describe what economic mechanism caused the dispersion in your right hand variables.
No, God does not hand us true natural experiments very often.
2. Describe what economic mechanism constitutes the error term. What things other
than your right hand variable cause variation in the left hand variable?
3. Hence, explain why you think the error term is uncorrelated with the right hand
variables in economic terms. There is no way to talk about this crucial assumption
unless you have done items 1 and 2!
4. Explain the economics of why your instruments are correlated with the right hand
variable and not with the error term.
5. Do you understand the difference between an instrument and a control? In regressing
y on x, when should z be used as an additional variable on the right hand side and
when should it be an instrument for x?
6. Describe the source of variation in the data that drives your estimates, for every single
number you present. For example, the underlying facts will be quite different as you
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add fixed effects. With firm fixed effects, the regression coefficient is driven by how
the variation over time within each firm. Without firm fixed effects, the coefficient is
(mostly) driven by variation across firms at a moment in time.
7. Are you sure you’re looking at a demand curve, not a supply curve? As one way to
clarify this question, ask “whose behavior are you modeling?”
Example: Suppose you are interested in how interest rates affect housing demand, so
you run the number of new loans on interest rates. But maybe when housing demand is
large for other reasons, demand for mortgages (and other borrowing demand correlated
with demand for mortgages) drives interest rates up. You implicitly assumed stable
demand, so that an increase in price would lower quantity. But maybe the data are
generated by a stable supply, so that increased demand raises the price, or some of
both. Are you modeling the behavior of house purchasers or the behavior of savers
(how savings responds to interest rates)?
8. Are you sure causality doesn’t run from y to x, or from z to y and x simultaneously?
Think of the obvious reverse-causality stories.
Example: You can also think about the last example as causality: Do interest rates
cause changes in housing demand or vice versa (or does the overall state of the economy
cause both to change)?
9. Consider carefully what controls should and should not be in the regression. Most
papers have far too many right hand variables. You do not want to include all the
“determinants” of y on the right hand side.
(a) High R2 is usually bad — it means you ran left shoes = α + β right shoes +γprice
+ error. Right shoes should not be a control!
(b) Don’t run a regression like wage = a + b education + c industry + error. Of
course, adding industry helps raise the R2 , and industry is an important other
determinant of wage (it was in the error term if you did #2). But the whole point
of getting an education is to help people move to better industries, not to move
from assistant burger-flipper to chief burger-flipper.
Give the stylized facts in the data that drive your result, not just estimates and p values.
For a good example, look at Fama and French’s 1996 “Multifactor explanations.” In the old
style we would need one number: the GRS test. Fama and French show us the expected
returns of each portfolio, they show us the beta of each portfolio, and they convince us that
the pattern of expected returns matches the pattern of betas. This is the most successful
factor model of the last 15 years ...even though the GRS test is a disaster! They were
successful because they showed us the stylized facts in the data.
Explain the economic significance of your results. Explain the economic magnitude of
the central numbers, not just their statistical significance. Especially in large panel data sets
even the tiniest of effects is “statistically significant.” (And when people show up with the
usual 2.10 t statistic in large panel data sets, the effect is truly tiny!)
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Of course, every important number should include a standard error.
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Seminar presentations
You will not believe how fast the time will go by.
Since time is limited, it’s especially important to get to the point. We can’t skim to the
important stuff in a seminar!
You don’t need any literature review or motivation in a seminar. Just get to the point.
Gene Fama usually starts his seminars with “Look at table 1.” That’s a good model to
emulate.
Don’t “preview” results. It wastes time; why say it twice rather than say it once, right?
Don’t make slides with a bullet point for every word you intend to say. This forces you
into a preplanned order, and then you can’t change on the fly when you figure out how fast
time is going by. Slides are fine that only contain equations, tables and graphs — things
we really need to see. At most use words for the one or two really important things you
want people to know, e.g. “Identification: interest rates do not respond to fiscal shocks in the
Ricardian model.” Also, you want people to remember the structure of the model, definitions
of variables, etc. If you have too much junk on the slides, people can’t see the utility function
while you’re talking about the production function, so they get lost. People don’t remember
equations from one slide to the next.
You have to leave slides up for a decent amount of time in order for people to digest
them. That means you will not be able to put up 1 slide per minute!
As in writing the paper, your main objective is to get to the #1 important contribution
as fast as possible.
Most seminars are a disaster. They start with pointless motivation and policy implications, which the audience can’t follow since we don’t know the result. Then we get a long
literature review, which is even more boring since we don’t know the point of this paper
much less what everyone else did. Then we get a results preview. Usually, the presenter says
“I’ll preview the results now because I may not have time to get to them all,” a strangely
self-fulfilling prophecy. Since showing the main results is the only reason you came, why not
just start right now! Worse, the reason we run out of time is because we wasted half an
hour on the stupid preview! The seminar then bogs down as people start asking questions
about the previewed results; most of the questions are dumb (“I measure the demand elasticity at 0.3.” “But how did you identify supply shifts?”) since they will be explained in a
proper presentation of the results. But the questions are totally reasonable since the claim
with no documentation is meaningless. Next, we get (in empirical papers) some “theory”
that is really beside the point and only serves to provoke more needless argument (no, there
really is no way to distinguish the “behavioral” and “rational” explanation. Clever audience
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members will come up with stories that reverse all the signs.) Then we get some distracting
preliminary results and tables and graphs of unrelated observations. More pointless discussion erupts; people don’t know what point the speaker is trying to make and the discussion
goes off in to tangents. Finally the speaker sees there is only 10 minutes to go, tells people
to be quiet, and the main results go by in a big rush. Everyone is tired and confused and
doesn’t follow anything. I timed the finance workshop last winter quarter and not one paper
got to the main results in under an hour!
Listen to the questions, all the way to the end, then count to three before answering.
Yes, you’re in a rush, and yes, you think you can guess what the question will be and you
know the answer. This isn’t a game show, and much of the time you actually don’t know
what the question will be.
Keep a sheet of paper handy. You may not have a quick answer to every question, and
some questions may point to good things to change in the paper.
You cannot make it too simple. Most presenters, especially Ph. D. students overestimate
dramatically how much theory people can digest in one sitting, and how quickly they can
memorize and digest models and results.
Speak loudly, slowly and clearly.
There’s nothing wrong with ending early!
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Conclusion
May economists falsely think of themselves as scientists who just “write up” research. We
are not; we are primarily writers. Economics and finance papers are essays. Most good
economists spend at least 50% of the time they put into any project on writing. For me, it’s
more like 80%.
Pay attention to the writing in papers you read, and notice the style adopted by authors
you admire.
I got a lot out of reading William Zinsser’s On Writing Well, and D. McCloskey’s Rhetoric
of Economics. I also found Glenn Ellison’s “The slowdown of the economics publishing
process” in the JPE useful for thinking about how papers should be structured (and refereed
and edited, but that’s another story).
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The Student’s Guide to Writing
Economics
Economists bring clear thinking and a host of analytical techniques
to a wide range of topics. The Student’s Guide to Writing Economics
will equip students with the tools and skills required to write accomplished essays.
Robert Neugeboren provides a concise and accessible guide
to the writing process taking the student through the stages of
planning, revising, and editing pieces of work. This book presents
the core principles of the “economics approach” and covers essential topics such as:
■
■
■
■
■
the key to successful writing in economics
basic methods economists use to analyze data and communicate
ideas
suggestions for finding and focusing your chosen topic
vital techniques for researching topics
how to approach the citing of sources and creating a bibliography
The Student’s Guide to Writing Economics also includes up-to-date
appendices covering fields in economics, standard statistical
sources, online search engines, and electronic indices to periodical
literature.
This guide will prove an invaluable resource for students seeking
to understand how to write successfully in economics.
Robert Neugeboren is Lecturer in Economics and Assistant Director
of Undergraduate Studies at Harvard University, USA.
The Student’s Guide to
Writing Economics
Robert Neugeboren
First published 2005
by Routledge
270 Madison Ave, New York, NY 10016
Simultaneously published in the UK
by Routledge
2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN
Routledge is an imprint of the Taylor & Francis Group
This edition published in the Taylor & Francis e-Library, 2005.
“To purchase your own copy of this or any of Taylor & Francis or Routledge’s
collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.”
© 2005 Robert Neugeboren, and the President and Fellows of Harvard
College
All rights reserved. No part of this book may be reprinted or reproduced or
utilized in any form or by any electronic, mechanical, or other means, now
known or hereafter invented, including photocopying and recording, or in
any information storage or retrieval system, without permission in writing
from the publishers.
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Cataloging in Publication Data
Neugeboren, Robert
The student’s guide to writing economics/Robert Neugeboren.
p. cm.
Includes bibliographical references and index.
1. English language–Rhetoric–Problems, exercises, etc. 2.
Economics–Authorship–Problems, exercises, etc. 3. Academic
writing–Problems, exercises, etc. I. Title.
PE1479.E35.N48 2005
808⬘.06633–dc22
2005005272
ISBN 0-203-79954-2 Master e-book ISBN
ISBN10: 0–415–70122–8 (hbk)
ISBN10: 0–415–70123–6 (pbk)
ISBN13: 9–78–0–415–70122–8 (hbk)
ISBN13: 9–78–0–415–70123–5 (pbk)
Contents
Notes on contributors
Acknowledgments
vii
ix
Introduction: the economic approach
Economics and the problem of scarcity
The assumption of rationality
The theory of incentives
Types of writing assignments
Plan of this guide
1
2
3
4
4
6
1 Writing economically
with Mireille Jacobson
Overview of the writing process
Getting started
The keys to good economics writing
Achieving clarity
Managing your time
8
8
8
12
15
2 The language of economic analysis
Economic models
Hypothesis testing
Improving the fit
Applying the tools
17
18
20
21
22
7
v
CONTENTS
3 Finding and researching your topic
Finding a topic for a term paper
Finding and using sources
Doing a periodical search
Taking and organizing notes
25
26
28
29
30
4 The term paper
Outlining your paper
Writing your literature review
Presenting your hypothesis
Presenting your results
by Christopher Foote
Discussing your results
33
34
35
37
39
5 Formatting and documentation
by Kerry Walk
Placing citations in your paper
Listing your references
Three types of sources
Basic guidelines
Sample entries
49
Appendices
A Fields in economics
B Economics on the Internet
B1: Economics links
B2: Statistical sources
C Electronic indices to periodical literature
63
63
69
70
72
76
References
Index
vi
46
50
52
53
54
56
79
81
Contributors
CHRISTOPHER FOOTE is Senior Economist in the Research
Department at the Federal Reserve Bank of Boston. From 1996 to
2002, he taught at Harvard University’s Department of Economics,
where he also served as Director of Undergraduate Studies. In July
2002, he accepted a position as senior staff economist with the
Council of Economic Advisers, becoming chief economist at CEA in
February 2003. He joined the Boston Fed in October 2003.
MIREILLE JACOBSON is Assistant Professor of Planning,
Policy, and Design at the School of Social Ecology at the University
of California. In 2001, she earned a doctorate in economics from
Harvard University, where she was a National Science Foundation
Graduate Fellow. She is currently a Robert Wood Johnson
Foundation Scholar in Health Policy Research at the University of
Michigan.
KERRY WALK is Director of the Princeton Writing Program.
Before leaving Harvard University in 2001, she was Assistant
Director of the Harvard Writing Project, which seeks to enhance
the role of writing in courses and departments campus-wide. Walk
has given faculty workshops on assigning and responding to student
writing at institutions across the country. She received her Ph.D. in
English from the University of California, Berkeley.
vii
Acknowledgments
This guide was developed in conjunction with the Economics
Tutorial Program at Harvard University, with support and assistance from The Harvard Writing Project. Nancy Sommers, Sosland
Director of Expository Writing, proposed the idea in 1999, and I
was asked to write the guide, which has since been distributed to
the sophomores in the department each year. Kerry Walk, then
Assistant Director of the Writing Project, saw the project through
from inception to completion, commented on drafts, gave advice at
every stage, and ultimately added the section on “Formatting and
documentation” (Chapter 5). Christopher Foote, then Assistant
Professor of Economics and Director of Undergraduate Studies,
wrote part of Chapter 4, and Mireille Jacobson made substantial
contributions to the section on “Writing economically” (Chapter
1), and she compiled the original appendices. Oliver Hart, Michael
Murray, Lorenzo Isla, Tuan Min Li, Allison Morantz, and Stephen
Weinberg also gave very helpful comments. Rajiv Shankar updated
the appendices and prepared the manuscript for printing. Special
thanks to Anita Mortimer, with regrets for her recent passing.
ix
Introduction: The
economic approach
LIST OF SUB-TOPICS
■
■
■
■
■
Economics and the problem of scarcity
The assumption of rationality
The theory of incentives
Types of writing assignments
Plan of this guide
Economists study everything from money and prices to child rearing
and the environment. They analyze small-scale decision-making and
large-scale international policy-making. They compile data about
the past and make predictions about the future. Many economic
ideas have currency in everyday life, cropping up in newspapers,
magazines, and policy debates. The amount you pay every month to
finance a car or new home purchase will depend on interest rates.
Business people make investment plans based on expectations of
future demand, and policy-makers devise budgets to achieve a
desired macroeconomic equilibrium.
While the range of topics that interest economists is vast, there is
a unique approach to knowledge, something common to the way all
economists see the world. Economists share certain assumptions
1
INTRODUCTION: THE ECONOMIC APPROACH
about how the economy works, and they use standard methods for
analyzing data and communicating their ideas. The purpose of this
guide is to help you to think and write like an economist.
ECONOMICS AND THE PROBLEM OF SCARCITY
Since its beginnings as “the dismal science,” economics has been
preoccupied with the problem of scarcity. The hours in a day, the
money in one’s pocket, the food the earth can supply are all limited;
spending resources on one activity necessarily comes at the expense
of some other, foregone opportunity. Scarcity provides economics
with its central problem: how to make choices in the context of
constraint.
Accordingly, economists ask questions such as: How does a
consumer choose a bundle of commodities, given her income and
prices? How does a country choose to meet its objectives, given its
national budget? How do decision-makers allocate scarce resources
among alternative activities with different uses?
While this central economic problem may be rather narrow, the
range of topics that interest economists is vast. Indeed, insofar as it
can be characterized as choice under constraint, any kind of behavior
falls within the scope of economic analysis. As Lord Lionel Robbins
(1984), one of the great economists of the twentieth century, put it:
We do not say that the production of potatoes is economic
activity and the production of philosophy is not. We say
rather that, in so far as either kind of activity involves the
relinquishment of other desired alternatives, it has its
economic aspect. There are no limitations on the subject
matter of Economic Science save this.
It should come as no surprise that economists are sometimes
called “imperialists” by other social scientists for their encroachment
2
INTRODUCTION: THE ECONOMIC APPROACH
on fields that traditionally belong to other disciplines. For instance,
historians studying the migration patterns of eighteenth-century
European peasants have explained the movement out of the
countryside and into the cities in terms of broad social and cultural
factors: the peasants were subjects of changing times, swept along
by the force of history. By contrast, economists, such as Samuel L.
Popkin (1979), have attributed urban migration patterns to the
trade-offs faced and choices made by individual agents; from this
perspective, the peasants’ behavior was rational.
THE ASSUMPTION OF RATIONALITY
Economists approach a wide range of topics with the assumption
that the behavior under investigation is best understood as if it were
rational (though we know that not all behavior is, in fact, rational)
and that the best explanations, models, and theories we construct
take rationality as the norm. Rationality, in the words of Frank
Hahn, is the “weak causal proposition” that sets all economic
analyses in motion. “Economics can be distinguished from other
social sciences by the belief that most (all?) behavior can be
explained by assuming that agents have stable, well-defined preferences and make rational choices consistent with those preferences”
(Colin Camerer and Richard Thaler, 1995).
Rationality, in the standard sense of the economist, means that
agents prefer more of what they want to less. This may seem like a
rather strong proposition, insofar as it seems to imply that human
behavior is necessarily calculated and self-interested. But the
assumption of rationality does not imply anything about the content
of agents’ wants, or preferences; hence to be rational is not
necessarily to be selfish. One can want others to be better off and
rationally pursue this objective as well. Economists assume that
whatever their preferences, agents will attempt to maximize their
satisfaction subject to the constraints they face. And good economics
3
INTRODUCTION: THE ECONOMIC APPROACH
writing will take the assumption of rational behavior as its starting
point.
THE THEORY OF INCENTIVES
The theory of incentives posits that individual agents, firms, or
people, make decisions by comparing costs and benefits. When costs
or benefits – the constraints on choices – change, behavior may also
change. In other words, agents respond to incentives.
Many recent developments in economics and public policy are
based on the theory of incentives. For example, recent welfare
reforms recognize that traditional welfare, which guarantees a basic
level of income but is taken away once that level is surpassed,
provides incentives for those below the earnings threshold to stay
out of the formal workforce. This and other criticisms have led to
the adoption and expansion of programs such as the Earned Income
Tax Credit (EITC). The EITC seeks to rectify this particular incentive problem by making transfers only to working individuals. Such
policy changes suggest that incentives matter for behavior. Thus, a
thorough analysis of any behavior, and a well-written account of it,
must account for incentive effects.
TYPES OF WRITING ASSIGNMENTS
Depending on the course, the instructor, and the degree to which
writing has been integrated into the curriculum, there are several
types of writing assignments you might see. Some courses will
sequence their assignments, working on basic skills in short assignments and building to a longer term paper. No matter what the
format, length, etc., it is important to understand the assignment’s
goal or purpose.
4
INTRODUCTION: THE ECONOMIC APPROACH
Response paper (1–2pp)
Response papers might involve summarizing an assigned reading or
answering a specific set of questions about the text. Instructors use
these to focus your attention on important topics and to stimulate
class discussion. Response papers can also help develop the themes
and vocabulary needed for writing successful longer papers.
Short essay (3–4pp)
Short essays may require you to analyze two articles and compare
their policy implications, explain a model, criticize an argument,
present a case study, evaluate an intellectual debate, and so on. A
short essay differs from a response paper in that it will usually ask
you to have a thesis, or central argument, and then present some
kind of analysis to make your case.
Empirical exercise (5–6pp)
Often courses will assign an empirical exercise in which you are
asked to analyze economic data using a standard statistical software
package (e.g., Stata, Minitab, SAS, SPSS, etc.). An empirical exercise will give you experience in answering an economic question
with data and drawing conclusions from evidence.
Term paper (10–15pp)
The term paper addresses a topic in depth and combines skills
developed throughout the semester. It typically includes a literature
review, an empirical component, a discussion of results, and perhaps
a discussion of policy implications. It may build on earlier short assignments, including a prospectus, in which you will propose a thesis or
question and detail how the issue will be addressed. The term paper
may require research beyond what has been assigned to the class.
5
INTRODUCTION: THE ECONOMIC APPROACH
Make sure you clear up any confusion about the assignment by
asking your instructor specific questions about what he or she is
looking for. The earlier you get clarification, the better able you will
be to complete the assignment (and get a good grade). For longer
papers, you may want to hand in rough drafts. Getting feedback may
improve your writing considerably and generally makes for more
interesting papers.
PLAN OF THIS GUIDE
Understanding the way economists see the world is a necessary step
on the way to good economics writing. Chapter 1 describes the keys
you need to succeed as a writer of economics and offers an overview
of the writing process from beginning to end. Chapter 2 describes
the basic methods economists use to analyze data and communicate
their ideas. Chapter 3 offers suggestions for finding and focusing
your topic, including standard economic sources and techniques for
doing economic research. Chapter 4 tells you how to write a term
paper. Finally, Chapter 5 provides a guide to citing sources and
creating a bibliography. Three appendices provide useful information for developing your term papers. Appendix A provides a
roadmap of fields in economics and can help define very broad areas
of interest. Appendix B presents an overview of economics
resources on the Internet, with a brief directory of useful websites
and links to statistical sources that you may wish to use for your
own research. Appendix C lists the relevant electronic indices to
periodical literature, invaluable resources for the initial stages of any
paper.
6
Chapter 1
Writing economically
LIST OF SUB-TOPICS
■
■
■
■
■
Overview of the writing process
Getting started
The keys to good economics writing
Achieving clarity
Managing your time
Pick up any publication of the American Economics Association and
you will discover a few things about writing economics. First, the
discourse is often mathematical, with lots of formulas, lemmas, and
proofs. Second, writing styles vary widely. Some authors are very
dry and technical; a few are rather eloquent.
You do not have to be a great “writer” to produce good economics
writing. This is because economics writing is different from many
other types of writing. It is essentially technical writing, where the
goal is not to turn a clever phrase, hold the reader in suspense, or
create multi-layered nuance, but rather to achieve clarity. Elegant
prose is nice, but clarity is the only style that is relevant for our
purposes. A clear presentation will allow the strength of your underlying analysis and the quality of your research to shine through.
7
WRITING ECONOMICALLY
OVERVIEW OF THE WRITING PROCESS
If you have ever pulled an all-nighter and done reasonably well on
the assignment, you may be tempted to rely on your ability to churn
out pages of prose late at night. This is not a sensible strategy. Good
economics papers just do not “happen” without time spent on preparation; you cannot hide a lack of research, planning, and revising
behind cleverly constructed prose. More time will produce better
results, though returns to effort will be diminishing at some point.
Here, too, the principles of economy apply.
GETTING STARTED
Getting started is often the hardest part of writing. The blank page
or screen can bring on writer’s block, and sustaining an argument
through many pages can seem daunting, particularly when you
know your work will be graded. Do not let these concerns paralyze
you; break the paper down into smaller parts, and get started on the
simpler tasks. Economics writing usually requires a review of the
relevant literature (more on this later). Especially if you are stuck,
this can be a great way to begin.
THE KEYS TO GOOD ECONOMICS WRITING
Writing in economics, as in any academic discipline, is never simply
a matter of asserting your opinions. While your ideas are important,
your job includes establishing your credentials as a writer of economics, by demonstrating your knowledge of economic facts and
theories, identifying and interpreting the underlying economic
models, understanding what others have said about the relevant
issues, evaluating the available evidence, and presenting a persuasive
8
WRITING ECONOMICALLY
argument. Even if you do not write particularly well, you can produce good economics papers by attending to three basic tasks:
Research
Economic research generally entails three stages. First, you may
need to gain a broad overview of your topic: start from a text book
on the subject, or discover what resources are available in that field
over the internet (see Appendix B1). Second, you may need to
review the literature on the topic: simple or exhaustive searches can
be made through online academic search portals which will find
perhaps hundreds of articles based on your narrow search criteria
(see Appendix C). Sometimes the entire article is available online;
usually at least an abstract is given, and you have to manually locate
the article in your library, or get it via inter-library loan. Third, even
if you are referring to only a single paper, you may need to update
some of the relevant statistics, or collect and analyze substantial data
on your own, which you can get from any of a number of standard
statistical sources (see Appendix B2). In general, your writing
will reflect the quality of your research, and good writing will
demonstrate that you understand the findings that are relevant to
your topic.
Organization
Once you have found your sources, you will need to organize your
ideas and outline your paper. Economists usually organize their
writing by using simplified models (such as supply and demand,
cost/benefit analysis, and comparative advantage). Therefore, a
literature review is often followed by the presentation of a model,
usually one of the standard models or, for the theoretically inclined,
one of your own devising. Models are used to organize data and
generate hypotheses about how some aspect of the economy works.
9
WRITING ECONOMICALLY
Analysis
Reducing something complex into simpler parts is an integral part of
economic rigor. Statistical analysis (or econometrics) takes vast
piles of data and returns useful numerical summaries that can be
used to test various economic models and make predictions about
the future. Mathematics is very helpful here because it is a precise
language that can articulate the way basic economic relations are
conceptualized, measured, and defined. Nonetheless, even before
you have mastered sophisticated statistical and mathematical
techniques, your goals should be writing clearly, following a line
of deductive reasoning to its conclusion, and applying the rules
of inference correctly. These are the marks of good economics
writing.
AN EXAMPLE FROM THE LITERATURE
Generally, in the first few paragraphs of a paper, economists set
up their research question as well as the model and data they
use to think about it. This style can be useful to both writer and
reader as it establishes the structure of the work that follows.
Unfortunately, it sometimes means a stilted or dry presentation. An excerpt from a piece by two of the field’s most
eloquent authors, Claudia Goldin and Lawrence F. Katz
(1996), illustrates a skilful approach to setting up a research
question, placing it in the literature, and outlining how the work
to follow extends existing research. Notice, in particular, that
these steps need not be completely independent.
The piece, taken from the authors’ work on the historical
relationship among technology, human capital, and the wage
structure, starts by presenting the facts motivating the
question:
10
WRITING ECONOMICALLY
Recent technological advances and a widening of the
wage structure have led many to conclude that technology
and human capital are relative complements. The
possibility that such a relationship exists today has
prompted a widely held conjecture that technology and
skill have always been relative complements.
Next they explain the existing theories behind this relationship:
According to this view, technological advance always
serves to widen the wage structure, and only large
injections of education slow its relentless course. A
related literature demonstrates that capital and skill are
relative complements today and in the recent past (Zvi
Griliches, 1969). Thus capital deepening appears also to
have increased the relative demand for the educated,
serving further to stretch the wage structure.
Then they clearly and simply state their question:
Physical capital and technology are now regarded as the
relative complements of human capital, but have they
been so for the past two centuries?
Next they cite more of the related literature:
Some answers have already been provided. A literature
has emerged on the bias to technological change across
history that challenges the view that physical capital and
human capital have always been relative complements.
Finally they propose how they seek to answer this question:
We argue that capital–skill complementarity was
manifested in the aggregate economy as particular
11
WRITING ECONOMICALLY
technologies spread, specifically batch and continuous
process methods of production.
Their paper goes on to establish the empirical evidence that
backs up this assertion. As evidenced by the example above, the
clarity of your prose, the quality of your research, the organization of your argument, and the rigor of your analysis are the
keys to your success as an economics writer.
ACHIEVING CLARITY
Clear writing is easy to read but hard to write. It rarely occurs
without considerable effort and a willingness to revise and rework.
As McCloskey (1985), the dean of economics writing, tells us: “it is
good to be brief in the whole essay and in the single word, during the
midnight fever of composition and during the morning chill of
revision.” The rules of clear writing apply to the organization of the
entire paper, to the order of paragraphs, to sentences, and to words.
Clarity can be achieved in stages:
Organize your ideas into an argument with
the help of an outline.
↓
Define the important terms you will use.
↓
State your hypothesis and proceed deductively
to reach your conclusions.
↓
12
WRITING ECONOMICALLY
↓
Avoid excess verbiage.
↓
Edit yourself, remove what is not needed, and
keep revising until you get down to a simple,
efficient way of communicating.
This last stage is crucial. Take, for example, the following excerpt
from a student’s short response paper:
In the beginning of the 1980s, the problem of homelessness in the United States became apparent (Richard B.
Freeman and Brian Hall, 1989). Since then, the number of
homeless in this country has continued to grow. While the
problem of homelessness, in itself, is obviously a problem
that is quite relevant to other fields of economic study, it
has also given rise to a phenomenon that is an interesting
topic for the study of behavioral economics: the donation
of money to help the homeless population.
With a little revision, the author could have achieved a more clear
and concise introduction:
Early in the 1980s, increasing homelessness in the United
States became apparent (Freeman and Hall, 1989). Since
then, the number of homeless has continued to grow. While
homelessness is studied in many fields of economics, it has
given rise to a particular phenomenon – the donation of
money directly to the homeless – that interests behavioral
economists in particular.
13
WRITING ECONOMICALLY
Below are some additional tips to achieving clarity and some
examples that apply them. These and many other useful tips can be
found in Strunk and White (1979), Turabian (1996), and Gibaldi
(2003).
Use the active voice
It turns a weak statement (first one) into a more direct assertion
(second statement):
In this paper, the effect of centralized wage-setting institutions on the industry distribution of employment is
studied.
This paper studies the effect of centralized wage-setting
institutions on the industry distribution of employment.
Put statements in positive form
Many day-traders did not pay attention to the warnings of
experts.
This statement is more concisely conveyed as follows:
Many day-traders ignored the warnings of experts.
Omit needless words
In spite of the fact that the stock market is down, many
experts feel that financial markets may perform reasonably well this quarter.
14
WRITING ECONOMICALLY
A better way to express the same thing is:
Although the stock market is down, financial markets may
still perform reasonably well this quarter.
In summaries, generally stick to one tense
This study showed that dividend payouts increase when
dividend income was less tax-disadvantaged relative to
capital gains.
An improvement uses the present tense throughout:
This study shows that dividend payouts increase when
dividend income is less tax-disadvantaged relative to
capital gains.
Few writers achieve clarity without continual editing. Once
you have your basic ideas down, be sure to reread and revise your
work.
MANAGING YOUR TIME
The best laid plans for writing a good paper can be wrecked by poor
time management. Make sure you clear up any confusion about the
assignment right away. Set deadlines for completing each phase of
the project:
15
WRITING ECONOMICALLY
Start the project by finding your topic.
↓
Begin your research.
↓
Start an outline.
↓
Write a draft.
↓
Revise and polish.
Divide your time, from the moment you receive your assignment to
the moment it is due, into segments allotted to each task. Hold
yourself to the deadlines you set, and allow yourself time to revise
and polish the paper. The payoff will be a better product, a better
grade, and less anxiety throughout.
16
Chapter 2
The language of
economic analysis
LIST OF SUB-TOPICS
■
■
■
■
Economic models
Hypothesis testing
Improving the fit
Applying the tools
The economy is a complex web of interdependent elements, and
understanding any part is a significant accomplishment. The price of
tea in the USA is determined by many factors, including individual
preferences (or tastes), labor costs, weather conditions, and the price
of tea in China, among others. Preferences, labor costs, weather,
etc., are in turn connected to other factors, including the price of
coffee, which in turn can affect the price of tea. All the parts can be
moving simultaneously, making it hard to see what is causing what.
To write effectively about economics, you have to understand how
economists think about such complicated phenomena. In general, to
make their task easier, economists focus on and try to isolate simple
causal connections, often between two variables ceteris paribus, or
“other things being equal.” “Other things being equal,” what is the
17
THE LANGUAGE OF ECONOMIC ANALYSIS
effect of a change in labor costs on the price of tea? “Other things
being equal,” how does a change in the price of coffee affect the price
of tea?
This kind of analysis allows economists to say something very
precise about well-defined relationships and to run rigorous tests to
measure the strength and direction of their connections. Of course,
focusing on just one relationship at a time means other relationships
are artificially held constant, so that our analyses necessarily diverge
from reality. They are hypothetical. But simplification and abstraction are necessary ingredients of any theoretical enterprise, and a
good economist knows the real world is more complex.
ECONOMIC MODELS
Economic analysis is characterized by the use of models, simplified
representations of how economic phenomena work. Supply and
demand, cost/benefit analysis, and comparative advantage are
examples of basic economic models. A model is a theory rendered in
precise, usually mathematical, terms. Economists build models the
way curious scientists do: Reduce the phenomenon to its basic
elements and recombine these elements so as to produce a model
that resembles the original in relevant respects. Take it apart, figure
out how it works, then put it back together and see if it goes.
Economic models specify relationships between two kinds of
variables: exogenous variables and endogenous variables (Gregory N.
Mankiw, 1997). Exogenous variables are inputs to the model,
factors that influence what happens but are themselves determined
“outside” the model. They are givens, fixed values that are assumed
not to change over the period of analysis. Endogenous variables are
outputs of the model, determined “within.” Usually, a mathematical
function is used to represent the relationship between exogenous
and endogenous variables. Systems of relationships, in which changes
18
THE LANGUAGE OF ECONOMIC ANALYSIS
in one part of the economy have different consequences in others,
are often conveniently represented by systems of functions. For
example, we can model the market for ice cream in terms of three
functions:
The quantity of ice cream demanded
depends (negatively) on the price of ice
cream and (positively) on income (Y):
Qd = D(PI, Y)
The quantity of ice cream supplied
depends (negatively) on the price of
milk (because ice cream is made from
milk) and on the price of ice cream:
Qs = S(PI, PM)
In equilibrium, the quantity of ice
cream supplied equals the quantity
demanded:
Qd = Qs
In this model, the price of milk and the level of income are exogenous variables; the price of ice cream and the quantity of ice cream
exchanged are endogenous variables. By plugging data (exogenous
variables) into the model, it is possible to predict the behavior of the
endogenous variables, thus generating hypotheses about phenomena that have not yet been observed.
Applying basic models allows one to make predictions about the
real world economy, both forward-looking predictions about, say,
future interest rates and backward-looking predictions about,
say, the savings rate during the Depression. Models also provide
guidance about where to look for and how to look at data, and they
provide a structure on which the rest of the paper can hang.
19
THE LANGUAGE OF ECONOMIC ANALYSIS
HYPOTHESIS TESTING
A model’s predictions about the future or the past are essentially
empirical hypotheses: claims, supported by facts, about how some
economic phenomenon works. Most economists, aspiring to be good
social scientists, would like to test their hypotheses under laboratory
conditions. But this is not ordinarily possible. Instead, we take
sample data from the real world, by looking at census reports,
balance sheets and the like, and we use statistical methods to test the
predictive power of our models and the hypotheses they generate.
Most economic data come in, or can be easily transformed into,
numerical terms. Prices and quantities are numbers, and economists
also attach numerical measurements to factors such as standards of
living that do not usually come in quantified form. But a long list of
numbers is just that until a relationship among them can be specified
that imparts some order. By building and using models, economists
are able to focus on simple, sometimes subtle, relationships in the
data and explain the causal links involved. Finding the pattern in the
data allows one to say something about how the economy works. A
set of well-known models can greatly simplify the task of organizing
and communicating your ideas. But the real test of a model is how
well it helps us understand the workings of the economy.
AN EXAMPLE: REGRESSION
Say, for instance, you are interested in explaining the causes of
inflation. You study the literature and learn about a connection
between the level of economic activity and the level of inflation.
You formulate a simple hypothesis:
Hypothesis: High levels of employment lead to high levels of
inflation.
20
THE LANGUAGE OF ECONOMIC ANALYSIS
Observations: Monthly employment (X) and inflation
rates (Y) in the US from 1980–1995. (Two lists of
12 × 16 = 192 observations.)
Regression: Y = a + bX + c. b measures the correlation
between X and Y. If b is positive and statistically
significant, the hypothesis cannot be rejected. (a is a
constant; c is an error term.)
In order to run such a regression you will need a fairly
large number of observations. Without enough data you
may not be able to decide between this and the alternative,
or null, hypothesis (i.e., high levels of employment have
no relationship to high levels of inflation) by statistical
measures alone. In such cases, there may be better ways
to do an empirical exercise (e.g., case study; experimental
methods).
Even with enough data, statistical analyses show correlation, not causation. A model is needed to explain how
things work – for instance, how high levels of employment
lead to high levels of inflation.
IMPROVING THE FIT
The fit between a model and reality is never perfect. When the fit is
good, we can make better predictions about the future and better
understand the past. In the former case, the passage of time will fail
to disconfirm the prediction; in the latter case, historical research
will match our expectations. As in any science, our theories can
really only be disproved. However, when our predictions are
correct, the weight we place on our models increases. When our
predictions are wrong, we are left either looking for more data or
21
THE LANGUAGE OF ECONOMIC ANALYSIS
perhaps a new or revised model. That model may be used to
generate new predictions, which can then be confronted with new
data, which may again bring disconfirmation of the prediction and
suggest a revision of the current model.
APPLYING THE TOOLS
Most of the writing done in economics involves the application of
old models to new data, with the goal of better understanding some
real world economic phenomenon. This may or may not involve
analyzing a large dataset. This example applies economic tools –
namely, game theoretic analysis – to one particular issue, the role of
international institutions in the post-Cold War era:
The purpose of this paper is to discuss the continuing role
of NATO and the likelihood of lasting cooperation among
the organization’s member states in a post-Cold War
world. Game theory and the study of strategic interactions,
although initially devised as a tool for understanding Cold
War motives and actions, nevertheless are extremely
applicable to a post-Cold War environment. I therefore
plan to incorporate several relevant international relations
issues into a game theoretical perspective – first to discuss
the cooperation that actually occurred in NATO since the
1940s, and then to explain why similar cooperation may be
unlikely among security-based regimes after the collapse of
the Soviet Union.
Another kind of writing, the theory paper, involves criticizing the
models we use and proposing better ones. The goal of the theory
paper is to improve the conceptual underpinnings of the particular
22
THE LANGUAGE OF ECONOMIC ANALYSIS
analytical tools we use to understand the actual economy. This may
be a better model of how firms behave in uncertain market
conditions, or a new way to measure the level of national economic
activity, or a synthesis of existing theories to produce a new, more
general theory.
Because all economic models are crude approximations of a
complex world, it is necessary to assess just how crude the approximations are before we can say which model better fits the data.
Interpreting statistics and determining what can and cannot be
reliably inferred given the observations available requires knowledge of economic theory as well as a healthy dose of mathematics.
Mathematical logic is also used to build new models, both to
formalize the logical structure of the model and to test for its
coherence and internal consistency. The mathematics of model
building does not involve numbers, but it does specify quantities
(quantifiers) and uses well-defined operators to combine (sets of )
propositions.
Economic theory was not always so mathematical. And the
mathematization of economic theory has had costs as well as benefits. The benefits are that, in many cases, more can be said quickly
and precisely, because mathematics is a powerful language and
convenient shorthand. The cost is that not all relevant phenomena
are easily cast in mathematical terms or can be only crudely captured
mathematically. Another cost is that economic theory becomes
somewhat less accessible to students and to the world at large, in
which public policy debates are conducted.
23
Chapter 3
Finding and researching
your topic
LIST OF SUB-TOPICS
■
■
■
■
Finding a topic for a term paper
Finding and using sources
Doing a periodical search
Taking and organizing notes
Economists view the world through the lens of efficiency, starting
from the assumption that individuals behave rationally and focusing
on the problem of allocating scarce resources. From this common
analytical perspective, economists study a wide range of topics,
involving the behavior of individuals, organizations, and nations.
The economic approach can be applied so broadly that choosing a
topic to write on can be difficult. Indeed, once you start looking at
the world through the eyes of an economist, almost anything can be
analyzed in terms of choice under constraint.
Your own research has to meet the terms of the assignment as
well as the time and other constraints you face. You may need to
read books and journal articles in the library or pore over data sets
on a computer. In either case, you will need a topic before you can
begin. If your instructor gives you a list of topics, a review of related
25
FINDING AND RESEARCHING YOUR TOPIC
research may help you choose among them. If the research question
is entirely up to you, a literature search is often not the best way to
begin. Immersing yourself in the literature before you have found
a topic may convince you that all the interesting questions have
already been tackled. At the very least, literature searches should be
guided by very general topic ideas.
FINDING A TOPIC FOR A TERM PAPER
Though there is no one way to find a topic, thinking of the issues that
interest you is a great place to begin. While the range of possible
topics is large, there are some well-defined fields in economics, and
your own interests are likely to fit into one of these (see Appendix A
for an annotated list of fields). Course materials, textbooks, handouts, and so on are obvious and convenient places to look, especially
since your topic will most likely have to pertain to the course
subject. But reading the newspaper and keeping an eye on current
events can be even more helpful. Once you have a general idea, you
should go to the literature and see how economists have tried
thinking about it.
For example, say your interest is piqued by recent shootings in
both schools and workplaces. What role has the availability of guns
played in these events? What are the effects of banning guns?
Implementing tougher gun control laws? Though this might initially
strike you as a government or law project, many of the underlying
issues are fundamentally economic – gun control measures explicitly
place limits on supply and attempt to put guns in disfavor or reduce
demand. Once you have identified guns and gun control as an area of
interest, do your literature search (more on this later). Pick out the
relevant articles and scour them for content as well as for additional
sources. Try to narrow down your topic. Have the authors pointed
out any future research areas? Are there any issues that you think
have not been fully addressed?
26
FINDING AND RESEARCHING YOUR TOPIC
In addition to finding something that interests you, you will also
need a project that can be done within the parameters of the assignment (for example, length, due date, access to research materials).
If the topic does not interest you, you probably will not put in the
effort needed to do a good job or ask the right questions along the
way. On the other hand, a profoundly interesting topic may not be
manageable given the time and other constraints that you face.
As another example, say you are interested in the stock market
and want to know what determines stock prices. From basic economic theory, you know that prices are determined by supply and
demand, but what specific relationships do you need to study and
what data do you need to gather? You think about it for a while and
realize there are many parts to your question. What determines the
price of a particular company’s stock is a different question from
what determines the level of stock prices in general (as measured by
Dow Jones or another index), though the two may be related. And
what determined stock prices yesterday might be different from
what explains changes in stock prices in the future. Each of these
questions could be the subject of an interesting paper. Your original
topic was overly broad; you should focus on a single, manageable
question.
Get started on your research even if you do not have a precise
topic; it will evolve along the way. The question you begin with may
become less interesting, and something new may draw your
attention. You may be persuaded by an argument you encounter or
find data that pose a problem you had not considered. You may find
no data on one topic and a goldmine on another. Shaping your topic
in this way is perfectly fine, but do not get trapped in an endless
maze of new, or just slightly revised, topics. You want your search
to converge on a manageable topic in a reasonable amount of time.
Find a question you can answer and begin your work.
27
FINDING AND RESEARCHING YOUR TOPIC
FINDING AND USING SOURCES
All academic writing involves the use of source materials. Archaeologists look in the ground for artifacts, about which volumes of
research may subsequently appear. Biologists look through microscopes and write up the laboratory experiments they perform.
Historians study documents; sociologists interview subjects . . .
Economic research typically begins with a (large) set of numerical
data – say, a list of per capita incomes for every country in the
United Nations or the history of daily closing prices for shares of
XYZ Corporation over the last year. In these long lists of numbers,
economists look for patterns, or regularities, that reveal some
underlying relationship between economic variables and help
explain how some part of the economy works. A data set could
include hundreds or thousands of entries; thus, statistical tools are
used to summarize this information and ease your job of communicating with your audience. The mean of a large set of numbers
conveys important information in a compact form. Knowing the
standard deviation and other statistical measures can also be helpful
when describing the population under investigation and presenting
the results of your research.
Economic sources come in two types. The first is empirical data:
facts about the real world that come in, or can be easily converted
into, numerical form (for example, prices, quantities, income
levels). The second is academic literature: books or articles that you
read in the library that can help you organize your ideas and make
sense of the heaps of data you have accumulated.
In general you will not have the time or resources to go into the
field and compile your own data – administer questionnaires, study
individual balance sheets, budgets, etc. Instead, you will rely on
others to collect your data, including other economists as well as
demographers, auditors, and “official” statisticians. These data are
compiled in a number of standard secondary sources, such as the
Economic Report of the President and the Statistical Abstract of the United
28
FINDING AND RESEARCHING YOUR TOPIC
States. These volumes and others (see Appendix B2) contain detailed
information on public and private spending, wage and tax rates, and
work force size and education levels, as well as other information
grouped by states, industries, and nations. Economists frequently
begin their research with these sources; they will either point you to
the proper primary source or contain the precise data you need for
your paper.
You will also want to look at academic journals and other
scholarly literature on your topic. Using scholarly sources will allow
you to invoke the authority of experts in the field to sanction your
analysis or to establish the point of departure for your own original
contribution. You need to become familiar with what others have
thought and written so that you can communicate your findings in
terms your audience will recognize. Perhaps you will apply a
standard model found in the literature to new evidence or compare
two models and see which does a better job explaining the data you
have found.
These works will also point you to additional sources. Bibliographies, citations, and footnotes may reveal a single, seminal
forerunner. Read it. If you come across a “review” or “survey”
article, you have hit the jackpot. It will contain an authoritatively
complete summary of the literature in the field.
DOING A PERIODICAL SEARCH
Periodical literature was once indexed in cumbersome hardbound
volumes. Nowadays, there are a number of very useful electronic
indices available on-line and updated frequently. Most are publicly
available on the Internet, although some reside on your institution’s
proprietary system. Appendix C describes those sources that are
used most frequently by economists.
Depending on the service you are using, your search can be very
deep, including title, author, and subject as well as abstracts, tables
29
FINDING AND RESEARCHING YOUR TOPIC
of contents, and related topic fields. This makes electronic searching
far more powerful than anything that could be done just a few years
ago. Once you find a relevant article, look at the abstract. Check a
few more items and retrieve from the shelves whatever looks
interesting and useful.
TAKING AND ORGANIZING NOTES
The books, articles, charts, and tables strewn before you are the
objects of your research, the evidence you will marshal to support
your argument. Your first encounter with your sources should be
carefully recorded: you should document your findings and give
proper credit to the sources you use.
First, take down the complete bibliographic record:
Author(s) (or Editor(s)).
Title.
Journal.
Volume.
Date.
Pages.
Number.
For the Goldin and Katz (1996) example used in Chapter 1, your
notes would look as follows:
Goldin, Claudia and Katz, Lawrence F.
“Technology, Skill and the Wage Structure: Insights from
the Past.”
American Economic Review, 86 (2).
May 1996. Pp. 252–257.
30
FINDING AND RESEARCHING YOUR TOPIC
Keep a file of notes on each article you read. This should include
the main points of the article and any important results. Make sure
to clearly set off direct quotations by using quotation marks. Avoid
paraphrasing, because it will be difficult to separate the original
wording from your own later on. You can add your own comments
afterwards, but it is important to keep an accurate record of your
first encounter with the source.
Taking good notes will accomplish several things. First, you will
have all your references at hand when you are writing the paper, so
you will not have to go searching for a quote or chart when you are in
your dorm room and the article you need is in the library. Second,
you will leave a clear record for your readers to follow, so that they
can go to the originals for more information or to see the facts for
themselves. Finally, you will leave signposts for yourself so that you
can know where you have been and separate your own ideas and
results from those you found in your sources. This will help you
avoid plagiarizing, which can happen inadvertently as your own
ideas blur into what you have “learned” from others. The unacknowledged use of another writer’s words or ideas is plagiarism,
whether intended or not. Poor note taking and sloppy documentation mechanics can lead to plagiarism, but such mistakes are easy
to correct and avoid.
Start taking notes right away. A word processor can make things
easier, but even if you use pen and paper, try to develop good notetaking habits from the outset. Create a note file for each source you
find. Group your notes by topic, alphabetically, chronologically, or
otherwise. As you organize them, add comments and summaries,
pick out important themes, and focus on issues for further research.
These notes should help motivate your project by shaping the
analytical model used and, through your summaries, form the
beginnings of a good literature review.
31
Chapter 4
The term paper
LIST OF SUB-TOPICS
■
■
■
■
■
Outlining your paper
Writing your literature review
Presenting your hypothesis
Presenting your results
Discussing your results
You have chosen your topic, done your research, and settled on
your ideas, and now you have to write the paper. If you have done
your job properly up to now, you should have a topic, some data,
and plenty of notes on things you have read. Now your task is to
decide how to focus your question and ideas, assemble the pieces
into a structure that hangs together, and present an argument others
will find persuasive.
Remember: writing is a process. Start with a few lines, perhaps
just section headings, and then build up detail and flesh out your
analysis. The key to the process is not to become too rigid too soon.
While you want enough structure to get started, you also want to
allow the overall shape of your paper to evolve somewhat along
the way.
33
THE TERM PAPER
OUTLINING YOUR PAPER
The outline for your term paper is the agenda you set for the things
you want to accomplish. A good term paper will ask an interesting
question and offer a plausible answer. It should be plausible in
that it is (probably) true, but also not obviously or patently true;
and it should be supportable in that it is subject to factual
observation or logical demonstration (Gordon Harvey, Harvard
Writing Program).
No matter what your field or topic, there is a fairly standard set of
things you want to accomplish in the paper:
INTRODUCTION
pose an interesting question
or problem
LITERATURE REVIEW survey the literature on your
topic
METHODS/DATA
formulate your hypothesis
and describe your data
RESULTS
present your results with the
help of graphs and charts
DISCUSSION
critique your method and/or
discuss any policy implications
CONCLUSIONS
summarize what you have
done; pose questions for
further research
Not every assignment will require all of these parts, but your
term paper will impress your reader if you have done a good job on
most of them. You might want to write the introduction and
conclusions after you have completed the body of the paper. Few
34
THE TERM PAPER
points are given for subtlety or surprise. You should prepare your
audience for what you are going to do, then do it, then summarize
what you have done.
WRITING YOUR LITERATURE REVIEW
Depending on your assignment, preparing a literature review might
entail an exhaustive library search or referencing the single paper
your instructor has assigned. You should have notes, either on index
cards or in files on your computer, on the books and articles you
have read. Read over your summaries and comments and begin to
look for common themes that can organize your review. What is the
main point of the article, and how does it relate to your topic? Do
other authors offer a similar position? An opposing one?
As you think through these questions, keep in mind that the literature review has two functions. The first is simply to demonstrate
your familiarity with scholarly work on your topic – to provide a
survey of what you have read, trace the development of important
themes, and draw out any tensions in prior research. The second
function is to lay the foundations for your paper, to provide motivation. The particular issues you intend to raise, the terms you will
employ, and the approach you will take should be defined with
reference to previous scholarly works. By drawing on such sources,
you can find sanction for your own approach and invoke the
authority of those who have written on the topic before you.
In some instances, these two functions will pull in opposite
directions: the first toward including as many sources as possible,
the second toward selecting only those that are useful for your argument. In any case, more research is better than less, and a summary
is always selective, insofar as only some things can be included and
others left out. The selections you make will necessarily reflect your
own interests and, hopefully, lead the reader to take an interest in
the argument you will present.
35
WRITING ECONOMICALLY
FOR EXAMPLE
Martin Feldstein begins his article, “Social Security, Induced
Retirement, and Aggregate Capital Accumulation” (1974),
with a discussion of the development of economists’ thinking on
lifetime savings patterns. He starts with a famous early work in
the field:
Ever since Harrod’s (1948) discussion of “hump
savings,” economists have recognized the importance of
saving during working years for consumption during
retirement (p. 906).
“Hump-savings” refers to the shape of an individual’s savings
curve over time: low at the beginning, higher in the middle,
lower at the end. This basic model is used throughout the paper
and holds together all that follows. Feldstein cites a number of
authors who have observed this regularity in empirical data on
personal savings patterns as confirmation of the model. He goes
on to argue that while the “hump-savings” model works well to
explain most of the observed data, the effect of certain government policies on individual savings has never been measured
empirically. In particular, he poses the question: What is the
effect of social security on individuals’ lifetime savings? He
then cites the work of three other authors as well as his own
earlier work as examples of this neglect.
In this way, Feldstein presents his current research as a
necessary development out of well established research
program, the next question to ask on a line stemming from
important ancestors to contemporary scholarly research. The
reader is thus prepared for the empirical analysis that follows,
36
WRITING ECONOMICALLY
which shows that “social security depresses personal savings by
30–50 percent” (Martin Feldstein, 1974).
PRESENTING YOUR HYPOTHESIS
The literature review sets out the issues that motivate your paper
and demonstrates your familiarity with what others have written on
the topic. The next step is to formulate a specific questions, problem,
or conjecture, and to describe the approach you will take to answer,
solve, or test it. Often, this will take the form of an empirical hypothesis: “social security depresses personal savings”; “high levels of
employment are related to high levels of inflation,” etc. An empirical hypothesis makes a claim about how some part of the economy
works and can be assessed by analyzing the relevant data.
In presenting your hypothesis, you need to discuss the data set
you are using and, in most cases, the type of regression you will run.
You should say where you found the data, and use a table, graph, or
simple statistics to summarize them. You should explain how the
data relate to your hypothesis and note any problems they pose. If
you have only a small set of observations, or have to use proxies
for data you cannot directly observe, you should explicitly acknowledge this.
FOR EXAMPLE
In “Employment-Based Health Insurance and Job Mobility: Is
There Evidence of Job-Lock?,” Brigitte Madrian (1994)
writes:
37
THE TERM PAPER
To study the phenomenon of job-lock, one would like
information on individual and family health status,
worker mobility, and the health insurance plans of both
the firm for which and individual works and to which one
could move. Unfortunately, information on health status
and health insurance is not widely available in labor force
surveys, information on worker mobility is not typically
available in health surveys, and information on insurance
plans of companies for which an individual could have
worked is nonexistent.
Madrian goes on to offer an alternative method to study joblock by looking at two groups of workers who are similar in all
respects but one: one group has employer provided health
insurance and the other does not. She then measures the
number of times the workers change jobs and observes a
significant negative relationship between employment-based
health insurance and job turnover.
Madrian is careful not to jump to a hasty conclusion, noting
that this correlation is not itself conclusive evidence of job-lock.
Employers that provide health insurance often provide other
benefits that will affect mobility. In addition, unobserved
characteristics of workers’ health status may independently
affect job sorting and mobility because workers with preexisting conditions may have a harder time getting new health
insurance. Still, Madrian’s careful analysis controls for as
many factors as possible and allows her to conclude: “that
there is substantial health insurance-related job-lock.”
In a term paper, it may not be possible to reach conclusive empirical results. You may have incomplete data, or your regression
coefficients may not be significant, or you may not have controlled
38
THE TERM PAPER
for significantly all the factors involved. It is better to acknowledge
these shortcomings than to make overly broad and unsupported
statements.
PRESENTING YOUR RESULTS
by Christopher Foote
One of the more common mistakes made by authors of economic
papers is to forget that their results need to be written up as carefully
and clearly as any other part of the paper. There are essentially two
decisions to make. First, how many empirical results should be presented? Second, how should these results be described in the text?
How many results should I report?
Less is usually more. A common mistake made by virtually all novice
researchers (including graduate students) is to include every parameter estimate from every regression specification that was run.
Such a “kitchen sink” approach is usually taken to show the world
that the researcher has been careful and done a lot of work and that
the main results of the paper are not sensitive to the choice of sample
period, minor changes in the list of regressors, etc. However, pages
of parameter estimates usually muddy the message of the paper. The
reader will get either lost or bored. A good general rule is to present
only those parameter estimates that speak directly to your topic.
FOR EXAMPLE
Suppose you are writing about the effect of education on wages.
Your main regression places an individual’s wage on the
39
THE TERM PAPER
left-hand side and regressors such as education, race, gender,
seniority at the individual’s job, labor market experience, and
state of residence on the right hand side. You believe that the
regressor of interest (education) is correlated with the error
term of the wage equation – more “able” people earn more at
their jobs, i.e. have a high residual in the wage equation, and
also obtain more education. Because of this correlation
between the error term and education, the measured effect of
education in the regression will reflect not only the true causal
effect of education on wages but also some of the effect of
ability on wages. To circumvent this “ability bias” you use a
separate measure as a proxy for ability. Though such a proxy is
probably not available, assume for the sake of exposition that a
special dataset contains an individual’s evaluation by his or her
second grade teacher. When presenting your results you want to
focus only on the estimates of the education effect and the
ability effect. Your table might look something like this:
Table I OLS estimates of the effect of education on wagesdependent variable: log of yearly earnings
1985–1995
(1)
Years of education
(2)
(3)
(4)
(0.091 (0.031 (0.086 (0.027
(0.001) (0.003) (0.002) (0.005)
Ability dummy
(0.251
(0.010)
State dummies included?
No
No. of obs.
35,001 35,001 19,505 19,505
No. of persons
Adj. R
40
2
No
(0.301
(0.010)
Yes
Yes
5,505
5,505
4,590
4,590
0.50
0.55
0.76
0.79
THE TERM PAPER
Notes: Standard errors are in parentheses. Data are from the Tennessee
Second Grade Ability Survey and Wage Follow-up, and include individuals evaluated between 1962 and 1971. The “ability dummy” equals
one if the individual’s second grade teacher classified the individual as
“able,” zero otherwise. Each regression also includes yearly dummies,
10 one-digit industry and 20 Census-defined occupation dummies, labor
market experience (defined as age –6), experience squared, seniority on
the current job, seniority squared, Census region of current residence,
marital status, race, gender, and a dummy variable denoting whether the
individual lives in a city of more than 100,000 persons. Columns (3) and
(4) have fewer observations because state of residence is not available
for some individuals.
Note that Table I does not present the parameter estimates of
your control variables, regressors such as marital status and
seniority, but presents any detail that helps interpret the
parameters of interest (including the identification of the
dependent variable, which is annoyingly left off of many
tables). For example, explain how you define labor market
experience as well as why the third and fourth regressions have
fewer observations than the first and second regressions. The
notes to your table should be extensive enough so that the
reader does not have to look back at the text to understand what
is being presented. The cardinal sin, to be avoided at all costs, is
to report your estimates in terms of “α” or “β” (the actual
Greek letters from your equations) without stating what these
coefficients mean. Using eight-letter abbreviations from your
Stata or SAS program (YEDUCT1 or ABIL25A) is not much
better.
Do not worry about repeating yourself in the text and the
notes – this will often be necessary so the reader can understand
your table without looking back at the text. You should present
enough information in total so that a researcher could replicate
your results. For very detailed projects, this may require a data
appendix. Finally, the notes to the table should indicate
whether you are reporting standard errors or t-statistics in the
41
THE TERM PAPER
parentheses underneath the coefficients. Both are seen in the
literature, so you must be clear which you are using. As a
general rule, it is better to report standard errors. That way,
your readers can more easily choose the statistical method they
would like to use in evaluating your numbers.
After presenting these results you may want to discuss any
additional robustness checks that you performed. The third and
fourth columns of Table I are robustness checks of sorts; they
show that the effect of including ability in the regression is the
same whether or not we include state level dummy variables.
We may also have checked whether the estimate of the
education effect is lower when ability is included, if we subset
only on male household heads or if we restrict the sample to the
1990s. Sometimes all that is necessary is to let the reader know
in the text that you performed these tests and that the main
results were unaffected. For a single robustness check, this
information can even appear in a footnote keyed to the relevant
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