URL: http://faculty.haas.berkeley.edu/levine/cheap_advice.html


<h>David Levine's Cheap Advice:

<h>Going on the Job Market

   <p>To go on the academic job market requires that by late November you
   have one pretty good paper, and two paper ideas. When first sending
   your packet to departments, ask for a faculty list with research
   interests, so you will know with whom you are dealing.

<h>Questions you are likely to be asked many times

   <l>1. Tell me about your thesis.

   §         <p>Prepare a five minute talk. Sound enthusiastic! Realize that
   most of your interviewers know little about your field, so provide
   lots of motivation for your study. Practice the talk with friends
   before the meetings.

   §         <p>Prepare answers to the three or four most frequent questions
   and criticisms of your work.

   §         <p>Prepare a few thoughts about further research concerning
   your thesis.

   <l>2. When do you think you will finish your dissertation?

   <p>Your odds of landing a job are higher if you can convincingly argue
   you will be done by June (best) or at least by September. Employers do
   not like new assistant professors to arrive with unfinished
   dissertations (although many such assistant professors exist).

   <l>3. What are you thinking about working on next?

   <p>Describe one or two research projects that you would like to work on
   next. You don't need to carry out these exact projects. You can
   include extensions of your thesis: ideas it has spawned, or tests of
   it you will someday do. At least one idea should be distinct from your
   thesis. On the other hand, don't be scattered. Most of your ideas
   should hang together, as if you were writing a book or two.

   <l>4. What courses would you like to teach?

   <p>Be sure to know the needs of the department before answering this one.
   Mention undergrad and grad courses, and perhaps an advanced grad
   course. The advanced courses are sought after; don't sound as if you
   demand to teach one. Mention a service course (intro, micro, or macro)
   that you are willing to teach.

   <p>Know the text you might use in the course, particularly for
   undergraduates. (You can ask around for plausible texts, and perhaps
   reading lists.) Think about an outline of topics for one or two
   courses.

<h>Questions to ask

   <p>The interviews are also for you to find out things. Also, asking
   questions shows you are interested, and fills gaps in the conversation
   that the incompetent interviewers leave when they run out of things to
   say. Do not discuss money. There is lots of time for that.

   <l>Facilities: library, research assistants, computers,
   research institutes, etc.

   <l>Teaching:

   o       <p>Load: anything above four quarters or 3 semesters a year is
   heavy, below that is light.

   o       <p>Likely courses you would teach

   o       <p>The choice you would have

   §         <p>Possible to create your own course?

   o       <p>Quality of students: undergrad and grad

   <l>Faculty:

   o       <p>Size, interests, mix of fields

   §         <p>Visit faculty web pages to find out who is in your field
   beforehand.

   §         <p>Department: direction it is going, research vs. teaching,

   <l>Later in the process you can ask about:

   o       <p>Class size, TA's, readers, undergrad vs. grad

   o       <p>Summer money and travel money

   o       <p>Tenure patterns (% assistants who get tenured)

   o       <p>Secretary, photocopy and phone rules, parking

   §         <p>These sound minor, but can be important in the long run

   o       <p>Personal computer and printer; access to a larger research
   machine

   o       <p>Housing help: search, mortgage, faculty housing, flybacks to
   look for housing

   o       <p>Research assistant

   o       <p>Reduced teaching load first year

   o       <p>Minimize # of preparations (separate courses) you teach in one
   year

   o       <p>Any grants that are available. (Some may have deadlines before
   your arrival.)

<h>Helpful links

   <h>Job Sites

   §         <l>Jobs for Economists

   §         <l>Academy of Management (AOM)

   §         <l>Chronicle Careers

   o       <p>Mgmt: 

   o       <p>Policy:

   §         <l>Association for Public Policy Analysis and Management
   (APPAM)

   §         <l>Academy of International Business
   

   <h>Other Useful Sites

   §         <l>Two articles on market for junior economists at JOE website:



   §         <l>The importance of asking good questions
   

   §         <l>Landing Your First Job
   

   §         <l>On negotiating your offer
   

<h>Final Hint

   <p>The key to the interview is to be enthusiastic. Interviewers are
   looking for (1) people who would accept an offer, and (2) nice
   colleagues. The first consideration implies that you should have a
   reason why the interviewer's school is really your first choice ("Oh,
   I just love -40 in winter and searing heat in summer," she explained
   to the Minnesotans). The second point implies that you must be
   friendly, witty, and easygoing (during the high-pressure meetings!).
   Nothing is more important than being friendly and collegial. They are
   looking for someone they would like to have lunch with every day-this
   dominates most other criteria.

   <p>This is just one in a series of David Levine's Cheap Advice. Collect
   them all! Dazzle your friends! Feel free to circulate to anyone who
   might find them useful.

   

   <p>Write to David Levine, Haas School of Business, University of
   California, Berkeley CA 94720; levine@haas.berkeley.edu for additional
   Cheap Advice, or to give Cheap Advice back to the source. Feedback is
   always appreciated.

<h>David Levine's Cheap Advice:

<h>Writing a Dissertation

   <p>I was trained as a graduate student to read other people's research.
   Then I finished my special field exams and was told to go write some
   research. I compare my experience to learning how to read literature,
   then being asked to do creative writing. Not unrelated, but hardly the
   same set of skills. Here is some advice I found helpful when I was
   searching for a topic.

   <p>Hints for finding paper topics: Choosing a paper topic requires
   balancing the importance and feasibility of the topic. Feasibility
   involves tractability for theoretical research, and data availability
   for empirical research. I recommend creating a number of one-page
   paper proposals, each with a topic sentence and data source.

   <p>There are several heuristics for finding researchable paper topics.
   One way is to list three of four papers you like. This list may hint
   at the style, political point of view, level of abstraction, and
   methods that are appropriate for you.

   <p>Other paper ideas are motivated by bad research, not good: find
   statements by policy-makers, analysts and journalists that make you
   angry, and find data sets to address the issue. When studying for
   exams, keep a list of stupid things you read to return to during the
   dissertation stage.

   <p>Don't be afraid of normal science: repeating in a longitudinal data
   set what others have done only in the cross section. Some paper ideas
   are data-driven: read codebooks from a variety of data sets and see if
   certain questions spark ideas or tests of theories you find
   interesting. For every paper you read, think what else you would have
   done with that dataset or methodology.

   <p>Write a paper, not a dissertation. A dissertation can be a daunting
   prospect. If possible, focus on a 25-page paper with a clear
   one-sentence topic. If you like this paper, then it can become the
   basis of a dissertation. I promise you that just about any topic can
   grow to 150 pages; nearly all topics students first choose are WAY too
   broad.

   <p>A dissertation is any stack of papers with three signatures on the top
   sheet. Paul Samuelson's dissertation was modestly entitled Foundations
   of Economics. It lived up to that title, and remains a classic to this
   day. I initially felt that my dissertation should be, if not that
   good, at least vaguely comparable in the sense of answering one of the
   Big Questions.

   <p>Do not fall prey, as I did, to the "magnum opus fallacy". A
   dissertation should be normal science that certifies your competency.
   Save the big thoughts in a file, and get finished! Write an opus when
   you are a professor, and are being paid for it. Meanwhile, negotiate
   the smallest useful chunk of the Big Project with your dissertation
   advisers, and do that single piece of research.

   <p>A dissertation group is essential. Having folks to bounce your ideas
   off of at an early stage is irreplaceable. The members of your
   dissertation group do not need to have similar fields; any smart
   person will be useful at each stage of a project, from vague ideas
   through research design, and write up. All you need are people who are
   willing to listen to raw ideas, and willing to read first "pre-drafts"
   of chapters.

   <p>This is just one in a series of David Levine's Cheap Advice. Collect
   them all! Dazzle your friends! Feel free to circulate to anyone who
   might find them useful.

   

   <p>Write to David Levine, Haas School of Business, University of
   California, Berkeley CA 94720; levine@haas.berkeley.edu for additional
   Cheap Advice, or to give Cheap Advice back to the source. Feedback is
   always appreciated.

<h>David Levine's

<h>Cheap Advice for New Faculty

   <p>When people evaluate you for tenure, they need to know (1) who you
   are, and (2) what (one or two sentences) results you are associated
   with. Thus, my basic advice is focus your research, get it read, and
   get seen. Sadly, the visibility of yourself is as important as the
   quality of your work in professional success.

   <p>Have a theme: You should think of your research as writing a book, not
   articles. The idea is that your first five years' research should
   involve one or two unifying themes.

   <p>The reason for sticking to a theme is that people evaluating you need
   to be able to say "This young scholar is one of the world's experts at
   _______." You get to fill the blank. However, your work must hold
   together so that there is some word or phrase they can stick in the
   blank.

   <p>In an ideal world, academics would be able to study any important
   topic they were competent to shed light on. In the real world,
   assistant professors are being evaluated; you don't need to play the
   game I describe, but now you know the rules.

   <p>Get read: List people who should read your papers. The list should
   include at least three groups: a dozen or so senior people in your
   field who are likely to write letters evaluating you when you go up
   for tenure; classmates and other buddies who are likely to actually
   read the stuff; and people who work on related topics and you would
   like to cite your stuff. Make up a master list that receives most
   papers, and modify it for each paper. Look at each paper's
   bibliography for ideas on who might want to see it. (Everyone wants to
   see papers that cite them -- that's why so many professors read papers
   from the back.)

   <p>Typically you should mail out papers in their working paper stage, one
   draft before submission.

   <p>Feedback is crucial. All research has flaws, and all drafts have
   easy-to-correct flaws. Make sure your research and writing has lots of
   feedback to fix both types. Especially for the clarity issues, be open
   minded. If your parents, friends, colleagues in unrelated disciplines,
   will read the sucker, send it to them!

   <p>Get seen: Travel every year to give seminars. If you are going to be
   near a university, call up six months early and tell them you are
   available and would like to give a seminar.

   <p>Don't be shy: figure out how to give a talk at your field's annual
   convention, and do it! Invite a mix of friends and more well-known
   people.

   <p>Learn how to be a Manager: Secretaries and research assistants are
   just a few of the people you need to learn to manage. The secrets are
   few: respect and communication. Respect is shown, for example, by
   asking their schedule when you propose work, and by always saying,
   "Thank you." In addition, if they have expertise in a job, only give
   advice on how to do it if they ask.

   <p>Most attempts at communication are not completely successful. (In the
   classroom this problem is reflected in my maxim: "I can teach faster
   than they can learn.") Thus, the golden rule of communication is "Say
   unto others what you believe others have said unto you." After giving
   your instructions, always ask your RA to explain what she thought you
   asked her to do. (Do this in a way that makes it clear you consider
   yourself at fault for any miscommunication. Perhaps: "I didn't explain
   that very well. Can you tell me what you are planning to do?") If they
   don't repeat back to me their understanding of my instructions, then
   it is unlikely the job will be accomplished as I expect.

   <p>Budget your research time: In economics research begun in year t
   usually leads to a first draft in year t+1 or t+2. Circulating it and
   presenting it at a seminar or two brings us to year t+3. Submit it to
   a journal and they will (if you are lucky) ask for a revision in year
   t+4, which you might complete that year. If so, they could accept it
   as fast as year t+5, but it might not come out till year t+6. On the
   one hand, many papers can move from conception to publication in less
   than six years; on the other hand, many papers take more.

   <p>Count back from the time you need to submit your tenure file. If you
   are three years away and your case is less than 100% solid, don't
   begin any new research! At this point your priority must be to move
   working papers and papers with requested revisions into the Accepted
   pile.

   <p>This is just one in a series of David Levine's Cheap Advice. Collect
   them all! Dazzle your friends!

  
   <p>Write to David Levine, Haas School of Business, University of
   California, Berkeley CA 94720; levine@haas.berkeley.edu for additional
   Cheap Advice, or to give Cheap Advice back to the source. Feedback is
   always appreciated.

<h>David Levine's Cheap Advice:

<h>How to Present Results

<h>Presenting Your Results

   <p>Authors must work hard to make their results easy to follow. Thus,
   tables must be comprehensible by themselves. That is, a reader should
   be able to understand a table without reference to the text (and
   preferably without reference to other tables). The converse rule is
   that the text should stand by itself, even if a reader ignores the
   tables.

   <p>Variable names should be self-explanatory. The text should flow
   without ever showing that the reader has encountered a variable name.
   For example, "Each plant visit by a social scientist corresponded to
   3.1% higher voluntary turnover per month (SE = .9%, P < .05)" is much
   better than "The coefficient of SCISTUD on VOLTUR was .031 (.009),"
   which is better than "S and V were significantly related." In short,
   nobody should know what passed between you and your computer in the
   middle of the night. Name your dummy variable Male or Female, but not
   Sex.

   <p>Often variables are proxies for conceptual variables. If you want to
   measure complexity, but your variable is log(employment), name the
   variable employment (if all variables are expressed in logs) or
   log(employment), not complexity.

   <p>Each table has number and a meaningful title: "Wages Do Not Rise with
   Tenure," not "Wages."

   <p>All statistical tests include the name of the test, the test
   statistic, and the significance level. Include a brief description of
   complex procedures at the bottom of the table. Remind readers of the
   meaning of complicated variables.

   <p>Each estimated equation lists the dependent variable and sample size.
   If one of these is constant for an entire table, list it only once.
   Always include measures of goodness of fit such as R² or
   log-likelihood. Usually include a test of the significance of the
   entire regression (such as an F test for ordinary least squares), and
   appropriate residual diagnostics (such as Durbin-Watson statistics and
   heteroskedasticity tests).

   <p>Coefficients should include standard errors or t statistics, and some
   indication of statistical significance (P values or * for P < .05, **
   for P < .01). A note explains whether there are standard errors or t
   statistics. Report P < .10 only if the sample size is small.  For very
   large datasets it makes sense to demand a higher degree of certainty,
   so only report P < .01.

   <p>Include a meaningful number of digits, usually at two or three
   significant places. Neither .34849560 (3.132534) nor 0.00 (SE = 0.00,
   P < .001) is useful. Sometimes multiply or divide a variable by 10 so
   the coefficient is in a meaningful range.

   <p>Always in the text, and often in the tables, translate the
   coefficients of interest into words. For example, convert logit
   coefficients to measure how a one-unit change in the variable affects
   the probability of the occurrence of the event (dP/dX). Translate
   hazard rate coefficients to show how a one unit change in the variable
   affects the expected time until some event occurs: "If the union local
   is in a city, its expected lifetime was four months shorter than if it
   was rural."

   <p>Also, always explain whether the effect is large or not, perhaps by
   comparing its size to something readers understand. For example, the
   importance of marital status on wages can be expressed as how many
   years of education are required to raise wages by as much. Sometimes
   standardized coefficients (expressed in standard deviation units) are
   useful: "A one month increase in training (approximately one standard
   deviation) corresponds to 4 percent lower turnover (approximately one
   half of a standard deviation)."

   <p>Effect sizes from Lisrel, factor analysis, path analysis, ordered
   logits, etc., are hard to understand. Thus, explain the size as well
   as the statistical significance of the important effects.

   <p>Statistical significance: Most authors focus on whether coefficients
   are statistically significantly different from zero at the 5 percent
   level.  Thus, if b[1] is statistically significant from zero at the 5%
   level, but b[2] is not, some authors write as if b[1] is different
   from and more important than b[2].  At a minimum, authors should focus
   on confidence intervals, and explicitly test if b[1] and b[2] differ
   by statistically significant amounts.

   <p>Summary statistics should be included for the referee, although they
   do not always need to be in the paper. Usually include means, standard
   deviations, units, sources, geographical region covered, and sample
   size. Usually include summary statistics for control variables as well
   as for the main variables of interest. Include the statistics for the
   un-logged version of any important variables you use in log form. If
   your paper computes important and meaningful intermediate results
   (residuals from a first-stage equation, for example), include their
   summary statistics.

   <p>Often give the referee a table of correlations of either the main
   variables or of all the variables.

   <p>Use simple statistical procedures to complement fancier analyses. Many
   papers have a simple comparison of means as their main result (to be
   formalized and measured more precisely in later sections). If your
   paper has such a comparison at its core, then present the unadjusted
   means (e.g., men vs. women, or U.S. vs. Japan) before the fancier
   statistical analysis.

   <p>Figures and graphs, like tables, are supposed to be comprehensible
   without reference to the text, and the text without reference to the
   figure. Place labels (in words, not symbols or variable names) and
   units on axes.

   <p>Equations worthy of being in your paper can be expressed as a
   sentence. Do so. Many economic theories generate an interesting
   first-order condition. Restate it in words: "At the optimum, a dollar
   spent today must bring the same utility as a dollar spent tomorrow,
   suitably discounted."

   <p>Abstracts present the question the paper will answer. Since social
   scientists are not mystery writers, abstracts also summarize the
   results. Inability to write an abstract of fewer than 100 words often
   indicates deeper problems with the paper.

<h>Robustness checks and limitations of the study

   <p>No research is perfect. This section presents a checklist of common
   imperfections in empirical research. Discuss the limitations of your
   paper and plausible alternate explanations for the results.

   <p>Surveys face problems with the match between the actual sample and the
   perfect sample. Always mention the response rates and possible
   response biases. Are responses likely to be sensitive to changes in
   the wording of the questions? Do respondents have incentives to hide
   their attitudes? Are attitudes likely to match behaviors?

   <p>A naming issue appears when data undergo factor analysis or are summed
   into an index. Do not merely name the factors or indices, but present
   a sample of the questions along with the factor weights. Differentiate
   exploratory from confirmatory factor analysis.

   <p>Econometric and statistical analyses are subject to all the
   difficulties of surveys. They also fall prey to the "textbook
   chapters:" simultaneity, sample selection, measurement error,
   outliers, and so forth.  Almost all analyses should use methods that
   adjust for clustering of the sample (as in most common datasets) and
   that are robust to the presence of heteroskedasticity.  Re-analyze the
   data several times to check the specification, and make sure that your
   results are not sensitive to changes in the estimating technique,
   functional forms, control variables, and so forth. If all is well,
   allude to these results briefly, but do not include them in the paper.
   Often include copies of these tables for the referee.

   <p>Experiments almost always have questionable external validity. Is
   there any reason to believe people in actual organizations involved in
   complex social networks making decisions that affect their careers
   over many years act the way the college sophomores do in your one-hour
   treatment?

   <p>Is the name you have given your treatment appropriate? If you tell one
   group of people they are not worth the wage they receive, this
   treatment may affect self-esteem as well as perceived equity. Thus,
   naming the treated group perceived inequity can mislead readers.

   <p>Case studies have limited generalizability. Explain in what sense this
   case study generalizes, and outline the limits of its
   generalizability. What are the likely biases due to subjective
   perception and reporting?

   <p>Causality is almost never clear in the social sciences. Common
   problems include reverse causality, selection effects, and omitted
   variable bias. Discuss alternative causal explanations for the
   results.  These alternative channels often suggest additional tests
   you might perform.

   <p>When using instrumental variables or multi-equation methods such as
   two-stage least squares and maximum likelihood, always list your
   instruments or other identifying assumptions. Include these lists in
   both the text and the tables. Justify why it is plausible that your
   instruments are exogenous. Both identification by functional form (as
   in many sample selection models) and instrumenting with lagged
   variables require strong justification.

   <p>Economic theory: Explain the robustness of the results in "assumption
   space." Differentiate assumptions that are crucial from those that
   merely simplify. Even if you do not prove, explain what happens if
   preferences are not Cobb-Douglas, or if agents are not identical.
   Usually include detailed derivations in an appendix for the referee.

<h>Stylistic issues

   <p>Go for clear exposition of substance as opposed to trying to impress
   readers with big words, hard statistics, or fancy theory. Present the
   main conclusions so that they will be accessible to the nonspecialist
   reader in the final section.

   <p>Use footnotes sparingly, and Latin almost never. Don't rely on
   variable names if you can spell them out. Remind readers often of the
   meaning of your symbols: often replace "q" with "the elasticity of
   substitution." Readers have to expand out the entire phrase--help them
   out.

<h>Final words

   <p>No article has ever suffered from too much helpful advice from
   colleagues. Be sure many readers look at your article. Use family,
   friends, colleagues from other departments: most of your paper should
   be understandable even to the nonspecialist.
   _______________________

   [1] From the BPP class of 2006.

