First Year

I think first year is crucial for a couple reasons:

1) you can waste a lot of time either under-investing in coursework or over-investing in coursework.

2) the returns to starting research your first year are large

You can take your macro, micro, and metrics sequences through either Wharton or the economics department. That choice does not matter tremendously but depends on what kind of research you want to pursue. If you want to pursue theory (macro, micro, metrics) the economics department coursework is more oriented towards training theory producers (Wharton's coursework is geared to train theory consumers). Most economists pursue applied micro which is probably not uniquely aided by the economics department's coursework. If, however, you'd like to keep your options open to work with someone in the economics department, or pursue theory, or do well in structural applied work--pursuing your coursework in the economics department may be well worth it. They are more time-consuming, so be prepared.

In your first year also consider taking your second-year econometrics requirement through Wharton. Learning basic econometric tools for applied research will enable you to pursue worth-while research your first summer and generally turn you on to thinking of question-design pairs (that is, being able to think of an appropriate design to respond to a particular interesting question). Thinking of ideas for a longer period of time and having an extra summer of investing in your own research will pay rich dividends since the research production function is concave in time.

Lastly, put aside one day every week your first year to invest in your own research. Keep a notebook of ideas that come to you, look around at data, read papers, and start pursuing a few projects that turn you on--it doesn't really matter what they are but when you have a few you like ask a faculty member which ones are the most interesting. Parallel pursue a few different questions until one takes off (you've got an interesting question with a sharp design and appropriate data loaded in your computer) and then break hell on that question. Contrary to the appearances, you are not in graduate school to do problem sets--you're here to do research. Starting early will enable you to think of better ideas and execute more appropriately. I think a lot of students have barely touched research when they start third year. They feel clumsy with data, have little idea of a research agenda, and have no idea about what they can reasonably expect to finish by the time they present their job market paper so they have difficulty finding and choosing a project, and they have no idea what their research production function looks like. In short, start early.

Pursue a design-lite project for instance an event study, instrumental variable (IV) design, or regression discontinuity (RD) design during your first summer.

Wharton's qualifying exams aren't particularly difficult; the exam for microeconomics usually has four questions:

  1. Some sort of novel strategic interaction game for which you need to find a the Bayesian Nash Equilibrium. The game won't have been something you've seen and derivatives might not cut it.

  2. A novel auction question where you need to derive the Bayesian Nash Equilibrium. Consider a risk-averse and a risk-nuetral agent. How and why are their optimal strategies different.

  3. Some sort of Kuhn-Tucker constrained optimization problem with a tax dropped in half-way through the problem. Calculate the compensating variation. What is the tax incidence?

  4. General equilibrium: there is a firm or two (with one or two production goods and one or two input goods) and two agents with differing utility functions. Solve for the general equilibrium quantities and prices. Know properties of different utility and production functions (convexity, CRS, concavity).

The econometrics exam is more difficult to describe. It covers the gritty details of:

  1. Generalized-Least Squares (derive properties)

  2. Maximum Likely Estimation (derive estimator given distribution)

  3. Instrumental Variables estimation (prove the effects on the standard errors using VIF)

  4. Matrix theory (lots of it)

  5. Bootstrapping (code it, what is it used for, properties)

  6. Practical regression inference (everything you could know)

Keywords: Wharton Applied Economics, first year, Andrew Johnston, Andrew, Johnston, economics, applied economics, economist, microeconomics, empirics, empirical economics, Wharton