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Second, some research philosophy: 

I don't believe that most people are conniving or manipulative most of the time. I also don't believe that most economists have this view. Nonetheless, most economic theory research in the last 40 years has centered around what we call "strategic" behavior. In large part, I suspect that this is because non-strategic behavior is assumed to be uninteresting. Welfare will be maximized. Everyone will get along. A substantial share of my work is dedicated to showing that there are many interesting areas to explore that have nothing to do with strategic behavior. Indeed, first-order facts about the world that have never been researched in Economics or Finance are easily explained by people generally being good and helpful.

Compensation policies reflect a lot more than moral hazard and adverse selection:

1) The frequency at which people are paid and the timing of worker bonuses reflect workers' difficulties in saving money.

2) Bonuses aren't just about risk sharing and incentives: the size, frequency, timing, and performance sensitivity of bonuses serve to coordinate the labor market.

Communication practices reflect a lot more than the struggle to overcome divergent interests:

3) Even when an expert honestly wants to provide the best information, her advice may be less reliable than you think.

4) Discrete ratings, like Yelp reviews, student grades, corporate debt ratings, and stock analyst ratings reflect the inherent difficulty in interpreting just what a rater or reviewer means.

5) Different settings feature different patterns of language: referees are harsh, recommendation letters are kind, grades are inflated, my aunt is hyperbolic. This is consistent with saving the "breadth" of the language for the situations in which it most matters that the listener/reader understand what's being said.

This way of thinking about my work is, I hope, helpful, but it's not standard. An alternative way to categorize my work is by topic. I primarily study financial compensation of rank-and-file employees. Past research has concerned the use of signing bonuses, severance pay, incentive pay, stock options, and pay timing as motivation, retention, and screening devices. I'm currently studying compensation practices in the finance industry and the basis of discrete reviews and ratings (think stock analyst ratings, film critic reviews, student grades, and Yelp ratings). Other research interests are corporate governance, short sales, shareholder voting.

1) Who are the most prolific authors in all of economics and finance since 1974?  Take a look at data from a paper I wrote with three co-authors: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3565487. In each year we rank all publications in that year across 48 prestigious journals based on their citations in 2017 (when the data were pulled). We then count the number of papers that each author has above the 95th percentile in each year and add those numbers up for all the years since 1974. That sum is in the column X=95. We do the same for papers above the 90th percentile (X=90) etc. X=0 means that every published paper is counted. Andrei Shleifer is the most prolific author in Economics and Finance in terms of producing highly cited papers. As of 2017, he had published 64 papers that ranked in the top 5% of all papers published in the same year, measured by Web of Science citations. Others have come close in terms of total papers produced, but not in terms of those that are highly cited. For many other interesting meta-facts, check out our paper, linked above, called On the Causal Effect of Fame on Citations.

2) What happens to academic productivity post-tenure? The facts for economists appear in the figure below (full paper and details can be found here: https://papers.ssrn.com/Sol3/papers.cfm?abstract_id=2781693). The solid line plots the average number of publications per year for economics and finance faculty across a wide set of institutions. The number is adjusted so that an author is credited with 1/N publications for an N-authored paper. The dashed line plots the number of publications per year that are among the top 10% most-cited of all publications in that year. In both cases, productivity rises until the researcher is granted tenure, falls abruptly in the following two years, and then drifts down for the remainder of the decade following tenure. 

3) One might imagine that the problem is confined to academics who are barely able to get tenure. Perhaps the best of the best are immune. In the figure below, we separate the sample by how many years it took the researcher to get tenure and plot the average annual number of publications pre- and post-tenure, adjusted for the number of co-authors on a paper. Clearly, those who are tenured earlier are stronger, both before and after tenure. Those who are granted tenure in less than five years are especially productive. But, in all cases, productivity declines substantially after tenure.

4) Do academics branch out into new research areas after getting tenure? These regressions have a paper-author pair as an observation, and have as dependent variables whether the author's paper was with a new co-author, published in a new journal, or published in a new research area. One dependent variable is a dummy for whether the researcher has tenure. We find no evidence that researchers branch out after tenure.

Not all interesting questions are about academic tenure! Here are a few others. 

5) Do CEOs and other executives tend to give to the same politicians as the firms that they control? We calculate, for each executive and each firm in each year, whether the person/firm gave more in aggregate to republicans or democrats that year. If the person/firm gave more to republicans, then that person/firm-year is coded as "1" and if the person/firm gave more to democrat, then that person/firm-year is coded as "-1". We then calculate, in each year, the correlation between CEO giving and the giving of other top-five executives, the correlation between CEO giving and firm giving, and the correlation between top-five executive giving and firm giving. On average, CEOs and other top executives tend to give to similar parties. The correlations of both groups with the firms that they control is low. Deeper analysis shows that firms tend to give to whichever party controls the US congress (though with a substantial bias toward republicans) while executives tend to give to republicans regardless of who controls congress.

6) What determines how often we get paid? When I was in graduate school, I was paid quarterly. Let me just say that it took a lot of planning to be sure that I had money at the end of each pay period! Most people are paid a lot more often. Pay timing is not random, as Chris Parsons and I show in the paper here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1706206. Paying workers more often reduces the volatility of their consumption streams, making them better off in the long-run. Not surprisingly, pay tends to be more frequent for workers who might have more trouble smoothing consumption on their own. As shown below, workers with less education tend to be paid more frequently. Acquiring an education requires planning and long-term focus, both of which correlate positively with the ability to smooth consumption. Workers who own stock or certificates of deposit are also paid less often.

7) Since I got taxi medallion transaction data in a FOIL request to NYC, I thought I'd share some facts. These facts won't be in the paper they were planned for anymore so here you go.  Transaction volume was high in the early years, but prices were low. As prices have risen over time, medallions traded hands less often. When Uber hit the market, prices collapsed, multiple medallion-focused lenders went under, and many medallion owners' lives were ruined.

Prices more than tripled from 2003 to 2013, peaking above $1,000,000. Many of the sales since 2015 have been at foreclosure auctions.