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The Puzzle of Price Dispersion on Amazon

Price dispersion is an excellent indicator of transactional frictions. It isn't that absent price dispersion; we can confidently say that frictions are negligible. Frictions can be substantial even when price dispersion is zero. For instance, if the search costs are high enough that it makes it irrational to

It Pays to Search

In Reinventing the Bazaar, John McMillan discusses how search costs affect the price the buyer pays. John writes: “Imagine that all the merchants are quoting $1[5]. Could one of them do better by undercutting this price? There is a downside to price-cutting: a reduction in revenue from any customers

Feigning Competence: Checklists For Data Science

You may have heard that most published research is false (Ionnadis). But what you probably don’t know is that most corporate data science is also false. Gaurav Sood The returns on data science in most companies are likely sharply negative. There are a few reasons for that. First, as

Ruling Out Explanations

The paper (pdf) makes the case that the primary reason for electoral cycles in dissents is priming. The paper notes three competing explanations: 1) caseload composition, 2) panel composition, and 3) volume of caseloads. And it “rules them out” by regressing case type, panel composition, and caseload on quarters from

Preference for Sons in the US: Evidence from Business Names

I estimate preference for passing on businesses to sons by examining how common words son and sons are compared to daughter and daughters in the names of businesses. In the US, all businesses have to register with a state. And all states provide a way to search business names, in

Learning From the Future with Fixed Effects

Say that you want to predict wait times at restaurants using data with four columns: wait times (wait), the restaurant name (restaurant), time, and date of observation. Using the time and date of the observation, you create two additional columns: time of the day (tod) and day of the week

Rehabilitating Forward Stepwise Regression

Forward Stepwise Regression (FSR) is hardly used today. That is mostly because regularization is a better way to think about variable selection. But part of the reason for its disuse is that FSR is a greedy optimization strategy with unstable paths. Jigger the data a little, and the search paths,

Faites Attention! Dealing with Inattentive and Insincere Respondents in Experiments

Respondents who don’t pay attention or respond insincerely are in vogue (see the second half of the note). But how do you deal with such respondents in an experiment? To set the context, a toy example. Say that you are running an experiment. And say that 10% of the

The Declining Value of Personal Advice

There used to be a time when before buying something, you asked your friends and peers about advice, and it was the optimal thing to do. These days, it is often not a great use of time. It is generally better to go online. Today, the Internet abounds with comprehensive,

Maximal Persuasion

Say that you want to persuade a group of people to go out and vote. You can reach people by phone, mail, f2f, or email. And the cost of reaching out f2f > phone > mail > email. Your objective is to convert as many people as possible. How would