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Gaurav

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

Deliberation as Tautology

We take deliberation to be elevated discussion, meaning at minimum, discussion that is (1) substantive, (2) inclusive, (3) responsive, and (4) open-minded. That is, (1) the participants exchange relevant arguments and information. (2) The arguments and information are wide-ranging in nature and policy implications—not all of one kind, not

The Value of Bad Models

This is not a note about George Box’s quote about models. Neither is it about explainability. The first is trite. And the second is a mug’s game. Imagine the following: you get hundreds of emails a day, and someone must manually sort which emails are urgent and which