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Economics

A collection of 57 issues

Reducing Friction in Selling Data Products: Protecting IP and Data

Traditionally, software has been distributed as a binary. The customer “grants” the binary a broad set of rights on the machine and expects the application to behave, e.g., not snoop on personal data, not add the computer to a botnet, etc. Most SaaS can be delivered with minor alterations

Is The Price Right? Dramatic Variability in Prices of Generic Goods Over Short Periods on Major Web Retailers

It used to be that retail prices of generic products like coffee mugs, soap, etc., moved slowly. Not anymore. On major web retailers like Amazon, for a range of generic household products, the variation in prices over short periods of time is immense. For instance, on 12-Piece Porcelain, 12 Oz.

Out of Network: The Tradeoffs in Using Network Based Targeting

In particular, in 521 villages in Haryana, we provided information on monthly immunization camps to either randomly selected individuals (in some villages) or to individuals nominated by villagers as people who would be good at transmitting information (in other villages). We find that the number of children vaccinated every month

Noise: A Flaw in Book Writing

This is a review of Noise, A Flaw in Human Judgment by Kahneman, Sibony, and Sunstein. The phrase “noise in decision making” brings to mind “random” error. Scientists, however, shy away from random error. Science is mostly about systematic error, except, perhaps, quantum physics. So Kahneman et al. conceive of

Profit Maximizing Staffing

Say that there is a donation solicitation company. Say that there are 100M potential donors they can reach out to eachyear. Let’s also assume that the company gets paid on a contingency fee basis, getting a fixed percentage of all donations. The company currently follows the following process: it

Fairly Certain: Using Uncertainty in Predictions to Diagnose Roots of Unfairness

One conventional definition of group fairness is that the ML algorithms produce predictions where the FPR (or FNR or both) is the same across groups. Fixating on equating FPR etc. can harm the very groups we are trying to help. So it may be useful to rethink how to solve

Equilibrium Fairness: How Fair Algorithms Can Hurt Those They Purport to Help

One definition of a fair algorithm is an algorithm that yields the same FPR across groups (an example of classification parity). To achieve that, we often have to trade in some accuracy. The final model is thus less accurate but fair. There are two concerns with such models: 1. Net

Market Welfare: Why Are Covid-19 Vaccines Still Underfunded?

“To get roughly 70% of the planet’s population inoculated by April, the IMF calculates, would cost just $50bn. The cumulative economic benefit by 2025, in terms of increased global output, would be $9trn, to say nothing of the many lives that would be saved.” https://www.economist.com/leaders/

Liberalizing Daughters: Do Daughters Cause MCs to be Slightly More Liberal on Women's Issues?

Two papers estimate the impact of having a daughter on Members of Congress’ (MCs) position on women’s issues. Washington (2008) finds that each additional daughter (conditional on the number of children) causes about a 2-point increase in liberalism on women’s issues using data from the 105th to 108th

It Depends! Effect of Quotas On Women's Representation

“[Q]uotas are often thought of as temporary measures, used to improve the lot of particular groups of people until they can take care of themselves.”Bhavnani 2011 So how quickly can be withdraw the quota? The answer depends—plausibly on space, office, and time. “In West Bengal …[i]n