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Tuesday's Assorted Links
City income, weekday fun, dating sites, Beyoncé, and apartments
Hi y’all! Here are five stories from this week that contained some neat applications of economic principles or are related to teaching:
After taxes and adjusting for the cost of living, a six-figure paycheck doesn’t take you as far as you might expect in some cities [Bloomberg]
Remote workers have fueled a surge in weekday exercise, cosmetics, and leisure [The New York Times]
If you use dating sites as an example of product differentiation, you can add a new one to your list: conspiracy theorists [Vice]
Tickets to see Beyoncé in the U.S. are so expensive that some American fans are flying to Europe instead [NBC News]
As the demand for additional studio and 1-bedroom apartments grows, it has pushed the average size of an apartment in the U.S. down to 887 square feet [RentCafe]
Last summer, Disney+ announced a 38% price increase, which caused concern among customers, with surveys indicating that 23% would change their ad-free subscription. However, when the price change took effect at the end of the year, only 6% of customers actually followed through with cancellation, revealing the significant gap between stated and revealed preferences. Yesterday’s article looked into the concepts of stated and revealed preferences to see why people behave differently than they say would:
One of the stories that stood out in today’s links was the one on conspiracy theories and dating. The online dating market is fascinating to economists because it relies on a lot of key concepts in order to be successful. Paul Oyer, a Stanford professor of economics, wrote “Everything I Ever Needed to Know about Economics I Learned from Online Dating,” which draws parallels between online dating and economic principles.
The book discusses how online dating has changed the dating landscape by allowing for a more efficient market, where people can better match with potential partners who meet their criteria. Oyer explains economic concepts such as supply and demand, signaling, and adverse selection, using real-life examples and anecdotes to make them relatable.