Article Summary. Brandeis University economist Benjamin Shiller has written a
paper which explains how Netflix could combine demographic data with
customers’ Web browsing habits to more accurately predict how much a customer
would be willing to pay for a Netflix subscription, and how using this method of
first-degree price discrimination would generate higher profits. Shiller explains
that the more information a company has about its customers, the better it is at
being able to set prices to increase profits. As he stated in his paper, “Using all
variables to tailor prices, one can yield variable profits 1.39 percent higher than
variable profits obtained using non-tailored 2nd degree price-discrimination.
Using demographics alone to tailor prices raises profits by much less, yielding
variable profits only 0.14% higher than variable profits attainable under 2nd
degree [price discrimination].”
Source: Brian Fung, “How Netflix could use Big Data to make twice as much
money off you,” Washington Post, September 4, 2013.
The pricing method described in the article is referred to as first-degree price
discrimination. First-degree price discrimination is also known as
A) arbitrage.
B) perfect price discrimination.
C) odd pricing.
D) two-part tariff pricing.
Suppose two countries use different combinations of inputs, such as labor and capital,
to produce the same product. This implies all of the following except that
A) the two countries use different technologies to produce the product.
B) the inputs are not equally productive in the two countries.
C) the prices of the inputs are not the same in the countries.