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It seems to me that the variation of prices for similar or identical products has grown over the last decade. A few examples:

  • On major air routes, price differences between low-cost and traditional carriers are extreme.
  • Retail sales appear more frequent and significant than ever.
  • At a grocery store, on any given day, it seems like some 30% of products are discounted. And I have received up to seven non-negligible coupons (for future use) even when making negligible purchases (under $5).
  • "Deal sites" like Groupon (and a thousand others) have become prevalent.
  • Single consumer electronics items are released as many different versions (with many different prices) with only slightly differing specifications.

All in all, it just seems like companies are getting more sophisticated (and more aggressive) about extracting as much of each consumer's willingness-to-pay as possible. This begs the question:

Can you think of any data that could be used to quantify the increase of price discrimination across time?

Note on edit: I originally asked about welfare considerations also, but found a fantastic answer to that question here.

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  • $\begingroup$ A note on your examples, #2 and #3 are not instances of price discrimination as sales and such don't meet the criteria of price discrimination. To test whether or not price discrimination is used more frequently, this is a tough one. My guess is that price discrimination is more noticeable. $\endgroup$
    – c4sadler
    May 9 '17 at 18:11
  • $\begingroup$ @c4sadler I don't agree. Sales and coupons are used for many reasons other than price discrimination, but they're also used for price discrimination reasons. Take coupons. People with lower incomes clip more coupons than people with higher incomes. People with lower incomes have lower willingness to pay than those with higher income. Coupons allow the producer to serve the two groups of consumers at two different prices. This is pretty classic price discrimination. $\endgroup$
    – Shane
    May 12 '17 at 21:12
  • $\begingroup$ I agree that coupons are a form of price discrimination, however, I disagree that (non-coupon) sales are price discrimination. A price that is discounted to everyone doesn't allow the seller to serve separate groups at different prices. $\endgroup$
    – c4sadler
    May 12 '17 at 22:27
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    $\begingroup$ If the seller keeps a constant discounted price, sure. But given that the price fluctuates between discounted and non-discounted, you are charging different prices to different consumers. Take Black Friday sales: if us poor folk want a TV in March, we can't afford the price and wait until Black Friday. The rich folk wanting a TV in March buy it in March. Same TV, different prices for different consumers. If you want to say the same TV purchased at different times is a different good, fine. But I think you're missing part of the picture if you're not viewing this as price discrimination. $\endgroup$
    – Shane
    May 16 '17 at 12:53
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For current data, you could use a scraping program to collect data from firms' websites. This was the approach taken by a recent paper for airline pricing, so it would definitely work for your first example. In general, it should work for any market that has a significant online presence with universal price quoting. Retail sales should more or less satisfy that description. Grocery stores too nowadays, at least the big ones. See the paper cited for more info on its methods.

But, as your question pertains to the evolution over time, you'd need past data as well. Have a look at The Billion Prices Project at MIT and Harvard. http://www.thebillionpricesproject.com/datasets/

Williams, K. R. (2017). Dynamic Airline Pricing and Seat Availability (Cowles Foundation Discussion Papers No. 2103). Cowles Foundation for Research in Economics, Yale University. Retrieved from https://ideas.repec.org/p/cwl/cwldpp/2103.html

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As said previously, for current data you probably need to do some webscraping yourself. (There are tools out there to download for free.)

I have also found this paper, which might be relevant:

Benjamin Reed Shiller, 2013. "First Degree Price Discrimination Using Big Data," Working Papers 58, Brandeis University, Department of Economics and International Businesss School, revised Jan 2014.

They mainly used comscore data, but looking through the references may be worthwhile for you.

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