Lightnews — Scholar-powered news

Alex MacKay

@amackay.bsky.social

800 followers 190 following 47 posts

Economist and professor at the University of Virginia. www.alexandermackay.org

Posts Media Videos Starter Packs

Reposted by Alex MacKay

NBER @nber.org · Aug 21

New evidence from a field experiment finds that Amazon brands generate positive benefits to consumers, despite having similar substitutes and receiving priority in search rankings, from Chiara Farronato, Andrey Fradkin, and @amackay.bsky.social https://www.nber.org/papers/w34135

Alex MacKay @amackay.bsky.social · Aug 19

The paper, joint with Chiara Farronato and
@andreyfradkin.bsky.social , is now available as an NBER working paper.

@nber.org link: nber.org/papers/w34135

@ssrn.bsky.social link: ssrn.com/abstract=538...

#EconSky

Alex MacKay @amackay.bsky.social · Aug 19

Our findings suggest that policymakers and regulators should exercise caution when the assessing the role of vertically integrated products and services on platforms.

Even corrections for self-preferencing can reduce consumer welfare, as we show in the paper.

Alex MacKay @amackay.bsky.social · Aug 19

A big reason why is that tastes vary, and some consumers have a preference for Amazon products. Amazon brands add about 5% to consumer surplus in the short run.

This effect varies a lot across categories. We found the largest benefits in acid reducers and batteries.

Alex MacKay @amackay.bsky.social · Aug 19

We found:
1. Consumers select similar products when Amazon brands are not available
2. No evidence for changes in search behavior
3. No evidence for shifts to other retailers

Despite these findings, we still found that consumers valued Amazon brands!

Alex MacKay @amackay.bsky.social · Aug 19

We also used structural modeling to quantify the benefits to consumers of Amazon products and simulate the potential price effects of having low-cost Amazon brands.

Alex MacKay @amackay.bsky.social · Aug 19

Using a custom browser extension we designed, we hid Amazon brands from a random subset of shoppers.
We then looked at:
- What products were selected in their absence
- If consumer search behavior changed
- If consumers went to other retail websites more often

Alex MacKay @amackay.bsky.social · Aug 19

Using a field experiment, we studied how consumers valued Amazon brands and the extent of self-preferencing by Amazon.

We found that Amazon brands bring benefits to consumers, even though they receive a modest prioritization in search rankings.

Alex MacKay @amackay.bsky.social · Aug 11

There is more in the paper, including how dynamics in bargaining translate to dynamic in pass-through.

@nberpubs
link here: nber.org/papers/w34110

Also available on SSRN: dx.doi.org/10.2139/ssrn...

Joint with Santiago Alvarez-Blaser, Alberto Cavallo, and Paolo Mengano

#econsky

Markups and Cost Pass-through Along the Supply Chain

Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings among academics, public policy makers, an...

Alex MacKay @amackay.bsky.social · Aug 11

The model helps explain the observed patterns. It allows us to interpret manufacturer-retailer profit shifts as changes in bargaining leverage.

We evaluate the drivers of this leverage. The manufacturer gets a higher split with (e.g.) lower costs and greater market penetration.

Alex MacKay @amackay.bsky.social · Aug 11

Given the heterogeneity in product-level markups and the stability over time, we model pricing as occurring in two stages:

1. The manufacturer proposes downstream retail prices.
2. The manufacturer and retailers bargain over the wholesale price (and/or lump sum transfers).

Alex MacKay @amackay.bsky.social · Aug 11

We document supply chain markups in the US, the UK, Canada, and Mexico. We find several similarities, though the split of markups between manufacturers and retailers varies across countries.

Alex MacKay @amackay.bsky.social · Aug 11

But: manufacturer and retailer markups move up and down quite a bit. Retail markups fell at the end of 2020 and increased starting in 2022. Manufacturer markups did the opposite.

The movements offset each other, leading to stable total markups.

Alex MacKay @amackay.bsky.social · Aug 11

In the US, total product markups are around 0.67 and relatively flat from July 2018 through June 2023.

Retail prices increase starting in 2022, coinciding with general inflation.

But there is no increase in total markups, i.e., no evidence for "greedflation."

Alex MacKay @amackay.bsky.social · Aug 11

With unique data from a large global manufacturer, we were able to study how product markups vary along the supply chain and over time.

One thing that surprised us: though manufacturer and retail markups bounce up and down, total (manufacturer + retail) markups are stable.

Reposted by Alex MacKay

NBER @nber.org · Jul 31

Pricing algorithms that provide a speed advantage and commitment can be worse for consumers than full collusion, from Zach Y. Brown and Alexander MacKay https://www.nber.org/papers/w34070

Alex MacKay @amackay.bsky.social · Jul 28

Link here: www.nber.org/papers/w34070

Algorithmic Coercion with Faster Pricing

Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings among academics, public policy makers, an...

Alex MacKay @amackay.bsky.social · Jul 28

New NBER WP on algorithmic "coercion."

Unlike collusion, coercion can be achieved by a single firm's pricing algorithm.

It can be worse for consumers than collusion.

@nber.org

Alex MacKay @amackay.bsky.social · Jul 24

Rivals' prices, and the ability to monitor them, play a special role in pricing algorithms. Zach Brown and I discuss the research and the implications in the latest CPI Antitrust Chronicle on Surveillance Pricing.

Read the article here:
tinyurl.com/2pj93aat

Alex MacKay @amackay.bsky.social · May 28

Thank you!

Alex MacKay @amackay.bsky.social · May 27

Link here: alexandermackay.org/files/Algori...

This is joint work with Zach Brown. Comments welcome.

I'll wrap up this thread with a question:

What are some examples where you think pricing speed matters?

alexandermackay.org

Alex MacKay @amackay.bsky.social · May 27

This has implications for the pricing technology that platforms make available to sellers on the platform. Platforms that prioritize profits might allow some sellers faster pricing algorithms, as this softens competition without explicit coordination.

Alex MacKay @amackay.bsky.social · May 27

Coercion can happen even with naive rivals that use simple learning rules. An algorithm that is linear in the rival’s price can lead the rival to set prices well above the competitive level - even when the rival isn’t aware of the algorithm.

Alex MacKay @amackay.bsky.social · May 27

In a few ways, coercive equilibrium is more robust than traditional collusion. It doesn't require all firms to be forward-looking or understand dynamic strategies. This suggests a broad scope for high-speed algorithms to strategically raise prices in practice.

Alex MacKay @amackay.bsky.social · May 27

The intuition: faster pricing provides the algorithmic firm with a “stick” to punish rivals, while commitment across periods enables the algorithmic firm to lead with a high price: the “carrot.”