1. Price differentiation under narrow MFNs
ACE annual conference 2017
Tim Reuter
17 November 2017

2. Introduction
Various national competition authorities investigated online travel agents’ (OTAs) most favoured nation clauses; RBB advised Booking.com during these investigations
Two flavours of MFNs
Wide MFN / horizontal parity: Hotels cannot post lower prices on competing OTAs than on Booking.com vs
Narrow MFN / vertical parity: Hotels cannot post lower prices on own websites than on Booking.com
Prevention of free-riding as a potential efficiency rationale (not discussed today)
Relevance also in the broader context of the CMA’s and BKartA’s investigation into digital comparison websites (and the CMA’s resulting case for home insurance comparison websites)
17 November 2017

3. Overview Introduction Theory of harm A timeline of events
Testable hypotheses of the theory of harm
Analysis of price differentiation
Description of the data set
Analysis and results
Shortcomings of data set
17 November 2017

4. Theory of harm
Wide MFN
If OTAs cannot obtain lower room rates than Booking.com, OTAs have no incentive to lower commission rates in exchange for lower room rates
=> Competition between OTAs harmed (and between hotels)
Narrow MFN
A lower price on some OTA than on Booking.com implies that the price on this OTA is below the price on the hotel’s website
=> Hotels risk cannibalizing direct sales
If cost of generating a direct booking is below OTA commission rates, hotels would be unwilling to set higher prices on their own websites than on OTAs
=> Narrow MFNs may replicate the effects of wide MFNs
17 November 2017

5. A timeline of events
Analyses presented were conducted between May and November 2016
Aug 2015: French parliament adopts legislation blocking narrow MFNs. However, by obtaining preferred status with Booking.com, hotels opt-in to accepting narrow MFNs again
Dec 2013: BKA prohibits HRS’ (wide) MFNs – confirmed in appeal
Forthcoming: Higher Regional Court Düsseldorf to decide on Booking.com’s appeal
Dec 2015: BKA prohibits Booking.com’s narrow MFNs
Feb / Apr 2017: ADLC and ECN issue review of switch from wide to narrow MFNs
Jul 2015: Narrow MFNs accepted as commitments by a number of CAs
17 November 2017

6. Testable hypotheses of the theory of harm
Hotel pricing data allow to test the theory of harm
Assumption that hotels are unwilling to set higher prices on their own website than on OTAs
Are there instances of higher prices on hotel websites than on OTAs?
Prediction that there is little price differentiation under narrow MFNs
Is there price differentiation between OTAs?
Prediction that price differentiation between OTAs under narrow MFNs is lower than under no MFNs
Test by comparing price differentiation under different MFN policies
Before-and-after the prohibition decision in Germany
Between preferred and standard accommodations in France
Diff-and-diff under benchmarking these comparison to those in other countries
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7. 2. Analysis of price differentiation
17 November 2017

8. Description of the data set
Both OTAs and (sometimes) hotels post prices on metasearch-sites (MSS) such as Trivago and TripAdvisor
Internet bot queries MSSs for a set of selected hotels and records prices founds on OTAs and the hotels’ websites
Mimics consumer behaviour
Records for each OTA (and direct distribution) the cheapest price of a given hotel
Operates as part of Booking.com’s ordinary course of business
Representative sample for all accommodations found on Booking.com (only about 15% of accommodations; but representing > 80% of revenues)
We assessed data for 12 ECN working group countries (plus Austria and Switzerland)
Only available after Booking.com implemented commitments (i.e. no comparison of wide to narrow MFNs possible)
17 November 2017

9. MSS Screenshot
17 November 2017

10. Practical problems assessing the data
Large data set
Close to 50,000 hotels queried (in relevant countries); each queried six times per day -> 54 million queries
Each query can return up to one price per OTA, corresponding to one observation
Raw data set with several hundred million observations and >100GB size
Limited access to the raw data by advisors
Client was running SQL scripts providing aggregated data for our specific needs, e.g. number of searches, in which price on Booking.com ≠ price on other OTAs
Limited number of analyses we could run
Limited visibility on some data specificities (e.g. changes in the booking window and length of stay adopted)
17 November 2017

11. Result 1: Evidence of higher prices on hotel websites
Share of searches for which prices in direct distribution are above the prices of at least one OTA
Prices in direct distribution higher than on OTAs in a significant share of searches
Figures contradict the centrepiece assumption of the theory of harm
Similar figures are robustly found across all countries and subsamples of accommodations
Average share of searches for which price in direct distribution is higher than on OTAs
Proportion of hotels that are cheaper on OTAs on more than 50% of searches
[10-15%]
[5-10%]
17 November 2017

12. Result 2: Price differentiation under narrow MFNs
Definition out-of-parity-rate (OOP): share of searches with price on at least one OTA ≠ price on Booking.com
Significant level of price differentiation between OTAs under narrow MFNs
Hotels can set different prices on different OTAs (in exchange for lower commission rate)
Result robust for all countries and hotels subject to narrow MFNs
Is the level of price differentiation lower than it would be under no MFNs?
Average OOP-rate
Proportion of hotels with OOP-rate of at least 50%
[35-40%]
17 November 2017

13. Result 3: Price differentiation under no MFNs not higher than under narrow MFNs
Comparison between preferred and standard accommodations in France benchmarked on other countries
(OOPFrance_Preferred – OOPFrance_Standard) – (OOPECN_Preferred – OOPECN_Standard)>0
No evidence that hotels not subject to narrow MFNs price differentiate more than others
Confirmed by regression analysis relying on both German and France “experiment”
 OOP-rate
France
Rest of ECN WG
Delta
Standard
[35-40%]
[2-4pp]
Preferred
[40-45%]
[0-2pp]
[8-10pp]
[6-8pp]
17 November 2017