De mechanismes van algoritmische collusie

De populariteit van zelflerende algoritmes heeft zorgen gewekt bij academici en mededingingstoezichthouders over het mogelijk prijsverhogende effect van algoritmes voor prijszetting. Experts waarschuwen dat zelflerende algoritmes stilzwijgend zouden kunnen samenspannen en hogere prijzen kunnen bewerkstelligen (colluderen). Aan de andere kant zijn er auteurs die stellen dat coördinatie zelfs voor algoritmes te complex is om zonder verboden informatie-uitwisseling te bereiken. Wij overbruggen het gat tussen theoretische zorgen en dit praktisch scepticisme. In dit artikel analyseren wij mechanismes die ervoor zorgen dat zelflerende algoritmes in een setting met concurrentie relatief hoge prijzen kunnen bereiken, met een onderscheid tussen vorming en stabiliteit van stilzwijgende samenspanning. We analyseren de praktische toepasbaarheid van deze mechanismes. Stabiliteit-bevorderende mechanismes kunnen vóórkomen, maar we vinden het minder aannemelijk dat ook de prijsverhogende mechanismes in de praktijk kunnen worden gerealiseerd, vanwege de aanzienlijke kosten van experimentatie met prijzen, die essentieel is voor deze mechanismes. We concluderen dat het gebruik van AI (Artifical Intelligence) voor prijszetting mechanismes biedt die het risico op algoritmische collusie verhogen, maar de praktische belemmeringen betekenen dat het risico op dit moment beperkt lijkt te zijn tot specifieke markten of samenloop van omstandigheden

Hospital Competition in the Netherlands:An Empirical Investigation

The Dutch government introduced managed competition to the health care sec- tor in 2006. In this regulatory framework insurers compete for enrollees and providers compete for contracts with insurers. The resulting contracts are de- termined by bargaining, which outcome depends on the relative position of the provider. In this paper, we compare how commonly used market power indi- cators predict bargaining outcomes. We combine 2013 transaction data with bilateral contract data. Our empirical models explain the relative dierences in hospitals' revenues while controlling for dierences in the complexity of patients. Four indicators are used: the logit competition index (LOCI), willingness-to-pay (WTP), Elzinga-Hogarty market share and a rule-of-thumb market share. We nd that WTP and LOCI perform best empirically

Price effects of search advertising restrictions

Some suppliers prohibit their distributors from advertising on search engines if the consumer searches for the supplier's brand name. Such restrictions are referred to as “non-brand bidding agreements” (NBBAs). This paper investigates the effect of NBBAs on retail prices in the Dutch hotel sector, where some hotels impose NBBAs on online hotel booking platforms. An NBBA may protect the hotel's own website against competition from hotels on booking platforms because booking platforms cannot target consumers searching for the hotel with a search ad. This may lead to higher prices on the hotel website. However, an NBBA may also generate ad savings, which may lead to lower prices. We use hotel prices from a meta-search site and data on NBBAs from two hotel booking platforms. To correct for unobserved heterogeneity between hotels with and without NBBA, we apply a trajectory balancing approach within a synthetic difference-in-differences framework. Compared to non-NBBA-hotels, NBBA-hotels charge higher prices on their website relative to the price on booking platforms, suggesting a price increase. We identify cases where it is unlikely that consumers benefit from passed-on ad savings

Economic impact of competition policy:A look beyond consumer surplus

Competition authorities try to mitigate negative distortionary effects on the markets by tackling abuse of market power or cartels and by controlling mergers. This study attempts to assess the impact of these endeavours by going beyond calculations of lumpsum effects on consumer surplus. We revise the simulation of Van Sinderen and Kemp (Economist 156(4):365-385, 2008) who use a cut in income taxes as a modelling device to simulate the impact of anti cartel policies. Our approach avoids attributing effects caused purely by changes in taxation to market power and uses changes in the Lerner index as the impuls. We have updated the model to enable simulating the impact of competition policies on productivity and R&D in order to get a balanced view on the effects. We find that the re-distribution of surplus from producers to consumers supported by ACM in this new setting is likely to have a positive effect on productivity, GDP, wages and consumption, and a small positive effect on employment. This differs from the outcome of Van Sinderen and Kemp, who did not find a positive impact on productivity, due to an overestimation of the employment growth

Price effects of search advertising restrictions

Some suppliers prohibit their distributors from advertising on search engines if the consumer searches for the supplier's brand name. Such restrictions are referred to as “non-brand bidding agreements” (NBBAs). This paper investigates the effect of NBBAs on retail prices in the Dutch hotel sector, where some hotels impose NBBAs on online hotel booking platforms. An NBBA may protect the hotel's own website against competition from hotels on booking platforms because booking platforms cannot target consumers searching for the hotel with a search ad. This may lead to higher prices on the hotel website. However, an NBBA may also generate ad savings, which may lead to lower prices. We use hotel prices from a meta-search site and data on NBBAs from two hotel booking platforms. To correct for unobserved heterogeneity between hotels with and without NBBA, we apply a trajectory balancing approach within a synthetic difference-in-differences framework. Compared to non-NBBA-hotels, NBBA-hotels charge higher prices on their website relative to the price on booking platforms, suggesting a price increase. We identify cases where it is unlikely that consumers benefit from passed-on ad savings

De mechanismes van algoritmische collusie

De populariteit van zelflerende algoritmes heeft zorgen gewekt bij academici en mededingingstoezichthouders over het mogelijk prijsverhogende effect van algoritmes voor prijszetting. Experts waarschuwen dat zelflerende algoritmes stilzwijgend zouden kunnen samenspannen en hogere prijzen kunnen bewerkstelligen (colluderen). Aan de andere kant zijn er auteurs die stellen dat coördinatie zelfs voor algoritmes te complex is om zonder verboden informatie-uitwisseling te bereiken. Wij overbruggen het gat tussen theoretische zorgen en dit praktisch scepticisme. In dit artikel analyseren wij mechanismes die ervoor zorgen dat zelflerende algoritmes in een setting met concurrentie relatief hoge prijzen kunnen bereiken, met een onderscheid tussen vorming en stabiliteit van stilzwijgende samenspanning. We analyseren de praktische toepasbaarheid van deze mechanismes. Stabiliteit-bevorderende mechanismes kunnen vóórkomen, maar we vinden het minder aannemelijk dat ook de prijsverhogende mechanismes in de praktijk kunnen worden gerealiseerd, vanwege de aanzienlijke kosten van experimentatie met prijzen, die essentieel is voor deze mechanismes. We concluderen dat het gebruik van AI (Artifical Intelligence) voor prijszetting mechanismes biedt die het risico op algoritmische collusie verhogen, maar de praktische belemmeringen betekenen dat het risico op dit moment beperkt lijkt te zijn tot specifieke markten of samenloop van omstandigheden

The urban economics of retail

This paper is the first to document empirically that urban shopping areas have a pronounced centre where the rents are the highest, and a negative rent gradient. We use this insight to build and test empirically a simple theoretical model of the competition between the residential and the retail land in a city. The model predicts that rents and occupancy rates on the edges of shopping areas are most sensitive to changes in economic conditions. Demand shocks may lead to transformations between\u3cbr/\u3eretail and residential land use, mostly at the edge, and to a contraction or expansion of shopping areas. The model predictions are tested on unique data on the location and characteristics of all retail and non-retail properties within 300 largest shopping areas in the Netherlands in 2004-2014, a period including the Great Recession. With every 100 metre distance from the centre of a shopping area rents fall, on average, by\u3cbr/\u3e15 percent. Shopping streets, areas located on attractive sites and areas offering free parking have a flatter distance decay. The vacancy rate on the edge of a shopping area is almost twice as high as in the centre. During the Great Recession some 2% of the\u3cbr/\u3eretail properties were transformed into other use, mostly on the edges of the shopping areas

Winkelleegstand na de crisis:de vastgoedmarkt reageert marktconform. Overheidsingrijpen is soms nodig

Ondanks een sterke daling van de winkelhuren in de grote recessie, is er sprake van toegenomen en deels blijvende winkelleegstand. De huren van nieuw gesloten contracten zijn na 2008 met ruim 20% gedaald in reactie op de afname van de consumptie van goederen en van de omzet van winkels. Voor sommige winkellocaties helpt een lagere huur echter niet: ze zijn onrendabel geworden voor de detailhandel bij ieder niveau van de huur