Centrality and pricing in spatially differentiated markets: The case of gasoline

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper highlights the importance of "centrality" for pricing. Firms characterised by a more central position in a spatial network are more powerful in terms of having a stronger impact on their competitors' prices and on equilibrium prices. These propositions are derived from a simple theoretical model and tested empirically for the retail gasoline market in Vienna (Austria). We compute different measures of network centrality by using information on the locations of gasoline stations in the road network. Results from a spatial autoregressive model confirm that the strategic interaction in pricing between competitors is significantly related to their degree of centrality.

Price Competition in Product Variety Networks

“…As stated above, this result is the opposite to the one obtained in spatial competition models a la Hotelling. For example, one could use the data of Firgo et al (2015) to test whether this relationship is positive or negative.…”

“…17 We have seen in Section 4 that more central firms can either charge higher or lower prices. Interestingly, Firgo et al (2015) have tested this kind of relationship. Using data from the retail gasoline market of Vienna, Austria, they show that the relationship between centrality and pricing in a spatially differentiated market is not significant.…”

“…This is exactly what our model also predicts, suggesting a more sophisticated test of this relationship. For example, Firgo et al (2015) only use the degree centrality while our model suggests to use the sign-alternating Bonacich centrality measure of varieties (defined in Section 3.1), which is different to the standard Bonacich centrality measure (Ballester et al, 2006) since the sign of the weights changes with the length of the path in the network. Second, our model demonstrates that prices across firms are not necessary strategic complements.…”

A Bayesian heterogeneous coefficients spatial autoregressive panel data model of retail fuel duopoly pricing

“…Exceptions include Pennerstofer's (2009) application of a spatial lag model to study price competition using cross-section data on gasoline stations in Austria and, more recently, Filippini and Heimsch's (2015) analysis of the impact of CO2 taxes on gas demand, which employs a spatial autoregressive model with autoregressive disturbances on panel data from Switzerland. Firgo et al (2015) also applies a spatial-autoregressive model to examine the importance of centrality using a measure of network centrality based on the locations of gasoline stations in the road network of retail gasoline stations in Vienna, Austria. Their results show that prices of gasoline stations are more strongly correlated with prices of central competitors.…”

Network Centrality and Market Prices. An Empirical Note

“…In equilibrium, more efficient firms will be more isolated and will set higher markups (because their competitors offer relatively poor substitutes). In Braid (2013) and Firgo et al (2015) firms are located in a network of links and nodes that can be interpreted as roads and intersections. Both papers argue that firms characterized by a more central position in a spatial network are more powerful in terms of having a stronger impact on their competitors' prices and on equilibrium prices.…”