17,458 research outputs found

    Multi-objective road pricing: a cooperative and competitive bilevel optimization approach

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    Costs associated with traffic externalities such as congestion, air pollution, noise, safety, etcetera are becoming unbearable. The Braess paradox shows that combating congestion by adding infrastructure may not improve traffic conditions, and geographical and/or financial constraints may not allow infrastructure expansion. Road pricing presents an alternative to combat traffic externalities. The traditional way of road pricing, namely congestion charging, may create negative benefits for society. In this effect, we develop a flexible pricing scheme internalizing costs arising from all externalities. Using a game theoretical approach, we extend the single authority road pricing scheme to a pricing scheme with multiple authorities/regions (with likely contradicting objectives)

    Competition Policy In Network Industries: An Introduction

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    We discuss issues of the application of antitrust law and regulatory rules to network industries. In assessing the application of antitrust in network industries, we analyze a number of relevant features of network industries and the way in which antitrust law and regulatory rules can affect them. These relevant features include (among others) network effects, market structure, market share and profits inequality, choice of technical standards, relationship between the number of active firms and social benefits, existence of market power, leveraging of market power in complementary markets, and innovation races. We find that there are often significant differences on the effects of application of antitrust law in network and non-network industries.networks, network effects, public policy, antitrust, telecommunications, technical standards

    Competition Policy in Network Industries: An Introduction

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    The author discusses issues of the application of antitrust law and regulatory rules to network industries. In assessing the application of antitrust in network industries, we analyze a number of relevant features of network industries and the way in which antitrust law and regulatory rules can affect them. These relevant features include (among others) network effects, market structure, market share and profits inequality, choice of technical standards, relationship between the number of active firms and social benefits, existence of market power, leveraging of market power in complementary markets, and innovation races. The author finds that there are often significant differences on the effects of application of antitrust law in network and non-network industries.

    Indirect Network Effects and Adoption Externalities

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    The conventional wisdom is that indirect network effects, unlike direct network effects, do not give rise to externalities. In this paper we show that under very general conditions, indirect network effects lead to adoption externalities. In particular we show that in markets where consumption benefits arise from hardware/software systems, adoption externalities will occur when there are (i) increasing returns to scale in the production of software, (ii) free-entry in software, and (iii) consumers have a preference for software variety. The private benefit of the marginal hardware purchaser is less than the social benefit since the marginal hardware purchaser does not internalize the welfare improving response of the software industry, particularly the increase in software variety, on inframarginal purchasers when the market for hardware expands.Network Externalities, Network Effects

    Pricing of Complementary Goods and Network Effects*

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    We discuss the case of a monopolist of a base good in the presence of a complementary good provided either by it or by another firm. We assess and calibrate the extent of the influence on the profits from the base good that is created by the existence of the complementary good, i.e., the extent of the network effect. We establish an equivalence between a model of a base and a complementary good and a reduced-form model of the base good in which network effects are assumed in the consumers’ utility functions as a surrogate for the presence of direct or indirect network effects, such as complementary goods produced by other firms. We also assess and calibrate the influence on profits of the intensity of network effects and quality improvements in both goods. We evaluate the incentive that a monopolist of the base good has to improve its quality rather than that of the complementary good under different market structures. Finally, based on our results, we discuss a possible explanation of the fact that Microsoft Office has a significantly higher price than Microsoft Windows although both products have comparable market shares.calibration; monopoly; network effects; complementary goods; software; Microsoft

    Network Externalities and Critical Mass in the Mobile Telephone Network: a Panel Data Estimation

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    This paper develops a simple demand model with network externalities which allow us to identify the shape of the network externalities function in the mobile telephone market and to estimate the critical mass. If the mobile telephone network exhibits positive network externalities, we expect that the demand curve is not downward sloping everywhere but it has an increasing part, the critical mass of the installed base of subscribers. Once the critical mass is reached, the growth of the network is self-sustaining. We use a panel data of the 30 OEDC Countries from 1989 to 2006 for estimating the relationship between price of 3-minute cellular call and the installed base of subscribers; we find strong network externalities effects in mobile telephone market which drive the demand curve for this network good to be an inverted U function. Moreover, given that the concavity of the demand curve depends on the extent of network externalities, the idea is to identify some variables which could affect the intensity of network effects in the mobile telephone market, because the more concave the demand curve is, sooner the critical mass is reached for any price. This may have important implications for producers in terms of initial investment and marketing strategies which they have to do to attain the critical mass.Network Externalities, Mobile Telecommunication, Critical Mass

    Identification of Network Externalities in Markets for Non-Durables

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    This paper introduces a structural econometric model of consumer demand for non-durable goods, which exhibits network externalities. The structural model allows us to identify the parameters, which determine the strength of the externalities in the underlying economic model from the empirical estimation results. The estimates of these parameters can then be employed to test the economic significance of the externalities and the compatibility of networks. The identifying assumption that drives our results is that consumers care about the lagged instead of the current network size. We argue that it does not necessarily bound their rationality. To complete our structural model, we provide an example of functional specification that yields a simple linear stochastic model of demand. Using this functional specification, we identify all structural parameters of the model. In the end, the estimation and the stochastic structure of the resulting econometric model are discussed. ZUSAMMENFASSUNG - ( Identifikation der Netzwerkeffekten in den MĂ€rkten fĂŒr nicht-dauerhafte GĂŒter) Der vorliegende Beitrag stellt ein strukturelles ökonometrisches Modell der Konsumnachfrage fĂŒr nicht-dauerhafte GĂŒter mit externen Netzwerkeffekten vor. Das strukturelle Modell lĂ€sst uns die Parameter von Netzwerkeffekten im zugrunde liegenden ökonomischen Modell empirisch zu identifizieren. Die SchĂ€tzer der Strukturparameter könnten fĂŒr das Testen der NetzwerkkompatibilitĂ€t und der ökonomischen Signifikanz der Netzwerkeffekte verwendet werden. FĂŒr die Identifikation nehmen wir an, dass die Konsumenten die NetzwerksgrĂ¶ĂŸe verzögert wahrnehmen. Wir argumentieren, dass diese Annahme nicht notwendigerweise mit irrationalem Verhalten gleichzusetzen ist. Um das strukturelle Modell zu vollstĂ€ndigen, geben wir eine funktionale Spezifikation, aus der ein lineares stochastisches Nachfragemodell folgt. Unter Verwendung dieser Spezifikation sind alle Strukturparameter von dem Modell identifiziert. Zum Schluss diskutieren wir die SchĂ€tzung und die stochastische Struktur des sich ergebenden ökonometrischen Modells.Structural Econometric Model, Network Externalities, Innovation Diffusion

    The correlation of externalities in marginal cost pricing: lessons learned from a real-world case study

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    Negative externalities cause inefficiencies in the allocation of capacities and resources in a transport system. Marginal social cost pricing allows to correct for these inefficiencies in a simulation environment and to derive real-world policy recommendations. In this context, it has been shown for analytical models considering more than one externality, that the correlation between the externalities needs to be taken into account. Typically, in order to avoid overpricing, this is performed by introducing correction factors which capture the correlation effect. However, the correlation structure between, say, emission and congestion externalities changes for every congested facility over time of day. This makes it close to impossible to calculate the factors analytically for large-scale systems. Hence, this paper presents a simulation-based approach to calculate and internalize the correct dynamic price levels for both externalities simultaneously. For a real-world case study, it is shown that the iterative calculation of prices based on cost estimates from the literature allows to identify the amplitude of the correlation between the two externalities under consideration: for the urban travelers of the case study, emission toll levels—without pricing congestion—turn out to be 4.0% too high in peak hours and 2.8% too high in off-peak hours. In contrary, congestion toll levels—without pricing emissions—are overestimated by 3.0% in peak hours and by 7.2% in off-peak hours. With a joint pricing policy of both externalities, the paper shows that the approach is capable to determine the amplitude of the necessary correction factors for large-scale systems. It also provides the corrected average toll levels per vehicle kilometer for peak and off-peak hours for the case study under consideration: again, for urban travelers, the correct price level for emission and congestion externalities amounts approximately to 38 EURct/km in peak hours and to 30 EURct/km in off-peak hours. These toll levels can be used to derive real-world pricing schemes. Finally, the economic assessment indicators for the joint pricing policy provided in the paper allow to compare other policies to this benchmark state of the transport system
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