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on Information and Communication Technologies |
| By: | Sue Mialon; Samiran Banerjee |
| Abstract: | We provide a new model of platform competition on the Internet and analyze the effect of last-mile access charges on market outcomes. Consumers subscribe to two vertically related platforms, an Internet service provider (ISP) and a content network platform (CNP), to reach content providers (CPs). CPs interact with consumers via CNPs. Local ISPs provide an essential input: the internet connection for consumers and the last-mile access for the CNPs. The effects of access regulation that lowers the ISPs' last-mile access charges depend on (i) how much consumers value the network services, (ii) how much an increase in the Internet price lowers CNPs' fees from CPs, and (iii) the elasticities of consumer demand for the Internet with respect to price and network externality. When consumers' valuation of the network services is very high, the market for Internet connection is fully covered and access regulation unambiguously improves welfare since it lowers the fees for CPs without affecting consumer demand. When consumers' valuation is very low, access regulation does not have any impact because ISPs optimally set the access charge at zero. When consumers' valuation is moderate and the CNPs' fee reduction in response to a higher Internet price is large, access regulation lowers not only the fees from CPs but also consumer Internet prices. Hence, the "seasaw principle" between consumer Internet price and access charge breaks down in this case, and access regulation unambiguously improves welfare for consumers and CPs. On the other hand, if CNPs' fee adjustment is minimal, access regulation induces a higher consumer internet price and the welfare implication of access regulation is ambiguous. Access regulation improves welfare in this case if consumer demand responds more to the change in network externality than the change in price. |
| Date: | 2012–01 |
| URL: | http://d.repec.org/n?u=RePEc:emo:wp2003:1201&r=ict |
| By: | Liran Einav; Chiara Farronato; Jonathan D. Levin; Neel Sundaresan |
| Abstract: | Consumer auctions were very popular in the early days of internet commerce, but today online sellers mostly use posted prices. Data from eBay shows that compositional shifts in the items being sold, or the sellers offering these items, cannot account for this evolution. Instead, the returns to sellers using auctions have diminished. We develop a model to distinguish two hypotheses: a shift in buyer demand away from auctions, and general narrowing of seller margins that favors posted prices. Our estimates suggest that the former is more important. We also provide evidence on where auctions still are used, and on why some sellers may continue to use both auctions and posted prices. |
| JEL: | D02 D43 D44 D82 L13 L86 |
| Date: | 2013–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:19021&r=ict |
| By: | Gianluca Amori (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"); Luca Becchetti (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"); Giuseppe Persiano (Università di Salerno Dipartimento di Informatica); Andrea Vitaletti (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza") |
| Abstract: | With the growing di usion of devices with wireless communication capa- bilities as well as the success of social networking platforms, it has become more and more interesting to study dynamic evolving networks, in which the set of connections (however de ned) between the agents in the network varies over time. For instance, ad-hoc mobile networks are evolving networks in which a number of mobile hosts are free to move about a given area and capable when close enough of interacting with each other over wireless links without the need of an underlying backbone network. Other examples include P2P networks and in general social network contexts, in which the users dynamically establish and terminate social interactions. The topology of such networks changes over time, as edges (either directed or undirected) that represent interactions between nodes are dynamically added or removed in the network graph. Computing measures of centrality in such scenarios can be a challenging task. Classic measures of centrality and nodes' importance from graph theory and network analysis can be computed by a centralized en- tity on an aggregated representation of a dynamic network. However, privacy and/or scalability issues, or simply the absence of central coordination, may suggest a fully decentralized approach in which the computation is carried out by each node considering its own interactions with other nodes in the net- work. In this Master's thesis we propose lightweight algorithms for computing some importance measures of nodes in a dynamic evolving network in a fully decentralized way, without any knowledge of the whole network structure or assumptions on its future evolution. In particular, the main part of our work regards the computation of decentralized estimations of Google's PageRank and its theoretical analysis as a problem of random walks on dynamic graphs. We also introduce algorithms for computing some classical degree centrality measures with e cient use of resources. As it turns out, while straightfor- ward in a centralized setting, some of these measures are hard to compute in a fully decentralized way. We analyze all these algorithms in terms of hardware resources (storage space and computational power) required at each node as well as time complexity and network overhead in the transmissions, showing how they are implementable also on low-power devices such as RFID tags. We also run simulations of our algorithms on real-world dynamic evolving network data and show their performances with respect to centralized computations of analogous measures on aggregated static representations of such networks. |
| Keywords: | Dynamic Networs; importance measures; PageRank |
| Date: | 2013–06 |
| URL: | http://d.repec.org/n?u=RePEc:aeg:report:2013-06&r=ict |
| By: | Diego A. Comin; Martí Mestieri Ferrer |
| Abstract: | We study the lags with which new technologies are adopted across countries, and their long-run penetration rates once they are adopted. Using data from the last two centuries, we document two new facts: there has been convergence in adoption lags between rich and poor countries, while there has been divergence in penetration rates. Using a model of adoption and growth, we show that these changes in the pattern of technology diffusion account for 80% of the Great Income Divergence between rich and poor countries since 1820. |
| JEL: | E23 N1 O11 O12 O4 |
| Date: | 2013–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:19010&r=ict |