Information Economics and Policy最新文献

Has the transitional exemption granted to the least developed countries (LDCs) Members of the World Trade Organization (WTO) in the WTO's Trade-Related Intellectual Property (TRIPS) Agreement helped LDCs reduce the strength of their Intellectual Property Protection (IPR)? The present study addresses this question by using 24 LDCs (treatment group) and two control groups, over the period from 1970 to 2015. The empirical analysis has established that the LDC transitional exemption was instrumental in reducing the IPR levels in LDCs, and LDCs that had lower IPR levels (i.e., those located in the lower quantiles) enjoyed larger reductions in IPR levels, thanks to this transitional exemption. Moreover, the effect of the LDC transitional exemption on LDCs' IPR levels depended on LDCs' duration of the membership in the WTO, as well as on their level of export variety-driven innovation, measured by their level of export product concentration or alternatively their degree of economic complexity.

This paper assesses the impact of mobile network sharing in Europe during the 2000-2019 period, looking at 140 mobile operators in 29 countries. We find that - consistent with economic theory - network sharing generated significant benefits for operators and consumers, including lower prices and improved network coverage and quality. This was driven by cost reductions, higher returns on investment and increased competition. These effects materialized heterogeneously, with the impact of network sharing depending on the type of sharing, the technology cycle in which it is entered into as well as the market position and size of the operators entering the agreement. This has important implications going forward as it shows that network sharing can play a vital role in the deployment of new 5G networks and that the technological and market specificity of each type of sharing agreement can significantly affect its outcomes.

In this paper, we utilize survey data collected in 2017 from 12,735 individuals across nine Sub-Saharan African countries. We merge the survey data with geographic information related to the proximity of mobile network towers and banking facilities, based on the geo-locations of the respondents. Our estimation approach comprises a two-stage model. In the first stage, consumers make choices between adopting a feature phone or a smartphone. In the second stage, they make decisions regarding the use of mobile money services. Our findings reveal that network coverage significantly influences the adoption of mobile phones. Moreover, we observe that mobile money services are more favored by younger and relatively wealthier individuals for sending money, while older individuals and those with lower incomes tend to use mobile wallets for receiving money. Consequently, mobile money services facilitate younger migrant workers residing in areas with better infrastructure in providing support to their older relatives in less developed regions.

In this paper, we analyze the competitive and welfare effects of imperfect consumer recognition based on the consumers' purchase history in a duopoly model with discrete brand preferences and switching costs. We demonstrate that the impact of consumer recognition on firms' pricing strategies, industry profits, and welfare crucially depends on the accuracy of consumer recognition, i.e., the relative magnitude of correct and incorrect consumer recognition. An increase in the extent of incorrect recognition softens the competition if it is less than that of correct recognition; otherwise, it intensifies the competition. The impact of the accuracy of the information on consumer surplus and welfare follows from price and profit effects. We also analyze asymmetric price discrimination and the optimal strategies of a data broker if firms purchase consumer recognition technology from it.

This paper presents a methodology for estimating a sequential model of online consumer search. The literature on such structural econometric models typically assumes that, for each alternative, there is only one stage of optimal information acquisition. For many e-commerce websites, however, there are two stages: obtaining information from (1) the search results page and (2) clicking on an alternative. We develop a methodology for estimating a model with two stages, in which the consumer makes optimal decisions in each stage. The search problem is viewed as a variant of a multi-armed bandit problem. We estimate this model using a dataset of clicks and purchases on the website expedia.com. In contrast to models with one stage of optimal information acquisition, our model can be used to analyse not only the clicking and purchasing behaviour of consumers but also the extent to which they browse alternatives on the search results page.

We address the need to regulate Internet infrastructure usage to take into account environmental externalities. We model the interactions between an internet service provider and some content providers in settings where the former chooses the network size and the latter influence congestion on the network. We then discuss how different regulatory frameworks (Net Neutrality, Laissez-Faire, Price Regulation) impact both the economic efficiency and the environmental performance. In particular, we highlight that inducing more efficiency effort from the content providers may either improve or worsen the final environmental outcome, and provide some conditions for one case or the other to prevail.

This study reviews the economic benefits analysis conducted in 2014 for the National Broadband Network (NBN), one of Australia's largest ever public infrastructure projects. The review identifies that the NBN's benefits were overstated due to error by an estimated $17–20 billion in 2014 present value terms, an amount sufficient to eliminate the NBN's forecast net economic benefits. To provide an updated view on the benefits of high-speed broadband in 2022, a stated choice experiment is conducted, finding that the WTP has grown since 2014 at an annual real rate of 8.8 percent for download speeds and 11.5 percent for upload speeds. Even at these growth rates, however, the benefits of the NBN remain materially lower than forecast in 2014. Further, the analysis finds high heterogeneity in the household WTP, with smaller and lower-income households reluctant to pay a premium for speeds much faster than 50 Mbps, indicating that the adoption of the fastest available broadband speeds is likely to remain low. The study highlights the potential value of cost-benefit analyses, but also the risks, particularly where they are relied on to justify enduring extensions of government ownership and control. The paper concludes by identifying learnings for policymakers and cost-benefit analysis practitioners seeking to assess and optimize the economic value of public infrastructure investments.

This paper investigates the impact of broadband Internet on the provision of public media in a large developing country. We use new panel data on public broadcasting at the province level from 2005 to 2017 and a control function approach exploiting variation in China's centralized roll-out of digital infrastructure. We find that rising broadband penetration has substantial negative impacts on the quantity of public media provision—including news, public-service programs, and entertainment—in China's local radio and television. Except for news, these effects are driven by changes in both the extensive margin (i.e., fewer channels) and the intensive margin (i.e., less broadcasting per channel). While industry ad revenues decrease significantly, ad intensity and volume per channel increase with higher broadband penetration rates. Lastly, we find that broadband Internet attracts young, educated, and urban viewers away from television but has no effect on the elderly, the less educated, and those with low-paying jobs.

The ability to make accurate predictions relating to consumer preferences is a key factor of a digital firm's success. Examples include targeted advertisements and, more broadly, business models relying on capturing consumers' attention. The prediction technologies used to learn consumer preferences rely on consumer generated data. Despite the importance of data-driven technologies, there is a lack of knowledge about the precise role that data-scale plays for prediction accuracy. From a policy perspective, a better understanding about the role of data is needed to assess the risks that “big data” might pose for competition. This article highlights potential complementarities between different data dimensions in algorithmic learning. We analyze our hypothesis using search engine data from Yahoo! and provide evidence that more data in the within-user dimension enhances the efficiency of algorithmic learning in the across-user dimension. Our findings suggest that ignoring these complementarities might lead to underestimating scale advantages from data.

We connect various streams of academic literature to analyze how alternative competition and regulatory policies may affect the development of digital financial services, and particularly of mobile payments. Our main objective is to highlight the extent to which existing models, often coming from related industries (such as telecom, payments, and banking) can be applied to study the effects of mobile money interoperability. We focus on four dimensions of interoperability. First, we consider mobile network interoperability (whether clients of one telecom can access another telecom's payment services) in connection with the IO literature on tying. Second, we discuss platform level interoperability (the ability to send money off-network) in light of the literature on compatibility. We also build on the behavioral IO literature to suggest how the effects of interoperability may be very heterogeneous across various types of firms and consumers, or even backfire. Third, we consider interoperability in the cash-in-cash-out agent network, in light of the literature on co-investment in network industries, and of more specific studies on ATMs' interoperability. Fourth, we discuss how the literature in banking and on data ownership can be used to understand interoperability of data. We conclude with some broader remarks on policy implications and on possible directions for future research.