Information Economics and Policy最新文献

We investigate patent litigation, settlements and R&D incentives on a market where two firms develop technologies in order to obtain patents and produce goods. Firms may sell IP rights to a Patent Assertion Entity (PAE) that acts as intermediary for patent monetization. We find that compared to simultaneous market entry, the effect of this so-called patent privateering is mitigated if firms enter sequentially. Furthermore, we show that privateering may decrease industry profits by distortion of R&D incentives even when there is no rent extraction by the PAE.

Two federal programs in the United States subsidize internet access for rural healthcare providers, namely, Healthcare Connect Fund (HCF) and the Telecom Program. HCF uses a subsidy mechanism that strongly incentivizes healthcare providers to shop for faster or cheaper internet. Telecom does not incentivize shopping. Theoretically, this predicts that HCF must achieve faster or cheaper internet than Telecom. I empirically test this question and find that Telecom subsidy recipients pay 132-179% more than HCF subsidy recipients on similar internet plans. Evidence point to Telecom's poor incentive design as the root cause. Eliminating this price gap would save American taxpayers $143 million annually. The findings highlight the power of program design, showcase the unintended consequences of misaligned incentives, and encourage policymakers to thoroughly examine program features, the impact on consumer behavior, and the effect on competition and market outcomes.

We study collusion sustainability in an infinitely repeated game in which firms might price discriminate, by offering personalized prices for the share of consumers they have information about. We do not impose any restrictions to the distribution of consumers and the product characteristic space. In such a general framework we show that when firms share their personal information about consumers, collusion is more difficult to sustain. We also show that, for intermediate levels of the discount factor, an antitrust policy aiming to discourage joint profit maximization and to maximize the consumer surplus should allow information sharing between firms. Instead, a ban on information sharing is optimal only if firms have imperfect information about their own consumers.

Technological development and better information systems potentially increase firms' abilities to use personalized pricing. Should firms take advantage of such an opportunity, or should they rather charge all consumers the same price (uniform pricing)? It might seem obvious that it is optimal for an individual firm to use personalized pricing; if it does, it can charge each consumer a price equal to her maximal willingness to pay. No other price plan can possibly yield higher profits. However, we show that if a firm is expected to use personalized pricing, then it effectively eliminates a rival's possibility to select values on non-price variables, such as horizontal differentiation, that can soften competition and increase profits for all firms. Once we take this into account, we might no longer expect that personalized pricing is a dominant strategy. Indeed, we show that it may be a dominant strategy for a firm to commit to uniform pricing prior to the rival's choice of non-price variables if it has the ability to do so.

We estimate the returns to online skills certification for engineering graduates in India using a regression discontinuity design. Individuals in our dataset take a computer programming exam, and are required to score above a threshold to receive a widely used software engineer IT-services certificate provided by an online job skills credentialing platform in India. We find that certified candidates have approximately 0.25 higher probability of finding employment following the exam. Our results indicate that skill certification in this context is a strong one-time signal of quality. Certification cannot replace education, however, and fails to predict longer-term job market outcomes as demonstrated by the lack of estimated causal impact on current employment status or income level. Our findings suggest the promise and limits of certification in an educational market where university training is highly variable.

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.