Tom Lam (Clemson) and Meng Liu (MIT) calculate surplus gains at 72 cents per dollar spent.
“Demand and Consumer Surplus in the On-Demand Economy: The Case of Ride Sharing” Read it here:
Thomas W. Hazlett, Clemson University
Michael Honig, Northwestern University
Observing trends in which Wi-Fi and Bluetooth have become widely popular, some argue that unlicensed allocations hosting such wireless technologies are increasingly valuable and that administrative spectrum allocations should shift accordingly. We challenge that policy conclusion. A core issue is that the social value of a given spectrum allocation is widely assumed to equal the gains of the applications it is likely to host. This thinking is faulty, as vividly seen in what we deem the Broadcast TV Spectrum Valuation Fallacy – the idea that because wireless video, or broadcast network programs are popular, TV channels are efficiently defined. This approach has been appropriately rejected, in key instances, by spectrum regulators, but is similarly applied in other instances regarding unlicensed allocations. While traditional allocations have garnered widespread criticism for imposing rigid barriers tending to block innovation, and flexible-use spectrum access rights have gained favor, the regulatory methods used to allocate (or reallocate) bandwidth remain embedded in a “command and control” process. Reconfiguring spectrum usage to enable emerging wireless markets often requires lengthy, costly rule makings. The expense of this administrative overhead is generally omitted from spectrum allocation policy analysis. Yet, it constitutes an essential component of the consumer welfare analysis. We propose a more fulsome policy approach, one that includes not only the appropriate measures of marginal value and opportunity cost for rival allocations, but incorporates transaction costs. Instead of regulators attempting to guess how much bandwidth should be allocated to various types of licensed and unlicensed services – and imposing different rules within and across these allocations – a more generic approach is called for. By better enabling spontaneous adjustments to changing consumer demands and technological innovation, spectrum allocations can be more efficiently brought into their most valuable employments.
Thomas W. Hazlett & Michael Honig, Valuing Spectrum Allocations, 23 Mich. Telecomm. & Tech. L. Rev. 45 (2016).
Available at: http://repository.law.umich.edu/mttlr/vol23/iss1/2
Thomas Hazlett recently reviewed two new volumes on the Information Economy for the International Journal of Economics of Business. Both Martin Campbell-Kelly and Daniel D. Garcia-Swartz, From mainframes to smartphones: A history of the international computer industry (Harvard University Press, 2015), and Shane Greenstein, How the Internet became commercial: Innovation, privatization, and the birth of a new network (Princeton University Press, 2015), offer important histories — and abundant insights — into today’s tech economy.
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(Dr. Babur De Los Santos with Michael R. Baye and Matthijs R. Wildenbeest, Journal of Economics &
Management Strategy, forthcoming)
The lion’s share of retail traffic through search engines originates from organic (natural) rather than sponsored (paid) links. We use a dataset constructed from over 12,000 search terms and 2 million users to identify drivers of the organic clicks that the top 759 retailers received from search engines in August 2012. Our results are potentially important for search engine optimization (SEO). We find that a retailer’s investments in factors such as the quality and brand awareness of its site increases organic clicks through both a direct and an indirect effect. The direct effectstems purely from consumer behavior: The greater the brand equity of an online retailer, the greater the number of consumers who click its link rather than a competitor in the list of organic results. The indirect effect stems from our finding that search engines tend to place better-branded sites in better positions, which results in additional clicks since consumers tend to click links in more favorable positions. We also find that consumers who are older, wealthier, conduct searches from work, use fewer words or include a brand name product in their search are more likely to click a retailer’s organic link following a product search. Finally, the brand equity of a retail site appears to be especially important in attracting organic traffic from individuals with higher incomes. The beneficial direct and indirect effects of an online retailer’s brand equity on organic clicks, coupled with the spillover effects on traffic through other online and traditional channels, leads us to conclude that investments in the quality and brand awareness of a site should be included as part of an SEO strategy.
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(Dr. Babur De Los Santos with Ali Hortaçsu and Matthijs R. Wildenbeest, Journal of Business & Economic Statistics, forthcoming)
This paper provides a method to estimate search costs in a differentiated product environment in which consumers are uncertain about the utility distribution. Consumers learn about the utility distribution by Bayesian updating their Dirichlet process prior beliefs. The model provides expressions for bounds on the search costs that can rationalize observed search and purchasing behavior. Using individual-specific data on web browsing and purchasing behavior for MP3 players sold online we show how to use these bounds to estimate search costs as well as the parameters of the utility distribution. Our estimates indicate that search costs are sizable. We show that ignoring consumer learning while searching can lead to severely biased search cost and elasticity estimates.
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(Dr. Babur De Los Santos with Matthijs R. Wildenbeest)
This paper empirically analyzes how the use of vertical price restraints has impacted retail prices in the market for e-books. In 2010 five of the six largest publishers simultaneously adopted the agency model of book sales, allowing them to directly set retail prices. This led the Department of Justice to file suit against the publishers in 2012, the settlement of which prevents the publishers from interfering with retailers’ ability to set e-book prices. Using a unique dataset of daily e-book prices for a large sample of books across major online retailers, we exploit cross- publisher variation in the timing of the return to the traditional wholesale model to estimate its effect on retail prices. We find that e-book prices for titles that were previously sold using the agency model decreased by 18 percent at Amazon and 8 percent at Barnes & Noble. Our results are robust to different specifications, placebo tests, and synthetic control groups. Our findings illustrate a case where upstream firms prefer to set higher retail prices than retailers and help to clarify conflicting theoretical predictions on agency versus wholesale models.
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(Dr. Babur De Los Santos with Michael R. Baye and and Matthijs R. Wildenbeest, in NBER’s Economic
Analysis of the Digital Economy, ed. by S. Greenstein, A. Goldfarb, and C. Tucker.
University of Chicago Press, May 2015.)
This chapter provides a data-driven overview of the different online platforms that consumers use to search for books and booksellers, and documents how the use of these platforms is shifting over time. Our data suggest that, as a result of digitization, consumers are increasingly conducting searches for books at retailer sites and closed systems (e.g., the Kindle and Nook) rather than at general search engines (e.g., Google or Bing). We also highlight a number of challenges that will make it difficult for researchers to accurately measure internet-based search behavior in the years to come. Finally, we highlight a number of open agenda items related to the pricing of books and other digital media, as well as consumer search behavior.
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What lessons can be learned for spectrum policy from the management of other natural resources? Here, an expert on resource management says good governance depends on a transparent, rules-based approach that will minimise regulatory uncertainty. This stability is key to encouraging the necessary investment in networks.
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(Dr. Babur De Los Santos with Sergei Koulayev, invited for third round review, Marketing Science)
The vast amount of information available online has revolutionized the way firms present consumers with product options. Presenting the best alternatives first reduces search costs associated with a consumer finding the right product. We use novel data on consumer click-stream behavior from a major web-based hotel comparison platform to estimate a random coefficient discrete choice model and propose an optimal ranking tailored to anonymous consumers that differ in their partially revealed price sensitivity. We are able to customize rankings by relating price sensitivity to request parameters, such as the length of stay, number of guests, and day of the week of the stay. In contrast to a myopic popularity-based ranking, our model accounts for the rapidly changing prices that characterize the hotel industry and consumers’ search refinement strategies, such as sorting and filtering of product options. We propose a method of determining the hotel ordering that maximizes consumers’ click-through rates (CTR) based on the information available to the platform at that time, its assessment of consumers’ preferences, and the expected consumer type based on request parameters from the current visit. We find that CTRs almost double when consumers are provided with customized rankings that reflect the price/quality trade-off inferred from the consumer’s request parameters. We show that the optimal ranking results in an average consumer welfare 173 percent greater than in the default ranking.
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(Dr. Babur De Los Santos with Michael R. Baye and and Matthijs R. Wildenbeest, Information Economics and
Organic product search results on Google and Bing do not systematically include information about seller characteristics (e.g., feedback ratings and prices). Consequently, it is often assumed that a retailer’s organic traffic is driven by the prominence of its position in the list of search results. We propose a novel measure of the prominence of a retailer’s name, and show that it is also an important predictor of the organic traffic retailers enjoy from product searches through Google and Bing. We also show that failure to account for the prominence of retailers’ names—as well as the endogeneity of retailers’ positions in the list of search results—significantly inflates the estimated impact of screen position on organic clicks.
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