market design
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2022 ◽  
Vol 306 ◽  
pp. 117979
Author(s):  
Monish Mukherjee ◽  
Trevor Hardy ◽  
Jason C. Fuller ◽  
Anjan Bose

2021 ◽  
Vol 34 (9) ◽  
pp. 107030
Author(s):  
Debabrata Chattopadhyay ◽  
Michael Klein

2021 ◽  
Vol 19 (2) ◽  
pp. 32-36
Author(s):  
Yannai A. Gonczarowski ◽  
Assaf Romm ◽  
Ran Shorrer

Inspired by the SIGecom Exchanges' annual survey of job market candidates, 1 this is the second annual collection of profiles of the junior faculty job market candidates of the market design community. The nine candidates are listed alphabetically. Along with information regarding the candidate's bio, job market paper, other representative papers, and short research summary, each profile also contains links to the candidate's homepage and CV.


Energy Policy ◽  
2021 ◽  
Vol 158 ◽  
pp. 112522
Author(s):  
Ksenia Poplavskaya ◽  
Jesus Lago ◽  
Stefan Strömer ◽  
Laurens de Vries

Energy Policy ◽  
2021 ◽  
Vol 158 ◽  
pp. 112558
Author(s):  
Maurício T. Tolmasquim ◽  
Tiago de Barros Correia ◽  
Natália Addas Porto ◽  
Wikus Kruger

Author(s):  
Elisabetta Iossa ◽  
Patrick Rey ◽  
Michael Waterson

Abstract We study competition for the market in a setting where incumbents (and, to a lesser extent, neighbouring incumbents) benefit from a cost or information advantage. We first compare the outcome of staggered and synchronous tenders, before drawing the implications for market design. We find the timing of tenders interrelates with the likelihood of monopolisation. For high incumbency advantages and/or discount factors monopolisation is expected, in which case synchronous tendering is preferable as it strengthens the pressure that entrants exercise on the monopolist. For low incumbency advantages and/or discount factors other firms remain active, in which case staggered tendering is preferable as it maximises competitive pressure coming from the other firms. We use bus tendering in London to illustrate our insights and draw policy implications.


2021 ◽  
Author(s):  
Monica Jane Barratt ◽  
Francois Lamy ◽  
Liam Engel ◽  
Emma Davies ◽  
Cheneal Puljević ◽  
...  

Background and Aims. Digital technologies continue to facilitate drug trading. Televend’s backend is hosted on the darknet—like a cryptomarket, but purchases are made through the messaging app Telegram—like an app-mediated market. Here, we provide an initial characterisation of the Televend drug market. Design. Web scrapes and global cross-sectional web survey of drug buyers (Global Drug Survey; GDS).Setting. Televend and White House Market (WHM) (Jun–Jul 2021). Participants. 15,513 drug buyers (Dec 2020–Mar 2021)Measurements. For scrapes: Drug listing information including advertised product, vendor name, country of origin and destination. For survey: Modes of drug sourcing in the last 12 months, drug types sourced, demographic and drug use characteristics. Findings. Televend was 10% of the size of the largest drug cryptomarket (WHM) (4,515/44,830 listings per week). Televend listings increased slightly (4.9%), while WHM listing totals decreased slightly (-2.6%) over the same 8-week period. Both markets predominantly contained drug-related listings covering similar drug categories, with similar country of origin and destination. While around 1/10 reported sourcing from darknet markets (11.3%) or apps (9.0%), very few GDS drug buyers reported use of Televend (0.73%). Most Televend buyers (68/114) reported buying cannabis, then cocaine (20), MDMA (17), and LSD (12). The Televend and darknet groups had similar demographic and drug use characteristics; whereas compared with app purchasers, older age increased the odds of Televend use (aRRR=1.06, p<.001), identifying as a woman decreased the odds (aRRR=0.43, p=.004), while last-year use of a greater number of drug types (aRRR=1.20, p<.001) and less frequent drug use (aRRR=0.998, p=.032) increased the odds of Televend purchase. Conclusions. While smaller, Televend is not noticeably different in its drug offerings to its largest cryptomarket competitor, and at this time, our data suggest that Televend attracts a cohort more similar to darknet than to app drug buyers.


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