@manuascript {114,
	title = {Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets},
	year = {Working Paper},
	abstract = {As LLM agents advance, they are increasingly mediating economic decisions, ranging from product discovery to transactions, on behalf of users. Such applications promise benefits but also raise many questions about agent accountability and value for users. Addressing these questions requires understanding how agents behave in realistic market conditions. However, previous research has largely evaluated agents in constrained settings, such as single-task marketplaces (e.g., negotiation) or structured two-agent interactions. Real-world markets are fundamentally different: they require agents to handle diverse economic activities and coordinate within large, dynamic ecosystems where multiple agents with opaque behaviors may engage in open-ended dialogues. To bridge this gap, we investigate two-sided agentic marketplaces where Assistant agents represent consumers and Service agents represent competing businesses. To study these interactions safely, we develop Magentic-Marketplace-- a simulated environment where Assistants and Services can operate. This environment enables us to study key market dynamics: the utility agents achieve, behavioral biases, vulnerability to manipulation, and how search mechanisms shape market outcomes. Our experiments show that frontier models can approach optimal welfare-- but only under ideal search conditions. Performance degrades sharply with scale, and all models exhibit severe first-proposal bias, creating 10-30x advantages for response speed over quality. These findings reveal how behaviors emerge across market conditions, informing the design of fair and efficient agentic marketplaces.},
	url = {https://arxiv.org/abs/2510.25779},
	author = {Gagan Bansal and Wenyue Hua and Zezhou Huang and Adam Fourney and Amanda Swearngin and Will Epperson and Tyler Payne and Jake M. Hofman and Brendan Lucier and Chinmay Singh and Markus Mobius and Akshay Nambi and Archana Yadav and Kevin Gao and David M. Rothschild and Aleksandrs Slivkins and Daniel G. Goldstein and Hussein Mozannar and Nicole Immorlica and Maya Murad and Matthew Vogel and Subbarao Kambhampati and Eric Horvitz and Saleema Amershi}
}
@manuascript {113,
	title = {The Agentic Economy},
	year = {2025},
	abstract = {Generative AI has transformed human-computer interaction by enabling natural language interfaces and the emergence of autonomous agents capable of acting on users{\textquoteright} behalf. While early applications have improved individual productivity, these gains have largely been confined to predefined tasks within existing workflows. We argue that the more profound economic impact lies in reducing communication frictions between consumers and businesses. This shift could reorganize markets, redistribute power, and catalyze the creation of new products and services. We explore the implications of an agentic economy, where assistant agents act on behalf of consumers and service agents represent businesses, interacting programmatically to facilitate transactions. A key distinction we draw is between unscripted interactions -- enabled by technical advances in natural language and protocol design -- and unrestricted interactions, which depend on market structures and governance. We examine the current limitations of siloed and end-to-end agents, and explore future scenarios shaped by technical standards and market dynamics. These include the potential tension between agentic walled gardens and an open web of agents, implications for advertising and discovery, the evolution of micro-transactions, and the unbundling and rebundling of digital goods. Ultimately, we argue that the architecture of agentic communication will determine the extent to which generative AI democratizes access to economic opportunity.},
	url = {https://arxiv.org/abs/2505.15799},
	author = {David Rothschild and Markus Mobius and Jake Hofman and Eleanor Dillon and Daniel Goldstein and Nicole Immorlica and Sonia Jaffe and Brendan Lucier and Alexandrs Slivkins and Matthew Vogel}
}
@unpublished {102,
	title = {Communicating with Anecdotes},
	year = {2024},
	abstract = {We study a communication game between a sender and receiver. The sender chooses one of her signals about the state of the world (i.e., an anecdote) and communicates it to the receiver who takes an action affecting both players. The sender and receiver both care about the state of the world but are also influenced by personal preferences, so their ideal actions can differ. We characterize perfect Bayesian equilibria. The sender faces a temptation to persuade: she wants to select a biased anecdote to influence the receiver{\textquoteright}s action. Anecdotes are still informative to the receiver (who will debias at equilibrium) but the attempt to persuade comes at a cost to precision. This gives rise to informational homophily where the receiver prefers to listen to like-minded senders because they provide higher-precision signals. Communication becomes \textit{polarized} when the sender is an expert with access to many signals, with the sender choosing extreme outlier anecdotes at equilibrium (unless preferences are perfectly aligned). This polarization dissipates all the gains from communication with an increasingly well-informed sender when the anecdote distribution is heavy-tailed. Experts can therefore face a curse of informedness: receivers will prefer to listen to less-informed senders who cannot pick biased signals as easily.},
	author = {Nika Haghtalab and Nicole Immorlica and Brendan Lucier and Markus Mobius and Divyarthi Mohan}
}
@article {80,
	title = {
	Do Celebrity Endorsements Matter? A Twitter Experiment Promoting Vaccination in Indonesia

},
	journal = {Economic Journal},
	volume = {134},
	number = {659},
	year = {2024},
	month = {April 2024},
	pages = {913{\textendash}933},
	type = {Working Paper},
	abstract = {Do celebrity endorsements matter? And if so, how can celebrities communicate effectively? We conduct a nationwide Twitter experiment in Indonesia promoting vaccination. Celebrity messages are 72\% more likely to be passed on or liked than similar messages without a celebrity{\textquoteright}s imprimatur. In total, 66\% of the celebrity effect comes from authorship, compared to passing on messages. Citing external medical sources decreases retweets by 27\%. Phone surveys show that those randomly exposed to messaging have fewer incorrect beliefs and report more vaccination among friends and neighbours. The results can inform public health campaigns and celebrity public service more generally.},
	url = {https://doi.org/10.1093/ej/uead102},
	author = {Vivi Alatas and Arun G. Chandrasekhar and Markus M. Mobius and Ben Olken and Cindy Paladines}
}
@manuascript {115,
	title = {A Memory Model of Belief Formation},
	year = {2023},
	abstract = {We propose a model of belief formation based on sampling from memory. The agent in our model retrieves memories and combines them with the prior to form a belief. The agent is fully Bayesian and rational but faces a constraint on memory retrieval {\textemdash} she can only sample observations one at a time instead of retrieving all of them at once. Retrieval is mostly random, but the agent can partially target retrieval using an index. The index splits the database of memories into two (or more) groups based on the values of one (or more) attribute. To ensure that her beliefs are as accurate as possible, the agent chooses which indexed group tosample from in each period. We show that the expert will generically oversample one group and characterize three forces that determine which group is sampled more intensely. We then show that oversampling translates directly into ex-post belief bias. We use this insight to explain well-known biases in beliefs across individuals such as the {\textquotedblleft}depression babies{\textquotedblright} effect, rational stereotypes, and the dependence of beliefs on the history of previously encountered problems.},
	author = {Maxim Bakhtin and Markus Mobius and Muriel Niederle}
}
@unpublished {110,
	title = {Assembling News Like Legos (working paper coming soon with expanded list of authors)},
	year = {2023},
	abstract = {In recent years, there has been a lot of concern about "fake news" driving polarization of society. However, recent research has shown that factually incorrect news is relatively rare and that bias and polarization in news reporting might arise from the selection and framing the news rather than making up news. We model this process as a three-stage process: first of all, the publisher selects what topics to report on the homepage. Conditional on reporting a topic, the publisher decides what factual statements to select (such as summarizing an event or quoting a politician). Finally, conditional on reporting a factual statement, the publisher has some leeway in framing the statement by adding slant. We use a simple sender/receiver model to understand selection and framing where the sender tries to influence the receiver by deciding on how to best assemble a news article. We then use our framework to document selection and framing in 14 US newspapers by using generative AI (ChatGPT) to disassemble the top homepage articles into unique factual statements. We measure the extent to which a statement is supporting the world-view of left-leaning and right-leaning partisans on an online crowdsourcing platform where human raters are incentivized to label each statement accurately. In a separate framing survey we compare how each statement is framed in different newspapers on a left to right spectrum.},
	author = {Oliver Kiss and Markus Mobius and Tanya Rosenblat}
}
@article {108,
	title = {Quantifying Partisan News Diets in Web and TV Audiences},
	journal = {Science Advances},
	volume = {8},
	number = {28},
	year = {2022},
	abstract = {Partisan segregation within the news audience buffers many Americans from countervailing political views, posing a risk to democracy. Empirical studies of the online media ecosystem suggest that only a small minority of Americans, driven by a mix of demand and algorithms, are siloed according to their political ideology. However, such research omits the comparatively larger television audience and often ignores temporal dynamics underlying news consumption. By analyzing billions of browsing and viewing events between 2016 and 2019, with a novel framework for measuring partisan audiences, we first estimate that 17\% of Americans are partisan-segregated through television versus roughly 4\% online. Second, television news consumers are several times more likely to maintain their partisan news diets month-over-month. Third, TV viewers{\textquoteright} news diets are far more concentrated on preferred sources. Last, partisan news channels{\textquoteright} audiences are growing even as the TV news audience is shrinking. Our results suggest that television is the top driver of partisan audience segregation among Americans.},
	url = {https://doi.org/10.1126/sciadv.abn0083},
	author = {Daniel Muise and Homa Hosseinmardi and Baird Howland and Markus Mobius and David Rothschild and Duncan Watts}
}
@article {58,
	title = {Managing Self-Confidence: Theory and Experimental Evidence},
	journal = {Management Science},
	volume = {68},
	number = {11},
	year = {2022},
	pages = {7793-8514},
	abstract = {We use a series of experiments to understand whether and how people{\textquoteright}s beliefs about their own abilities are biased relative to the Bayesian benchmark and how these beliefs then affect behavior. We find that subjects systematically and substantially overweight positive feedback relative to negative (asymmetry) and also update too little overall (conservatism). These biases are substantially less pronounced in an ego-free control experiment. Updating does retain enough of the structure of Bayes{\textquoteright} rule to let us model it coherently in an optimizing framework, in which, interestingly, asymmetry and conservatism emerge as complementary biases. We also find that exogenous changes in beliefs affect subjects{\textquoteright} decisions to enter into a competition and do so similarly for more and less biased subjects, suggesting that people cannot {\textquotedblleft}undo{\textquotedblright} their biases when the time comes to decide.},
	url = {https://doi.org/10.1287/mnsc.2021.4294},
	author = {Markus Mobius and Muriel Niederle and Paul Niehaus and Tanya Rosenblat}
}
@article {109,
	title = {Research note: Examining potential bias in large-scale censored data},
	volume = {2},
	number = {4},
	year = {2021},
	abstract = {We examine potential bias in Facebook{\textquoteright}s 10-trillion cell URLs dataset, consisting of URLs shared on its platform and their engagement metrics. Despite the unprecedented size of the dataset, it was altered to protect user privacy in two ways: 1) by adding differentially private noise to engagement counts, and 2) by censoring the data with a 100-public-share threshold for a URL{\textquoteright}s inclusion. To understand how these alterations affect conclusions drawn from the data, we estimate the prevalence of fake news in the massive, censored URLs dataset and compare it to an estimate from a smaller, representative dataset. We show that censoring can substantially alter conclusions that are drawn from the Facebook dataset. Because of this 100-public-share threshold, descriptive statistics from the Facebook URLs dataset overestimate the share of fake news and news overall by as much as 4X. We conclude with more general implications for censoring data.},
	url = {https://misinforeview.hks.harvard.edu/article/research-note-examining-potential-bias-in-large-scale-censored-data/},
	author = {Jennifer Allen and Markus Mobius and David Rothschild and Duncan Watts}
}
@article {107,
	title = {Examining the Consumption of Radical Content on YouTube},
	journal = {PNAS},
	volume = {118},
	number = {32},
	year = {2021},
	abstract = {Although it is under-studied relative to other social media platforms, YouTube is arguably the largest and most engaging online media consumption platform in the world. Recently, YouTube{\textquoteright}s scale has fueled concerns that YouTube users are being radicalized via a combination of biased recommendations and ostensibly apolitical {\textquotedblleft}anti-woke{\textquotedblright} channels, both of which have been claimed to direct attention to radical political content. Here we test this hypothesis using a representative panel of more than 300,000 Americans and their individual-level browsing behavior, on and off YouTube, from January 2016 through December 2019. Using a labeled set of political news channels, we find that news consumption on YouTube is dominated by mainstream and largely centrist sources. Consumers of far-right content, while more engaged than average, represent a small and stable percentage of news consumers. However, consumption of {\textquotedblleft}anti-woke{\textquotedblright} content, defined in terms of its opposition to progressive intellectual and political agendas, grew steadily in popularity and is correlated with consumption of far-right content off-platform. We find no evidence that engagement with far-right content is caused by YouTube recommendations systematically, nor do we find clear evidence that anti-woke channels serve as a gateway to the far right. Rather, consumption of political content on YouTube appears to reflect individual preferences that extend across the web as a whole.},
	url = {https://doi.org/10.1073/pnas.2101967118},
	author = {Homa Hosseinmardi and Amir Ghasemian and Aaron Clauset and Markus Mobius and David M. Rothschild and Duncan Watts}
}
@article {106,
	title = {Comparing Estimates of News Consumption from Survey and Passively Collected Behavioral Data},
	journal = {Public Opinion Quarterly},
	volume = {85},
	number = {S1},
	year = {2021},
	pages = {347{\textendash}370},
	url = {https://doi.org/10.1093/poq/nfab023},
	author = {Tobias Konitzer and Jennifer Allen and Stephanie Eckman and Baird Howland and Markus Mobius and David Rothschild and Duncan J Watts}
}
@article {105,
	title = {Measuring the News and its Impact on Democracy},
	journal = {PNAS},
	volume = {118 (15)},
	number = {15},
	year = {2021},
	abstract = {Since the 2016 US presidential election, the deliberate spread of misinformation online, and on social media in particular, has generated extraordinary concern, in large part because of its potential effects on public opinion, political polarization, and ultimately democratic decision making. Recently, however, a handful of papers have argued that both the prevalence and consumption of {\textquotedblleft}fake news{\textquotedblright} per se is extremely low compared with other types of news and news-relevant content. Although neither prevalence nor consumption is a direct measure of influence, this work suggests that proper understanding of misinformation and its effects requires a much broader view of the problem, encompassing biased and misleading{\textemdash}but not necessarily actually incorrect{\textemdash}information that is routinely produced or amplified by mainstream news organizations. In this paper, we propose an ambitious collective research agenda to measure the origins, nature, and prevalence of misinformation, broadly construed,as well as its impact on democracy. We also sketch out some illustrative examples of completed, ongoing, or planned research projects that contribute to this agenda.},
	url = {https://doi.org/10.1073/pnas.1912443118},
	author = {Markus Mobius and David Rothschild and Duncan Watts}
}
@article {78,
	title = {Naive Learning with Uninformed Agents},
	journal = {American Economic Review},
	volume = {111},
	number = {11},
	year = {2021},
	pages = {3540-74},
	type = {Working Paper},
	abstract = {The DeGroot model has emerged as a credible alternative to the standard Bayesian model for studying learning on networks, offering a natural way to model na{\"\i}ve learning in a complex setting. One unattractive aspect of this model is the assumption that the process starts with every node in the network having a signal. We study a natural extension of the DeGroot model that can deal with sparse initial signals. We show that an agent{\textquoteright}s social influence in this generalized DeGroot model is essentially proportional to the degree-weighted share of uninformed nodes who will hear about an event for the first time via this agent. This characterization result then allows us to relate network geometry to information aggregation. We show information aggregation preserves {\textquotedblleft}wisdom{\textquotedblright} in the sense that initial signals are weighed approximately equally in a model of network formation that captures the sparsity, clustering, and small-world properties of real-world networks. We also identify an example of a network structure where essentially only the signal of a single agent is aggregated, which helps us pinpoint a condition on the network structure necessary for almost full aggregation. Simulating the modeled learning process on a set of real-world networks, we find that there is on average 22.4 percent information loss in these networks. We also explore how correlation in the location of seeds can exacerbate aggregation failure. Simulations with real-world network data show that with clustered seeding, information loss climbs to 34.4\&nbsp;percent},
	url = {https://www.aeaweb.org/articles?id=10.1257/aer.20181151},
	author = {Abhijit Banerjee and Arun Chandrasekhar and Emily Breza and Markus Mobius}
}
@article {104,
	title = {Evaluating the fake news problem at the scale of the information ecosystem},
	journal = {Science Advances },
	volume = {6},
	number = {14},
	year = {2020},
	abstract = {{\textquotedblleft}Fake news,{\textquotedblright} broadly defined as false or misleading information masquerading as legitimate news, is frequently asserted to be pervasive online with serious consequences for democracy. Using a unique multimode dataset that comprises a nationally representative sample of mobile, desktop, and television consumption, we refute this conventional wisdom on three levels. First, news consumption of any sort is heavily outweighed by other forms of media consumption, comprising at most 14.2\% of Americans{\textquoteright} daily media diets. Second, to the extent that Americans do consume news, it is overwhelmingly from television, which accounts for roughly five times as much as news consumption as online. Third, fake news comprises only 0.15\% of Americans{\textquoteright} daily media diet. Our results suggest that the origins of public misinformedness and polarization are more likely to lie in the content of ordinary news or the avoidance of news altogether as they are in overt fakery.},
	url = {https://doi.org/10.1126/sciadv.aay3539},
	author = {Jennifer Allen and Baird Howland and Markus Mobius and Davids Rothschild and Duncan Watts}
}
@conference {103,
	title = {Trimming the Hairball: Edge Cutting Strategies for Making Dense Graphs Usable},
	booktitle = {2018 IEEE International Conference on Big Data (Big Data)},
	year = {2018},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The application of modern NLP and ML techniques to large-scale datasets can generate implicit graphs that are so densely connected as to be unusable when rendered as node-link diagrams. We present a two-stage approach to extracting usable, map-like layouts from large, dense input graphs. This approach uses edge-cutting strategies based on node and edge metrics to reduce a graph to a skeletal structure showing only essential relationships, before filling in the resulting communities to create dense but usable layouts. Through a case study on a 145k-document adversarial health communication dataset, we show that each edge-cutting strategy has advantages and disadvantages, and that the appropriate choice of strategy depends on the data, user, and task.},
	url = {https://doi.org/10.1109/BigData.2018.8622521},
	author = {Darren Edge and Jonathan Larson and Markus Mobius and Christopher White}
}
@unpublished {55,
	title = {The Impact of Aggregators on Internet News Consumption},
	year = {2017},
	abstract = {A policy debate centers around the question whether news aggregators such as Google News decrease or increase traffic to online news sites. One side of the debate, typically espoused by publishers, views aggregators as substitutes for traditional news consumption because aggregators{\textquoteright} landing pages provide snippets of news stories and therefore reduce the incentive to click on the linked articles. Defendants of aggregators, on the other hand, view aggregators as complements because they make it easier to discover news and therefore drive traffic to publishers. This debate has received particular attention in the European Union where two countries, Germany and Spain, enacted copyright reforms that allow newspapers to charge aggregators for linking to news snippets. In this paper, we use Spain as a natural experiment because Google News shut down all together in response to the reform in December 2014. We compare the news consumption of a large number of Google News users with a synthetic control group of similar non-Google News users. We find that the shutdown of Google News reduces overall news consumption by about 20\% for treatment users, and it reduces page views on publishers other than Google News by 10\%. This decrease is concentrated around small publishers while large publishers do not see significant changes in their overall traffic. We further find that when Google News shuts down, its users are able to replace some but not all of the types of news they previously read. Post-shutdown, they read less breaking news, hard news, and news that is not well covered on their favorite news publishers. These news categories explain most of the overall reduction in news consumption, and shed light on the mechanisms through which aggregators interact with traditional publishers.},
	author = {Susan Athey and Markus Mobius and Jeno Pal}
}
@unpublished {63,
	title = {Social Networks and Vaccination Decisions},
	journal = {FRB of Boston Working Paper No. 07-12},
	year = {2017},
	month = {November 2007},
	abstract = {We combine survey responses, network data, and medical records in order to examine how friends affect the decision to get vaccinated against influenza. The random assignment of undergraduates to residential halls at a large private university generates exogenous variation in exposure to the vaccine, enabling us to credibly identify social effects. We find evidence of positive peer influences on health beliefs and vaccination choices. In addition, we develop a novel procedure to distinguish between different forms of social effects. Most of the impact of friends on immunization behavior is attributable to social learning about the medical benefits of the vaccine.},
	url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1073143},
	author = {Neel Rao and Markus Mobius and Tanya Rosenblat}
}
@inbook {69,
	title = {Informal Transfers in Social Networks},
	booktitle = {The Oxford Handbook of the Economics of Networks},
	year = {2016},
	pages = {611-629},
	publisher = {Oxford University Press},
	organization = {Oxford University Press},
	abstract = {Social networks can facilitate informal lending and risk-sharing in situations where for-mal institutions such as banks and insurance companies do not exist. The social collateral approach provides an analytically tractable framework that can be used to analyze a wide range of informal transfers. Moreover, the approach is easily amenable to empirical analysis.},
	url = {https://doi.org/10.1093/oxfordhb/9780199948277.013.28},
	author = {Markus Mobius and Tanya Rosenblat}
}
@article {68,
	title = {Ethnic Discrimination: Evidence from China},
	journal = {European Economic Review},
	volume = {90},
	year = {2016},
	pages = {165-177},
	abstract = {We study the role of ethnicity in experimental labor markets where {\textquotedblleft}employers{\textquotedblright} determine wages of {\textquotedblleft}workers{\textquotedblright} who perform a real effort task. This task requires a true skill which we show is not affected by minority status. In some treatments, we provide subtle priming to employers about minority status of workers as commonly depicted on Chinese {\textquotedblleft}Hukou{\textquotedblright} identification system. We conduct our experiments at two sites located in provinces that differ by their historical shares of ethnic groups in the population. We find that: (1) Han and minority workers are equally productive in both provinces; (2) in the diverse province, there is no difference in the wages between Han and minority workers; (3) in the non-diverse province, minority workers receive 4\%-7\% lower wages than Han workers.},
	url = {https://doi.org/10.1016/j.euroecorev.2016.04.004},
	author = {Markus Mobius and Tanya Rosenblat}
}
@unpublished {62,
	title = {Measuring Trust in Peruvian Shantytowns},
	journal = {Working Paper},
	year = {2015},
	month = {September 2010},
	abstract = {This paper uses a microfinance field experiment in two Lima shantytowns to measure the relative importance of social networks and prices for borrowing. Our design randomizes the interest rate on loans provided by a microfinance agency, as a function of the social distance between the borrower and the cosigner. This design effectively varies the relative price (interest rate differential) of having a direct friend versus an indirect friend as a cosigner. After loans are processed, a second randomization relieves some cosigners from their responsibility. These experiments yield three main results. (1) As emphasized by sociologists, connections are highly valuable: having a friend cosigner is equivalent to 18 per cent of the face value of a 6 month loan. (2) While networks are important, agents do respond to price incentives and switch to a non-friend cosigner when the interest differential is large. (3) Relieving responsibility of the cosigner reduces repayment for direct friends but has no effect otherwise, suggesting that different social mechanisms operate between friends and strangers: Non-friends cosign known high types, while friends also accept low types because of social collateral or altruism.},
	author = {Dean Karlan and Markus Mobius and Tanya Rosenblat and Adam Szeidl}
}
@unpublished {56,
	title = {Treasure Hunt: Social Learning in the Field},
	year = {2015},
	abstract = {We seed noisy information to members of a real-world social network to study how information diffusion and information aggregation jointly shape social learning. Our environment features substantial social learning. We show that learning occurs via diffusion which is highly imperfect: signals travel only up to two steps in the conversation network and indirect signals are transmitted noisily. We then compare two theories of information aggregation: a naive model in which people double-count signals that reach them through multiple paths, and a sophisticated model in which people avoid double-counting by tagging the source of information. We show that to distinguish between these models of aggregation, it is critical to explicitly account for imperfect diffusion. When we do so, we find that our data are most consistent with the sophisticated tagged model.},
	author = {Markus Mobius and Tuan Phan and Adam Szeidl}
}
@unpublished {57,
	title = {The Evolution of Work},
	year = {2014},
	abstract = {The division of labor first increased during industrialization, and then decreased again after 1970 as job roles have expanded. In this paper, we explain these trends in the organization of work through a simple model, making two minimal assumptions: (a) machines require standardization to exploit economies of scale and (b) more customized products are subject to trends and fashions which make production tasks less predictable and a strict division of labor impractical. The model predicts capital-skill substitutability during industrialization and capital-skill complementarity in the maturing industrial economy: At the onset of industrialization, the market supports only a small number of generic varieties which can be mass-produced under a strict division of labor. Then, thanks to productivity growth, niche markets gradually expand, producers eventually move into customized production, and the division of labor decreases again. We test our model by exploiting the time-lags in the introduction of bar-coding in three-digit SIC manufacturing industries in the U.S.. We find that both increases in investments in computers and bar-coding have led to skill-upgrading. However, consistent with our model bar-coding has affected mainly the center of the skill distribution by shifting demand away from the high-school educated to the less-than-college educated.},
	author = {Markus Mobius and Raphael Schoenle}
}
@article {43,
	title = {Buy-it-now or Take-a-chance: Price Discrimination through Randomized Auctions},
	journal = {Management Science},
	volume = {60},
	number = {12},
	year = {2014},
	pages = {2927 - 2948},
	abstract = {Increasingly detailed consumer information makes sophisticated price discrimination possible. At fine levels of aggregation, demand may not obey standard regularity conditions. We propose a new randomized sales mechanism for such environments. Bidders can "buy-it-now" at a posted price, or "take-a-chance" in an auction where the top d \&gt; 1 bidders are equally likely to win. The randomized allocation incentivizes high valuation bidders to buy-it-now. We analyze equilibrium behavior, and apply our analysis to advertiser bidding data from Microsoft Advertising Exchange. In counterfactual simulations, our mechanism increases revenue by 4.4\% and consumer surplus by 14.5\% compared to an optimal second-price auction.},
	url = {https://doi.org/10.1287/mnsc.2014.2009},
	author = {L. Elisa  Celis and Gregory Lewis and Markus Mobius and Hamid Nazerzadeh}
}
@article {44,
	title = {Consumption Risk-sharing in Social Networks},
	journal = {American Economic Review},
	volume = {104},
	number = {1},
	year = {2014},
	pages = {149-82},
	abstract = {We develop a model in which connections between individuals serve as social collateral to enforce informal insurance payments. We show that: (1) The degree of insurance is governed by the expansiveness of the network, measured with the per capita number of connections that groups have with the rest of the community. Two-dimensional networks---like real-world networks in Peruvian villages---are sufficiently expansive to allow very good risk-sharing. (2) In second-best arrangements, insurance is local: agents fully share shocks within, but imperfectly between endogenously emerging risk-sharing groups. We also discuss how endogenous social collateral affects our results. (JEL D02, D31, D70)},
	url = {https://doi.org/10.1257/aer.104.1.149},
	author = {Attila Ambrus and Markus Mobius and Adam Szeidl}
}
@article {45,
	title = {Social Learning in Economics},
	journal = {Annual Review of Economics},
	volume = {6},
	number = {1},
	year = {2014},
	pages = {827-847},
	abstract = {Social learning is a rapidly growing field for empirical and theoretical research in economics. We encounter social learning in many economically important phenomena, such as the adoption of new products and technologies or job search in labor markets. We review the existing empirical and theoretical literatures and argue that they have evolved largely independently of each other. This suggests several directions for future research that can help bridge the gap between both literatures. For example, the theory literature has come up with several models of social learning, ranging from na{\"\i}ve DeGroot models to sophisticated Bayesian models whose assumptions and predictions need to be empirically tested. Alternatively, empiricists have often observed that social learning is more localized than existing theory models assume, and that information can decay along a transmission path. Incorporating these findings into our models might require theorists to look beyond asymptotic convergence in social learning.},
	url = {http://www.annualreviews.org/doi/abs/10.1146/annurev-economics-120213-012609},
	author = {Markus Mobius and Tanya Rosenblat}
}
@unpublished {59,
	title = {The Impact of News Aggregators on Internet News Consumption: The Case of Localization},
	year = {2012},
	abstract = {This paper analyzes the impact of news aggregators on the quantity and composition of internet news consumption. In principle, news aggregators can be a substitute or a complement to the news outlets who invest in the creation of news stories. A policy debate centers around the decrease in the incentives for news creation that results if readers choose to consume their news through aggregators without clicking through to the news websites or generating any revenue for the outlets. This paper provides a case analysis of an example where Google News added local content to their news home page for users who chose to enter their location. Using a dataset of user browsing behavior, we compare users who adopt the localization feature to a sample of control users who are similar to the treatment users in terms of recent internet news consumption. We find that users who adopt the localization feature subsequently increase their usage of Google News, which in turn leads to additional consumption of local news. Users also navigate directly to the new sites they have discovered, further increasing their local news consumption. The increase in local news consumption diminishes over time, however, and in the longer run most of the additional local news consumption derives from increased Google News usage. Patterns of news consumption change: users read a wider variety of outlets, more outlets that are new to them, and a larger fraction of their news {\textquotedblleft}home page{\textquotedblright} views come from Google News rather than the home page of other news outlets. Thus, the inclusion of local content by Google News had mixed effects on local outlets: it increased their traffic, especially in the short run, but it also increased the reliance of users on Google News for their choices of news, and increased the dispersion of user attention across outlets.},
	author = {Susan Athey and Markus Mobius}
}
@unpublished {61,
	title = {Death through Success: The Rise and Fall of Local Service Competition at the Turn of the Century},
	year = {2011},
	abstract = {This paper develops a model of delayed network effects to explore the curious dynamics of competition in the local telephone market between AT\&amp;T and the {\textquoteright}Independents{\textquoteright} at the turn of the century. In the early years of telephone diffusion, local service competition between these two non-interconnected networks became widespread, but declined rapidly when diffusion rates started to slow down after 1907. The analysis is based on the observation that urban markets subdivide into social {\textquoteright}islands{\textquoteright} along geographical and socio-economic dimensions: users are more likely to communicate with subscribers {\textquoteright}inside{\textquoteright} their island than with those {\textquoteright}outside{\textquoteright} it. A simple dynamic model demonstrates how minority networks can thrive and preserve their market share at a low state of development when islands form essentially independent niche markets. As the industry matures, these niches {\textquoteright}grow{\textquoteright} together and standardization occurs. The implications of the model are confirmed using a small panel data set of US cities.},
	author = {Markus Mobius}
}
@unpublished {60,
	title = {Social Networks and Consumer Demand},
	year = {2011},
	month = {January 2011},
	author = {Markus Mobius and Paul Niehaus and Tanya Rosenblat}
}
@proceedings {46,
	title = {Buy-it-now or Take-a-chance: A Simple Sequential Screening Mechanism},
	journal = {Proceedings of the 20th international conference on World wide web},
	volume = {WWW {\textquoteright}11},
	number = {March 2011},
	year = {2011},
	pages = {147-156},
	publisher = {International World Wide Web Conference Committee},
	address = {Hyderabad, India},
	abstract = {We present a simple auction mechanism which extends the second-price auction with reserve and is truthful in expectation. This mechanism is particularly effective in private value environments where the distribution of valuations are irregular. Bidders can {\textquotedblleft}buy-it-now{\textquotedblright}, or alternatively {\textquotedblleft}takea- chance{\textquotedblright} where the top d bidders are equally likely to win. The randomized take-a-chance allocation incentivizes high valuation bidders to buy-it-now. We show that for a large class of valuations, this mechanism achieves similar allocations and revenues as Myerson{\textquoteright}s optimal mechanism, and outperforms the second-price auction with reserve. In addition, we present an evaluation of bid data from Microsoft{\textquoteright}s AdECN platform. We find the valuations are irregular, and counterfactual experiments suggest our BINTAC mechanism would improve revenue by 11\% relative to an optimal second-price mechanism with reserve.},
	url = {https://dl.acm.org/citation.cfm?id=1963429},
	author = {L. Elisa  Celis and Gregory Lewis and Markus Mobius and Hamid Nazerzadeh}
}
@article {47,
	title = {What Do We Expect From Our Friends?},
	journal = {Journal of European Economic Association},
	volume = {8},
	number = {1},
	year = {2010},
	pages = {120-138},
	abstract = {We conduct a field experiment in a large real-world social network to examine how subjects expect to be treated by their friends and by strangers who make allocation decisions in modified dictator games. While recipients{\textquoteright} beliefs accurately account for the extent to which friends will choose more generous allocations than strangers (i.e. directed altruism), recipients are not able to anticipate individual differences in the baseline altruism of allocators (measured by giving to an unnamed recipient, which is predictive of generosity towards named recipients). Recipients who are direct friends with the allocator, or even recipients with many common friends, are no more accurate in recognizing intrinsically altruistic allocators. Recipient beliefs are significantly less accurate than the predictions of an econometrician who knows the allocator{\textquoteright}s demographic characteristics and social distance, suggesting recipients do not have information on unobservable characteristics of the allocator.},
	url = {https://doi.org/10.1162/qjec.2009.124.4.1815},
	author = {Stephen Leider and Markus Mobius and Tanya Rosenblat and Quoc-Anh Do}
}
@article {48,
	title = {Directed Altruism and Enforced Reciprocity in Social Network},
	journal = {Quarterly Journal of Economics},
	volume = {124},
	number = {1},
	year = {2009},
	pages = {1815{\textendash}1851},
	abstract = {We conduct online field experiments in large real-world social networks in order to decompose prosocial giving into three components: (1) baseline altruism toward randomly selected strangers, (2) directed altruism that favors friends over random strangers, and (3) giving motivated by the prospect of future interaction. Directed altruism increases giving to friends by 52 percent relative to random strangers, while future interaction effects increase giving by an additional 24 percent when giving is socially efficient. This finding suggests that future interaction affects giving through a repeated game mechanism where agents can be rewarded for granting efficiency-enhancing favors. We also find that subjects with higher baseline altruism have friends with higher baseline altruism.},
	url = {https://doi.org/10.1162/qjec.2009.124.4.1815},
	author = {Stephen Leider and Markus Mobius and Tanya Rosenblat and Quoc-Anh Do}
}
@article {49,
	title = {Trust and Social Collateral},
	journal = {Quarterly Journal of Economics},
	volume = {124},
	number = {3},
	year = {2009},
	pages = {1307{\textendash}1361},
	abstract = {This paper builds a theory of trust based on informal contract enforcement in social networks. In our model, network connections between individuals can be used as social collateral to secure informal borrowing. We dene network-based trust as the highest amount one agent can borrow from another agent, and derive a reduced-form expression for this quantity which we then use in three applications. (1) We predict that dense networks generate bonding social capital that allows transacting valuable assets, while loose networks create bridging social capital that improves access to cheap favors like information. (2) For job recommendation networks, we show that strong ties between employers and trusted recommenders reduce asymmetric information about the qualityof job candidates. (3) Using data from Peru, we show empirically that network-based trust predicts informal borrowing, and we structurally estimate and test our model.},
	url = {https://doi.org/10.1162/qjec.2009.124.3.1307},
	author = {Dean Karlan and Markus Mobius and Tanya Rosenblat and Adam Szeidl}
}
@article {50,
	title = {Community Size and Network Closure},
	journal = {American Economic Review Papers and Proceedings},
	volume = {97},
	number = {2},
	year = {2007},
	pages = {80-85},
	url = {http://www.jstor.org/stable/30034425},
	author = {Hunt Allcott and Dean Karlan and Markus Mobius and Tanya Rosenblat and Adam Szeidl}
}
@article {51,
	title = {Existence of Equilibrium in Large Double Auctions},
	journal = {Journal of Economic Theory},
	volume = {133},
	number = {1},
	year = {2007},
	pages = {550-567},
	abstract = {We show the existence of a pure strategy, symmetric, increasing equilibrium in double auction markets with correlated, conditionally independent private values and many participants. The equilibrium we find is arbitrarily close to fully revealing as the market size grows. Our results provide strategic foundations for price-taking behavior in large markets.},
	url = {https://doi.org/10.1016/j.jet.2005.07.014},
	author = {Drew Fudenberg and Markus Mobius and Adam Szeidl}
}
@article {52,
	title = {Why Beauty Matters},
	journal = {American Economic Review},
	volume = {96},
	number = {1},
	year = {2006},
	pages = {222-235},
	abstract = {We decompose the beauty premium in an experimental labor market where "employers" determine wages of "workers" who perform a maze-solving task. This task requires a true skill which we show to be una{\textregistered}ected by physical attractiveness. We find a sizable beauty premium and can identify three transmission channels. (1) Physically-attractive workers are more confident and higher confidence increases wages. (2) For a given level of confidence, physically-attractive workers are (wrongly) considered more able by employers. (3) Controlling for worker confidence, physically-attractive workers have oral skills (such as communication and social skills) that raise their wages when they interact with employers. Our methodology can be adapted to study the sources of discriminatory pay differentials in other settings.},
	url = {https://doi.org/10.1257/000282806776157515},
	author = {Tanya Rosenblat and Markus Mobius}
}
@article {53,
	title = {Competing Auctions},
	journal = {Journal of European Economic Association},
	volume = {2},
	number = {1},
	year = {2004},
	pages = {30-66},
	abstract = {This paper examines a simple model of competing auction sites to give some insights into the concentration of auction markets. In our model, there are B ex-ante identical buyers, each with unit demand, and S sellers, each with a single unit of the good to sell and a reservation value of zero. At the start of the model, buyers and sellers simultaneously choose between two possible locations. Buyers then learn their private values for the good, and a uniform-price auction is held at each location. This is a very stark model, but we believe that it provides some useful insights, and that it serves as a benchmark case for richer and more realistic models.},
	url = {https://doi.org/10.1162/154247604323015472},
	author = {Glenn Ellison and Drew Fudenberg and Markus Mobius}
}
@article {54,
	title = {Getting Closer or Drifting Apart},
	journal = {Quarterly Journal of Economics},
	volume = {119},
	number = {3},
	year = {2004},
	pages = {971-1009},
	abstract = {Advances in communication and transportation technologies have the potential to bring people closer together and create a {\textquoteleft}global village{\textquoteright}. However, they also allow heterogenous agents to segregate along special interests which gives rise to communities fragmented by type rather than geography. We show that lower communication costs should always decrease separation between individual agents even as group-based separation increases. Each measure of separation is pertinent for distinct types of social interaction. A group-based measure captures the diversity of group preferences that can have an impact on the provision of public goods. An individual measure correlates with the speed of information transmission through the social network that affects, for example, learning about job opportunities and new technologies. We test the model by looking at coauthoring between academic economists before and during the rise of the Internet in the 1990s.},
	url = {https://doi.org/10.1162/0033553041502199},
	author = {Tanya Rosenblat and Markus Mobius}
}
@unpublished {64,
	title = {Formation of Social Capital: An Experiment},
	year = {2002},
	month = {December 2002},
	abstract = {We study the formation of social capital in an environment where specialized agents have frequent diverse needs. This limits the potential of purely bilateral cooperation because the interaction frequency between any two particular agents is low. Such interactions usually invite defection by both sides unless agents are altruistic, or there exist information aggregation institutions that facilitate the use of group punishments. In a companion paper Gentzkow and Mobius (2002) develop a theory of how agents can cooperate even in a limited information environment as long as they can relay requests for help. This mechanism creates networks with long-term relationships which are continuously recombined to satisfy short-term needs. We test the theoretical predictions by conducting an experiment with two treatments: in the first treatment, agents can only utilize direct {\textquoteleft}favors{\textquoteright} while the second treatment adds the ability to provide indirect {\textquoteleft}favors{\textquoteright} as well. Our results help us understand how agents form and sustain weak links.},
	author = {Markus Mobius and Tanya Rosenblat}
}
@unpublished {66,
	title = {The Process of Ghetto Formation: Evidence from Chicago},
	year = {2001},
	month = {December 2001},
	author = {Markus Mobius and Tanya Rosenblat}
}
@unpublished {67,
	title = {Trading Favors},
	year = {2001},
	author = {Markus Mobius}
}
@unpublished {65,
	title = {On the Transition Between Monetary Regimes},
	year = {2001},
	month = {July 2001},
	abstract = {Historically, commodity money preceded fiat money. Standard search-theoretical models of money such as Kiyotaki and Wright (1989) cannot explain this transition because of multiple equilibria: a small infusion of fiat money with superior intrinsic characteristics into a commodity money equilibrium is always valued if agents believe in its acceptability. We propose a natural extension of the standard model in order to break this indeterminacy. We assume (1) that agents derive positive utility from consuming even non-favorite commodities and (2) that agents have to consume regularly. We find that agents accept only commodity money if search frictions are large. Fiat money can become valuable in sufficiently advanced economies with small search frictions.},
	author = {Tanya Rosenblat and Markus Mobius}
}
@unpublished {75,
	title = {The Formation of Ghettos as a Local Interaction Phenomenon},
	year = {2000},
	abstract = {I analyze a simple evolutionary model of residential segregation based on decentralized racism which extends Schelling{\textquoteright}s (1972) well-known tipping model by allowing for local interaction between residents. The richer set-up explains not only the persistence of ghettos, but also provides a mechanism for the rapid transition from an all-white to an all-black equilibrium. On one-dimensional streets segregation arises once a group becomes sufficiently dominant in the housing market. However, the resulting ghettos are not persistent, and periodic shifts in the market can give rise to "avenue waves". On two-dimensional inner-cities, on the other hand, ghettos can be persistent due to the \encircling phenomenon" if the majority ethnic group is sufficiently less tolerant than the minority. I review the history of residential segregation in the US and argue that my model can explain the rapid rise of almost exclusively black ghettos at the beginning of the 20th century. For the analysis of my model I introduce a new technique to characterize the medium and long-run stochastic dynamics. I show that clustering predicts the behavior of large-scale processes with many agents more accurately than standard stochastic stability analysis, because the latter concept overemphasizes the {\textquoteright}noisy{\textquoteright} part of the stochastic dynamics.},
	author = {Markus Mobius}
}
