Bike-Share Systems: Accessibility and Availability
Ashish Kabra (University of Maryland)
Elena Belavina (Cornell University)
Karan Girotra (Cornell University)
Abstract
The cities of Paris, London, Chicago, and New York (among many others) have set up bike-share systems to facilitate the use of bicycles for urban commuting. This paper estimates the impact of two facets of system performance on bike-share ridership: accessibility (how far the user must walk to reach stations) and bike-availability (the likelihood of finding a bicycle). We obtain these estimates from a structural demand model for ridership estimated using data from the Vélib』 system in Paris. We find that every additional meter of walking to a station decreases a user’s likelihood of using a bike from that station by 0.194% (±0.0693%), and an even more significant reduction at higher distances (>300 m). These estimates imply that almost 80% of bike-share usage comes from areas within 300 m of stations, highlighting the need for dense station networks. We find that a 10% increase in bike-availability would increase ridership by 12.211% (±1.097%), three-fourths of which comes from fewer abandonments and the rest of which comes from increased user interest. We illustrate the use of our estimates in comparing the effect of adding stations or increasing bike-availabilities in different parts of the city, at different times, and in evaluating other proposed improvements.
Capacity Pooling in Hospitals: The Hidden Consequences of Off-Service Placement
Hummy Song (University of Pennsylvania)
Anita L. Tucker (Boston University)
Ryan Graue (Beth Israel Deaconess Medical Center)
Sarah Moravick (Beth Israel Deaconess Medical Center)
Julius J. Yang (Beth Israel Deaconess Medical Center)
Abstract
Hospital managers struggle with the day-to-day variability in patient admissions to different clinical services, each of which typically has a fixed allocation of hospital beds. In response, many hospitals engage in capacity pooling by assigning patients from a service whose designated beds are fully occupied to an available bed in a unit designated for a different service. This 「off-service placement」 occurs frequently, yet its impact on patient and operational measures has not been rigorously quantified. This is, in part, because of the challenge of properly accounting for the endogenous selection of off-service patients. We use an instrumental variable approach to quantify the causal effects of off-service placement of hospitalized medical/surgical patients, having accounted for the endogeneity issues. Using data from a large academic medical center with 19.6% of medical/surgical patients placed off service on average, we find that off-service placement is associated with a 22.8% increase in remaining hospital length of stay (LOS) and a 13.1% increase in the likelihood of hospital readmission within 30 days. We find no significant effect on in-hospital mortality or clinical trigger (rapid response) activation. We identify longer distances to the service’s home unit as a key mechanism that drives the effect on LOS. In contrast, a mismatch in nursing specialization does not seem to explain this effect. By quantifying the effects of off-service placement on patient and operational outcomes, we enable clinicians and hospital managers to make better-informed short-term decisions about off-service placement and longer-term decisions about capacity allocation.
Token-Weighted Crowdsourcing
Gerry Tsoukalas (University of Pennsylvania)
Brett Hemenway Falk (University of Pennsylvania)
Abstract
Blockchain-based platforms often rely on token-weighted voting (「τ-weighting」) to efficiently crowdsource information from their users for a wide range of applications, including content curation and on-chain governance. We examine the effectiveness of such decentralized platforms for harnessing the wisdom and effort of the crowd. We find that τ-weighting generally discourages truthful voting and erodes the platform’s predictive power unless users are 「strategic enough」 to unravel the underlying aggregation mechanism. Platform accuracy decreases with the number of truthful users and the dispersion in their token holdings, and in many cases, platforms would be better off with a 「flat」 1/n mechanism. When, prior to voting, strategic users can exert effort to endogenously improve their signals, users with more tokens generally exert more effort—a feature often touted in marketing materials as a core advantage of τ-weighting—however, this feature is not attributable to the mechanism itself, and more importantly, the ensuing equilibrium fails to achieve the first-best accuracy of a centralized platform. The optimality gap decreases as the distribution of tokens across users approaches a theoretical optimum, which we derive, but tends to increase with the dispersion in users』 token holdings.
Stock or Print? Impact of 3-D Printing on Spare Parts Logistics
Jing-Sheng Song (Duke University)
Yue Zhang (Pennsylvania State University)
Abstract
We present a general framework to study the design of spare parts logistics in the presence of three-dimensional (3-D) printing technology. We consider multiple parts facing stochastic demands and adopt procure/manufacture-to-stock versus print-on-demand to highlight the main difference of production modes featured in traditional manufacturing and 3-D printing. To minimize long-run average system cost, our model determines which parts to stock and which to print. We find that the optimal 3-D printer’s utilization increases as the additional unit cost of printing declines and the printing speed improves. The rate of increase, however, decays, demonstrating the well-known diminishing returns effect. We also find the optimal utilization to increase in part variety and decrease in part criticality, suggesting the value of 3-D technology in tolerating large part variety and the value of inventory for critical parts. By examining the percentage cost savings enabled by 3-D printing, we find that, although the reduction in printing cost continuously adds to the value of 3-D printing in a linear fashion, the impact of the improvement of printing speed exhibits S-shaped growth. We also derive various structural properties of the problem and devise an efficient algorithm to obtain near optimal solutions. Finally, our numerical study shows that the 3-D printer is, in general, lightly used under realistic parameter settings but results in significant cost savings, suggesting complementarity between stock and print in cost minimization.
Value of High-Quality Logistics: Evidence from a Clash Between SF Express and Alibaba
Ruomeng Cui (Emory University)
Meng Li (Rutgers University)
Qiang Li (RutgersUniversity)
Abstract
Consumers regard product delivery as an important service component that influences their shopping decisions on online retail platforms. Delivering products to customers in a timely and reliable manner enhances customer experience and companies』 profitability. In this research, we explore the extent to which customers value a high-quality delivery experience when shopping online. Our identification strategy exploits a natural experiment: a clash between SF Express and Alibaba, the largest private logistics service provider with the highest reputation in delivery quality in China and the largest online retail platform in China, respectively. The clash resulted in Alibaba unexpectedly removing SF Express as a shipping option from Alibaba’s retail platform for 42 hours in June 2017. Using a difference-in-differences design, we analyze the market performance of 129,448 representative stock-keeping units on Alibaba to quantify the economic value of a high-quality delivery service to sales, product variety, and logistics rating. We find that the removal of the high-quality delivery option from Alibaba’s retail platform reduced sales by 14.56% during the clash, increased the contribution of long-tail to total sales—sales dispersion—by 3%, but did not impact the variety and logistics rating of sold products. Furthermore, we also identify product characteristics that attenuate the value of high-quality logistics and find that the removal of SF Express is more obstructive for (1) star products as compared with long-tail products because the same star products are likely to be supplied by competing retail platforms that customers can easily switch to, (2) expensive products because customers need a reliable delivery service to protect their valuable items from damage or loss, and (3) less-discounted products because customers are more willing to sacrifice the service quality over a price markdown.
Why Do Option Prices Predict Stock Returns? The Role of Price Pressure in the Stock Market
Luis Goncalves-Pinto (University of New South Wales; Chinese University of Hong Kong, Hong Kong)
Bruce D. Grundy (University of Melbourne)
Allaudeen Hameed (National University of Singapore)
Thijs van der Heijden (University of Melbourne)
Yichao Zhu (Australian National University)
Abstract
Stock and options markets can disagree about a stock’s value because of informed trading in options and/or price pressure in the stock. The predictability of stock returns based on this cross-market discrepancy in values is especially strong when accompanied by stock price pressure, and it does not depend on trading in options. We argue that option-implied prices provide an anchor for fundamental stock values that helps to distinguish stock price movements resulting from pressure versus news. Overall, our results are consistent with stock price pressure being the primary driver of the option price-based stock return predictability.
Consumption and Portfolio Choice Under Loss Aversion and Endogenous Updating of the Reference Level
Servaas van Bilsen (University of Amsterdam)
Roger J. A. Laeven (University of Amsterdam)
Theo E. Nijman (Tilburg University)
Abstract
We explicitly derive and explore the optimal consumption and portfolio policies of a loss-averse individual who endogenously updates his or her reference level over time. We find that the individual protects current consumption by delaying painful reductions in consumption after a drop in wealth, and increasingly so with higher degrees of endogeneity. The incentive to protect current consumption is stronger with a medium wealth level than with a high or low wealth level. Furthermore, this individual adopts a conservative investment strategy in normal states and typically a more aggressive strategy in good and bad states. Endogeneity of the reference level increases overall risk-taking and generates an incentive to reduce risk exposure with age even without human capital. The welfare loss that this individual would suffer under the conventional constant relative risk aversion (CRRA) consumption and portfolio policies easily exceeds 10%.
Timing of Auctions of Real Options
Lin William Cong (Cornell University)
Abstract
This paper endogenizes auction timing and initiation in auctions of real options. Because bidders have information rent, a seller faces a 「virtual strike price」 higher than the actual exercise cost. The seller inefficiently delays the auction to encourage bidder participation and uses the irreversible nature of time to gain partial control over option exercises. The seller’s private benefit at option exercise may restore efficient auction timing, but option exercises are always inefficiently late. When the seller lacks commitment to auction timing, bidders always initiate in equilibrium, resulting in earlier option exercise and higher welfare than auctions proscribing bidder initiation. Overall, auction timing modifies the distribution of the bidder valuations and has important implications for bidding strategies, auction design, and real outcomes.
What Drives Risk Perception? A Global Survey with Financial Professionals and Laypeople
Felix Holzmeister (University of Innsbruck)
Jürgen Huber (University of Innsbruck)
Michael Kirchler (University of Innsbruck)
Florian Lindner (Max Planck Institute for Research on Collective Goods)
Utz Weitzel ( Vrije Universiteit Amsterdam; Radboud University; Tinbergen Institute)
Stefan Zeisberger (Radboud University; University of Zurich)
Abstract
Risk is an integral part of many economic decisions and is vitally important in finance. Despite extensive research on decision making under risk, little is known about how risks are actually perceived by financial professionals, the key players in global financial markets. In a large-scale survey experiment with 2,213 finance professionals and 4,559 laypeople in nine countries representing ~50% of the world’s population and more than 60% of the world’s gross domestic product, we expose participants to return distributions with equal expected return, and we systematically vary the distributions』 next three higher moments. Of these, skewness is the only moment that systematically affects financial professionals』 perception of financial risk. Strikingly, variance does not influence risk perception, even though return volatility is the most common risk measure in finance in both academia and the industry. When testing other, compound risk measures, the probability to experience losses is the strongest predictor of what is perceived as being risky. Analyzing professionals』 propensity to invest, skewness and loss probability also have strong predictive power, while volatility and kurtosis have some additional effect. Our results are very similar for laypeople, and they are robust across and within countries with different cultural backgrounds, as well as for different job fields of professionals.
Competitive Personalized Pricing
Zhijun Chen (Monash University)
Chongwoo Choe (MonashUniversity)
Noriaki Matsushima (Osaka University)
Abstract
We study a model where each competing firm has a target segment where it has full consumer information and can exercise personalized pricing, and consumers may engage in identity management to bypass the firm’s attempt to price discriminate. In the absence of identity management, more consumer information intensifies competition because firms can effectively defend their turf through targeted personalized offers, thereby setting low public prices offered to nontargeted consumers. But the effect is mitigated when consumers are active in identity management because it raises the firm’s cost of serving nontargeted consumers. When firms have sufficiently large and nonoverlapping target segments, identity management can enable firms to extract full surplus from their targeted consumers through perfect price discrimination. Identity management can also induce firms not to serve consumers who are not targeted by either firm when the commonly nontargeted market segment is small. This results in a deadweight loss. Thus, identity management by consumers can benefit firms and lead to lower consumer surplus and lower social welfare. Our main insight continues to be valid when a fraction of consumers are active in identity management or when there is a cost of identity management. We also discuss the regulatory implications for the use of consumer information by firms as well as the implications for management.
Analyst Forecast Bundling
Michael Drake (Brigham Young University)
Peter Joos (INSEAD)
Joseph Pacelli (IndianaUniversity)
Brady Twedt (University of Oregon)
Abstract
Changing economic conditions over the past two decades have created incentives for sell-side analysts to both provide their institutional clients tiered services and to streamline their written research process. One manifestation of these changes is an increased likelihood of analysts』 issuing earnings forecasts for multiple firms on the same day. We identify this bundling property and show that bundling has increased steadily over time. We provide field evidence that the practice is a cost-saving measure, a natural by-product of analysts focusing on thematic research, and a reflection of forecast updating that occurs in advance of important events. Our empirical analyses show that bundled forecasts are less accurate, less bold, and less informative to investors than nonbundled forecasts. We also find that analysts who produce bundled forecasts provide valuable specialized services to their institutional clients. Our findings ultimately demonstrate that forecast bundling has important implications for the properties of analysts』 forecasts.
Steering in Online Markets: The Role of Platform Incentives and Credibility
Moshe A. Barach (University of Minnesota)
Joseph M. Golden (Collage.com)
John J. Horton (Massachusetts Institute of Technology; National Bureau of Economic Research)
Abstract
Platform marketplaces can potentially steer buyers to certain sellers by recommending or guaranteeing those sellers. Money-back guarantees—which create a direct financial stake for the platform in seller performance—might be particularly effective at steering as they align buyer and platform interests in creating a good match. We report the results of an experiment in which a platform marketplace—an online labor market—guaranteed select sellers for treated buyers. The presence of a guarantee strongly steered buyers to these guaranteed sellers, but offering guarantees did not increase sales overall, suggesting financial risk was not determinative for the marginal buyer. This preference for guaranteed sellers was not the result of their lower financial risk, but rather because buyers viewed the platform’s decision to guarantee as informative about relative seller quality. Indeed, a follow-up experiment showed that simply recommending the sellers that the platform would have guaranteed was equally effective at steering buyers.
A Structural Estimation Approach to Study Agent Attrition
Seyed Morteza Emadi (University of North Carolina at Chapel Hill)
Bradley R. Staats (University of North Carolina at Chapel Hill)
Abstract
Worker attrition is a costly and operationally disruptive challenge throughout the world. Although large bodies of research have documented drivers of attrition and the operational consequences of attrition, managers still lack an integrated approach to understanding attrition and making decisions to address it on a forward-going basis. To fill this need, we build a structural model that both captures the firm’s decision to terminate a worker’s employment (involuntary attrition) and uses an optimal stopping problem process to model a worker’s decision to leave the firm (voluntary attrition). We then estimate the parameters of the model and conduct counterfactual analyses on the population of 1,118 agents serving one client over 3 years for an Indian business process management company. Our model reveals a number of interesting findings. We find that supervisors have a strong impact on whether employees stay because they reshape the way that agents make their decisions. We also find that the impact of supervisors on agent attrition is more significant than the impact of salary. For example, increasing salary by 20% decreases the total attrition level by 5%. However, if agents were managed by the best supervisors, among those that manage similar agents, the attrition rate decreases by 10%. Altogether, our paper contributes to the burgeoning literature on people operations and managerial practice.
Customer Supercharging in Experience-Centric Channels
David R. Bell (Idea Farm Ventures)
Santiago Gallino (University of Pennsylvania)
Antonio Moreno (Harvard University)
Abstract
We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon 「supercharging」 and test our thesis using data from a digital-first men’s apparel retailer and a pioneer of the so-called zero inventory store (ZIS) format—a small-footprint, experience-centric retail location that carries no inventory for immediate fulfillment, but fulfils orders via e-commerce. Using a risk-set matching approach, we calibrate our estimates on customers who are 「treated,」 that is, have a ZIS experience, and matched with identical customers who shop online only. We find that after the ZIS experience, customers spend more, shop at a higher velocity, and are less likely to return items. The positive impact on returns is doubly virtuous as it is more pronounced for more tactile, higher-priced items, thus mitigating a key pain point of online retail. Furthermore, the ZIS shopping experience aids product discovery and brand attachment, causing sales to become more diffuse over a larger number of categories. Finally, we demonstrate that our results are robust to self-selection and potentially confounding effects of unobservable factors on the matched pairs of customers. Implications for retailing practice, including for legacy, offline-first retailers, are discussed.
Not in the Job Description: The Commercial Activities of Academic Scientists and Engineers
Wesley M. Cohen (Duke University; National Bureau of Economic Research)
Henry Sauermann (National Bureau of Economic Research; European School of Management and Technology Berlin)
Paula Stephan (National Bureau of Economic Research; Georgia State University)
Abstract
Scholarly work seeking to understand academics』 commercial activities often draws on abstract notions of the academic reward system and the representative scientist. Few scholars have examined whether and how scientists』 motives to engage in commercial activities differ across fields. Similarly, efforts to understand academics』 choices have focused on three self-interested motives—recognition, challenge, and money—ignoring the potential role of the desire to have an impact on others. Using panel data for a national sample of over 2,000 academics employed at U.S. institutions, we examine how the four motives are related to commercial activity measured by patenting. We find that all four motives are correlated with patenting, but these relationships differ systematically between the life sciences, physical sciences, and engineering. These field differences are consistent with differences across fields in the rewards from commercial activities as well as in the degree of overlap between traditional and commercializable research, which affects the opportunity costs of time spent away from 「traditional」 academic work. We discuss potential implications for policy makers, administrators, and managers as well as for future research on the scientific enterprise.
Ties That Bind: The Value of Professional Connections to Sell-Side Analysts
Daniel Bradley (University of South Florida)
Sinan Gokkaya (Ohio University)
Xi Liu (Miami University)
Abstract
We examine professional connections among executives and analysts formed through overlapping historical employment. Analysts with professional connections to coverage firms have more accurate earnings forecasts and issue more informative buy and sell recommendations. These analysts are more likely to participate, be chosen first, and ask more questions during earnings conference calls and analyst/investor days. Homophily based on gender, age, and ethnicity is orthogonal to professional connections. Brokers attract greater trade commissions on stocks covered by connected analysts. Firms benefit through securing research coverage and invitations to broker-hosted investor conferences emulating from these connections.
Owning, Using, and Renting: Some Simple Economics of the 「Sharing Economy」
Apostolos Filippas (Fordham University)
John J. Horton (Massachusetts Institute of Technology)
Richard J. Zeckhauser (Harvard University)
Abstract
New Internet-based 「sharing-economy」 markets enable consumer-owners to rent out their durable goods to nonowners. We model such markets and explore their equilibria both in the short run, in which ownership decisions are fixed, and in the long run, in which ownership decisions can be changed. We find that sharing-economy markets always expand consumption and increase surplus, but may increase or decrease ownership. Regardless, ownership is decoupled from individual preferences in the long run, as the rental rates and the purchase prices of goods become equal. If there are costs of bringing unused capacity to the market, they are partially passed through, creating a bias toward ownership. To test our theoretical work empirically, we conduct a survey of consumers, finding broad support for our modeling assumptions. The survey also allows us to offer a partial decomposition of the bring-to-market costs, based on attributes that make a good more or less amenable to being shared.
Differentiation Strategies in the Adoption of Environmental Standards: LEED from 2000 to 2014
Marc Rysman (Boston University)
Timothy Simcoe (Boston University; National Bureau of Economic Research, Cambridge)
Yanfei Wang (Renmin University of China)
Abstract
We study the role of vertical differentiation in the adoption of LEED (Leadership in Energy & Environmental Design), a multitier environmental building certification system. Our identification strategy relies on the timing of adoption and shows that builders seek to differentiate from each other by choosing a different certification level from previously certified buildings. A common concern in this framework is that mean-reverting behavior could be mistaken for differentiation. We develop a new method for establishing the importance of strategic interactions based on simulating from a model with independent choice and unobserved heterogeneity, and showing that such a model cannot generate the level of interaction that we observe. Finally, we estimate a model that incorporates both differentiation incentives and correlated market-level unobservables and use our estimates from this model to simulate the impact of reducing the number of LEED tiers from four to two. The simulations indicate that environmental investments depend on the location of the threshold between tiers.
Pollution Regulation of Competitive Markets
Krishnan S. Anand (University of Utah)
Fran?ois C. Giraud-Carrier (Weber State University)
Abstract
We develop a model of oligopolistic firms that produce partially differentiated products and generate pollution as a byproduct. We analyze and compare two types of pollution regulation: Cap-and-Trade and Taxes. Firms can respond to regulation by any combination of pollution abatement, output reduction, emissions trading (under Cap-and-Trade), or payment of pollution taxes (under Taxes). We prove that well-chosen regulation can, besides reducing pollution, actually improve firms』 profits relative to laissez-faire (unregulated markets), and simultaneously improve consumer surplus and welfare. Thus, regulation Pareto-dominates laissez-faire under a wide range of plausible conditions. These results are driven by an unintended consequence of pollution regulation: Competing firms can use the regulation to tacitly (and credibly) collude to reduce production and improve their profits. We show that the degree of competition plays a critical role in determining the economic consequences of pollution regulation. Our results suggest that the regulator’s primary consideration should be the impact of regulation on consumers rather than producers.
Inflexible Repositioning: Commitment in Competition and Uncertainty
Jiajia Cong (Fudan University)
Wen Zhou (The University of Hong Kong)
Abstract
We study the value of commitment in a business environment that is both competitive and uncertain, in which two firms face stochastic demands and compete in positioning and repositioning. If the future demand tends to disperse or the demand uncertainty is sufficiently large, one firm chooses rigidity (i.e., commits not to change its positions), and the other chooses flexibility (i.e., to reposition freely). We find that a firm’s rigidity can benefit not only itself, but also its flexible rival. When uncertainty is larger, rigidity becomes more valuable relative to flexibility. These results arise because the asymmetric equilibrium generates two collective gains in addition to the usual individual gain (in terms of competitive advantages) accrued to the committing firm. A firm’s rigid repositioning can soften competition and generate a commitment value, and the other firm’s flexible repositioning generates an option value. Both values then spill over to competitors within the ecosystem. These results suggest that, when firms compete under uncertainty, commitment and options are valuable not only for the party that is making the choice, but also for all competing parties collectively. Commitment value and option value do not have to be mutually exclusive; they can coexist and even strengthen each other through unilateral commitment, which achieves the best of both strategies.
Sequential Learning in Designing Marketing Campaigns for Market Entry
Somayeh Moazeni (Stevens Institute of Technology)
Boris Defourny (Lehigh University)
Monika J. Wilczak (Accenture)
Abstract
Developing marketing campaigns for a new product or a new target population is challenging because of the scarcity of relevant historical data. Building on dynamic Bayesian learning, a sequential optimization assists in creating new data points within a finite number of learning phases. This procedure identifies effective advertisement design elements as well as customer segments that maximize the expected outcome of the final marketing campaign. In this paper, the marketing campaign performance is modeled by a multiplicative advertising exposure model with Poisson arrivals. The intensity of the Poisson process is a function of the marketing campaign features. A forward-looking measurement policy is formulated to maximize the expected improvement in the value of information in each learning phase. A computationally efficient approach is proposed that consists of solving a sequence of mixed-integer linear optimization problems. The performance of the optimal learning policy over a set of benchmark policies is evaluated using examples inspired from the property and casualty insurance industry. Further extensions of the model are discussed.
Cascading Losses in Reinsurance Networks
Ariah Klages-Mundt (Cornell University)
Andreea Minca (Cornell University)
Abstract
We develop a model for contagion in reinsurance networks by which primary insurers』 losses are spread through the network. Our model handles general reinsurance contracts, such as typical excess of loss contracts. We show that simpler models existing in the literature—namely proportional reinsurance—greatly underestimate contagion risk. We characterize the fixed points of our model and develop efficient algorithms to compute contagion with guarantees on convergence and speed under conditions on network structure. We characterize exotic cases of problematic graph structure and nonlinearities, which cause network effects to dominate the overall payments in the system. Last, we apply our model to data on real-world reinsurance networks. Our simulations demonstrate the following. (1) Reinsurance networks face extreme sensitivity to parameters. A firm can be wildly uncertain about its losses even under small network uncertainty. (2) Our sensitivity results reveal a new incentive for firms to cooperate to prevent fraud, because even small cases of fraud can have outsized effect on the losses across the network. (3) Nonlinearities from excess of loss contracts obfuscate risks and can cause excess costs in a real-world system.
Growth Options and Credit Risk
Andrea Gamba (University of Warwick)
Alessio Saretto (University of Texas at Dallas)
Abstract
We calibrate a dynamic model of credit risk and analyze the relation between growth options and credit spreads. Our model features real and financing frictions, a technology with decreasing returns to scale, and endogenous investment options driven by both systematic and idiosyncratic shocks. We find a negative relation between credit spreads and growth options after controlling for determinants of credit risk. This negative relation is a result of the current decision to invest and the associated change in leverage, which, in the presence of external financing needs and financing frictions, increase credit spreads while reducing the value of future investments. We do not find evidence that growth options accrue value in response to systematic risk, thus increasing credit risk premia.
Capital Budgeting and Risk Taking Under Credit Constraints
Felipe S. Iachan (EPGE Brazilian School of Economics and Finance)
Abstract
Limited external financing creates a hedging motive that distorts resource allocation for investment projects. I study these distortions through a dynamic model with endogenous collateral constraints. The hedging motive can be broken into three components: expected future productivity, leverage capacity, and current net worth. Although constrained firms behave as if averse to transitory fluctuations in net worth, they can endogenously pursue increased exposure to both persistent factors that predict future productivity and fluctuations in credit tightness. The most constrained firms abstain from financial hedging, while still distorting capital-allocation decisions, thereby influencing firm-level volatility. These distortions contribute to a potential explanation for the negative cross-sectional relationship between volatility and net worth.
Analysts』 Beauty and Performance
Ying Cao (Chinese University of HongKong)
Feng Guan (Shanghai Universityof Financeand Economics)
Zengquan Li (Shanghai Universityof Financeand Economics)
Yong George Yang (Chinese University of HongKong)
Abstract
We study whether sell-side financial analysts』 physical attractiveness is associated with their job performance. We find that attractive analysts make more accurate earnings forecasts than less attractive analysts. Moreover, more attractive analysts make stock recommendations that are more informative in the short run and more profitable in the long run. Additional analyses reveal that attractive analysts attain their better job performance at least partly through their privileged access to information from firm management. For the sources of the beauty effect, we find that more attractive analysts gain more media exposure, have better connections to institutional investors, and receive more internal support from their employers. Additional evidence suggests that analysts』 physical appearance per se at least partly explains our findings. Overall, our study shows that physical attractiveness has a profound impact on the job performance and information access of sell-side financial analysts.
Influence Activities, Coalitions, and Uniform Policies: Implications for the Regulation of Financial Institutions
Henry L. Friedman (University of California, LosAngeles)
Mirko S. Heinle (University of Pennsylvania)
Abstract
We examine a setting in which agents can form lobbying coalitions to influence a policy maker. Policy uniformity causes agents to free ride on each other’s lobbying and gives them an incentive to form lobbying coalitions. We investigate when coalitions are formed by similar or dissimilar agents and show that endogenous coalition formation causes the effects of policy uniformity and lobbying costs on aggregate lobbying activity and policy strength to be nonmonotonic. Our model suggests that increased competition in the market for coalition-facilitating lobbyists can lead to less lobbying. We discuss implications for the regulation of financial institutions.