Breaking the Cycle: How the News and Markets Created a Negative Feedback Loop in COVID-19
New research from CBS Professor Harry Mamaysky reveals how negativity in the news and markets can escalate a financial crisis.
New research from CBS Professor Harry Mamaysky reveals how negativity in the news and markets can escalate a financial crisis.
Adapted from “Global Value Chains in Developing Countries: A Relational Perspective from Coffee and Garments,” by Laura Boudreau of Columbia Business School, Julia Cajal Grossi of the Geneva Graduate Institute, and Rocco Macchiavello of the London School of Economics.
Adapted from “Online Advertising as Passive Search,” by Raluca M. Ursu of New York University Stern School of Business, Andrey Simonov of Columbia Business School, and Eunkyung An of New York University Stern School of Business.
This paper from Columbia Business School, “Meaning of Manual Labor Impedes Consumer Adoption of Autonomous Products,” explores marketing solutions to some consumers’ resistance towards autonomous products. The study was co-authored by Emanuel de Bellis of the University of St. Gallen, Gita Johar of Columbia Business School, and Nicola Poletti of Cada.
Co-authored by John B. Donaldson of Columbia Business School, “The Macroeconomics of Stakeholder Equilibria,” proposes a model for a purely private, mutually beneficial financial agreement between worker and firm that keeps decision-making in the hands of stockholders while improving the employment contract for employees.
At Columbia Business School, our faculty members are at the forefront of research in their respective fields, offering innovative ideas that directly impact the practice of business today. A quick glance at our publication on faculty research, CBS Insights, will give you a sense of the breadth and immediacy of the insight our professors provide.
As a student at the School, this will greatly enrich your education. In Columbia classrooms, you are at the cutting-edge of industry, studying the practices that others will later adopt and teach. As any business leader will tell you, in a competitive environment, being first puts you at a distinct advantage over your peers. Learn economic development from Ray Fisman, the Lambert Family Professor of Social Enterprise and a rising star in the field, or real estate from Chris Mayer, the Paul Milstein Professor of Real Estate, a renowned expert and frequent commentator on complex housing issues. This way, when you complete your degree, you'll be set up to succeed.
Columbia Business School in conjunction with the Office of the Dean provides its faculty, PhD students, and other research staff with resources and cutting edge tools and technology to help push the boundaries of business research.
Specifically, our goal is to seamlessly help faculty set up and execute their research programs. This includes, but is not limited to:
All these activities help to facilitate and streamline faculty research, and that of the doctoral students working with them.
This article describes randomized field experiments implemented on two online labor market platforms examining the effect of employer charitable giving on a source of human capital that is becoming increasingly important to firms: the gig worker. It provides support that a message about charitable giving increases gig workers' willingness to complete extra work, and that pro-socially oriented gig workers are most responsive.
We estimated the effects of information avoidance and information seeking among parents of children diagnosed with ASD on age of diagnosis. An online survey was completed by 1,815 parents of children with ASD. Children of parents who self-reported that they had preferred "not to know," reported diagnoses around 3 months later than other children.
We study how small and medium enterprise (SME) lenders react to information about their competitors’ contracting decisions. To isolate this learning from lenders’ common reactions to unobserved shocks to fundamentals, we exploit the staggered entry of lenders into an information-sharing platform. Upon entering, lenders adjust their contract terms toward what others offer. This reaction is mediated by the distribution of market shares: lenders with higher shares or that operate in concentrated markets react less.
Global firms finance themselves through foreign subsidiaries, often shell companies in tax havens, which obscures their true economic location in official statistics. We associate the universe of traded securities issued by firms in tax havens with their issuer’s ultimate parent and restate bilateral investment positions to better reflect the financial linkages connecting countries around the world. Bilateral portfolio investment from developed countries to firms in large emerging markets is dramatically larger than previously thought.
We investigate risk and return in the major corporate bond markets of the developed world. We find that average returns increase with maturity and ratings class (where ratings go from high to low) and that this pattern is fit well by a global CAPM model, where the market consists of equity, sovereign and corporate bonds. Nonetheless, we strongly reject "asset class integration," finding a model which separates the market portfolio into its three components to fit much more of the corporate bond return variation.
The authors propose that purchasing luxury can be a unique means to engage in sustainable consumption because high-end products are particularly durable. Six studies examine the sustainability of high-end products, investigate consumer decision making when considering high-end versus ordinary goods, and identify effective marketing strategies to emphasize product durability, an important and valued dimension of sustainable consumption.
Shared Appreciation Mortgages (SAMs) feature mortgage payments that adjust with house prices. These mortgage contracts are designed to stave off home owner default by providing payment relief in the wake of a large house price shock. SAMs have been hailed as an innovative solution that could prevent the next foreclosure crisis, act as a work-out tool during a crisis, and alleviate fiscal pressure during a downturn. They have inspired Fintech companies to offer home equity contracts. However, the home owner's gains are the mortgage lender's losses.
We examine the statistical term structure model of cochrane and Piazzesi (2005) and its affine counterpart, developed in cochrane and Piazzesi (2008) in several out-of-sample analyzes. The model’s one-factor forecasting structure characterizes the term structures of additional currencies in samples ending in 2003. In post-2003 data one-factor structures again characterize each currency’s term structure, but we reject equality of the coefficients across the two samples.
In this paper, we examine a novel two-stage mechanism for selling government securities, wherein the dealers underwrite in the first stage the sale of securities, which are auctioned in stage 2 via either a discriminatory auction (DA) or a uniform price auction (UPA).
According to the Lucas-Stokey result, a government can structure its debt maturity to guarantee commitment to optimal fiscal policy by future governments. In this paper, we overturn this conclusion, showing that it does not generally hold in the same model and under the same definition of time-consistency as in Lucas-Stokey. Our argument rests on the existence of an overlooked commitment problem that cannot be remedied with debt maturity: a government in the future will not necessarily tax above the peak of the Laffer curve, even if it is ex-ante optimal to do so.
We investigate underlying sources of the US entrepreneurial ecosystem's advantage compared to other innovative economies by assessing the benefits Israeli startups derive from migrating to the US. Addressing positive sorting into migration, we show that migrants raise larger funding amounts and are more likely to have a US trademark and be acquired than non-migrants. Migrants also achieve a higher acquisition value. However, their patent output is not larger.
This paper examines the impact of mandatory reporting and auditing of firms' financial statements on industry-wide resource allocation. Using threshold-induced variation in the share of mandated firms in a given industry, I document that reporting mandates facilitate ownership dispersion in capital markets and spur competition in product markets. I, however, do not find that reporting mandates unambiguously improve the efficiency of industry-wide resource allocation. With respect to auditing mandates, I find only that they impose a fixed cost on firms, deterring smaller entrants.
We consider the pricing problem faced by a revenue maximizing platform matching price-sensitive customers to flexible supply units within a geographic area. This can be interpreted as the problem faced in the short-term by a ride-hailing platform. We propose a two-dimensional framework in which a platform selects prices for different locations, and drivers respond by choosing where to relocate in equilibrium based on prices, travel costs and driver congestion levels.
Advice to the Biden administration as it seeks to account for mounting losses from storms, wildfires and other climate impacts.
One of the first executive orders US President Joe Biden signed in January began a process to revise the social cost of carbon (SCC). This metric is used in cost–benefit analyses to inform climate policy. It puts a monetary value on the harms of climate change, by tallying all future damages incurred globally from the emission of one tonne of carbon dioxide now.
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The use of order flow information by financial firms has come to the forefront of the regulatory debate. A central question is: Should a dealer who acquires information by taking client orders be allowed to use or share that information? We explore how information sharing affects dealers, clients and issuer revenues in U.S. Treasury auctions. Because one cannot observe alternative information regimes, we build a model, calibrate it to auction results data, and use it to quantify counter-factuals. The model's key force is that sharing information reduces uncertainty about future value.
Despite a recent surge in corporate activism, with firm leaders communicating about social-political issues unrelated to their core businesses, we know little about its strategic implications. This paper examines the effect of an employer communicating a stance about a social-political issue on employee motivation, using a two-phase, pre-registered field experiment in an online labor market platform. Results demonstrate an asymmetric treatment effect of taking a stance depending on whether the employee agrees or disagrees with that stance.
Many service systems are staffed by workers who work in shifts. In this work, we study the dynamic assignment of servers to different areas of a service system at the beginning of discrete time-intervals, i.e., shifts. The ability to reassign servers at discrete intervals, rather than continuously, introduces a partial flexibility that provides an opportunity for reducing the expected waiting time of customers.
Patients whose transfer to the Intensive Care Unit (ICU) is unplanned are prone to higher mortality rates and longer length-of-stay than those who were admitted directly to the ICU. Recent advances in machine learning to predict patient deterioration have introduced the possibility of proactive transfer from the ward to the ICU. In this work, we study the problem of finding robust patient transfer policies which account for uncertainty in statistical estimates due to data limitations when optimizing to improve overall patient care.
Deciding between the use of market orders and limit orders is an important question in practical optimal trading problems. A key ingredient in making this decision is understanding the uncertainty of the execution of a limit order, that is, the fill probability or the probability that an order will be executed within a certain time horizon. Equivalently, one can estimate the distribution of the time-to-fill. We propose a data-driven approach based on a recurrent neural network to estimate the distribution of time-to-fill for a limit order conditional on the current market conditions.
Deciding between the use of market orders and limit orders is an important question in practical optimal trading problems. A key ingredient in making this decision is understanding the uncertainty of the execution of a limit order, that is, the fill probability or the probability that an order will be executed within a certain time horizon. Equivalently, one can estimate the distribution of the time-to-fill. We propose a data-driven approach based on a recurrent neural network to estimate the distribution of time-to-fill for a limit order conditional on the current market conditions.
The author proposes a topic model tailored to the study of creative documents (e.g., academic papers, movie scripts), which extends Poisson factorization in two ways. First, the creativity literature emphasizes the importance of novelty in creative industries. Accordingly, this article introduces a set of residual topics that represent the portion of each document that is not explained by a combination of common topics. Second, creative documents are typically accompanied by summaries (e.g., abstracts, synopses).
This Better Marketing for a Better World special issue of the Journal of Marketing is motivated by the gap that remains between what is studied in our field and what is possible. We believe that we still know too little about marketing’s role in improving -- or harming -- our world.
Marketing is the functional area primarily responsible for driving the organic growth of a firm. In the age of digital marketing and big data, marketers are inundated with increasingly rich data from an ever-expanding array of sources. Such data may help marketers generate insights about customers and competitors. One fundamental question remains: How can marketers wrestle massive flows of existing and nascent data resources into coherent, effective growth strategies?
We examine how choice bracketing affects expected value maximization in experience-based choice. Experience-based choices are a series of individual choices made sequentially, for which feedback follows each choice, and are thus naturally bracketed narrowly. Previous research broadly bracketed multiple experience-based choices for decision makers by aggregating the choices (such that each choice pertained to multiple individual choices) or by reducing feedback frequency.
We develop a flexible content-based search model that links the content preferences of search engine users to query search volume and click-through rates, while allowing content preferences to vary systematically based on the context of a search. Content preferences are defined over latent topics that describe the content of search queries and search result descriptions.
We develop a flexible content-based search model that links the content preferences of search engine users to query search volume and click-through rates, while allowing content preferences to vary systematically based on the context of a search. Content preferences are defined over latent topics that describe the content of search queries and search result descriptions.
We evaluate the impacts of tax policy on asset returns using the U.S. municipal bond market. In theory, tax-induced ownership segmentation limits risk-sharing, creating downward-sloping regions of the aggregate demand curve for the asset. In the data, cross-state variation in tax privilege policies predicts differences in in-state ownership of local municipal bonds; the policies create incentives for concentrated local ownership. High tax privilege states have muni-bond yields that are more sensitive to variations in supply and local idiosyncratic risk.
Narratives, and other forms of discourse, are powerful vehicles for informing, entertaining, and making sense of the world. But while everyday language often describes discourse as moving quickly or slowly, covering a lot of ground, or going in circles, little work has actually quantified such movements or examined whether they are beneficial.
This research provides a first investigation into how interest-free financing promotions influence consumer behavior. Five experiments demonstrate that framing an economically equivalent financing offer in a way that makes salient that it is interest-free increases consumers’ demand for credit to finance experiential, but not material goods.
Is firm behavior mainly driven by its environment or rather by the characteristics of its managers? We develop a cognitive theory of manager fixed effects, where the allocation of managerial attention determines firm behavior. We show that in complex environments, the endogenous allocation of attention exacerbates manager fixed effects. Small differences in managerial expertise then may result in dramatically different firm behavior, as managers devote scarce attention in a way which amplifies initial differences.
Is firm behavior mainly driven by its environment or rather by the characteristics of its managers? We develop a cognitive theory of manager fixed effects, where the allocation of managerial attention determines firm behavior. We show that in complex environments, the endogenous allocation of attention exacerbates manager fixed effects. Small differences in managerial expertise then may result in dramatically different firm behavior, as managers devote scarce attention in a way which amplifies initial differences.
This research highlights how gender shapes consumer payments in pay-what-you-want contexts. Four studies involving hypothetical and real payments show that men typically pay less than women in pay-what-you-want settings, due to gender differences in agentic versus communal orientation. Men approach the payment decision with an agentic orientation, and women approach it with a communal orientation. These orientations then shape payment motives and ultimately affect payment behavior.
We document that governments whose local currency debt provides them with greater hedging benefits actually borrow more in foreign currency. We introduce two features into a government's debt portfolio choice problem to explain this finding: risk-averse lenders and lack of monetary policy commitment. A government without commitment chooses excessively countercyclical inflation ex post, which leads risk-averse lenders to require a risk premium ex ante.
We cast new light on the influence of pensions on labor supply. To do so, we compare the retention patterns of pension-eligible workers to those of pension-ineligible ones, allowing us to non-parametrically identify the counterfactual in large, administrative data. Pensions exert a retentive force as workers approach the eligibility threshold and apply strong expulsive pressure thereafter (since employees lose pension wealth by remaining employed once eligible).
We study games of incomplete information as both the information structure and the extensive-form vary. An analyst may know the payoff-relevant data but not the players' private information, nor the extenstive-form that governs their play. Alternatively, a designer may be able to build a mechanism from these ingredients. We characterize all outcomes that can arise in an equilibrium of some extensive-form with some information structure.
We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model. We obtain better out-of-sample performance through a random search of plain LDA models. A branching procedure that reinforces effective topic assignments often performs best. We test these methods on an archive of over 90,000 news articles about S&P 500 firms.
We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model. We obtain better out-of-sample performance through a random search of plain LDA models. A branching procedure that reinforces effective topic assignments often performs best. We test these methods on an archive of over 90,000 news articles about S&P 500 firms.
We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model. We obtain better out-of-sample performance through a random search of plain LDA models. A branching procedure that reinforces effective topic assignments often performs best. We test these methods on an archive of over 90,000 news articles about S&P 500 firms.