Columbia Business School Research

We recover valuations of time using detailed data from a large ride-hail platform, where drivers bid on trips and consumers choose between a set of rides with different prices and wait times. Leveraging a consumer panel, we estimate demand as a function of both prices and wait times and use the resulting estimates to recover heterogeneity in the value of time across consumers. We study the welfare implications of personalized pricing and its effect on the platform, drivers, and consumers.

Should consumer researchers employ silicon samples and artificially generated data based on large language models, such as GPT, to mimic human respondents' behavior? In this paper, we review recent research that has compared result patterns from silicon and human samples, finding that results vary considerably across different domains. Based on these results, we present specific recommendations for silicon sample use in consumer and marketing research.

We consider a New Keynesian model with strategic monetary and fiscal interactions. The fiscal authority maximizes social welfare. Monetary policy is delegated to a central bank with an anti-inflation bias that suffers from a lack of commitment. The impact of central bank hawkishness on debt issuance is non-monotonic because increased

The United States recently passed major federal laws supporting the energy transition, and analyses suggest that their successful implementation could reduce US emissions more than 40% below 2005 levels by 2030. However, achieving maximal emissions reductions would require frictionless supply and demand responses to the laws’ incentives and implementation that avoids polarization and efforts to repeal or undercut them. In this Perspective, we discuss some of these supply, demand and polarization challenges.

Industry groups engage in venue shifting when they seek to overturn or alter restrictive regulations imposed by one political venue through another. A critical step in this process is resolving uncertainties surrounding the preference of the targeted venue and the nature of the relevant policy proposal. While existing studies emphasize a long-term trial-and-error process of policy learning, we focus on nascent industries and argue that ventures seek other information sources to resolve these uncertainties quickly.

Making good health insurance decisions is important for health outcomes and longevity, but consumers’ errors are well documented. The authors examine whether targeted choice architecture interventions can reduce these mistakes. The article examines the interaction of two choice architecture tools on improved consumer insurance decisions in online health care exchanges: (1) ordering the options from best to worst based on a high-quality user model and (2) partitioning the total set of options.

‘Moral hazard’ links geoengineering to mitigation via the fear that either solar geoengineering (solar radiation management, SRM) or carbon dioxide removal (CDR) might crowd out the desire to cut emissions. Fear of this crowding-out effect ranks among the most frequently cited risks of (solar) geoengineering. We here test moral hazard versus its inverse in a large-scale, revealed-preference experiment (n~340,000) on Facebook and find little to no support for either outcome. For the most part, talking about SRM or CDR does not motivate our study population to support a large U.S.

Although organizations increasingly seek to communicate allyship with the Black community, their ally statements can receive vastly different responses from Black observers. We develop and test a theoretical model outlining key drivers of allyship evaluations among these perceivers. Drawing from signaling theory and integrating insights from the literature on identity safety, we reveal the costliness and consistency of ally statements as critical determinants of Black perceivers’ evaluations of organizations as allies.

Big data technologies change the way in which data and human labor combine to create knowledge. Is this a modest technological advance or a data revolution? Using hiring and wage data, we show how to estimate firms' data stocks and the shape of their knowledge production functions. Knowing how much production functions have changed informs us about the likely long-run changes in output, in factor shares, and in the distribution of income, due to the new, big data technologies.

Due to the Covid-19 pandemic, many employees have spent a considerable amount of time being forced to work from home (WFH). We draw on the Job Demands-Resources (JD-R) model and self-affirmation theory to study how the anticipation of returning to the physical workplace affects work engagement and burnout. We assumed that employees are conflicted about returning to work (RTW). Whereas they may look forward to RTW they also appreciate aspects of WFH which would have to be foregone.

In response to increasing societal divisions, an extensive literature has emerged examining the construct of receptiveness. This literature suggests that signaling receptiveness to others confers a variety of interpersonal benefits, such as increased persuasiveness. How do people signal their receptiveness to others? The current research investigates whether one of the most fundamental aspects of language—pronoun use—could shape perceptions of receptiveness.

How much will it cost to meaningfully reduce greenhouse gas (GHG) emissions on a global scale? The answer is critical for assessments of how to address climate change—affecting public support, political will, and policy choices. We find that the “bottom-up” estimation approach emphasized by the United Nations Intergovernmental Panel on Climate Change (IPCC) reports considerably lower costs for emission reductions than leading “top-down” economic models.

Professional house price forecast data are consistent with a rational model where agents must learn about the parameters of the house price growth process and the underlying state of the housing market. Slow learning about the long-run mean generates overreaction to forecast revisions and a modest response of forecasts to lagged realizations. Heterogeneity in signals and priors about the long-run mean helps the model account for cross-sectional dispersion in forecasts. Introducing behavioral biases helps improve the model's predictions for short-horizon overreaction and dispersion.

The speed of stock price reaction to news exhibits substantial time variation. Higher risk-bearing capacity of financial intermediaries, lower passive ownership of stocks, and more informative news increase price responses to contemporaneous news; surprisingly, these interaction variables also increase price responses to lagged news (underreaction). A simple model with limited attention and three investor types (institutional, noninstitutional, and passive) predicts the observed variation in news responses.

This paper theoretically and empirically investigates the effects of liquidity regulation on the banking system. We document that the current quantity-based liquidity rule has reduced banks’ liquidity risks. However, the mandated liquidity buffer appears to crowd out bank lending and lead to a migration of liquidity risks to banks that are not subject to liquidity regulation. These findings motivate a model of liquidity regulation with endogenous liquidity premiums and heterogeneous banks.

The contemporary art world is conservatively estimated to be a $65 billion USD market that employs millions of human artists, sellers, and collectors globally. Recent attention paid to AI-made art in prestigious galleries, museums, and popular media has provoked debate around how these statistics will change. Unanswered questions fuel growing anxieties. Are AI-made and human-made art evaluated in the same ways? How will growing exposure to AI-made art impact evaluations of human creativity? Our research uses a psychological lens to explore these questions in the realm of visual art.

We propose a tractable model of dynamic investment, spinoffs, financing, and risk management for a multi-division firm facing costly external finance. Our analysis formalizes

This is the first study to consider the relationship between open source software (OSS) and entrepreneurship around the globe. This study measures whether country-level participation on the GitHub OSS platform affects the founding of innovative ventures, and where it does so, for what types of ventures. We estimate these effects using cross-country variation in new venture founding and OSS participation. We propose an approach using instrumental variables, and cannot reject a causal interpretation.

The onset of COVID-19 was characterized by voluminous, negative news. Higher narrativity news topics (measured by textual proximity to articles describing the 1987 stock market crash and textual distance from Federal Reserve communications) were systematically associated with contemporaneous market responses, which were larger on high volatility days (hypersensitivity), and with markets–news feedback. Hypersensitive news topic-market pairs were associated with next-day reversals.

We develop a model of investor information choices and asset prices in which the availability of information about fundamentals is time-varying and responds to investor demand for information. A competitive research sector produces more information when more investors are willing to pay for that research. This feedback, from investor willingness to pay for information to more information production, generates two regimes in equilibrium, one having high prices and low volatility, the other the opposite.

An investor receives utility bursts from realizing gains and losses at the individual-stock level (Barberis and Xiong, 2009, 2012; Ingersoll and Jin, 2013) and dynamically allocates his mental budget between risky and risk-free assets at the trading-account level. Using savings, he reduces his stockholdings and is more willing to realize losses. Using leverage, he increases his stockholdings beyond his mental budget and is more reluctant to realize losses. While leverage strengthens the disposition effect, introducing leverage constraints mitigates it.

We propose a theory of banking in which banks cannot perfectly control deposit flows. Facing uninsurable loan and deposit shocks, banks dynamically manage lending, wholesale funding, deposits, and equity. Deposits create value by lowering funding costs. However, when the bank is undercapitalized and at risk of breaching leverage requirements, the marginal value of deposits can turn negative as deposit inflows, by raising leverage, increase the likelihood of costly equity issuance.

In the months before the 2020 U.S. election, several political campaign websites added prechecked boxes (defaults), automatically making all donations into recurring weekly contributions unless donors unchecked them. Since these changes occurred at different times for different campaigns, we use a staggered difference-in-differences design to measure the causal effects of defaults on donors’ behavior. We estimate that defaults increased campaign donations by over $43 million while increasing requested refunds by almost $3 million.

In the twenty-first century, the most valuable firms in the world are valued primarily for their data. This makes data central to finance. Data are an important asset to price; they change firm valuation and are a key consideration for an entrepreneur starting a new firm.

Can accelerators pick the most promising startup ideas no matter their provenance? Using unique data from a global accelerator where judges are randomly assigned to evaluate startups headquartered across the globe, we show that judges are less likely to recommend startups headquartered outside their home region by 4 percentage points. Back-of-the-envelope calculations suggest this discount leads judges to pass over 1 in 20 promising startups.

This study presents moral cost as a novel behavioral constraint on firm resource adjustment, specifically layoff decisions that can cause severe harm to employees. Revising the prevailing negative view of managers as purely self-interested, we propose that managers care about their employees and incur moral cost from layoffs. We leverage expansions in unemployment insurance as a quasi-natural experiment that reduces economic hardship for laid-off workers and, in turn, the moral cost of layoffs to managers. We find that these expansions license larger layoffs.

ASC 842, which requires balance sheet recognition of right-of-use (ROU) lease assets, resulted in a large increase in reported assets since 2019, thus impairing the time-series consistency of metrics that use assets (e.g., asset turnover). This paper shows that ROU assets can be estimated quite precisely using lease disclosure. Adding the estimated ROU asset for pre-ASC 842 observations substantially improves the ability of operating assets to explain sales. It also increases the ability of growth in operating assets to predict sales growth and explain analysts’ revenue growth forecasts.

How should market designers trade off targeting and competition? We study a natural experiment in the release of new targeting technology for online ads. A platform in our study introduced targeting into select geographic markets based on a discontinuity in local characteristics. We find that advertisers used new targeting to avoid low quality ad inventory. This led to a reduction in ad impressions. When advertisers avoided this inventory, they retreated into smaller, less competitive ad auctions featuring fewer bidders for available ad space.

Problem definition: Motivated by ride-hailing platforms such as Uber, Lyft and Didi, we study the problem of matching riders with self-interested drivers over a spatial network.

In the past decades, as traditional luxury goods and conspicuous consumption have become more mainstream and lost some of their signaling value, new alternative signals of status (e.g., vintage, inconspicuous consumption, sustainable luxury) have progressively emerged. This research applies the grounded theory method to establish a novel framework that systematically unifies existing conceptualizations, findings, and observations on alternative signals of status.

There is a consensus that global value chains have aided developing countries' growth. This essay highlights the governance complexities arising from participating in such chains, drawing from lessons we have learned conducting research in the coffee and garment supply chains. Market power of international buyers can lead to inefficiently low wages, prices, quality standards, and poor working conditions. At the same time, some degree of market power might be needed to sustain long-term supply relationships that are beneficial in a world with incomplete contracts.

How can firms encourage consumers to adopt smartphone apps? The authors show that several inexpensive choice architecture techniques can make users more likely to enable important app features and complete app onboarding. In six preregistered experiments (n = 5,968) and a field experiment (n = 594,997), choice architecture interventions manipulating choice sequence, color, and wording of app adoption decisions dramatically increased app adoption. Across experiments, integrating multiple feature decisions into a single choice increased adoption.

Strategies for coping with businesses that face the declining demand of late life-cycle products are
revisited in light of the enhanced competitive capabilities made possible by access to the World
Wide Web and connectivity to the Internet. Presumably endgame competitors may draw upon a
wider variety of implementation options on both the demand and supply sides when serving the
highly-connected markets reached via Internet access. Results are posited to be mixed since supply-

Emissions abatement alone cannot address the consequences of global warming for weather disasters. We model how society adapts to manage disaster risks to capital stock. Optimal adaptation — a mix of firm-level efforts and public spending — varies as society learns about the adverse consequences of global warming for disaster arrivals. Taxes on capital are needed alongside those on carbon to achieve the first best.

We study a regulation in Chile that mandates warning labels on products whose sugar or caloric concentration exceeds certain thresholds.We show that consumers substitute from labeled to unlabeled products—a pattern mostly driven by  products that consumers mistakenly believe to be healthy. On the supply side, we find substantial reformulation of products and bunching at the thresholds.

This paper analyzes the entire business registry of Colombia during 2015 to 2022, a period when Colombia received two million Venezuelan immigrants and refugees. We present two main findings. First, firms owned by foreigners, most of them Venezuelans, tend to be 10 to 20 percent more capitalized when founded, as compared to firms owned by locals within the same industry, geographic location, and year of registration. Second, while more intensive in capital, these firms owned by foreigners are just as likely to survive the first 2 and 3 years as firms owned by locals.

Big data is changing every corner of economics and finance. The largest firms in the US economy are valued chiefly for their data. Yet, these data are largely excluded from macroeconomic and finance research. We review work and relevant tools for measuring economic activity, market power, data markets, and the role of data in financial markets. We also highlight areas where future work is needed.

In light of the widely discussed political divide and increasing societal polarization, we investigate in this paper whether the polarization of political ideology extends to consumers’ preferences, intentions, and purchases. Using three different data sets—the publicly available social media data of over three million brand followerships of Twitter users, a YouGov brand-preference survey data set, and Nielsen scanner panel data—we assess the evolution of brand-preference polarization.

To study the impacts of NewYork’s 2018 Paid Family Leave (PFL) policy on employer outcomes, we designed and fielded a survey of small firms in NewYork and a control state, Pennsylvania, which does not have a PFL policy. We match each NY firm to a comparable PA firm and use difference-in-differences models to analyze within-match-pair changes in outcomes. Contrary to common concerns about the burdens of PFL on employers, we find no evidence that PFL had any adverse impacts on employer ratings of employee performance or their ease of handling long employee absences.

In-group bias can be detrimental for communities and economic development. We study the causal effect of financial constraints on in-group bias in prosocial behaviors – cooperation, norm enforcement, and sharing – among low-income rice farmers in rural Thailand, who cultivate and harvest rice once a year. We use a between-subjects design – randomly assigning participants to experiments either before harvest (more financially constrained) or after harvest. Farmers interacted with a partner either from their own village (in-group) or from another village (out-group).