Columbia Business School Research

Political connections to a regime with an authoritarian history present a dilemma for firms during a democratic transition. Such connections provide an essential competitive advantage when the regime is in power but become a liability when a democratic transition results in regime change. This study theorizes that when mass protests expose the regime’s policy distortion and signal a high probability of regime turnover, firms may hedge against the risks associated with their political connections by engaging in philanthropy.

Advancements in data analytics and increased access to consumer data have revolutionized companies’ price discrimination capabilities. These technological advancements have not only changed how prices are determined but also who determines them, with companies increasingly relying on algorithms rather than humans to set prices. We examine consumers’ fairness perceptions of demographic price discrimination—a prevalent yet controversial practice that can trigger considerable consumer backlash—and find that it depends on who is responsible for setting prices.

With multinational corporations (MNCs) increasingly taking public stances on sociopolitical issues such as immigration, LGBTQ+ rights, and racism, it is imperative that International Business (IB) research keeps pace with normative societal debates. In this paper, we introduce the concept of corporate sociopolitical activism (SPA) to the IB literature and develop theory on why MNCs consistently or inconsistently engage in SPA in response to the same issue in their home country and a host country.

The extent of future climate change is largely a policy choice. We illuminate this choice with climate policy curves (CPCs), which link climate policies to subsequent global temperatures. The estimated downward sloping CPCs highlight the key trade-off between initial policy ambition, expressed via an overall effective carbon price, and the subsequent policy burden left for future generations. We also demonstrate how different CPCs can illustrate the range of climate policy paths towards attaining the Paris Agreement temperature goals.

Immigrants are highly entrepreneurial. But, what is the broader relationship between high-skilled immigration and regional entrepreneurship activity beyond the ventures that immigrants establish themselves? Using administrative data on newly awarded H-1B visas in the United States, we document a positive relationship between highskilled immigration and regional entrepreneurship. A doubling of immigrants to a metropolitan statistical area is followed by a 6% increase in entrepreneurship within three years.

We propose that social-media users’ own post histories are an underused yet valuable resource for studying fake-news sharing. By extracting textual cues from their prior posts, and contrasting their prevalence against random social-media users and others (e.g., those with similar socio-demographics, political news-sharers, and fact-check sharers), researchers can identify cues that distinguish fake-news sharers, predict those most likely to share fake news, and identify promising constructs to build interventions. Our research includes studies along these lines.

Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling influences consumer choice in e-commerce settings even when there is no face-to-face interaction.

Previous research has shown that consumers respond differently to decisions made by humans versus algorithms. Many tasks, however, are not performed by humans anymore but entirely by algorithms. In fact, consumers increasingly encounter algorithm-controlled products, such as robotic vacuum cleaners or smart refrigerators, which are steered by different types of algorithms. Building on insights from computer science and consumer research on algorithm perception, this research investigates how consumers respond to different types of algorithms within these products.

Acquisitions can shift the market structure of a digital platform in ways that affect subsequent entries and hence the platform’s base of complementors. Synergies that complementor acquirers accrue can be entry-deterring. We develop a two-by-two typology of acquisition synergies in a multisided platform based on the two sides of a platform market (user side or complementary-technology side) and two sources of synergies (scale or scope economies).

Organizational secrecy is central to national security, politics, business, technology, healthcare, and law, but its effects are largely unknown. Keeping organizational secrets creates social divides between those who are required to keep the secret and those who are not allowed to know it. We demonstrate that keeping organizational secrets simultaneously evokes feelings of social isolation and status, which have opposing effects on employee well-being.

As concern with climate change increases, people seek to behave and consume sustainably. This requires understanding which behaviours, firms and industries have the greatest impact on emissions. Here we ask if people are knowledgeable enough to make choices that align with growing sustainability intentions.

We develop a financial-economic model for carbon pricing with an explicit representation of decision making under risk and uncertainty that is consistent with the Intergovernmental Panel on Climate Change’s sixth assessment report. We show that risk associated with high damages in the long term leads to stringent mitigation of carbon dioxide emissions in the near term, and find that this approach provides economic support for stringent warming targets across a variety of specifications.

In this paper, we develop a computational measure of the firm-level rhetorical nationalism. We first review the literature and develop a four-dimensional theoretical framework of nationalism relevant to firms: national pride, anti-foreign, dominant agenda, and corporate role. We then use machine-learning-based text analysis of over 41,000 annual reports of Chinese public firms from 2000 to 2020 and identify a dictionary of words for each dimension.

Using publicly available data from 299 pre-registered replications from the social sciences, we find that the language used to describe a study can predict its replicability above and beyond a large set of controls related to the paper characteristics, study design and results, author information, and replication effort. To understand why, we analyze the textual differences between replicable and nonreplicable studies.

How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information
about others’ characteristics. It can value data that is public or private, about one or many assets, relevant for dividends or for sentiment. While different data types, of course, have different valuations, heterogeneous investors also value the same data

We propose a political economy mechanism that explains the presence of fiscal regimes punctuated by crisis periods. Our model focuses on the interaction between successive deficit-biased governments subject to i.i.d. fiscal shocks. We show that the economy transitions between a fiscally responsible regime and a fiscally irresponsible regime, with transitions occurring during crises when fiscal needs are large. Under fiscal responsibility, governments limit their spending to avoid transitioning to fiscal irresponsibility.

Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines — which we define as repeated behaviors with recurring, temporal structures — for customer management. One reason for this dearth is the difficulty of measuring routines from transaction data, particularly when routines vary substantially across customers. We propose a new approach for doing so, which we apply in the context of ridesharing.

To investigate general patterns in news information in the United States, we combine a protocol for identifying major political news stories, 11 monthly surveys with 15,000 participants, and a model of news discernment. When confronted with a true and a fake news story, 47 percent of subjects confidently choose the true story, 3 percent confidently choose the fake story, and the remaining half are uncertain. Socioeconomic differences are associated with large variations in the probability of selecting the true news story.

Nearly everyone keeps secrets, but only recently have we begun to learn about the secrets people keep in their everyday lives and the experiences people have with their secrets. Early experimental research into secrecy sought to create secrecy situations in the laboratory, but in trying to observe secrecy in real time, these studies conflated secrecy with the act of concealment. In contrast, a new psychology of secrecy recognizes that secrecy is far more than biting our tongues and dodging others’ questions.

Constituency mobilization is a widely prevalent corporate political strategy, yet we lack systematic evidence on the scope of its effectiveness. One emerging form of constituency mobilization is user mobilization, wherein a company focuses on rallying political support among its users. This approach differs from traditional lobbying, which relies on tightly controlled insider strategies to exert influence over lawmakers. In our study of user mobilization by platform-based companies in the U.S.

Policymakers increasingly rely on behavioral science in response to global challenges, such as climate change or global health crises. But applications of behavioral science face an important problem: Interventions often exert substantially different effects across contexts and individuals. We examine this heterogeneity for different paradigms that underlie many behavioral interventions. We study the paradigms in a series of five preregistered studies across one in-person and 10 online panels, with over 11,000 respondents in total.

Disagreement over divergent viewpoints seems like an ever-present feature of American life—but how common is debate and with whom do debates most often occur? In the present research, we theorize that the landscape of debate is distorted by social media and the salience of negativity present in high-profile spats. To understand the true landscape of debate, we conducted three studies (N = 2985) across online and lab samples.

We study the effects of competition by state-owned firms, leveraging the decentralized entry of public pharmacies to local markets in Chile. Public pharmacies sell the same drugs at a third of private pharmacy prices, because of stronger upstream bargaining and market power in the private sector, but are of lower quality. Public pharmacies induced market segmentation and price increases in the private sector, which benefited the switchers to the public option but harmed the stayers.

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.

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.

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.

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.

Under standard assumptions, individuals and the government are indifferent between traditional tax-deferred retirement accounts and “front-loaded” (Roth) accounts. Adding investment fees to this benchmark, individuals are still indifferent but the government is not. We show that under weak conditions firms charge equal percent fees under both systems, yielding higher dollar fees under Traditional. We estimate that tax deferral increases demand for asset management services by $3.8 trillion, costing the government $23.4 billion in annual fees.

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.

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.

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.