Columbia Business School Research

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.

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.

Loss aversion, the principle that losses impact decision making more than equivalent gains, is a fundamental idea in consumer behavior and decision making, though its existence has recently been called into question. Across five unique samples (N_total = 17,720), we tested several moderators of loss aversion, which supported a preference construction account. Across studies, more domain knowledge and experience were associated with lower loss aversion, though people of all knowledge and experience levels were loss averse.

Utilizing transaction-level financial data, we explore how household consumption responded to the onset of the COVID-19 pandemic. As case numbers grew and cities and states enacted shelter-in-place orders, Americans began to radically alter their typical spending across a number of major categories. In the first half of March 2020, individuals increased total spending by over 40% across a wide range of categories.

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.

A principal faces an agent who is better informed but biased toward higher actions. She can verify the agent's information and specify his permissible actions. We show that if the verification cost is small enough, a threshold with an escape clause (TEC) is optimal: the agent either chooses an action below a threshold or requests verification and the efficient action above the threshold. For higher costs, however, the principal may require verification only for intermediate actions, dividing the delegation set.

Auctions are widely used in practice. While also extensively studied in the literature, most of the developments rely on the significant common prior assumption. We study the design of optimal prior-independent selling mechanisms: buyers do not have any information about their competitors and the seller does not know the distribution of values, but only a general class it belongs to.

There has been extensive discussion about gender gaps in representation and career advancement in the sciences. However, psychological science itself has yet to be the focus of discussion or systematic review, despite our field’s investment in questions of equity, status, well-being, gender bias, and gender disparities. In the present article, we consider 10 topics relevant for women’s career advancement in psychological science.

We examine a Query Theory account of risky choice framing effects — when risky choices are framed as a gain, people are generally risky averse but, when an equivalent choice is framed as a loss, people are risk seeking. Consistent with Query Theory, frames affected the structure of participants’ arguments: gain frame participants listed arguments favoring the certain option earlier and more often than loss frame participants. These argumentative shifts mediated framing effects; manipulating participants initial arguments attenuated them.

Current accounting practice expenses many investments in intangible assets to the income statement, confusing earnings from current revenues with investments to gain future revenues. This has led to increasing calls to book those investments to the balance sheet. Drawing on the relevant research, this paper proposes solutions for the accounting for intangible assets that contrast with balance sheet recognition, and compares them to current practice and the IFRS standards that dictate practice.

Common wisdom holds that uncertainty impedes trade—yet we show that uncertainty can fuel more trade in a simple general equilibrium trade model with information frictions. In equilibrium, increases in uncertainty increase both the mean and variance in returns to exporting. This implies that trade can increase or decrease with uncertainty, depending on preferences. Under general conditions on preferences, we characterize the importance of these forces using a sufficient statistics approach.

Using US Census employer-employee matched data, I show that employer financial distress accelerates the exit of employees to found start-ups. This effect is particularly evident when distressed firms are less able to enforce contracts restricting employee mobility into competing firms. Entrepreneurs exiting financially distressed employers earn higher wages prior to the exit and after founding start-ups, compared to entrepreneurs exiting non-distressed firms. Consistent with distressed firms losing higher-quality workers, their start-ups have higher average employment and payroll growth.

Companies that freeze defined benefit pension plans save the equivalent of 13.5% of the long-horizon payroll of current employees. Furthermore, firms with higher prospective accruals are more likely to freeze their plans. Cost savings would not be possible in a benchmark model in which i) all workers receive compensation equal to their marginal product and ii) workers value equally all identical-cost forms of pension benefits.

"Big data" financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others' information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others' demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies.

The Great Recession was a deep downturn with long-lasting effects on credit, employment and output. While narratives about its causes abound, the persistence of GDP below pre-crisis trends remains puzzling. We propose a simple persistence mechanism that can be quantified and combined with existing models. Our key premise is that agents don't know the true distribution of shocks, but use data to estimate it non-parametrically. Then, transitory events, especially extreme ones, generate persistent changes in beliefs and macro outcomes.

New technologies such as Internet of Things (IoT), Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), virtual assistants, chatbots, and robots, which are typically powered by Artificial Intelligence (AI), are dramatically transforming the customer experience. In this paper, we offer a fresh typology of new technologies powered by AI and propose a new framework for understanding the role of new technologies on the customer/shopper journey.

The increased focus on misinformation has spurred development of data and systems for detecting the veracity of a claim as well as retrieving authoritative evidence. The Fact Extraction and VERification (FEVER) dataset provides such a resource for evaluating end-to-end fact-checking, requiring retrieval of evidence from Wikipedia to validate a veracity prediction.

Climate change has myriad physical and economic impacts. Even those that can be easily quantified indicate the need for ambitious climate action. Other climate impacts have yet to be quantified. We argue here that uncertainties in climate and weather extremes only further increase the social cost of carbon emissions.