SPEAKER

Prof. Bentley MacLeod
Visiting Professor and Senior Research Scientist 
Yale University

Sami Mnaymneh Professor Emeritus of Economics 
Professor of International and Public Affairs Emeritus
Columbia University

ABSTRACT

This paper proposes novel natural language methods to measure worker rights from collective bargaining agreements (CBAs) for use in empirical economic analysis. Applying unsupervised text-as-data algorithms to a new collection of 30,000 CBAs from Canada in the period 1986-2015, we parse legal obligations (e.g., “the employer shall provide…”) and legal rights (e.g., “workers shall receive…”) from the contract text. We validate that contract clauses provide worker rights, which include both amenities and control over the work environment. Companies that provide more worker rights score highly on a survey indicating pro-worker management practices. Using time varying province-level variation in labor income tax rates, we find that higher taxes increase the share of worker-rights clauses while reducing pre-tax wages in unionized firms, consistent with a substitution effect away from taxed compensation (wages) toward untaxed amenities (worker rights). Further, an exogenous increase in the value of outside options (from a leave-one-out instrument for labor demand) increases the share of worker rights clauses in CBAs. Combining the regression estimates, we infer that a one-standard-deviation increase in worker rights is valued at about 5.7% of wages.

SPEAKER

Prof. Samina Karim
Professor
D’Amore-McKim School of Business
Northeastern University

ABSTRACT

As startups scale, they often professionalize their management structure, and the decision to appoint the first non-founder manager—whether through internal promotion or external hiring—may influence firm performance. Using employer-employee matched data from Brazilian firms founded between 2004 and 2010, we examine the relationship between this decision and firm survival. Distinguishing managerial human capital into firm-specific, industry-specific, and generic categories, we observe that firms promoting internal candidates tend to have higher survival rates, which we associate with the value of firm-specific knowledge. For firms hiring externally, performance outcomes vary based on the external hire’s industry and managerial experience. These findings contribute to research on organizational scaling, managerial human capital, and decision-making in growing ventures by exploring how early managerial roles are associated with startup performance trajectories.

SPEAKER

Ms. Jingyi Cui
Ph.D. candidate in Economics
Yale University

ABSTRACT

Reputation is often important in markets for experience goods. New sellers commonly invest in reputation by offering introductory pricing or other incentives. By encouraging buyers to try new sellers, these investments generate information externalities for future buyers while diverting business from other sellers. I study reputation investment behavior by workers in the context of a large online labor platform. I show that employers value worker reputation and experience, and that new workers initially bid low wages but raise their bids after obtaining experience and public reviews. I estimate a dynamic equilibrium model where forward-looking workers bid anticipating the impact of reputation and experience on future employment outcomes. Compared to a counterfactual with bidding based only on immediate payoffs, forward-looking bidding increases the equilibrium number of reviewed workers by 52% and quadruples the number of matches on the platform. However, workers’ investments remain below the social optimum. The socially optimal platform-funded subsidy for hiring new workers raises total surplus by 22% while increasing platform profit. The subsidy level that maximizes platform profit is lower, but achieves 80% of the total surplus gain.

SPEAKER

Mr. Jesse Silbert
Ph.D. candidate in Economics
Princeton University

ABSTRACT

Large language models (LLMs) like ChatGPT have significantly lowered the cost of producing written content. This paper studies how LLMs, through lowering writing costs, disrupt markets that traditionally relied on writing as a costly signal of quality (e.g., job applications, college essays). Using data from Freelancer.com, a major digital labor platform, we explore the effects of LLMs’ disruption of labor market signaling on equilibrium market outcomes. We develop a novel LLM-based measure to quantify the extent to which an application is tailored to a given job posting. Taking the measure to the data, we find that employers had a high willingness to pay for workers with more customized applications in the period before LLMs were introduced, but not after. To isolate and quantify the effect of LLMs’ disruption of signaling on equilibrium outcomes, we develop and estimate a structural model of labor market signaling, in which workers invest costly effort to produce noisy signals that predict their ability in equilibrium. We use the estimated model to simulate a counterfactual equilibrium in which LLMs render written applications useless in signaling workers’ ability. Without costly signaling, employers are less able to identify high-ability workers, causing the market to become significantly less meritocratic: compared to the pre-LLM equilibrium, workers in the top quintile of the ability distribution are hired 19% less often, workers in the bottom quintile are hired 14% more often.

SPEAKER

Prof. Thomas Jungbauer
Assistant Professor of Strategy & Business Economics
Johnson School of Management
Cornell University

ABSTRACT

This paper presents a model of employee poaching with asymmetric employer learning. Firms poach managers not only due to their track record but also for their personnel-specific information about workers. In equilibrium, more productive firms poach managers, whose compensation increases in their supply of and the demand for their information about workers. While poaching reassigns more able workers to more productive firms, efficiency does not obtain due to information frictions. Drawing on the universe of contracts in Brazil’s formal labor market, we test implications of our model and show their consistency with manager and worker movements and their compensation histories.

SPEAKER

Prof. Tom Lawrence
Professor of Strategic Management
Saïd Business School
University of Oxford

ABSTRACT

This study explores the role of imagined communities in shaping organizational trajectories of inclusion—longer-term movements in organizations’ efforts to foster inclusion. We draw on a qualitative comparative revisit study of three organizations that were considered disability inclusion champions at the beginning of the study. We found that organizational trajectories of inclusion moved in unexpected downward directions—in which disability inclusion was diluted, expelled, and compartmentalized. These shifts did not occur because of explicit opposition to inclusion or wholesale abandonment of diversity commitments, but because organizational changes reshaped how members understood the workforce as a collective, altering patterns of social relations, expectations of membership, and the distribution of responsibility for accommodating difference. We contribute to inclusion research by showing how inclusion can be a fragile, temporally unfolding organizational achievement shaped by material changes and dependent on the relational and moral capacities of imagined organizational communities. It contributes to the research on imagined communities by demonstrating how dynamically evolving workforce imaginaries mediate these changes and reshape the governance of difference and inequality.

SPEAKER

Mr. Eric Bruno Klemm
Ph.D. candidate in Economics
University College London

ABSTRACT

Older workers are often viewed as obstacles to innovation, suggesting that their exit allows firms to reallocate resources toward new capital and technology. We argue instead that older, experienced workers support both the continuity of current production and the capacity to integrate new technologies into existing operations. The key empirical challenge is that when retirements are anticipated, firms have time to transfer knowledge internally, making the productivity value of older workers difficult to observe. We address this by studying a 2014 German pension reform that unexpectedly lowered the early retirement age for experienced workers by up to 29 months, inducing a sudden and unanticipated loss of long-tenured employees. Firms exposed to the reform reduce capital accumulation, delay technology adoption, and experience subsequent declines in revenue and value added, consistent with the erosion of firm-specific human capital. To interpret these findings, we develop a stylized model in which older workers transfer uncodified, firm-specific knowledge that is essential for maintaining legacy capital and integrating new technologies into firms’ operations. The model predicts, and the data confirm, that unexpected retirements weaken firms’ ability to sustain production and slow the pace of technological upgrading.

SPEAKER

Prof. Wouter Dessein
Eli Ginzberg Professor of Finance and Economics
Columbia Business School
Columbia University

ABSTRACT

We examine how organizational flexibility influences investment decisions. We develop a novel measure of decentralized decision-making based on observed differences in the pricing of loans across subsidiaries of a banking group. We find that decentralized banks earn economically meaningful higher spreads on loans to borrowers with comparable characteristics. We provide evidence that this can be explained by them better exploiting lending opportunities arising from high, and urgent, demand. They do so by being more flexible in terms of the industries and countries they lend to, and by reacting more quickly to changes in aggregate lending conditions. Overall, the results suggest that a decentralized organization yields material benefits by facilitating more flexible decision-making.

SPEAKER

Prof. Jan B Heide
Professor
Wisconsin School of Business
University of Wisconsin-Madison

ABSTRACT

Firms are increasingly outsourcing marketing functions to offshore parties. In general, a decision to outsource must be accompanied by the deployment of governance mechanisms that regulate the “play of the game” with an exchange partner. Offshore outsourcing raises particular challenges, since governance mechanisms are deployed in institutional contexts with unique “rules of the game”. We develop a conceptual framework based on the premise that particular governance mechanisms have unique requirements for institutional support. Ultimately, relationship efficiency depends on the interactions between governance mechanisms (which regulate the “play of the game”) and the institutional environment (which represent the “rules of the game”). Based on an empirical study comprising primary and secondary data, we show that standard governance mechanisms like financial incentives, formal contracts, and informal norms have important boundary conditions tied to the institutional context in which they are deployed. Furthermore, these effects themselves have boundary conditions related to the characteristics of an offshore partner. Our findings extend existing governance research and suggest specific guidelines for managing offshore outsourcing relationships.

SPEAKER

Ms. Sijie Lin
Ph.D. candidate in Economics
Rotman School of Management
University of Toronto

ABSTRACT

What is the role of human input in AI-assisted production? Humans interact with generative AI through combinations of words called prompts. A key feature of human input is adaptation: users dynamically modify their prompts based on their understanding of AI. I empirically investigate two types of adaptation: (1) adaptation to new AI versions, referring to how people change their prompts in response to AI upgrades; (2) adaptation to outputs from previous prompts, referring to how people adjust their prompts iteratively to converge on desired outcomes. I study this adaptation using prompt-level data from Midjourney, a leading AI image generator. First, users adapt to AI upgrades by writing different words in their prompts. By submitting prompts written for the old version to the new AI and vice versa, I decompose the output shifts as arising from prompt changes (73%), AI changes (20%), and a residual (7%), implying complementarity between AI and human inputs. Second, prompts evolve within the creative process of an artwork. I estimate a structural model of the creative process using the sequential search framework. Counterfactual shows that without human adaptation, users need three times more prompts to achieve data-observed results. Both results highlight the importance of human judgment and adaptation in the creative process.