Working Papers

Credit Reallocation and Technological Change (with Luis Araujo, Raoul Minetti and Pierluigi Murro)

This paper studies the impact of the dynamic process of credit reallocation on aggregate innovative activities. To draw out theoretical predictions, we build a model with financial and matching frictions and investigate the consequences of lenders' credit reallocation decisions on borrowers' innovation choices. We show that an intensification of the credit reallocation process improves the matching between lenders and innovative firms but, overall, it disrupts innovation activities. Using a novel data set on bank balance sheets and the number of patents in Italian local markets (provinces) during a period of great economic growth and tighter banking regulation, we construct measures of credit reallocation and examine their effect on innovation. Consistent with the predictions of the model, we find that an increase in credit reallocation depresses innovative activity while aggregate credit growth helps to expand it.

Strategic Bank Consolidations: Intangible Capital Channel (with Suleyman Gozen and David Hong)

This paper examines how internally generated intangible capital shapes merger patterns and post-merger performance in the U.S. banking sector. We construct a novel measure of intangible capital using granular regulatory expense data and quantify assortative matching between acquirers and targets. Employing a difference-in-differences design with propensity score matching, we causally show that higher assortative matching in intangible capital leads to significant improvements in post-merger bank performance. We complement the empirical analysis with a dynamic search-theoretic model of bank mergers, demonstrating that strategic complementarities in intangibles give rise to assortative matching equilibria. Our findings provide new insights into banking consolidation.

Credit Market Dynamism, Bank Ownership, and Capital Misallocation (with Yogeshwar Bharat,  Suleyman Gozen, and David Hong)

We leverage the Reserve Bank of India’s 2006 Bank Authorization Policy as a quasi-natural experiment to causally examine the policy impact through the bank credit channel on capital misallocation at the district level. Using a difference-in-differences approach, the policy increases private-sector bank (PVB) branches by an average of 3.9 and expands net credit growth in industrial loans by 1.9 percentage points in underbanked districts. The underlying mechanism shows that the boost in PVB lending to ex-ante high MRPK industrial firms experienced a 60% reduction in MRPK after the policy relative to low MRPK firms located in underbanked districts. With the additional credit, these high-MRPK firms expand their capital base disproportionately to sales growth, resulting in a decline in capital misallocation in underbanked districts. We find nil policy effects on public-sector banks. Our evidence highlights the efficacy of financial reforms in developing economies and shows bank ownership characteristics are an important factor for policymakers.

Artificial Intelligence, Trade, and Firm Dynamics (with Suleyman Gozen and Pinar Gunes)

This paper investigates the role of artificial intelligence (AI) workers in shaping firm sales through trade channels. We provide novel empirical evidence on the association between the AI workforce and firm-level sales across the firm-size distribution, with a particular focus on domestic and foreign sales. Using a propensity score matching approach, we establish causal estimates of the impact of AI workers on firm sales. Our results show that the presence of AI workers leads to an approximately 18.6% increase in total sales. Furthermore, we find that this positive impact is even stronger for exporting firms, suggesting that AI can provide advantages in international markets. Examining the relationship across the firm-size distribution, we observe that the positive association between AI workers and sales becomes weaker as firm size and AI worker share increase, indicating potential diminishing returns to expanding the AI workforce beyond a certain point. Our event study analysis offers additional insights into trade channels and firm size heterogeneity, revealing that smaller firms benefit more from AI in domestic sales, while larger firms experience greater gains in foreign sales. To illustrate the underlying mechanisms behind our empirical findings, we develop an illustrative model that incorporates AI as a production input alongside production labor, with a focus on trade channels under firm heterogeneity. Our model delivers equilibrium characterizations consistent with our empirical insights, showing that lower AI adoption costs and reduced trade costs lead to increased AI adoption and higher productivity, particularly among exporting firms.

Intangible Capital, Heterogeneous Borrowing Types, and Firm Dynamics (with Suleyman Gozen and David Hong)

The rising importance of intangible capital presents a paradox: despite its critical role in innovation and productivity, aggregate U.S. productivity growth has slowed. This paper develops a firm-dynamics framework in which firms, depending on their reliance on intangible capital, face heterogeneous borrowing constraints—earnings-based and asset-based—that influence their ability to expand firm scope and productivity. We highlight a novel channel: firms more reliant on intangible capital are subject to earnings-based borrowing constraints, which tighten particularly during downturns, limiting their scope expansion and affecting firm cycle dynamics. This, in turn, contributes to the decline in aggregate productivity growth. We develop a model that incorporates firm-cycle behavior, including firm entry, where constraints shape investment and scope. This framework helps us understand how heterogeneous financial frictions influence firm scope and productivity through the lens of intangible capital.

Managerial Incentives and Intangibles: Rethinking the Firm Response to Tax-Induced Shocks, (with Mehmet T. Demir, Suleyman Gozen, and David Hong)

This paper investigates the joint role of managerial incentives and corporate taxation in shaping firm innovation and intangible capital accumulation through utilizing the 2017 U.S. Tax Cuts and Jobs Act (TCJA) as a laboratory for empirical analysis. Using a difference-in-differences design combined with propensity score matching and detailed firm-level data, we find that firms with higher pre-TCJA exposure to performance-based executive pay significantly increased R&D spending, patenting activity, and intangible investment following the reform, particularly among those experiencing an increase in marginal tax rates. Concurrently, these firms reallocated incentive pay away from top executives toward broader employee groups. The effects are most pronounced among growth-oriented firms, which internally financed their innovation surge. These findings highlight the joint role of tax exposure and managerial incentives in driving strategic investment decisions.