Using a market-indicator-based approach, this paper empirically examines whether the stability of the US and EU financial systems is affected by the digital finance revolution driven by BigTechs, FinTechs, and crypto-assets. These three sectors display different downside volatility profiles, with financial intermediaries being particularly sensitive to shocks from the crypto ecosystem only under extremely severe downturns, which are prevented in regulated equity markets. In that vein, we provide evidence that the Markets in Crypto Assets Regulation reduced financial systemic risk in EU. Overall, our empirical analysis shows that markets perceive the performance and riskiness of tech-driven companies and assets in differentiated ways, and that the transmission of shocks from digital finance ecosystems operates uniquely under varying conditions of systemic stress. Finally, we also document asymmetric spillover effects between advanced and emerging economies, with shock transmission from the US and EU to emerging markets being systematically stronger than in the reverse direction.

We use secondary corporate loan-market prices to construct a novel loan-market-based credit spread. This measure has considerable predictive power for economic activity across macroeconomic outcomes in both the U.S. and Europe and captures unique information not contained in public market credit spreads. Loan-market borrowers are compositionally different and particularly sensitive to supply-side frictions as well as financial frictions that emanate from their own balance sheets. This evidence highlights the joint role of financial intermediary and borrower balance-sheet frictions in understanding macroeconomic developments and enriches our understanding of which type of financial frictions matter for the economy.

We review an empirical literature that studies how political polarization affects financial decisions. We first discuss the degree of partisan segregation in finance and corporate America, the mechanisms through which partisanship may influence financial decisions, and the available data sources used to infer individuals’ partisan leanings. We then describe and discuss the empirical evidence. Our review suggests an economically large and often growing partisan gap in the financial decisions of households, corporate executives, and financial intermediaries. Partisan alignment between individuals explains team and financial relationship formation, with initial evidence suggesting that high levels of partisan homogeneity may be associated with economic costs. We conclude by proposing several promising directions for future research.

We propose a novel mechanism through which established firms contribute to the startup ecosystem: the allocation of R&D tax credits to startups via the M&A channel. We show that when established firms become eligible for R&D tax credits, they increase their R&D and M&A activity. In particular, they acquire more venture capital (VC)-backed startups, but not non-VC-backed firms. Moreover, the impact of R&D tax credits on firms’ R&D is increasing with their acquisition of VC-backed startups. The results suggest that established firms respond to R&D tax credits by acquiring startups rather than solely focusing on increasing their R&D intensity in-house. We also highlight evidence that startups do not appear to benefit from R&D tax credits directly, perhaps because they typically lack the taxable income necessary to directly benefit from the tax credits. In this context, established firms can play an intermediary role by acquiring startups and reallocating R&D tax credits, effectively relaxing the financial constraints faced by startups.

We use secondary corporate loan-market prices to construct a novel loan-market-based credit spread. This measure has considerable predictive power for economic activity across macroeconomic outcomes in both the U.S. and Europe and captures unique information not contained in public market credit spreads. Loan-market borrowers are compositionally different and particularly sensitive to supply-side frictions as well as financial frictions that emanate from their own balance sheets. This evidence highlights the joint role of financial intermediary and borrower balance-sheet frictions in understanding macroeconomic developments and enriches our understanding of which type of financial frictions matter for the economy.

Do prior lending relationships result in pass‐through savings (lower interest rates) for borrowers, or do they lock in higher costs for borrowers? Theoretical models suggest that when borrowers experience greater information asymmetry, higher switching costs, and limited access to capital markets, they become locked into higher costs from their existing lenders. Firms in Chapter 11 seeking debtor‐in‐possession (DIP) financing often fit this profile. We investigate the presence of lock‐in effects using a sample of 348 DIP loans. We account for endogeneity using the instrument variable (IV) approach and the Heckman selection model and find consistent evidence that prior lending relationship is associated with higher interest costs and the effect is more severe for stronger existing relationships. Our study provides direct evidence that prior lending relationships do create a lock‐in effect under certain circumstances, such as DIP financing.

Finding the proper balance between state and market is challenging. Especially in banking (Stiglitz, 1993). Banks in their function as financial intermediaries are risky and inherently prone to failure (Diamond and Dybvig, 1983; Diamond, 1984). But they provide services of vital importance to the economy in the form of payment services, credit supply for investments, inter-temporal liquidity transformation, or management of savings accounts. Consequently, the stability of the banking and financial sector is of public interest. In the least, the financial crisis was an unpleasant reminder to the industrialized world about the severe repercussions of unstable banking systems.

We examine the effect of finance on long-term economic growth using Bayesian model averaging to address model uncertainty in cross-country growth regressions. The literature largely focuses on financial indicators that assess the financial depth of banks and stock markets. We examine these indicators jointly with newly developed indicators that assess the stability and efficiency of financial markets. Once we subject the finance-growth regressions to model uncertainty, our results suggest that commonly used indicators of financial development are not robustly related to long-term growth. However, the findings from our global sample indicate that one newly developed indicator—the efficiency of financial intermediaries—is robustly related to long-term growth.