The influence of external institutional environments on the internal functioning of business groups remains a critical yet underexplored area of research. In this paper, we focus on China's pro-market judicial reforms and examine how these reforms affect internal product and service transactions within business groups, finding that such reforms significantly reduce intra-group transactions. We further demonstrate that this decline reflects a strategic substitution toward external market transactions rather than an overall contraction in firm operations, and that the effect is not driven by managerial self-dealing but aligns with institutional voids theory. The effect is particularly pronounced in regions with underdeveloped product markets and weaker informal institutions, and in firms with lower reputations and stronger political connections. Moreover, our results hold consistently across various transaction types, whether seller- or buyer-initiated, service- or goods-related, and remain robust across alternative regression models, explanations, and regardless of the geographic proximity of group firms. These findings contribute to understanding the role of internal transactions within business groups in addressing institutional voids and add to the broader literature on how business groups emerge and adapt in response to gaps in institutional frameworks.

Using the Troubled Asset Relief Program (TARP) as a laboratory, this paper examines the impacts of bank bailouts on bank-dependent clients. We find that large TARP recipient banks reduce credit supply to dependent borrowers in the post-TARP period. A large fraction of credit supply reduction is due to regulatory uncertainty on account of an increased likelihood of fines. Liquidity hoarding by TARP banks also drives part of the reduction in credit supply. Relationship borrowers experience a valuation loss around the announcements of their main banks’ TARP approvals consistent with a credit supply reduction.

This paper explores how the emergence of generative artificial intelligence is reshaping the information environment in capital markets. Leveraging an unexpected ban on ChatGPT in Italy, we examine its impact on the information processing capabilities of market participants. We employ metrics for AI-generated text detection to show that the ban coincides with decreased AI usage by domestic financial analysts and fewer earnings forecasts issued relative to foreign analysts covering the same firm. The negative effects are more pronounced among analysts whose pre-ban reports are more consistent with AI use or analysts with a technical background. The ban also diminishes forecast accuracy, increases reliance on industry-specific information, and reduces information efficiency. Furthermore, investor reactions to earnings announcements become more pronounced, and bid–ask spreads widen, reflecting lower market efficiency.