Is ESG the key to unlock debt financing during the COVID-19 pandemic? International evidence.

In this article, we examine whether stakeholder engagement impacts firms' ability to raise debt during the COVID-19 pandemic. Using firm-level data from 51 countries, we find that firms with greater stakeholder engagement obtain higher debt financing during the COVID-19 pandemic. This effect is more pronounced for riskier firms, highlighting the importance of maintaining relationships with stakeholders. Moreover, we find that stakeholder engagement facilitates higher debt financing for less asset-intensive firms and firms in emerging economies. Our empirical analysis reinforces the role of firms' stakeholder engagement in mitigating the adverse impact of economic shocks.

COVID-19 pandemic and debt financing by firms: Unravelling the channels.

The COVID-19-induced disruptions and the consequent government responses stretched the financial resources of firms. Recent studies document an increase in debt financing by firms during the pandemic. Using firm-level data from 61 countries, we deepen the understanding of the impact of the pandemic by examining the variation in loan and bond financing attributable to COVID-19-specific factors. Indicative of heightened precautionary needs, firms with higher pandemic exposure and those located in countries with stringent lockdowns have a higher propensity to raise debt. Furthermore, firms in industries less amenable to remote working also have a higher propensity to raise debt, but face higher financing costs compared to their peers. Reflective of opportunistic investment motives, firms that hold a relatively positive outlook have a greater likelihood of raising loan financing. The findings draw attention to the role of real-side factors and managerial motives that drive debt financing during a distress episode.

Financial fluctuations anchored to economic fundamentals: A mesoscopic network approach.

We demonstrate the existence of an empirical linkage between nominal financial networks and the underlying economic fundamentals, across countries. We construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and infer the relative importance of the sectors in the nominal network through measures of centrality and clustering algorithms. Eigenvector centrality robustly identifies the backbone of the minimum spanning tree defined on the return networks as well as the primary cluster in the multidimensional scaling map. We show that the sectors that are relatively large in size, defined with three metrics, viz., market capitalization, revenue and number of employees, constitute the core of the return networks, whereas the periphery is mostly populated by relatively smaller sectors. Therefore, sector-level nominal return dynamics are anchored to the real size effect, which ultimately shapes the optimal portfolios for risk management. Our results are reasonably robust across 27 countries of varying degrees of prosperity and across periods of market turbulence (2008-09) as well as periods of relative calmness (2012-13 and 2015-16).