Global Corporate Stress Tests—Impact of the COVID-19 Pandemic and Policy Responses

Abstract

Corporate sector vulnerabilities have been a central policy topic since the outset of the COVID-19 pandemic. In this paper, we analyze some 17,000 publicly listed firms in a sample of 24 countries, and assess their ability to withstand shocks induced by the pandemic to their liquidity, viability and solvency. For this purpose, we develop novel multi-factor sensitivity analysis and dynamic scenariobased stress test techniques to assess the impact of shocks on firm's ability to service their debt, and on their liquidity and solvency positions. Applying the October 2020 WEO baseline and adverse scenarios, we find that a large share of publicly-listed firms become vulnerable as a result of the pandemic shock and additional borrowing needs to overcome cash shortfalls are large, while firm behavioral responses and policies substantially help overcome the impact of the shock in the near term. Looking forward, while interest coverage ratios tend to improve over time after the initial shock as earnings recover in line with projected macroeconomic conditions, liquidity needs remain substantial in many firms across countries and across industries, while insolvencies rise over time in specific industries. To inform policy debates, we offer an approach to a triage between viable and unviable firms, and find that the needs for liquidity support of viable firms remain important beyond 2020, and that medium-term debt restructuring needs and liquidations of firms may be substantial in the medium-term.

The Financial Performance and Macrofinancial Implications of Large State-Owned Enterprises in Sub-Saharan Africa

“…While the debt-to-EBITDA ratio refers to the sustainability of the debt stock, another metric, the interest coverage ratio (ICR, defined as earnings before interest and taxes (EBIT) over net interest payments), assesses the viability of firms' debt service, with the critical value typically assumed to be in the range of 1.5 (Chow, 2015) to 1.0 (Tressel and Ding, 2021). In this study, only the debt stock metric is used because we do not have sufficient data coverage to compute the ICR (in a number of cases, reports only list EBITDA but not the necessary subcomponents, notably interest payments).…”

“…E.g.,Baum et al, 2021;Tressel and Ding, 2021;Wezel and Synak, 2021;Caceres et al, 2020; Chow, 2015. 24 Benchmarks derived from quartile distributions of four financial indicators for about 22,000 SOEs worldwide.…”

A koronavírus-járvány kezelése a külföldi tulajdonú magyarországi vállalatoknál

“…A világjárvány a világgazdaságban összességében igen negatívan érintette a vállalatokat, amint azt az összehasonlító (például Apedo-Amah és szerzőtársai [2020], Tressel-Ding [2021]) és az országtanulmányok (például Bartik és szerzőtársai [2020] az Egyesült Államok esetében, Shen és szerzőtársai [2020] Kína vagy Tourek [2021] Ruanda esetében) mutatják. Ugyanakkor a világjárvány okozta visszaesésnek a vállalatok teljesítményére gyakorolt hatása heterogén, különböző tényezőktől függ.…”

“…A világjárvány hatása szempontjából további befolyásoló tényezőt jelent a vállalat pénzügyi helyzete. Tressel-Ding [2021] megállapította, hogy mind a feltörekvő piacokon, mind néhány nagyobb és fejlett gazdaságban a sokk rövid távú hatása a cégek készpénzegyenlegére és a működési nyereségből a kamatkiadások kifizetésére való képességre igen súlyos, mivel az adóssággal rendelkező, nem pénzügyi vállalatok jelentős hányada likviditási nehézségekkel szembesül. Sok cég esetében ez az adósságállomány növekedését okozhatja.…”

Corporate Vulnerabilities in the Middle East, North Africa, and Pakistan in the Wake of COVID-19 Pandemic

“…Using a multi-year dynamic scenario-based stress testing model developed by Tressel and Ding (2021) and adapted to the region's context, we simulate over the years the evolution of individual firms' financial indicators, including profitability, liquidity, equity, and capacity to service debt. The stress testing model makes use of firmlevel panel data regressions where certain indicators are regressed on firm-level structural and time-varying factors, a macroeconomic variable (real GDP growth), and industry-and country-fixed effects.…”