Rare Disasters Research Articles

Corporate “dash-for-cash” amidst the Covid-19 Pandemic: Evidence from an Emerging Economy

This paper seeks to examine the impact of Covid-19 pandemic on corporate cash holding. The research collects data from 531 listed Vietnamese firms for the period 2020Q1-2021Q1. The data are analyzed using panel Fixed Effect model. Results show that corporations hoard more cash in response to the Covid-19 pandemic. This can be attributed to firms’ precautionary purpose and investment delays to a limited extent. Firms’ increased cash holdings are channeled through conservative payout policy. The results further reveal that hoarding cash amid the pandemic alleviates the adverse impacts of the Covid-19 outbreak on investment. Previous studies identified various determinants that affect firms’ cash holding. Our study adds another critical factor, a rare disaster, as an important determinant of corporate cash policy.

Which discount rate for sustainability?

There is a long-standing controversy about determining the discount rate at which companies should discount the long-term benefits of sustainability investments (e.g. for climate change mitigation and adaptation). While financial capital is discounted at the standard financial discount rate, this paper argues that companies should discount social and natural capital at the social discount rate. We add a risk parameter to the social discount rate to deal with the macroeconomic risk of rare disasters. Social discount rates are typically lower than financial discount rates. So, if applied, they should lead to higher investments in social and natural capital.

Disaster learning and aggregate investment

We extend a production-based asset pricing model by introducing learning about disaster risk. The information is not perfect, and Bayesian learning is adopted to update beliefs about the likelihood of rare disasters. We show that disaster learning reconciles key stylized facts about macroeconomic quantities and financial markets. For macroeconomic quantities, during the crisis, the decline in aggregate investments is much worse than that of output, whereas the decline in aggregate consumption is moderate relative to that of output. Additionally, the model endogenously features lower consumption volatility and higher investment volatility than that of output. For financial markets, belief updating over a rare disaster produces a higher equity premium, lower risk-free rate, and more volatile stock returns. Finally, we show that jump intensity uncertainty accounts for a substantial fraction of the total welfare cost of rare disasters.

Measuring macroeconomic tail risk

This paper estimates consumption and GDP tail risk dynamics over the long run (1900–2020). Our predictive approach circumvents the scarcity of large macroeconomic crises by exploiting a rich information set covering 42 countries. This flexible approach does not require asset price information and can thus serve as a benchmark to evaluate the empirical validity of rare disaster models. Our estimates covary with asset prices and forecast future stock returns, in line with theory. A calibration disciplined by our estimates supports the prediction that macroeconomic tail risk drives the equity premium.

Traditional seismic hazard analyses underestimate hazard levels when compared to observations from the 2023 Kahramanmaras earthquakes

A sequence of two major earthquakes, Mw7.8 Pazarcik, and Mw7.5 Elbistan, struck Southeastern Turkey in February 2023. The large magnitudes of the earthquakes and the short time between the two events raised questions about whether this sequence was an extremely rare disaster. Here, based on prior knowledge, we perform seismic hazard assessment for the region to estimate exceedance probabilities of observed magnitudes and ground motions. We discuss that many regional studies indicated the seismic gap in the area but with lower magnitude estimations. Observed ground motions generally agree with empirical models for the Pazarcik event. However, some records with high amplitudes exceed the highest observed amplitudes in an extensive database of shallow crustal earthquakes. We observe a notable trend of residuals for the Elbistan earthquake, leading to underestimation at long periods. We discuss potential advances in science for better characterization of such major earthquakes in the future.

Rare Disaster, Liquidity Provision, and Monetary-Fiscal Policy Choices

Rare Disaster, Liquidity Provision, and Monetary-Fiscal Policy Choices

Questions on Cost-Benefit Analysis and a Discussion of Present Answers: How Should One Determine the Social Discount Rate to Be Announced?

In the wake of the CBA used for public investment programming in France, new recommendations have been formulated for projects whose advantages (costs or benefits) are exposed to macroeconomic risks (correlation with GDP per capita), distinguishing between classically Gaussian hazards and “rare disasters” à la Barro. Taking rare disasters into account significantly modifies the value of the discount rate, along with the mathematical expectation of the advantages, and accentuates the distinction between procyclical and counter-cyclical projects.

Does the Interest Parity Puzzle Hold for Central and Eastern European Economies?

AbstractThis paper examines the uncovered interest parity puzzle in Central and Eastern European countries. Apart from investigating baseline UIP regressions, we check for structural breaks in this relationship, scrutinize deviations from the UIP, and employ different estimation methods and models augmented with various risk measures. Moreover, we offer several extensions to the common UIP testing that account for foreign-exchange interventions, the implied volatility of exchange rates, and the limited availability of data on direct measures of market expectations. The study shows that the choice of the reference currency matters for the outcome of the interest parity tests in the CEE economies. In particular, we demonstrate that inconsistencies between the results of the UIP tests vis-à-vis the euro and the US dollar that appear in CEE economies may be accounted for by the movements of the euro-dollar risk premium. This regularity has not been documented in previous studies. Additionally, we show that (a) the FX interventions in Czechia distorted the UIP, (b) the directly measured exchange rate expectations (granular survey data) in Poland do not seem to be informed by the UIP relationship, (c) the limited resilience of CEE economies to rare disasters may plausibly explain deviations from the UIP.

Rare disaster, economic growth, and disaster risk management with preferences for liquidity

AbstractThis paper examines the effect of preferences for liquidity on the relationship between disasters and growth along with disaster risk management. It further demonstrates that preferences for liquidity lead to less consumption. Moreover, from preferences for liquidity perspective, our model can potentially reconcile the conflicting predictions on the interaction between disasters and growth in the empirical findings. Finally, we find that preferences for liquidity cause policymakers to become more incentivized in mitigating disaster risk and lead them overestimate the welfare benefit of policy instruments.

Bone Cement Implantation Syndrome: A Rare Disaster Following Cemented Hip Arthroplasties-Clinical Considerations Supported by Case Studies.

Severe symptoms such as hypoxemia, hypotension, and unexpected loss of consciousness may develop during surgical interventions that use polymethyl methacrylate (PMMA), or as it is commonly known, bone cement. Physicians recognize this amalgam of clinical manifestations more and more as a distinct entity that bears the name of bone cement implantation syndrome (BCIS). Trauma cases, especially hip fractures, are seen to have a higher incidence of developing this complication compared to orthopedic elective ones. This research aims to present a detailed description of six severe BCIS cases in order to raise awareness and to emphasize its importance. Five of them had fatal outcomes, which demonstrate the necessity of future research on this topic, as little is known about it presently. In the Discussion section, a narrative overview from the scientific literature is performed on potential risk factors, prevention measures, and management strategies. The experience gathered through this case series may aid medical staff in the development of diagnostic and therapeutic protocols, thus improving safety when cemented surgical techniques are used on a high-risk group of patients.

Estimation of rare disaster concerns from option prices—An arbitrage‐free RND‐based smile construction approach

AbstractThis research addresses the estimation of measures of rare disaster concerns from option prices. We propose a new smile construction approach to obtain the required continuum of implied volatilities from discretely sampled observations that are affected by microstructure noise. We extrapolate implied volatilities of far out‐of‐the‐money options by modeling the tails of the risk‐neutral return distribution (RND) ensuring that option prices do not admit arbitrage. Our numerical analysis and empirical application show that the RND‐based approach consistently outperforms standard techniques. It substantially reduces estimation errors resulting in considerably higher estimates of the rare disaster concern index () when event risk is high.

Options on Interbank Rates and Implied Disaster Risk

The identification of disaster risk has remained a significant challenge due to the rarity of macroeconomic disasters. We show that the interbank market can help characterize the time variation in disaster risk. We propose a risk-based model in which macroeconomic disasters are likely to coincide with interbank market failure. Using interbank rates and their options, we estimate our model via MLE and filter out the short-run and long-run components of disaster risk. Our estimation results are independent of the stock market and serve as an external validity test of rare disaster models, which are typically calibrated to match stock moments.

Economic disasters and inequality: a note

This paper analyzes the dynamic effects of economic disasters, captured by cumulative decline in output of at least 10% over 1 or more years, on disposable income inequality of a sample of 99 countries over the annual period of 1960–2017. Based on impulse response functions derived from a robust local projections method, we find that economic disasters increase inequality by 4%, with the overall effect being statistically significant and highly persistent over a period of 20 years following the shock. When we repeat the analysis by categorizing the 99 countries based on income groups and regions, we find that the strongest effects are felt by high-income countries (8%), and in Europe, Central Asia and North America (16%) taken together, as primarily driven by ex-socialist economies. Though of lesser magnitude, statistically significant increases in inequality are also observed for low-, and upper-middle-income economies, and the regions of Latin America and Caribbean, Middle East and North Africa (MENA) and South Asia, and to some extent also for Sub-Saharan Africa. Our findings have important policy implications. Our findings suggest that the avoidance of economic crises is of paramount importance to ensure the sustainability of the welfare state, which in turn would allow for sound redistributive policies to reduce inequality, which can also help in indirectly reducing the negative impact of rare disasters on asset markets. In other words, our results have both economic and financial implications.

Firm-bank linkages and optimal policies after a rare disaster

We study optimal government support following a rare disaster that creates heterogeneous firm liquidity needs. Firms’ increase in debt reduces their output due to moral hazard. Banks are subject to a minimum capital requirement that limits deposit insurance costs upon bad aggregate shocks. Without government support, firms’ moral hazard and banks’ funding frictions reinforce each other amplifying output losses. Optimal support is implemented with firm-specific transfers combined with the provision of aggregate risk insurance through a capital requirement relaxation and a public preferred equity stake in banks. Our results shed light on suboptimality features in the actual policy responses to Covid-19 lockdowns.

Rare Disaster Events, Growth Volatility, and Financial Liberalization: International Evidence

Rare Disaster Events, Growth Volatility, and Financial Liberalization: International Evidence

Safe-haven properties of green bonds for industrial sectors (GICS) in the United States: Evidence from Covid-19 pandemic and Global Financial Crisis

The Covid-19 pandemic unfolds the vulnerability of financial markets at the time of rare disasters. To hedge the mean-dependent risk, investors rely upon traditional assets such as gold; however, the tail-dependent risk, especially during market turbulence, considerably dampened the hedging effectiveness. On the contrary, green bonds emphasize sustainable investment in the long term and have become an inevitable tool to hedge against financial risks, and climate risks, and rare disasters. Thus, this study explores the hedging and safe haven aspects of the bullish market of green bonds against bearish markets of industry sectors across the United States (U.S.) over the period of 1st January 2008 to 7th May 2021, including the Global Financial Crisis and the Covid-19 pandemic. The findings of cross-quantilogram analysis disclose that green bonds reap diversification benefits during overall market conditions as well as market turmoil, hence confirm the safe-haven behavior of green bonds. Furthermore, our results disclose that the potential role of investment in green bonds can reboot the economy without affecting low-carbon transition targets.

Robust leverage choice of hedge funds with rare disasters

We study the effects of hedge fund manager’s ambiguity aversion for jump and diffusion risks on the leverage policy under a high-water mark contract. We find that the jump risk has an inverted U-shaped effect on the leverage choice, which can be explained by the variance effect and skewness effect. Our result also indicates that diffusion ambiguity aversion has a larger negative impact on leverage than jump ambiguity aversion. Manager’s ambiguity aversion in jump risk amplifies the skewness effect when the price jump is positive. Our findings provide some insights into the risk taking strategy of hedge fund under ambiguity.

Global DSGE models

We introduce our GDSGE framework and a novel global solution method, called simultaneous transition and policy function iterations (STPFIs), for solving dynamic stochastic general equilibrium models. The framework encompasses many well-known incomplete markets models with highly nonlinear dynamics such as models of financial crises and models with rare disasters including the current COVID-19 pandemic. Using consistency equations, our method is most effective at solving models featuring endogenous state variables with implicit laws of motion such as wealth or consumption shares. Finally, we incorporate this method in an automated and publicly available toolbox that solves many important models in the aforementioned topics, and in many cases, more efficiently and/or accurately than their original algorithms.

Learning about Debt Crises

The European debt crisis presents a challenge to our understanding of the relationship between government bond yields and economic fundamentals. I argue that information frictions are an important missing element and support that claim with evidence on the evolution of GDP forecast errors after 2008. I build a quantitative model of sovereign default where output features rare disasters and agents learn about their realizations. Debt crises coincide with economic depressions and develop gradually while markets update their expectations about future income. Calibrated to the Portuguese economy, the model replicates the comovement of bond spreads and output before and after 2008. (JEL E23, E27, E32, E43, F34, H63)

Asset pricing with long-run disaster risk.

Traditional disaster models with time-varying disaster risk are not perfect in explaining asset returns. We redefine rare economic disasters and develop a novel disaster model with long-run disaster risk to match the asset return moments observed in the U.S. data. The difference from traditional disaster models is that our model contains the long-run disaster risk by treating the long-run ingredient of consumption growth as a function of time-varying disaster probability. Our model matches the U.S. data better than the traditional disaster model with time-varying disaster risk. This study uncovers an additional channel through which disaster risk affects asset returns and bridges the gap between long-run risk models and rare disaster models.