Financial Shocks Research Articles

Dynamic linkage between environmental segments of stock markets: the role of global risk factors

ABSTRACT This study evaluates the links between representative indices of companies with high environmental performance and the propensity of such indices to economic and financial shocks. Five indices, representing environmental segments and four global macroeconomic and financial variables, were analyzed over a thirteen-year period, which included various crisis moments, such as the sovereign debt crisis, the COVID-19 pandemic and the onset of the Russia/Ukraine conflict. Using dynamic and nonlinear models, our research reveals statistically significant and consistent relationships between the variables under investigation, particularly during periods of global financial and pandemic crises. The analysis revealed that the VIXCLS is the most influential global risk factor, with certain risk factors being influenced by environmental segments, particularly Alternative Energy. This influence can create conditions conducive to contagion risk and diminish the benefits of portfolio diversification. This study contributes to a deeper understanding of the connection between environmental investments and their vulnerability to significant global events and risks.

Decoding financial performance of US-listed entities: A sectoral exploration of input efficiency amid stochastic volatility

This study explores the complex relationship between firm efficiency and stochastic volatility, focusing on how firms utilise inputs to generate sales and the impact of financial shocks on efficiency levels. Utilising a dataset of 476 U.S. firms across 23 sectors from 2010 to 2022, it integrates stochastic volatility into efficiency analysis, treating volatility as an evolving, unobserved process diverging from traditional methods. The research classifies sectors into various efficiency performance categories based on their response to economic fluctuations. Findings show divergent patterns across sectors, with some exhibiting consistent efficiency and others facing erratic performance due to market and technological changes. This analysis provides valuable insights into sectoral adaptability and resilience in fluctuating economic conditions, offering strategic implications for managers and policymakers.

External financial and monetary policy shocks: Do they matter for Korean macroeconomy?

Given Korea's status as a small, open economy, it exhibits a pronounced sensitivity to external shocks. Consequently, this article seeks to elucidate the impact of external financial and monetary policy shocks on the fluctuation of critical macroeconomic variables within Korea. Employing Bayesian estimation alongside the impulse response function for empirical analysis, the findings reveal that external financial and monetary policy shocks precipitate declines in exports, output, employment, real wages, consumption, investment, and imports. Conversely, these shocks are associated with increases in both the price level and inflation, highlighting the multifaceted effects of external pressures on the domestic economic landscape. Further, through forecast error variance decomposition, this study demonstrates that, relative to shocks stemming from productivity, terms of trade, and real exchange rate variations, external financial and monetary policy shocks exert a considerably milder impact on the fluctuations of Korea's key macroeconomic variables. This insight suggests a potential area for enhancement in the existing Korean literature on this topic, advocating for the integration of these findings to enrich understanding and analysis. In summary, by delving into the nuanced effects of external shocks on Korea's economy, this article contributes valuable perspectives to the discourse, suggesting avenues for further research and policy formulation. The integration of these results into the broader body of Korean economic literature could significantly augment current understandings and interpretations of Korea's economic dynamics in the face of global financial and monetary turbulence.

Economic policy uncertainty and capital flows' tail risk in China

Since the financial crisis, uncertainty has been a focus of attention in the financial sector. As the two-way opening-up of China's financial market continues to accelerate, special attention must be paid to the risks and challenges arising from cross-border capital flows to maintain financial market stability in China. This study uses predictive quantile regression and skewed t-distribution fitting method to examine the impact of Economic Policy Uncertainty (EPU) on the full probability distribution and tail risks of capital flows. Additionally, we apply the “Capital Flows at Risk (CFaR)” analysis framework from the new paradigm of macroeconomic research to the situation in China, to study the impact of EPU on CFaR. We find that EPU significantly affects the predictive distribution of capital flows. When EPU is rising, the downside risk of capital flows, that is, the left-tail risk of capital flows, will increase; however, when EPU is declining, the upside risk of capital flows, that is, the right-tail risk of capital flows, will increase. In recent years, the scale of China's CFaR has shown a fluctuating upward trend, and EPU has increased the scale of CFaR in the country. This study is significant for stabilizing international capital flows and preventing and defusing the external financial shocks of cross-border capital inflows and outflows.

Dividend Taxation and Financial Business Cycles

We examine the interactions between different dividend tax systems and financial shocks in a dynamic stochastic general equilibrium (DSGE) model with an occasionally-binding investment credit limit. We show that dividend taxes largely determine the collateral value of assets, thereby occasionally distorting investment decisions and altering the propagation of financial shocks. Permanently lower dividend taxes dampen financially-driven business cycles in a state-contingent fashion. They also help explain substantial macroeconomic asymmetries following equally-sized expansionary and contractionary financial shocks.

International financial stress spillovers during times of unconventional monetary policy interventions

In this study, we estimate a Bayesian global vector autoregressive model to uncover the effects of financial stress on output growth, inflation, and interest rates, accounting for several advanced and emerging economies for a period spanning from February 2008 until May 2022. We construct a financial stress index applicable to all countries, tracking periods of financial instability in the economies, and employ shadow short rates as a proxy measure of unconventional monetary policy. This study provides strong evidence that financial stress shocks are transmitted abroad as financial stress increases in all the countries in the sample. Our results also show that financial stress innovation generates important domestic and cross-border output, inflation, and interest rate spillovers for several countries. Additionally, we identify the active role of the financial and bank credit channels in the transmission of shocks across financial systems, while macroprudential policy can intercept the propagation of the shock. Our results carry policy implications for monetary and regulatory authorities.

Financial shock transmission in China's banking and housing sectors: A network analysis

Rising housing prices in China present a significant risk to financial and economic stability. Our study investigates this "gray rhino" risk by analyzing the financial shock transmission network, using a novel high-dimensional network approach applied to data from 45 real estate firms and 15 banks from 2011 to 2023. We discover that the network's connectedness is predominantly short-term and internal to each sector, with weaker inter-sectoral links. Key macroeconomic indicators, notably monetary policy uncertainty, and inflation, significantly drive this connectedness. Our results indicate that, despite concerns, China's real estate risk remains within manageable bounds, offering critical insights for market stakeholders.

Information warfare: Analyzing COVID-19 news and its economic fallout in the US

By separating the ‘good news’ from the ‘bad news,’ we analyze the asymmetric effects of the infodemic and market emotions on the US weekly economic activity index (WEI) during COVID-19. The ‘hot stove effect’ and complicated, asymmetric, and time-varying coherence structures are present when we use the nonlinear autoregressive distributed lag and wavelet coherence methods. Our findings contrast existing literature based on the pandemic’s symmetric impacts, which claim that the economy was negatively affected by non-pharmaceutical actions and that the severity of COVID-19 was the cause of the negative economic and financial shocks. We also discovered that while ‘good news’ has strong and favorable effects on WEI, ‘bad news’ has little to no impact. Furthermore, policymakers react to ‘bad news’ more slowly than they do to ‘good news.’ Therefore, to affect the representative agent’s behavior and ensure an effective response to pandemic occurrences, policymakers should distinguish between deterioration (bad news) and improvements (good news) in shocks.

Energy efficiency, technological innovation, and financial development-based EKC premise: Fresh asymmetric insights from developing Asian regions

This study analyses the impact of energy efficiency, technological innovation, and financial development on carbon dioxide emissions in developing Asian regions. It considers both positive and negative effects and incorporates the concept of the environmental kuznets curve (EKC). Utilizing data from fifteen developing Asian economies from 1995 to 2021, the study employs a dynamic panel data approach to examine the relationship between the variables. More specifically, the study utilizes econometric techniques, such as the error correction model (ECM), to consider both short-term and long-term dynamics and estimate the size and direction of the effects. In addition, the study incorporates squared-term financial development variables to measure the non-linear effects and examine the existence of an inverted U-shaped EKC pattern. The findings indicate that when financial development experiences positive shocks, it tends to align with the U-shaped premise of the EKC. On the other hand, when financial development experiences negative shocks, it tends to result in environment-friendly outcomes. In addition, the study analyses the varying effects of fossil fuels and renewable energy sources during periods of both positive and negative shocks. Technological innovation is also assessed for its impact on environmental sustainability. In general, the approach integrates econometric modeling and theoretical frameworks to offer insights into the intricate relationship between energy efficiency, financial development, technological innovation, and CO2 emissions in developing Asian economies.

Describing financial crisis propagation through epidemic modelling on multiplex networks

This paper proposes a novel framework for modelling the spread of financial crises in complex networks, combining financial data, Extreme Value Theory and an epidemiological transmission model. We accommodate two key aspects of contagion modelling: fundamentals-based contagion, where the transmission is due to direct financial linkages, and pure contagion, where a crisis might trigger additional crises due to global effects. We use stock price, geographical location and economic sector data for a set of 398 companies to construct multiplex networks of four layers, on which a susceptible-infected-recovered transmission model is defined, in order to model the spread of financial shocks between companies by accounting for their interconnected nature. By utilizing stock price data for the 2008 and 2020 financial crises, we investigate and assess the effectiveness of our model in forecasting the propagation of financial shocks through the network, where a shock is detected by measuring stock price volatility. The results suggest that the proposed framework is effective in predicting the spread of financial crises. Our findings demonstrate the significance of each layer of the multiplex network structure, which differentiates between various transmission pathways, for predicting the number of affected companies, as well as for company-, sector- or location-specific predictions.

Influence of scissors difference of money growth rate on stock market return in different financial cycles

We use TVP-VAR model to study the relationship between the scissors difference of money growth and stock returns in different financial cycles from February 2001 to October 2022. The results show that the scissors difference of money growth rate has a positive effect on the stock return rate that lags behind for one month, but a negative effect on the stock return rate that lags behind for three months. The impact on the half-year lag is almost negligible. In addition, during the financial cycle contraction, the scissors difference of money growth rate has a greater impact on stock returns; In the period of financial cycle expansion, its impact is small. During the financial shock, its impact is between the first two.

Business Models of Ukrainian Banks: the Impact of the Revolution of Dignity, the COVID–19 Pandemic, and Russia’s Military Aggression

The purpose of the article is to identify key banking activity models in Ukraine and show how they changed under the influence of the Revolution of Dignity, the COVID–19 pandemic, and the imposition of martial law. The proposed method uses cluster analysis of the main indicators for banking activity (concerning assets, liabilities and income) based on Ward’s agglomerative hierarchical clustering algorithm and the Tau index in the NbClust package as the criterion for evaluating the optimal number of clusters. The research covers all Ukrainian banks, spanning the period 2013–2022. In 2014 (after the Revolution of Dignity), the actions of the National Bank of Ukraine (NBU) had a positive impact on the models of Ukrainian banks: there was no opaque model of banks and banking models became more transparent and more resilient to financial shocks. Between 2021 and 2022, five banking models were identified: universal banks, wholesale funding banks, corporate‑investment banks, retail banks, and commission banks. The negative impact of COVID–19 on the Ukrainian economy was reflected in all banking models by the following: (1) a significant increase in the role of securities in assets, which was caused by a decrease in lending due to an increase in their riskiness; (2) the use of central bank funds to liabilities management, which was evidence of a deterioration in financing conditions in the deposit market. The following main changes in Ukraine’s banking system at the end of 2022 (during the war) were identified: (1) a decrease in the number of banks that mainly use funds from the NBU to support their activities; (2) the closure of only four banks by the NBU (including two with majority shareholders from Russia) during the year; (3) an increase in the share of the non‑government debt securities portfolio in banks’ assets; (4) declines in ROE and ROA for all banking models during the war, and three banking models became unprofitable; (5) the significantly higher share of non‑performing loans in the credit portfolio for all banking models, especially for the retail banking model. The value‑added of this research is the analysis of how banking models in Ukraine have changed at the micro level (reflected in the financial statements) inter alia in wartime.

Max Share Identification of Multiple Shocks: An Application to Uncertainty and Financial Conditions

We generalize the Max Share approach to allow for simultaneous identification of a multiplicity of shocks in a Structural Vector Autoregression. Our machinery therefore overcomes the well-known drawbacks that individually identified shocks (i) tend to be correlated to each other or (ii) can be separated under orthogonalizations with weak economic ground. We show that identification corresponds to solving a nontrivial optimization problem. We provide conditions for non-emptiness of solutions and point-identification, and Bayesian algorithms for estimation and inference. We use the approach to study the effects of uncertainty and financial shocks, allowing for the possibility that the former responds contemporaneously to other shocks, distinguishing macroeconomic from financial uncertainty and credit supply shocks. Using U.S. data we find that financial uncertainty mimics a demand shock, while the interpretation of macro uncertainty is more mixed. Furthermore, variation in uncertainty partially represents the endogenous response of uncertainty to other shocks.

The Effect of Crises on Fiscal and Political Re-Centralization

Economic stability plays a crucial role in any fiscal and political decentralization process. In the face of financial and economic shocks, when revenues and expenditures are reduced, countries may decide to gather resources at the central level creating a re-centralization scenario or may take away devolved powers and centralize political institutions. Using data from 75 countries, we examine the effects of the economic crisis on fiscal and political decentralization. We find that several types of crises lead to fiscal re-centralization. However, in the case of domestic borrowing crises, the effect is further revenue decentralization, probably reflecting the central government's willingness to empower sub-national governments to avoid similar crises. In addition, we explore the impact of the economic crisis on political decentralization and find that they are concordant with the fiscal decentralization effects, suggesting an alignment of the impact along political and fiscal dimensions of subnational autonomy. We also explore whether the economic crises trigger more permanent rather than just transitory changes in the level of decentralization, and we generally find more long-lasting effects in the case of fiscal decentralization measured from the expenditure side. This pattern is apparent in the cases of inflation and banking crises and is less precise but still present in the cases of currency and external debt crises. The main results are robust to different specifications, estimation methods, and the measurement of decentralization.

Bank’s strategic interaction, adverse price dynamics and systemic liquidity risk

AbstractWhen a widespread funding shock hits the banking system, banks may engage in strategic behaviour to deal with funding shortages by a pre-emptive disposal of assets. Alternatively, they may adopt a more cautious strategy to mitigate price reactions, thereby distributing the assets sales into smaller portions over time. We model banks’ optimal behaviour using standard optimisation techniques and show that an equilibrium always exits in a stylised setting. A numerical analysis to approximate the equilibrium supplements the theoretical part. The implementation delivers two liquidity measures for the German banking system: the Systemic Liquidity Buffer and the Systemic Liquidity Shortfall. These measures are more informative about systemic liquidity risk than regulatory liquidity measures, such as the LCR, because they model adverse, nonlinear price dynamics in a more realistic way. Our approach is applied to different stress scenarios.

Effect of Financial Frictions on Monetary Policy Conduct: A Comparative Analysis of DSGE Models with and without Financial Frictions

In this study, we explored the impact of bank leverage and financial frictions on the transmission of real and financial shocks. Two new Keynesian dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, were employed in the context of the Tunisian economy. In the analysis, we considered three types of shocks—productivity, monetary, and adverse bank capital shocks. The findings reveal that, in the model with financial frictions, the response of macroeconomic and financial variables to demand and supply shocks was more pronounced than in the baseline model, where frictions primarily exist at the borrower level. In this study, we underscored the significance of financial shocks, particularly negative bank capital shocks, in triggering substantial macroeconomic and financial fluctuations, especially when banks operate with higher leverage ratios. Additionally, the inclusion of financial frictions in the DSGE model enhanced its ability to capture the empirical features of real and financial shocks, providing valuable insights for effective monetary policymaking. The results provide foundational insights for Tunisian policymakers to assess the impact of financial frictions in the context of the Tunisian economy. This is significant for the Central Bank of Tunisia, which has not yet adopted a specific DSGE model. Therefore, through our analysis, we determined the amplificatory role of financial frictions in the dynamics of macroeconomic and financial variables in Tunisia and examined the main transmission channels of shock propagation.

CORPORATE EARNINGS ANNOUNCEMENTS AND ECONOMIC ACTIVITY

AbstractAre corporate earnings (CE) announcements important for economic activity? We address this question using a novel identification method that combines the valuable information from CE announcements with the heteroscedasticity of shocks experienced on these particular days. Our results demonstrate that CE announcements have a significant impact on the macroeconomy, exhibiting dynamics similar to traditional financial disruptions. We establish that CE announcements' shocks can be classified as financial shocks, highlighting their critical role in the financial system.

Resilience in a noisy urban system

The ability of cities to recuperate from disturbances and return to their evolutionary pathways depends, first and foremost, on the type of damage that the shock created. But in addition, it depends on how information is transmitted in the urban system and on how noise filters distort the information that reaches economic agents. So long as the transmission of information does not disturb the functioning of the urban economy, shocks do not prevent the return to the long‐run evolutionary paths. We study the migration decisions of agents, following information that they receive using an agent‐based model of endogenous growth in a closed urban system. These decisions affect the spread of innovative ideas, of innovations, and the birth rate of new firms. The aggregate reactions of agents to shocks can affect the resilience of the entire urban system and of individual cities, sometimes allowing a return to the same domain, and sometimes driving the system and parts of its constituents to another regime of behavior. We analyze the repercussion of shocks on the resilience of urban systems by considering how noise in the transmission of information affects the decisions of agents at various times and locations. The conclusions are that, while information noise is a burden that constantly and systematically hinders the economic potential of the system, financial shocks reshuffle resources causing a fundamental change in the urban system trajectories.

Statistical identification in panel structural vector autoregressive models based on independence criteria

SummaryThis paper introduces a novel panel approach to structural vector autoregressive analysis. For identification, we impose independence of structural innovations at the pooled level. We demonstrate robustness of the method under cross‐sectional correlation and heterogeneity through simulation experiments. In an empirical application on monetary policy transmission in the Euro area, we find that bond spreads rise significantly after an unexpected monetary tightening. Furthermore, the central bank responds to offset effects of adverse financial shocks. Additionally, we document sizable heterogeneity in country‐specific output responses.

China's risk contagion using the mixed-frequency macro-financial network

We explore and compare the fundamental laws of risk contagion under different shocks during the global financial crisis and COVID-19 pandemic periods. Using the daily returns of financial market indices and the monthly growth rates of macroeconomic data for two periods, from January 1, 2003, to December 31, 2010, and from January 1, 2015, to December 31, 2021, we construct a macro-financial network with the mixed-frequency vector autoregression (MF-VAR) method to produce well-defined measures of intra-system and cross-system risk contagion. We investigate the differences in risk contagion under different types of major events using an event study model. The empirical results show that the financial system is the center of risk contagion. Regarding the direction of the cross-system risk contagion, the risk contagion from the financial to the macroeconomic system dominates the contagion in the opposite direction. The impacts of financial and pandemic shocks on the macro-financial risk contagion differ significantly. Importantly, both investor sentiment and consumer confidence mediate these impacts, providing useful insights into the prevention of risk contagion.