Negative Shocks Research Articles

Geopolitical Risk Versus Supply- and Demand-Induced Oil Shocks

Amid ongoing geopolitical events and their associated impact on energy markets, this study probes into the predictive capability of geopolitical risk (GPR) for various components of oil shocks. It also evaluates whether incorporating GPR in oil shock-model improves the forecast accuracy of global oil shocks, focusing exclusively on out-of-sample analysis. The findings indicate that (i) GPR induces a negative shock to oil supply, (ii) GPR generates a positive shock to oil consumption demand, and (iii) GPR causes a negative shock to oil inventory demand. These predictive effects are consistent across different oil shock dynamics and at different forecasting horizons, underscoring the significance of integrating GPR into oil shock models to enhance their accuracy and reliability.

Contagion from crypto exchange hacks: Wealth effect or portfolio rebalancing?

ABSTRACT This study explores the contagion mechanism from the cryptocurrency market to stock markets of 30 countries with the highest Bitcoin trading volumes, focusing on cyberattacks targeting cryptocurrency exchanges. We identify investor-induced contagion through the wealth effect as the primary transmission channel, which intensifies over time. In contrast, contagion driven by portfolio rebalancing, particularly evident in Asian markets, tends to gradually weaken. The wealth effect is initially amplified during periods of consecutive cyberattacks, but this impact diminishes as investors gradually adapt to repeated negative shocks. Individual cyberattacks do not significantly increase the co-exceedance probability of stock returns, but consecutive attacks within one week significantly amplify it.

Unemployment and Prosocial Engagement: Behavior Changes During the COVID-19 Pandemic

Successive social shocks have reinforced unemployment as a persistent issue, yet its impact on prosocial engagement remains underexplored. This study examines the relationship between job loss and prosocial behaviors, specifically volunteering and donating participation, hypothesizing that short-term unemployment acts as a negative personal shock with heterogeneous effects depending on individuals’ economic resources. Using nationally representative survey data from the United States collected during the COVID-19 pandemic, we employ propensity score weighting enhanced by a machine learning approach to address potential confounders. Our findings indicate that unemployment is associated with reduced formal volunteering participation among lower-income individuals and decreased participation in donating among higher-income individuals. However, we find no significant relationship between unemployment and informal volunteering. Furthermore, our analysis suggests that conventional methods, which fail to adequately control for confounders, tend to underestimate the negative impact of unemployment on prosocial behaviors.

Stock market price dynamics in Africa: evidence from 14 countries

PurposeThis paper deals with the stock market prices in Africa. In particular, we focus on data from 14 African countries that have stock exchanges with a market capitalisation of more than US$1bn also capturing stock market dynamics during the COVID-19 pandemic.Design/methodology/approachThe methodology is based on the concept of fractional integration that indicates that the number of differences to be taken in a series to render it stationary I(0) may be a fractional value.FindingsAssuming a white noise process, only the South African stock market displays transitory shocks. Allowing for autocorrelation, the time trend is statistically significant in four countries: Namibia, South Africa, Tunisia and Zimbabwe, although mean reversion is found in two countries: Morocco and South Africa. These two countries are the ones where the random walk can be rejected and thus are informationally inefficient. There is one country (Rwanda) with an estimated value of d above 1, while the unit root null hypothesis cannot be rejected in the remaining countries, implying that in all of them, other than Morocco and South Africa, the random walk hypothesis cannot be rejected.Research limitations/implicationsA limitation of this work is the number of countries examined, 14, due to the lack of available data. Dealing with the methodology, a limitation is also the linear nature of the trend structure examined, which may be extended to non-linear approaches.Practical implicationsThe practical implication is the mean-reverting nature of some of the series examined, implying that no strong measures should be adopted in these cases if exogenous negative shocks occur.Social implicationsThe academia and also practitioners can be interested in the present work, in particular in relation to the mean-reverting nature of the series and the efficient market hypothesis.Originality/valueThe originality in this work comes from the use of fractional integration, a methodology that is not very usual in the analysis of time series data.

THE IMPACT OF COVID 19 PANDEMIC ON THE TOURISM AND TRANSPORTATION SECTORS: EVIDENCE FROM BORSA ISTANBUL

The Covid-19 pandemic is recognized as one of the most important pandemics of the last century and has led to a global recession and decline, affecting all sectors in different ways. In this study, volatility spillovers between variables are analyzed. In this context, Covid daily case count, volatility spillovers between Borsa Istanbul tourism and transportation indices are examined with the EGARCH model using daily data covering the period 15 March 2020- 31 May 2022. According to the results of the conditional variance equation derived from the EGARCH model, it is determined that there is a volatility spillover from the Covid variable to the tourism and transport indices, but this volatility interaction is not asymmetric and positive and negative shocks do not have any effect on the volatility of these indices.

The impact of climate policy uncertainty on agricultural investments

Purpose: The agricultural sector is strategically important for sustainable development and food security. However, climate change and the increasing physical and political uncertainties that come with it put investments in this sector at risk. This study examines the relationship between climate policy uncertainty and agricultural investments in the USA from 1995-2022. Design/Methodology/Approach: Symmetric and asymmetric causality tests, as well as the Nonlinear ARDL method are used to analyze the relationships between variables. Nonlinear methods allow us to measure asymmetric effects on the dependent variable by evaluating the positive and negative changes of the explanatory variables separately. Findings: No symmetric causality relationship is found between the variables. However, there is a statistically significant asymmetric causality from the positive shock of climate policy uncertainty to the negative shock of agricultural investments. The results of the NARDL model robust this finding. Accordingly, increases in climate policy uncertainty reduce agricultural investments in the long run. Originality/Value: This study fills the gap in the literature by examining the impact of climate policy uncertainty on investments in the agricultural sector. This provides a new perspective to understand the long-term consequences of this relationship in a highly climate-sensitive area such as the agricultural sector.

Asymmetric Relationship between Oil Prices, Agricultural Production, and Industrial Production in Kazakhstan: Application of the NARDL Method

Two important factors contributing to oil revenues in Kazakhstan are the agricultural and industrial production sectors. This study examines the asymmetric effects of variability in these sectors on oil revenues. The analysis was conducted using the Nonlinear Autoregressive Distributed Lags (NARDL) model. In this model, oil revenues are represented as a ratio of oil revenues to GDP, while industrial and agricultural productions are represented by the industrial production index and the agricultural production index, respectively. The asymmetric effect refers to the differing impacts that positive or negative shocks in industrial or agricultural production have on oil revenues. Using annual data from 1992 to 2023, the study found that industrial production had statistically significant effects on oil revenues in the short term; however, this effect did not persist in the long term. In contrast, agricultural production demonstrated significant effects on oil revenues in both the short and long term, with notable seasonal differences in the impacts of short-term positive and negative shocks. Additionally, the error correction model indicated that both production sectors had asymmetric effects that led to deviations from expected oil revenues. In conclusion, the findings of this research highlight the significant role that production sectors play in explaining fluctuations in oil revenues.

Energy-Related Uncertainty and Tourism Stock Markets: New Insights from Time-Varying Relationship with TVP- VAR Approach

In this study, a time-varying parameter vector autoregressive (TVP-VAR) model is estimated to examine the effects of energy-related uncertainty, geopolitical risk and global economic activity on tourism stock prices in the United States (US) over the period February 1996-September 2022. The time-varying responses reveal that tourism stocks are negatively affected by energy-related uncertainty, particularly during financial crisis and COVID-19. Moreover, geopolitical risk shocks also negatively influence tourism stocks. Global economic activity exhibits both positive and negative shocks in tourism stocks. The results highlight the importance of considering sector-specific dynamics of energy-related uncertainty on tourism stocks in US.

The Symmetric and Asymmetric Effects of Climate Change and Carbon Dioxide Emissions on Crop Production in Tunisia

Agriculture remains a cornerstone of the Tunisian economy, accounting for over 12% of the country’s GDP and providing employment for more than 14% of the labor force in 2022 (WDI, 2023). However, the sector is increasingly vulnerable to climate change particularly variations in temperature and precipitation as well as environmental pressures such as air pollution, all of which can harm crops, vegetation, and forest resources. This study explored the influence of climate change and air pollution on Tunisia’s agricultural sector, employing both the ARDL and NARDL models to examine the effects of temperature, precipitation, and CO2 emissions on crop production over the period 1996-2022. The findings reveal significant short- and long-term relationships among the studied variables. In the short term, CO2 emissions were associated with a reduction in agricultural productivity, though this relationship was not statistically significant. In contrast, the long-term results demonstrate a substantial negative impact of environmental degradation on the crop production index. The analysis further shows that water productivity, fertilizer usage, and male employment in agriculture contribute positively to long-term agricultural output. Conversely, female employment in agriculture appears to have a negative impact on crop production over the same period. Additionally, while variables such as arable land, average temperature, and precipitation exhibit positive effects on crop production, these relationships were not statistically significant. The study also highlights the asymmetric effects of climate change and CO2 emissions, where positive and negative shocks exert varying degrees of influence on agricultural output in Tunisia. These results emphasize the crucial role of natural resources, particularly water productivity, as well as the importance of human capital in enhancing agricultural development. Notably, to the best of the author’s knowledge, this research is the first to simultaneously investigate both the symmetrical and asymmetrical dynamic interactions between climate change, carbon emissions, and crop production in Tunisia using ARDL and NARDL cointegration frameworks.

Exploring Stock Returns Volatility of Select NSE – Listed Diversified Sector Companies: An Empirical Study

Global financial meltdowns have massive shock on different sectors as well as on scripts returns. The study empirically examines the stock returns volatility of selected NSE-listed diversified sector companies to assess their risk exposure and market behavior based on time series dataset taking into consideration of daily closing adjusted stock price from 2001-02 to 2015-16. The application of GARCH, T-GARCH and E-GARCH models provides the evidence of the persistence of time varying asymmetric volatility. The findings reveal significant variations in stock return volatility among diversified firms, influenced by market conditions, and firm-specific factors due to recent global financial meltdown which is originated from US sub-prime crisis. The study also explores the effect captured by different models show that negative shocks have significant effect on conditional volatility.

Do cash transfers mitigate risks and crowd out informal insurance? Evidence from a randomized experiment in the Philippines

This study evaluates the impact of a Conditional Cash Transfer (CCT) program on risk mitigation and informal insurance systems among poor Filipino households during exposure to negative income shocks. CCTs can reduce dependence on informal arrangements by increasing beneficiaries' income, making them more resilient to shocks and less reliant on informal networks. Conversely, it can reinforce informal arrangements by enhancing the financial capacity of eligible households, enabling them to lend money to others during shocks. Theoretical outcomes can thus be ambiguous. Using a sample of 1,415 households from 130 village clusters randomly assigned to treatment and control groups, intention-to-treat (ITT) estimates suggest that CCT has unintended consequences on risk mitigation and positive spillover effects on the informal system. Beneficiaries’ medical expenses and borrowings from the informal system increased during shocks. Additionally, increased lending support was observed among ineligible households in treatment areas, along with a decrease in their borrowings from the informal system.

Young Children and Parents’ Labor Supply During COVID-19

We study the COVID-19 pandemic's effects on the labor supply of parents with young children. Using the monthly Current Population Survey, and following a pre-analysis plan, we use three variations of difference-in-differences to compare workers with childcare needs to those without. The first compares parents with young children and those without young children, while the second and third rely on the presence of someone who could provide childcare in the household: a teenager in one and a grandparent in the other. We analyze three outcomes: whether parents were "at work" (not sick, on vacation, or otherwise away from his or her job); whether they were employed; and hours worked. Contrary to expectation, we find the labor supply of parents with young children was not negatively affected by the COVID-19 pandemic. Instead, some evidence suggests they were more likely to be working after the pandemic unfolded. For the outcomes of being at work and employed, our results are not systematically different for men and women, but some findings suggest women with young children worked almost an hour longer per week than those without. These results suggest that factors like employers allowing employees to work at home and informal sources of childcare aided parents in avoiding negative shocks to their labor supply during the pandemic.

Nonlinear growth and cyclical effects of energy: evidence from Fiji with a Fourier NARDL model

ABSTRACT This study examines the growth and cyclical effects of energy using annual data from Fiji over the period 1980 to 2021. Drawing insights from the post-Keynesian demand-led growth framework, the study finds negative energy shocks reduce output more strongly in expansions compared to how positive energy shocks increase output in recessions. Positive energy shocks and negative energy shocks do not impact GDP in expansions, and recessions, respectively. The results are robust to alternative cyclical decomposition filters and structural breaks through the Fourier NARDL model. Moreover, the Fourier-based Granger causality test results indicate unidirectional causality from energy to growth. The results underscore the role of energy to support growth in expansion, albeit highlighting bottlenecks in production. The results indicate that due to weak demand, declines in energy do not further depress output in recessions. Policymakers may use the findings to benefit from energy’s economic effects whilst mitigating climate risks.

Assessing the Socioeconomic and Public Health Impacts of Cyclical Oil Price Shocks in Nigeria

Nigeria’s overdependence on oil revenue distorts its fiscal system and exposes public health to global oil price volatility. This study examines the socioeconomic and public health impacts of cyclical oil price shocks, focusing on infant mortality, life expectancy, and healthcare expenditure. Guided by the Oil Price Shock Theory and New Keynesian Theory, it employs Impulse Response Function (IRF) and Variance Decomposition (VD) analysis using time-series data from 1981 to 2023. Oil shocks are disaggregated into supply, oil-specific demand, and aggregate demand shocks to model fiscal responses and health outcomes. Findings reveal that negative oil shocks significantly reduce public revenues, triggering healthcare budget cuts and worsening health outcomes, especially for vulnerable groups. The study recommends establishing stabilization funds, prioritizing healthcare investment, and strengthening economic resilience to reduce oil dependency. Achieving sustainable health outcomes requires adaptive fiscal policies that ensure equity and stability in the face of oil market fluctuations.

Assessing differential impacts of a trade agreement using a quantile regression approach

Abstract Using farm‐level panel data, we directly estimate the impacts of the Korea–Chile Free Trade Agreements (FTA) on the revenue of the firms in South Korea that faced greater imports—agricultural producers as the FTA induced greater imports of fruits and vegetables from Chile to South Korea. As expected, we find the negative effect of the increased imports on the total crop revenue and profit of the farms. We model and examine the differential impacts and find that the negative effects are greater for high‐revenue farms. We document the evidence of the lack of immediate adjustment as a response to the negative shocks from the trade agreement.

Exploring Stock Returns Volatility of Select NSE – Listed Pharmaceutical Companies: An Empirical Study

Volatility of a financial time series has become a fertile area for research during last decades. Global financial meltdowns have massive shock on different sectors as well as on scripts returns. The current study empirically explores the volatility pattern of NSE listed pharmaceutical companies considering daily closing adjusted stock price from 2001-02 to 2015-16. The objective of the paper is to study the volatility design of daily stock returns. The application of GARCH, and T-GARCH models provides the evidence of the persistence of time varying asymmetric volatility. Main findings suggest that time varying volatility behaviour of Indian stock market may be due to recent global financial meltdown, which is originated from US sub-prime crisis. Likewise, effect captured by different models show that negative shocks have significant effect on conditional volatility.

Minimum Wages and Homelessness

ABSTRACTEconomic theory offers competing predictions about how minimum wage policies might affect homelessness. While minimum wages might reduce homelessness by raising incomes, they could also trigger employment disruptions and negative income shocks identified in the literature as proximate causes of homelessness. Policy effects might be heterogeneous because the risk factors for homelessness—substance abuse, mental illness, unstable support network, and so on—correlate with lower labor market competitiveness. Using synthetic and local‐projection difference‐in‐differences methods with Department of Housing and Urban Development point‐in‐time counts, I find minimum wage increases between 2006 and 2019 led to more homelessness in American municipalities. This finding could help explain why homelessness surged in places that substantially increased minimum wages like New York, Seattle, and San Francisco while falling in localities with inflation‐adjusted declines. Further analysis suggests employment effects more likely drove these increases than housing prices or migration. The findings highlight distributional consequences of minimum wage policies and add to our understanding of homelessness.

Do Exchange Rates Behave Asymmetrically with Services Trade in India?

ABSTRACT The aim of this article is to examine whether exchange rates behave asymmetrically with services trade in India. Results from the nonlinear autoregressive distributed lag (NARDL) model using quarterly data from 2010 to 2021 demonstrate the asymmetric behavior of exchange rates toward trade in services for both exports and imports. Service exports responded significantly to positive and negative exchange rate shocks in the long run. However, service imports showed an insignificant response to exchange rate shocks in the long and short run. Therefore, it appears that exchange rate behavior in India is more sensitive toward service exports than service imports.

Volatility and Returns of Bitcoin During US Elections 2016 and 2020

Bitcoin's return volatility from 2014 to 2022 reveals significant changes in response to political and macroeconomic developments, particularly during the 2016 and 2020 U.S. presidential elections. In 2016, Bitcoin exhibited modest price movement and low volatility, while in 2020, the asset experienced dramatic price increases and heightened volatility, reflecting increased market maturity and institutional interest. Political uncertainty, regulatory shifts, and market sentiment played crucial roles in shaping volatility dynamics during these periods. Using GARCH(1,1) and EGARCH(1,1) models, time-varying volatility patterns and asymmetric effects of market shocks are analyzed. GARCH results confirm volatility clustering and high persistence, whereas EGARCH captures leverage effects, showing that negative shocks influence volatility more than positive ones. Visualizations of conditional variance support these findings, indicating that Bitcoin reacts more intensely to adverse news, especially during politically turbulent periods. Residual diagnostics suggest model adequacy and enhance the reliability of insights. These results underscore Bitcoin's evolving role as a financial asset increasingly affected by global events and investor sentiment, offering valuable implications for market participants and policymakers monitoring risk in cryptocurrency markets.

The Response of Global Oil Inventories to Supply Shocks

Oil inventories are essential in alleviating realized and anticipated supply shocks and represent a key market indicator. This study examines the responses of global and country oil inventories to supply shocks under tight and loose market conditions. We utilize an expanded version of the GVAR model, adding the OECD oil inventories variable, incorporating major oil-producing countries: Iran, Russia, and Venezuela, and extending the coverage period. Our simulations indicate that a negative global supply shock significantly affects oil inventories under “tight” market conditions. The model correctly predicts the trajectory of changes to oil inventories in South Korea following a supply shock to Russian production in tight markets and Iranian output in loose markets. This case also shows that commercial players, using their inventories as a buffer, can negate government attempts to maintain constant levels of reserves. Overall, the response to the oil inventory tends to vary across producing and importing countries and market conditions. Such dynamics highlight potential problems with specific policies, such as using inventories as a buffer to alleviate price fluctuations or disrupting the oil production of individual countries through sanctions, as these measures oftentimes result in unintended consequences due to complex interconnections of the global oil market.