Uncertainty Shocks Research Articles

Oil price uncertainty shocks and the gender gap in U.S. unemployment

This study relates to a new literature which investigates the distributional effects of uncertainty shocks. In particular, we examine the effect of oil price uncertainty on unemployment rates of different age cohorts based on gender in the U.S. We find that oil price uncertainty shocks tend to increase the female unemployment rate, although the effect tends to be smaller in magnitude than for the male unemployment rate in each age cohort, except those over 55. The largest disparity between males and females occurs in the younger working age cohorts. Our results are robust to three different measures of oil price uncertainty from three different empirical models: an SVAR with multivariate GARCH, an SVAR with implied volatility, and an asymmetric Markov switching ARCH model. Our results are also robust to a structural VAR which separately identifies shocks to oil demand and oil supply.

UIP deviations: Insights from event studies

We evaluate the behavior of the UIP relationship around monetary policy and global uncertainty shocks using event studies. We find that the covariance between exchange rate movements and changes in long-term yield differentials is conditional on the nature of shocks. A model of partial arbitrage between domestic and US bond markets predicts that tighter US monetary policy appreciates the dollar while increasing US yields relative to domestic bonds, a response that is consistent with UIP forces, while global uncertainty shocks appreciate the dollar while raising domestic yields relative to US bonds, exacerbating the widely documented UIP violation. The empirical analysis supports these mechanisms, specially for developed economies. For emerging economies, both relationships are weaker, consistent with more pervasive currency stabilization policies that mute the FX response at the expense of higher volatility in longer yields. Our results suggest a more nuanced interpretation of the unconditional failure of the UIP.

US uncertainty shocks on real and financial markets: A multi-country perspective

The international propagation of uncertainty shocks from the United States is not fully understood, despite extensive literature on domestic effects. This study examines the impact of U.S. financial, macroeconomic, and policy uncertainty on credit growth, stock prices, economic activity, bond yields, and inflation in five major recipients of U.S. foreign investment from 1950 to 2019. Findings highlight the pivotal role of U.S. financial uncertainty in driving global business cycles. Increased uncertainties in the U.S. financial sector negatively affect global economic activity by impeding credit and stock prices, limiting funding opportunities for firms and households worldwide. This underscores the significant influence of U.S. financial markets on global economic fluctuations.

Os efeitos dos choques de incerteza imobiliária na dinâmica econômica em nível estadual

Abstract In this paper, we analyze how uncertainty shocks in the real estate market affect the economy of different US states. Firstly, we construct a measure of real estate uncertainty for each state. Using this measure, we estimate a Bayesian Panel Vector Autoregressive model to obtain impulse response functions to real estate uncertainty shocks. We then examine which state characteristics can explain the variations in economic activity responses to such shocks. Our results show that real estate uncertainty shocks have adverse effects on economic activity, with varying intensities across states. We also show that the adverse impacts on income are larger in states with a high share of financial, construction, and manufacturing industries, as well as a large proportion of small banks. On the other hand, states that allocate more resources to welfare policies experience lower impacts.

Energy Price Dynamics in the Face of Uncertainty Shocks and the Role of Exchange Rate Regimes: A Global Cross-Country Analysis

Energy Price Dynamics in the Face of Uncertainty Shocks and the Role of Exchange Rate Regimes: A Global Cross-Country Analysis

Uncovering the Transmission of Uncertainty Shocks in an Emerging Economy: Evidence from India

Uncovering the Transmission of Uncertainty Shocks in an Emerging Economy: Evidence from India

Quantile connectedness between the climate policy and economic uncertainty: Evidence from the G7 countries

In this study, we investigate the transmission mechanism between climate policy uncertainty (CPU) and economic policy uncertainty (EPU) in the G7 countries. To account for different conditions, we use a quantile-based VAR (Q-VAR) model over the period between 2000 and 2021. Our results show high connectedness between the CPU and the EPU of G7 countries, particularly at extreme quantile orders. On the other hand, the spillover effects between climate and economic policy uncertainty differ depending on the distributional levels of the uncertainty indices. The CPU is a net receiver of uncertainty shocks, while for almost all countries, the EPU acts as a net receiver or emitter, depending on the economic situation. During times of high or low economic uncertainty, the EPU of all G7 countries is strongly affected by shocks originating from the CPU. Moreover, the results indicate that the dynamic spillover patterns between EPU and CPU vary over time, responding to different economic events and financial crises. These results call for policymakers and governments to urgently integrate climate considerations into economic planning, fiscal policies, and regulatory frameworks to promote sustainable economic growth and mitigate the impacts of climate change.

Home country uncertainty and cash holdings: Evidence from multinational subsidiaries in South Korea

Using data on South Korean subsidiaries with 18 different countries of origin and a newspaper-based economic policy uncertainty (EPU) index, we investigate the effect of uncertainty transmission on multinationals’ key decisions. Subsidiaries of multinational corporations face host and home country uncertainty. We document that Korean subsidiaries significantly increase their cash holdings when EPU increases in their home countries, indicating that national uncertainty shocks are transmitted to other countries through multinational networks. We further show a more pronounced home EPU effect when parent companies hold a greater share of subsidiary equity. The home EPU effect is robust to the inclusion of additional home country factors and alternative definitions of home EPU and cash holdings. Additionally, we find that subsidiaries reduce their capital expenditures when their home EPU increases.

The Asymmetric Effects of Real Estate Uncertainty Shock

In this paper, we explore the asymmetric impact of real estate uncertainty (REU) shock on the U.S. economy and housing market in high- and low-volatility states. To do this, we apply the Markov-switching vector autoregression model. Our empirical results show that the macroeconomic and housing markets react negatively to unexpected uncertainties, and the response to the REU shock is much greater than other housing-related variables in high-volatility states. We confirm the presence of the real-options channel based on the following results: both housing starts and construction employment decrease, and housing inventory increases, especially in low-volatility states. In the short run, we observe a delayed pattern in housing starts and construction employment variables. The effect of the channel is less significant in times of high volatility but confirmed in low volatility. The forecast error variance decomposition results show that the REU shock is greater under high REU volatility and plays a more significant role in explaining most housing-related variables.

Uncertainty shocks, financial frictions, and business cycle asymmetries across countries

I show that uncertainty shocks trigger sharper declines in consumption, investment, and GDP – and a sharper increase in trade balances – in emerging countries relative to advanced countries during recessions. Using an open-economy model – estimated on a set of advanced and emerging countries – I demonstrate that these facts can be explained by an interaction between uncertainty and financial frictions. In particular, the results imply that during recessions, elevated borrowing costs in emerging countries – about 5.9% greater than advanced countries – interact nonlinearly with uncertainty to generate the observed excess volatility.

U.S. economic uncertainty shocks and extreme capital flows episodes: An empirical analysis of emerging and developing economies

AbstractWe use the two‐way fixed‐effect panel logit model to examine the impact of U.S. economic uncertainty shocks on the probability of extreme capital flow episodes based on quarterly data from 71 emerging and developing economies from 1998Q1 to 2022Q4. According to the findings, U.S. economic uncertainty shocks has a negative effect on the probability of gross capital surges, gross capital flight, and net capital surges, and has a positive effect on the probability of gross capital sudden stops, gross capital retrenchment, and net capital sudden stops. Moreover, we find differences in the factors affecting net and gross capital flows, which are usually more closely related to earnings factors dominated by real economic growth rates. Additionally, the sample's heterogeneity is analysed in accordance with the exchange rate regimes. Our results differ from traditional views, as floating exchange rates do not act as a buffer against extreme capital flows. Finally, capital flows are classified into direct investment, other investment, and portfolio investment, and it is found that U.S. economic uncertainty shocks have a significant impact on the extreme flow episodes of other and portfolio investment.

Non-linear dimension reduction in factor-augmented vector autoregressions

This paper introduces non-linear dimension reduction in factor-augmented vector autoregressions to analyze the effects of different economic shocks. I argue that controlling for non-linearities between a large-dimensional dataset and the latent factors is particularly useful during turbulent times of the business cycle. In simulations, I show that non-linear dimension reduction techniques yield good forecasting performance, especially when data is highly volatile. In an empirical application, I identify a monetary policy as well as an uncertainty shock excluding and including observations of the COVID-19 pandemic. Those two applications suggest that the non-linear FAVAR approaches are capable of dealing with the large outliers caused by the COVID-19 pandemic and yield reliable results in both scenarios.

Green credit, uncertainty and corporate pollution emissions

ABSTRACT The Chinese government introduced the green credit policy (GCP) in 2007 to address deteriorating ecological conditions. Using an enterprise-heterogeneity dynamic stochastic general equilibrium (DSGE) model that includes a financial accelerator mechanism, uncertainty shocks, and GCP, we reveal that GCP significantly reduces emissions. However, this effect is inhibited by rising external uncertainty, as evidenced by the findings from impulse response and welfare loss analyses. Additionally, this negative effect and inhibition are more pronounced for privately-owned enterprises (POEs) while muted for state-owned enterprises (SOEs). Moreover, this study presents that uncertainty weakens the role of GCP through two channels: tightening firms’ financing constraints and discouraging investment. Building upon the theoretical analysis above, we validate our findings by employing detailed firm-level data and the difference-in-differences (DID) method. The empirical results confirm the robustness of our findings. This study offers theoretical and quantitative support for developing GCP in China.

Uncertainty about the war in Ukraine: Measurement and effects on the German economy

We assemble a data set of more than eight million German Twitter posts related to the war in Ukraine. Based on state-of-the-art methods of text analysis, we construct a daily index of uncertainty about the war as perceived by German Twitter. We then estimate a VAR model with daily financial and macroeconomic data and identify an exogenous uncertainty shock. The increase in uncertainty has strong effects on financial markets and causes a significant decline in economic activity as well as an increase in expected inflation. We find the effects of uncertainty to be particularly strong in the first months of the war.

Relationship Stickiness, International Trade, and Economic Uncertainty

Abstract We study how stickiness in business relationships influences the trade impact of aggregate uncertainty. To begin, we construct a product-level index of relationship stickiness using firm-to-firm relationship duration data. We then demonstrate how relationship stickiness shapes trade dynamics in response to uncertainty shocks. We find that episodes of uncertainty lead to a decline in the overall establishment of new business relationships, with the impact varying depending on the level of stickiness. In markets characterized by high stickiness, uncertainty shocks primarily impede investments in new firm-to-firm relationships. In contrast, for non-sticky products, the adjustment to uncertainty shocks mainly manifests as the disruption of existing relationships.

Dynamic industry uncertainty networks and the business cycle

This paper identifies smoothly varying industry uncertainty networks from option prices that contain valuable information about business cycles, especially in terms of forecasting. Such information is stronger when the network is formed on uncertainty hubs, firms identified as the main contributors to uncertainty shocks. The stronger predictive ability of the hubs-based network is robust to a wide range of checks, the inclusion of a large set of controls, and is also confirmed out-of-sample.

Improved prediction of global gold prices: An innovative Hurst-reconfiguration-based machine learning approach

With gold being one of the most important precious metals that play irreplaceable roles in the global market, understanding the future movement of the gold price is of significant importance for investment and risk management worldwide. However, gold prices are subject to volatility and can experience significant fluctuations over time due to economic uncertainty shocks such as the China-US Trade War, Russia-Ukraine war, and COVID-19, which make the forecasting of gold price a challenging task. In this paper, we propose a hybrid forecasting model for gold prices based on the Hurst-oriented reconfiguration and machine learning approach and illustrate its usefulness by analyzing the gold prices of three major markets. We conduct a multifractal analysis of the decomposed series and scrutinize the predictability of each sub-series and its relationship with the Hurst exponent. Empirical results show that there are negative relationships between forecasting error and the Hurst exponent and between the number of embedding dimensions and the Hurst exponent. Our Hurst-based hybrid model outperforms other conventional prediction models in terms of prediction errors and accuracy of direction prediction. The findings of this study shed light on a better understanding of the temporal features of the gold market and provide references for improving investment and hedging strategies.

Does risk matter more in recessions than in expansions? Implications for monetary policy

We employ a nonlinear vector autoregression and a non-recursive identification strategy to show that an equal-sized uncertainty shock generates a larger contraction in real activity when growth is low (as in recessions) than when growth is high (as in expansions). An estimated New Keynesian model with recursive preferences replicates these state-contingent responses when approximated to third order around its risky steady state due to a stronger upward nominal pricing bias in recessions than in expansions. Empirical evidence supports this state-contingent channel, and we show that it can greatly reduce the ability of systematic monetary policy to stabilize output during recessions.

Global impacts of US monetary policy uncertainty shocks

We build a new empirical model, which admits time-varying variances of local structural shocks, to estimate the global impact of an increase in the volatility of US monetary policy shocks. By allowing for rich dynamic interaction between the endogenous variables and time-varying volatility in the global setting, we find that US interest rate uncertainty not only drives local output and inflation volatility, but also causes declines in output, inflation, and the interest rate. Moreover, we document strong global impacts, making the world move in a very synchronous way. Crucially, spillback effects are found to be significant even for the US economy.

On portfolio frictions, asset returns and volatility

We rationalize the observed short-run differences in corporate and long-term government bond yields in an financial-accelerator model with frictions that restrict changes in portfolio shares. We estimate the model on quarterly data for the Euro Area from 1999 to 2019, and show that the portfolio friction parameter is positive and significant. Portfolio frictions not only generate a time-varying wedge between the two returns that fits the data, but also raise the volatility of return differentials, and the precautionary motive of savers. As a result, the macroeconomic effects of uncertainty shocks are amplified by portfolio frictions.