Macroeconomic Uncertainty Shocks Research Articles

A greater crisis? Investigating MSA-level housing markets during the COVID-19 pandemic

This study analyzes the impact of uncertainties on ten major metropolitan statistical area (MSA)-level housing markets in the US from 2000 to 2022, elucidating the distinctive characteristics of crisis-like phenomena triggered by COVID-19. The study assesses crisis and noncrisis periods and finds that time-varying volatility in uncertainty is evident during crises, and economic policy uncertainty and macroeconomic uncertainty shocks show heightened volatility. The results suggest that the COVID-19 pandemic represents a more substantial crisis than the housing market crisis of 2007–2009. The findings indicate that uncertainty elevated MSA-level housing returns in 2000–2022 and offer supporting evidence for a flight-to-quality pattern as investors tended to allocate capital to safer real estate assets. The transmission mechanism from uncertainty to metropolitan housing markets is phase-dependent, with estimated responses to uncertainty shocks during crisis phases being more robust than those observed in normal times. This study provides valuable insights for monetary policymakers and offers guidance for investors’ risk management strategies.

A positive effect of uncertainty shocks on the economy: Is the chase over?

How large and persistent are the effects of uncertainty shocks on the economy? Are the effects of macroeconomic uncertainty shocks different from those of financial uncertainty shocks? In the empirical literature, there was a consensus on an estimated negative impact of uncertainty on macroeconomic variables. Recently, some studies identifying shocks with a novel methodology, namely the events constraint approach, find that macroeconomic uncertainty shocks may trigger an increase in the industrial production. The goal of this paper is to question this striking result. We have identified two main shortcomings in this literature that could explain the positive correlation between macroeconomic uncertainty and economic activity. We show that this method of identification can be sensitive depending on how to identify and select the structural uncertainty shocks in a SVAR model. Our main conclusion is that the controversial result of a positive effect of macroeconomic uncertainty on economic activity does not yet seem to be proven. Whether financial or macroeconomic, there is no evidence allowing for rejection of the hypothesis that they have a negative impact on economic activity.

Uncertainty and long-run economy: the role of R &D and business dynamism

In this paper, we study the effects of macroeconomic uncertainty shocks on the US economy in the long-run using an IV-SVAR methodology for the period 1960–2019. Following Piffer and Podstawski (Econ J 128(616):3266–3284, 2018), we use variation in gold prices as an instrument to identify the uncertainty shocks. We find that potential output decreases persistently in response to an uncertainty shock. Furthermore, our study shows that decline in the R &D investments and business dynamism are the two key transmission channels of the uncertainty shocks that generate long lasting effects on the economy.

Uncertainty shocks, network position, and inventory

PurposeThis paper aims to conduct an empirical study to investigate whether an industry’s position affects the transmission of information and economic shocks.Design/methodology/approachThis paper conducts an empirical study of inventory performance based on a large panel of 71 industries in the manufacturing, wholesale and retail sectors over a 10-year period (2007–2016).FindingsIt is found that the position of a focal industry in the supply chain network moderates the impacts of macroeconomic uncertainty shocks and shocks from supplier/customer industries on the focal industry’s inventory. On the one hand, more central industries are more sensitive to macroeconomic uncertainty shocks as well as spillover shocks from their supplier and customer industries. On the other hand, uncertainty shocks from more central industries have higher impact on their partner industries than those from less central industries.Practical implicationsA manager needs to take into account the network positions of suppliers/customers in supply network when making inventory decisions. For example, when sharing information with partners, the network position of a partner affects how important its information is.Originality/valueThe key novelty of this paper is the introduction of network structure that represents the supplier–customer relationships in the entire economy, and the modeling of uncertainty shocks transmitted through the supply chain network.

Uncertainty Shocks, Innovation, and Productivity

Abstract In this paper, we argue that macroeconomic uncertainty shocks cause a persistent decline in economic activity, investment in R&D, and total factor productivity. After providing empirical evidence, we build a DSGE model with sticky prices and endogenous growth through investment in R&D. In this framework, uncertainty shocks lead to a short-term fall in demand because of precautionary savings and rising markups. The reduction in the utilised aggregate stock of R&D determines a fall in productivity, which causes a long-term reduction in the main macroeconomic aggregates. When households feature Epstein–Zin preferences, they become averse to these long-term risks affecting their consumption process (long-run risk channel), which severely exacerbates the precautionary savings motive and the overall adverse effects of uncertainty shocks.

Measuring uncertainty: A streamlined application for the Ecuadorian economy.

This paper develops a macroeconomic uncertainty index based on the multistage procedure that combines maximum likelihood and Bayesian estimation methods proposed by Jurado et al. (Am Econ Rev 105(3):1177–1216, 2015). Our approach streamlines the computation of the macroeconomic uncertainty index by specifying a state-space model estimated by maximum likelihood that allows us to obtain in one step the parameters of the model, the dynamic factors, and the forecast errors of the macroeconomic variables used to construct the index. Moreover, we estimate stochastic volatility models on the forecast errors also by maximum likelihood using a density filter that proves to be faster than a Bayesian estimation. After showing that our methodology produces reasonable results for the USA, we apply it to compute a macroeconomic uncertainty index for Ecuador, becoming the first index of this kind for a small developing or middle-income country. The results show that the Ecuadorian economy is more volatile and less predictable during recessions. We also provide evidence that macroeconomic uncertainty is detrimental to economic activity, finding that the responses of non-oil output, employment in the formal sector, and consumer prices to macroeconomic uncertainty shocks are sizable and persistent.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00181-021-02069-5.

Macroeconomic uncertainty shocks and households’ consumption choice

Exploiting U.S. households’ consumption survey data, we study whether recently developed indices of macroeconomic uncertainty (e.g., Jurado et al., 2015; Baker et al., 2016; Bekaert et al., 2019) affect household consumption choices. We find that positive shocks to financial, real, and macroeconomic uncertainty indices by Jurado et al. (2015), as well as S&P 500 implied volatility (VIX) significantly depress U.S. households’ consumption. We also find that households that are more uncertain about their individual future consumption react to economic uncertainty more sensitively. The real and macro uncertainty indices by Jurado et al. (2015) also have a long-lasting effect on consumption choices, consistent with the habit formation model.

Macroeconomic uncertainty and natural gas prices: Revisiting the Asian Premium

Abstract While macroeconomic uncertainty and its impact on commodity, mainly oil prices, have been frequently studied, there is no study investigating the role of macroeconomic uncertainty in natural gas pricing. To fill this gap, we construct homogeneous macroeconomic uncertainty measures for three major natural gas markets and investigate the dynamic causal effects of macroeconomic uncertainty shocks on the formation of natural gas prices. We show that macroeconomic uncertainty plays a vital role in determining natural gas price variations, in addition to driving business cycle fluctuations in these economies. Compared to oil price, the uncertainty impact on gas pricing is relatively moderate but significant. Market-specific supply and demand analysis shows the drivers of gas prices are substantially different in three different markets, which helps to understand the “Asian Premium” phenomenon in the natural gas trade.

The Environmental Impacts and Optimal Environmental Policies of Macroeconomic Uncertainty Shocks: A Dynamic Model Approach

The existing literature on carbon policy analysis in a random environment focuses on the existence of the level (first-moment) shocks, whereas recent research emphasized the nonnegligible impact of uncertainty (second-moment) shocks on macroeconomy. This paper studies the impact of uncertainty (second-moment) shocks on the carbon emissions, abatement investment, and output. We construct an environmental dynamic stochastic general equilibrium (E-DSGE) model that features uncertainty shocks from the good demand and supply. By comparing the social welfare among carbon taxation, intensity, and capacity regimes, we show that the carbon taxation is the best policy regarding positive uncertainty shocks of households preference (good demand), whereas capacity and intensity targets are preferable under the uncertainty shocks of firms productivity (good supply).

Macroeconomic uncertainty, information competition, and liquidity

In this study we provide evidence regarding the effect of macroeconomic uncertainty on stock market liquidity by analyzing the time-series relation between both types of macroeconomic uncertainty shocks: good and bad uncertainty and various measures of liquidity. Our study also sheds light on whether the impact of macroeconomic uncertainty on liquidity varies with information environment by examining the effects of investor competition over information on the relation between good and bad uncertainty and liquidity in the Taiwan markets. We find that there is a negative (positive) relation between bad (good) uncertainty and the subsequent liquidity of stocks. We also find that the magnitude of the impact of bad uncertainty on stock market liquidity is larger than good uncertainty. On the other side, macroeconomic uncertainty would exerts a larger impact on liquidity when the market is imperfectly competitive.

The Impact of Uncertainty Shocks in the United Kingdom

This paper uses a data-rich environment to produce direct econometric estimates of macroeconomic and financial uncertainty in the United Kingdom for the period 1991-2016. These indices exhibit significant independent variation from popular proxies for macroeconomic and financial uncertainty. We identify the impact of uncertainty shocks using narrative sign restrictions, which allow us to exploit individual historic events to separate the impact of macroeconomic, financial and credit shocks on real variables. Using only traditional sign restrictions, we find that the real effects of macroeconomic uncertainty shocks are generally weaker than proxies suggest and that the effects depend on a subsequent rise in financial uncertainty and credit spreads to have a negative impact on GDP. Exploiting narrative events such as the disorderly exit from the Exchange Rate Mechanism, the dot-com recession and the financial crisis support this finding. However, conditioning on narrative events more closely associated with political uncertainty, ie tight general elections, suggests a stronger impact response of GDP to macro uncertainty shocks. We find these results are robust to controlling for both financial and global uncertainty.

Does the volatility of commodity prices reflect macroeconomic uncertainty?

While there exists numerous studies on the macroeconomic effects of oil and commodity shocks, the literature is quite silent on the impact of macroeconomic uncertainty on oil and commodity prices and, especially, on their volatility. This paper tackles this issue through the estimation of a structural threshold vector autoregressive (TVAR) model on a sample of 19 commodity markets. We aim at (i) assessing whether the effect of macroeconomic uncertainty shocks on commodity price returns depends on the degree of uncertainty, and (ii) investigating the transfer from macroeconomic uncertainty to price uncertainty using a newly developed measure of commodity price uncertainty. Our findings show that both agricultural and industrial markets are highly sensitive to the variability and the level of macroeconomic uncertainty, while the impact on precious metals is more parsimonious given their well-identified safe-haven role in time of economic turmoil. In addition, we find evidence that the recent 2007–09 recession has generated an unprecedented episode of high uncertainty in numerous commodity prices. Interestingly, our analysis further reveals that volatility and uncertainty in prices can be disconnected. This is especially true for the oil market as most important shocks in the 1990s and the beginning of the 2000s that lead to price volatility do not generate price uncertainty, highlighting the relevance of our uncertainty measure in linking uncertainty to predictability rather than to volatility.

The impact of macroeconomic uncertainty on international commodity prices

PurposeThe purpose of this paper is to empirically analyze the impact of macroeconomic uncertainty on a large sample of 19 commodity markets.Design/methodology/approachThe authors rely on Jurado et al.’s (2015) measure of macroeconomic uncertainty based on a wide range of monthly macroeconomic and financial indicators and estimate a threshold VAR model to assess whether the impact of macroeconomic uncertainty on commodity prices differs under the high- or low-uncertainty state.FindingsThe findings show that positive macroeconomic uncertainty shocks affect commodity prices returns negatively on average and the impact of macroeconomic uncertainty is generally higher in high-uncertainty states compared with low-uncertainty states. Besides, although the safe-haven role of precious metals is confirmed, energy and industrial markets are more sensitive to short-run and long-run macroeconomic uncertainty, respectively.Research limitations/implicationsThe findings in this study suggest that commodity prices reflect not only the level of economic fundamental but also the volatility of economic fundamental.Originality/valueThis study empirically analyzes and verifies the influence of macroeconomic uncertainty not only on oil prices but also on four groups of 19 raw materials. As for the methodological issues, the authors rely on a structural threshold vector autoregressive specification for modeling commodity price returns to account for potentially different effects depending on the macroeconomic uncertainty states.

Does the Volatility of Commodity Prices Reflect Macroeconomic Uncertainty?

While there exists numerous studies on the macroeconomic effects of oil and commodity shocks, the literature is quite silent on the impact of macroeconomic uncertainty on oil and commodity prices and, especially, on their volatility. This paper tackles this issue through the estimation of a threshold vector autoregressive (TVAR) model on a sample of 19 commodity markets. We aim at (i) assessing whether the effect of macroeconomic uncertainty shocks on commodity price returns depends on the degree of uncertainty, and (ii) investigating the transfer from macroeconomic uncertainty to price uncertainty using a newly developed measure of commodity price uncertainty. Our findings show that both agricultural and industrial markets are highly sensitive to the variability and the level of macroeconomic uncertainty, while the impact on precious metals is more parsimonious given their well-identified safe-haven role in time of economic turmoil. In addition, we find evidence that the recent 2007-09 recession has generated an unprecedented episode of high uncertainty in numerous commodity prices. Interestingly, our analysis further reveals that volatility and uncertainty in prices can be disconnected. This is especially true for the oil market as most important shocks in the 1990s and the beginning of the 2000s that lead to price volatility do not generate price uncertainty, highlighting the relevance of our uncertainty measure in linking uncertainty to predictability rather than to volatility.

Real-Time Learning, Macroeconomic Uncertainty, and the Variance Risk Premium

The variance risk premium represents the compensation paid to index option sellers for the risk of losses following upward movements in realized market return volatility. Common wisdom connects these spikes with elevated uncertainty on economic fundamentals. I incorporate this link within a single-agent general equilibrium model, embedding real-time learning on state variables and parameters. I show that infrequent, large and relatively transitory macroeconomic uncertainty shocks produce a sizable and volatile variance risk premium. These shocks coincide with major events such as the LTCM/Russian crisis, the onset of the second Gulf War, and the great financial crisis of 2008-2009. I compute macroeconomic uncertainty as the dispersion of the agent’s belief about the expected growth rate of consumption. Its time-varying nature reflects in the variance risk premium, generating short-term predictability for market excess returns, consistent with the data. In addition, the model matches the higher order moments of the realized equity premium, with a reasonably low level of relative risk aversion equal to five. I finally provide evidence that parameter uncertainty may represent an extra-source of risk which is priced in equilibrium. In fact, a model with parameter learning and standard CRRA preferences, matches around half of the historical variance risk premium.