Macroeconomic Uncertainty Indices Research Articles

The spillover effects of U.S. uncertainties on the systemic tail risk of Chinese enterprises

This study examines the impact of U.S. uncertainties, as indicated by the Macroeconomic Uncertainty Index (MU), Financial Uncertainty Index (FU), and Economic Policy Uncertainty Index (EPU), on the systemic tail risk within Chinese enterprises. Our findings reveal a significant positive relationship between U.S. uncertainties and systemic tail risk of Chinese enterprises. Additionally, this relationship is mediated through two main transmission channels—investor sentiment and financing constraints.

Macroeconomic Uncertainty Indices for European Countries

The present article seeks to develop a macroeconomic uncertainty index for the EU Member States based on Google Trends for a period of fifteen years (from January 2008 to December 2022). Monthly data were collected for the 12 countries for four different word-terms, as well as for unemployment rate, inflation and the 10-year Government Bond yield. For simplifying the research the keywords searched were in English and were not translated into the countries’ own languages. Our findings were then compared to existing uncertainty indices. Lastly, we employed Impulse Response Functions (IRFs) with the existing economic indicators to highlight the effect that one standard deviation shock on the uncertainty index has on all three indicators and its ability to accurately depict the future precariousness of the country.

The impact of macroeconomic uncertainty on the relationship between financial volatility and real economic activity

ABSTRACT A stock market volatility index is a widely used proxy of uncertainty in the macroeconomy, where a rise in the index dampens real economic activity. By contrast, the macroeconomic uncertainty index proposed by Jurado et al. (2015) measures the predictability of a wide range of macroeconomic indicators and thus, is a comprehensive indicator of macroeconomy-wide uncertainty. This study empirically investigates the nonlinear link between financial volatility and real economic activity based on the level of the macroeconomic uncertainty index. Employing data from the United States and Japan, the empirical analysis suggests that an increase in financial volatility lowers industrial production and business-fixed investment more persistently when macroeconomic uncertainty is higher.

Macroeconomic uncertainty and firms’ investment in China

This paper constructs macroeconomic uncertainty indices for China from 2009 to 2021 based on the distribution of forecast errors of major macroeconomic variables. The indices effectively capture the economy’s deep slump and rebound in 2020. This study reveals a negative relationship between macroeconomic uncertainty and firms’ investment, with downside uncertainty having a larger negative impact than upside uncertainty.

Economic uncertainty and cross section of stock returns: Australian evidence

In this paper, we construct a new macroeconomic uncertainty index for the Australian economy. We then examine the pricing implication of macroeconomic uncertainty on the cross section of Australian equity returns. Our paper replicates Bali, Brown and Tang (2017)’s findings that U.S. investors pay (require) higher prices (lower premium) for stocks that perform well when economic uncertainty increases. We also find evidence supporting such premium in the Australian equity market.

Bitcoin, uncertainty and internet searches

PurposeThis paper aims to examine the predictive power of the volume of Economic Uncertainty Related Queries and the Macroeconomic Uncertainty Index on the Bitcoin returns.Design/methodology/approachData consists of 118 monthly observations from September 2010 to June 2020. Due to the departure of series from Gaussian distribution and the existence of outliers, the authors use the quantile analysis framework to investigate the persistency of the shocks, the long-run relationships and Granger causality among the variables.FindingsThis research provides several important findings. First, the substantial differences between conventional and quantile test results stress the importance of the method selection. Second, throughout the conditional distribution of the series, stochastic properties of the variables, long-run and the causal relationships between the variables might be significantly different. Third, rich information provided by the quantile framework might help the investors design better investment strategies.Originality/valueThis study differs from the previous research in terms of variable selection and econometric methodology. Therefore, it presents a more comprehensive framework that suggests implications for empirical researchers and Bitcoin investors.

Estimating an optimal macroeconomic uncertainty index for Australia

ABSTRACT In this article, an optimal macroeconomic uncertainty index is constructed for the Australian economy. This index is derived from a small structural macroeconomic model. The structural model is first estimated using GMM to extract the parameter estimates, which are then used to initialize maximum likelihood techniques in order to obtain the optimal coefficient values for the relevant variables. The relevant variables are then weighted by the obtained optimal coefficients and, finally, are aggregated to produce the optimal macroeconomic uncertainty index for Australian economy. The empirical results show that the uncertainty index constructed is a good indicator of the optimal economic conditions in Australia, providing a useful tool to assist the Reserve Bank of Australia in its decision-making process.

A Macroeconomic Uncertainty Index for the Euro Area

A Macroeconomic Uncertainty Index for the Euro Area

Macroeconomic uncertainty, speculation, and energy futures returns: Evidence from a quantile regression

This paper aims to investigate the impact of the macroeconomic uncertainty index (MU) on the futures returns of energy, including crude oil, heating oil, and natural gas. The quantile regression is used in this paper for examining the heterogeneity across market conditions. The empirical results show that changes in MU negatively affect futures returns of crude oil and heating oil in downward market conditions, and positive changes in MU dominate this impact. The MU changes also have a negative effect on natural gas futures returns in an extremely downward period, but this impact is not asymmetric. Further analysis indicates that speculation mitigates the negative impact of positive MU changes on crude oil futures returns during downward periods, while the association of the MU changes with the futures returns of heating oil and natural gas is not affected by speculation.

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.

Disentangling the Effects of Uncertainty, Monetary Policy and Leverage Shocks on the Economy*

AbstractIn this paper, we assess the information content and predictive ability of various risk and uncertainty measures in predicting various measures of real economic activity as well as undertake a comparative analysis of the relative importance of uncertainty, monetary policy and leverage shocks in the macroeconomic business cycle. We find that the macroeconomic uncertainty index and the Chicago Fed national financial conditions risk index have the strongest predictive relationship with economic activities. Also, in the context of a Bayesian monetary structural vector autoregressive, we use the penalty function approach to a sequential identification of uncertainty, monetary policy and leverage shocks, and find that uncertainty shocks are a relatively more important source of variations in the economy than traditional monetary policy shocks. However, monetary policy shocks still outperform uncertainty shocks in explaining inflation dynamics.

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.

Construction of Macroeconomic Uncertainty Indices for Financial Market Analysis Using a Supervised Topic Model

The uncertainty in the financial market, whether the US—China trade war will slow down the global economy or not, Federal Reserve Board (FRB) policy to increase the interest rates, or other similar macroeconomic events can have a crucial impact on the purchase or sale of financial assets. In this study, we aim to build a model for measuring the macroeconomic uncertainty based on the news text. Further, we proposed an extended topic model that uses not only news text data but also numeric data as a supervised signal for each news article. Subsequently, we used our proposed model to construct macroeconomic uncertainty indices. All these indices were similar to those observed in the historical macroeconomic events. The correlation was higher between the volatility of the market and uncertainty indices with larger expected supervised signal compared to uncertainty indices with the smaller expected supervised signal. We also applied the impulse response function to analyze the impact of the uncertainty indices on financial markets.

International Economic Cooperation，Domestic Economic Stability and the Improvement of Current Account Imbalances

After 2008, the barriers to cross-border flows of production factors such as commodities, capital, and labor have become increasingly apparent. The new round of liberalism has quietly risen, triggering a wave of counter-globalization characterized by anti-free trade and anti-integration”. Some developed countries have attempted to go beyond the constraints of the structural adjustment of the global economy and embark on the so-called priority of interest and self-development”. This, to a certain extent, weakened the synchronization of the world economic cycle and objectively exacerbated the synthetic fallacy” in the global economic development. In the absence of effective international economic rules and regulations, this synthetic fallacy” may cause frictions in trade, finance, and other areas to increase, thereby accelerating current account imbalances.Based on the above facts, this paper regards current account imbalances as the result of the internal and external factors, and combines the changes in the economic globalization process with macroeconomic uncertainty to explore whether the synchronization between China and the world economic cycle has changed. Is there any uncertainty in China’s macro-economy, and how does it affect current account imbalances, accelerating or smoothing? If the synchronization between China and the world economic cycle is reduced and macroeconomic uncertainty is raised, will it accelerate current account imbalances? What is the impact? Firstly, the method of real-time measurement of macroeconomic uncertainty using large-scale mixed macroeconomic data sets is proposed, and the macroeconomic uncertainty index is constructed. It avoids the possibility of directly using the substitution variables such as financial market volatility in the past literature to reflect the possible deviation of macroeconomic uncertainty. Then we use the Markov framework to establish a macroeconomic cycle synchronization index. Finally, the vector autoregressive model with Bayesian variable selection （VAR-BVS） weakens the endogeneity problem caused by missing or mistaken variables, and analyzes the dynamic relationship between the three before and after the global financial crisis. The study examines the possible links between the three.The study finds that: The relationship between the two is similar to a U-shape curve with the synchronization of the world economic cycle as the horizontal axis and current account imbalances growth rate as the vertical axis. Whether before or after the crisis, macroeconomic uncertainty plays an accelerator” role in current account imbalances. In the long term, the increase in macroeconomic uncertainty has an accelerating effect on current account imbalances. In the short term, in addition to the impact of the domestic economic environment, the decline in the synchronization of the world economic cycle will play an important role in accelerating current account imbalances. The reason for the synchronization between China and the world economic cycle, and macroeconomic uncertainty affecting current account imbalances may be due to the international division of labor, factor mobility, and preventive savings motivation. There is structural heterogeneity in the relationship between domestic and foreign economic environment and current account imbalances, which is different from the relationship between trade in goods and trade in services. The findings show that a stable domestic economic environment and a cooperative international economic environment are important conditions to improve current account imbalances.

The Role of Economic Uncertainty in UK Stock Returns

We investigated the role of domestic and international economic uncertainty in the cross-sectional pricing of UK stocks. We considered a broad range of financial market variables in measuring financial conditions to obtain a better estimate of macroeconomic uncertainty compared to previous literature. In contrast to many earlier studies using conventional principal component analysis to estimate economic uncertainty, we constructed new economic activity and inflation uncertainty indices for the UK using a time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model. We then estimated stock sensitivity to a range of macroeconomic uncertainty indices and economic policy uncertainty indices. The evidence suggests that economic activity uncertainty and UK economic policy uncertainty have power in explaining the cross-section of UK stock returns, while UK inflation, EU economic policy and US economic policy uncertainty factors are not priced in stock returns for the UK.

The Role of Economic Uncertainty in UK Stock Returns

We investigate the role of domestic and international economic uncertainty in the cross-sectional pricing of UK stocks. We consider a broad range of financial market variables in measuring financial conditions in order to obtain a better estimate of macroeconomic uncertainty compared to previous literature. In contrast to many earlier studies using conventional principal component analysis to estimate economic uncertainty, we construct new economic activity and inflation uncertainty indices for the UK using a time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model. We then estimate stock sensitivity to a range of macroeconomic uncertainty indices and economic policy uncertainty indices. The evidence suggests that economic activity uncertainty and UK economic policy uncertainty have power in explaining the cross-section of UK stock returns, while UK inflation, EU economic policy and US economic policy uncertainty factors are not priced in stock returns for the UK.

The spillover of macroeconomic uncertainty between the U.S. and China

We investigate the spillover of macroeconomic uncertainty between the U.S. and China since 2002. Following Jurado et al. (2015), we construct a monthly aggregate macroeconomic uncertainty index for China from 224 economic variables. The structural vector autoregression model suggests a unidirectional spillover of macroeconomic uncertainty from the U.S. to China. Both U.S. and Chinese uncertainty have negative effects on China’s real economy, but the impact of U.S. uncertainty is greater.

SOME NEW ESTIMATES OF SHADOW ECONOMY FOR 80 COUNTRIES USING POOLED MEAN GROUP ESTIMATOR

The purpose of this study is to estimates the size of the shadow economy for 80 countries from nine regions spanning the period 1975-2012 based on Tanzi-type currency demand approach (CDA). This study contributes to the literature in three distinct ways. First, we augment CDA regression with a macroeconomic uncertainty index (MUI). Second, the construction of the uncertainty index is based on the dynamic factor model (DFM). Third, the pooled mean group (PMG) estimator allows in capturing the heterogeneity across countries in the short-run dynamics but imposing restrictions in the long-run parameters. The results confirm the existence of the longrun equilibrium relationship among the variables examined. All coefficients show expected signs along with statistical significance. More importantly, the macroeconomic uncertainty index variable show positive relationship, suggesting that public tend to hold more currency in an uncertain macroeconomic environment. In addition, we observe that developing regions (ranging from 19.9% to 37.3%) exhibit relatively large size of the shadow economy. On the contrary, developed regions have a considerable smaller estimate (ranging from 13.7% to 19.0%) of the size of shadow economy. On average, the world estimate of the shadow economy as a percentage of GDP is about 23.1%. Keywords: Shadow Economy; Currency Demand; Macroeconomic Uncertainty; Pooled Mean Group.

Macroeconomic uncertainty, growth and inflation in the Eurozone: a causal approach

ABSTRACTIn this article, we evaluate the causal relationship between macroeconomic uncertainty indices, inflation and growth rate for 17 Eurozone countries on a county-level examination. In performing a series of linear and nonlinear causality tests, we find little evidence of a causal relationship between uncertainty and macroeconomic variables. Thus, macroeconomic analysis based on uncertainty indices should be treated with caution.

Macroeconomic uncertainty indices for the Euro Area and its individual member countries

This paper introduces the Rossi and Sekhposyan (Am Econ Rev 105(5): 650–655, 2015) uncertainty index for the Euro Area and its member countries. The index captures how unexpected a forecast error associated with a realization of a macroeconomic variable is relative to the unconditional distribution of forecast errors. Furthermore, it can differentiate between upside and downside uncertainty, which could be relevant for addressing a variety of economic questions. The index is particularly useful since it can be constructed for any country/variable for which point forecasts and realizations are available. We show the usefulness of the index in studying the heterogeneity of uncertainty across Euro Area countries as well as the spillover effects via a network approach.