scholarly journals The Dynamic Spillover Effects of Macroeconomic and Financial Uncertainty on Commodity Markets Uncertainties

Economies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 91
Author(s):  
Hedi Ben Haddad ◽  
Imed Mezghani ◽  
Abdessalem Gouider
Keyword(s):  
Raw Materials ◽  
Precious Metals ◽  
Fats And Oils ◽  
Spillover Effects ◽  
Commodity Price ◽  
Commodity Markets ◽  
Time Varying ◽  
Vector Autoregressive ◽  
Macroeconomic Uncertainty ◽  
Price Uncertainties

The present paper has two main objectives: first, to accurately estimate commodity price uncertainty; and second to analyze the uncertainty connectedness among commodity markets and the macroeconomic uncertainty, using the time-varying vector-autoregressive (TVP-VAR) model. We use eight main commodity markets, namely energy, fats and oils, beverages, grains, other foods, raw materials, industrial meals, and precious metals. The sample covers the period from January 1960 to June 2020. The estimated commodity price uncertainties are proven to be leading indicators of uncertainty rather than volatility in commodity markets. In addition, the time-varying connectedness analysis indicates that the macroeconomic uncertainty has persistent spillover effects on the commodity uncertainty, especially during the recent COVID-19 pandemic period. It has also found that the energy uncertainty shocks are the main drivers of connectedness among commodity markets, and that fats and oils uncertainty is the influence driver of uncertainty spillovers among agriculture commodities. The achieved results are of important significance to policymakers, firms, and investors to build accurate forecasts of commodity price uncertainties.

The impact of macroeconomic uncertainty on international commodity prices

2017 ◽  
Vol 7 (2) ◽  
pp. 163-184 ◽  
Author(s):  
Xiaofen Tan ◽  
Yongjiao Ma
Keyword(s):  
Raw Materials ◽  
Commodity Prices ◽  
Precious Metals ◽  
Commodity Price ◽  
Content Type ◽  
Vector Autoregressive ◽  
Macroeconomic Uncertainty ◽  
Wide Range ◽  
The Impact ◽  
Low Uncertainty

Purpose The purpose of this paper is to empirically analyze the impact of macroeconomic uncertainty on a large sample of 19 commodity markets. Design/methodology/approach The 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. Findings The 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/implications The findings in this study suggest that commodity prices reflect not only the level of economic fundamental but also the volatility of economic fundamental. Originality/value This 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.

scholarly journals African financial markets in a storm: Cryptocurrency safe havens during the COVID-19 pandemic

2021 ◽  
Vol 3 (2) ◽  
pp. 60-70
Author(s):  
Seyram Pearl Kumah ◽  
David Adjei Abbam ◽  
Ransford Armah ◽  
Evelyn Appiah-Kubi
Keyword(s):  
Financial Markets ◽  
Frequency Domain ◽  
Significant Risk ◽  
Spillover Effects ◽  
Commodity Markets ◽  
Time Varying ◽  
Medium Term ◽  
Bear Market ◽  
Daily Frequency ◽  
Contagion Risk

The COVID-19 pandemic provides the first widespread bear market conditions since the inception of cryptocurrencies. We test the haven properties of cryptocurrencies for African stocks and commodity markets in a pandemic implementing the frequency domain spillover index. Data spans 11th August 2015 to 28th August 2020 at a daily frequency. Findings show weak interconnectedness across markets suggesting non-contagion risk and that cryptocurrency are safe havens for African stocks and commodity indices from the medium-term. We find the major transmitters of spillover effects across markets to be time-varying and heterogeneous. This study provides significant risk diversification benefits for policymakers and investors in the African financial markets.

The Economics of Commodities and Commodity Markets

2018 ◽  
Author(s):  
Florian Ielpo
Keyword(s):  
Raw Materials ◽  
Commodity Prices ◽  
Essential Element ◽  
Commodity Markets ◽  
Production Costs ◽  
Demand And Supply ◽  
Spot Prices ◽  
Supply Shocks ◽  
The Business Cycle

This chapter covers the economic fundamentals of commodity markets (i.e., what shapes the evolution of the price of raw materials) in three steps. First, it covers the theories explaining why the futures curve can be upward or downward sloping, an essential element for commodity producing companies. The evolution of inventories and hedging pressures are the two dominant sources of explanation. Second, the chapter reviews the fundamentals of commodity spot prices: technologies, supply, demand, and speculation. Production costs draw the long-term evolution of prices, but demand and supply shocks can trigger substantial variations in commodity prices. Third, the chapter presents how commodity prices interact with the business cycle. Commodities are influenced by the world activity but can also have a material impact on it.

Financialization of Commodity Markets

2018 ◽  
Author(s):  
Kyle J. Putnam
Keyword(s):  
Business Cycle ◽  
Futures Markets ◽  
Commodity Price ◽  
Commodity Markets ◽  
Commodity Futures ◽  
Futures Prices ◽  
Price Behavior ◽  
Risk And Return ◽  
Commodity Futures Markets ◽  
Asset Class

In the early 2000s, financial investors began pouring billions of dollars into the commodity futures markets seeking the unique investment benefits of this distinct asset class. This “financialization” process has called into question the fundamental risk and return properties of commodity futures as evidence has emerged favoring the idea that the massive increase in investor flows caused a rise in futures prices, volatility, and intra- and intermarket return correlations. However, a contrarian line of research contends that the effects of the new “speculative” capital on the futures markets are unsubstantiated and the increased participation of financial investors poses little consequence to the economics of the marketplace. This latter line of literature maintains that the investment benefits of commodity futures have not been diminished and that fundamental factors and business cycle variations can explain the observed changes in commodity price behavior.

scholarly journals Commodity price pass-through along the pricing chain

2021 ◽  
Author(s):  
Rebeca Jiménez-Rodríguez ◽  
Amalia Morales-Zumaquero
Keyword(s):  
Emerging Economies ◽  
Raw Materials ◽  
Commodity Prices ◽  
Commodity Price ◽  
Emerging Countries ◽  
Consumer Prices ◽  
Advanced Economies ◽  
The World ◽  
Producer Prices ◽  
Pass Through

AbstractThis paper analyses the commodity price pass-through along the pricing chain for the global commodity price index and the indices of its main categories (i.e., agricultural raw materials, food and beverages, energy and metals) in the world, advanced and emerging economies. To do so, the study considers country-by-country vector autoregression models and pool the results by taking weighted means for 18 advanced economies and 19 emerging countries, as well as for the world (defined as the sum of advanced and emerging economies). The results show the following: (i) there is evidence in favour of partial pass-through from commodity prices to producer prices, although the evidence for the pass-through to consumer prices is less evident; (ii) the pass-through in the world seems to be led by both advanced and emerging countries for producer prices and only by advanced economies for consumer prices; (iii) higher prices in the four categories (agricultural raw materials only in the short-run) induce significant higher producer prices in almost all cases, with shocks in the prices of energy and metals showing the largest effects; and (iv) energy prices explain the highest variability of producer and consumer prices.

scholarly journals The Dynamic Impacts of the COVID-19 Pandemic on Log Prices in China: An Analysis Based on the TVP-VAR Model

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 449
Author(s):  
Chenlu Tao ◽  
Gang Diao ◽  
Baodong Cheng
Keyword(s):  
Exchange Rate ◽  
Structural Changes ◽  
Raw Materials ◽  
Supply And Demand ◽  
Oil Prices ◽  
Control Measures ◽  
Var Model ◽  
Time Varying ◽  
Wood Industry ◽  
The Impact

China’s wood industry is vulnerable to the COVID-19 pandemic since wood raw materials and sales of products are dependent on the international market. This study seeks to explore the speed of log price recovery under different control measures, and to perhaps find a better way to respond to the pandemic. With the daily data, we utilized the time-varying parameter autoregressive (TVP-VAR) model, which can incorporate structural changes in emergencies into the model through time-varying parameters, to estimate the dynamic impact of the pandemic on log prices at different time points. We found that the impact of the pandemic on oil prices and Renminbi exchange rate is synchronized with the severity of the pandemic, and the ascending in the exchange rate would lead to an increase in log prices, while oil prices would not. Moreover, the impulse response in June converged faster than in February 2020. Thus, partial quarantine is effective. However, the pandemic’s impact on log prices is not consistent with changes of the pandemic. After the pandemic eased in June 2020, the impact of the pandemic on log prices remained increasing. This means that the COVID-19 pandemic has long-term influences on the wood industry, and the work resumption was not smooth, thus the imbalance between supply and demand should be resolved as soon as possible. Therefore, it is necessary to promote the development of the domestic wood market and realize a “dual circulation” strategy as the pandemic becomes a “new normal”.

Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate

2021 ◽  
pp. 1-38
Author(s):  
Travis J. Berge
Keyword(s):  
Aggregate Demand ◽  
Stochastic Volatility Model ◽  
Output Gap ◽  
Time Varying ◽  
Common Component ◽  
Macroeconomic Variables ◽  
Macroeconomic Uncertainty ◽  
Volatility Model ◽  
The Common ◽  
Gap Estimate

Abstract A factor stochastic volatility model estimates the common component to output gap estimates produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. The output gap estimates are uncertain even well after the fact. Nevertheless, the common component is clearly procyclical, and positive innovations to the common component produce movements in macroeconomic variables consistent with an increase in aggregate demand. Heightened macroeconomic uncertainty, as measured by the common component's volatility, leads to persistently negative economic responses.

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