The Unassuming Economist

From a paper by Yiran Zhao, Xiangyun Gao, Huiling Zheng, Yupeng Zhang, Qingru Sun, Anjian Wang, and HaiZhong An:

“This study examines the impact of international crude oil prices on national sub-price indices following external shocks. It analyzes the heterogeneous transmission mechanisms of these shocks across diverse national price index networks. To achieve this, we employ Granger causality tests as the filter to construct impulse response networks. This approach helps unveil the duration, magnitude, and pathways of impact on sub-price indices in five countries: China, the US, Russia, Germany, and the UK. Our findings suggest that the impact of crude oil price changes on national sub-price indices is most pronounced within 1-2 months, and more persistent on the Producer Price Index (PPI) than the Consumer Price Index (CPI). Identifying specific sub-price indices affected by shocks shows that China and the US are more significantly impacted. Moreover, identifying the transmission paths of crude oil price changes within a country’s internal price system underscores the significance of the CPI of transportation. This study of price transmission within countries offers key insights for managing economic shocks at the microeconomic level.”

From a paper by Aviral Kumar Tiwari, Mehmet Metin Damm, Halil Altıntaş and Festus Victor Bekun:

“This paper uses the dynamic connectedness framework to investigate the interrelationship between the decomposed oil supply, demand and risk shocks that Ready (2018) developed and the stock market returns of emerging market economies. For this purpose, we use daily data from 11 October 2001 to 5 April 2021. Novel empirical methodologies, including wavelet quantile correlation (WQC), cross-quantilogram analysis, nonparametric causality-in-quantile approaches, contemporaneous R² connectedness approach and generalized R² connectedness approaches, are employed. The results show that oil price fluctuations significantly impact the economic performance of emerging market economies, reflecting historical events. Demand price shocks are regarded as net transmitters within the system, whereas supply and risk price shocks are net receivers of spillovers. Concurrently, our findings indicate a considerable degree of dynamic connectedness among the stock markets of emerging market economies. In particular, the stock markets of Brazil, Mexico, and Argentina have been identified as net transmitters of spillovers. In contrast, the stock markets of Turkey, South Korea, Malaysia, Indonesia and India are classified as net receivers of spillovers. Furthermore, we examine and document the advantages of diversified portfolios that include all sector indices, including oil price shocks and emerging market economy stock markets, in terms of portfolio performance. The insights offered here are valuable for investors and policymakers striving to enhance their strategic approaches in today’s interconnected global financial context. The results show that oil price fluctuations significantly impact the economic performance of emerging market economies and reflect historical events. Demand shocks affecting the stock market indices of Brazil, Argentina and Mexico tend to act as net spillover transmitters. In contrast, supply shocks affecting the stock market indices of Indonesia, South Korea, India, Turkey and Malaysia mainly act as net spillover receivers. Net pairwise interconnectedness analysis reveals that, except for crisis periods, interactions between financial markets or macroeconomic indicators are evenly distributed. Thus, systemic risk is lower, and markets act independently. Empirical findings obtained using WQC generally show the presence of negative correlations at long-time scales and low quantiles, which is considered an indicator of the safe-haven feature associated with the asset in question. The hedge feature is observed to be evident only at long time scales. The results of the cross-quantilogram analysis show mixed evidence of correlation in all stock indices, especially in the weekly lag structure, compared to daily and monthly lags. Finally, non-parametric Granger causality test results show that stock returns are insensitive to oil price fluctuations, making these markets attractive for investors seeking diversification strategies. These findings provide valuable recommendations for investors seeking sustainable equities in a volatile oil market.”

From a paper by Afees Salisu and Etsubdink Sileshi:

“In recent decades, many African countries have been experiencing structural transformation. During
this same period, these countries were witnessing unfavorable external balance. This has challenged
conventional wisdom as these two are considered to be moving in opposite directions. This study
examines the effect of the shift in sectoral composition of African economies on their external balance
position. Using balanced panel data for 38 countries from 2000 to 2022, we estimate the effect of
structural change measured by sectoral shares in value added to GDP on external balance (% GDP).
Our methodology includes both static and dynamic panel models. However the dynamic panel models(GMM) are found to be the appropriate ones. The results show that agricultural sector’s share of
GDP has a negative effect on external trade balance, while the industrial sector is found to have a
positive impact. These results are robust to various model specifications. For additional robustness
check, we also used control variables- foreign direct investment to GDP ratio and official exchange rate.
Our results are consistent in sign, magnitude of coefficients and significance levels. As far as external
trade balance is concerned, African countries should give the necessary support to the expansion of
industrial sector. We also advise future researches to examine the composition of the each sector in
Africa and its implication for the external balance.”

From a paper by Neha Gupta, Namita Sahay, and Miklesh Prasad Yadav:

“We analyse the asymmetric impact of oil prices on the stock markets of the BRICS nations. Employing the Nonlinear Autoregressive Distributed Lag (NARDL) model, we examine the weekly data spanning from October 29, 2010, to May 28, 2021 for West Texas Intermediate (WTI) spot prices in USD per barrel, alongside stock price data from official stock market indices websites. The findings reveal a substantial long-run association of oil prices with stock markets of BRICS nations except South Africa with significant asymmetry observed in both short and long-term impacts. Specifically, fluctuations in oil prices exhibit divergent effects on stock markets within these nations necessitating nuanced policy responses. Investors and portfolio managers are encouraged to adopt nonlinear models for forecasting and portfolio management leveraging asymmetric effects for risk mitigation strategies. These suggestions underscore the importance of recognizing the nonlinear and asymmetric nature of oil price dynamics in shaping investment decisions and formulating effective policy measures to mitigate associated risks in BRICS stock markets.”

From a paper by Aina B. Aidarova, Aissulu Nurmambekovna Ramashova, Karlygash Baisholanova, Galiya Jaxybekova, Aliy Imanbayev, Indira Kenzhebekova, and Dinmukhamed Kelesbayev:

“In 2001, Jim O’Neil coined the term “BRIC” to refer to the economies of Brazil, Russia, India and China. In 2011, South Africa joined the group, and it was updated to “BRICS.” These countries have a significant impact on the world economy, and there are numerous studies examining their macroeconomic structures. This study focuses on the relationship between economic growth, oil revenues, and inflation levels in BRICS countries from 2000 to 2021 and uses panel cointegration analysis. Many studies showed a relationship between these variables in different countries and unions. This study aims to determine if these relationships hold for BRICS countries. The results suggest a cointegration relation and a causality relation between economic growth, inflation, and oil revenues in BRICS countries. This finding demonstrates the impact of energy, specifically oil revenues, on economic growth. However, other macro indicators also affect economic growth, as suggested by existing literature. Therefore, future studies could improve on this research by including additional social and economic variables to evaluate the impact of oil revenues on economic growth from multiple perspectives.”