The Unassuming Economist

From a paper by Luciano Vereda, Helder Ferreira de Mendonça, and George Morcerf:

“Our study advances the modeling of forecast revisions by accounting for the nuanced impact of informational shocks across different time horizons. Specifically, we introduce modifications to the error structure of regression models used to detect biases in macroeconomic forecasts. Drawing on consensus forecasts of inflation and output growth from the central banks of Brazil, Chile, and Mexico, our approach offers a nuanced understanding of bias estimation uncertainty, leading to a more robust rejection of the null hypothesis of no biases. By elucidating the differential effects of informational shocks on forecast accuracy across time periods, our findings not only contribute to the refinement of forecasting methodologies but also have implications for policymakers and economic analysts striving for more accurate and reliable predictions in dynamic economic environments.”

From a paper by Boqiang Lin, and Yijie Song:

“Macroeconomic factors such as coal prices affect corporate decision making. With a set of 39,795 observations of firm-year data, encompassing 30 provinces and spanning the years 2005–2022, this paper estimates the impact of coal price shocks to corporate risk-taking of listed companies in China. The empirical results show that coal prices change negatively affect corporate risk-taking due to internal risk aversion. Further analysis shows that this effect is asymmetric between positive and negative shocks, and is more significant among higher coal dependence provinces. External factors such as economic policy uncertainty further reduce risk-taking. This study provides both macro and micro perspective analysis of corporate risk-taking and coal prices influences, contributing to the policy references for corporate strategic choices and coal price adjustments in the process of energy transition of China.”

From a paper by Khoja Akhmet Yassawi, Mukhtar Auezov, and Miras University:

“The investigation delved into the dynamic interplay between oil price fluctuations and their ramifications on the pricing of agricultural products, employing the Vector Autoregression methodology. The dataset spanned 3 months, commencing from January 2010 and concluding in December Upon subjecting the data to an in-depth analysis, it was ascertained that it possesses a unit root, indicating an integrated order of one (I [1]), and achieves stationarity subsequent to the first-order differencing. The findings of the inquiry revealed that the paramount driver influencing agricultural product prices is the inherent volatility within the agricultural sector itself. Contrary to initial expectations, the impact of oil price fluctuations on agricultural prices was discerned to be comparatively modest. Intriguingly, the outcomes underscored that the preeminent factor contributing to fluctuations in agricultural product prices is the influence wielded by oil prices. This implies that alterations in oil prices exert a more pronounced effect on the variability in agricultural product prices as opposed to the overall revenue generated from agricultural endeavors.”

From a paper by Weizhuojia Peng, Weibai Liu, Yijia Li:

“This paper examines the impact of financial development on pollution reduction at the enterprise level using statistical data from 30 provinces in China from the period 2018 to 2022. The effect of financial development on pollution reduction is examined separately from the perspectives of scale effect and technology effect. Although there are significant regional differences in the impact of the increased use of financial instruments on pollution reduction in different provinces of China, on balance the greater use of financial tools decreases pollution, reflecting the technological effect of utilizing financial tools exceeds the scale effect. Heterogeneity analysis shows that the impact of financial development on pollution reduction of private enterprises is higher than that of state-owned enterprises. The paper also discusses the implications for China in achieving carbon peak and carbon neutrality and promoting high-quality economic development and an economic green transformation. Since improvement in the financial system is a key to improving the environment, the increased efficiency of financial tools enhances this improvement.”

From a paper by Hlalefang Khobai, Ponalo Xinishe, Mpho Lenoke:

“The surge in oil price levels remains a world-wide concern, more specifically to oil-importing countries such as South Africa. The dependence on crude oil from these net exporters makes the country vulnerable to external shocks, such as geopolitics. These effects have a pass-through effect to domestic headline inflation, induced by imported inflation. The general objective of the study is to investigate the asymmetric effect that the price of oil has on inflation in South Africa. To achieve these objectives, the study applied the Nonlinear Autoregressive Distributed Lags (NARDL), Error Correction Model (ECM), Pairwise Granger Causality, Impulse Response Function and Variance Decomposition. The bounds test of cointegration revealed that cointegration exists between the observed variables of the study. After estimating the error correction model, the study found that in the short-run, the relationship between a positive change in oil price and inflation is negative and significant. However, the relationship between a negative change in oil price and inflation in the short-run is now positive and significant. Therefore, the correction of disequilibrium will take place in the long run by means of short-run adjustments, with the speed of 1.71%. Pairwise Granger Causality test revealed that a unidirectional relationship occurs from oil prices to inflation. The Variance Decomposition results show that a shock to oil price accounts for a greater percentage of fluctuation in inflation. The Impulse Response Function reveals that within a 10-year period there is a positive response of inflation to oil prices, specifically from year three to year five. The study recommends the South African oil import diversification policy to source oil from multiple exporting countries to ensure steady supply and reduce dependence on any single source. This strategy improves security and reduces vulnerability to oil price shocks and supply disruptions caused by various factors.”