The Unassuming Economist

From a paper by Cheol-Keun Cho and Myunghyun Kim:

“We consider a proxy FAVAR (Factor-Augmented Vector Autoregression) model to analyze the
impact of an oil supply news shock on the Korean economy. To identify an oil supply news shock, we
use the variation in oil futures prices around OPEC production announcements as a proxy. Moreover, we
include a factor that captures the common movement of many Korean macro variables such as various
price indices and investment. The estimation results of the proxy FAVAR model show that an oil supply
news shock increases the real oil price and the US CPI, and decreases world oil production and US GDP.
As for Korean macro variables, GDP and net exports fall and CPI increases in response to the shock.”

From a paper by Puneet Vatsa:

“I use a structural vector autoregression model to analyse the links between oil prices, petrol prices, inflation, inflation perceptions, and inflation expectations in New Zealand. Findings reveal that although inflation expectations are sensitive to shocks to oil prices, petrol prices, and inflation itself, they are considerably more sensitive to inflation perception shocks. Shocks to inflation perceptions explain 54% of the forecast error variance in inflation expectations after one quarter and 37% after 18 months. The results underscore the importance of including inflation perceptions in models seeking to account for inflation expectations and their associations with energy prices.”

From a paper by Guilherme Spinato Morlin, Marco Stamegna, and Simone D’Alessandro:

“The surge in energy prices following the Russian-Ukrainian conflict triggered the most significant inflation in advanced economies in recent decades. Using the Eurogreen model for the Italian economy, we examine the macroeconomic and distributional impacts of rising energy prices alongside two policy measures: wage indexation and a temporary housing rent cap. We compare policy scenarios with a baseline reflecting the observed price shocks. We find that: i) energy price shocks disproportionately affect lower-income individuals due to the larger share of energy goods in their consumption baskets; ii) wage indexation results in higher average real wages compared to the baseline scenario, without triggering inflation acceleration, while temporarily boosting output and employment by supporting aggregate demand; iii) a temporary housing rent cap improves distribution in workers’ favor while reducing inflation; iv) both policies have a more substantial effect for low-skilled workers; and v) best outcomes appear when these policies are jointly implemented.”

From a paper by Oussama Ritahi, and Abdellah Echaoui:

“This study examines the impact of Brent oil price shocks on key economic variables—namely inflation, GDP, exchange rate, trade openness, and unemployment rate using annual data from 1990 to 2022. The results of the study show that the variables considered under this study are cointegrated in the long-run which means that there is a relationship between these variables in the long-run. By employing a vector error correction model (VECM), we analyze the impulse response functions to understand the short- and long-term effects of oil price fluctuations on these economic indicators. Our findings reveal that Brent oil price increases lead to higher inflation and depreciation of the exchange rate, with both effects persisting in the short and long run. Conversely, GDP experiences a consistent negative impact from oil price hikes, suggesting a detrimental effect on economic growth over time. Trade openness shows a positive response, indicating increased trade activity due to rising oil prices. Additionally, the unemployment rate decreases in response to higher oil prices, reflecting a potential reduction in joblessness.”

From a paper by Jinfang Pu, and Fangzhou Xia:

“As global climate change intensifies and urbanization accelerates, research on urban climate change has become a global concern. Urban decision-makers must determine optimal city sizes to achieve net-zero emissions. However, previous studies have mainly focused on average relationships between city size and carbon emissions, overlooking non-linear dynamics. This study used urban scaling laws to investigate relationships between city size and carbon emissions from population and land perspective across 294 Chinese cities. Results showed a sub-linear relationship between urban population size (UPS) and carbon emissions and a super-linear relationship between urban land size (ULS) and carbon emissions. Regionally, cities in central regions demonstrated higher carbon emission performance than those in western and eastern regions. The land perspective indicated lower carbon emission performance compared to the population perspective. Both perspectives revealed non-linear relationships between city size and urban scaling exponent for carbon emissions, characterized by multiple minima. Multiple city sizes can achieve optimal carbon emissions; however, only one ULS is ideal for a specific city size to ensure environmental sustainability. This study provides valuable policy insights for decision-makers in formulating reasonable low-carbon strategies.”