The Unassuming Economist

From a paper by Yoosoon Chang, Soyoung Kim, Joon Y. Park:

“This paper investigates the interactions between macroeconomic aggregates and income distribution by developing a structural VAR model with functional variables. With this novel empirical approach, we are able to identify and analyze the effects of various shocks to the income distribution on macro aggregates, as well as the effects of macroeconomic shocks on the income distribution. Our main findings are as follows: First, contractionary monetary policy shocks reduce income inequality when focusing solely on the redistributive effects, without considering the negative impact on aggregate income levels. This improvement is achieved by reducing the number of low and high-income families while increasing the proportion of middle-income families. However, when the aggregate income shift is also taken into account, contractionary monetary policy shocks worsen income inequality. Second, shocks to the income distribution have a substantial effect on output fluctuations. For example, income distribution shocks identified to maximize future output levels have a significant and persistent positive effect on output, contributing up to 30% at long horizons and over 50% for the lowest income percentiles. However, alternative income distribution shocks identified to minimize the future Gini index do not have any significant negative effects on output. This finding, combined with the positive effect of output-maximizing income distribution shocks on equality, suggests that properly designed redistributive policies are not subject to the often-claimed trade-off between growth and equality. Moreover, variations in income distribution are primarily explained by shocks to the income distribution itself, rather than by aggregate shocks, including monetary shocks. This highlights the need for redistributive policies to substantially alter the income distribution and reduce inequality.”

From a paper by Xiaoke Zhu, and Xiaohua Yu:

“This study aims to investigate whether and how food inflation influences U.S. macroeconomic dynamics. To this end, we develop and estimate a heterogeneous dynamic stochastic general equilibrium (DSGE) model incorporating both the food and non-food sectors. Calibration and Bayesian estimation methods are employed to derive the key parameters involved in this model. Our analysis reveals that key macroeconomic variables exhibit significant nonlinear responses to food price shocks. Notably, a quarter of headline inflation can be attributed to food inflation in the post-pandemic era. Furthermore, a higher labor substitution parameter and lower consumption substitution elasticity amplify the economic recession. In response to food price shocks, moderate monetary policies can mitigate declines in real GDP and consumption but potentially exacerbate inflation.”

From a paper by Shuang Wang, Yan Wang, and Jing Li:

“Crude oil is a critical resource for modern industrialized societies and is heavily affected by geopolitical factors. However, existing studies on oil security assessment often overlook the interdependence among evaluation indicators and dimensions, leading to biased estimations. Furthermore, few studies have examined the varying impacts of geopolitical risks on oil security, ignoring potential heterogeneous impacts. To address these gaps, we propose a novel analytical framework. First, we introduce an innovative approach to evaluate oil security using a refined multi-level nested copula, which captures the dependence structure among indicators and dimensions. Second, we employ copula functions to explore how geopolitical risks affect a nation’s oil security and uncover their transmission channels. Empirical analysis using data from China shows that geopolitical risks significantly weaken oil security, with a symmetric tail dependence between them, indicating consistent effects regardless of geopolitical fluctuations. Moreover, we identify diminishing supply security as the primary pathway through which geopolitical risks impact oil security. These findings offer valuable policy insights for strengthening energy security amidst geopolitical uncertainties.”

From a paper by Dong-Hyeon Kim, Peiyao Liu, Shu-Chin Lin:

“Rising income and wealth inequality have renewed interest in their determinants, positioning the financial sector as a central focus of the ongoing debate. Nevertheless, controversy persists regarding the relationship between financial development and economic inequality. While much of the empirical literature focuses on income inequality, wealth inequality has received comparatively less attention. Given the extreme concentration of wealth and its influence on economic opportunity and political power, this paper explores whether it is excessive or insufficient financial development that contributes to the widening disparities in wealth distribution. Using a cross-country panel data framework, the study finds that financial development exacerbates wealth inequality by increasing wealth concentration at the top and diminishing wealth shares in the bottom 50% up to a certain threshold. Beyond this point, financial development results in a reduction of top wealth shares and an increase in the wealth shares of the bottom 50%, thereby narrowing wealth inequality. A similar pattern is observed for income inequality. Pathway analyses indicate that these effects are partially mediated through entrepreneurship. Insufficient financial development adversely impacts both wealth and income distribution.”

From a paper by Liesel A. Ritchie, Susan L. Cutter, Nnenia Campbell, Melanie Gall:

“In the United States, segments of the population were suddenly and unexpectedly thrown into need during the COVID-19 pandemic and began to use food banks and other non-profit organizations providing food services. Here we examine the meaning of what we call the “new vulnerable.” The pandemic became a test of the entire food system, and clearly exposed the need for a re-examination of preparedness in the short run, and vulnerability and resilience in the long term. We explore whether the demographics associated with the drivers of vulnerability (e.g., ageism, racism, ethnocentrism) have changed. The lived experiences of vulnerable groups are defined by a form of epistemic and structural injustice—the dismissal of the knowledge of their own lives and needs that socially marginalized groups experience.”