The Unassuming Economist

From a paper by Nora Lustig and Andrea Vigorito:

“Inequality measures based on household surveys may be biased because they typically fail to capture incomes of the wealthy properly. The “missing rich” problem stems from several factors, including sampling errors, item and unit nonresponse, underreporting of income, and data preprocessing techniques like top coding. This paper presents and compares prominent correction approaches to address issues concerning the upper tail of the income distribution in household surveys. Correction approaches are classified based on the data source, distinguishing between those that rely solely on within-survey information and those that combine household survey data with external sources. We categorize the correction methods into three types: replacing, reweighting, and combining reweighting and replacing. We identify twenty-two different approaches that have been applied in practice. We show that both levels and trends can be quite sensitive to the approach and provide broad guidelines on choosing a suitable correction approach.”

From a paper by Xiaoshan Hu, Guanghua Wan, and Congmin Zuo:

“Education has long been perceived as a “great equalizer”, but even with universal rises in schooling years, income distribution worsened world-wide. We propose a method for decomposing the contribution of a variable to the change in inequality into three components: the mean, the dispersion, and the price components. The proposed method is then used to investigate the roles of the education variable in driving down China’s wage inequality between 2010 and 2018. We find that (1) education accounted for over 30% of total wage inequality in 2010 and 2018; (2) 70% of the overall decline in wage inequality from 2010 to 2018 can be attributed to education development, and (3) the 70% inequality-reducing effect was made up of 95% benign dispersion and price components and 25% malign mean component. The benign components are attributable to an improvement in educational equity and a decrease in the college premium.”

From a paper by Amaama Abdul Malik and Asad Ul Islam Khan:

“The Covid 19 pandemic was a strong shock that plummeted into the entire interconnected economic activities of the world. As a result of the lockdown associated with the pandemic, the economies of the world were affected through restrictions like lockdown leading to the reduction of economic indicators like Gross Domestic Product (GDP) and increase in Unemployment. This paper set out to look at the relationship between the GDP and unemployment in Ghana in the periods prior and during the covid pandemic. The Autoregressive Distributed Lag (ARDL) model was used on data from 1991 to 2021. The result shows the nonexistence of the Okun’s law in Ghana in each of these periods. We conclude by advising policy makers to implement policies that directly generate more jobs like improvement in the agriculture sector through training and financial support to enable increased employment to match the increase in economic growth.”

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 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.”