This article examines the mismatch among U.S. immigrants and native-born workers, using the National Survey of College Graduates data in 2017- 2021. I compare the wage effects between immigrants and native-born workers. The results indicate that immigrants have similar returns to education compared to the native-born in the years. However, during the pandemic period, it appears that immigrants outperformed native-born in terms of returns to education. This study also uses the multinomial logit model to examine the likelihood of job mismatch based on the proportion of related jobs. The results show that two groups with related jobs are likely to earn higher wages and returns on education. By race, White Americans are more likely to have related jobs. Immigrants with either a bachelor’s or master’s degree tend to have a similar percentage of jobs related to their field of study as those who were born in that country. On the other hand, native-borns with professional degrees are more likely to have related jobs. Additionally, a comparison of those who study computer science & mathematics, and engineering fields shows a greater possibility of job-relatedness than those in non-S&E and social science. Immigrants who are overeducated for their jobs show a significant drop in earnings compared to their native-born counterparts between 2017 and 2019. In 2021, both workers experienced an increase in the wage penalty. Therefore, the wage penalty due to overeducation is relatively large for immigrants.

Keywords: Educational mismatch, Overeducation, Wages Panelty, Occupation 

 This study examines how non-economic factors influence Korean family migration to the United States. Using 1990 and 2000 micro-level household data, it challenges the neoclassical theory's assumption that immigration maximizes human capital. Results show no significant link between the expected income gap and immigration likelihood. This suggests neoclassical economic theories may not fully explain Korea-to-U.S. immigration. Instead, non-economic factors like network theory and family reunion play a crucial role. Though focused on Korean immigrants to the U.S., this study's insights can inform analyses of other Asian immigration streams to North America. It underscores the need for interdisciplinary approaches to understand the multifaceted nature of migration.

Keywords: International migration, Korean family migration, non-economic motivation; structural probit model

This study constructs Divisia monetary aggregates for the “Asian Tigers”—Hong Kong (1999-2024), South Korea (2009-2024), Singapore (1991-2021), and Taiwan (2005-2024) and assesses whether Divisia monetary aggregates explain Nominal GDP better than simple sum money. Our findings demonstrate that Divisia indices respond more sensitively to economic shocks. For Hong Kong and Taiwan, narrow Divisia money provides the best explanations for fluctuations in nominal GDP. Our results suggest that Divisia monetary aggregates can be beneficial for monetary policy analysis in these countries and underscore the importance of further research into the empirical performance of Divisia monetary aggregates in macroeconomic prediction.

Keywords: Divisia index; Divisia monetary aggregates; Vector error correction model