Labor market penalties for foreign degrees among college educated immigrants

Supporting College Choice Among International Students through Collaborative Filtering

In this paper we use historic score-reporting records and test-taker metadata to inform data-driven recommendations that support international students in their choice of undergraduate institutions for study in the United States. We investigate the use of Structural Topic Modeling (STM) as a context-aware, probabilistic recommendation method that uses test-takers' selections and metadata to model the latent space of college preferences. We present the model results from two perspectives: 1) to understand the impact of TOEFL score and test year on test-takers' preferences and choices and 2) to recommend to the test-taker additional undergraduate institutions for application consideration. We find that TOEFL scores can explain variance in the probability that test-takers belong to certain preference-groups and, by accounting for this, our system adjusts recommendations based on student score. We also find that the inclusion of year, while not significantly altering recommendations, does enable us to capture minor changes in the relative popularity of similar institutions. The performance of this model demonstrates the utility of this approach for providing students with personalized college recommendations and offers a useful baseline approach that can be extended with additional data sources.

Vertical Education-Occupation Mismatch and Wage Inequality by Race/Ethnicity and Nativity among Highly Educated US Workers

Despite remarkable educational gains of minorities, ethnoracial wage inequality persists and has even expanded among highly educated workers. Conventional explanations for this inequality are primarily derived from comparing workers across different educational levels and are less salient for understanding inequalities within the highly educated workforce. This study examines a previously overlooked source of ethnoracial inequality among highly educated workers: vertical mismatch between workers' educational level and the education requirements for their occupation. Using a longitudinal sample of college graduates from the Survey of Income and Program Participation, we find that vertical mismatch accounts for a large part of racial/ethnic and nativity wage inequality. Specifically, highly educated minorities (especially blacks and Hispanics) and immigrants (especially those holding a foreign degree) are disproportionately channeled into mismatched jobs and subsequently consigned to such positions. Also, highly educated Hispanics and Asians, as well as foreign-educated immigrants, face greater wage penalties of vertical mismatch. The findings offer new insights into a key source of ethnoracial and nativity stratification.

Economic Integration of Skilled Migrants in Japan: The Role of Employment Practices

Scholars argue that institutional arrangements shape migrants’ economic integration trajectories, and yet few studies empirically substantiate this. This study identifies employment institutions in Japan that affect skilled foreign workers. We demonstrate that practices ostensibly introduced to benefit these workers are associated with lower pay, after adjusting for human capital and firm characteristics. High levels of gender inequality also severely disadvantage female skilled migrants. These findings demonstrate that in the Japanese case, detrimental employment institutions often cancel out skilled foreign workers’ returns to human capital. The results may explain why Japan has failed to attract and retain more skilled migrants.

Staying in STEM or changing course: Do natives and immigrants pursue the path of least resistance?

This paper examines why Science, Technology, Engineering and Math (STEM) fields are becoming "immigrant" fields of study as native students shift from STEM fields to law, medicine and business. Using data from the 2010 National Survey of College Graduates, the analyses find that foreign college-educated immigrants with STEM degrees tend to remain in STEM fields, while natives are more likely to shift from STEM fields to law, medicine and business in graduate school. Among those who moved into law, medicine and business, the gains in earnings are larger for natives than for foreign educated immigrants. These results have important implications for the social mobility of highly educated natives and immigrants.

Her earnings: Exploring variation in wives' earning contributions across six major Asian groups and Whites

Previous research on understanding race-ethnic differentials in employment and economic contributions by married women has primarily focused on Blacks, Hispanics, or Whites. This study investigates variations in wives' earning contributions as measured by wives earnings as a proportion of total annual household earnings among six Asian groups, Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese relative to native born non-Hispanic White. I disaggregate the six Asian groups by their ethnicity and nativity status. Using pooled data from 2009-2011 American Community Survey, the findings show significance of human capital, hours of paid labor market engagement and nativity status. There is strong and negative association between husbands' human capital and labor supply with wives' earning contributions suggesting near universality of male-breadwinner status. Notwithstanding the commonalities, there is significant intergroup diversity. While foreign born and native born Filipina wives despite their spouses' reasonably high human capital and work hours, contribute one of the highest shares, the same cannot be said for the Asian Indians and Japanese. For foreign born Asian Indian and to some extent Japanese women, their high human capital is not translated to high earning contribution after controlling for husband's human capital. Further, nativity status impacts groups differentially. Native born Vietnamese wives contribute the greatest. Overall, the findings underscore the relevance of employing multiple conceptual frameworks in understanding earning contributions of foreign and native born Asian wives belonging to the six Asian groups, Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese.