Statistical Discrimination, Productivity and the Height of Immigrants

Wang, Shing-Yi B.

doi:10.2139/ssrn.1851845

Cited by 3 publications

(3 citation statements)

References 37 publications

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“…Second, training has a higher return in urban areas because employers may use training as additional information with which to discern migrants’ productivities across migrants. This idea is consistent with statistical discrimination of migrants (Wang, 2015). Another possible explanation of the little impact of education is the limited variation in educational attainment among rural migrants.…”

Section: Resultssupporting

confidence: 89%

Training, skill-upgrading and settlement intention of migrants: Evidence from China

Qing

Ren

Liu³

2018

Urban Studies

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The massive rural-to-urban migration has been one of the most important features of China’s labour market in recent decades. The recent pattern of return migration and migrant wages has increased the costs of firms in urban areas and has negatively affected urbanisation. Therefore, it is important to understand the determinants of settlement intention of migrants. Using data from Rural Urban Migration in China (RUMiC), we find that migrants express higher settlement intention in a city after receiving training that is provided by firms. The effect is larger for females, high school graduates and dropouts, and wage earners. These findings suggest that training may complement migrants’ human capital and upgrade their skills. Therefore, training in cities may act as an instrument that facilitates the migration decisions and transforms a temporary migrant to a permanent resident in an urban area.

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Section: Resultssupporting

confidence: 89%

Training, skill-upgrading and settlement intention of migrants: Evidence from China

Qing

Ren

Liu³

2018

Urban Studies

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“…Altonji and Pierret provide a first important strand literature on learning models (Altonji & Pierret, 2001). We complement the studies surveyed in the recent paper (Lang & Lehmann, 2011) by mentioning: (Cheung, 2010), in testing whether parental education is used as a proxy for the ability of workers; and (Wang, 2010), in considering height as an easily observable characteristic.…”

Section: Labour Economic Perspectivementioning

confidence: 97%

Discrimination Data Analysis: A Multi-disciplinary Bibliography

Romei

Ruggieri

2013

Studies in Applied Philosophy, Epistemology and Rational Ethics

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Discrimination data analysis has been investigated for the last fifty years in a large body of social, legal, and economic studies. Recently, discrimination discovery and prevention has become a blooming research topic in the knowledge discovery community. This chapter provides a multi-disciplinary annotated bibliography of the literature on discrimination data analysis, with the intended objective to provide a common basis to researchers from a multi-disciplinary perspective.We cover legal, sociological, economic and computer science references

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“…(2010); Lang and Manove (2011), who correlate, through a median regression, the level of education across races with a worker's ability, measured by the AFQT test; Fadlon (2011), using OLS regression in extending the theoretical model to account for employer–employee racial matches; Cheung (2010), analyzing data from the Australian NLSY partitioned by the hiring channel 16 . Finally, Wang (2010) considers the height of immigrant workers as grounds for discrimination, and investigates whether it is used as a signal of productivity by employers.…”

Section: Observational Studies I: Labor Economic Perspectivementioning

confidence: 99%

A multidisciplinary survey on discrimination analysis

Romei

Ruggieri

2013

The Knowledge Engineering Review

234

173

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The collection and analysis of observational and experimental data represent the main tools for assessing the presence, the extent, the nature, and the trend of discrimination phenomena. Data analysis techniques have been proposed in the last fifty years in the economic, legal, statistical, and, recently, in the data mining literature. This is not surprising, since discrimination analysis is a multi-disciplinary problem, involving sociological causes, legal argumentations, economic models, statistical techniques, computational issues. The objective of this survey is to provide a guidance and a glue for researchers and anti-discrimination data analysts on concepts, problems, application areas, datasets, methods and approaches from a multidisciplinary perspective. We organize the approaches according to their method of data collection as observational, quasi-experimental and experimental studies. A fourth line of recently blooming research on knowledge discovery based methods is also covered. Observational methods are further categorized on the basis of their application context: labor economics, social profiling, consumer markets, and others.

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Statistical Discrimination, Productivity and the Height of Immigrants

Cited by 3 publications

References 37 publications

Training, skill-upgrading and settlement intention of migrants: Evidence from China

Training, skill-upgrading and settlement intention of migrants: Evidence from China

Discrimination Data Analysis: A Multi-disciplinary Bibliography

A multidisciplinary survey on discrimination analysis

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