International Migration with Heterogeneous Agents: Theory and Evidence for Germany, 1967-2009

By Herbert Brücker, Philipp J. H. Schröder. 2006

326 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Sociology and Political Science

Citations in the corpus

• Delayed Impact of Fair Machine Learning (2018, neutral): “Knowles et al. (2001) consider a more dynamic model in which individuals react to their probabilities of being searched.”
• The Problem of Infra-marginality in Outcome Tests for Discrimination (2016, neutral): “Though originally proposed in the context of lending decisions, outcome tests have gained popularity in a variety of domains, particularly policing (Goel et al., 2016, 2017; Ayres, 2002; Knowles et al., 2001).”
• Racial Disparity in Federal Criminal Sentences (2014, unknown): “bias against minority suspects ðe.g., Gelman, Fagan, and Kiss 2007Þ, although there is considerable debate as to whether these are driven by statistical or preference-based discrimination ðe.g., Knowles, Persico, and Todd 2001; Antonovics and Knight 2009Þ.”
• You can win but I can't lose: Bias against high-status groups increases their zero-sum beliefs about discrimination (2015, unknown): “Despite the fact that Whites are better off than Blacks according to most metrics (e.g. Bertrand & Mullainathan, 2004; Knowles, Persico, & Todd, 2001; Pettit, 2012; also seeNorton & Sommers, 2011 ) and men continue to make more money and occupy greater positions of power than women (Cohen, 2013),…”
• Assessing the Effect of Race Bias in Post-traffic Stop Outcomes Using Propensity Scores (2006, unknown): “Other authors have covered that topic well (see Knowles et al., 2001 ).”
• Testing for Racial Profiling in Traffic Stops From Behind a Veil of Darkness (2006, unknown): “Knowles, Persico, and Todd (2001) showed that in an environment in which police seek to maximize arrests, the equality of hit rates by race implies that police do not intentionally discriminate.”
• Pretrained AI Models: Performativity, Mobility, and Change (2019, unknown): “For fairness specifically, there are even batteries of statistical tests that could be administered as pretrained models move into new applications [8, 43], but their deployment may be improved by greater understanding of the self-fulfilling prophecy of Barnesian performativity.”