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Yu Xie

Researcher at Princeton University

Publications -  197
Citations -  15556

Yu Xie is an academic researcher from Princeton University. The author has contributed to research in topics: China & Population. The author has an hindex of 52, co-authored 180 publications receiving 12934 citations. Previous affiliations of Yu Xie include University of Michigan & University of Wisconsin-Madison.

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The influences of family background and structural factors on children’s academic performances: A cross-country comparative study:

TL;DR: It is well known that children's academic performances are affected by both their family backgrounds and contextual or structural factors such as the urban-rural difference and regional variation as discussed by the authors...
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Short-term trends in China’s income inequality and poverty: evidence from a longitudinal household survey

TL;DR: Surprisingly, there is a modest decline in income inequality as measured by the Gini coefficients in the CFPS data, and the urban–rural gap narrowed, with rural families enjoying faster income growth than urban families enjoyed.
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An Alternative Purging Method: Controlling the Composition-Dependent Interaction in an Analysis of Rates

TL;DR: An alternative method is proposed, partial CD purging, that controls the interaction between composition and the dependent variable, and the purged rates from this new method are invariant to changes in the marginal distribution of composition.
Posted Content

HTE: Stata module to perform heterogeneous treatment effect analysis

TL;DR: In this article, Xie, Brand, and Jann proposed three methods, the stratification-multilevel method, the matching-smoothing method, and the smoothing-differencing method, for heterogeneous treatment effect analysis.
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Ethnic enclaves revisited: Effects on earnings of migrant workers in China.

TL;DR: It is found that migrants with a high propensity to work in an enclave benefit more from enclave participation than those with a low propensity, and this effect is smaller than that resulting from a naïve comparison.