2015
DOI: 10.1080/00036846.2015.1085642
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Returns to schooling for urban and migrant workers in China: a detailed investigation

Abstract: This paper uses a new dataset, the 2009 Rural Urban Migration in China (RUMiC) to estimate returns to schooling in China using an instrumental variable (IV) methodology. After identifying a set of instruments, we conduct comprehensive validity and relevance testing of different combinations of instruments as well as robustness analysis of our estimates for rural to urban migrants and urban residents in China. We find that our estimates are in a fairly tight band for all four sub-samples examined (urban men, ur… Show more

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Cited by 7 publications
(5 citation statements)
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“…More precisely, the rate increased from 2.2% in 1989 to 10.3% in 2009 for women, but only from 2.6% to 7% for men. Additionally, these increased returns to schooling since the mid-1990s have been recorded in a large number of studies that used non-CHIP or non-CHNS survey datasets, including studies on rural workers (De Brauw and Rozelle 2008); migrant workers (Meng and Zhang 2001;Maurer-Fazio and Dinh 2004;De Brauw and Rozelle 2008;Deng and Li 2010;Frijters, Lee, and Meng 2010;Sakellariou and Fang 2016); and urban workers using the Chinese Twins Survey dataset (Li, Liu, Ma, and Zhang 2005;Zhang, Liu, and Yung 2007;Li et al 2007;; CULS (Giles, Park, and Wang 2008;Cai and Du 2011;Gao and Smyth 2015); and CUHIES (Meng, Shen, and Xue 2013).…”
Section: Literature Review: What Do We Know About Returns To Education In the People's Republic Of China?mentioning
confidence: 99%
See 2 more Smart Citations
“…More precisely, the rate increased from 2.2% in 1989 to 10.3% in 2009 for women, but only from 2.6% to 7% for men. Additionally, these increased returns to schooling since the mid-1990s have been recorded in a large number of studies that used non-CHIP or non-CHNS survey datasets, including studies on rural workers (De Brauw and Rozelle 2008); migrant workers (Meng and Zhang 2001;Maurer-Fazio and Dinh 2004;De Brauw and Rozelle 2008;Deng and Li 2010;Frijters, Lee, and Meng 2010;Sakellariou and Fang 2016); and urban workers using the Chinese Twins Survey dataset (Li, Liu, Ma, and Zhang 2005;Zhang, Liu, and Yung 2007;Li et al 2007;; CULS (Giles, Park, and Wang 2008;Cai and Du 2011;Gao and Smyth 2015); and CUHIES (Meng, Shen, and Xue 2013).…”
Section: Literature Review: What Do We Know About Returns To Education In the People's Republic Of China?mentioning
confidence: 99%
“…First, recent research has employed an instrumental variable (IV) approach to solve the endogeneity bias in educational attainment. 6 For the PRC, the IV estimates were higher than the corresponding ordinary least squares (OLS) estimates (Fleisher and Wang 2004;Heckman and Li 2004;Li and Luo 2004;Fleisher et al 2005;Fleisher and Wang 2005;Zhang, Liu, and Yung 2007;Giles, Park, and Wang 2008;Chen and Hamori 2009;Zhong 2011;Fang et al 2012;Kang and Peng 2012;Wang 2012;Mishra and Smyth 2013;Wang 2013;Gao and Smyth 2015;Mishra and Smyth 2015;Sakellariou and Fang 2016). Most of these studies used family-background variables to estimate the IV model.…”
Section: Literature Review: What Do We Know About Returns To Education In the People's Republic Of China?mentioning
confidence: 99%
See 1 more Smart Citation
“…More precisely, the rate increased from 2.2% in 1989 to 10.3% in 2009 for women, but only from 2.6% to 7% for men. Additionally, these increased returns to schooling since the mid-1990s have been recorded in a large number of studies that used non-CHIP or non-CHNS survey datasets, including studies on rural workers (De Brauw and Rozelle 2008); migrant workers (Meng and Zhang 2001;Maurer-Fazio and Dinh 2004;De Brauw and Rozelle 2008;Deng and Li 2010;Frijters, Lee, and Meng 2010;Sakellariou and Fang 2016); and urban workers using the Chinese Twins Survey dataset (Li, Liu, Ma, and Zhang 2005;Zhang, Liu, and Yung 2007;Li et al 2007;; CULS (Giles, Park, and Wang 2008;Cai and Du 2011;Gao and Smyth 2015); and CUHIES (Meng, Shen, and Xue 2013).…”
Section: Introductionmentioning
confidence: 97%
“…Attempting to correct for ability bias and measurement error, most articles estimate returns to schooling in an Instrumental Variables (IV) framework using compulsory schooling laws and educational background variables as instruments. Estimates range widely, from large positive returns (Harmon & Walker, 1995;Oreopoulos, 2006;Wang, 2013, Winters, 2015, through moderate positive returns (Angrist & Krueger, 1991;Devereux & Fan, 2011;Sakellariou & Fang, 2016), to no returns to schooling at all (Grenet, 2013;Meghir & Palme, 2005;Oosterbeek & Webbink, 2007;Pischke & von Wachter, 2008;Stephens & Yang, 2014). The conventional practice in the literature is to consider education as a continuous variable measuring the number of years of schooling.…”
Section: Introductionmentioning
confidence: 99%