劳动力迁移对教育回报率阶层差异及收入差距的影响——采用“中国劳动力动态调查”数据的实证分析
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摘要
基于"中国劳动力动态调查"数据分析表明,我国的教育回报率存在明显的收入阶层差异,其总体上随收入水平的上升而增加,且低收入阶层与其他收入阶层差距较大,中等收入阶层的高等教育回报率最高;劳动力迁移能显著提升接受高等教育的中、高收入群体和接受中等教育的中等收入群体的教育回报率,进而强化其收入优势;教育回报率差异对收入差距的贡献比受教育水平分布不均更大,劳动力迁移总体上有助于缩小与个体受教育(特别是高等教育)差异相关的收入差距。因此,教育资源的分配要有利于提升低收入群体的教育层次,并清除阻碍劳动力迁移的制度障碍,以缩减由个体受教育差异引致的收入差距。
The analysis based on the China Labor-force Dynamic Survey data shows that China's education return rate has significant difference in income hierarchies,that the education return rate rises with the rising of income level as a whole,that there is big difference between lower income hierarchy and other income levels,that the education return rate of middle income hierarchy is the highest,and that the labor immigration can obviously promote the education return rate for receiving high education of middle and high income groups and for receiving middle education of middle income group to further strengthen their income advantages. The contribution of education return rate to income difference is more uneven than education level,as a whole,the labor immigration is conducive to narrowing the income gap related to individual education( especially high education). Thus,the allocation of education resources should be helpful to raise the education level of lower income groups,we should eliminate the systematic barrier resisting labor immigration to narrow the income gap resulting from the difference in individual education.
The analysis based on the China Labor-force Dynamic Survey data shows that China's education return rate has significant difference in income hierarchies,that the education return rate rises with the rising of income level as a whole,that there is big difference between lower income hierarchy and other income levels,that the education return rate of middle income hierarchy is the highest,and that the labor immigration can obviously promote the education return rate for receiving high education of middle and high income groups and for receiving middle education of middle income group to further strengthen their income advantages. The contribution of education return rate to income difference is more uneven than education level,as a whole,the labor immigration is conducive to narrowing the income gap related to individual education( especially high education). Thus,the allocation of education resources should be helpful to raise the education level of lower income groups,we should eliminate the systematic barrier resisting labor immigration to narrow the income gap resulting from the difference in individual education.
引文
[1] CARD D. The causal effect of education on earnings[J].Handbook of Labor Economics,1999(3):1801-1863.
[2]杨俊,黄潇,李晓羽.教育不平等与收入分配差距:中国的实证分析[J].管理世界,2008(1):38-47.
[3] MINCER JA. Age and experience profiles of earnings[M]. NBER Chapters,1974:64-82.
[4] BUCHINSKY M. Changes in the U.S. wage structure 1963—1987:Application of quantile regression[J]. Econometrica,1994,62(2):405-458.
[5] MWABU G,SCHULTZ T P. Education returns across quantiles of the wage function:Alternative explanations for returns to education by race in South Africa[J].The American Economic Review,1996,86(2):335-339..
[6] BUCHINSKY M. The dynamics of changes in the female wage distribution in the USA:A quantile regression approach[J].Journal of Applied Econometrics,1998,13:1-30.
[7] STAVENA A,ARABSHEIBANI G,MURPHY R P. Returns to education in four transition countries:Quantile regression approach[J]. IZA Discussion Paper,2010,No 5210:1-34.
[8] MARTINS P S,PERIRA P T. Does education reduce wage inequality? Quantile regression evidence from 16 countries[J]. Labor Economics,2004,11:355-371.
[9]张车伟.人力资本回报率变化与收入差距:马太效应及其政策含义[J].经济研究,2006(12):59-70.
[10]邓曲恒.城镇居民与流动人口的收入差异[J].中国人口科学,2007(2):8-16.
[11]邢春冰.中国不同所有制部门的工资决定与教育回报:分位数回归的证据[J].世界经济文汇,2006(04):1-26.
[12]张涛.工资收入差异的解释:基于分位数回归的经验研究[J].统计与信息论坛,2011(11):50-56.
[13] BASSETT G,CHEN H. Economic applications of quantile regression[M]. Physica-Verlag HD,2002:293-305.
[14] LESLEY T. The returns to higher education for marginal students:Evidence from Colorado welfare recipients[J]. Economics of Education Review,2015(9):1-16.
[15] MAGDALENA T D. Estimate of the private return on education in Indonesia:Evidence from sibling data[J]. International Journal of Educational Development,2015,42:14-24.
[16] KNIGHT J,SONG L. Increasing urban wage inequality in China[J]. Economics of Transition,2003,1:597-619.
[17] GOEDHUYS M,SLEUWAEGEN L. High-growth entrepreneurial firms in Africa:A quantile regression approach[J]. Small Business Economics,2010,34:31-51.
[18]徐舒.技术进步、教育收益与收入不平等[J].经济研究,2010(9):79-92.
[19]邵宜航,汪宇娟,刘雅南.劳动力流动与收入差距演变:基于我国城市的理论与实证[J].经济学家,2016(1):33-41.
[20]甄小鹏,凌晨.农村劳动力流动对农村收入及收入差距的影响[J].经济学(季刊),2017,16(3):1073-1096.
[21]樊士德,姜德波.劳动力流动与地区经济增长差距研究[J].中国人口科学,2011(2):27-38.
[22]彭国华.技术能力匹配、劳动力流动与中国地区差距[J].经济研究,2015(1):99-110.
[23]邢春冰,贾淑艳,李实.教育回报率的地区差异及其对劳动力流动的影响[J].经济研究,2013(11):114-126.
[24]赵西亮.教育、户籍转换与城乡教育收益率差异[J].经济研究,2017(12):150-163.
[25] ABADIE A,ANGRIST J,IMBENS G. Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings[J].Econometrica,2002,70(1):91-117.
[26]张苏,曾庆宝.教育的人力资本代际传递效应述评[J].经济学动态,2011(8):127-132.
[27] FIRPO S. Efficient semiparametric estimation of quantile treatment effects[J]. Econometrica,2007,75(1):259-276.
[28]孙三百,黄薇,洪俊杰.劳动力自由迁移为何如此重要——基于代际收入流动的视角[J].经济研究,2012(5):147-159.
[29] HECKMAN J,URZUA S,VYTLACIL E. Understanding instrument variables in models with essential heterogeneity[J]. Review of Economics and Statistics,2006,88:389-432.
[30]陆铭,高虹,佐藤宏.城市规模与包容性就业[J].中国社会科学,2012(10):47-66.
(1)为尽可能地保留真实的现实经济活动信息,本文并不是简单按照年龄(男性≥60、女性≥55)来进行划分,而是按照其实际经济活动能力进行划分,认定条件为“收入仅来源于退休工资且未从事其他生产性经营活动”。
(1)考虑到CLDS 2014的样本数据更新,因此主要采用该年度的数据进行分析;引入CLDS 2012样本主要出于分析劳动力迁移对收入差距的影响时构建反事实收入分布函数的需要。
(2)CLDS对非货币收入的统计相对完备,据此可计算出受访者个体的实物收入; CLDS对于财产性收入的统计缺失较多,本文在统计时未将其考虑在内。
(3)我国现行的硕士研究生有专硕和学硕之分,二者的学制不一样(前者为两年、后者为三年),问卷中也对此进行了区分,但考虑到获得该层次教育的样本占比较少,因此不进行划分,取其均值18. 5年。
(1)这种情形下传统OLS模型的估计是有偏的。因为具备大学学历群体与和不具备大学学历群体可能具有不同的特征,而是否上大学又在很大程度上与这些特征相关,且这些特征(如禀赋、家庭文化等)会对收入产生影响。
(2)只要受访者父亲或母亲任意一方受过大学教育,则认为其父母具备大学教育背景。
[2]杨俊,黄潇,李晓羽.教育不平等与收入分配差距:中国的实证分析[J].管理世界,2008(1):38-47.
[3] MINCER JA. Age and experience profiles of earnings[M]. NBER Chapters,1974:64-82.
[4] BUCHINSKY M. Changes in the U.S. wage structure 1963—1987:Application of quantile regression[J]. Econometrica,1994,62(2):405-458.
[5] MWABU G,SCHULTZ T P. Education returns across quantiles of the wage function:Alternative explanations for returns to education by race in South Africa[J].The American Economic Review,1996,86(2):335-339..
[6] BUCHINSKY M. The dynamics of changes in the female wage distribution in the USA:A quantile regression approach[J].Journal of Applied Econometrics,1998,13:1-30.
[7] STAVENA A,ARABSHEIBANI G,MURPHY R P. Returns to education in four transition countries:Quantile regression approach[J]. IZA Discussion Paper,2010,No 5210:1-34.
[8] MARTINS P S,PERIRA P T. Does education reduce wage inequality? Quantile regression evidence from 16 countries[J]. Labor Economics,2004,11:355-371.
[9]张车伟.人力资本回报率变化与收入差距:马太效应及其政策含义[J].经济研究,2006(12):59-70.
[10]邓曲恒.城镇居民与流动人口的收入差异[J].中国人口科学,2007(2):8-16.
[11]邢春冰.中国不同所有制部门的工资决定与教育回报:分位数回归的证据[J].世界经济文汇,2006(04):1-26.
[12]张涛.工资收入差异的解释:基于分位数回归的经验研究[J].统计与信息论坛,2011(11):50-56.
[13] BASSETT G,CHEN H. Economic applications of quantile regression[M]. Physica-Verlag HD,2002:293-305.
[14] LESLEY T. The returns to higher education for marginal students:Evidence from Colorado welfare recipients[J]. Economics of Education Review,2015(9):1-16.
[15] MAGDALENA T D. Estimate of the private return on education in Indonesia:Evidence from sibling data[J]. International Journal of Educational Development,2015,42:14-24.
[16] KNIGHT J,SONG L. Increasing urban wage inequality in China[J]. Economics of Transition,2003,1:597-619.
[17] GOEDHUYS M,SLEUWAEGEN L. High-growth entrepreneurial firms in Africa:A quantile regression approach[J]. Small Business Economics,2010,34:31-51.
[18]徐舒.技术进步、教育收益与收入不平等[J].经济研究,2010(9):79-92.
[19]邵宜航,汪宇娟,刘雅南.劳动力流动与收入差距演变:基于我国城市的理论与实证[J].经济学家,2016(1):33-41.
[20]甄小鹏,凌晨.农村劳动力流动对农村收入及收入差距的影响[J].经济学(季刊),2017,16(3):1073-1096.
[21]樊士德,姜德波.劳动力流动与地区经济增长差距研究[J].中国人口科学,2011(2):27-38.
[22]彭国华.技术能力匹配、劳动力流动与中国地区差距[J].经济研究,2015(1):99-110.
[23]邢春冰,贾淑艳,李实.教育回报率的地区差异及其对劳动力流动的影响[J].经济研究,2013(11):114-126.
[24]赵西亮.教育、户籍转换与城乡教育收益率差异[J].经济研究,2017(12):150-163.
[25] ABADIE A,ANGRIST J,IMBENS G. Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings[J].Econometrica,2002,70(1):91-117.
[26]张苏,曾庆宝.教育的人力资本代际传递效应述评[J].经济学动态,2011(8):127-132.
[27] FIRPO S. Efficient semiparametric estimation of quantile treatment effects[J]. Econometrica,2007,75(1):259-276.
[28]孙三百,黄薇,洪俊杰.劳动力自由迁移为何如此重要——基于代际收入流动的视角[J].经济研究,2012(5):147-159.
[29] HECKMAN J,URZUA S,VYTLACIL E. Understanding instrument variables in models with essential heterogeneity[J]. Review of Economics and Statistics,2006,88:389-432.
[30]陆铭,高虹,佐藤宏.城市规模与包容性就业[J].中国社会科学,2012(10):47-66.
(1)为尽可能地保留真实的现实经济活动信息,本文并不是简单按照年龄(男性≥60、女性≥55)来进行划分,而是按照其实际经济活动能力进行划分,认定条件为“收入仅来源于退休工资且未从事其他生产性经营活动”。
(1)考虑到CLDS 2014的样本数据更新,因此主要采用该年度的数据进行分析;引入CLDS 2012样本主要出于分析劳动力迁移对收入差距的影响时构建反事实收入分布函数的需要。
(2)CLDS对非货币收入的统计相对完备,据此可计算出受访者个体的实物收入; CLDS对于财产性收入的统计缺失较多,本文在统计时未将其考虑在内。
(3)我国现行的硕士研究生有专硕和学硕之分,二者的学制不一样(前者为两年、后者为三年),问卷中也对此进行了区分,但考虑到获得该层次教育的样本占比较少,因此不进行划分,取其均值18. 5年。
(1)这种情形下传统OLS模型的估计是有偏的。因为具备大学学历群体与和不具备大学学历群体可能具有不同的特征,而是否上大学又在很大程度上与这些特征相关,且这些特征(如禀赋、家庭文化等)会对收入产生影响。
(2)只要受访者父亲或母亲任意一方受过大学教育,则认为其父母具备大学教育背景。