Can Two Consecutive Generations’ Data Predict Longterm Intergenerational Transition? Evidence from China with three generations
He Zhu and
Additional contact information
He Zhu: Graduate student of Osaka School of International Public Policy, Osaka University
Tsunehiro Otsuki: Professor, Osaka School of International Public Policy, Osaka University
No 18E004, OSIPP Discussion Paper from Osaka School of International Public Policy, Osaka University
Most of the studies on long-term intergenerational human capital transition are restricted to two consecutive generations based on the Becker-Tomes model, and assume that the transition will be wiped out during the third generation. However, in developing countries such as China, ancestors play a key role in the family decision-making process. Thus, this research uses a data set of China rural households, which includes three generations of data,to analyze the long-term intergenerational transition. The results provide empirical evidence that separate generations have had an independent and significant influence on the offspring’s human capital outcome. Precisely, the grandparent generation influences the child generation independently rather than influencing the child generation through the parent generation. Therefore, the influence of generations on educational achievements has been overestimated by the data that only encompass two consecutive generations.
JEL-codes: O14 J62 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cna, nep-gro and nep-tra
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:osp:wpaper:18e004
Access Statistics for this paper
More papers in OSIPP Discussion Paper from Osaka School of International Public Policy, Osaka University Contact information at EDIRC.
Bibliographic data for series maintained by Akiko Murashita ().