Are Princelings Truly Busted? Evaluating Transaction Discounts in China's Land Market

This paper replicates Chen and Kung’s 2019 analysis ($The$ $Quarterly$ $Journal$ $of$ $Economics$ 134(1): 185-226). Inspecting the data reveals that nearly one-third of transactions (388,903 out of 1,208,621) are perfect duplicates of other rows, excluding the transaction number. The analysis on the data sans duplicates replicates their statistically significant princeling effect, robust across various specifications. Further analysis reveals a disagreement between Chen and Kung’s text and code: the paper’s ‘’logarithm of area’’ is actually area ($\text{m}^2$) divided by one million. This therefore necessitates a reinterpretation of the estimation results, revealing that the princeling effect is extremely large.

💡 Research Summary

This paper conducts a thorough replication and extension of Chen and Kung (2019), the seminal study that documented substantial price discounts for “princeling” firms—companies linked to relatives of senior Chinese political elites—in China’s primary land market. The author begins by scrutinizing the original transaction‑level dataset, which contains 1,208,621 observations. By stripping away the transaction identifier, she discovers that 388,903 rows (approximately 32 % of the sample) are perfect duplicates: they share the same buyer, city, month, year, land‑use code, parcel quality, area, and price. The duplication problem is especially acute for princeling transactions, where more than half of the 19,812 observations are duplicated. The paper discusses two plausible explanations—genuine simultaneous purchases of identical parcels versus erroneous multiple recordings of the same parcel—and, using the Ministry of Land’s public database, finds evidence for both, but concludes that a substantial share of the duplicates are data errors.

Armed with this diagnostic, the author creates a cleaned dataset of 819,718 unique transactions and re‑estimates the core regression model used by Chen and Kung:

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