NUS academics distance themselves from study on civil servants' home purchases near unannounced MRT stations

The two professors say they have asked the authors to have their names removed from the paper’s acknowledgements.

This general view shows a private residential complex and the financial district in Singapore. (File photo: AFP/Roslan Rahman)

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SINGAPORE: Two National University of Singapore (NUS) professors Ivan Png and Jessica Pan said on Tuesday (Sep 15) they knew nothing of a working paper alleging "informed trading by civil servants" and have asked the authors to remove their names from its acknowledgements.

Two other NUS academics named in the paper, Sumit Agarwal and Wenlan Qian, referred CNA to the authors. A fifth NUS academic, Professor David Reeb, said he may have made a comment or asked a question when an earlier version of the paper was presented years ago.

Prof Png, who is a Distinguished Professor at NUS, told CNA he was puzzled to have been thanked in the paper, which examined property purchases by public officials near MRT stations whose locations had not yet been made public.

“I do not know the authors and did not know of their paper until a colleague referred me to the CNA report, following which I received a stream of WhatsApp messages from friends,” he said.

Prof Png, whose research interests include the economics of productivity and innovation, said he provided neither comments nor data for the study.

“Please remove my name from the acknowledgements,” he wrote to the lead author of the study in an email seen by CNA.

Prof Pan, who is vice-provost for graduate education at NUS, said her name appeared by "mistake". "I only found out about the paper today and have asked the authors to remove my name from the acknowledgements," she said.

CNA has contacted the authors of the paper: Tomasz Piskorski of Columbia University, Jian Zhang of the University of Hong Kong and Amit Seru and Chun Zhao of Stanford University.

CNA has also contacted all the other academics named in the acknowledgements to find out more about their input and involvement in the study.

Among these were four academics whom the authors said they had discussions with and “benefited immensely” from. They are University of Chicago’s Chang-Tai Hsieh and Luigi Zingales and Harvard University's Li Shengwu and Jesse Shapiro.

Prof Hsieh, whose research interests are in areas such as growth and development, said he had discussed the paper at a conference previously. However, he questioned the results of the study. Among other things, he argued that since private housing is typically farther from the MRT stations compared with public housing, the "gain" from inside information on the locations of unannounced MRT stations would be “much smaller”.

Prof Zingales is a professor of entrepreneurship and finance at the University of Chicago, while Prof Shapiro is a professor of economics and business administration at Harvard. Prof Li, the estranged nephew of Senior Minister Lee Hsien Loong, is a professor of economics at Harvard. CNA has contacted them but has yet to receive replies.

At least 16 other academics, including the five from NUS, were thanked by the authors for their “helpful comments”. Some of the research by these academics was also cited in the bibliography .

The working paper, titled Do Social Norms Substitute for Enforcement? Evidence from Public Officials' Home Purchases in Singapore, was published by the Massachusetts-based National Bureau of Economic Research this month.

The authors matched private property transactions from legal filings in Singapore against the Singapore Government Directory Interactive to identify civil servants, then examined purchases near unannounced MRT stations around announcement dates as a "proxy for access to privileged location information".

“We find clear evidence of informed trading by civil servants: purchase intensity near planned MRT stations is higher for civil servants than for matched controls, with the difference concentrated one to two years before public announcements,” they alleged.

The Public Service Division said on Monday that it was reviewing the paper's data and methodology.

"We take any integrity concerns extremely seriously. We are currently reviewing the data and methodology within the paper and will refer to CPIB (Corrupt Practices Investigation Bureau) if there is a material basis to do so," a spokesperson said.

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HOW THE RESEARCH WAS CONDUCTED

The authors wrote that they collected data from three sources to observe property trading activity of civil servants and other individuals, and integrated these datasets with property transaction records.

The first was the Singapore Government Directory Interactive, which lists the names and designations of civil servants. They collected data from six cohorts to reduce misclassification, since individuals may have left or just joined the public service at the time of a transaction.

The second was the public register of the Council for Estate Agencies, and the third a proprietary dataset of demographic details and residential addresses for a large sample of Singapore residents as of 2013.

The authors also referred to filings of private property transactions with the Registry of Land Titles between January 1995 and December 2019.

The analysis focused on private housing, which the authors said offers easier access to anyone hoping to profit from privileged information, and where prices are expected to rise once station plans become public.

The researchers defined circular buffers around proposed stations and classified homes within them as "target" properties, using a 1km radius in the main analysis.

“For robustness, we also consider other cutoffs to separate houses that are more likely to experience price increases due to their proximity to the proposed MRT stations, from those that do not have such advantages,” they wrote.

To account for confounding factors, they created a control group matched closely to the civil servant group on age, gender, marital status and ethnicity.

ECONOMICALLY MEANINGFUL RETURNS

The paper reported a "significant relative increase" in purchases near forthcoming MRT stations by civil servants in the one to two years before announcements.

Against the control group, civil servants made about 50 additional purchases near unannounced stations two years before plans were made public and 63 additional purchases one year before.

“A back-of-the-envelope calculation yields approximately S$138 million (US$108 million) in gross target-property acquisition value associated with the excess pre-announcement purchases identified by our design,” the paper said.

People identified as relatives of civil servants made 108 additional purchases near unannounced stations up to three years ahead of announcements, with these properties worth about S$132 million.

After announcements, civil servants and the control group exhibited similar trading behaviour, which the authors said pointed to pre-emptive buying in anticipation of the station announcements.

The paper put the additional annual return on such a purchase at nearly S$147,000.

Civil servant buyers also held properties for slightly shorter periods, which the authors said suggested an economic motive. "However, these findings should be interpreted with caution due to the relatively small number of ex-post sales observations in our sample," they said.

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这两位教授表示，他们已要求作者将他们的名字从论文的致谢部分删除。

这张照片展现了新加坡的一处私人住宅区和金融区。（资料照片：法新社/罗斯兰·拉赫曼）

这段音频由人工智能工具生成。

新加坡：新加坡国立大学（NUS）两位教授 Ivan Png 和 Jessica Pan 周二（9 月 15 日）表示，他们对一份指控“公务员进行知情交易”的工作文件一无所知，并已要求作者从致谢名单中删除他们的名字。

论文中提到的另外两位新加坡国立大学学者，Sumit Agarwal 和 Wenlan Qian，建议 CNA 联系论文作者。第五位新加坡国立大学学者，David Reeb 教授表示，几年前该论文的早期版本发表时，他可能发表过评论或提出过问题。

新加坡国立大学杰出教授彭教授告诉亚洲新闻台，他很困惑为什么这篇论文会感谢他。该论文调查了公职人员在地铁站附近购买房产的情况，而这些地铁站的位置尚未公开。

“我不认识这些作者，也不知道他们的论文，直到一位同事向我推荐了 CNA 的报道，之后我收到了朋友们发来的大量 WhatsApp 消息，”他说。

Png教授的研究兴趣包括生产力和创新的经济学，他表示自己既没有为这项研究提供评论，也没有提供数据。

“请将我的名字从致谢名单中删除，”他在一封发给该研究主要作者的电子邮件中写道，这封邮件被 CNA 看到。

新加坡国立大学研究生教育副教务长潘教授表示，她的名字出现在论文中是“误打误撞”。她说：“我今天才发现这篇论文，已经要求作者将我的名字从致谢部分删除。”

CNA联系了该论文的作者：哥伦比亚大学的Tomasz Piskorski、香港大学的Jian Zhu以及斯坦福大学的Amit Seru和Chun Zhu。

CNA 还联系了致谢部分提到的所有其他学者，以了解他们对这项研究的贡献和参与情况。

其中包括四位学者，作者表示他们曾与他们进行过讨论，并从中“受益匪浅”。他们分别是芝加哥大学的谢昌泰和路易吉·津加莱斯，以及哈佛大学的李胜武和杰西·夏皮罗。

谢教授的研究领域包括增长与发展等，他表示此前曾在一次会议上讨论过这篇论文。然而，他对研究结果提出了质疑。他认为，私人住宅通常比公共住宅距离地铁站更远，因此，从未公布的地铁站位置等内部信息中获得的“收益”会“小得多”。

辛加莱斯教授是芝加哥大学创业与金融学教授，沙皮罗教授是哈佛大学经济与工商管理教授。李教授是李显龙高级部长的侄子，两人关系疏远，李教授也是哈佛大学经济学教授。亚洲新闻台已联系他们，但尚未收到回复。

作者感谢至少其他16位学者（包括来自新加坡国立大学的5位学者）提出的“有益意见”。这些学者的部分研究成果也被列入参考文献。

这份题为《社会规范能否替代执法？来自新加坡公职人员购房行为的证据》的工作论文由位于马萨诸塞州的国家经济研究局于本月发布。

作者将新加坡法律文件中的私人财产交易与新加坡政府互动名录进行匹配，以识别公务员，然后检查在公告日期前后未公布的地铁站附近的购买情况，以此作为“获取特权位置信息的代理”。

他们声称：“我们发现了公务员进行知情交易的明确证据：公务员在规划中的地铁站附近的购买强度高于匹配的对照组，而且这种差异集中在公开宣布前一到两年。”

公共服务部门周一表示，正在审查该报纸的数据和方法。

一位发言人表示：“我们极其重视任何诚信问题。我们目前正在审查论文中的数据和方法，如果确有实质性依据，我们将把案件移交贪污调查局（CPIB）处理。”

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研究是如何进行的

作者写道，他们从三个来源收集数据，观察公务员和其他个人的房地产交易活动，并将这些数据集与房地产交易记录整合在一起。

第一个是新加坡政府互动名录，其中列出了公务员的姓名和职称。他们收集了六个批次的数据，以减少分类错误，因为在交易发生时，个人可能已经离职或刚刚加入公共服务部门。

第二个是房地产代理理事会的公共登记册，第三个是截至 2013 年新加坡大量居民的人口统计详情和居住地址的专有数据集。

作者还提到了 1995 年 1 月至 2019 年 12 月期间向土地所有权登记处提交的私人财产交易文件。

分析的重点是私人住宅，作者表示，私人住宅更容易让任何希望利用特权信息获利的人获得，而且一旦车站计划公开，价格预计会上涨。

研究人员在拟建站点周围划定了圆形缓冲区，并将缓冲区内的房屋归类为“目标”房产，在主要分析中使用了 1 公里半径。

他们写道：“为了确保结果的稳健性，我们还考虑了其​​他划分标准，将那些由于靠近拟建地铁站而更有可能经历价格上涨的房屋，与那些没有这种优势的房屋区分开来。”

为了排除混杂因素，他们创建了一个对照组，该对照组在年龄、性别、婚姻状况和种族方面与公务员组非常匹配。

经济上有意义的回报

该报报道称，在地铁线路宣布开通前的1到2年内，公务员在即将开通的地铁站附近购买的商品数量出现了“显著的相对增长”。

与对照组相比，公务员在计划公布前两年在未公布的车站附近额外购买了约 50 件商品，在计划公布前一年额外购买了约 63 件商品。

该报告称：“根据我们的设计，与公告前超额购买相关的目标物业收购总价值约为 1.38 亿新加坡元（1.08 亿美元）。”

被确认为公务员亲属的人在未公布的车站附近额外购买了 108 处房产，这些房产价值约 1.32 亿新元，购买时间甚至早于公布时间长达三年。

公告发布后，公务员和对照组表现出类似的交易行为，作者表示，这表明他们为了等待电台公告而提前购买股票。

该报告指出，此类购买的额外年收益接近 147,000 新元。

公务员购房者的持有房产时间也略短，作者认为这表明他们购房可能存在经济动机。“然而，由于我们样本中售后观察数据相对较少，因此应谨慎解读这些发现。”他们说道。

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