伪外资

过去二十年间，中国推行了一系列政策以推动资本市场的对外开放。早期推出的合格境外机构投资者（QFII）和人民币合格境外机构投资者（RQFII）制度，允许持牌的国际机构投资者直接投资于中国大陆的证券市场。作为新一轮资本市场改革开放的关键举措，2014年11月17日启动的“沪港通”（“深港通”随后于2016年12月5日启动），已迅速成为境外投资者参与中国股票市场最重要的方式之一。

“沪深港通”的独特之处在于其创新性的机制设计——在未放开资本账户管制的同时，促进中国资本市场与全球其他资本市场的融合。在沪深港通中，中国香港和海外的投资者以及中国内地的合格投资者，通过本地交易所直接交易在另一交易所上市的合格股票。更重要的是，跨境投资者的资金流动是一个闭环，只能在对面的股票市场中交易证券，不能进入对面市场的其他领域。

注: 这张图描绘了根据北向资金构造多空策略组合的累计收益率，具体做法为根据股票的北向资金流动进行排序，买入前10%的股票并卖出后10%的股票，每周调整投资组合，时间范围从2017年3月17日（监管机构自此开始公布日度股票层面的北向资金流动）至2019年12月31日（之后中国爆发新冠肺炎大流行）。投资收益率根据股票流动市值加权，并进行了5%和95%的缩尾处理。在监管法规改革之后（2018年之后的16个月），北向资金多空策略的年化累计收益率只有8.8%（作为对比，同期股票市场相对于国开债收益率的超额回报为9.6%）。

然而，沪深港通这一对外开放的创举也存在弊端。该研究指出，“沪深港通”可能为部分投机的内地投资者创造了监管漏洞，让他们可以通过绕道投资的方式进行监管套利。具体而言，本文的发现表明，部分来自大陆的投资者（可能是出于隐藏身份这一目的的企业内部人）通过“沪深港通”伪装成“外国投资者”进行跨境交易。

为什么内地投资者有动机伪装成外资？已有研究关注了以逃税、隧道效应和误导市场为目的的伪外资，而本文关注的是上市公司内部人利用监管套利的手段和非公开信息获利的动机。近日，内地和香港交易所就进一步扩大沪深港通合格股票范围达成协议，基于沪深港通的影响力日渐扩大，关注伪外资问题的重要性得以彰显。

投机者如何通过“沪深港通”隐藏身份呢？事实上，与内地交易所针对交易和结算采取穿透式监管的制度不同，按照香港原有的制度，当地金融中介机构（如经纪商/托管人）通常以中介机构的名义代理持有客户的证券。在沪深港通计划推出后的三年内，通过“沪深港通”的北向交易采用了符合香港原有制度的方案，即以托管人的名义持股，由此为大陆投资者提供了一个隐藏身份从而间接交易连通股票的机会。

在介绍本文的主要结论之前，值得注意的是一项颠覆性的监管改革。2018年8月24日，大陆和香港的证券监管机构发布联合声明宣布，在“沪深港通”市场上推出“投资者识别码”制度。这一制度要求参与北向交易的托管人为其客户分配唯一的身份标识符，使得内地监管机构能够识别北上交易的实际受益者。

关于“沪深港通”如何重塑中国内地和北向资金的交易行为，读者可以参阅完整的工作论文。简而言之，作者们基于在香港交易所参与北向交易的托管人完整的持仓数据，探究了北向资金中潜在的异常交易，尝试回答哪些投资者更有可能利用“沪深港通”隐藏身份并以此获利。他们发现：

• 首先，从不同来源的北向资金对股票收益的预测能力切入，作者们发现对于声誉较弱的外资托管人和跨境经营的内资托管人，其交易在沪深港通开通初期展现出预测收益的能力。但是，自“投资者识别码”制度出台以来，这两类托管人的北向交易对股票未来收益的预测能力明显减弱。

• 政府对国有企业（SOE）和非国有企业（POE）的监管强度存在差异，可能允许非国有企业的内部人更易伪装成外资。同时，中央国有企业的组织架构更复杂，缺乏信息透明度，亦为“伪外资”创造了空间。与预期一致，研究发现，无论是中央国有企业还是非国有企业，经由问题托管人的北上资金的收益预测能力在穿透改革后均有所下降。

• 最后，研究发现穿透改革之后，来自问题托管人的北向交易与大陆的内部人减持的同步性明显下降。

事实上，打击跨境监管套利的改革仍在继续。如，自2022年7月25日起，海外券商不得再为内地投资者设立交易账户，这可能进一步提升“伪外资”的交易成本和法律风险。作者们预期，未来穿透监管改革可能会鼓励真正的外资流入新兴资本市场，提高市场效率。

中美贸易战中的非关税贸易壁垒

2018至2019年中美贸易战时期，两国间的多轮关税上调备受关注。然而也有大量的实例研究表明，中国为抑制美国产品的购买而实施的非关税机制存在显著影响，例如对某些产品延迟检查、繁琐的许可证要求以及其他限制美国对中国出口的针对性措施。

非关税壁垒可以对贸易和福利产生巨大影响，但其不透明性使这种影响难以量化。在本文中，作者利用清华大学中国数据中心的中国海关数据，通过构建需求理论模型，推断2018年至2020年中美贸易争端中非关税壁垒的作用。上述非关税壁垒既包括2018至2019年中国在贸易战最激烈时为惩罚美国出口商实行的监管措施，又包括2020年中国为结束贸易战实行的使美国出口商受益的调控措施。

首先，作者估计了2018年、2019年及2020年（中美双方签署经贸协议的第一年）内，中国在贸易战中使用非关税贸易壁垒的影响。他们首先估计了中国进口的美国产品相对于其他国家产品的需求弹性，以及美国产品对中国出口的供给弹性，发现：

• 国外出口的供给曲线基本上是水平的，这表明中国贸易壁垒（无论是关税还是非关税法规）的增加完全由中国消费者承担。

随后，作者使用需求弹性的估计值倒推非关税壁垒对美国产品进口的影响，即在控制关税作用后，美国产品进口量相对于其他国家相同产品进口量的变化的残差。这些估计表明：

• 在2018年和2019年，中国针对美国进口产品的非关税壁垒显著增加，其中农产品平均增加56个百分点（关税当量单位），工业制品平均增加17个百分点。而在2020年（第一阶段经贸协议的第一年），美国农产品出口增加的非关税壁垒被部分扭转。
• 与关税相比，非关税壁垒的使用也更加针对特定产品，并且主要适用于非国有进口商。例如，“油籽”、“谷物”和“矿石、矿渣和灰烬”等类别的非关税壁垒的关税当量在2018年和2019年增加了近300个百分点。

作者还采用需求理论模型来估计贸易壁垒（包括关税和非关税壁垒）对中国福利的影响，发现：

• 2017至2019年间，美国对华出口量约50%的下降来自于更高的非关税贸易壁垒，另50%来自于更高的关税。然而，中国在贸易战中遭受的大部分福利损失是由非关税贸易壁垒造成的。
• 具体而言，2018年和2019年实施的贸易壁垒使中国2019年的福利减少了 400 亿美元，其中 93% 的福利损失来自非关税贸易壁垒。由于更高的关税，上述福利损失大约是同等进口下降的六倍。与关税相比，非关税壁垒的成本更高，因为它们仅适用于某些进口商，而不适用于其他进口商，这会导致资源错配。而且非关税壁垒不会产生任何收入。

作者不仅关注2018-2019年的美中贸易战，也提供了近期其他争端的类似例子，以说明非关税法规在贸易争端中的广泛影响。例如，当加拿大当局逮捕华为首席财务官孟晚舟时，中国当局以类似的非透明监管程序对加拿大的出口进行反击，如声称加拿大菜籽油感染了害虫，并长时间拖延其他食品的文书工作。与此相关的是，在澳大利亚通过国家安全法并阻止中国公司使用其 5G 移动网络后，澳大利亚的大麦出口受到反倾销税的打击，澳大利亚牛肉、龙虾和铜的进口许可证被吊销，澳大利亚棉花和煤炭也被禁止购买。

总结：基于“中国政府的目标是通过削减从美国的进口来报复美国对中国产品征收关税的行为”这一想法，本篇文章表明，非关税贸易壁垒比单独征收关税的成本更高，而且负担落在了中国消费者身上。此外，这项工作不仅针对美中贸易战相关的非关税成本问题发表了重要见解，也提供了一个有效的框架用于检验其他贸易争端的类似影响。

Investing With the Government: A Field Experiment in China

Government participation in the economy, via direct or indirect ownership of private sector firms, is pervasive around the world and is often characterized by two distinct models: the “grabbing hand” model, commonly used to describe Russia and Eastern Europe in the 1990s, where government interference by bureaucrats and politicians represents a key friction to the growth of private businesses; and the “helping hand” model where the government helps private sector firms overcome market failures.

The authors bring these models to an investigation of China’s massive and high-growth economy to determine whether market participants view the government as a grabbing or helping hand, in the context of the multi-trillion-dollar venture capital and private equity (VCPE) market. They combine a field experiment with new administrative and survey data to ask whether—all else equal—firms prefer to receive capital from the government vis-à-vis private investors. Specifically, the authors focus on the matching between capital investors, or Limited Partners (LPs), and profit-seeking firms, that is, the fund managers or General Partners (GPs), that manage invested capital by deploying it to high-growth entrepreneurs.

The authors characterize the role of government in the Chinese VCPE market by matching data on VCPE investments from 2015–2019 with administrative business registration records, through which they can observe the ownership structure of all firms (GPs) and investors (LPs) in the data, to establish four descriptive facts:

• The government—represented by central, provincial, and local government agencies as well as state-owned enterprises (SOEs)—is the leading investor, with the government as a majority owner of about half of LPs, and government LPs significantly larger investors than private LPs.
• The government is also a minority owner of a significant share (about a third) of GPs.
• Government-owned GPs perform worse than private GPs.
• There is a pattern of assortative matching, with government LPs investing disproportionally more in government-owned GPs.

These facts, while informative, can support many different interpretations, which motivates the authors to estimate actual firm demand for government capital. To do so, they conduct a field experiment in 2019 in collaboration with the leading VCPE industry service provider in China. This collaboration led to an experimental survey of 688 leading GPs in the market (with a response rate of 43 percent), which together manage nearly $1 trillion. GPs are asked to rate 20 profiles of LPs along two main dimensions: (i) how interested they would be in establishing an investment relationship with the LP (under the assumption the LP is interested); and (ii) the likelihood that the LP would be interested in entering an investment relationship with them if they had the chance. Importantly, there is no deception in this survey because GPs know the LP profiles are hypothetical. (Please see the working paper for more details on the survey instrument.)

The authors’ novel experimental survey finds the following:

• The negatives of receiving capital that is tied to the government outweigh the positive value GPs may obtain from establishing a link to a government-related politically connected investor.
• This finding is consistent with a “grabbing hand” interpretation of the government’s involvement in the market.
• Using both the administrative micro-data and follow-up surveys, and consistent with several anonymous discussions with active VCPE firms, the authors find support for an explanation according to which government connections of the investors lead to interference in decision-making that is due to political, rather than profit-maximizing, incentives.

This work has several implications. On the one hand, by providing direct evidence of the private sector perspective of the advantages and disadvantages of government investors, this research deepens our understanding of the nature of China’s model of economic growth grounded on the dominance of state economic actors. On the other hand, this work makes the simple point that the demand for government capital differs across different types of firms. As a result, to the extent that how capital is allocated depends on the agents receiving it, understanding the demand side is important to fully capture the efficiency implications of government participation, an aspect of the debate that the authors believe has been largely neglected but that is crucial for both theory and policy.

中国工业用地有价格折扣吗？ 基于公共财政视角的研究

中国的土地市场对过去四十年间中国经济的飞速增长发挥 了重要作用。和多数发达经济体不同的是，中国的地方政府 并不通过征收房产税的方式从土地市场获得收入，而是作为 土地供给的垄断者，其财政收入严重依赖于土地出让收入。

中国严格的土地使用规划将不同地块按不同的用途进行划 分，其中，住宅用地比工业用地的价格高了十倍左右。作者 将这一价格差异称为工业用地价格折扣（或简称工业折扣）。地方政府似乎需要在出让住宅用地以增加财政收入，或出 于非金钱目的低价出售工业用地以刺激地方经济发展之间 做出选择。至少这是现有文献对这一权衡的常规解释。本文 则另辟蹊径，从公共财政而非工业补贴的角度对工业用地 价格折扣提出了不同的解释。 作者提出，出售住宅或工业用地的抉择涉及对跨时期收入的权 衡。来自企业的税收和土地出让收入是中国地方政府的主要收入 来源，共占地方政府收入的60%左右。由于工业企业需要支付增 值税、企业所得税及其他各项费用，工业用地会产生未来的税收 流；住宅用地则不会。从这一简单的差异出发，上面提到的权衡可 被重新描述为:

• 地方政府面临着出售住宅用地或工业用地的选择，其中住宅 用地以其更高的价格会带来更多的一次性收入，而工业用地 虽然一次性收入较少，但随之而来的将是税收收入所产生的 未来现金流。

这一动态视角暗示地方政府并不一定是为了补贴工业而低价出售 土地；相反，作者发现工业用地的未来税收收入远足以补偿工业用 地出让时的一次性价格折扣。这一结果对理解中国土地价格的影 响因素有重要的意义，同时也对理解这些影响因素如何与中央政 府和地方政府的税收分享制度相联系，以及地方政府的跨期收入 权衡有重要启示。从中央政府的角度来看，中央和地方政府的税收 分享制度可以仔细地进行设计，以抵消地方政府在居住和工业土 地市场上不同的垄断能力，从而实现合理的土地分配结果。

概括而言，该研究表明地方政府的财政需求影响了对中国所有工 业行业的土地出让，这意味着地方公共财政通过土地分配渠道对 塑造中国经济增长道路发挥着不可忽视的作用.

中国的股票质押:投资上市公司还是初创公司?

中国的政策试点:政策学习中的政治经济学

政策的选择和落实是政府的根本职能，然而我们很难在政策真正得到实施之前了解它的效果与影响。因此，许多国家的政府都曾进行不同程度上的政策试点来降低未来政策的不确定性。本文分析了自20世纪80年代以来中国的系统性政策试点。在这期间，中国政府在决定是否将某些政策推广到全国之前，曾有选择地在一些局部地区尝试执行这些政策并评估其效果。

以下两个原因使中国的政策试点成为一个重要的研究对象。第一，中国的系统性政策试点无论在深度、广度和持续时间上都是其他国家无可比拟的。第二，学者们普遍认为，在过去40年里，系统性的政策试点是促进中国经济增长的关键机制。即便如此，令人惊讶的是，学界对这类政策试点的特征或结构、以及其可能如何影响政策选择和政策效果都知之甚少。

为评估政策试点是否为政策向全国推广提供了有效而准确的信息，作者关注了其以下两个特点。第一，由于同一项政策可能在不同地区产生不同的影响，在评估政策效果时，需要确保进行试点的地区能够准确代表其他没有进行试点的地区。第二，政策执行者（例如地方官员）的行为往往能影响政策的结果，因此，如果一项试点带来了政治激励，这可能会导致地方官员将更多精力和资源倾斜到这项试点当中，从而在试点阶段夸大了“实验效果”。

从这两个角度出发，作者收集了 1980 年至 2020 年期间中国政策试点的 19,812 份政府文件，并构建了由 98 个中央部委发起的 633 项政策实验的数据库。关于研究方法，作者在论文中有详细描述。简而言之，他们将包含政策指导意见的中央政府文件与所有相应的地方政府文件联系起来，从而可以追踪每项政策在全国的实施情况。他们衡量了政策试点的许多特征，包括事前对政策有效性的确信程度、涉及政策试点的中央和地方官员的职业轨迹、政策发起部门的层级结构、地方政府政策实施的差异程度、以及当地的社会经济条件等等。

通过分析这些数据，作者发现了以下结果：

• 政策试点的“样本选择”不具有代表性：被选中参加政策试点的地区，相比于没有被选中参加试点的地区，往往具有更高的经济发展水平。这种“正向选择”在很大程度上来自于中央与地方政府之间所存在的激励不相容。
• 政策试点过程中的“实验情境”不具有代表性：在试点过程中，地方官员为了获得试点成功从而博取政治资本，往往会有意识地将精力和资源向试点政策倾斜。这可能会导致该政策的有效性被夸大：当政策最终推广到全国时，其他地区的官员不会同样把精力和资源倾斜给该政策。
• 中央政府在评估政策试点的结果时，没有完全考虑到上述不具有代表性的“样本选择”和“实验情境”，从而会导致对政策效果的评估以及相应的政策选择存在一定程度上的系统性偏差。

这项研究揭示了中国政府在政策试点中所面临的一个制度设计问题：如果构建政治激励机制，以鼓励政府官员努力执行国家政策，但同时又确保这些激励机制不会在试点阶段影响样本选择和实验情境，从而降低政策试点结果的偏差？从机制设计的角度解答这一问题，将有助于政府开展更加科学的政策试点，并进而做出更为有效的政策选择。

In developing countries, indirect impacts of COVID-19 may be greater than direct health impacts

The poorest countries of the world have so far avoided the worst of Covid-19, a result we attribute to a younger population and limited obesity. In the long run, the highest costs may be due to the indirect effects of virus containment policies, especially for girls.

Early in 2020, the general expectation was that the coronavirus pandemic’s effects would be more severe in developing countries than in advanced economies, both on the public health and economic fronts. Preliminary evidence as of July 2020 supports a more optimistic assessment. To date, most low- and middle-income countries have a significantly lower death toll per capita than richer countries, a pattern that can be partially explained by younger population and limited obesity. On the economic front, emerging market and developing economies (EMDEs) have seen massive capital outflows and large price declines for certain commodities, especially oil and non-precious metals, but net capital outflows are in line with earlier commodity price shocks. While there is considerable heterogeneity in how specific countries will be affected in the short and medium run, we are cautiously optimistic that financial markets in the largest EMDEs, especially those not reliant on energy and metal exports, could recover quickly – assuming the disease burden is ultimately not as dire in these countries. In the long run, the highest costs may be due to the indirect effects of virus containment policies on poverty, health and education as well as the effects of accelerating deglobalization on EMDEs. An important caveat is that there is still considerable uncertainty about the future course of the pandemic and the consequences of new waves of infections.

This paper is part of the Summer 2020 special edition of the Brookings Papers on Economic Activity.

Healthcare Crowd-out During COVID-19

During COVID, the issue of healthcare crowd-out is critical even in non-hotspot areas. The alpha-reserve capacity reallocation through tele-medicine could mitigate this.

There are lots of anecdotic evidence and news articles talking about large amount of healthcare needs have remained unmet during COVID-19, including whether COVID-related care may have displaced non-COVID care (so-called crowd-out effect). If so, efficient healthcare resource allocation is required during such a critical period. We aim to understand the extent healthcare demand may be shifted and can be rearranged. The non-availability of timely and reliable medical claim data during a public health crisis like COVID, makes this task difficult. To surmount this practical challenge, we leverage the dataset of online drug retailing transactions across geographic regions in Mainland China during the pandemic’s first wave. The key data aspect that allows us to infer crowd-out regards demand differences between prescription (Rx) and over-the-counter (OTC) drugs. Specifically, because a provider-written prescription is required for Rx but not for OTC purchases, relative Rx/OTC demand changes reflect changes in the amount of used medical consultations. Since most sample drugs target non-C19 symptoms, changes in the amount of used non-COVID care can be inferred from this variation.

We embed the above insights in a differences-in-differences-in-differences (DDD) identification framework. We find COVID-fueled relative surge of online Rx/OTC demand in lower-capacity regions. Given that the Chinese system implicitly bundles utilization with offline Rx demand, this suggests that patients from lower-capacity regions were less likely to receive care as demand for COVID-related care strained the system. At the pandemic’s peak, this crowd-out effect is equivalent to 10% decrease of non-C19 care. We propose and evaluate an alpha-reserve capacity reallocation policy. Relying on tele-health infrastructure, this policy would reallocate healthcare supply across regions on a spot basis, aiming to minimize aggregate crowd-out. Significant crowd-out reduction is achieved without drastically undercutting any region’s healthcare capacity. This provides meaningful managerial and policy suggestions to lessen the adverse impacts of such a public health crisis.

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A Large-scale Policy Experiment to Stimulate Consumption post COVID-19 outbreak

The small-value short-duration digital coupon issued by local governments in China is highly effective in driving excess consumption.

In response to the significant economic contraction caused by the COVID-19 pandemic, many local governments in China have experimented with an innovative policy tool to stimulate consumption, the digital consumption coupon program. The program departs from other commonly adopted fiscal stimulus programs such as cash payment or tax rebate in several salient ways. First, the coupon typically takes the form of saving with certain amount of spending, e.g. “spend RMB 40, get RMB 10 off,” and hence has the nature of “use-it-or-lose-it.” Second, the coupons are of small face value and short duration, and involve a small amount of government subsidy per voucher. Third, the coupons are disbursed through mobile payment platform with limited quantity in each round.

Using the high-frequency transaction-level data of more than one million de-identified consumers, the authors evaluate the effectiveness of the digital coupon program in a major city in China. Exploiting a difference-in-differences approach, they find that the consumers who successfully acquired the government coupon spent significantly more during the coupon redemption week compared to similar individuals who applied but failed to acquire the coupon due to limited quantity. Defining MPC as the ratio of excess spending over the effective amount of government subsidy, they find the MPC ranges from 3.4 to 5.8 across several waves of coupon issuance. The excess spending mostly concentrates in the catering services and food and drinks purchases. The authors do not find significant intertemporal substitution of consumption. In addition, the coupon effect does not wear out over multiple waves of the program. Behavioral factors such as mental accounting and loss framing are likely to play a role in the underlying mechanism.

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Response to Stimulus Checks Driven Primarily by Liquidity

Households with low levels of liquidity spent about a third of their stimulus checks within the first two weeks, while households with ample liquidity spent approximately zero.

The 2020 CARES Act directed large cash payments to households. With policy-makers considering future stimulus programs, we work to analyze how household spending responded to the first checks using high-frequency transaction data from a FinTech nonprofit. Households respond rapidly to the receipt of stimulus payments, with spending increasing by $0.25-$0.30 per dollar of stimulus during the first weeks across a range of categories.

The authors also explore heterogeneity across households along dimensions like income levels, recent income declines, and liquidity. Households with lower incomes, greater income drops, and lower levels of liquidity display stronger responses, highlighting the importance of targeting when thinking about fiscal multipliers. Liquidity plays the most important role, with no observed spending response for households with high levels of bank account balances.

Relative to the effects of previous economic stimulus programs in 2001 and 2008, the authors see faster effects, smaller increases in durables spending, and larger increases in spending on food, likely reflecting the impact of shelter-in-place orders and supply disruptions. Additionally, they see substantial increases in payments like rents, mortgages, and credit cards reflecting a short-term debt overhang. The authors formally show that these differences can make direct payments less effective in stimulating aggregate consumption.

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