学术论文

Online auction markets host a large number of transactions every day. The transaction data in auction markets are useful for understanding the buyers and sellers in the market. Previous research has shown that sellers with different levels of reputation, as shown by the ratings and comments left in feedback systems, enjoy different levels of price premiums for their transactions. Feedback scores and feedback texts have been shown to correlate with buyers’ level of trust in a seller and the price premium that buyers are willing to pay (Ba and Pavlou 2002; Pavlou and Dimoka 2006). However, existing models do not consider the time-order effect, which means that feedback posted more recently may be considered more important than feedback posted less recently. This paper addresses this shortcoming by (1) testing the existence of the time-order effect, and (2) proposing a Bayesian updating model to represent buyers’ perceived reputation considering the time-order effect and assessing how well it can explain the variation in buyers’ trust and price premiums. In order to validate the time-order effect and evaluate the proposed model, we conducted a user experiment and collected real-life transaction data from the eBay online auction market. Our results confirm the existence of the time-order effect and the proposed model explains the variation in price premiums better than the benchmark models. The contribution of this research is threefold. First, we verify the time-order effect in the feedback mechanism on price premiums in online markets. Second, we propose a model that provides better explanatory power for price premiums in online auction markets than existing models by incorporating the time-order effect. Third, we provide further evidence for trust building via textual feedback in online auction markets. The study advances the understanding of the feedback mechanism in online auction markets.

我们的研究发现有诈骗行为的公司与作风诚实正当的公司在资源分配方面迥异不同。以诈骗方式获取的资源倾向被视为不劳而获的收益，因此较少会用于投资具生产效益的活动，例如招聘人才。我们假设作风诚实正当的公司与有诈骗行为的公司会投资不同类别的创新发明：作风诚实正当的公司追求重要的技术性发明；而有诈骗行为的公司则倾向进行低价值型的投资，且避免投资具挑战性的机会，着重外观型专利的申请多于实际性发明专利的申请。我们运用跨时间段的数据验证上述假设。我们追踪了467间中国高科技公司的人才招聘及专利申请活动，而这些公司都申请了国家创新基金资助。透过比较每间公司在同一财政年度的两套财务报表，我们找出诈骗的端倪。纵使法律上要求两套财务报表必须相同，但超过一半的财务报表存在差异，而这些差异均有利于该公司。我们发现相对于作风诚实正当的公司，有诈骗行为的公司更加可能获得国家的创新基金补助，但他们很少在获得补助后招聘技术人材或进行实质性的研发活动。

We assess the impact of geographic diversification on a bank’s costs of interest-bearing liabilities. We employ a new identification strategy and discover that geographic expansion across U.S. states lowered funding costs. Consistent with expansion facilitating risk diversification, we find that (1) funding costs fall more when banks expand into states whose economies are less correlated with the banks’ state and (2) geographic diversification reduces the costs of uninsured, but not insured, deposits. Consistent with expansion intensifying agency frictions, which puts upward pressures on funding costs, we discover that geographic diversification reduces the costs of interest-bearing liabilities more in better-monitored and better-run banks.

一些媒体平台从消费者及广告商双方赚取利润（例如Spotify、Hulu），而另一些平台的利润则单方面来自广告商（例如Jango、Tubi）或消费者（例如Tidal、Netflix）。因此，根据如何将有限的版面空间分配给内容和广告，媒体平台的策略不尽相同。在本文中，我们考虑到多边媒体市场的跨边网络相应以及内容提供商的竞争特性，考察媒体平台的内容提供策略及其对媒体平台和内容供应商在利润方面的影响。为了帮助分析，我们建立了一个媒体平台与内容供应商、消费者和广告商三方互动的模型。首先，我们关于完全竞争的内容市场的分析表明，尽管消费者对内容的渴望可以提高其支付意愿，却同时可以伤害到媒体平台的利润。其次，和人们的预期相反，平台的利润可以因获取内容成本的提高而增长。第三，当平台使用付费内容加广告的策略时，广告商对于触达消费者的意愿会降低垄断市场的内容供应商的利润。第四，一个垄断市场的内容供应商无法从榨取竞争平台的全部利润。此外，互相竞争的内容供应商可能会收取比垄断市场的内容供应商更高的价格。最后，我们阐述了内容市场的竞争特性如何影响平台对于无广告策略的选择。

尽管人们对与促销相关的消费主义越趋关注，这项研究引证价格促销对消费者慈善捐款行为产生的正面影响。具体而言，作者指出价格促销能够提高消费者对资源的感知，从而促进消费者的捐款行为。一系列共七项研究，结合实地和实验数据，均支持是项研究的立论及对资源感知的潜在机制。此外，研究发现出现下列情况时，均会削弱价格促销对消费者捐款行为的正面影响：当消费者聚焦开销而非因价格促销而节省的金额；当消费者认为他们的开支超出预算；以及当消费者未能即时节省金钱。最后，作者发现在价格促销后马上进行募捐，对比价格促销结束后一段时间才进行募捐，此正面影响效果更强。是项研究引证在价格促销下消费者作出新的行为模式及披露其潜在机制，指出价格促销可为社会带来正面的影响，为建设一个更美好的世界作出贡献。

We investigate the effect of pre-IPO investments by public market institutional investors (institutions) on the exit of venture capitalists (VCs). Results indicate that institutions’ pre-IPO investments reduce IPO underpricing by mitigating VCs’ reliance on all-star analysts to boost market liquidity. We conclude that institutions facilitate VC exits in the secondary market. Supporting this view, our analysis reveals that the presence of institutions allows VCs to exit with a reduced price impact in the secondary market. Consistent with the ease of exit, VCs offer fewer shares at the IPO and are more likely to invest in institutionally backed startups.

In finance, economics and many other fields, observations in a matrix form are often generated over time. For example, a set of key economic indicators are regularly reported in different countries every quarter. The observations at each quarter neatly form a matrix and are observed over consecutive quarters. Dynamic transport networks with observations generated on the edges can be formed as a matrix observed over time. Although it is natural to turn the matrix observations into long vectors, then use the standard vector time series 2 models for analysis, it is often the case that the columns and rows of the matrix represent different types of structures that are closely interplayed. In this paper we follow the autoregression for modeling time series and propose a novel matrix autoregressive model in a bilinear form that maintains and utilizes the matrix structure to achieve a substantial dimensional reduction, as well as more interpretability. Probabilistic properties of the models are investigated. Estimation procedures with their theoretical properties are presented and demonstrated with simulated and real examples.

We explore a large sample of analysts' estimates of the cost of equity capital (CoE) to evaluate their usefulness as expected return proxies (ERP). We find that the CoE estimates are significantly related to a firm's beta, size, book-to-market ratio, leverage, and idiosyncratic volatility but not other risk proxies. Even after controlling for the popular return predictors, the CoE estimates incrementally predict future stock returns. This predictive ability is better explained as the CoE estimates containing ERP information rather than reflecting stock mispricing. When evaluated against traditional ERPs, including the implied costs of capital, the CoE estimates are found to be the least noisy. Finally, we document CoE responses around earnings announcements, demonstrating their usefulness to study discount-rate reactions of market participants. We conclude that analysts' CoE estimates are meaningful ERPs that can be fruitfully employed in a variety of asset pricing contexts.

Product price risk is a potentially important factor for firms’ liquidity management. A natural place to evaluate the impact of this risk on liquidity management is the electricity industry, because producing firms face substantial price volatility in wholesale markets. Empirically, higher volatility of electricity prices leads to an increase in cash holdings, and this effect is robust to instrumenting for price risk using weather volatility. Cash increases more with price risk in firms using inflexible production technologies and those that cannot easily hedge electricity prices, indicating that operating flexibility and hedging are substitutes for liquidity management.