中文目錄?（機(jī)翻）
1.數(shù)字經(jīng)濟(jì)時(shí)代的知識(shí)生產(chǎn)（RFS）
2.衡量企業(yè)復(fù)雜性（JFQA）
3.深挖財(cái)務(wù)約束（JFQA）
4.年報(bào)文件中的數(shù)據(jù)可視化（JAE）
5.機(jī)器人顧問(wèn) VS 人類(lèi)投資者（POM）
6.最低工資與技術(shù)采用（JFQA）

1.The Changing Economics of Knowledge Production

Big data technologies change the way in which data and labor combine to create knowledge. Is this a modest innovation or a data revolution? Using hiring and wage data, we estimate firms’ data stocks and their knowledge production functions. Quantifying changes in production functions informs us about the likely long-run changes in output, in factor shares, and in the distribution of income, due to big data technologies. For the investment management industry, our structural estimates predict a 5% decline in the labor share of income; that change is comparable to similar estimates for the industrial revolution.

2.Measuring Firm Complexity

In business research, firm size is both ubiquitous and readily measured. Complexity, another firm-related construct, is also relevant, but difficult to measure and not well-defined. As a result, complexity is less frequently incorporated in empirical designs. We argue that most extant measures of complexity are one-dimensional, have limited availability, and/or are frequently misspecified. Using both machine learning and an application-specific lexicon, we develop a text solution that uses widely available data and provides an omnibus measure of complexity. Our proposed measure, used in tandem with 10-K file size, provides a useful proxy that dominates traditional measures.

3.Uncovering Financial Constraints

We use a random forest model to classify firms’ financial constraints using only financial variables. Our methodology expands the range of classified firms compared to text-based measures while maintaining similar levels of informativeness. We construct two versions of our constraint measures, one using many firm characteristics and the other using a small set of more primitive characteristics. Using our measures, we find that institutional investors hold a lower percentage of shares in equity-focused constrained firms, while retail investors show a preference for them. Equity issuance and investment of constrained firms also increases during periods of high investor sentiment.

4.Data visualization in 10-K filings

The Securities and Exchange Commission encourages the presentation of information or data in graphical form to improve users' ability to understand financial disclosures. We find a dramatic increase in the disclosure of both qualitative and quantitative infographics in 10-K filings over time and substantial cross-sectional variation in firms' choices regarding image types, data content, and the placement of infographics within 10-Ks. We provide evidence on factors associated with firms’ use of infographics and explore the persistence with which they are disclosed over time. Finally, we investigate the relation between the use of infographics and uncertainty in capital markets.

5.Judge me on my losers: Do robo-advisors outperform human investors during the COVID-19 financial market crash?

As financial institutions increasingly offer robo-advisors (RAs) as a service, the empirical evidence on their performance, particularly during market downturns, remains limited. We study the impact of using RAs on investment performance during the 2020 financial crisis caused by the COVID-19 global pandemic. We obtain daily portfolio and transaction data of investors on an online investment platform. Besides making investment decisions by themselves, investors can also leverage an RA system offered by the platform. We match RA users with other investors who did not use the RA with similar investor and portfolio characteristics before the market crash, then compare their portfolio returns after the crash. We find that RA users experienced significantly fewer losses during the market downturn, and this performance advantage came from the RA-managed assets (rather than assets managed by RA users themselves). We further show that the RA system adjusted its portfolios to hold less risky funds, whereas human investors stayed with their status quo and did not reduce the risk of their portfolios, which partly accounted for the performance discrepancy. Importantly, the RA’s superior performance was not simply a continuation of its performance in a normal market; in fact, we find RA users to have similar portfolio returns as non-RA investors during normal markets, and the benefits of RA's risk-reduction trading strategy only manifested during the financial crisis. Our work offers an empirical assessment of RAs’ performance under different market conditions and advances the understanding of algorithmic decision making in financial markets.

6.Minimum Wage Hikes and Technology Adoption: Evidence from U.S. Establishments

This article studies the effects of state minimum wage increase on information technology (IT) adoption at the establishment level in the United States. Our results show that treatment establishments on average allocate between?66,808 more per year to their IT budgets during the first 3 years after experiencing significant state minimum wage increases. Additional evidence shows that state minimum wage increases on average lead to an economically small decrease in employment. The estimated employment effect is larger for establishments that have more incentives to automate labor. Our results suggest that establishments adopt technology to countervail increased labor costs.