Abstract

This paper studies the impact of generative AI technologies on the demand for online freelancers, using a large dataset from a leading global freelancing platform. We focus on how the demand effect of the release of ChatGPT differs across various jobs that require different skills or software. Our findings indicate a 14 percent decrease following the ChatGPT introduction in the number of job posts in jobs associated with writing, statistical analysis, engineering, accounting research, and web development when compared to jobs associated with data entry, video services, and audio services, which require more manual tasks. Furthermore, we utilize prior evidence on AI exposure to different occupations and Google Trends to demonstrate that the more pronounced decline in freelancer demand within those specific occupations is linked with their heightened exposure to AI technology, as well as higher general public awareness of ChatGPT's substitutability.

Abstract

In this paper we study the market effects of common ownership in a setting where any ownership structure and any shareholder size is allowed. We depart from the standard reduced form approach of assuming that firms maximize a weighted average of shareholders' portfolios, and instead study the collective choice problem of shareholders head-on. In our model shareholder meetings elect firm managers by one-share one-vote majority rule. Managers differ in their degree of aversion to the negative externality of production. Voting for socially concerned managers therefore provides a mechanism for common owners to direct away the firm from own profit towards industry profit maximization. We show that allowing shareholders of any size to freely diversify their portfolio leads to monopolistic outcomes. Our results have the novel policy implication that the anticompetitive effects of common ownership can emerge even when blockholders are undiversified, but the majority of shares belongs to small diversified shareholders, indicating that small diversified portfolios may also be a threat.

Abstract

The development of blockchains technologies, including smart contracts and cryptographic tokens, have a potential to change the competition between platforms. In this presentation, based on a couple of projects, I will discuss how utility tokens can help new platforms enter the market, and how governance tokens can help platforms to increase social welfare. I will also discuss limitations of these technologies in improving platform strategy and competition.

Abstract

Harassment can be harmful to mental health and reduce creativity and productivity. This paper provides evidence on the productivity effects of online harassment by examining a sudden and unanticipated change on YouTube where dislike counts were hidden from public view. Using detailed channel-level data, I show that this design change had several effects on content creators. First, harassment in form of “dislike attacks”, where users drive up dislike counts unrelated to video quality, decreases following this platform design change. Prior to this design change, women seem to have been more affected by this type of harassment. Second, this design change leads to a persistent increase in productivity for female, relative to male, content creators. Third, there is some evidence of redistribution of demand among content creators.

Abstract

We empirically investigate the relevance of multi-homing in two-sided markets. We build a structural econometric model that allows for multihoming. We then estimate readers’ and advertisers’ demand using an original dataset on the Italian daily newspaper market that includes information on double-homing by readers. The results show that a model that does not allow for multi-homing produces biased estimates on both sides of the market. On the reader side, accounting for multi-homing helps to recognize complementarity between products; on the advertising side, it allows to measure to what extent advertising demand depends on the shares of exclusive and overlapping readers.

Abstract

Online platforms often face challenges being both fair (i.e., non-discriminatory) and efficient (i.e., maximizing revenue). Using computer vision algorithms and observational data from a microlending marketplace, we find that choices made by borrowers creating online profiles impact both of these objectives. We further support this conclusion with a web-based randomized survey experiment. In the experiment, we create profile images using Generative Adversarial Networks that differ in a specific feature and estimate it’s impact on lender demand. We then counterfactually evaluate alternative platform policies and identify particular approaches to influencing the changeable profile photo features that can ameliorate the fairness-efficiency tension.

Abstract

In this paper, we consider competition across two markets where data collected in each market adds value in the other market. A multiproduct firm (1) is a monopolist in market A, and is also active in a second market B where it competes with an established (specialist) firm 2. Firm 1 leverages its presence in both markets to gain a data advantage. In such a market structure, we study the incentive of the specialist firm to share data with its dominant competitor and its implications on profitability, competition and consumer welfare. Our main contribution is to show that the smaller firm has incentives to share data with the dominant firm even for free. This data altruism acts as a strategic device employed by the small firm to lower the intensity of competition by transforming a competitor into a co-opetitor by creating "co-dependence". Specifically, by sharing value-enhancing data, the specialist firm makes the dominant firm a stakeholder in the valuable data collected by the specialist and hence also in its market share. This lowers the competitive intensity of the dominant firm in the competitive market B which enhances (demand and hence also) data collection by the smaller firm. This value creation arising from data altruism substitutes value addition through costly investments made by the dominant firm. A direct managerial implication of this result is that data altruism by the specialist firm can be a win-win outcome for both firms. While data altruism increases market share of the smaller firm, it is not consumer welfare enhancing as it lowers competition (in the secondary market). This result has clear policy implications.