Periodic Reporting for period 2 - EMBED (Embedded Markets and the Economy)
Reporting period: 2019-12-01 to 2021-05-31
Developing a model in which firms interact to form potentially complex supply networks has provided new tools for studying supply networks and raised related questions. In joint ongoing work with Professor Matt Jackson (Stanford) we seek to provide a supply network model of innovation and trade, and ask what implications globalization and lower trade costs have for the fragility of the world economy, long run innovation and growth. Building on these same supply network foundations, I have also started writing a paper with Professor Vasco Carvahlo (Cambridge) and my former postdoc Dr. John Spray (IMF) considering the Ugandan economy. We show how the universe of firm-to-firm transactions in Uganda can be used to construct the supply network for the Ugandan economy and, by marrying theory and empirics, how we can find those firms whose network position confers market power on them.
In Elliott and Galeotti (2019) we also take up the question of market power and network position, but here it is the network position of firms with respect to accessing customers. We show that a network approach can incorporate weak competitive constraints that would otherwise be excluded from antitrust analysis and show that these constraints might be collectively important. This led to a further working paper, Elliott, Galeotti and Koh (2021) showing how platforms can reveal information to competing firms that segments markets and dramatically reduce competition. In a further related working paper Chen, Elliott, and Koh (2020) we use hypergraphs (a generalization of networks) to model overall industry structure, and show how changes in the modern economy can precipitate the emergence of very large conglomerate firms.
The foundations for subproject (iii) as envisioned are given by a paper that was ongoing at the time of the grant application. The first order of business has been to complete and publish that paper which we have now done (Agranov and Elliott (2020)). While working on the experimental design for this subproject, we also noticed some unexpected regularities in the theoretical examples we were playing with. This led to some new theory which is developed in the working paper Elliott and Talamas (2020). Here we explore and find necessary and sufficient conditions for there to be good investment incentives in dynamic networked markets. Nevertheless, the experiment we envisioned at the centre of subproject (iii) has evolved and adjusted its focus to problems of communication. We are still working on the finer details of the new design, which has been further interrupted by COVID-19 crisis.
Since the start of subproject (ii) we have worked on defining markets that lend themselves well for the purpose of our study. An ideal market would meet a number of criteria, including repeated interactions between buyers and sellers, local self-containment and frictions such as information asymmetries along the supply chain. For the first phase of the project, we scoped a number of markets across 2 states in India– flower, silk, furniture, clothes, bakeries, fisheries and others, to assess which would be a good fit. Having narrowed our search down to fish markets, we have conducted pilots to explore facets such as consistency in relationships, information asymmetry and presence of shocks. Further progress has been disrupted by the COVID19 pandemic, but we have worked to transition our operations to a remote model and made use of the crisis to create some key exogenous variation in the structure of supply networks.
Subproject (i) envisioned a theoretical model of network formation based on relational contracts. Although this work has helped inform aspects of subproject (ii), especially since the onset of the crisis, we have not yet found a satisfactory way of generalizing the theory or good data that would enable us to add an empirical component to the paper. The COVID-19 crisis might also create an opportunity for subproject (ii) to provide this empirical part. Part of the foundations for subproject (i) come from Elliott and Ambrus (2020) in which we also consider a model of implicit contracting and network formation, albeit in a rather different context. That paper is now published.
• Agranov, M. and Elliott, M. Commitment and (in) Efficiency: A Bargaining Experiment, (2020) Journal of the European Economic Association.
• Ambrus, A. and Elliott, M. Investments in Social Ties, Risk Sharing, and Inequality , Review of Economic Studies, forthcoming.
• Chen, J., Elliott, M. and Koh, A. Capability Accumulation and Conglomeratization in the Information Age, (2020) CWPE2069.
• Elliott, M., and Galeotti, A. The Role of Networks in Antitrust Investigations, (2019) Oxford Review of Economic Policy.
• Elliott, M., Galeotti, A. and Koh, A., Market segmentation through information (2021) CWPE2069.
• Elliott, M., Golub, B. and Leduc, M. V. Supply Network Formation and Fragility, (2020) CWPE2028.
• Elliott, M. and Talamàs, E. No Holdup in Dynamic Markets, (2020) CWPE2070.
• Elliott, M., Georg, C-P. and Hazell, J. Systemic Risk Shifting in Financial Networks, Journal of Economic Theory, forthcoming.
• The discovery of a novel and strong amplification mechanism for shocks that emerge through the endogenous formation of supply networks. Better understanding this can help policies be developed to help mitigate the impact of future shocks.
• A better understanding of the externalities that prevent the efficient formation of supply networks and financial networks, and when these result in fragility. This can inform financial regulations and policies around supply networks.
• Technology for analysing the structure of supply networks from data on business-to-business transactions. This can be deployed for a variety of purposes: to identify firms whose network position confers market power; to identify businesses that are essential for meeting a specific supply goal (e.g. the production of glass vials for vaccine); and to stress-test supply networks to a variety of possible disruptions (e.g. as induced by the COVID-19 pandemic or by Brexit). This has attracted attention from practitioners seeking to apply these tools.
• Theory that provides a better understanding of the role that market dynamics and future possible trading opportunities can play in creating good investment incentives in networked markets. This provides foundations for a literature on competitive matching and improves our understanding of key assumptions in this literature helping to indicate when they are most likely to be appropriate.
• Identified key forces that lead to the emergence of large conglomerates and more specifically an explanation for why internet companies are coming to dominate many markets. This has antitrust implications for the evaluation of conglomerate mergers.
• Tools for incorporating (many) weak competitive constraints into antitrust analysis by taking a networks approach, and an illustration that collectively these competitive constraints can be important.
• Built a simple theoretical model to understand how intermediaries can use information about consumers to extract rents. Specifically, we have found necessary and sufficient conditions under which an intermediary that controls information about consumers’ willingness to pay for different products can share that information by recommending discounts for firms to offer in an incentive compatible way that perfectly segments the market, and effectively monopolise it.
• Steps towards empirically testing whether the formation of relationships results in markets functioning efficiently. This is hard to evaluate as the network is an inherently endogenous object, so it is hard to observe a market and understand whether there would be large gains from forming additional links, or whether relationships have been formed primarily for the purpose of affecting the terms of trade and redistributing, rather than creating, surplus. However, the COVID-19 crisis has created exogenous variations in business networks. In subproject (ii) this should allow us to better understand the role of business relationships. It has also opened up questions of dynamic efficiency that we can study by considering how new relationships are formed to replace lost ones in the wake of the crisis. Thus far, we’ve been able to zero in on a market that is suitable for studying these forces and have been able to interview participants in the market to understand the conditions under which they operate. This has given us a better understanding of how to go about enumerating the networks in the market, and factors that need to be taken into consideration while building the intervention. This knowledge would also benefit future projects that look to study social capital effects in markets.