Reader in Economics, Cambridge University
Fellow, Jesus College
Email: mle30 [at] cam.ac.uk
Address: Faculty of Economics, Austin Robinson Building, Sidgwick Avenue, Cambridge, CB3 9DD.
COVID-19 related work
Which firms that are essential for ensuring the production of crucial goods and services in times of pandemics?
Vasco Carvalho, John Spray and I, take a supply chain network view on this and argue that business-to-business transaction data + economic theory can help locate "bottleneck" firms: firms which, directly or indirectly, ensure final production meets demand for key goods (e.g. ventilators) and services in the economy. We also offer a proof of concept based on such data for a developing country. Out here. A short presentation on this can be viewed here.
Can robust supply chains be expected to form, and what are the implications for macroeconomy?
Ben Golub, Matt Leduc and I have a new paper showing that business' investments in their supply chain, like the extent of multisourcing they do, have a tendency to make supply chains fragile. Ben tweets about the paper and some of the implications for better understanding the impact of COVID-19 on the economy here. The paper is here.
Published and accepted papers
Accepted, Review of Economic Studies, Draft date: September 2020
Journal of Political Economy, 2019
American Economic Review, 2014.
Accepted, Journal of Economic Theory, Draft date: October 2020
Journal of the European Economic Association, 2020
Theoretical Economics, 2019
Oxford Review of Economic Policy, 2019, Special issue on the economics of networks.
Oxford Review of Economic Policy, 2019, Special issue on the economics of networks.
American Economic Journal: Microeconomics, 2015.
We model the production of complex goods in a large supply network. Firms source several essential inputs through relationships with other firms. Due to the risk of such supply relationships being idiosyncratically disrupted, firms multisource inputs and invest to make relationships with suppliers stronger. In equilibrium, aggregate production is robust to idiosyncratic disruptions. However, depending on parameters, the supply network may be robust or arbitrarily sensitive to small aggregate shocks that affect the functioning of relationships. We give conditions under which the equilibrium network is driven to a fragile configuration, where arbitrarily small aggregate shocks cause discontinuous losses. We use the model to provide a unified account of a number of stylized facts about complex economies.
(with Andrea Galeotti and Andrew Koh, Draft Date: November 2020)
Prodigious amounts of data are being collected by internet companies about their users’ preferences. We consider the information design problem of how to share this information with traditional companies which, in turn, compete on price by offering personalised discounts to customers. We provide a necessary and sufficient condition under which the internet company is able to perfectly segment and monopolise all such markets. This condition is surprisingly mild, and suggests room for regulatory oversight.
(with Jun Chen and Andrew Koh, Draft date: July 2020)
The past twenty years have witnessed the emergence of internet conglomerates fueled by acquisitions. We provide a simple theoretical model to shed some light on this. Following a large literature in management (Wernerfelt, 1984) we endow firms with a set of scarce competencies which drive their competitiveness across markets. Firms can merge to combine their competencies, spin-off new firms by partitioning their competencies, or procure unassigned competencies. We study stable industry structures, in which there are no profitable mergers, demergers, or procurements, and find an upper and lower bound on the size of the largest firm. As markets increasingly value more of the same competencies, abrupt transitions in these bounds occur. We posit that this force can help explain the sudden conglomeratization of internet companies.
(with Eduard Talamas, Draft Date: May 2020)
In many markets, heterogenous agents make non-contractible investments before bargaining over both who matches with whom and the terms of trade. In static markets, the holdup problem—that is, inefficient investments caused by agents receiving only a fraction of their returns—is ubiquitous. Markets are often dynamic, however, with agents entering over time. Taking a general non-cooperative investment and bargaining approach, we show that the holdup problem vanishes in markets with dynamic entry as agents become patient: While there is substantial wiggle room for bargaining to determine outcomes, every bargaining outcome gives everyone her marginal product.
(with Ben Golub, Draft date: February 2015)
Consider a negotiation in which agents will make costly concessions to benefit others -- e.g., by implementing tariff reductions, environmental regulations or nuclear disarmament. An agenda specifies which issue or dimension agents will make concessions on; after an agenda is chosen, the negotiation comes down to the magnitude of each agent's contribution. We seek a ranking of agendas based on the marginal costs and benefits they each generate at the status quo, which are captured in a Jacobian matrix. In a transferable utility (TU) setting, there is a simple ranking based on the best available social return per unit of cost (measured in the numeraire). When transfers are not available, the problem of ranking agendas is more difficult, and we take an axiomatic approach. First, we require the ranking not to depend on economically irrelevant changes of units. Second, we require that the ranking be consistent with the TU ranking on problems that are equivalent to TU problems in a suitable sense. The unique ranking satisfying these axioms is represented by the spectral radius (Frobenius root) of a matrix closely related to the Jacobian, whose entries measure the marginal benefits per unit marginal cost agents can confer on one another.
(Draft date: Nov 2015)
Workers' labor market participation decisions and firms' vacancy creation decisions are studied in a model where different matches generate different surpluses. An immediate consequence of these heterogeneities is that better matches are possible in thicker markets. This creates a thick market externality: when additional workers and firms enter the market, they confer net benefits on the other workers and firms by improving the expected quality of their matches. As a consequence, there is always too little entry by both workers and firms. The thick market externality has further implications. Quite generally labor markets will be fragile. Considering shocks to average match productivities, there will be a critical threshold at which a labor market suddenly collapses from supporting multiple workers and multiple firms in equilibrium to supporting no workers or firms in any equilibrium. All but one agent will suffer discontinuous losses as this threshold is passed and the market collapses.
We model two experts who must make predictions about whether an event will occur or not. The experts receive private signals about the likelihood of the event occurring, and simultaneously make one of a finite set of possible predictions, corresponding to varying degrees of alarm. The information structure is commonly known among the experts and the recipients of the advice. Each expert's payoff depends on whether the event occurs, her prediction, and possibly the prediction of the other expert. Our main result shows that when either or both experts receive uniformly more informative signals, their predictions can become unambiguously less informative. We call such information improvements perverse. Suppose a third party wishes to use the experts' recommendations to decide whether to take some costly preemptive action to mitigate a possible bad event. The third party would then trade off the costs of two kinds of mistakes: (i) failing to take action when the event will occur; and (ii) needlessly taking the action when the event will not occur. Regardless of how this third party trades off the associated costs, he will be worse off after a perverse information improvement. These perverse information improvements can occur when each expert's payoff is independent of the other expert's predictions and when the information improvement is due to a transfer of technology between the experts.