Maia King is an economist and researcher on the History of UK Public Spending Control project at the Blavatnik School of Government. She joined the Blavatnik School in June 2017 after a PhD at Queen Mary, University of London.
Maia has academic and professional expertise in public finance, governance and institutions, public goods and networks. Her doctoral research was on microeconomic theory, investigating the welfare implications of the structure of networks with local public goods; and the role of information in supporting cooperation in networks with community enforcement. Other research projects examine the links between public finance, clientelistic networks and political institutions in developing countries; and policy reform to tackle carbon leakage.
Maia has worked as an economist at the UK Treasury, focusing on macroeconomic analysis and tax policy; and as an ODI Fellow in the Ministry of Economy, Trade & Industry in Madagascar and the Macro-Fiscal Analysis Unit of the Liberian Ministry of Finance. She also worked as a researcher and consultant at the Overseas Development Institute, focusing mainly on public finance in fragile states, aid management, and the political economy of service delivery.
Maia has PhD from Queen Mary, University of London. She has an MA in Economics from the Université Catholique de Louvain in Belgium, a PGCert in Economics from Birkbeck College, University of London; and a BA in Natural Sciences from the University of Cambridge (Queens' College).
Community enforcement is an important device for sustaining efficiency in some repeated games of cooperation. We investigate cooperation when information about players' reputations spreads to their future partners through links in a social network that connects them. We find that information supports cooperation by increasing trust between players, and obtain the `radius of trust': an endogenous network listing the potentially cooperative relationships between pairs of players in a community. We identify two aspects of trust, which relate to the network structure in different ways. Where trust depends on the shadow of punishment, players are trusted if others can communicate about them. This is linked to 2-connectedness of the network and the length of cycles within it. Where trust relates to knowledge of a player's type, players are trusting if they are more likely to receive information through their network connections. Both aspects of trust are linked to new centrality measures that we construct from the probabilities of node-to-node information transmission in networks, for which we provide a novel and simple method of calculation.