CONTRACTING FOR AN INNOVATION UNDER BILATERAL ASYMMETRIC INFORMATION*

We analyze licensing contracts between informed innovators and developers exerting profit‐increasing effort. Those contracts must simultaneously induce innovators to convey information on the value of their ideas, while inducing developers to exert effort and protecting the innovators' intellectual property rights. We show that the best innovators signal themselves by taking more royalties even if it reduces the developers' share of returns and their incentives. Moreover, royalties are more likely to be used when property rights are easy to enforce and pre‐contractual evidence on innovation quality is hard to produce.     

Traditional Management Systems, Poverty and Change in the Arid Zone Fisheries of Northern Nigeria

This paper, based on fieldwork results, explores traditional management systems (TMS) in the arid zone fisheries of north-eastern Nigeria with particular reference to their impact on rural poverty. The first section provides a historical background by tracing the evolution of the TMS since the nineteenth century, with reference to government policy on fisheries management and poverty alleviation. The second gives an overview of TMS, including definitions, distribution, principal objectives, regulatory mechanisms and the impact of TMS on the performance of the fisheries and on the livelihoods of rural people. The third considers the perceptions and attitudes of the fishing communities with regards to the fisheries and TMS. The paper concludes, paradoxically, that while TMS provide a basis for the sustainable livelihoods of many fishing people, they also reflect and enforce the social positions of the rich and powerful members of society who oversee them, at the expense of the poor. In the future, poverty alleviation in fisheries will need to incorporate both sectoral and non-sectoral strategies – dealing with the existing 'paradox of TMS' by encouraging appropriate institutional changes and community development, and recognizing the importance of employment creation in other sectors of the economy as a source of alternative income.     

Response to ‘Duplications’ by Drelichman and Voth

In this response, we demonstrate that Mauricio Drelichman and Hans‐Joachim Voth, in their 2015 Economic History Review note ‘Duplication without constraints: Álvarez‐Nogal and Chamley's analysis of debt policy under Philip II’, provide a misconceived and inaccurate account of our argument about the finances of Philip II in ‘Debt policy under constraints: Philip II, the Cortes, and Genoese bankers’ (Economic History Review, 2014). Here, we summarize our position in the context of the current literature and provide a few comments on data gathering.     

From Search to Match: When Loan Contracts Are Too Long

A model of lending is presented where loans are established in matches between banks (lenders) and entrepreneurs (borrowers) who meet in a search process. Projects turn out randomly a quick payoff or a long‐term payoff that requires a rollover of the loan. The model generates, under proper parameter conditions, two steady states without or with rollover, and rollover is socially inefficient. Under imperfect information, the standard debt contract is privately efficient. However, it extends the domains of equilibria with socially inefficient rollover. The global dynamics displays a continuum of equilibrium paths that each exhibits sudden discontinuities—crises—in which the mass of outstanding loans is reduced by a quantum amount of terminations. Crises have a cleansing effect.     

Directed Networks with Spillovers

We study noncooperative network formation in two types of directed networks. In the first type, called the model with global spillovers, the payoff of a player depends on the number of links she forms as well as the total number of links formed by all other players. In the second type, called the model with local spillovers, the payoff of a player depends on the number of links she forms and the total number of links formed by her immediate neighbors, as well as the number of links formed by players outside her neighborhood. For both classes of games we investigate the existence of pure strategy Nash equilibria and characterize the Nash networks under a number of different second order conditions on the payoff function.     

Wholesale Funding Dry‐Ups

We empirically explore the fragility of wholesale funding of banks, using transaction‐level data on short‐term, unsecured certificates of deposit in the European market. We do not observe a market‐wide freeze during the 2008 to 2014 period. Yet, many banks suddenly experience funding dry‐ups. Dry‐ups predict, but do not cause, future deterioration in bank performance. Furthermore, during periods of market stress, banks with high future performance tend to increase reliance on wholesale funding. We therefore fail to find evidence consistent with adverse selection models of funding market freezes. Our evidence is in line with theories highlighting heterogeneity between informed and uninformed lenders.     

Assessing the Macroeconomic Effects of LTROs during the Great Recession

In response to the 2008–2009 crisis, faced with distressed financial intermediaries, the European Central Bank (ECB) embarked in longer term refinancing operations (LTROs) with full allotment. Using an estimated DSGE model with a frictional banking sector, we find that such liquidity injections have played a key role in averting a major credit crunch. A counterfactual analysis suggests that, absent these nonconventional measures, output, consumption, investment, and the GDP deflator would have been 2.5%, 0.5%, 9.7%, and 0.5% lower on average over 2009, respectively.     

Biased Auctioneers

We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and nonvisual object characteristics. We find that higher automated valuations relative to auction house presale estimates are associated with substantially higher price-to-estimate ratios and lower buy-in rates, pointing to estimates' informational inefficiency. The relative contribution of machine learning is higher for artists with less dispersed and lower average prices. Furthermore, we show that auctioneers' prediction errors are persistent both at the artist and at the auction house level, and hence directly predictable themselves using information on past errors.