Research Paper Series

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  • Author(s)


Departments: Economics & Decision Sciences, GREGHEC (CNRS)

We provide possibility results on the aggregation of beliefs and tastes for Monotone, Bernoullian and Archimedian preferences of Cerreia-Vioglio, Ghirardato, Maccheroni, Marinacci, and Siniscalchi (2011). We propose a new axiom, Unambiguous Pareto Dominance, which requires that if the unambiguous part of individuals’ preferences over a pair of acts agree, then society should follow them. We characterize the resulting social preferences and show that it is enough that individuals share a prior to allow non dictatorial aggregation. A further weakening of this axiom on common-taste acts, where cardinal preferences are identical, is also characterized. It gives rise to a set of relevant priors at the social level that can be any subset of the convex hull of the individuals’ sets of relevant priors. We then apply these general results to the Maxmin Expected Utility model, the Choquet Expected Utility model and the Smooth Ambiguity model. We end with a characterization of the aggregation of ambiguity attitudes.

Keywords: Preference Aggregation, Social Choice, Uncertainty

  • SPE-2014-1056
  • Projecting Different Identities: A Longitudinal Study of the 'Whipsaw' Effects of Changing Leadership Discourse About the Triple Bottom Line
  • J. BAYLE-CORDIER, P. MIRVIS, B. MOINGEON

Departments: Strategy & Business Policy, GREGHEC (CNRS)


Departments: Finance, GREGHEC (CNRS)

Aggregate art price patterns mask a lot of underlying variation — both in the time series and in the cross-section. We argue that, to increase our understanding of the market for aesthetics, it is helpful to take a micro perspective on the formation of art prices, and acknowledge that each artwork gives rise to a market for trading in its private-value benefits. We discuss relevant recent literature, and illustrate the potential of this approach through a historical study of art price records between 1701 and 2014. Our newly constructed series also points to the importance of developments in the industrial organization of the art market for long-term price trends.

Keywords: art market, auctions, art prices, records, private values


Departments: Tax & Law, GREGHEC (CNRS)

At a time in which behavioural science has gained increasing attention for the design of population-wide health interventions, this chapter discusses its potential contributions to the prevention and control of Non-Communicable-Diseases (NCDs). Given the largely preventable nature of NCDs, any lifestyle intervention faces the challenge to induce behavioural change. By highlighting the role of social and physical environments in shaping our behaviour, applied behavioural science provides policymakers with a new understanding of human decision-making and, as a result, may support an innovative approach to the promotion of behaviour change leading to healthier lives. While only a combination of policy instruments, such as legislation, regulation, and even financial and fiscal incentives, may induce behaviour change to the scale required to reduce the burden of chronic disease at the population level, a behavioural informed approach may valuably complement the current regulatory mix. In particular, an analysis of the WHO NCD Action Plan and its accompanying strategies suggests an increased awareness of the roles played by environmental and social factors on behaviour change. Although the language employed falls short of operationalizing the major behavioural insights into the NCD agenda, it clearly highlights that their integration into the current regulatory mix appears fundamental today for the design of any lifestyle policy intervention. As behavioural change is progressively becoming the focus of health promotion efforts, the lesson learned is that there is more to behaviour change than merely empowering the targeted individuals, communities and populations with the necessary information.

Keywords: Health law, NCD, WHO, Nudge, Libertarian Paternalism, Behavioral change, Lifestyle, Regulation


Departments: Finance, GREGHEC (CNRS)

Political activism positively affects firm innovation. Firms that support more politicians, politicians on Congressional committees with jurisdictional authority over the firms’ industries and politicians who join those committees innovate more. We employ instrumental variables estimation and a natural experiment to show a causal effect of political activism on innovation. The results are consistent with the hypothesis that political activism is valuable because it helps reduce policy uncertainty, which, in turn, fosters firm innovation. Also consistent with this hypothesis, we show that politically active firms successfully time future legislation and set their innovation strategies in expectation of future legislative changes.

Keywords: political contributions, innovation, investment policy, policy uncertainty


Departments: Finance, GREGHEC (CNRS)

We study a dynamical model of interconnected firms which allows for certain market imperfections and frictions, restricted here to be myopic price forecasts and slow adjustment of production. Whereas the standard rational equilibrium is still formally a stationary solution of the dynamics, we show that this equilibrium becomes linearly unstable in a whole region of parameter space. When agents attempt to reach the optimal production target too quickly, coordination breaks down and the dynamics becomes chaotic. In the unstable, "turbulent", phase the aggregate volatility of the total output remains substantial even when the amplitude of idiosyncratic shocks goes to zero or when the size of the economy becomes large. In other words, crises become endogenous. This suggests an interesting resolution of the "small shocks, large business cycles" puzzle.

Keywords: volatility of aggregate output, network theory, rational expectations, general equilibrium


Departments: Economics & Decision Sciences, GREGHEC (CNRS)

A theory of incomplete preferences under uncertainty is proposed, according to which a decision maker’s preferences are indeterminate if and only if her confidence in the relevant beliefs does not match up to the stakes involved in the decision. We use the model of confidence in beliefs introduced in Hill (2013), and axiomatise a class of models, differing from each other in the appropriate notion of stakes. Comparative statics analysis can distinguish the decision maker’s confidence from her attitude to choosing in the absence of confidence. The model naturally suggests two possible strategies for completing preferences, and hence for choosing in the presence of incompleteness. One strategy respects confidence – it relies only on beliefs in which the decision maker has sufficient confidence given the stakes – whereas the other goes on hunches – it relies on all beliefs, no matter how little confidence the decision maker has in them. Axiomatic characterizations are given for each of the strategies. Finally, we consider the consequences of the model in markets, where indeterminacy of preference translates into refusal to trade. The incorporation of confidence adds an extra friction, beyond the standard implications of non-expected utility models for Pareto optima

Keywords: Incomplete preferences, confidence, multiple priors, choice under incomplete preferences, absence of trade


Departments: Finance, GREGHEC (CNRS)

As most Exchange-Traded Funds (ETFs) engage in securities lending or are based on total return swaps, they expose their investors to counterparty risk. To mitigate the funds' exposure, their counterparties must pledge collateral. In this paper, we present a framework to study collateral risk and provide empirical estimates for the $40.9 billion collateral portfolios of 164 funds managed by a leading ETF issuer. Overall, our findings contradict the allegations made by international agencies about the high collateral risk of ETFs. Finally, we theoretically show how to construct an optimal collateral portfolio for an ETF

Keywords: Asset management, passive investment, derivatives, optimal collateral portfolio, systemic risk


Departments: Economics & Decision Sciences, GREGHEC (CNRS)

Simple exchange rate models based on economic fundamentals were shown to have a difficulty in beating the random walk when predicting the exchange rates out of sample in the modern floating era. Using methods from machine learning -- sequential adaptive ridge regression -- that prevent overfitting in-sample for better and more stable forecasting performance out-of-sample we show that fundamentals from the PPP, UIRP and monetary models consistently improve the accuracy of exchange rate forecasts for major currencies over the floating period era 1973-2013 and are able to beat the random walk prediction giving up to 5% improvements in terms of the RMSE at a 1 month forecast. "Classic'' fundamentals hence contain useful information about exchange rates even for short forecasting horizons -- and the Meese and Rogoff (1983) puzzle is overturned. Such conclusions cannot be obtained when rolling or recursive OLS regressions are used as is common in the literature

Keywords: exchange rates, forecasting, machine learning, purchasing power parity, uncovered interest rate parity, monetary exchange rate models


Departments: Finance, GREGHEC (CNRS)

This paper proposes an indirect inference (Gourieroux, Monfort and Renault, 1993; Smith, 1993) estimation method for a large class of dynamic equilibrium models. Our approach is based on the observation that the econometric structure of these systems naturally generates auxiliary equilibria that can serve as building blocks for estimation. We use this insight to develop an accurate estimator for the long-run risk model of Bansal and Yaron (2004). We demonstrate the accuracy of our method by Monte Carlo simulation and estimate the long-run risk model on U.S. data. We also illustrate the good performance of the methodology on an asset pricing model with investor learning

Keywords: Hidden Markov model, long-run risk, learning, value at risk, indirect inference, particle filters