Research Paper Series

  • Title
  • Author(s)


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


Departments: Operations Management & Information Technology, GREGHEC (CNRS)

We examine the effect of a hospital's objective (i.e., non-profit versus for-profit) in hospital markets for elective care. Using game-theoretic analysis and queueing models to capture the operational performance of hospitals, we compare the equilibrium behavior of three market settings in terms of such criteria as waiting times and the total patient cost from waiting and hospital care payments. In the first setting, patients are served exclusively by a single non-profit hospital; in the second, patients are served by two competing non-profit hospitals. In our third setting, the market is served by one non-profit hospital and one for-profit hospital. A non-profit hospital provides free care to patients, although they may have to wait; for-profit hospitals charge a fee to provide care with minimal waiting. A comparison of the first two settings reveals that competition can hamper a hospital's ability to attain economies of scale and can also increase waiting times. A comparison between the second and third settings indicates that, when the public funder is not financially constrained, the presence of a for-profit sector may allow the funder to lower both the financial costs of providing coverage and the total costs to patients. Our analysis suggests that the public funder should exercise caution when using policy tools that support the for-profit sector -- for example, patient subsidies -- because such tools may increase patient costs in the long run; it might be preferable to raise the level of reimbursement to the non-profit sector

Keywords: hospitals, for-profit healthcare, non-profit healthcare, queueing models, service provider competition


Departments: Finance, GREGHEC (CNRS)

This paper uses reductions of import tariffs to examine how incumbents modify their investment decisions when the threat of entry by foreign rivals suddenly intensifies. We find that incumbents significantly reduce investment by 8.6% in response to higher entry threat following tariff reductions. Various tests indicate that this finding is robust and likely causal. Moreover, and in consistency with strategic investment models, we provide evidence suggesting that the reduction of investment is related to strategic motives to influence the competitive behavior of foreign rivals. Overall, the paper provides novel evidence on how strategic interactions in the product market influence firms' investment decisions

Keywords: Corporate investment, Entry Threat, Tariff Reduction, Strategic Interactions


Departments: Accounting & Management Control, GREGHEC (CNRS)

The purpose of this article is to explore the role of instruments in the transformation of institutional logics and their associated practices at the micro level. Based on an ethnographic study, this article compares two working groups — one responsible for equity and the other for fixed-income investments — in an asset management company attempting to integrate new demands for socially responsible investment (SRI). These two working groups both sought to change their investment processes through the introduction of new calculative devices. The equity group was perceived to be more successful than the fixed-income group in introducing SRI because of its greater ability to fabricate calculative devices capable of mediating between financial returns and social responsibility. Elaborating on these findings, the article argues that instruments can effect institutional change when actors come to believe that available instruments are sufficiently flexible and incomplete to act as "mediating instruments" between practice and institutional change

Keywords: Equity Investment, Fixed-Income Investment, Institutional Logics, Mediating Instruments, Materiality, Socially Responsible Investment


Departments: GREGHEC (CNRS), Strategy & Business Policy

The important role of entrepreneurship in the dynamics of the arts sector and the influence of the leader’s personality make succession a key issue in creative industries. What happens to an artistic organization when its founder leaves? How does it evolve? Can it adopt a style of management that is compatible with the founder’s absence? This article focuses on the case of Groupe Bernard Loiseau, an iconic French company in the culinary arts whose owner and chef died suddenly. It sheds light on how the question of succession and that of style were addressed in this organization and how they are addressed in artistic organizations in general

Keywords: Succession, culinary art, entrepreneurial management, creative industries


Departments: Finance, GREGHEC (CNRS)

This paper investigates the determinants of value and growth investing in a large administrative panel of Swedish residents over the 1999-2007 period. We document strong relationships between a household's portfolio tilt and the household's financial and demographic characteristics. Value investors have higher financial and real estate wealth, lower leverage, lower income risk, lower human capital, and are more likely to be female than the average growth investor. Households actively migrate to value stocks over the life-cycle and, at higher frequencies, dynamically offset the passive variations in the value tilt induced by market movements. We verify that these results are not driven by cohort effects, financial sophistication, biases toward popular or professionally close stocks, or unobserved heterogeneity in preferences. We relate these household-level results to some of the leading explanations of the value premium.

Keywords: Value premium, household finance, portfolio allocation, human capital


Departments: Strategy & Business Policy, GREGHEC (CNRS)

We propose a task for eliciting attitudes towards risk that is close to real world risky decisions which typically involve gains and losses. The task consists of accepting or rejecting gambles that provide a gain with probability p and a loss with probability 1 - p. We employ finite mixture models to uncover heterogeneity in risk preferences and find that (i) behavior is heterogeneous, with slightly less than one half of the subjects behaving as expected utility maximizers, (ii) for the others, reference-dependent models perform better than those where subjects derive utility from final outcomes, (iii) models with sign dependent decision weights perform better than those without, and (iv) there is no evidence for loss aversion. The procedure is sufficiently simple so that it can be easily used in field or lab experiments where risk elicitation is not the main experiment.

Keywords: Individual risk taking behavior; latent heterogeneity; finite mixture models; reference-dependence; loss aversion