Working Papers This paper studies risk premia in the foreign exchange market when investors entertain multiple models for consumption growth. Investors confront two sources of uncertainty: (1) individual models might be misspecified, and (2) it is not known which of these potentially misspecified models is the best approximation to the actual data-generating process. Following Hansen and Sargent (2010), agents formulate `robust' portfolio policies. These policies are implemented by applying two risk-sensitivity operators. One is forward-looking, and pessimistically distorts the state dynamics of each individual model. The other is backward-looking, and pessimistically distorts the probability weights assigned to each model. A robust learner assigns higher weights to worst-case models that yield lower continuation values. The magnitude of this distortion evolves over time in response to realized consumption growth. It is shown that robust learning not only explains unconditional risk premia in the foreign exchange market, it can also explain the dynamics of risk premia. In particular, an empirically plausible concern for model misspecification and model uncertainty generates a stochastic discount factor that uniformly satisfies the spectral Hansen-Jagannathan bound of Otrok et. al. (2007).

This paper studies the Forward Premium Puzzle in a setting where investors doubt the specification of their models, and thus engage in robust portfolio strategies ( Hansen and Sargent, 2008). It shows that an empirically plausible concern for model misspecification can explain the Forward Premium Puzzle. In particular, the paper shows that Hansen and Jagannathan (1991) volatility bounds can be attained with both reasonable degrees of risk aversion and reasonable detection error probabilities. Hence, observed excess returns in the foreign exchange market appear to be primarily driven by a model uncertainty premium.

This paper studies exchange rate volatility within the context of the monetary model of exchange rates. We assume that agents regard this model as merely a benchmark, or reference model, and attempt to construct forecasts that are robust to model misspecification. We show that revisions of robust forecasts are more volatile than revisions of nonrobust forecasts, and that empirically plausible concerns for model misspecification can explain observed exchange rate volatility. We also briefly discuss the implications of robust forecasts for a number of other exchange rate puzzles.

Two approaches are used to analyze the sustainability of the current account deficits of Cameroon in order to find out whether current economic policies are sound enough to guarantee the country’ s financial solvency.  The first uses a structural procedure to compare current account deficits relative to an optimal benchmark using the Campbell-Shiller’s methodology. The second uses a reduced form approach to test for intertemporal budget constraint through cointegration tests between imports and exports plus net transfer payments on foreign obligations.  Our results suggest that the current account imbalances for Cameroon based on data from the period 1970-2002 are “excessive” and the deficits are currently unsustainable.

  • Work in Progress
  1. Recursive robust mean field games, 2016 (With Kenneth Kasa)
  2. Heterogeneous agent model with fear of model misspecification : A Mean Field Game Approach (2015)
  3. Supply chain, intermediation and international trade, 2015 (with Nicolas Schmitt)
  4. Inference for Nonlinear Exchange Rate Dynamics (2013)[slides]

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International Economic Analysis Department
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