The Department of Economics at the University of Warwick has an active Economic Development and History Research Group, with a weekly external seminar, a weekly internal workshop, and high quality PhD students. We also organise international conferences on campus, or in Venice.
Economic History and Development Workshop/Seminar
For faculty and PhD students at Warwick and other top-level academic institutions across the world. For a detailed scheduled of speakers please follow the link below:
History and Development Workshops
Organisers: Yannick Dupraz
Academics associated with the Economic Development and History Research Group are:
CWIP Lunchtime Workshop - Eric Renault
Title of talk is Identification Robust Inference for Risk Prices in Structural Stochastic Volatility Models.
Co-authors : Xu Cheng and Paul Sangrey (University of Pennsylvania)
Abstract: In structural stochastic volatility asset pricing models, changes in volatility affect risk premia through two channels: (1) the investor’s willingness to bear high volatility in order to get high expected returns as measured by the market return risk price, and (2) the investor’s direct aversion to changes in future volatility as measured by the volatility risk price. Disentangling these channels is difficult and poses a subtle identification problem that invalidates standard inference. We adopt the discrete-time exponentially affine model of Han, Khrapov, and Renault (2018), which links the identification of the volatility risk price to the leverage effect. In particular, we develop a minimum distance criterion that links the market return risk price, the volatility risk price, and the leverage effect to well-behaved reduced-form parameters that govern the return and volatility’s joint distribution. The link functions are almost flat if the leverage effect is close to zero, making estimating the volatility risk price difficult. We translate the conditional quasi-likelihood ratio test that Andrews and Mikusheva (2016) develop in a nonlinear GMM framework to a minimum distance framework. The resulting conditional quasi-likelihood ratio test is uniformly valid. We invert this test to derive robust confidence sets that provide correct coverage for the risk prices regardless of the leverage effect’s magnitude.