Published online by Cambridge University Press: 16 March 2018
We investigate the demand for money and the degree of substitutability among monetary assets in the United States using the generalized Leontief and the Minflex Laurent (ML) models as suggested by Serletis and Shahmoradi (2007). In doing so, we merge the demand systems literature with the recent financial econometrics literature, relaxing the homoskedasticity assumption and instead assuming that the covariance matrix of the errors of flexible demand systems is time-varying. We also pay explicit attention to theoretical regularity, treating the curvature property as a maintained hypothesis. Our findings indicate that only the curvature constrained ML model with a Baba, Engle, Kraft, and Kroner (BEKK) specification for the conditional covariance matrix is able to generate inference consistent with theoretical regularity.
This paper is based on Chapter 4 of Dongfeng Chang's Ph.D. dissertation at the University of Calgary. We would like to thank Bill Barnett and the following members of Dongfeng's dissertation committee: Herbert Emery, Daniel Gordon, Ron Kneebone, David Walls, and Philip Chang.