In an economy with multiple sources of risk, the short-term interest rate does not capture all the information that determines the conditional distribution of bond yields. This is also true for path-dependent term structure models. In either case, the current short rate level is not a sufficient statistic for the conditional density of future short rates. This paper studies the empirical relevance of both issues from a time-series nonparametric perspective. The analysis is formulated as a test for the dependence of the short rate drift and diffusion on variables other than the short rate, and exploits Ait-Sahalia, Bickel, and Stocker (2001) dimension reduction method. The paper explores the finite sample performance of the method and applies the test to US interest rate data. Results reject a single-factor Markovian model, although conclusions are sensitive to the choice of additional conditioning variables.
SNDE recognizes that advances in statistics and dynamical systems theory can increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.