Is the nominal interest stationary

Introductory studies on interest structure models

Modeling the Interest Structure in Germany pp 23-76 | Cite as

Part of the Gabler Edition Science book series (GEW)


Interest structure models can be differentiated according to whether they model the short-term interest rate as an integrated or a stationary process. In particular, it assumes a stochastic differential equation with a mean value tendency (mean reversion) for the process of the underlying factor stationarity.1 While in the empirical financial literature on interest structure models, interest rates are regarded as random variables of satational processes, empirical macroeconomic studies mostly proceed I.(1) processes. Aït-Sahalia (1996) explains this with the fact that the data there is too low in frequency; Tests of his work on the basis of daily data allow for a I.Close (0) property.2 It can be countered that, according to the Monte Carlo studies in Perron (1991), the expressiveness (power) less common stationarity tests. Stock / Watson (1993) argue that interest rates are conceptually not as random variables of I.(1) processes can apply. A process with time-dependent variance results in negative observation values ​​for an infinite time horizon, whereas nominal interest rates are always positive. Consequently, the test result of non-stationarity for interest rates can only be justified in the limited observation period. Against this, it must be countered that an integrated process can follow a path with exclusively positive values ​​with a positive probability. Still is but ex antethe probability of negative observation values ​​in the future is strictly positive. The first subsection of this chapter is devoted to this problem.

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© Springer Fachmedien Wiesbaden 1999

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