Threshold cointegration test of the Fisher effect

Xu, Biyong
Major Professor
Barry Falk
Committee Member
Journal Title
Journal ISSN
Volume Title
Research Projects
Organizational Units
Organizational Unit
Journal Issue

According to the Fisher hypothesis, the nominal interest rate moves one-to-one with the rate of inflation anticipated by the public, and the expected real rate of return is constant over time. The hypothesis implies that in the long run there is a one-to-one correspondence between changes of the nominal interest rate and the changes of inflation, which is often referred to as the Fisher effect in the literature.;To test the Fisher hypothesis, most of the previous empirical studies are using linear models in time series, which was predicated on the assumption that the path of adjustment towards long-run equilibrium is necessarily symmetric. The assumption of symmetric adjustment, however, may not be warranted. It is frequently argued that some fundamental economic variables, including the real GNP and the unemployment rate, display asymmetric adjustment paths, which cannot be properly modeled by linear models. Since the real interest rate is closely related to these variables, it may also follow an asymmetric adjustment path.;In this dissertation, we study the Fisher relationship within a fresh nonlinear framework. The dissertation is filling several blanks in the empirical literature. First, we test the stationarity of the nominal interest rate and the inflation rate under a nonlinear threshold autoregressive model, and it seems a unit root can not be rejected for most of countries under our study. Second, a two-stage threshold cointegration analysis has been applied to test for the presence of nonlinearity in the long-term equilibrium between the nominal interest rate and the inflation rate. We find some evidences nonlinearity in the Fisher relationship. Third, a two-regime threshold vector error correction model (TVECM) is used to explicitly model the nonlinearity and encompassing tests are carried out to compare the out-of-sample forecast efficiency of linear and nonlinear models. Our study seems to support the existence of the Fisher effect in the long run, which is consistent with previous studies.