Motivated by economic-theory concepts - the Fisher hypothesis and the theory of the term structure - we consider a small set of simple bivariate closed-loop time-series models for the prediction of price inflation and of long- and short-term interest rates. The set includes vector...

The New-Keynesian Phillips curve has recently become an important ingredient in monetary policy models. However, using limited information methods, the empirical support for the New-Keynesian Phillips curve appear to be mixed. This paper argues, by means of Monte Carlo simulations with a simple...

In this paper, I investigate quantitatively how sensitive a typical backward-looking model used in monetary plicy analysis is to the Lucas critique. To do this, I use an equilibrium business cycle model with a Taylor-type rule for nominal money growth. The backward-looking model displays...

In this paper, I try to shed some new light on the puzzle why the Lucas critique, belived to be important by most economists, seems to have received very little empirical support. I use a real business cycle model to examine the properties of the super exogeneity test, which is used to detect...

Using data from Germany, Japan, UK, and the U.S., we explore possible threshold cointegration in nominal short- and long-run interest rates with corresponding inflation rates. Traditional cointegration implies perfect mean reversion in real rates and hence confirms the Fisher hypothesis....

In systems of variables with a specified or already identified cointegrating rank, stationarity of component variates can be tested by a simple restriction test. The implied decision is often in conflict with the outcome of unit root tests on the same variables. Using a framework of Bayes...

Many macroeconometric models depict situations where the shares of the major demand aggregates in output are stable over time. The joint dynamic behavior of the considered demand aggregate and output may thus be approximated by a cointegrated vector autoregression. However, the shares of many...