Summary of the findings—Norway vs. Euro area

The overall conclusion from the comparisons of inflation models for the Norwegian economy is that monetary measures do not play an important part in explaining and/or predicting Norwegian inflation. The preferred specifica­tions of money demand do not include inflation as a significant explanatory
variable and hence the money demand equation cannot be interpreted as an inverted inflation equation. An attempt to model an inflation equation as an inverted money demand function shows clear signs of mis-specification and the MdInv model is demonstrated to be inferior to all other competitors based on in-sample evaluations as well as in forecasting (Figure 8.19). Also the P*-model, which embody several aggregates which monetarist theorists predict would explain inflation, fails to do so...

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Undetermined coefficients

This method is more practical. It consists of the following steps:

1. Make a guess at the solution.

2. Derive the expectations variable.

3. Substitute back into the guessing solution.

4. Match coefficients.

We will first use the technique, following the excellent exposition of Blanchard and Fisher (1989: ch. 5), to derive the solution conditional upon the expected path of the forcing variable, as in Gall et al. (2001), so we will ignore any information about the process of the forcing variable.

In the following we will define

zt — bp2xt + &pt-

Since the solution must depend on the future, a guess would be that the solution will consist of the lagged dependent variable and the expected values of the forcing value:


Apt — aAp—i + 53 PiEtZt+i■ (A.19)


We now take the expectation o...

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Dynamic models

The equilibrium-correction model provides a flexible dynamic specification for the money demand function. This entails explicit and separate modelling of the short-run dynamic specification and the long-run cointegrating relationship for mt, which allows us to distinguish between shocks which will only cause tem­porary effects on money holdings and shocks with persistent long-run effects. Furthermore, the economic variables which exert the strongest short-run effects in money holdings, say, in the first quarters following the shock, need not be the same as the variables which drive money holdings in the long run...

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Model performance

The model (9.5)-(9.13) is a small econometric model for Norway, which is characterised by the inclusion of labour market effects in addition to effects of aggregated demand and the exchange rate. The motivation for the extended model is given in the preceding chapters: in order to capture the effects of monetary policy in general and on inflation in particular, it is essential to include the workings of the labour market.

Figure 9.6 gives an overview of the transmission mechanism in the model, focusing on the relationship between interest rates and inflation. The most direct effect on inflation from a rise in the interest rate is an exchange rate appreciation which feeds into lower consumer price inflation with a time lag...

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Empirical evidence from Euro-area data

In this section, we present estimated reduced form versions of the AWM and ICM inflation equations in order to evaluate the models and to compare fore­casts based on these equations with forecasts from the inflation models referred to in Section 8.5, that is, the P*-model and the NPCM. The models are estim­ated on a common sample covering 1972(4)-2000(3), and they are presented in turn below, whereas data sources and variable definitions are found in Jansen (2004).

8.6.1 The reduced form AWM inflation equation

We establish the reduced form inflation equation from the AWM by combining the wage and price equations of the AWM (see appendix B of Jansen 2004)...

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Forecasting using. econometric models

The non-stationary nature of many economic time series has a bearing on virtually all aspects of econometrics, including forecasting. Recent devel­opments in forecasting theory have taken this into account, and provide a, framework for understanding typical findings in forecast evaluations: for example, why certain types of models are more prone to forecast fail­ure than others. In this chapter we discuss the sources of forecast failure most likely to occur in practice, and we compare the forecasts of a large econometric forecasting model with the forecasts stemming from simpler forecasting systems, such as dVARs...

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