Category THE ECONOMETRICS OF MACROECONOMIC MODELLING

An encompassing representation

The main alternatives to the NPCM as models of inflation are the Standard Phillips Curve Model (PCM) and the Incomplete Competition Model (ICM). They will therefore be important in suggesting ways of evaluating the NPCM from an encompassing perspective. To illustrate the main differences between alternative specifications, consider the following stylised framework—see also Bardsen et al. (2002a). Let w be wages and p consumer prices; with a as productivity, the wage share ws is given as real unit labour costs: ws = ulc — p = w — a —p; u is the unemployment rate, and gap the output gap, all measured in logs. We abstract from other forcing variables, like open economy aspects. A model of the wage-price process general enough for the present purpose then takes the form

Aw = aApe — fiw...

Read More

Closing the model: marginal models for feedback variables

We have established a wage-price model conditional upon the exchange rate vt (which works through pit), GDP mainland output yt, the rate of unemploy­ment ut, and average labour productivity at. In this section, we enlarge the model to include relationships for these four variables and functions for real credit crt, and two interest rates: for government bonds RBOt and for bank loans RLt. This serves three purposes: first, all of these variables are affected by the monetary policy instrument (represented in the model by the money market interest rate) and are therefore channels for monetary instruments to influence inflation; second, none of these variables are likely to be strongly exogenous. For example, import prices depend by definition on the nominal exchange rate...

Read More

Calculation of interim multipliers in a linear dynamic model: a general exposition

Interim multipliers provide a simple yet powerful way to describe the dynamic properties of a dynamic model. We follow Lutkepohl (1991) and derive the dynamic multipliers in a simultaneous system of n linear dynamic equations with n endogenous variables yt and m exogenous variables xt. The structural

form of the model is given by:

q q

r0yt riyt-i + – i+£t – (A.23)

i=1 i=0

To investigate the dynamic properties of the model it will be more convenient to work with the reduced form of the model:

qq

yt=£ Aiyt-i+£ Bi xt-i+ut (A.24)

i=1 i=0

defining the n x n matrices Ai = Г-1Гі, i = 1,…,q, and the n x m matrices
Bi = r-1Di, i = 0,…,q. The reduced form residuals are given by ut= r-1et.
It is also useful to define the autoregressive final form of the model as:

yt = A(L)-1B(L)xt + A(L)-1ut (A.25)

Read More

8.4 Monetary analysis of Norwegian data

8.4.1 Money demand in Norway—revised and extended data

The demand for broad money in Norway has previously been analysed by Eitrheim (1998) using seasonally unadjusted data from 1969(1) to 1993(4). In that study a cointegrating relationship for money was derived jointly with

 

cointegrating relationships for wages and consumer prices, and the analysis showed that in the long run, real money balances adjust dynamically to absorb shocks in the real GDP level and the relative price of financial assets (the yield spread) and the relative price of goods (the own real interest rate). In the short run, money balances were also affected by shocks in the exchange rate and private wealth...

Read More

Revisions of output data: a case for real-time variables?

A first version of the quarterly national accounts (QNA) data is published by Statistics Norway shortly after the end of each quarter, based on a limited information set. As more information accrues, the data are revised and the final figures appear with a 18-months lag. Often there are substantial discrep­ancies between the first and the final quarterly data. The Norwegian QNA show that on average for the period 1995-99 growth in GDP for Mainland Norway was revised up by almost 1 percentage point per year, and, for example, the output growth for 1999 was adjusted from 1.1% to 2.7%. In Figure 10.1(a) we plot the growth rates for output according to the two sources together. The graphs reveal substantial revisions of output growth in the Norwegian mainland economy...

Read More

Evaluation of the inflation models’ properties

In this section, we summarise the statistical properties of the different infla­tion models, in order to make more formal comparisons. In Table 8.6 we have collected the p-values for the mis-specification tests for residual autocorrela­tion, autoregressive conditional heteroskedasticity, non-normality, and wrong functional form. With the exception of the normality tests which are x2(2), we report F-versions of all tests, as in the previous sections. We also report k, the number of estimated coefficients, and aAp%, the estimated standard error.

One way of condensing this information is to perform encompassing tests.[80] In Table 8.7 we consider AWM as the incumbent model, the one we want to

Подпись: Table 8.6 Mis-specification tests Ap model к aAp% p values FAR(1-5) FARCH(1-5) ^normality F HETx2 F RESET AWM 13 0.19 0.84 0.78 0.60 0.17 0.80 ICM 11 0.21 0.68 0.95 0.92 0.87 0.09 p* 12 0.21 0.76 0.61 0.81 0.70 0.008** P*_enh 14 0.19 0.66 0.56 0.15 0.77 0.93 NPCM 7 0.23 0.00** 0.48 0.08 О о 1—1 *

Подпись: 19

image157

Table 8.7

Encompassing tests with AWM as incumbent model

Ap

k

u

c

Ш

LL

Read More