In reviewing the lineages of the Phillips curve in Chapter 4, we saw that the relationship between wage growth and the level of economic activity (or unemployment) has a prominent position in the new classical macroeconomics literature; see, for example, Lucas and Rapping (1969, 1970) and Lucas (1972). Two issues were in focus. First, according to this literature, the causality of Phillips’ original model is reversed: if a correlation between inflation and unemployment exists at all, the causality runs from inflation to the level of activity and unemployment. Since price and wage growth are then determined from outside the Phillips curve, the rate of unemployment would typically be explained by the rate of wage growth (and/or inflation)...Read More
Category THE ECONOMETRICS OF MACROECONOMIC MODELLING
In this section, we discuss the dynamic properties of the full model. In the
simulations of the effects of an increase in the interest rate below we have not
Figure 9.9. Accumulated responses of some important variables to a 1 per
cent permanent increase in the interest rate RSt
incorporated the non-linear effect in the unemployment equation. Hence the results should be interpreted as showing the impact of monetary policy when the initial level of unemployment is so far away from the threshold value that the non-linear effect will not be triggered by the change in policy.
Figure 9.9 shows the simulated responses to a permanent rise in the interest rate RSt by 100 basis points, that is, by 0.01, as of 1994(1)...Read More
We derive a reduced form inflation equation for the ICM much in the same vein as for the AWM. The information set for this model is given by all variables included in the estimation of the price-unit labour cost system in Jansen (2004). The information set differs from that of the AWM on the following points: lags of changes in unit labour costs, Aulct, are used instead of lags of changes in trend unit labour costs; the changes in the wage share, Awst, the world commodity price index, Aptaw, and the GDP deflator at factor prices, Aqt, are not included; and the equilibrium-correction terms are those of the ICM,
Figure 8.6. Recursive estimates for the coefficients of the (reduced form)
AWM inflation equation
ecmpjCM and ecmulcjCM, which are derived from the estimated steady-state equat...Read More
The development of macroeconometric models in the course of the 1980s and 1990s, with more emphasis on dynamic specification and on model evaluation, meant that the models became less exposed to the critique against earlier generations of models, namely that models that largely ignore dynamics and temporal properties of the data, will necessarily produce suboptimal forecasts; see, for example, Granger and Newbold (1986: ch. 6). At the same time, other model features also changed in response to developments in the real economy, for example, the more detailed and careful modelling of the supply-side factors and the transmission mechanism between the real and financial sectors of the economy; see Wallis (1989) for an overview...Read More
We first model the long-run equilibrium equations for wages and prices based on the framework of Chapter 5. As we established in Section 5.4 the long-run equations of that model can be derived as a particular identification scheme for the cointegrating equations; see (5.19)-(5.20). Second, we incorporate those long-run equations as equilibrium correcting terms in a dynamic two-equation simultaneous core model for (changes in) wages and prices.
From equations (5.19)-(5.20), the variables that contain the long-run real wage claims equations are collected in the vector [wt pt at pit ut]’. The wage variable wt is average hourly wages in the mainland economy, excluding the oil producing sector and international shipping...Read More
Remember that the model is
APt = bp1Et APt+1 + bp1 APt —1 + bp2Xt + Zpt, which can be rewritten as
n = jEtnt+1 + SxH + vpt.
The model is usually estimated by means of instrumental variables, using the ‘errors in variables’ method (evm)—where expected values are replaced by
actual values and the expectational errors:
nt = Y^t+i + 5xt + vpt – YVt+i – (A.22)
The implications of estimating the model by means of the ‘errors in variables’ method is to induce moving average errors. Following Blake (1991), this can be readily seen using the expectational errors as follows.
1. Lead (A.15) one period and subtract the expectation to find the RE error:
3. Finally, re-express in terms of original variables, again using Apt = n + aApt-i:
Apt – aiApt-i = (— ) (Apt+i – aiApt) + ( ) xt + ( f— ) ...Read More