Forecasting Economic Time Series by Michael Clements, David Hendry

By Michael Clements, David Hendry

David Hendry is among the world's major econometricians, and during this significant new paintings he and Michael Clements offer a longer formal research of monetary forecasting with econometric versions: their research builds in lots of of the beneficial properties of the genuine international which are frequently neglected in conventional, textbook analyses of forecasting. therefore, Clements and Hendry may be able to recommend ways that present forecasting practices could be enhanced, in addition to supplying a motive for a few of the recurring practices of forecasters that experience hitherto lacked a systematic beginning.

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The random number generator used was that in PcNaive: see Hendry, Neale and Ericsson, 1991). To counter the dependence on the non-stochastic start-up conditions, we discarded the first 50 observations: the resulting time series were of length 188, corresponding to quarterly data from 1950:1 to 1996:4, say. All subsequent calculations and graphing of the data are performed using PcGive (see Hendry and Doornik, 1996b) and PcFiml (see Doornik and Hendry, 1997). The units and form of the model actually correspond best to a logarithmic formulation on annual data, so that St denotes the annual (log) savings ratio rather than the level of saving.

8. There is no evidence of model non-constancy from any of these statistics. 10) indicate the 6 As positive examples, the UK National Institute for Economic and Social Research now reports confidence bands around the main forecasts from its macroeconometric system, and the Bank of England does so graphically for its inflation forecasts (known in the trade as 'rivers of blood' from the colour coding). 44 deterioration in forecast performance, particularly for St. In chapter 6, we provide a formal analysis of the impact of omitting equilibrium correction terms.

24 An introduction to forecasting whenever the column dimension of a and f3 is less than the number of variables in the system. 2 reports trace and maximum eigenvalue tests for the rank of TT, along with the 95 percent critical values (given automatically by PcFiml). We (correctly) infer that the cointegrating rank is 1, so that there is one stationary or 1(0) linear combination of the variables. Finding two linearly independent 1(0) combinations would have been at odds with Ct and Yt being individually 1(1).

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