Handbook of Economic Forecasting part 84 docx
Handbook of Economic Forecasting part 84 docx
... using
ˆ
θ
T
in place of the true unknown parameters in the
forecasting formulas. Of course, in many financial applications the size of the sample
used in the parameter estimation phase is often very large ... in excess of
those for the normal distribution for small values of p. Of course, the exact value of
F
−1
z
(p) will depend upon the specific parametric estimates for the di...
Handbook of Economic Forecasting part 7 docx
... linear combination of the elements of
Y (his exam-
ple of such a function of interest is a discounted sum) will be distributed as univariate
Student-t, so that expectations of such linear combinations ... applications of Metropolis within Gibbs in Bayesian
forecasting models.
3.3. The full Monte
We are now in a position to complete the practical Bayesian agenda for forecastin...
Handbook of Economic Forecasting part 9 docx
... of the outcome of the conventional procedure for
determining the rank of the error correction matrix.
The paper offers an extensive comparison of root mean square forecasting errors for
all of ... treated as a function of φ, is the kernel of a p-variate normal distri-
bution. If the prior distribution of φ is Gaussian, truncated to S
p
, then the same is true of
the produc...
Handbook of Economic Forecasting part 11 docx
... Honor of Arnold Zellner. Wiley, New York,
pp. 243–256.
McNees, S.K. (1975). “An evaluation of economic forecasts”. New England Economic Review, 3–39.
McNees, S.K. (1986). Forecasting accuracy of ... Ph.D. thesis,
University of Wisconsin, Unpublished.
Chapter 2
FORECASTING AND DECISION THEORY
CLIVE W.J. GRANGER and MARK J. MACHINA
Department of Economics, University of Calif...
Handbook of Economic Forecasting part 15 docx
... Ee
1t+1
x
t
= 0 with
out of sample prediction errors.
The remainder of this section considers the implications of a test that does fail the
rank condition of the theory of the previous section ... models.
6. A small number of models, nested: MSPE
Analysis of nested models per se does not invalidate the results of the previous sections.
A rule of thumb is: if the rank of th...
Handbook of Economic Forecasting part 25 docx
... approach of DGT) should be of interest from the perspective of
out -of- sample evaluation. For this reason, and for sake of completeness, in this section
we provide out -of- sample versions of all of the ... set of moment conditions
which are satisfied under the null of a particular distribution. This leads to a GMM
type test. Of interest is the fact that, the tests suggested...
Handbook of Economic Forecasting part 26 docx
... of the estimation scheme used, the contribution of parameter
estimation error is asymptotically negligible.
3.3. Out -of- sample implementation of Corradi and Swanson tests
We now outline out -of- sample ... following
sections, application of Theorem 3.6 allows us to capture the contribution of (recur-
sive) parameter estimation error to the covariance kernel of the limiting distr...
Handbook of Economic Forecasting part 28 docx
... →∞.
P
ROOF. For the proof of part (ii), see Appendix B.
Note that under the null, the least favorable case arises when E(g(u
1,t+1
) −
g(u
k,t+1
)) = 0, ∀k. In this case, the distribution of S
P
coincides ... check whether a more accurate forecasting
model can be constructed by including possibly unknown (non)linear functions of the
past of the process or of the past of some...
Handbook of Economic Forecasting part 44 docx
... Journal
of Forecasting 6, 187–198.
Harvey, A.C., Todd, P.H.J. (1983). Forecasting economic time series with structural and Box–Jenkins models
(with discussion)”. Journal of Business and Economic ... analysis of a cross-section of time series by stochas-
tically convergent parameter regression”. Annals of Economic and Social Measurement 2, 399–428.
Schweppe, F. (1965). “Eval...
Handbook of Economic Forecasting part 71 docx
... w
Sn+s
is a vector of I(0) variables that can include lags of
1
y
Sn+s
. Three
forecasting models can be considered: the complete true model given by (41), the long-
run forecasting model of y
Sn+s
= ... forecast horizon of h = 8, or two years. In this sense,
the specification of seasonality as being of the nonstationary stochastic or deterministic
form may not be of great...
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