Handbook of Economic Forecasting part 107 pps

I-22 Subject Index
Federal Reserve Board 749
feedback 704
FIEGARCH 806
filter 799
filtering 814, 882
filtering problem 782
final equations form 311
financial risk management 203
financial time series 662
first order term 565
fixed scheme 107
fixed-weighted data 971
flexible Fourier form 698
forecast biases 620
forecast combination 23, 141, 438, 520, 864
forecast combination puzzle 186
forecast comparisons 416
forecast distributions 809
forecast efficiency 975
forecast encompassing 101, 109, 157
forecast errors 101, 611, 975
forecast evaluation 101, 106, 782, 786, 855
forecast horizon 843, 937
forecast loss function 787, 854
forecast MSE 296, 462
forecast performance 610
forecast pooling 883
forecast quality 785
forecast-equivalent labeling 92
forecast-origin 613

forecast-origin inaccuracy 611
forecasting aggregated processes 299
forecasting competitions 607
forecasting conditional covariances and correla-
tions 786
forecasting “horse race” 52
forecasting performance 883, 934
forecasting vector of interest 9
forecasting volatility 854
forecasting with estimated processes 316
forward premium 592
fractional integrated EGARCH 806
fractional integration 59
fractionally integrated FIGARCH 805
frequentist formulation 23
fully efficient forecasts 786
GARCH 111, 405, 615, 782
GARCH volatility 798
GARCH(1, 1) model 696
GDP 881
generalized error distribution 813
generically comprehensively revealing activation
functions 475
Gibbs sampler 31, 826
GMM 112
Goldsmith–Nagan Bond and Money Market Let-
ter 736, 758
Gompertz function 999
Granger causality 301
Granger causality tests 976

greedy algorithm 472
gross national product 884
growth or deviation cycle 881
GW test 443
“h-block” cross-validation 482
heavy-tailed distributions 399
hedging problem 67
heterogeneity 716
heterogeneous information 722
hidden Markov regression model 421
hierarchical Bayes 1002
hierarchical prior 11, 12
high-frequency data 786, 830
higher order integrated process 305
highest density region 438
highly nonlinear approximation 471
hold-out sample 494
Holt–Winters procedure 358
h step ahead forecast 565
“hv-block” cross-validation 482
hyperbolic tangent function 418
hyperparameters 12
IFO 751, 764
IGARCH 800
impact parameter 584
implied volatility 780, 838
importance sampling 25, 29
impulse response functions 1005
in-sample forecasts 977
index of leading indicators 963

industrial production 881, 884
inflation expectations 730
inflation forecasting 63
inflection point 992
information criteria 520, 896, 974
information set 782
initial condition 563
innovation outlier 625
innovations 364
INSÉE 747
Subject Index I-23
instantaneous elasticity 998
Institut für Wirtschaftsforschung 735
Institute of Supply Management survey 735
integrated GARCH 800
integrated process 290, 905
integrated variance 784, 795
integrated volatility 784, 795
integration by Arnold Zellner 43
intercept corrections 633
interpreting approximation-based forecasts 485
interpreting linear forecasts 484
interpreting nonlinear forecasts 490
interval forecast 438, 788, 859, 860
intervention variables 354
intra-daily seasonality 696
invertibility 425
invertibility condition for the MA operator 293
Iowa Economic Forecast 68
Italy’s Survey of Household Income and Wealth

736
Japan Centre for International Finance 760
Joseph Livingston 735
jump 818
jump component 835
Kalman filter 43, 362, 821, 895, 978
Kalman smoother 895
kernel 27
kernel density estimator 201
Kolmogorov 203
Kolmogorov–Smirnov test 202
Koyck model 993, 994
Koyck transformation 994
Kronecker indices 308
Kuipers Score 85
Kullback–Leibler Information Criterion (KLIC)
205
Lagrange multiplier 427
latent class 1002
latent variables 8, 814
latent volatility process 820
latest-available data 970
latest-available forecasts 972
LDGP 608
leading indicators 54, 382, 881
left-coprime operator 307
level shifts 625
leverage effects 11, 803
likelihood function 8, 846
likelihood ratio tests 314

limiting distribution 203
Lin-Lin 731, 732, 758, 759
linear forecasts 289
linear models 289
linear parametric model 463
linear transformations of VARMA process 294
LINEX 731, 732
Litterman prior 46
Livingston Survey 735, 736, 748, 750
Ljung–Box statistics 863
local DGP 608
local level model 337
local linear trend 339
local power 560
local to unity 560
location shifts 620
location-dependent error-based form 96
log probability score 935
log-likelihood function of VARMA model 311
logical consistency 17, 1004
logistic function 418, 928, 999
logistic STR model 419
logit 890, 993
long horizon 565, 579
long horizon forecasts 125
long memory 12, 59, 805
long run models 681
long run variance 113
loss function 20, 83, 93, 103, 104, 141, 447,
897

marginal likelihood 15
marginal process 295
marginalization 10
market microstructure frictions 853
market share attraction model 997
market shares 986, 988
market timing tests 860
marketing activities 985
marketing-mix 987
Markov chain 421, 890
Markov chain Monte Carlo (MCMC) 30, 826
Markov chain Monte Carlo model composition
539
Markov-switching model (MS) 421, 636, 693,
882
martingale difference 120, 721
martingale processes 756, 757
martingalization 204
matrix Student-t 42
maximum likelihood 112, 200, 910
I-24 Subject Index
Maximum Likelihood Estimation 807
MDH 815
mean absolute error 109, 440, 935
mean absolute prediction error 101, 104, 110
mean prediction error 104, 109
mean square error 205, 559, 895
mean square forecast error 13, 101, 424, 663,
935
mean squared error (MSE) loss 88, 142

mean utility or profit 104
measures of performance 104
Method of Simulated Moments (MSM) 823
methods of moments 200
Metropolis independence chain 33
Metropolis random walk 33
Metropolis within Gibbs 34
Metropolis–Hastings algorithm 33
Michigan Survey 734, 754, 760, 761, 763, 765,
766
Mincer–Zarnowitz volatility regression 856
minimum MSE forecast 296
Minneapolis Fed model 69
“Minnesota” prior 45
missing observations 369, 883
misspecification bias 138
misspecification test 429
misspecified models 462, 481
misspecified seasonal models 672
mixed estimator 47
mixed normal distribution 594
mixture model 816
mixture model for time-variation in the combina-
tion weights 168
mixture of distributions hypothesis 815
model instability 154
model selection 200, 481, 977
model selection criteria 430
model specification 782, 815
moment matching 821

momentum-TAR model 420
monetary policy 705
Monetary Policy Committee 737
Money Market Services Inc. 755
Monte Carlo 570, 637, 811, 974
Monte Carlo forecast 434
MSPE-adjustment 121
multi-level regression model 993
multicollinearity 44
multinomial logit 993
multinomial probit 993
multiple structural break 623
multistep predictions 118, 200, 416
multivariate 600, 786
multivariate GARCH 841
multivariate innovations algorithm 297
multivariate normal 12
multivariate stochastic volatility 847
multivariate Student-t density 42
multivariate volatility 839
National Association of Business Economists
736
National Association of Purchasing Managers’
Surveys 752
national income account data 974
NBER 895
nearly nonstationary model 560
nested models 102, 117
Netherlands’ Socio-Economic Panel 765
Netherlands’ VSB Panel Survey 736

neural networks 170, 416, 883
new product diffusion 989, 991
new product introduction 986
nonlinear approximations 469
nonlinear combination 165, 169
nonlinear dynamic regression model 417
nonlinear forecasting 416
nonlinear least squares 467, 493, 502
nonlinear model 117, 200, 416, 635, 691, 886,
985
nonlinear model building 417
nonlinear moving average model 424
nonlinear parametric model 466
nonlinearities 391
nonnested model 104, 123
nonnormal 119, 306
nonparametric 117
nonparametric combination 160
nonparametric empirical Bayes 544
nonparametric forecasting 416
nonrejection 18
nonstationarity 560, 647
“normal-diffuse” prior 51
normal-gamma posterior 41
normal-Wishart 50
normal-Wishart sampling 71
‘nowcasting’ 340
nuisance parameters 204, 563
numerical integration 6
numerical solutions 637

numerical standard error 29
Subject Index I-25
objective function 88
observed transition model 883
one step ahead prediction error 107
one-step-ahead forecasts 54
optic scanner data 985
optimal action function 89
optimal combination 141, 521
optimal forecast 788, 854
optimal hedging strategy 67
optimal linear approximation 463
optimal nonlinear approximation 466
optimal point forecast 467
option valuation 794
order of integration 305
ordered regression model 993
ordinary least squares estimator 465
orthogonality condition 112, 728
orthogonality regression 598
out-of-sample forecast error 598
out-of-sample forecasting 827, 977
outliers 400, 625, 882
output gap 976
overall tightness 47
overfit 480
overidentified 112
Panel Survey of Income Dynamics 750
panels of time series 993
PAR (periodic autoregressive) models 683

parameter constancy 608, 909
parameter estimation error 131, 202
parameter fluctuation test 624
parameter instability 623
parameter-estimation uncertainty 609
parameterization 463, 466, 468, 474
parametric empirical Bayes 544
parametric rate 201
particle filter 827
pattern recognition algorithm 929
PCA: large-n theoretical results 529
peak 881
periodic cointegration 688
periodic GARCH model 700
periodic integration 684
periodic model 360, 683
periodic process 304
periodic stochastic volatility model 701
permanent shifts 625
persistence in the performance of forecasting
models 184
Philadelphia Fed’s Survey of Professional Fore-
casters 736
Phillips curve 976
piecewise linear model 420
pivotal test statistic 18
plug-in principle 467
point expectations 720
point forecast 37, 83, 200, 431, 787
point-forecast equivalent 90

point-forecast/point-realization loss function
89
point-in-time sampling 302
polynomials 500
pooling 635
pooling information 143
portfolio allocations 10
portfolio diversification 137
portfolio weights 839
posterior density 16
posterior distribution 11
posterior odds ratio 15
posterior pdf 907
posterior predictive distributions 17
posterior probability 15, 205
posterior simulation 25
power 123, 204
predictability 966
predicting business cycle phases 883
prediction error decomposition 368
predictive Bayes factor 16
predictive conditional distributions 200
predictive density 16
predictive density evaluation 200
predictive inference 103
predictive intervals 38
predictive least squares 933
predictive likelihood 16
predictive pdf 907
price elasticities 1001

prices 985
pricing strategies 986
principal components analysis 528
prior distribution 10
prior information 6
prior odds ratio 15
prior predictive density 11
probability and duration forecasts 951
probability approach 739
probability density forecasts 176
probability density function 8
probability forecast evaluation 860
I-26 Subject Index
probability forecasting 22, 788
probability integral transform 22, 202
probability integral transform (PIT) 861
probability limits 201
probability of transition 899
probit model 890, 993
projection pursuit 446
promotional activities 986
propagation mechanism 951
QMLE 808
quadratic probability score 935
qualitative data 395, 753, 763
qualitative questions 734
qualitative responses 728
qualitative survey data 739
qualitative surveys 751
quantile predictions 810

questionnaires 986
QuickNet 476, 478, 497, 503
radial basis function 423, 472
random walk 623
rank condition 117
Rao–Blackwellization 27
rational expectations hypothesis 721
RATS 69
real-time data 962
real-time data setfor macroeconomists (RTDSM)
965
real-time forecasting 40, 624, 972
real-time information 883
reality check 130
realized covariances and correlations 849, 850
realized covariation 849, 850
realized volatility 783, 786, 795, 830
realized volatility errors 849
realized volatility forecasting 835
realized volatility modeling 834
recession 640, 963
recession indicator 911
recursive forecasting 433, 972
recursive formulation 19
recursive scheme 106
regime switching type models 851
regional forecasting 64
regression based tests 116
regression parameters 106
REH 727–729, 757

relative numerical efficiency 29
relaxed greedy algorithm 472, 478
relevant conditioning 7
repeated observation forecasting 971
residual adjustments 633
retrospective fluctuation test 624
return variability 818
return variance 818
return volatility 780
reversibility condition 34
revision 881
revision process 966
reweighting 40
ridge regression 13, 45
ridgelets 472, 498
risk 561
risk management 790
RiskMetrics 798, 840
rolling regressions 107, 798
rolling sample windows 798
root mean square error 55
root mean square forecast error 440
RR regression 312
S&P 500 index 492
sales 986
sample survey error 343
sampling frequency 836
SARIMA model 665
SARV 817
scalar component models 311

SCAN*PRO 1005
Schwarz information criterion 318, 685, 971
seasonal adjustment 662, 882, 967
seasonal ARIMA models 359
seasonal cointegration 677
seasonal component 355
seasonal differencing 666
seasonal dummies 670
seasonal heteroskedasticity 696
seasonal process 303
seasonal random walk 672
seasonal unit roots 305, 667
seasonality 662
seasonality in variance 696
seasonally integrated model 666
seemingly unrelated times series equation
(SUTSE) models 47, 370
segmentation 1002
self-exciting threshold autoregressive model(SE-
TAR) 418, 636
semi-martingale 832
semi-parametric models 200
sequential test bias 202
Subject Index I-27
serial correlation 567, 863
series functions 468
shrinkage 11, 170, 184, 185
shrinkage forecast 522
sign forecasting 788
similar cycle 370

simple combination forecast 155, 522
simulated annealing 423
simulated moments, Markov Chain Monte Carlo
(MCMC) 814
simulation based method 905, 985
simulation error 825
simulation-consistency 26
simulation-consistent approximation 40
simultaneous-equations model 112, 117, 975
skip-sampling 302
smooth transition autoregressive (STAR) model
416, 420, 692
smooth transition model 927
smooth transition regression model 418
smoothing 814
smoothing parameter 927
smoothness 470
source density 27
sources of forecast error 609–612
specification testing 200, 202
specifying Kronecker indices 314
specifying lag orders 314
“Spectre” 69
spot volatility 783
spurious regression 596
squared returns 784
stable process 293
state space 821, 895, 978
state space form 361
state space mixture models 14

state space observer system 43
state variable 912
stationarity 102
stationary linear models 56
statistical decision theory 84
statistical decisions 87
stochastic autoregressive volatility 817
stochastic cycle 344
stochastic differential equation 783
stochastic discount factor 792
stochastic random coefficient model 424
stochastic trend 335
stochastic volatility 9, 404, 786, 794, 814
stochastic volatility models 782
structural breaks 138, 154, 400, 607
structural change model 607
structural time series models 331
Student-t distribution 12
subjective uncertainty 749
suddenly changing autoregressive model 421
survey data 716, 986
Survey of Blue Chip Forecasters 736
Survey of Consumer Expectations 734
Survey of Household Income and Wealth 749
Survey of Professional Forecasters 186, 729,
733, 736, 749, 750, 759–761, 767, 965
switching regression model 419
systematic sampling 302
“take-off” point 992
Tankan 735

target density 33
target variable 881
taxonomy of forecast errors 607
temporal aggregation 295, 302, 995
term-structure-of-variance 801
test of conditional forecasting ability 442
testing cointegrating rank 313
testing for nonlinearity 636
testing linearity 425
tests for structural change 622
tests of rational expectations 716
TGARCH 803
Theil’s U 48
thick modeling 163, 425
threshold autoregressive (TAR) model 692
Threshold GARCH 803
threshold model 692
time consistency 728
time series models 993
time trend 567
time-variation in forecast combination weights
165
time-varying betas 792
time-varying coefficients 623
time-varying covariance 793, 840
time-varying parameters 168, 355, 523, 883
time-varying regression model 423
transition density 33
transition equation 822
transition function 419, 927

transition probability 421
trending regressors 562
trimming 162, 183, 185
trimming of forecasts 449
trough 881
true model 18
I-28 Subject Index
turning point 881
two-stage-least-squares 974
U.S. Health and Retirement Survey 736
U.S. Survey of Consumers 736
U.S. Survey of Economic Expectations 736
uncertainty 780
unconditional expected loss 574
unidentified parameter 623
uniform random variable 203
unimodular operator 307
unit root 12
unit root model 622
unit root pretesting 570
univariate model 563
univariate volatility forecasting 786
universal approximator 423
University of Wisconsin’s Survey of Economic
Expectations 749
unobserved components models 662
unobserved heterogeneity 1002
updating 630
utility function 83
Value-at-Risk 200, 790, 854

Value-at-Risk evaluation 859
VAR in differences (DVAR) 618
variable transformation 881
VARMA 58, 292
VA RM A (p, q) process 292
vech model 844
VECM 289, 294, 617
vector autoregression 8, 11, 289, 558, 612–614,
901, 993
vector autoregressive moving-average (VARMA)
models 289
volatility 780
volatility dynamics 789
“volatility feedback” effect 803
volatility forecast evaluation 855
volatility forecasting 416, 781, 796
volatility impulse response function 806
volatility modeling 781
volatility process 782
volatility proxy 857
volatility signature plot 858
Wald test 427
wavelets 469
weakly stationary 901
web-based surveys 985
weekly, daily or hourly observations 360
weighted average 23
weighted principal components 530
weighting scheme 882, 892
Wharton Econometric Forecasting Associates

69
Wiener 780
Wishart random matrix 50
Wold MA representation 293
Wolf’s sunspot numbers 446
X-11 method 702
X-12-ARIMA 702
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