Table Of Content

International Journal of Forecasting 8 (1992) 659-660 659 North-Holland Author Index Volume 8 (1992) (The issue number is given in parentheses) Ahlburg, D.A. and K.C. Land, Population fore- Dangerfield, B.J. and J.S. Morris, Top-down or casting: Guest Editors’ introduction (3) 289-299 bottom-up: Aggregate versus disaggregate (2) 233-241 Aksu, C. and S.I. Gunter, An empirical analy- extrapolations (4) 583-593 sis of the accuracy of SA, OLS, ERLS and Daouas, M., see M. Oral (1) 27 -43 (4) 595-611 NRLS combination forecasts Dattero, R., see E.M. White Alho, J.M., The magnitude of error due to De Gooijer, J.G. and K. Kumar, Some recent different vital processes in population fore- developments in non-linear time series mod- casts (3) 301-314 elling, testing, and forecasting (2) 135-156 (2) 251-267 Armstrong, J.S., Editorial policies for the pub- DeRoeck, R., see E. Mahmoud (4) 543-544 (3) 529-539 lication of controversial findings Diamond, I., see K. Spicer (4) 575-582 (4) 545-557 Armstrong, J.S., see F. Collopy Doll, J.M., see L.S.-Y. Wu Armstrong, J.S. and F. Collopy, Error mea- sures for generalizing about forecasting Edmonston, B. and J.S. Passel, Immigration (1) 69- 80 methods: Empirical comparisons and immigrant generations in population Assimakopoulos, V. and A. Konida, An object projections (3) 459-476 oriented approach to forecasting (2) 175-185 Fildes, R., The evaluation of extrapolative fore- Benson, P.G. and D. Onkal, The effects of casting methods (1) 81- 98 feedback and training on the performance (4) 595-611 Flores, B., see E.M. White (4) 559-573 of probability forecasters (3) 529-539 Bhrolchain, M.N., see K. Spicer (3) 339-365 Glied, S., see D.E. Bloom Bloom, D.E. and S. Glied, Projecting the num- (3) 339-365 Granger, C.W.J., Forecasting stock market ber of new AIDS cases in the United States (1) 3-13 prices: Lessons for forecasters Bos, E. and R.A. Bulatao, The demographic (1) 27- 43 impact of AIDS in sub-Saharan Africa. Gunter, S.I., see C. Aksu Short- and long-term projections (3) 367-384 Gunter, S.I., Nonnegativity restricted least (1) 45- 59 squares combinations Briscoe, G. and R. Wilson, Forecasting (2) 201-217 economic activity rates (4) 545-557 Brockwell, P.J. and R.J. Hyndman, On con- Hosking, J.R.M., see L.S.-Y. Wu tinuous-time threshold autoregression (2) 157-173 Hyndman, R.J., see P.J. Brockwell (2) 157-173 (4) 613-626 Brodie, R.J., see P.J. Danaher (2) 251-267 Brown, R., see E. Mahmoud Joutz, F. and R. Trost, Using stochastic simula- (3) 367-384 Bulatao, R.A., see E. Bos tion to test the effect of seasonal adjustment on forecast standard errors of motor Carter, L.R. and R.D. Lee, Modeling and fore- gasoline demand (2) 219-231 (3) 393-411 casting US sex differentials in mortality (3) 477-493 Chen, R., see S.P. Morgan (4) 583-593 Kettani, O., see M. Oral Coelho, C.H.M., and M. Tenenblat, Trading (2) 175-185 Konida, A., see V. Assimakopoulos days, seasonal unit root, and variance (1) 61- 67 Kontzalis, P., Identification of key attributes, change gap analysis and simulation techniques in Collopy, F. and J.S. Armstrong, Expert opin- forecasting market potential of ethical phar- ions about extrapolation and the mystery of (2) 243-249 (4) 575-582 maceutical products the overlooked discontinuities (2) 135-156 (1) 69- 80 Kumar, K., see J.G. De Gooijer Collopy, F., see J.S. Armstrong (4) 583-593 Cosset, J.-C., see M. Oral Lawrence, M. and M. O’Connor, Exploring (1) 15- 26 judgemental forecasting Danaher, P.J. and R.J. Brodie, Predictive ac- (3) 289-299 curacy of simple versus complex economet- Land, K.C., see D.A. Ahlburg (3) 315-327 Lee, R.D., Stochastic demographic forecasting ric market share models. Theoretical and empirical results (4) 613-626 Lee, R.D., see L.R. Carter (3) 393-411 660 Author Index Mahmoud, E., R. DeRoeck, R. Brown and G. Book Reviews Rice, Bridging the gap between theory and (2) 251-267 practice in forecasting Fields, P.J., Review of S.A. Delurgio and C.D. Manton, K.G., E. Stallard and B. Singer, Pro- Bhame, Forecasting Systems for Operations (4) 644-646 jecting the future size and health status of Management (3) 433-458 the US elderly population Fildes, R., Review of E.R. Berndt, The Practice Mason, A. and R. Racelis, A comparison of of Econometrics: Classical and Contem- four methods for projecting households (3) 509-527 porary (2) 269-270 McNown, R. and A. Rogers, Forecasting cause- Fildes, R., Review of A. Harvey, Forecasting (3) 413-432 specific mortality using time series methods Structural Time Series Models and the Kal- Morgan, S.P. and R. Chen, Predicting child- man Filter and M. West and J. Harrison, (4) 635-637 lessness for recent cohorts of American Bayesian Forecasting and Dynamic Models (3) 477-493 women Flavell, R., Review of W.T. Ziemba, W. Bailey (2) 233-241 Morris, J.S., see B.J. Dangerfield and T. Hamao, Japanese Financial Market (2) 270-271 Research (4) 559-573 Onkal, D., see P.G. Benson Goodwin, P., Review of T.L. Saaty and I.G. Oral, M., O. Kettani, J.-C. Cosset and M. Vargas, Prediction, Projection and Fore- Daouas, An estimation model for country casting (1) 118-119 (4) 583-593 risk rating Halal, W.E., Review of Union of International (1) 15- 26 O’Connor, M., see M. Lawrence Associations, Encyclopedia of World Prob- (4) 639-641 lems and Potential (3) 459-476 Passel, J.S., see B. Edmonston Henry, B., Review of F.A.G. den Butter and Pflaumer, P., Forecasting US population totals M.M.G. Fase, Seasonal Adjustment as a with the Box—Jenkins approach (3) 329-338 Practical Problem (2) 271-274 Kennedy, P., Review of A. Pankratz, Forecast- Racelis, R., see A. Mason (3) 509-527 ing with Dynamic Regression Models (4) 647-648 (2) 251-267 Rice, G., see E. Mahmoud Leitz, S., Review of W. Lutz, Future Demo- (3) 413-432 Rogers, A., see R. McNown graphic Trends in Europe and North (3) 541-542 America: What can we Assume Today Scott, S., An extended review of the Mahmoud, E., Review of S.F. Witt and C.A. X11ARIMA seasonal adjustment package (4) 627-633 Witt, Modeling and Forecasting Demand in (4) 643-644 Shoesmith, G.L., Non-cointegration and Tourism (2) 187-199 causality: Implications for VAR modeling Miles, I, Review of B. Burroughs, A. Mayne (3) 495-508 Sincich, T., see S.K. Smith and P. Newbury, Into the 21st Century: A (3) 433-458 Singer, B., see K.G. Manton Handbook for a Sustainable Future and Smith, S.K. and T. Sincich, Evaluating the W.W. Wager, The Next Three Futures: forecast accuracy and bias of alternative Paradigms of Things to Come (4) 637-639 population projections for states (3) 495-508 Monaco, R.M., Review of M.G. Morgan and Spicer, K., I. Diamond and M.N. Bhrolchain, M. Henrion, Uncertainty: A Guide to Deal- Into the twenty-first century with British ing with Uncertainty in Quantitative Risk (3) 529-539 households and Policy Analysis (1) 119-120 (3) 433-458 Stallard, E., see K.G. Manton Porter, A.L., Review of K.E.F. Watt, Taming (4) 641-643 the Future (1) 61- 67 Tenenblat, M., see C.H.M. Coelho Priesmeyer, H.R., Review of F. Morrison, The (2) 219-231 Trost, R., see F. Joutz Art of Modeling Dynamic Systems: Fore- Tuljapurkar, S., Stochastic population forecasts casting for Chaos, Randomness and De- and their uses (3) 385-391 terminism (4) 646-646 Stallings, D., Review of C. Dunis and M. White, E.M., R. Dattero and B. Flores, Com- Feeny, Exchange Rate Forecasting (1) 116-117 bining vector forecasts to predict Westlund, A., Review of L.M. Valentine and thoroughbred horse race outcomes (4) 595-611 D.F. Ellis, Business cycles and forecasting (1) 114-116 (2) 201-217 Wilson, R., see G. Briscoe Wilson, I., Review of F.W. Elwell, The Evolu- (2) 274-275 Wu, L.S.-Y., J.R.M. Hosking and J.M. Doll, tion of the Future Business planning under uncertainty. Will Yokum, T., Review of J.C. Compton and S.B. (4) 545-557 (1) 113-114 we attain our goal? Compton, Successful Business Forecasting International Journal of Forecasting 8 (1992) 661-662 North-Holland Subject Index Volume 8 (1992) (The issue number is given in parentheses) Accounting earnings (1) 27 Family forecasts (2) 233 (1) 27, 45 (3) 301, 315, 477 Accuracy of forecasts Fertility Age-sex-specific mortality (3) 393 Forecast accuracy (1) 69, (3) 329, 393 Aggregate forecasts (2) 233 Forecast combination (4) 595 (3) 315, 367 (2) 219 Aging Forecast confidence intervals AIDS (3) 339 Forecast practice (2) 251 ARCH (2) 135 Forecastability (1) 3 (3) 413, (4) 627 (4) 575 ARIMA models Forecasting guidelines (2) 243 Forecasting market share Bilinear (2) 135 Forecasting process (2) 251 (3) 477 (3) 459 Birth probabilities Foreign-born population (4) 559 (2) 243 Calibration Gap analysis (2) 187 (3) 459 Causality Generations (3) 477 (1) 27, 45 Childlessness Gross national product (3) 433 Chronic disease Cointegration (2) 187, (3) 393 Headship rates (3) 529 (3) 477 (3) 367 Cohort models HIV/AIDS modelling see also AIDS (3) 433 (3) 509,52 9 study Household projection (1) 27, 45 Combining forecasts Common factor (1)6 1 Identification 2) 13° Comparative methods — time series (1) 81 Implementing forecasting 2) 25 Competing risks (3) 433 Inequality restricted least squares l Conjoint analysis (2) 243 Invertibility 2 135 (2) 157 Continuous-time autoregression (2) 243 (4) 559 Correspondence analysis Judgmental forecasting (4) 583 Country risk (2) 175 Covariance decomposition (4) 559 Knowledge base CUSUMS (2) 135 Labour market (3) 529 De facto status Labour supply (3) 385 Decision analysis Lagrange-multiplier test (3) 509 Demographic methods Life-table functions Demographic projections and forecasts (3) 495 Loss functions—evaluation (3) 315 Dependency Difference equations (3) 329 M-competition (2) 233 (4) 575 (4) 613 Discontinuities Market share Mathematical programming (4) 583 Econometric model (4) 613 Maximum likelihood estimation (2) 157 (2) 201 (4) 613 Economic activity rates Mean squared error Efficient markets “a 3 Migration (3) 301 (1) 27 (4) 583 Equality restricted least squares Modeling (2) 187 (1) 27 Error correction Money supply Estimation (1) 27, (2) 157, (4) 583 Mortality (3) 301, 315, 413 Evaluation — methodology (1) 81 Multi-step-ahead forecasting (2) 135 (1) 81 Evaluation — time series methods Event forecasting (4) 595 Naive model (4) 613 Ex ante (1) 81 Non-linear demographic model (3) 393 Exponential AR (2) 135 Non-linear models (13), ( 2) 157 Extrapolation (4) 627 Non-sample information (1) 45 662 Subject Index Object oriented design (2) 175 State—space representation (2) 157 Order selection (2) 135 Statistical modeling (4) 545 Ordinary least squares (1) 27 Stochastic dynamic programming (3) 385 Outcome feedback (4) 559 Stochastic population forecasts (3) 385 Outliers — effect of (1) 81 Stochastic process (3) 433 Stochastic simulation (2) 219 Participation (2) 201 Stock returns i) 3 Performance feedback (4) 559 Sub-Sahara Africa (3) 367 Period models (3) 477 Subjective probability (4) 559 Pharmaceutical products (2) 243 Survival with covariates (3) 433 Physiological dynamics (3) 433 Planning (4) 545 Theil’s U (1) 69 Population forecasting (3) 315, 329, 367, 495 Thoroughbred racing (4) 595 Probability forecasting (4) 559 Threshold autoregression (2) 157 Projection (3) 315, 339, 509 Threshold model (2) 135 Propagation of Error (3) 301 Time series analysis (2) (201), (3) 329 Time series features (4) 575 Racial and ethnic composition (3) 459 Top-down forecasts (2) 233 Regional forecasting (2) 187 Tracking (4) 545 Regression (4) 583 Trade-off utility scores (2) 243 Relative absolute error (1) 69 Trading days (1) 61 Restricted least squares (1) 45 Transfer function (1) 61 Robust estimation (1) 81 Transition probabilities (3) 529 Robustness (1) 45 Treasury bill rates (1) 27 Resolution (4) 559 Two sex problem (3) 509 Scoring rules (4) 559 Uncertainty (3) 385 Seasonal adjustment techniques (2) 219 United States (3) 477 Seasonal time series (1) 61 Seasonal unit root (1) 61 Variance change (1) 61 Selection criteria (4) 575 Vector autoregression (2) 187 Simple average CE}: ar Simulation (3) 529 Wineglass chart (4) 545 Simulation model (2) 243 Social Security (3) 315 X-11 (4) 627