Business cycles, indicators, and forecasting [[electronic resource] /] / edited by James H. Stock and Mark W. Watson |
Pubbl/distr/stampa | Chicago, : University of Chicago Press, c1993 |
Descrizione fisica | 1 online resource (350 p.) |
Disciplina | 338.5/42 |
Altri autori (Persone) |
StockJames H
WatsonMark W |
Collana | Studies in business cycles |
Soggetto topico |
Economic forecasting
Economic indicators Business cycles Economic forecasting - United States Economic indicators - United States Business cycles - United States |
Soggetto genere / forma | Electronic books. |
ISBN |
1-281-43112-5
9786611431129 0-226-77474-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Front matter -- Relation of the Directors to the Work and Publications of the National Bureau of Economic Research -- Contents -- Acknowledgments -- Introduction -- 1. Twenty-two Years of the NBERASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance -- 2. A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience -- 3. Estimating Event Probabilities from Macroeconometric Models Using Stochastic Simulation -- 4. A Nine-Variable Probabilistic Macroeconomic Forecasting Model -- 5. Why Does the Paper-Bill Spread Predict Real Economic Activity? -- 6. Further Evidence on Business- Cycle Duration Dependence -- 7. A Dynamic Index Model for Large Cross Sections -- 8. Modeling Nonlinearity over the Business Cycle -- Contributors -- Author Index -- Subject Index |
Record Nr. | UNINA-9910451096903321 |
Chicago, : University of Chicago Press, c1993 | ||
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Lo trovi qui: Univ. Federico II | ||
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Business cycles, indicators, and forecasting [[electronic resource] /] / edited by James H. Stock and Mark W. Watson |
Pubbl/distr/stampa | Chicago, : University of Chicago Press, c1993 |
Descrizione fisica | 1 online resource (350 p.) |
Disciplina | 338.5/42 |
Altri autori (Persone) |
StockJames H
WatsonMark W |
Collana | Studies in business cycles |
Soggetto topico |
Economic forecasting
Economic indicators Business cycles Economic forecasting - United States Economic indicators - United States Business cycles - United States |
Soggetto non controllato | recession, economics, economy, finances, financial, money, economists, forecasting, congress, indicators, indications, business, businesses, united states of america, american society, usa, conditions, government, governing, nber-asa quarterly economic outlook surveys, recessions, prediction, looking ahead, event probabilities, stochastic simulation, macroeconometric models, dependence, cross sections, non-linearity |
ISBN |
1-281-43112-5
9786611431129 0-226-77474-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Front matter -- Relation of the Directors to the Work and Publications of the National Bureau of Economic Research -- Contents -- Acknowledgments -- Introduction -- 1. Twenty-two Years of the NBERASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance -- 2. A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience -- 3. Estimating Event Probabilities from Macroeconometric Models Using Stochastic Simulation -- 4. A Nine-Variable Probabilistic Macroeconomic Forecasting Model -- 5. Why Does the Paper-Bill Spread Predict Real Economic Activity? -- 6. Further Evidence on Business- Cycle Duration Dependence -- 7. A Dynamic Index Model for Large Cross Sections -- 8. Modeling Nonlinearity over the Business Cycle -- Contributors -- Author Index -- Subject Index |
Record Nr. | UNINA-9910784961603321 |
Chicago, : University of Chicago Press, c1993 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Business cycles, indicators, and forecasting / / edited by James H. Stock and Mark W. Watson |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Chicago, : University of Chicago Press, c1993 |
Descrizione fisica | 1 online resource (350 p.) |
Disciplina | 338.5/42 |
Altri autori (Persone) |
StockJames H
WatsonMark W |
Collana | Studies in business cycles |
Soggetto topico |
Economic forecasting
Economic indicators Business cycles Economic forecasting - United States Economic indicators - United States Business cycles - United States |
ISBN |
1-281-43112-5
9786611431129 0-226-77474-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Front matter -- Relation of the Directors to the Work and Publications of the National Bureau of Economic Research -- Contents -- Acknowledgments -- Introduction -- 1. Twenty-two Years of the NBERASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance -- 2. A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience -- 3. Estimating Event Probabilities from Macroeconometric Models Using Stochastic Simulation -- 4. A Nine-Variable Probabilistic Macroeconomic Forecasting Model -- 5. Why Does the Paper-Bill Spread Predict Real Economic Activity? -- 6. Further Evidence on Business- Cycle Duration Dependence -- 7. A Dynamic Index Model for Large Cross Sections -- 8. Modeling Nonlinearity over the Business Cycle -- Contributors -- Author Index -- Subject Index |
Record Nr. | UNINA-9910828315103321 |
Chicago, : University of Chicago Press, c1993 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Causality, integration and cointegration, and long memory : collected papers of Clive W.J. Granger / / edited by Eric Ghysels, Norman R. Swanson, Mark W. Watson |
Autore | Granger C. W. J (Clive William John), <1934-2009.> |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Cambridge ; ; New York, : Cambridge University Press, 2001 |
Descrizione fisica | 1 online resource (xviii, 378 pages) : digital, PDF file(s) |
Disciplina | 330/.01/5195 |
Altri autori (Persone) |
GhyselsEric <1956->
SwansonNorman R <1964-> (Norman Rasmus) WatsonMark W |
Collana |
Econometric Society monographs
Essays in econometrics |
Soggetto topico |
Econometrics
Economics |
ISBN |
1-139-88285-6
1-280-16035-7 1-139-14681-5 0-511-11903-8 0-511-06725-9 0-511-06094-7 0-511-29763-7 0-511-75397-7 0-511-06938-3 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Cover -- Half-title -- Series-title -- Title -- Copyright -- Dedication -- Contents -- Acknowledgments -- ACADEMIC PRESS -- AMERICAN STATISTICAL ASSOCIATION -- BLACKWELL PUBLISHERS -- BUREAU OF THE CENSUS -- CAMBRIDGE UNIVERSITY PRESS -- CHARTERED INSTITUTION OF WATER AND ENVIRONMENTAL MANAGEMENT -- THE ECONOMETRICS SOCIETY -- ELSEVIER -- FEDERAL RESERVE BANK OF MINNEAPOLIS -- HELBING AND LICHTENHAHN VERLAG -- JOHN WILEY & -- SONS, LTD. -- MACMILLAN PUBLISHERS, LTD. -- MIT PRESS -- TAYLOR & -- FRANCIS, LTD. -- Contributors -- Introduction -- Volume I -- SPECTRAL METHODS -- SEASONALITY -- NONLINEARITY -- METHODOLOGY -- FORECASTING -- Volume II -- CAUSALITY -- INTEGRATION AND COINTEGRATION -- LONG MEMORY -- REFERENCES -- PART ONE CAUSALITY -- CHAPTER 1 Investigating Causal Relations by Econometric Models and Cross-Spectral Methods -- I. SPECTRAL METHODS -- II. FEEDBACK MODELS -- III. CAUSALITY -- IV. TWO-VARIABLE MODELS -- V. THREE-VARIABLE MODELS -- VI. CONCLUSION -- REFERENCES -- CHAPTER 2 Testing for Causality -- 1. THE PROBLEM AND A DEFINITION -- 2. A VARIETY OF VIEWPOINTS ON CAUSALITY -- 3. AN OPERATIONAL DEFINITION -- 4. SOME DIFFICULTIES -- 5. TEST PROCEDURES -- 6. DISCUSSION AND CONCLUSIONS -- REFERENCES -- CHAPTER 3 Some Recent Developments in A Concept of Causality -- 1. INTRODUCTION -- 2. CO-INTEGRATION AND CAUSATION -- 3. INSTANTANEOUS CAUSALITY -- 4. CAUSALITY AND CONTROL VARIABLES -- REFERENCES -- CHAPTER 4 Advertising and Aggregate Consumption: An Analysis of Causality -- 1. INTRODUCTION -- 2. PREVIOUS STUDIES -- 3. TESTING FOR CAUSALITY -- 4. THE DATA -- 5. EMPIRICAL RESULTS -- 6. CONCLUSIONS -- APPENDIX -- REFERENCES -- PART TWO INTEGRATION AND COINTEGRATION -- CHAPTER 5 Spurious Regressions in Econometrics -- 1. INTRODUCTION -- 2. SOME RESULTS IN TIME SERIES ANALYSIS -- 3. HOW NONSENSE REGRESSIONS CAN ARISE.
4. SOME SIMULATION RESULTS -- 5. DISCUSSION AND CONCLUSION -- REFERENCES -- CHAPTER 6 Some Properties of Time Series Data and Their Use in Econometric Model Specification -- 1. INTRODUCTION -- 2. INTEGRATED SERIES AND FILTERS -- 3. THE ALGEBRA OF INTEGRATED SERIES AND IT'S IMPLICATIONS -- 4. CO-INTEGRATED SERIES -- 5. CONCLUSION -- REFERENCES -- CHAPTER 7 Time Series Analysis of Error-Correction Models -- 1. INTRODUCTION -- 2. THE ONE-WAY CAUSAL MODEL -- 3. MULTI-COMPONENT CO-INTEGRATED SERIES -- 4. THE BIVARIATE FEEDBACK CASE -- 5. AGGREGATION -- 6. TESTING FOR CO-INTEGRATION -- 7. APPLICATION 1: EMPLOYEES' INCOME AND NATIONAL INCOME -- 8. APPLICATION 2. M3 AND GNP -- 9. APPLICATION 3. PRICES, WAGES AND PRODUCTIVITY IN THE TRANSPORTATION INDUSTRY -- 10. CONCLUSIONS -- APPENDIX 1. FRACTIONAL INTEGRATED SERIES -- APPENDIX 2. ERROR CORRECTION AND SEASONALITY -- REFERENCES -- CHAPTER 8 Co-Integration and Error Correction: Representation, Estimation, and Testing -- 1. INTRODUCTION -- 2. INTEGRATION, CO-INTEGRATION, AND ERROR CORRECTION -- 3. PROPERTIES OF CO-INTEGRATED VARIABLES AND THEIR REPRESENTATIONS -- 4. ESTIMATING CO-INTEGRATED SYSTEMS -- 5. TESTING FOR CO-INTEGRATION -- 6. EXAMPLES -- 7. CONCLUSION -- REFERENCES -- CHAPTER 9 Developments in the Study of Cointegrated Economic Variables -- 1. INTRODUCTION -- 2. COINTEGRATION -- 3. TESTING FOR COINTEGRATION -- 4. GENERALISATION: MANY VARIABLES AND GENERAL COINTEGRATION -- 5. FURTHER GENERALIZATIONS -- 6. CONCLUSION -- REFERENCES -- CHAPTER 10 Seasonal Integration and Cointegration -- 1. INTRODUCTION -- 2. SEASONAL TIME-SERIES PROCESSES -- 3. TESTING FOR SEASONAL UNIT ROOTS -- 4. ERROR-CORRECTION REPRESENTATION -- 5. TESTING FOR COINTEGRATION: AN APPLICATION -- 6. CONCLUSION -- REFERENCES -- CHAPTER 11 A Cointegration Analysis of Treasury Bill Yields -- 1. INTRODUCTION -- 2. THEORETICAL FRAMEWORK. A. Theory of the Term Structure -- B. Integration and Cointegration within the Term Structure -- C. Modeling Cointegrated Data -- 3. THE DATA -- 4. THE EMPIRICAL EVIDENCE -- A. Time Series Properties of Individual Yields -- B. Cointegration Analysis -- C. Error Correction Models -- D. Forecasts -- 5. CONCLUSION -- REFERENCES -- CHAPTER 12 Estimation of Common Long-Memory Components in Cointegrated Systems -- 1. FACTOR MODEL -- 2. ESTIMATION AND TESTING -- 3. APPLICATIONS -- 3.1 Consumption and GNP, Dividends and Stock Prices -- 3.2 Interest Rates in Canada and the United States -- 4. CONCLUSION -- ACKNOWLEDGMENTS -- APPENDIX: PROOFS OF THE MAIN RESULTS -- REFERENCES -- CHAPTER 13 Separation in Cointegrated Systems and Persistent-Transitory Decompositions -- 1. INTRODUCTION -- 2. DEFINITION OF THE CONCEPTS -- 2.1 Notions of Separation in Cointegrated Systems -- 2.2 P-T Decomposition of a Vector Time Series -- 3. PERSISTENT-TRANSITORY DECOMPOSITION IN SEPARATED COINTEGRATING SYSTEMS -- 3.1 Erroneously Treating Non- and Partially-separated Systems as Completely Separated -- 3.2 Partial Separation and P-T Decomposition of the Full System -- 4. EXTENSIONS TO NON-LINEAR ERROR CORRECTION MODELS -- 5. CONCLUSION -- REFERENCES -- CHAPTER 14 Nonlinear Transformations of Integrated Time Series -- 1. INTRODUCTION -- 2. UNIT ROOT TESTS ON TRANSFORMED SERIES -- 3. COINTEGRATED VARIABLES -- 4. CONCLUSIONS -- ACKNOWLEDGEMENTS -- REFERENCES -- CHAPTER 15 Long Memory Series with Attractors -- 1. INTRODUCTION -- 2. SHORT AND LONG MEMORY -- 3. BIVARIATE ATTRACTOR -- 4. ESTIMATION OF THE ATTRACTOR -- 5. TESTING FOR AN ATTRACTOR -- 6. AN APPLICATION -- 7. CONCLUSION -- REFERENCES -- CHAPTER 16 Further Developments in the Study of Cointegrated Variables -- 1. INTRODUCTION -- 2. SIMPLE GENERALIZATIONS -- 3. NONLINEAR GENERALIZATIONS -- 4. CURRENT INTERPRETATIONS. 5. EXAMPLE OF NONLINEAR ERROR-CORRECTION -- 6. EARLY WARNINGS, FRAGILITY AND THE FUTURE -- REFERENCES -- PART THREE LONG MEMORY -- CHAPTER 17 An Introduction to Long-Memory Time Series Models and Fractional Differencing -- 1. ON DIFFERENCING TIME SERIES -- 2. TIME SERIES PROPERTIES -- 4. FORECASTING AND ESTIMATION OF d -- 5. PRACTICAL EXPERIENCE -- APPENDIX: THE d = 0 CASE -- REFERENCES -- CHAPTER 18 Long Memory Relationships and the Aggregation of Dynamic Models -- 1. INTRODUCTION -- 2. AGGREGATION OF INDEPENDENT SERIES -- 3. AGGREGATION OF DEPENDENT SERIES -- 4. SOME OTHER MODELS -- 5. CONCLUSION -- REFERENCES -- CHAPTER 19 A Long Memory Property of Stock Market Returns and a New Model -- 1. INTRODUCTION -- 2. THE DATA -- 3. AUTOCORRELATION ANALYSIS OF THE RETURN SERIES -- 4. SENSITIVITY OF AUTOCORRELATION STRUCTURE -- 5. MONTE-CARLO STUDY OF VARIOUS FINANCIAL TIME SERIES MODELS -- 6. A NEW MODEL - ASYMMETRIC POWER ARCH -- 6. CONCLUSION -- APPENDIX A -- APPENDIX B. CONDITIONS FOR THE EXISTENCE OF… -- REFERENCES -- Index. |
Record Nr. | UNINA-9910828467003321 |
Granger C. W. J (Clive William John), <1934-2009.>
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Cambridge ; ; New York, : Cambridge University Press, 2001 | ||
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Lo trovi qui: Univ. Federico II | ||
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Spectral analysis, seasonality, nonlinearity, methodology and forecasting : collected papers of Clive W.J. Granger / / edited by Eric Ghysels, Norman R. Swanson, Mark W. Watson |
Autore | Granger C. W. J (Clive William John), <1934-2009.> |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Cambridge ; ; New York, : Cambridge University Press, 2001 |
Descrizione fisica | 1 online resource (xix, 523 pages) : digital, PDF file(s) |
Disciplina | 330/.01/5195 |
Altri autori (Persone) |
GhyselsEric <1956->
SwansonNorman R <1964-> (Norman Rasmus) WatsonMark W |
Collana |
Econometric Society monographs
Essays in econometrics |
Soggetto topico |
Econometrics
Economics, Mathematical |
ISBN |
1-139-88279-1
0-511-06676-7 1-280-16020-9 0-511-11845-7 1-139-14636-X 0-511-06045-9 0-511-29762-9 0-511-75396-9 0-511-06889-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Cover -- Half-title -- Series-title -- Title -- Copyright -- Dedication -- Contents -- Acknowledgments -- ACADEMIC PRESS -- AMERICAN STATISTICAL ASSOCIATION -- BLACKWELL PUBLISHERS -- BUREAU OF THE CENSUS -- CAMBRIDGE UNIVERSITY PRESS -- CHARTERED INSTITUTION OF WATER AND ENVIRONMENTAL MANAGEMENT -- THE ECONOMETRICS SOCIETY -- ELSEVIER -- FEDERAL RESERVE BANK OF MINNEAPOLIS -- HELBING AND LICHTENHAHN VERLAG -- JOHN WILEY & -- SONS, LTD. -- MACMILLAN PUBLISHERS, LTD. -- MIT PRESS -- TAYLOR & -- FRANCIS, LTD. -- Contributors -- Introduction -- Volume I -- SPECTRAL METHODS -- SEASONALITY -- NONLINEARITY -- METHODOLOGY -- FORECASTING -- Volume II -- CAUSALITY -- INTEGRATION AND COINTEGRATION -- LONG MEMORY -- REFERENCES -- CHAPTER 1 The ET Interview: Professor Clive Granger -- BOOKS -- PAPERS -- Forthcoming -- Submitted -- PRICE RESEARCH -- SPECULATIVE MARKETS AND THEORY OF FINANCE -- STATISTICAL THEORY AND APPLIED STATISTICS -- PART ONE SPECTRAL ANALYSIS -- CHAPTER 2 Spectral Analysis of New York Stock Market Prices -- Summary -- 1. THE RANDOM WALK HYPOTHESIS -- 2. SPECTRAL METHODS -- 3. RESULTS OF THE ANALYSIS -- APPENDIX A -- Some Technical Considerations -- APPENDIX B -- Description of Series Analyzed -- Power Spectra -- Cross Spectra -- CHAPTER 3 The Typical Spectral Shape of an Economic Variable -- 1. INTRODUCTION -- 2. EXAMPLES OF ESTIMATED SPECTRA -- 3. THE PROBLEM OF TREND -- 4. INTERPRETATION: BUSINESS CYCLES -- 5. DESCRIPTION: MODEL FITTING -- 6. IMPLICATIONS FOR MODEL BUILDING -- 7. IMPLICATIONS FOR CONTROL -- REFERENCES -- PART TWO SEASONALITY -- CHAPTER 4 Seasonality: Causation, Interpretation, and Implications -- 1. CAUSES OF SEASONALITY -- 1.1 Calendar -- 1.2 Timing Decisions -- 1.3 Weather -- 1.4 Expectation -- 2. DEFINITION -- 2.1 Definition 1 -- 2.2 Definition 2 -- 2.3 Definition 3 -- 3. SEASONAL MODELS -- 3.1 Model 1.
3.2 Model 2 -- 3.3 Model 3 -- 3.4 Model 4 -- 3.5 Model 5 -- 3.6 Model 6 -- 4. DECOMPOSITION -- 5. WHY ADJUST? -- 6. OVERVIEW OF ADJUSTMENT METHODS -- 7. CRITERIA FOR EVALUATION -- 7.1 Property 1 -- 7.2 Property 2 -- 7.3 Property 3 -- 7.4 Property 4 -- 7.5 Property 5 -- 7.6 Property 6 -- 8. EFFECTS OF ADJUSTMENT IN PRACTICE -- 9. RELATING PAIRS OF ADJUSTED SERIES -- 10. CONCLUSIONS -- REFERENCES -- CHAPTER 5 Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process? -- 1. ON POTENTIAL SOURCES OF NONLINEARITY IN THE X-11 PROGRAM -- 1.1 The Decompositions -- 1.2 Multiplicative Versus Additive -- 1.3 Outlier Detections -- 1.4 Moving Average Filter Selection -- 1.5 Aggregation -- 2. A SIMULATION STUDY -- 2.1 The Data-Generating Processes -- 2.2 Properties of Linear Approximations -- 2.3 Linear Regression and Filtering -- 2.4 Technical Details -- 3. SIMULATION AND EMPIRICAL RESULTS -- 3.1 Seasonal Filtering and Linear Regression -- 3.2 Simulation Evidence on Properties of Linear Approximation -- 3.3 An Empirical Investigation -- 4. CONCLUSION -- ACKNOWLEDGMENTS -- REFERENCES -- PART THREE NONLINEARITY -- CHAPTER 6 Non-Linear Time Series Modeling -- 1. NON-LINEAR MODELS -- 2. INSTANTANEOUS DATA TRANSFORMATIONS -- 3. INTRODUCTION TO BILINEAR MODELS -- 4. PARTICULAR CASE 1: A DIAGONAL MODEL -- 5. PARTICULAR CASE 2: WHITE NOISE MODELS -- REFERENCES -- CHAPTER 7 Using the Correlation Exponent to Decide Whether an Economic Series is Chaotic -- Summary -- 1. INTRODUCTION -- 2. CORRELATION EXPONENT TABLES -- 3. THE BDS TEST -- 4. CONCLUSIONS -- ACKNOWLEDGEMENT -- REFERENCES -- CHAPTER 8 Testing for Neglected Nonlinearity in Time Series Models -- 1. INTRODUCTION -- 2. THE NEURAL NETWORK TEST -- 3. ALTERNATIVE TESTS -- 3.1 The Keenan, Tsay, and Ramsey RESET Tests -- 3.2 The White Dynamic Information Matrix Test -- 3.3 The McLeod and Li Test. 3.4 The BDS Test -- 3.5 The Bispectrum Test -- 4. THE SIMULATION DESIGN -- 4.1 Block1 -- 4.2 Block2 -- 4.3 Bivariate Models -- 5. RESULTS OF THE SIMULATION -- 6. TESTS ON ACTUAL ECONOMIC TIME SERIES -- 7. CONCLUSIONS -- REFERENCES -- CHAPTER 9 Modeling Nonlinear Relationships Between Extended-Memory Variables -- 1. INTRODUCTION -- 2. BALANCE OF AN EQUATION WITH SIMPLE NONLINEARITY -- 3. ALTERNATIVE DEFINITIONS OF EXTENDED MEMORY -- 4. TESTING FOR LINEARITY -- 5. NONLINEAR MODELING -- 6. CONCLUSIONS -- REFERENCES -- CHAPTER 10 Semiparametric Estimates of the Relation Between Weather and Electricity Sales -- 1. INTRODUCTION -- 2. THE NONPARAMETRIC REGRESSION MODEL -- 3. THE DATA AND SOME MODIFICATIONS -- 4. RESULTS -- 5. CONCLUSIONS -- REFERENCES -- PART FOUR METHODOLOGY -- CHAPTER 11 Time Series Modeling and Interpretation -- Summary -- 1. INTRODUCTION -- 2. THE SUM OF TWO INDEPENDENT SERIES -- 3. SERIES AGGREGATION AND OBSERVATIONAL ERROR MODELS -- 4. TIME AGGREGATION, NON-INTEGER LAGS AND FEEDBACK MODELS -- 5. REALIZABILITY OF SIMPLE MODELS -- 6. SIMULATION OF OBSERVATION ERROR MODELS -- REFERENCES -- CHAPTER 12 On the Invertibility of Time Series Models -- 1. A DEFINITION OF INVERTIBILITY -- 2. LINEAR MODELS -- 3. A CLASS OF NON-INVERTIBLE MODELS -- 4. BILINEAR MODELS -- 5. CONCLUSIONS -- REFERENCES -- CHAPTER 13 Near Normality and Some Econometric Models -- REFERENCES -- CHAPTER 14 The Time Series Approach to Econometric Model Building -- 1. TWO PHILOSOPHIES -- 2. NONSENSE REGRESSIONS -- 3. PREWHITENING -- 4. BUILDING BIVARIATE FEEDBACK MODELS -- 5. CONCLUSIONS -- CHAPTER 15 Comments on the Evaluation of Policy Models -- Abstract -- 1. INTRODUCTION -- 2. THE CONTROL MECHANISM -- 2.1 Test 1 -- 2.2 Test 2 -- 2.3 Test 3 -- 2.4 Test 4 -- 2.5 Test 5 -- 2.6 Test 6 -- 2.7 Discussion -- 3. AN APPLICATION TO A MODEL OF THE UNEMPLOYMENT RATE. 4. AN APPLICATION TO TWO MODELS OF THE DEMAND FOR BORROWED RESERVES -- 5. AN APPLICATION TO A MODEL FOR THE DEMAND FOR NARROW MONEY IN THE UNITED KINGDOM -- 6. CONCLUSION -- APPENDIX. DESCRIPTION OF THE DATA -- REFERENCES -- CHAPTER 16 Implications of Aggregation with Common Factors -- 1. INTRODUCTION -- 2. COMMON FACTORS, INDIVIDUAL FACTORS, AND MODEL SIMPLIFICATION -- 3. AN EXAMPLE: THE ARBITRAGE PRICING THEORY MODEL -- 4. EXPECTATIONS -- 5. SOME PRACTICAL CONSIDERATIONS -- 6. SUMMING UP -- APPENDIX: NONLINEAR MODELS -- REFERENCES -- PART FIVE FORECASTING -- CHAPTER 17 Estimating the Probability of Flooding on a Tidal River -- Abstract -- MATHEMATICAL THEORY -- PROBABILITY OF FLOODING AT GAINSBOROUGH -- Introduction -- Correlation Between Tides and Flow Over the Year -- The Distribution of Tide Heights -- Distribution of Flows -- Flood-Producing Flow/Tide Combinations -- The Probabilities of High Flows Occurring -- Final Results and Conclusion -- ACKNOWLEDGEMENTS -- APPENDIX -- Statistical Concepts Used in the Paper -- CHAPTER 18 Prediction with a Generalized Cost of Error Function -- INTRODUCTION -- QUADRATIC ERROR COST AND THE GAUSSIAN PROCESS -- LINEAR COST FUNCTION -- GENERAL SYMMETRIC COST FUNCTIONS -- NON-SYMMETRIC COST FUNCTIONS -- SOME PRACTICAL CONSEQUENCES OF THE RESULTS -- SUMMARY AND CONCLUSIONS -- APPENDIX -- Proofs of two Theorems -- REFERENCES -- CHAPTER 19 Some Comments on the Evaluation of Economic Forecasts -- 1. INTRODUCTION -- 2. UNIVARIATE TIME SERIES PREDICTION -- 3. COST FUNCTIONS -- 4. RANKING FORECASTS ON A LEAST SQUARES BASIS -- 5. FORECAST EFFICIENCY -- 6. HOW GOOD IS A PARTICULAR SET OF FORECASTS? -- 7. DIAGNOSTIC CHECKS ON FORECAST PERFORMANCE -- 8. CONCLUSIONS -- REFERENCES -- CHAPTER 20 The Combination of Forecasts -- INTRODUCTION -- CHOICE OF METHOD FOR DETERMINING WEIGHTS -- DESIRABLE PROPERTIES OF METHODS. PERFORMANCE OF DIFFERENT METHODS -- MINOR MODIFICATIONS TO METHODS -- COMBINING FORECASTS FROM THE OUTSET -- COMMENTS -- CONCLUSIONS -- APPENDIX -- A1 Combining an Arithmetic and a Logarithmic Forecast -- A2 The Relationship Between the Combined Forecast Variance and the Variances of the Original Forecast Errors -- A3 The Distribution of... -- A4 Results of Combining Forecasts of the Airline Passenger Data -- Brown -- Box-Jenkins -- Harrison -- Constant -- Changing -- REFERENCES -- CHAPTER 21 Invited Review Combining Forecasts - Twenty Years Later -- Abstract -- THE BEGINNINGS -- SIMPLE EXTENSIONS -- FURTHER EXTENSIONS -- CONCLUSION -- REFERENCES -- CHAPTER 22 The Combination of Forecasts Using Changing Weights -- Abstract -- 1. INTRODUCTION -- 2. SWITCHING REGRESSION MODELS AND THEIR APPLICATION TO THE COMBINATION OF FORECASTS -- 3. COMBINING FORECASTS USING SWITCHING REGRESSION MODELS -- 3.1 Switching Regression Models in Which the Regime is Indicated by the Lagged Forecast Error -- 3.2 Switching Regression Models in Which the Regime is Indicated by an Economically Relevant Variable -- 4. SMOOTH TRANSITION REGRESSION MODELS -- 5. A FURTHER EMPIRICAL EXAMPLE -- 6. A COMPARISON OF THE IN-SAMPLE AND OUT-OF-SAMPLE PERFORMANCE OF THE ALTERNATIVE COMBINING METHODS -- 7. CONCLUSION -- APPENDIX -- REFERENCES -- CHAPTER 23 Forecasting Transformed Series -- Summary -- 1. INTRODUCTION -- 2. AUTOCORRELATION PROPERTIES OF TRANSFORMED SERIES: THE STATIONARY CASE -- 3. AUTOCORRELATION PROPERTIES OF TRANSFORMED SERIES: INTEGRATED PROCESSES -- 4. FORECASTING TRANSFORMED VARIABLES -- 5. CONCLUSIONS -- APPENDIX -- Properties of Hermite Polynomials -- ACKNOWLEDGEMENT -- REFERENCES -- CHAPTER 24 Forecasting White Noise -- 1. INTRODUCTION -- 2. CAUSAL VARIABLES -- 3. INSTANTANEOUS TRANSFORMATIONS -- 4. BILINEAR MODELS -- 5. NORMED MARKOV CHAINS. 6. TRULY CHAOTIC MODELS. |
Record Nr. | UNINA-9910819062103321 |
Granger C. W. J (Clive William John), <1934-2009.>
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Cambridge ; ; New York, : Cambridge University Press, 2001 | ||
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Lo trovi qui: Univ. Federico II | ||
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