FORECASTING METHODS AND APPLICATIONS SPYROS MAKRIDAKIS European Institute of Business Administration (INSEAD) STEVEN С WHEELWRIGHT Harvard Business School. JOHN WILEY & SONS SANTA BARBARA NEW YORK CHICHESTER BRISBANE TORONTO A Wiley/Hamilton Publication
CONTENTS Preface PART ONE BACKGROUND AND PERSPECTIVE 2 CHAPTER 1 INTRODUCTION 4 1.1 Needs and Uses of Forecasting 4 1.2 Current Status of Quantitative and Technological Forecasting 7 1 2 CHAPTER 2 FUNDAMENTALS OF QUANTITATIVE FORECASTING 2.1 Explanatory versus Time-Series Forecasting 2.2 Least Squares Estimates 2.3 Discovering and Describing Existing Relationships 2.4 Variances and Covariances 2.5 Autovariance and Autocorrelation Appendix Chapter 2 14 14 17 23 28 34 36 39 39 PART TWO SMOOTHING AND DECOMPOSITION TIME-SERIES METHODS 42 CHAPTER 3 SMOOTHING METHODS 3.1 Introduction 3.2 Single Moving Averages 44 44 45
XII CONTENTS 3.3 Single Exponential Smoothing 48 3.4 Adaptive-Response-Rate Single Exponential Smoothing 53 3.5 Linear Moving Averages 55 3.6 Linear Exponential Smoothing 61 3.7 Brown's Quadratic Exponential Smoothing 66 3.8 Selecting the Appropriate Smoothing Method for the Data Pattern 69 3.9 Winters' Linear and Seasonal Exponential Smoothing 72 3.10 Other Smoothing Methods 74 3.1 1 General Aspects of Smoothing Methods 77 3.12 Development of the Mathematical Basis of Smoothing Methods 79 81 82 CHAPTER 4 DECOMPOSITION METHODS 88 4.1 Introduction 88 4.2 Trend Fitting 93 4.3 The Ratio-to-Moving Averages Classical Decomposition Method 94 4.4 Different Types of Moving Averages 101 4.5 The Census II Decomposition Method 106 4.6 The FORAN System 138 1 40 140 PART THREE REGRESSION METHODS 144 CHAPTER 5 SIMPLE REGRESSION 5.1 General Comments on Regression Methods 5.2 Different Forms of Functional Relationships 5.3 Determining the Parameters, a and b, of a Straight Line 5.4 The Correlation Coefficient 5.5 The Significance of a Regression Equation 5.6 Trend Analysis, Time-Series Forecasting 5.7 The Regression Equation as a Model Appendix Mathematical Supplement Chapter 5 146 146 147 150 153 155 164 165 167 176 176 CHAPTER 6 MULTIPLE REGRESSION 6.1 Introduction 6.2 Applying Multiple Regression 180 180 182
CONTENTS XIII 6.3 Multiple Correlation and the Coefficient of Determination 6.4 Tests of Significance 6.5 Transformations 6.6 The Assumptions of Regression Analysis 6.7 Multicollineanty 6.8 Model Specification 6.9 Lagged Variables 6.10 Dummy Variables 6.1 1 Summary Appendix Mathematical Supplement Chapter 6 183 184 186 205 209 211 216 217 220 221 226 226 CHAPTER 7 ECONOMETRIC MODELS AND FORECASTING 7.1 The Basis of Econometric Modeling 7.2 The Advantages and Drawbacks of Econometric Methods 7.3 Estimation Procedures Used by Econometric Models 7.4 Specification and Identification 7.5 Development and Application of Econometric Models 230 231 233 234 238 240 248 PART FOUR AUTOREGRESSIVE/MOVING AVERAGE (ARMA) TIME-SERIES METHODS 250 CHAPTER 8 TIME-SERIES ANALYSIS 8.1 Introduction to Autoregressive Schemes 8.2 Identifying the Characteristics of a Time Series 8.3 Autocorrelation Coefficients 8.4 The Sampling Distribution of Autocorrelations 8.5 Autocorrelation Analysis 8.6 The X 2 -Test 8.7 Partial Autocorrelations 8.8 Summary of Time-Series Analysis 252 252 254 255 258 260 269 270 271 273 273 CHAPTER 9 GENERALIZED ADAPTIVE FILTERING 9.1 Analyzing and Forecasting a Time Series 9.2 Autoregressive Models 9.3 The Method of Adaptive Filtering 276 276 284 286
XIV CONTENTS 9.4 Moving Average Models 9.5 Applying the Method of Adaptive Filtering in MA Models 9.6 Mixed Autoregressive Moving Average Models 9.7 Seasonal ARMA Models 9.8 Summary Comments on Generalized Adaptive Filtering Appendix Mathematical Supplement Chapter 9 294 296 299 307 309 310 326 326 CHAPTER 10 THE BOX-JENKINS METHOD 10.1 Identification 10.2 Estimating the Parameters of an ARMA Model 10.3 Diagnostic Checking of the Estimated Model 10.4 Using an ARMA Model to Forecast 10.5 Seasonal ARMA Models 10.6 An Application of Seasonal ARMA Processes 10.7 Achieving Stationarity in Variance 328 328 340 342 344 346 351 361 368 369 CHAPTER 1 1 MULTIVARIATE TIME-SERIES ANALYSIS 376 11.1 Introduction 376 1 1.2 Bivariate Time-Series Analysis 377 1 1.3 Identification of an Appropriate MARMA Model and Initial Estimation of Its Parameters 382 1 1.4 Estimation of the Parameters of a Specific MARMA Model and Diagnostic Checking 406 1 1.5 Identification of r, s. and b by Contracting the Cross Autocorrelations of the Estimates 419 1 1.6 Other Multivariate Models 422 1 1.7 Conclusions 428 430 PART FIVE QUALITATIVE AND TECHNOLOGICAL METHODS 432 CHAPTER 12 PREDICTING THE CYCLE 12.1 Introduction 1 2.2 Business Cycles 434 434 437
CONTENTS 12.3 Causes of Business Cycles 12.4 Anticipatory Surveys 12.5 Leading Indicators 1 2.6 Paired Indices 12.7 Tracking the Evolution of Cycles 440 441 443 443 451 455 CHAPTER 13 SUBJECTIVE ASSESSMENT METHODS 13.1 The Basic Framework of Decision Analysis 13.2 Methods for Obtaining Subjective Assessments 13.3 Combining Subjective Assessments and Decision Analysis in Practice 456 458 464 476 485 485 CHAPTER 14 QUALITATIVE AND TECHNOLOGICAL METHODS OF FORECASTING 492 14.1 Introduction 492 14.2 Exploratory Methods of Forecasting 494 14.3 Normative Approaches to Technological Forecasting 514 14.4 Summary 524 526 Exercise 528 PART SIX INTEGRATING FORECASTING AND PLANNING IN THE ORGANIZATION 530 CHAPTER 15 FORECASTING AND PLANNING 532 15.1 The Role of Forecasting in Planning 532 15.2 Relating Forecasting and Planning in the Organization 535 15.3 Forecasting as Input to Planning and Decision Making 541 15.4 Contribution of Forecasting to Analysis and Understanding 555 564 CHAPTER 16 COMPARISON AND SELECTION OF FORECASTING METHODS 566 16.1 The Accuracy of Forecasting Methods 568 16.2 Pattern of the Data and Its Effects on Individual Forecasting Methods 587
XVI CONTENTS 16.3 Time Horizon Effects on Forecasting Methods 16.4 The Costs of Forecasting Methods 16.5 The Ease of Application of Forecasting Methods 16.6 An Interactive Procedure for Selecting, Running, and Comparing Alternative Forecasting Methods 588 592 596 596 598 CHAPTER 17 DATA PROCUREMENT, PREPARATION, AND HANDLING 17.1 Definition and Specification of Variables in Forecasting 17.2 Data Procurement 1 7.3 Data Preparation 17.4 Data Management 600 601 606 614 621 631 CHAPTER 18 ORGANIZATIONAL AND BEHAVIORAL ASPECTS OF FORECASTING 632 18.1 Status of Forecasting in Business Firms 633 18.2 Reasons for the Organizational Status of Forecasting in the Mid-1970s 642 18.3 Organizational Steps for Improved Forecasting 649 18.4 Organizing for Individual Forecasting Projects 663 667 APPENDIX I STATISTICAL TABLES A Areas under the Normal Curve В Student f Distribution С Values of the F-Test D Values of the Durbin-Watson Statistic E Critical Points of the Chi-Squared (x 2 ) Statistic 668 668 669 670 674 675 APPENDIX II APPENDIX III INDEX GLOSSARY DATA SOURCES 676 698 703