STRUCTURAL ECONOMETRIC MODELLING

CONTENTS
FOREWORD 10
INTRODUCTION 11
THE EXAMPLE: A VERY BASIC MODEL 14
15
CHAPTER 1: NOTATIONS AND DEFINITIONS 15
1.1 THE MODEL AS A SET OF EQUATIONS 15
1.2 THE ELEMENTS IN A MODEL 15
1.2.1 VARIABLES: ENDOGENOUS AND EXOGENOUS 15
1.2.2 EQUATIONS: BEHAVIORAL AND IDENTITIES 17
1.2.3 PARAMETERS 20
1.2.4 THE RANDOM TERM 21
1.2.5 RESIDUALS VERSUS ERRORS 23
1.2.6 FORMULATIONS 23
1.2.7 THE TIME DIMENSION 23
1.2.8 LINEARITY 29
1.2.9 OTHER PROPERTIES 32
1.2.10 CONSTRAINTS THE MODEL MUST MEET 36
1.2.11 NORMALIZATION AND IDENTIFICATION 42
1.2.12 CONCLUSION 46
2 CHAPTER 2: MODEL APPLICATIONS 47
2.1 OPERATIONAL DIAGNOSES 47
2.1.1 DIFFERENT TYPES OF DIAGNOSES: SCENARIOS AND SHOCKS 47
2.1.2 ADVANTAGES OF MODELS 48
2.1.3 A CERTAIN REASSESSING 49
2.2 THEORETICAL MODELS 50
2.3 QUANTIFIED SMALL MODELS 50
2.3.1 WITH SCIENTIFIC PURPOSE 50
2.3.2 WITH AN EDUCATIONAL PURPOSE 51
3 CHAPTER 3: MODEL TYPES 52
3.1 THE FIELD 52
3.2 THE SIZE 53
3.2.1 DETERMINANTS OF THE SIZE 53
3.2.2 A CLASSIFICATION 54
3.3 THE HORIZON 54
3.3.1 FOR FORECASTING 54
3.3.2 FOR MODEL ANALYSIS 55
3.3.3 A CLASSIFICATION 55
3.4 THE PERIODICITY 55
3.5 OTHER MODELS 56
4 CHAPTER 4: GENERAL ELEMENTS 57
4.1 THE STAGES IN THE PROCESS 57
4.1.1 PREPARING THE MODEL 57
4.1.2 ESTIMATION 57
4.1.3 SOLVING AND TESTING OVER THE PAST. 57
4.1.4 SOLVING AND TESTING OVER THE FUTURE 58
4.1.5 USING THE MODEL FOR FORECASTS AND POLICY STUDIES 58
4.2 THE CHOICE OF SOFTWARE ERROR! BOOKMARK NOT DEFINED.
4.3 HOW TO ORGANIZE THE DEVELOPMENT OF THE MODEL 58
5 CHAPTER 5: PREPARING THE MODEL 61
5.1 PREPARING THE MODEL: THE FRAMEWORK 61
5.2 PREPARING THE MODEL: SPECIFIC DATA ISSUES 63
5.2.1 TYPES OF DATA 63
5.2.2 THE ACCESS TO DATA 64
5.2.3 PREPARING THE DATA FOR THE TRANSFER 66
5.2.4 THE PRELIMINARY PROCESSING OF SERIES 67
5.2.5 UPDATES 70
5.2.6 SUPPRESSIONS 70
5.2.7 THE DOCUMENTATION 70
5.2.8 CONSEQUENCES ON WORK ORGANIZATION 71
5.2.9 THE PRACTICAL OPTIONS 73
5.3 BACK TO OUR EXAMPLE 73
5.3.1 APPLICATION TO OUR EXAMPLE 77
5.3.2 THE EVIEWS PROGRAM 87
5.3.3 A FIRST TEST: CHECKING THE RESIDUALS IN THE IDENTITIES 97
5.4 USING LOOPS AND GROUPS IN EVIEWS 105
5.4.1 GROUPS 105
5.4.2 LOOPS 106
6 CHAPTER 6 THE ESTIMATION OF EQUATIONS 109
6.1 THE PROCESS OF ESTIMATION 110
6.2 SPECIFIC ISSUES 110
6.2.1 THE R2 OR R-SQUARED 110
6.2.2 THE CONSTANT TERM 114
6.3 APPLICATIONS: OUR MODEL 115
6.3.1 CHANGE IN INVENTORIES 116
6.3.2 INVESTMENT: THE NECESSITY TO ESTABLISH A CONSISTENT THEORETICAL EQUATION PRIOR TO ESTIMATION 128
6.3.3 EMPLOYMENT: STATIONARITY, ERROR CORRECTION MODELS, BREAKPOINT TEST. 135
6.3.4 EXPORTS: AUTOREGRESSIVE PROCESS, COINTEGRATION, LONG TERM STABILITY. 149
6.3.5 IMPORTS: GOING FURTHER ON COINTEGRATION AND LONG TERM STABILITY. 164
6.3.6 BACK TO THE RESIDUAL CHECK 180
6.3.7 THE PRESENT MODEL 182
7 CHAPTER 7: TESTING THE MODEL THROUGH SIMULATIONS OVER THE PAST 184
7.1 THE SOLUTION 185
7.1.1 GAUSS-SEIDEL 185
7.1.2 RITZ-JORDAN 186
7.1.3 NEWTON AND ITS VARIANTS 186
7.1.4 ITERATIONS AND TEST OF CONVERGENCE 191
7.1.5 STUDY OF THE CONVERGENCE 194
7.1.6 SOLVING THE MODEL: BASIC EVIEWS TECHNIQUES 217
7.2 A FIRST VALIDATION 231
7.2.1 EX POST SIMULATIONS 231
7.2.2 EX-POST FORECASTS 237
7.2.3 SOLVING THE MODEL: SCENARIOS 238
7.2.4 OUR EXAMPLE 241
7.2.5 ANALYTIC SHOCKS 243
7.2.6 OUR EXAMPLE 246
8 CHAPTER 8: TESTING THE MODEL OVER THE FUTURE 251
8.1 MAKING THE MODEL CONVERGE IN THE LONG RUN 252
8.1.1 THE ASSUMPTIONS 252
8.1.2 ADAPTING THE FORMULATIONS 253
8.1.3 IMPROVING THE CHANCE (AND SPEED) OF CONVERGENCE 255
8.1.4 SOLVING PARTIAL MODELS 255
8.1.5 CHECKING THE EXISTENCE OF A LONG TERM SOLUTION 255
8.2 CONVERGENCE PROBLEMS IN THE SHORT RUN 257
8.3 CONVERGENCE PROBLEMS IN THE MEDIUM RUN 258
8.4 TESTING THE RESULTS 259
8.4.1 OF SIMULATIONS 259
8.4.2 OF SHOCKS 259
8.5 EVIEWS FEATURES 259
8.5.1 PRODUCING SIMULATIONS 260
8.5.2 PRODUCING A BASE SOLUTION 262
8.5.3 PRODUCING SHOCKS 263
8.5.4 CHANGING MODEL SPECIFICATIONS 263
8.6 RATIONAL EXPECTATIONS 267
8.6.1 THE FRAMEWORK 267
8.6.2 CONSEQUENCES FOR MODEL SIMULATIONS 267
8.6.3 TECHNICAL ELEMENTS 268
8.6.4 OUR EXAMPLE 268
8.6.5 THE TEST 270
8.6.6 THE RESULTS 270
8.7 STOCHASTIC SIMULATIONS 272
8.7.1 PURELY STATISTICAL ERRORS 272
8.7.2 FORMULATION AND ASSUMPTION ERRORS 273
8.7.3 CONSIDERING THE ERRORS 273
8.7.4 THE INTEREST OF THE TECHNIQUE 275
8.7.5 BACK TO OUR EXAMPLE 276
8.7.6 THE RESULTS 276
8.8 GOING FURTHER: STUDYING MODEL PROPERTIES 279
8.8.1 EIGENVALUE ANALYSIS 279
8.8.2 THE CASE OF ERROR CORRECTION MODELS: A SIMPLE EXAMPLE 290