This book presents the most important and practically relevant quantitative models for marketing research. Each model includes a demonstration of the mechanics of the model, empirical analysis, real world examples, and an interpretation of results and findings. The reader will learn how to apply the techniques, as well as understand the latest methodological developments in the academic literature. Students and practitioners with differing numerical skills are guided through the book, although a knowledge of elementary numerical techniques is assumed.
Author(s): Philip Hans Franses, Richard Paap
Year: 2001
Language: English
Pages: 220
Cover......Page 1
Half-title......Page 3
Title......Page 5
Copyright......Page 6
Contents......Page 7
Figures......Page 11
Tables......Page 13
Preface......Page 15
1.1 Introduction......Page 17
1.1.1 On marketing research......Page 18
1.1.2 Data......Page 20
1.1.3 Models......Page 21
1.2.1 How to use this book......Page 22
1.2.2 Outline of chapter contents......Page 23
2.1 Quantitative models......Page 26
2.2 Marketing performance measures......Page 28
2.2.1 A continuous variable......Page 29
2.2.2 A binomial variable......Page 31
2.2.3 An unordered multinomial variable......Page 34
2.2.4 An ordered multinomial variable......Page 35
2.2.5 A limited continuous variable......Page 37
2.2.6 A duration variable......Page 40
2.3 What do we exclude from this book?......Page 42
3.1 The standard Linear Regression model......Page 45
3.2.1 Estimation by Ordinary Least Squares......Page 50
3.2.2 Estimation by Maximum Likelihood......Page 51
3.3 Diagnostics, model selection and forecasting......Page 54
3.3.1 Diagnostics......Page 55
3.3.2 Model selection......Page 57
3.3.3 Forecasting......Page 59
3.4 Modeling sales......Page 60
3.5 Advanced topics......Page 63
4.1 Representation and interpretation......Page 65
4.1.1 Modeling a binomial dependent variable......Page 66
4.1.2 The Logit and Probit models......Page 69
4.1.3 Model interpretation......Page 71
4.2 Estimation......Page 74
4.2.1 The Logit model......Page 75
4.2.2 The Probit model......Page 76
4.3 Diagnostics, model selection and forecasting......Page 77
4.3.1 Diagnostics......Page 78
4.3.2 Model selection......Page 79
4.3.3 Forecasting......Page 81
4.4 Modeling the choice between two brands......Page 82
4.5.1 Modeling unobserved heterogeneity......Page 87
4.5.3 Sample selection issues......Page 89
5 An unordered multinomial dependent variable......Page 92
5.1.1 The Multinomial and Conditional Logit models......Page 93
The Multinomial Logit model......Page 95
The Conditional Logit model......Page 98
The independence of irrelevant alternatives......Page 101
5.1.2 The Multinomial Probit model......Page 102
5.1.3 The Nested Logit model......Page 104
5.2 Estimation......Page 107
5.2.1 The Multinomial and Conditional Logit models......Page 108
5.2.3 The Nested Logit model......Page 111
5.3.1 Diagnostics......Page 112
5.3.2 Model selection......Page 113
5.3.3 Forecasting......Page 115
5.4 Modeling the choice between four brands......Page 117
5.5.1 Modeling unobserved heterogeneity......Page 123
5.5.2 Modeling dynamics......Page 124
5.A. EViews Code......Page 125
5.A.2 The Conditional Logit model......Page 126
5.A.3 The Nested Logit model......Page 127
6 An ordered multinomial dependent variable......Page 128
6.1.1 Modeling an ordered dependent variable......Page 129
6.1.2 The Ordered Logit and Ordered Probit models......Page 132
6.1.3 Model interpretation......Page 133
6.2.1 A general ordered regression model......Page 134
6.2.2 The Ordered Logit and Probit models......Page 137
6.3 Diagnostics, model selection and forecasting......Page 138
6.3.1 Diagnostics......Page 139
6.3.2 Model selection......Page 140
6.4 Modeling risk profiles of individuals......Page 141
6.5 Advanced topics......Page 145
6.5.2 Selective sampling......Page 146
7 A limited dependent variable......Page 149
7.1.1 Truncated Regression model......Page 150
Type-1 Tobit model......Page 153
Type-2 Tobit model......Page 155
7.2.1 Truncated Regression model......Page 158
Type-1 Tobit......Page 160
Type-2 Tobit......Page 161
Residuals......Page 163
Specification tests......Page 164
7.3.2 Model selection......Page 165
Censored Regression model......Page 166
7.4 Modeling donations to charity......Page 167
7.5 Advanced topics......Page 171
8 A duration dependent variable......Page 174
8.1 Representation and interpretation......Page 175
8.1.1 Accelerated Lifetime model......Page 181
8.1.2 Proportional Hazard model......Page 182
8.2 Estimation......Page 184
8.2.1 Accelerated Lifetime model......Page 185
8.2.2 Proportional Hazard model......Page 186
8.3.1 Diagnostics......Page 188
8.3.2 Model selection......Page 190
8.4 Modeling interpurchase times......Page 191
8.5 Advanced topics......Page 195
Accelerated Lifetime model......Page 196
Proportional Hazard model......Page 197
8.A.1 Accelerated Lifetime model (Weibull distribution)......Page 198
8.A.2 Proportional Hazard model (loglogistic distribution)......Page 199
A.1 Overview of matrix algebra......Page 200
A.2 Overview of distributions......Page 203
A.3 Critical values......Page 209
Bibliography......Page 212
Author index......Page 218
Subject index......Page 220
