Koen H. Pauwels

Marketing and performance data often include measures repeated over time. Time-series models are uniquely suited to capture the time dependence of both a criterion variable and predictor variables, and how they relate to each other over time. The objective of this monograph is to give you a foundation in these models and to enable you to apply them to your own research domain of interest. To this end, the author discusses both the underlying perspectives and differences between alternative models, and the practical issues with testing, model choice, model estimation and interpretation common in empirical research. This combination of marketing phenomena and modeling philosophy sets this work apart from previous treatments on the broader topic of econometics and time series analysis in marketing. Time series models on marketing and performance metrics come in different forms, and we distinguish between ‘traditional’ time series models and the ‘modern’ time series models. Modeling Dynamic Relations Among Marketing and Performance Metrics first details the analysis steps, interpretation and marketing insights from traditional time series models. Starting with the univariate treatment of each separate marketing time series in evolution/stationarity tests and ARIMA models. Next, the author considers the over-time relation of multivariate time series in transfer functions and intervention analysis. The monograph then turns to multi-equation models, which are the core workhorses of modern dynamic econometric and time series models of the dynamic relations among marketing and performance metrics. The concluding section discusses policy analysis based on modern time series models and connect them to other time series developments.

This book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. Its primary focus is on models that can be used by managers to support marketing decisions. Modeling Markets presents a comprehensive overview of the tools and methodologies that managers can use in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. In this book, the authors present a wealth of insights developed at the forefront of the field, covering all key aspects of specification, estimation, validation and use of models. The most current insights and innovations in quantitative marketing are presented, including in-depth discussion of Bayesian estimation methods. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.

This book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. Its primary focus is on models that can be used by managers to support marketing decisions. Modeling Markets presents a comprehensive overview of the tools and methodologies that managers can use in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. In this book, the authors present a wealth of insights developed at the forefront of the field, covering all key aspects of specification, estimation, validation and use of models. The most current insights and innovations in quantitative marketing are presented, including in-depth discussion of Bayesian estimation methods. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.