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Econometrics can at first appear a highly technical subject, but it can also equip the practitioner with a useful skillset of smart ways to formulate research questions and collect data. Enjoyable Econometrics applies econometric methods to a variety of unusual and engaging research questions, often beyond the realm of economics, demonstrating the great potential of using such methods to understand a wide range of phenomena. Unlike the typical textbook approach, Enjoyable Econometrics follows in the footsteps of Freakonomics by posing interesting questions first before introducing the methodology to find the answers. Therefore, rather than equation-heavy sections based around complex methodologies, the reader is presented with chapters on 'Money' and 'Fashion, Art and Music'. Franses writes in a way that will enthuse and motivate the economics student embarking upon the essential study of econometrics. Indeed, the book shows that econometric methods can be applied to almost anything

"This monograph aims to collect recent theoretical insights and various empirical results for a rapidly developing area concerning the analysis of business and economic forecasts. Strictly following econometric textbooks one would be tempted to assume that forecasts are the outcome of a careful modeling exercise and that the econometric model builder delivers the forecast to an end user"--

To what extent should anybody who has to make model forecasts generated from detailed data analysis adjust their forecasts based on their own intuition? In this book, Philip Hans Franses, one of Europe's leading econometricians, presents the notion that many publicly available forecasts have experienced an 'expert's touch', and questions whether this type of intervention is useful and if a lighter adjustment would be more beneficial. Covering an extensive research area, this accessible book brings together current theoretical insights and new empirical results to examine expert adjustment from an econometric perspective. The author's analysis is based on a range of real forecasts and the datasets upon which the forecasters relied. The various motivations behind experts' modifications are considered, and guidelines for creating more useful and reliable adjusted forecasts are suggested. This book will appeal to academics and practitioners with an interest in forecasting methodology

In this short and very practical 2002 introduction to econometrics Philip Hans Franses guides the reader through the essential concepts of econometrics. Central to the book are practical questions in various economic disciplines, which can be answered using econometric methods and models. The book focuses on a limited number of the essential, most widely used methods, before going on to review the basics of econometrics. The book ends with a number of case studies drawn from recent empirical work to provide an intuitive illustration of what econometricians do when faced with practical questions. Throughout the book Franses emphasises the importance of specification, evaluation and implementation of models appropriate to the data. Assuming basic familiarity only with matrix algebra and calculus the book is designed to appeal as either a short stand-alone introduction for students embarking on an empirical research project or as a supplement to any standard introductory textbook

International audience In this paper we correlate the key features of the distribution of wealth of the 500 wealthiest individuals in the Netherlands with economic growth and stock market returns for 1998 to 2009. We show that each year the distribution obeys a power law and that the key parameter measures the degree of inequality. Our main finding is that more inequality amongst the wealthiest is associated with higher economic growth.

Quarterly and annual gross domestic output (GDP) data are usually revised, and this revision process may cover a few years. It is also usually found that GDP figures are revised upwards. In this note, I provide a simple explanation for why this happens. Implications for interpreting and forecasting GDP data are less simple.

In this paper it is advocated to select a model only if it significantly contributes to the accuracy of a combined forecast. Using hold-out-data forecasts of individual models and of the combined forecast, a useful test for equal forecast accuracy can be designed. An illustration for real-time forecasts for GDP in the Netherlands shows its ease of use.