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.
The laws of modern physics are seen as the bedrock of our understanding of the material world that surrounds us. Newton's and Maxwell's mathematics reliably describe behaviour and events in the world, and have given us the age of technology from telephones to space travel. Yet the founders of modern scientific thought, such as Einstein, Bohr, Heisenberg and Pauli, struggled to pin down the paradoxical concepts they needed to present 'workable' theories, as the subatomic and quantum world began to reveal its mysteries. At the height of the debate about the nature of matter, Einstein famously objected that 'God does not play dice'. Starting from the significance of zero and one, with their contrasting Eastern and Western philosophies, Franses unravels the knots that surround elusive concepts such as matter, chance, time, light, darkness, emptiness, and form. Exploring current models in science, he asks: does light travel in time? Or is it time that travels in light? How can emptiness hold potential? Can chance create order? What does our own experience mean in all this? In this stimulating book, the author invites us to travel through a journey, and a life, full of surprise and ambiguity, from paradoxes in physics to the meaning of time and the mythology of creation.
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.
With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.
This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking and forecasting of univariate periodic autoregressive models. Tests for periodic integration, are discussed, and an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting is provided. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, as these are the most relevant. This overview contains single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, and the book will be of interest to advanced graduate students and researchers in econometrics, as well as practitioners looking for an understanding of how to approach seasonal data.
Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics. Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). · Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. · Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics. · Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. · Derivations and theory exercises are clearly marked for students in advanced courses. This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.
It is increasingly important for lawyers to know how to deal with quantitative data. It is about estimates and probabilities of the extent to which something will or will not happen in relation to a legally relevant insight or legal consideration. We all know the case of Lucia de Berk, the unfortunate nurse who had been present at (initially) thirty deaths. According to the Public Prosecution Service this was a remarkable number, too many and a reason to prosecute. They calculated that De Berk had a very small chance to have been involved so often by chance in a death. A miscarriage of justice? This book offers lawyers quantitative insights. It teaches them to deal with numbers. What is the context of those numbers? How can you make, interpret and evaluate probability judgements and predictions? As a lawyer, you do not need to know the exact technical details, but you do need to be able to ask the right questions and interpret the experts' answers. The idea to write this book came from the teaching of econometrician Philip Hans Franses to law students.
Time Series Models for Business and Economic Forecasting is the most up-to-date and accessible guide to one of the fastest growing areas in business and economic analysis. The author is regarded as one of the most accomplished econometricians in Europe and this book is based on his highly successful lecture program for multidisciplinary, graduate and upper level undergraduate students. Early chapters of the book focus on the typical features of time series data in business and economics. Later chapters are concerned with the discussion of some important concepts in time series analysis, the techniques that can be readily applied in practice, different modeling methods and model structures, multivariate time, and the common aspects across time series.
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