Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. Terence Mills introduces these various approaches to allow students and researchers to appreciate the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.
Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.
This book provides an introductory treatment of time series econometrics, a subject that is of key importance to both students and practitioners of economics. It contains material that any serious student of economics and finance should be acquainted with if they are seeking to gain an understanding of a real functioning economy.
Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.
This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.
The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.
Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.
Udny Yule’s seminal influence on time series analysis has long been recognized but much less recognized is that Yule was not only a wonderful expositor but that he had also published equally important research in an extraordinarily wide range of fields, from developing the theory of correlation and regression to providing mathematical models of evolutionary behavior, and from analyzing data on pauperism to using statistical methods to resolve cases of disputed authorship of medieval manuscripts. Yet little has been written about Yule and his work, apart from a few scattered articles, since his death in 1951 and the two obituaries that appeared in the following year. This book is an opportune moment to redress the balance and to embark on the first major study of Yule’s statistical research and subsequent legacy. Part of the text’s title is taken from Yule’s 1920 article in the Cambridge Review, ‘The wind bloweth where it listeth’, where Yule coined the phrase ‘loafers of the world’ to describe free spirits of academe, who have become an increasingly rare breed in modern university life. Udny Yule was Lecturer, then Reader, in Statistics at Cambridge University, England, from 1912 to 1930. He was a member, then Fellow, of St John’s College, at Cambridge Universty, from 1913 until his death in 1951. He was a member of the Royal Statistical Society from 1895 until his death, was awarded the Society’s Guy Medal in Gold in 1911, and was President from 1924 to 1926. Yule was awarded a C.B.E. in 1919 for his work during the First World War in the War Office and the Ministry of Food.
Terence Mills' best-selling graduate textbook provides detailed coverage of research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. This third edition, co-authored with Raphael Markellos, contains a wealth of material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing.
This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.
Udny Yule’s seminal influence on time series analysis has long been recognized but much less recognized is that Yule was not only a wonderful expositor but that he had also published equally important research in an extraordinarily wide range of fields, from developing the theory of correlation and regression to providing mathematical models of evolutionary behavior, and from analyzing data on pauperism to using statistical methods to resolve cases of disputed authorship of medieval manuscripts. Yet little has been written about Yule and his work, apart from a few scattered articles, since his death in 1951 and the two obituaries that appeared in the following year. This book is an opportune moment to redress the balance and to embark on the first major study of Yule’s statistical research and subsequent legacy. Part of the text’s title is taken from Yule’s 1920 article in the Cambridge Review, ‘The wind bloweth where it listeth’, where Yule coined the phrase ‘loafers of the world’ to describe free spirits of academe, who have become an increasingly rare breed in modern university life. Udny Yule was Lecturer, then Reader, in Statistics at Cambridge University, England, from 1912 to 1930. He was a member, then Fellow, of St John’s College, at Cambridge Universty, from 1913 until his death in 1951. He was a member of the Royal Statistical Society from 1895 until his death, was awarded the Society’s Guy Medal in Gold in 1911, and was President from 1924 to 1926. Yule was awarded a C.B.E. in 1919 for his work during the First World War in the War Office and the Ministry of Food.
This book develops the major themes of time series analysis from its formal beginnings in the early part of the 20th century to the present day through the research of six distinguished British statisticians, all of whose work is characterised by the British traits of pragmatism and the desire to solve practical problems of importance.
The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.
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