Handbook of Research Methods and Applications in Empirical Macroeconomics
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Handbook of Research Methods and Applications in Empirical Macroeconomics

Edited by Nigar Hashimzade and Michael A. Thornton

This comprehensive Handbook presents the current state of art in the theory and methodology of macroeconomic data analysis. It is intended as a reference for graduate students and researchers interested in exploring new methodologies, but can also be employed as a graduate text. The Handbook concentrates on the most important issues, models and techniques for research in macroeconomics, and highlights the core methodologies and their empirical application in an accessible manner. Each chapter is largely self-contained, whilst the comprehensive introduction provides an overview of the key statistical concepts and methods. All of the chapters include the essential references for each topic and provide a sound guide for further reading.
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Chapter 3: Trends, cycles and structural breaks

Terence C. Mills


The analysis of cycles in macroeconomic time series began in earnest in the 1870s with the sunspot and Venus theories of William Stanley Jevons and Henry Ludwell Moore and the rather more conventional credit cycle theory of Clément Jugler (see Morgan, 1990, Chapter 1). Secular, or trend, movements were first studied somewhat later, with the term ‘trend’ only being coined in 1901 by Reginald Hooker when analysing British import and export data (Hooker, 1901). The early attempts to take into account trend movements, typically by detrending using simple moving averages or graphical interpolation, are analysed by Klein (1997), while the next generation of weighted moving averages, often based on actuarial graduation formulae using local polynomials, are surveyed in Mills (2011, Chapter 10). The first half of the twentieth century saw much progress, both descriptive and theoretical, on the modelling of trends and cycles, as briefly recounted in Mills (2009a), but it took a further decade for techniques to be developed that would, in due course, lead to a revolution in the way trends and cycles were modelled and extracted.

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