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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.

Testing for a Unit Root is now an essential part of time series analysis but the literature on the topic is so large that knowing where to start is difficult even for the specialist. This book provides a way into the techniques of unit root testing, explaining the pitfalls and nonstandard cases, using practical examples and simulation analysis.

This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.

Covers the key issues required for students wishing to understand and analyse the core empirical issues in economics. It focuses on descriptive statistics, probability concepts and basic econometric techniques and has an accompanying website that contains all the data used in the examples and provides exercises for undertaking original research.

This book aims at meeting the growing demand in the field by introducing the basic spatial econometrics methodologies to a wide variety of researchers. It provides a practical guide that illustrates the potential of spatial econometric modelling, discusses problems and solutions and interprets empirical results.

An accessible discussion examining computationally-intensive techniques and bootstrap methods, providing ways to improve the finite-sample performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation-based tests to help perform econometric analyses.

This book gives an authoritative overview of the literature on non-stationarity, integration and unit roots, providing direction and guidance. It also provides detailed examples to show how the techniques can be applied in practical situations and the pitfalls to avoid.

Financial econometrics is one of the greatest on-going success stories of recent decades, as it has become one of the most active areas of research in econometrics. It describes the methods of evaluating these more complex forecasts which provide a fuller description of the range of possible future outcomes.

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.

This open access book focuses on the concepts, tools and techniques needed to successfully model ever-changing time-series data. It emphasizes the need for general models to account for the complexities of the modern world and how these can be applied to a range of issues facing Earth, from modelling volcanic eruptions, carbon dioxide emissions and global temperatures, to modelling unemployment rates, wage inflation and population growth.Except where otherwise noted, this book is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0.

Why should we be interested in macroeconomic survey expectations? Clements presents the nature of survey data, addresses some of the difficulties posed by the way in which survey expectations are elicited and considers the evaluation of point predictions and probability distributions.

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.

Testing for a unit root is now an essential part of time series analysis. This volume provides a critical overview and assessment of tests for a unit root in time series, developing the concepts necessary to understand the key theoretical and practical models in unit root testing.

Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of econometrics to real world problems.