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. Topics covered include unit roots, non-linearities and structural breaks, time aggregation, forecasting, the Kalman filter, generalised method of moments, maximum likelihood and Bayesian estimation, vector autoregressive, dynamic stochastic general equilibrium and dynamic panel models. Presenting the most important models and techniques for empirical research, this Handbook will appeal to students, researchers and academics working in empirical macro and econometrics.

Bringing together the recent advances and innovative methods in macroeconomic forecasting, this erudite Handbook outlines how to forecast, including following world events such as the Covid-19 pandemic and the global financial crisis. With contributions from global experts, chapters explore the use of machine-learning techniques, the value of social media data, and climate change forecasting. Investigating the opportunities and challenges brought about by 'Big Data', it examines how data can be used for forecasting by economists and analysts in international organisations as well as private practice. Utilising econometric techniques, it helps quantify the uncertainties regarding the future. The insightful Handbook is an excellent resource for scholars of advanced macroeconomic forecasting, as well those requiring a better understanding of econometrics, statistics, and modelling approaches. Practitioners in both private and public sectors will greatly appreciate the expert guidance for good future forecasting practices.

Bringing together the recent advances and innovative methods in macroeconomic forecasting, this erudite Handbook outlines how to forecast, including following world events such as the Covid-19 pandemic and the global financial crisis. With contributions from global experts, chapters explore the use of machine-learning techniques, the value of social media data, and climate change forecasting. This title contains one or more Open Access chapters.

The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. - Focuses on innovation in economic forecasting via industry applications - Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications - Makes details about economic forecasting accessible to scholars in fields outside economics

This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

Despite the important methodological critiques of the mainstream offered by heterodox economics, the dominant research method taught in heterodox programmes remains econometrics. This compelling Handbook provides a comprehensive introduction to a range of alternative research methods, invaluable for analysing the data prominent in heterodox studies. Providing a solid basis for a mixed methods approach to economic investigations, the expertly crafted contributions are split into three distinct sections: philosophical foundation and research strategy, research methods and data collection, and applications. Introductions to a host of invaluable methods such as survey, historical, ethnographic, experimental and mixed approaches, together with factor, cluster, complex and social network analytics, are complemented by descriptions of applications in practice. Practical and expansive, this Handbook is highly pertinent for students and scholars of economics, particularly those dedicated to heterodox approaches, as it provides a solid reference for mixed methods not available in mainstream economics research methods courses.

The main purpose of this Handbook is to provide overviews and assessments of the state-of-the-art regarding research methods, approaches and applications central to economic geography. The chapters are written by distinguished researchers from a variet

This comprehensive Handbook is aimed at both academic researchers and practitioners in the field of complexity science. The book’s 26 chapters, specially written by leading experts, provide in-depth coverage of research methods based on the sciences of complexity. The research methods presented are illustratively applied to practical cases and are readily accessible to researchers and decision makers alike.

Social capital is fundamentally concerned with resources in social relations. This Handbook brings together leading scholars from around the world to address important questions on the determinants, manifestations and consequences of social capital. Vario

Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.