Written in a comprehensive yet accessible style, this Handbook introduces readers to a range of modern empirical methods with applications in microeconomics, illustrating how to use two of the most popular software packages, Stata and R, in microeconometric applications.

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.

This volume offers a comprehensive review of experimental methods in economics. Its 21 chapters cover theoretical and practical issues such as incentives, theory and policy development, data analysis, recruitment, software and laboratory organization. The Handbook includes separate parts on procedures, field experiments and neuroeconomics, and provides the first methodological overview of replication studies and a novel set-valued equilibrium concept. As a whole, the combination of basic methods and current developments will aid both beginners and advanced experimental economists.

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.

This thought provoking book builds on existing research traditions that make small business, entrepreneurship and family business a resource rich arena for study.

This textbook articulates the elements of good craftsmanship in applied microeconomic research and demonstrates its effectiveness with multiple examples from economic literature. Empirical economic research is a combination of several elements: theory, econometric modelling, institutional analysis, data handling, estimation, inference, and interpretation. A large body of work demonstrates how to do many of these things correctly, but to date, there is no central resource available which articulates the essential principles involved and ties them together. In showing how these research elements can be best blended to maximize the credibility and impact of the findings that result, this book presents a basic framework for thinking about craftsmanship. This framework lays out the proper context within which the researcher should view the analysis, involving institutional factors, complementary policy instruments, and competing hypotheses that can influence or explain the phenomena being studied. It also emphasizes the interconnectedness of theory, econometric modeling, data, estimation, inference, and interpretation, arguing that good craftsmanship requires strong links between each. Once the framework has been set, the book devotes a chapter to each element of the analysis, providing robust instruction for each case. Assuming a working knowledge of econometrics, this text is aimed at graduate students and early-career academic researchers as well as empirical economists looking to improve their technique.

This Handbook examines the diverse methodologies and philosophies employed in research on entrepreneurship, small enterprises and family businesses. Exploring fundamental questions involved in data collection, this new and updated edition emphasises the increased importance of understanding the nuances of methods and applications in today's research landscape. Building on rich scholarly traditions, the Handbook places particular focus on ignored and misunderstood research concepts. New chapters consider the complex ethical dilemmas facing researchers in entrepreneurship and assess how to best leverage large-scale secondary data for maximum research impact. Expert contributors analyse key issues in the field including how to measure progress in research, experimental methods, theory development and testing, and how to conduct cross-cultural studies. They identify fruitful research directions for emerging and seasoned scholars, demonstrating how to produce work that is both practical and theoretically important. Covering both quantitative and qualitative techniques, this Handbook is an essential resource for students and scholars of entrepreneurship. It is also a valuable read for academics across business and management more widely, providing a detailed overview of essential methods for all researchers in the field.

A comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning. Reasoning about cause and effect—the consequence of doing one thing versus another—is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens. Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data. Martin Huber’s accessible approach highlights the intuition and motivation behind various methods while also providing formal discussions of key concepts using statistical notation. Causal Analysis covers several methodological developments not covered in other texts, including new trends in machine learning, the evaluation of interaction or interference effects, and recent research designs such as bunching or kink designs. Most complete and cutting-edge introduction to causal analysis, including causal machine learning Clean presentation of rigorous material avoids extraneous detail and emphasizes conceptual analogies over statistical notation Supplies a range of applications and practical examples using R