Haavelmo’s 1944 monograph, The Probability Approach in Econometrics, is widely acclaimed as the manifesto of econometrics. This book challenges Haavelmo’s probability approach, shows how its use is delivering defective and inefficient results, and argues for a paradigm shift in econometrics towards a full embrace of machine learning, with its attendant benefits. Machine learning has only come into existence over recent decades, whereas the universally accepted and current form of econometrics has developed over the past century. A comparison between the two is, however, striking. The practical achievements of machine learning significantly outshine those of econometrics, confirming the presence of widespread inefficiencies in current econometric research. The relative efficiency of machine learning is based on its theoretical foundation, and particularly on the notion of Probably Approximately Correct (PAC) learning. Careful examination reveals that PAC learning theory delivers the goals of applied economic modelling research far better than Haavelmo’s probability approach. Econometrics should therefore renounce its outdated foundation, and rebuild itself upon PAC learning theory so as to unleash its pent-up research potential. The book is catered for applied economists, econometricians, economists specialising in the history and methodology of economics, advanced students, philosophers of social sciences.

‘Situational Analysis’ represents Karl Popper’s methodological proposal for the social sciences. Although it has been widely studied and interpreted, this book argues that Situational Analysis remains underestimated and undeveloped and, if properly reformulated, could yet become a broad methodological framework that encompasses both the ‘historical’ social sciences and a large section of the ‘theoretical’ social sciences. The first part of this book develops this idea by returning to Popper’s texts. This book calls for both a reformulation of Situational Analysis and a clarification of the status and role of Popper’s ‘Rationality Principle’. This book also develops Situational Analysis by addressing two aspects of the Problem-Situation facing individual actors that are only sketched out in Popper’s work: institutions and expectations. The second part of this book utilizes the reformulated version of Situational Analysis to shed light on the core methodological differences across some of the most widespread approaches in contemporary economics and sociology. In particular, by showing that many of these approaches are variants of the reformulated version of Situational Analysis presented in the first part of this book, this book argues that apparent methodological differences across these approaches may be reinterpreted as differences in the way social scientists reconstruct the Problem-Situation facing individual actors. This book will be vital reading for academic economists, sociologists, philosophers of science, and other social scientists interested in methodology.

Are they spies? or not?

Reformation of Econometrics is a sequel to The Formation of Econometrics: A Historical Perspective (1993, OUP) which traces the formation of econometric theory during the period 1930-1960. This book provides an account of the advances in the field of econometrics since the 1970s. Based on original research, it focuses on the reformists' movement and schools of thought and practices that attempted a paradigm shift in econometrics in the 1970s and 1980s. It describes the formation and consolidation of the Cowles Commission (CC) paradigm and traces and analyses the three major methodological attempts to resolve problems involved in model choice and specification of the CC paradigm. These attempts have reoriented the focus of econometric research from internal questions (how to optimally estimate a priori given structural parameters) to external questions (how to choose, design, and specify models). It also examines various modelling issues and problems through two case studies - modelling the Phillips curve and business cycles. The third part of the book delves into the development of three key aspects of model specification in detail - structural parameters, error terms, and model selection and design procedures. The final chapter uses citation analyses to study the impact of the CC paradigm over the span of three and half decades (1970-2005). The citation statistics show that the impact has remained extensive and relatively strong in spite of certain weakening signs. It implies that the reformative attempts have fallen short of causing a paradigm shift.

The most authoritative and comprehensive synthesis of modern econometrics available Econometrics provides first-year graduate students with a thoroughly modern introduction to the subject, covering all the standard material necessary for understanding the principal techniques of econometrics, from ordinary least squares through cointegration. The book is distinctive in developing both time-series and cross-section analysis fully, giving readers a unified framework for understanding and integrating results. Econometrics covers all the important topics in a succinct manner. All the estimation techniques that could possibly be taught in a first-year graduate course, except maximum likelihood, are treated as special cases of GMM (generalized methods of moments). Maximum likelihood estimators for a variety of models, such as probit and tobit, are collected in a separate chapter. This arrangement enables students to learn various estimation techniques in an efficient way. Virtually all the chapters include empirical applications drawn from labor economics, industrial organization, domestic and international finance, and macroeconomics. These empirical exercises provide students with hands-on experience applying the techniques covered. The exposition is rigorous yet accessible, requiring a working knowledge of very basic linear algebra and probability theory. All the results are stated as propositions so that students can see the points of the discussion and also the conditions under which those results hold. Most propositions are proved in the text. For students who intend to write a thesis on applied topics, the empirical applications in Econometrics are an excellent way to learn how to conduct empirical research. For theoretically inclined students, the no-compromise treatment of basic techniques is an ideal preparation for more advanced theory courses.

This revised and updated edition of A Guide to Modern Econometrics continues to explore a wide range of topics in modern econometrics by focusing on what is important for doing and understanding empirical work. It serves as a guide to alternative techniques with the emphasis on the intuition behind the approaches and their practical relevance. New material includes Monte Carlo studies, weak instruments, nonstationary panels, count data, duration models and the estimation of treatment effects. Features of this book include: Coverage of a wide range of topics, including time series analysis, cointegration, limited dependent variables, panel data analysis and the generalized method of moments Empirical examples drawn from a wide variety of fields including labour economics, finance, international economics, environmental economics and macroeconomics. End-of-chapter exercises review key concepts in light of empirical examples.

Imad Moosa challenges convention with this comprehensive and compelling critique of econometrics, condemning the common practices of misapplied statistical methods in both economics and finance.

Summarizes developments and techniques in the field. It highlights areas such as sample surveys, nonparametic analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, and engineering.

This textbook offers a comprehensive introduction to panel data econometrics, an area that has enjoyed considerable growth over the last two decades. Micro and Macro panels are becoming increasingly available, and methods for dealing with these types of data are in high demand among practitioners. Software programs have fostered this growth, including freely available programs in R and numerous user-written programs in both Stata and EViews. Written by one of the world’s leading researchers and authors in the field, Econometric Analysis of Panel Data has established itself as the leading textbook for graduate and postgraduate courses on panel data. It provides up-to-date coverage of basic panel data techniques, illustrated with real economic applications and datasets, which are available at the book’s website on springer.com. This new sixth edition has been fully revised and updated, and includes new material on dynamic panels, limited dependent variables and nonstationary panels, as well as spatial panel data. The author also provides empirical illustrations and examples using Stata and EViews. “This is a definitive book written by one of the architects of modern, panel data econometrics. It provides both a practical introduction to the subject matter, as well as a thorough discussion of the underlying statistical principles without taxing the reader too greatly." Professor Kajal Lahiri, State University of New York, Albany, USA. "This book is the most comprehensive work available on panel data. It is written by one of the leading contributors to the field, and is notable for its encyclopaedic coverage and its clarity of exposition. It is useful to theorists and to people doing applied work using panel data. It is valuable as a text for a course in panel data, as a supplementary text for more general courses in econometrics, and as a reference." Professor Peter Schmidt, Michigan State University, USA. “Panel data econometrics is in its ascendancy, combining the power of cross section averaging with all the subtleties of temporal and spatial dependence. Badi Baltagi provides a remarkable roadmap of this fascinating interface of econometric method, enticing the novitiate with technical gentleness, the expert with comprehensive coverage and the practitioner with many empirical applications.” Professor Peter C. B. Phillips, Cowles Foundation, Yale University, USA.

Written by one of the world's leading researchers and writers in the field, Econometric Analysis of Panel Data has become established as the leading textbook for postgraduate courses in panel data. This new edition reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. Featuring the most recent empirical examples from panel data literature, data sets are also provided as well as the programs to implement the estimation and testing procedures described in the book. These programs will be made available via an accompanying website which will also contain solutions to end of chapter exercises that will appear in the book. The text has been fully updated with new material on dynamic panel data models and recent results on non-linear panel models and in particular work on limited dependent variables panel data models.