This is the first of a two-volume set of articles reflecting the current state of research in theoretical and applied econometrics. The topics covered include time series methods, semiparametric methods, seasonality, financial economics, model solution techniques, economic development, and labour economics. All the contributions were commissioned to be presented at the plenary sessions of the Sixth World Congress of the Econometric Society in Barcelona.

The contents of this volume are drawn from the seventh International Symposium in Economic Theory and Econometrics, and represent recent advances in the development of concepts and methods in political economy. Contributors include leading practitioners working on formal, applied, and historical approaches to the subject. The collection will interest scholars in the fields of political science and political sociology no less than economics. Part I outlines relevant concepts in political economy, including implementation, community, ideology, and institutions. Part II covers theory and applications of the spatial model of voting. Part III considers the different characteristics that govern the behaviour of institutions, while Part IV analyses competition between political representatives. Part V is concerned with the way in which government acquires information held by voters or advisors, and Part VI addresses government choice on monetary policy and taxation.

The contents of this volume are drawn from the seventh International Symposium in Economic Theory and Econometrics, and represent recent advances in the development of concepts and methods in political economy. Contributors include leading practitioners working on formal, applied, and historical approaches to the subject. The collection will interest scholars in the fields of political science and political sociology no less than economics. Section 1 investigates models of voting and representation, section 2 explores dimensions of political institutions, section 3 covers strategic aspects of competition, and section 4 examines key aspects of government behavior.

Two-sided matching provides a model of search processes such as those between firms and workers in labor markets or between buyers and sellers in auctions. This book gives a comprehensive account of recent results concerning the game-theoretic analysis of two-sided matching. The focus of the book is on the stability of outcomes, on the incentives that different rules of organization give to agents, and on the constraints that these incentives impose on the ways such markets can be organized. The results for this wide range of related models and matching situations help clarify which conclusions depend on particular modeling assumptions and market conditions, and which are robust over a wide range of conditions.

This book presents statistical methods for analysis of the duration of events. The primary focus is on models for single-spell data, events in which individual agents are observed for a single duration. Some attention is also given to multiple-spell data. The first part of the book covers model specification, including both structural and reduced form models and models with and without neglected heterogeneity. The book next deals with likelihood based inference about such models, with sections on full and semiparametric specification. A final section treats graphical and numerical methods of specification testing. This is the first published exposition of current econometric methods for the study of duration data.

Applied Nonparametric Regression brings together in one place the techniques for regression curve smoothing involving more than one variable. The computer and the development of interactive graphics programs has made curve estimation popular. This volume focuses on the applications and practical problems of two central aspects of curve smoothing: the choice of smoothing parameters and the construction of confidence bounds. The methods covered in this text have numerous applications in many areas using statistical analysis. Examples are drawn from economics--such as the estimation of Engel curves--as well as other disciplines including medicine and engineering. For practical applications of these methods a computing environment for exploratory Regression--XploRe--is described.

The contents of this volume comprise the proceedings of the conference, "Equilibrium theory and applications." Some of the recent developments in general equilibrium theory in the perspective of actual and potential applications are presented. The conference was organized in honor of Jacques Drèze on the occasion of his sixtieth birthday. Held at C.O.R.E., it was also the unanimous recognition, stressed by Gérard Debreu in his Address, of his role as "the architect and builder" of the Center for Operations Research and Econometrics. An introductory address by Gérard Debreu comprises Part 1 of the volume. The rest of the volume is divided into four parts spanning the scope of the conference. Part 2 is on incomplete markets, increasing returns, and information, Part 3 on equilibrium and dynamices, Part 4 on employment, imperfect competition, and macroeconomics, and Part 5 on applied general equilibrium models.

This collection of papers delivered at the Fifth International Symposium in Economic Theory and Econometrics in 1988 is devoted to the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data. Particularly in highly non-linear models, empirical results are very sensitive to the choice of the parametric form of the distribution of the observable variables, and often nonparametric and semiparametric models are a preferable alternative. Methods and applications that do not require string parametric assumptions for their validity, that are based on kernels and on series expansions, and methods for independent and dependent observations are investigated and developed in these essays by renowned econometricians.

This collection of papers delivered at the fifth international Symposium in Economic Theory and Econometrics in 1988 is devoted to recent advances in the estimation and testing of models that impose relatively weak restrictions on the stochastic behavior of data. Particularly in highly nonlinear models, empirical results are very sensitive to the choice of the parametric form of the distribution of the observable variables, and often nonparametric and semiparametric models are a preferable alternative. Methods and applications that do not require strong parametric assumptions for their validity, that are based on kernels and on series expansions, and methods for independent and dependent observations, are investigated and developed in these essays by renowned econometricians.

This book presents estimates of the sources of economic growth in Canada. The experimental measures account for the reproducibility of capital inputs in an input-output framework and show that advances in technology are more important for economic growth than previously estimated. Traditional measures of multifactor productivity advance are also presented. Extensive comparisons relate the two approaches to each change and labour productivity. The book will be of interest to macroeconomists studying economic growth, capital accumulation, technical advance, growth accounting, and input-output analysis.

Recent advances in establishing the nature and scope of estimators in econometrics have shed more light on the importance of instrumental variables. In this book, the authors argue that such methods may be regarded as a strong organizing principle for a wide variety of estimation and hypothesis testing problems in econometrics and statistics. In support of this claim they present and develop the methodology of instrumental variables in its most general and explanatory form. They show, for instance, that techniques commonly used to handle simultaneity and related problems can be reduced to one of two generic variables of instrumental variables estimators, allowing them to explore further the conditions under which different proposed estimators are efficient.

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method's flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software's SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the "how-tos" of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.

The advent of electronic computing permits the empirical analysis of economic models of far greater subtlety and rigour than before, when many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more intricate models is usually based on the method of Maximum Likelihood, which is a well-established branch of mathematical statistics. Its use in econometrics has led to the development of a number of special techniques; the specific conditions of econometric research moreover demand certain changes in the interpretation of the basic argument. This book is a self-contained introduction to this field. It consists of three parts. The first deals with general features of Maximum Likelihood methods; the second with linear and nonlinear regression; and the third with discrete choice and related micro-economic models. Readers should already be familiar with elementary statistical theory, with applied econometric research papers, or with the literature on the mathematical basis of Maximum Likelihood theory. They can also try their hand at some advanced econometric research of their own.

The most common mode of analysis in economic theory is to assume equilibrium. Yet, without a proper theory of how economies behave in disequilibrium, there is no foundation for such a practice. The necessary step in proposing a foundation is the formulation of a theory of stability, and in this 1984 book, Professor Fisher is primarily concerned with this subject, although disequilibrium behavior itself is analyzed. The author first undertakes a review of the existing literature on the stability of general equilibrium. He then proposes a more satisfactory general model in which agents realize their state of disequilibrium and act on arbitrage opportunities. The interrelated topics of the role of money, the nature of quantity constraints, and the optimal behaviour of arbitraging agents are extensively treated.

This book extrapolates on the Nash (1950) treatment of the bargaining problem to consider the situation where the number of bargainers may vary. The authors formulate axioms to specify how solutions should respond to such changes, and provide new characterizations of all the major solutions as well as the generalizations of these solutions.

Composed in honor of the 65th birthday of Lloyd Shapley, this volume makes accessible the large body of work that has grown out of Shapley's seminal 1953 paper. Each of the twenty essays concerns some aspect of the Shapley value.

The Regression Discontinuity (RD) design is one of the most popular and credible research designs for program evaluation and causal inference. This volume 38 of Advances in Econometrics collects twelve innovative and thought-provoking contributions to the RD literature, covering a wide range of methodological and practical topics. Some chapters touch on foundational methodological issues such as identification, interpretation, implementation, falsification testing, estimation and inference, while others focus on more recent and related topics such as identification and interpretation in a discontinuity-in-density framework, empirical structural estimation, comparative RD methods, and extrapolation. These chapters not only give new insights for current methodological and empirical research, but also provide new bases and frameworks for future work in this area. This volume contributes to the rapidly expanding RD literature by bringing together theoretical and applied econometricians, statisticians, and social, behavioural and biomedical scientists, in the hope that these interactions will further spark innovative practical developments in this important and active research area.

We live in a time of economic virtualism, whereby our lives are made to conform to the virtual reality of economic thought. Globalization, transnational capitalism, structural adjustment programmes and the decay of welfare are all signs of the growing power of economics, one of the most potent forces of recent decades. In the last thirty years, economics has ceased to be just an academic discipline concerned with the study of economy, and has come to be the only legitimate way to think about all aspects of society and how we order our lives. Economic models are no longer measured against the world they seek to describe, but instead the world is measured against them, found wanting and made to conform.This profound and dangerous change in the power of abstract economics to shape the lives of people in rich and poor countries alike is the subject of this interdisciplinary study. Contributors show how economics has come to portray a virtual reality -- a world that seems real but is merely a reflection of a neo-classical model -- and how governments, the World Bank and the IMF combine to stamp the world with a virtual image that condemns as irrational our local social and cultural arrangements. Further, it is argued that virtualism represents the worrying emergence of new forms of abstraction in the political economy, of which economics is just one example.

These twenty papers were selected by the author, who received the Nobel Prize in 1983. The book includes a major introduction by Werner Hildenbrand, who assesses Professor Debreu's contribution to economic theory and explains the part played by these papers in the development of the subject.

Getting accurate data on less developed countries has created great problems for studying these areas. Yet until recently students of development economics have relied on standard econometrics texts, which assume a Western context. Econometrics and Data Analysis for Developing Countries solves this problem. It will be essential reading for all advanced students of development economics.

Get up to speed on the application of machine learning approaches in macroeconomic research. This book brings together economics and data science. Author Tshepo Chris Nokeri begins by introducing you to covariance analysis, correlation analysis, cross-validation, hyperparameter optimization, regression analysis, and residual analysis. In addition, he presents an approach to contend with multi-collinearity. He then debunks a time series model recognized as the additive model. He reveals a technique for binarizing an economic feature to perform classification analysis using logistic regression. He brings in the Hidden Markov Model, used to discover hidden patterns and growth in the world economy. The author demonstrates unsupervised machine learning techniques such as principal component analysis and cluster analysis. Key deep learning concepts and ways of structuring artificial neural networks are explored along with training them and assessing their performance. The Monte Carlo simulation technique is applied to stimulate the purchasing power of money in an economy. Lastly, the Structural Equation Model (SEM) is considered to integrate correlation analysis, factor analysis, multivariate analysis, causal analysis, and path analysis. After reading this book, you should be able to recognize the connection between econometrics and data science. You will know how to apply a machine learning approach to modeling complex economic problems and others beyond this book. You will know how to circumvent and enhance model performance, together with the practical implications of a machine learning approach in econometrics, and you will be able to deal with pressing economic problems. What You Will Learn Examine complex, multivariate, linear-causal structures through the path and structural analysis technique, including non-linearity and hidden states Be familiar with practical applications of machine learning and deep learning in econometrics Understand theoretical framework and hypothesis development, and techniques for selecting appropriate models Develop, test, validate, and improve key supervised (i.e., regression and classification) and unsupervised (i.e., dimension reduction and cluster analysis) machine learning models, alongside neural networks, Markov, and SEM models Represent and interpret data and models Who This Book Is For Beginning and intermediate data scientists, economists, machine learning engineers, statisticians, and business executives

This book addresses one of the major theoretical issues that underlies, implicitly or explicitly, some recurrent controversies in macroeconomics - namely, whether a competitive monetary economy has built-in mechanisms that are strong enough to remove excess demands and supplies on all markets, through an automatic adjustment of the price system. Jean-Michel Grandmont sheds light on this complex subject by using the analytical techniques of general equilibrium theory alongside the methods of monetary analysis. The book warns against the indiscriminate use of the rational expectations hypothesis when approaching this topic, and conversely stresses the common-sense observation that short-run learning processes are among the most important characteristics of economic agents. Grandmont argues that such processes are deserving of careful theoretical study, and the result is a clear and rigorous analysis of all the issues involved.

This volume includes papers delivered at the Fourth World Congress of the Econometric Society. It will interest economic theorists and econometricians working in universities, government, and business and financial institutions.

The responses to questions such as 'What is the explanation for changes in the unemployment rate?' frequently involve the presentation of a mathematical relationship, a function that relates one set of variables to another set of variables. It should become apparent that as one's understanding of functions, relationships, and variables becomes richer and more detailed, one's ability to provide explanations for economic phenomena becomes stronger and more sophisticated. The author believes that a student's intuition should be involved in the study of mathematical techniques in economics and that this intuition develops not so much from solving problems as from visualizing them. Thus the author avoids the definition-theorem-proof style in favor of a structure that encourages the student's geometric intuition of the mathematical results. The presentation of real numbers and functions emphasizes the notion of linearity. Consequently, linear algebra and matrix analysis are integrated into the presentation of the calculus of functions of several variables. The book concludes with a chapter on classical programming, and one on nonlinear and linear programming. This textbook will be of particular interest and value to graduate and senior undergraduate students of economics, because each major mathematical idea is related to an example of its use in economics.

The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some relevant theory and introductory concepts are presented using practical examples and two running case studies. The book also describes in detail how to perform health economic evaluations using the R package BCEA (Bayesian Cost-Effectiveness Analysis). BCEA can be used to post-process the results of a Bayesian cost-effectiveness model and perform advanced analyses producing standardised and highly customisable outputs. It presents all the features of the package, including its many functions and their practical application, as well as its user-friendly web interface. The book is a valuable resource for statisticians and practitioners working in the field of health economics wanting to simplify and standardise their workflow, for example in the preparation of dossiers in support of marketing authorisation, or academic and scientific publications.