This text introduces students progressively to various aspects of qualitative models and assumes a knowledge of basic principles of statistics and econometrics. After the introduction, Chapters 2 through 6 present models with endogenous qualitative variables, examining dichotomous models, model specification, estimation methods, descriptive usage, and qualitative panel data. The final two chapters describe models that explain variables assumed by discrete or continuous positive variables.

Bayesian Econometrics introduces the reader to the use of Bayesian methods in the field of econometrics at the advanced undergraduate or graduate level. The book is self-contained and does not require previous training in econometrics. The focus is on models used by applied economists and the computational techniques necessary to implement Bayesian methods when doing empirical work. It includes numerous numerical examples and topics covered in the book include:

• the regression model (and variants applicable for use with panel data
• time series models
• models for qualitative or censored data
• nonparametric methods and Bayesian model averaging.

A website containing computer programs and data sets to help the student develop the computational skills of modern Bayesian econometrics can be found at: www.wiley.co.uk/koopbayesian

The editors bring together examples of microsimulation modeling that are at the frontiers of developments in the field, either because they extend the range of techniques available to modelers, or because they demonstrate new applications for established methods. This volume represents the state of the art with chapters on the use of microsimulation for comparative policy research and for challenging conventional assumptions, combining microsimulation with other types of economic models and the much-neglected subjects of model alignment and validation. Data and case studies are taken from regions including Asia-Pacific, Europe and North America.

Differential geometry has become a standard tool in the analysis of statistical models, offering a deeper appreciation of existing methodologies and highlighting the issues that can be hidden in an algebraic development of a problem. This volume is the first to apply these techniques to econometrics. An introductory chapter provides a brief tutorial for those unfamiliar with the tools of differential geometry. The following chapters offer applications of geometric methods to practical solutions and offer insight into problems of econometric inference.

The theory of competition has held a central place in economic analysis since the time of Adam Smith. This book, written by one of the most distinguished of contemporary economic theorists, reports on a major research program to provide strategic foundations for the theory of competition. Making use of insights from game theory, search theory and bargaining theory, the author develops a model to explain what actually goes on in markets and how a competitive general equilibrium is achieved. Essential reading for graduate courses in game theory and general equilibrium.

Gary Madden was a renaissance man with respect to the nexus between information and communications technology (ICT) and economics. He contributed to a variety of fields in ICT: applied econometrics, forecasting, internet governance and policy. This series of essays, two of which were co-authored by Professor Madden prior to his untimely death, cover the range of his research interests. While the essays focus on a number of ICT issues, they are on the frontier of research in the sector. Gerard Faulhaber provides a broad overview of how we have reached the digital age and its implications. The applied econometric section brings the latest research in the area, for example Lester Taylor illustrates how own-price, cross-price and income elasticities can be calculated from survey data and translated into real income effects. The forecasting section ranges from forecasting online political participation to broadband's impact on economic growth. The final section covers aspects of governance and regulation of the ICT sector.

This is the most up-to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed nonlinear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. It uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.

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

Nonlinear Econometric Modeling in Time Series Analysis presents recent developments in this important area of research. This is the first volume to focus on the more recent literature on nonlinear time series. Specific topics covered with respect to nonlinearity include cointegration tests, risk-related asymmetries, structural breaks and outliers, Bayesian analysis with a threshold, consistency and asymptotic normality, asymptotic inference, and error-correction models.

This important collection brings together leading econometricians to discuss recent advances in the areas of the econometrics of panel data, limited dependent variable models and limited dependent variable models with panel data. The contributors focus on the issues of simplifying complex real world phenomena into easily generalizable inferences from individual outcomes. As the contributions of G. S. Maddala in the fields of limited dependent variables and panel data have been particularly influential, it is a fitting tribute that this volume is dedicated to him.

This book systematically and thoroughly covers the vast literature on the nonparametric and semiparametric statistics and econometrics that has evolved over the last five decades. Within this framework this is the first book to discuss the principles of the nonparametric approach to the topics covered in a first year graduate course in econometrics, e.g. regression function, heteroskedasticity, simultaneous equations models, logit-probit and censored models. Nonparametric and semiparametric methods potentially offer considerable reward to applied researchers, owing to the methods' ability to adapt to many unknown features of the data. Professors Pagan and Ullah provide intuitive explanations of difficult concepts, heuristic developments of theory, and empirical examples emphasizing the usefulness of the modern nonparametric approach. The book should provide a new perspective on teaching and research in applied subjects in general and econometrics and statistics in particular.

This book systematically and thoroughly covers a vast literature on the nonparametric and semiparametric statistics and econometrics that has evolved over the past five decades. Within this framework, this is the first book to discuss the principles of the nonparametric approach to the topics covered in a first year graduate course in econometrics, e.g., regression function, heteroskedasticity, simultaneous equations models, logit-probit and censored models. Professors Pagan and Ullah provide intuitive explanations of difficult concepts, heuristic developments of theory, and empirical examples emphasizing the usefulness of modern nonparametric approach. The book should provide a new perspective on teaching and research in applied subjects in general and econometrics and statistics in particular.

This book presents the state of the art in extreme value theory, with a collection of articles related to a seminal paper on the bivariate extreme value distribution written by Professor Masaaki Sibuya in 1960, demonstrating various developments of the original idea over the last half-century. Written by active researchers, the unique combination of articles allows readers to gain a sense of the excellence of the field, ranging from theory to practice, and the tradition of theoretical developments motivated by practically important issues such as tsunamis and financial crises. The contributions discuss a range of topics, including the parameter estimation of the generalized beta distribution, resampling with the empirical beta copula, and regression analysis on imbalanced binary data, as well as the semiparametric estimation of the upper bound of extrema, the long-term analysis of extreme precipitation over Japanese river basins, and various rules of thumb in hydrology.

This report is a partial result of the China's Quarterly Macroeconomic Model (CQMM), a project developed and maintained by the Center for Macroeconomic Research (CMR) at Xiamen University. The CMR, one of the Key Research Institutes of Humanities and Social Sciences sponsored by the Ministry of Education of China, has been focusing on China's economic forecast and macroeconomic policy analysis, and it started to develop the CQMM for purpose of short-term forecasting, policy analysis, and simulation in 2005.Based on the CQMM, the CMR and its partners hold press conferences to release forecasts for China' major macroeconomic variables. Since July, 2006, twenty-six quarterly reports on China's macroeconomic outlook have been presented and thirteen annual reports have been published. This 27th quarterly report has been presented at the Forum on China's Macroeconomic Prospects and Press Conference of the CQMM at Xiamen University Malaysia on October 25, 2019. This conference was jointly held by Xiamen University and Economic Information Daily of Xinhua News Agency.

This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.

This proceedings volume presents new methods and applications in applied economics with special interest in advanced cross-section data estimation methodology. Featuring select contributions from the 2019 International Conference on Applied Economics (ICOAE 2019) held in Milan, Italy, this book explores areas such as applied macroeconomics, applied microeconomics, applied financial economics, applied international economics, applied agricultural economics, applied marketing and applied managerial economics. International Conference on Applied Economics (ICOAE) is an annual conference that started in 2008, designed to bring together economists from different fields of applied economic research, in order to share methods and ideas. Applied economics is a rapidly growing field of economics that combines economic theory with econometrics, to analyze economic problems of the real world, usually with economic policy interest. In addition, there is growing interest in the field of applied economics for cross-section data estimation methods, tests and techniques. This volume makes a contribution in the field of applied economic research by presenting the most current research. Featuring country specific studies, this book is of interest to academics, students, researchers, practitioners, and policy makers in applied economics, econometrics and economic policy.

This book contributes substantively to the current state of the art of macroeconomic modeling by providing a method for modeling large collections of heterogeneous agents subject to nonpairwise externality called field effects, i.e. feedback of aggregate effects on individual agents or agents using state-dependent strategies. Adopting a level of microeconomic description that keeps track of compositions of fractions of agents by "types" or "strategies", time evolution of the microeconomic states is described by (backward) Chapman-Kolmogorov equations.

This second edition of Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is organized into five parts. Chapters 2, 3, and 5 of Part I cover concisely many of the ideas discussed in Rosenbaum's Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates, and includes an updated chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV is new to this edition; it discusses evidence factors and the computerized construction of more than one comparison group. Part V discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher's striking advice for observational studies: "make your theories elaborate." This new edition features updated exploration of causal influence, with four new chapters, a new R package DOS2 designed as a companion for the book, and discussion of several of the latest matching packages for R. In particular, DOS2 allows readers to reproduce many analyses from Design of Observational Studies.

This Brief discusses impacts of the COVID-19 pandemic on the Portuguese tourism sector. Taking into account real-world conditions and the importance of the tourism sector for the Portuguese economy, this book highlights the economic contexts of tourism in Portugal at the regional and municipal levels, discussing pre-pandemic economic frameworks and projecting potential implications for the future. Using data provided by Statistics Portugal, the Brief performs econometric analysis on three cases: new paradigms for overnight stays and guests, changes in tourism revenues and prospective alternatives, and a comparison of effects on changes in number of guests and overnight stays at the regional level. Providing cutting edge analysis of a dynamic global situation, this Brief will be useful for researchers interested in tourism economics and European economics as well as policymakers and industry professionals.

This book explores new topics in modern research on empirical corporate finance and applied accounting, especially the econometric analysis of microdata. Dubbed "financial microeconometrics" by the author, this concept unites both methodological and applied approaches. The book examines how quantitative methods can be applied in corporate finance and accounting research in order to predict companies getting into financial distress. Presented in a clear and straightforward manner, it also suggests methods for linking corporate governance to financial performance, and discusses what the determinants of accounting disclosures are. Exploring these questions by way of numerous practical examples, this book is intended for researchers, practitioners and students who are not yet familiar with the variety of approaches available for data analysis and microeconometrics. "This book on financial microeconometrics is an excellent starting point for research in corporate finance and accounting. In my view, the text is positioned between a narrative and a scientific treatise. It is based on a vast amount of literature but is not overloaded with formulae. My appreciation of financial microeconometrics has very much increased. The book is well organized and properly written. I enjoyed reading it." Wolfgang Marty, Senior Investment Strategist, AgaNola AG

In this compelling 1995 book, David Hendry and Mary Morgan bring together the classic papers of the pioneer econometricians. Together, these papers form the foundations of econometric thought. They are essential reading for anyone seeking to understand the aims, method and methodology of econometrics and the development of this statistical approach in economics. However, because they are technically straightforward, the book is also accessible to students and non-specialists. An editorial commentary places the readings in their historical context and indicates the continuing relevance of these early, yet highly sophisticated, works for current econometric analysis. While this book provides a companion volume to Mary Morgan's acclaimed The History of Econometric Ideas, the editors' commentary both adds to that earlier volume and also provides a stand-alone and synthetic account of the development of econometrics.

Econometrics can at first appear a highly technical subject, but it can also equip the practitioner with a useful skillset of smart ways to formulate research questions and collect data. Enjoyable Econometrics applies econometric methods to a variety of unusual and engaging research questions, often beyond the realm of economics, demonstrating the great potential of using such methods to understand a wide range of phenomena. Unlike the typical textbook approach, Enjoyable Econometrics follows in the footsteps of Freakonomics by posing interesting questions first before introducing the methodology to find the answers. Therefore, rather than equation-heavy sections based around complex methodologies, the reader is presented with chapters on 'Money' and 'Fashion, Art and Music'. Franses writes in a way that will enthuse and motivate the economics student embarking upon the essential study of econometrics. Indeed, the book shows that econometric methods can be applied to almost anything.

Nonlinear Dynamics and Economics, first published in 1997, presents developments in nonlinear economic dynamics along with related research from associated fields, including mathematics, statistics, biology, and physics. Specific areas covered include instability in economic theory, nonlinearity in financial markets, tests for nonlinearity and chaos, frequency domain methods, nonlinear business cycles, and nonlinear prediction and forecasting. This volume comprises the tenth in the International Symposia in Economic Theory and Econometrics series under the general editorship of William Barnett. This proceedings volume includes revisions of the most important papers presented at a conference held at the European University Institute in Florence on July 6-17, 1992, along with revisions of the related, invited papers presented at the annual meetings of the American Statistical Association held in San Francisco on August 8-12, 1993.

Based on economic knowledge and logical reasoning, this book proposes a solution to economic recessions and offers a route for societal change to end capitalism. The author starts with a brief review of the history of economics, and then questions and rejects the trend of recent decades that has seen econometrics replace economic theory. By reviewing the different schools of economic thought and by examining the limitations of existing theories to business cycles and economic growth, the author forms a new theory to explain cyclic economic growth. According to this theory, economic recessions result from innovation scarcity, which in turn results from the flawed design of the patent system. The author suggests a new design for the patent system and envisions that the new design would bring about large economic and societal changes. Under this new patent system, the synergy of the patent and capital markets would ensure that economic recessions could be avoided and that the economy would grow at the highest speed.

In this book Herman Bierens provides a mathematically rigorous treatment of a number of timely topics in advanced econometrics. His subjects include nonlinear estimation, maximum likelihood theory, ARMA and ARMAX models, unit roots and cointegration, and nonparametric regression, together with an extensive and thorough treatment of the necessary probability theory. Professor Bierens' study is uniquely self-contained, providing the reader with a selection of the latest developments in econometric theory, along with the required introductory material on each topic. It will be of great use to graduate students of econometrics and statistics, and is particularly suitable for self-tuition.