This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

PREFACE TO THE COLLECTION PREAMBLE The editors are pleased to present a selection of Henri Theil's contributions to economics and econometrics in three volumes. In Volume I we have provided an overview of Theil's contributions, a brief biography, an annotated bibliography of his research, and a selection of published and unpublished articles and chapters in books dealing with topics in econometrics. Volume II contains Theil's contributions to demand analysis and information theory. Volume III includes Theil's contributions in economic policy and forecasting, and management science. The selection of articles is intended to provide examples of Theil's many seminal and path breaking contributions to economics in such areas as econometrics, statistics, demand analysis, information theory, economic policy analysis, aggregation theory, forecasting, index numbers, management science, sociology, operations research, higher education and much more. The collection is also intended to serve as a tribute to him on the occasion of his 67th birthday.! These three volumes also highlight some of Theil's contributions and service to the profession as a leader, advisor, administrator, teacher, and researcher. Theil's contributions, which encompass many disciplines, have been extensively cited both in scientific and professional journals. These citations often place Theil among the top 10 researchers (ranked according to number of times cited) in the world in various disciplines.

Provides a comprehensive and accessible introduction to general insurance pricing, based on the author’s many years of experience as both a teacher and practitioner. Suitable for students taking a course in general insurance pricing, notably if they are studying to become an actuary through the UK Institute of Actuaries exams. No other title quite like this on the market that is perfect for teaching/study, and is also an excellent guide for practitioners.

These three volumes contain an account of Professor Henri Theil's distinguished career as a leader, advisor, administrator, teacher, and researcher in economics and econometrics. The books also contain a selection of his contributions in many areas, such as econometrics, demand analysis, information theory, forecasting, statistics, economic policy analysis and management science. To date he has contributed over 250 articles in refereed journals and chapters in books, and 15 books, three of which became citation classics. His books and articles have appeared in (and have been translated into) many languages, such as Polish, Russian, Dutch, English, French, German, Hungarian, Italian and Japanese. This collection provides excellent reference material to researchers and graduate students working in a variety of disciplines, such as econometrics, economics, management science, operations research, and statistics. Moreover, Professor Theil's career serves as a role model for younger generations of scholars, both in terms of his approach to research and his commitment to his profession. Professor Theil's distinguished career as an academic began in 1953 when he was appointed Professor of Econometrics at the Netherlands School of Economics in Rotterdam (now Erasmus University). Three years later he founded the Econometric Institute in Rotterdam and served as its first director until 1966, when he accepted a joint appointment at the Graduate School of Business and Department of Economics, University of Chicago, U.S.A. In 1981, Theil was appointed to the McKethan-Matherly Eminent Chair at the Graduate School of Business Administration of the University of Florida in Gainesville. Theil hasreceived many international honours including four honorary degrees.

Econometrics of Health Care - which we have sometimes called 'medico metrics' - is a field in full expansion. The reasons are numerous: our knowl edge of quantitative relations in the field of health econometrics is far from being perfect, a large number of analytical difficulties - combining medical (latent factors, e. g. ) and economic facts (spatial behaviour, e. g. ) are faced by the research worker, medical and pharmaceutical techniques change rapidly, medical costs rocket more than proportionally with available resources, of being tightened. medical budgets are in the process So it is not surprising that the practice of 'hygieconometrics' - to produce a neologism - is more and more included in the programmes of econometri cians. The Applied Econometrics Association has devoted to the topic two symposia in less than three years (Lyons, February 1983; Rotterdam, December 1985), without experiencing any difficulties in getting valuable papers: on econometrics of risks and medical insurance, on the measurement of health status and of efficiency of medical techniques, on general models allowing simulation. These were the themes for the second meeting, but other aspects of medical-economic problems had presented themselves already to the analyst: medical decision making and its consequences, the behaviour of the actors - patients and physicians -, regional medicometrics and what not: some of them have been covered by the first meeting. Finally, in July 1988 took place in Lyons the Fourth International Conference on System Science in Health Care; it should not be astonishing ."

Econometric Business Cycle Research deals with econometric business cycle research (EBCR), a term introduced by the Nobel-laureate Jan Tinbergen for his econometric method of testing (economic) business cycle theories. EBCR combines economic theory and measurement in the study of business cycles, i.e., ups and downs in overall economic activity. We assess four methods of EBCR: business cycle indicators, simultaneous equations models, vector autoregressive systems and real business indicators. After a sketch of the history of the methods, we investigate whether the methods meet the goals of EBCR: the three traditional ones, description, forecasting and policy evaluation, and the one Tinbergen introduced, the implementation-testing of business cycles. The first three EBCR methods are illustrated for the Netherlands, a typical example of a small, open economy. The main conclusion of the book is that simultaneous equation models are the best vehicle for EBCR, if all its goals are to be attained simultaneously. This conclusion is based on a fairly detailed assessment of the methods and is not over-turned in the empirical illustrations. The main conclusion does not imply the end of other EBCR methods. Not all goals have to be met with a single vehicle, other methods might serve the purpose equally well - or even better. For example, if one is interested in business cycle forecasts, one might prefer a business cycle indicator or vector autoregressive system. A second conclusion is that many ideas/concepts that play an important role in current discussions about econometric methodology in general and EBCR in particular, were put forward in the 1930s and 1940s. A third conclusion is that it is difficult, if not impossible, to compare the outcomes of RBC models to outcomes of the other three methods, because RBC modellers are not interested in modelling business cycles on an observation-per-observation basis. A more general conclusion in this respect is that methods should adopt the same concept of business cycles to make them comparable.

o. Guvenen, University of Paris IX-Dauphine The aim of this publication is to present recent developments in international com modity market model building and policy analysis. This book is based mainly on the research presented at the XlIth International Conference organised by the Applied Econometric Association (AEA) which was held at the University of Zaragoza in Spain. This conference would not have been possible with out the cooperation of the Department of Econometrics of the University of Zaragoza and its Chairman A.A. Grasa. I would like to express my thanks to all contributors. I am grateful to J.H.P. Paelinck, J.P. Ancot, A.J. Hughes Hallett and H. Serbat for their constructive contributions and comments concerning the structure of the book. vii INTRODUCTION o. Guvenen The challenge of increasing complexity and global interdependence at the world level necessitates new modelling approaches and policy analysis at the macroeconomic level, and for commodities. The evaluation of economic modelling.follows the evolution of international economic phenomena. In that interdependent context there is a growing need for forecasting and simulation tools in the analysis of international primary com modity markets."

Use of information is basic to economic theory in two ways. As a basis for optimization, it is central to all normative hypotheses used in eco nomics, but in decision-making situations it has stochastic and evolution ary aspects that are more dynamic and hence more fundamental. This book provides an illustrative survey of the use of information in econom ics and other decision sciences. Since this area is one of the most active fields of research in modern times, it is not possible to be definitive on all aspects of the issues involved. However questions that appear to be most important in this author's view are emphasized in many cases, without drawing any definite conclusions. It is hoped that these questions would provoke new interest for those beginning researchers in the field who are currently most active. Various classifications of information structures and their relevance for optimal decision-making in a stochastic environment are analyzed in some detail. Specifically the following areas are illustrated in its analytic aspects: 1. Stochastic optimization in linear economic models, 2. Stochastic models in dynamic economics with problems of time-inc- sistency, causality and estimation, 3. Optimal output-inventory decisions in stochastic markets, 4. Minimax policies in portfolio theory, 5. Methods of stochastic control and differential games, and 6. Adaptive information structures in decision models in economics and the theory of economic policy."

This book reviews recent approaches for partial identification of average treatment effects with instrumental variables in the program evaluation literature, including Manski's bounds, bounds based on threshold crossing models, and bounds based on the Local Average Treatment Effect (LATE) framework. It compares these bounds across different sets of assumptions, surveys relevant methods to assess the validity of these assumptions, and discusses estimation and inference methods for the bounds. The book also reviews some empirical applications employing bounds in the program evaluation literature. It aims to bridge the gap between the econometric theory on which the different bounds are based and their empirical application to program evaluation.

The book is an in-depth review of the theory and empirics of the demand for money and other financial assets. The different theoretical approaches to the portfolio choice problem are described, together with an up-to-date survey of the results obtained from empirical studies of asset choice behaviour. Both single-equation studies and the more complete multi-asset portfolio models, are analysed.

This volume provides a coherent analysis of the economic, monetary and political aspects of growth dynamics in the Euro area. The different relevant aspects in this debate, presented and discussed by leading scholars and representatives of international organizations, include an assessment of the newest theoretical growth models for open economies, and empirical investigation of: the growth divergence between the US and Europe the extent to which fiscal co-ordination is desirable in a monetary union the role of product and labor market reforms the complex relationships between exchange rates and growth the contribution of monetary policy to economic growth and the prospects for economic growth in monetary unions. Although primarily focused on the Euro area, the analysis is equally relevant to all other common currency areas and will be welcomed by academics and students with an interest in European studies and financial economics, as well as policy and decision makers in international organisations, national institutions and central banks.

This volume focuses on the analysis and measurement of business cycles in Brazil, Russia, India, China and South Africa (BRICS). Divided into five parts, it begins with an overview of the main concepts and problems involved in monitoring and forecasting business cycles. Then it highlights the role of BRICS in the global economy and explores the interrelatedness of business cycles within BRICS. In turn, part two provides studies on the historical development of business cycles in the individual BRICS countries and describes the driving forces behind those cycles. Parts three and four present national business tendency surveys and composite cyclical indices for real-time monitoring and forecasting of various BRICS economies, while the final part discusses how the lessons learned in the BRICS countries can be used for the analysis of business cycles and their socio-political consequences in other emerging countries.

This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.

The present book is a collection of panel data papers, both theoretical and applied. Theoretical topics include methodology papers on panel data probit models, treatment models, error component models with an ARMA process on the time specific effects, asymptotic tests for poolability and their bootstrapped versions, confidence intervals for a doubly heteroskedastic stochastic production frontiers, estimation of semiparametric dynamic panel data models and a review of survey attrition and nonresponse in the European Community Household Panel. Applications include as different topics as e.g. the impact of uncertainty on UK investment, a Tobin-q investment model using US firm data, cost efficiency of Spanish banks, immigrant integration in Canada, the dynamics of individual health in the UK, the relation between inflation and growth among OECD and APEC countries, technical efficiency of cereal farms in England, and employment effects of education for disabled workers in Norway.

This volume is dedicated to the memory and the achievements of Professor Sir Clive Granger, economics Nobel laureate and one of the great econometricians and applied economists of the twentieth and early twenty-first centuries. It comprises contributions from leading econometricians and applied economists who knew Sir Clive and interacted with him over the years, and who wished to pay tribute to him as both a great economist and econometrician, and as a great man. This book was originally published as a special issue of Applied Financial Economics.

First published in 1987, this is an analysis of the contemporary breakdown of political and economic systems within the Eastern European communist countries. Rather than passively following the developments of this crisis, the author seeks instead to identify the reasons for failure and to examine alternative policies that offer solutions to these problems. Jan Winiecki's work offers a comparative study of the Soviet-type economies of the East with the market economies of the West; providing a cause and effect analysis of each model, with possible scenarios for their future prospects.

This book is intended for second year graduate students and professionals who have an interest in linear and nonlinear simultaneous equations mod els. It basically traces the evolution of econometrics beyond the general linear model (GLM), beginning with the general linear structural econo metric model (GLSEM) and ending with the generalized method of mo ments (GMM). Thus, it covers the identification problem (Chapter 3), maximum likelihood (ML) methods (Chapters 3 and 4), two and three stage least squares (2SLS, 3SLS) (Chapters 1 and 2), the general nonlinear model (GNLM) (Chapter 5), the general nonlinear simultaneous equations model (GNLSEM), the special ca'3e of GNLSEM with additive errors, non linear two and three stage least squares (NL2SLS, NL3SLS), the GMM for GNLSEIVl, and finally ends with a brief overview of causality and re lated issues, (Chapter 6). There is no discussion either of limited dependent variables, or of unit root related topics. It also contains a number of significant innovations. In a departure from the custom of the literature, identification and consistency for nonlinear models is handled through the Kullback information apparatus, as well as the theory of minimum contrast (MC) estimators. In fact, nearly all estimation problems handled in this volume can be approached through the theory of MC estimators. The power of this approach is demonstrated in Chapter 5, where the entire set of identification requirements for the GLSEM, in an ML context, is obtained almost effortlessly, through the apparatus of Kullback information."

This book discusses the need to carefully and prudently apply various regression techniques in order to obtain the full benefits. It also describes some of the techniques developed and used by the authors, presenting their innovative ideas regarding the formulation and estimation of regression decomposition models, hidden Markov chain, and the contribution of regressors in the set-theoretic approach, calorie poverty rate, and aggregate growth rate. Each of these techniques has applications that address a number of unanswered questions; for example, regression decomposition techniques reveal intra-household gender inequalities of consumption, intra-household allocation of resources and adult equivalent scales, while Hidden Markov chain models can forecast the results of future elections. Most of these procedures are presented using real-world data, and the techniques can be applied in other similar situations. Showing how difficult questions can be answered by developing simple models with simple interpretation of parameters, the book is a valuable resource for students and researchers in the field of model building.

It is unlikely that any frontier of economics/econometrics is being pushed faster, further than that of computational techniques. The computer has become a tool for performing as well as an environment in which to perform economics and econometrics, taking over where theory bogs down, allowing at least approximate answers to questions that defy closed mathematical or analytical solutions. Tasks may now be attempted that were hitherto beyond human potential, and all the forces available can now be marshalled efficiently, leading to the achievement of desired goals. Computational Techniques for Econometrics and Economic Analysis is a collection of recent studies which exemplify all these elements, demonstrating the power that the computer brings to the economic analysts. The book is divided into four parts: 1 -- the computer and econometric methods; 2 -- the computer and economic analysis; 3 -- computational techniques for econometrics; and 4 -- the computer and econometric studies.

A lot of economic problems can be formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories. The series is designed to bring together those mathematicians who are seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking effective mathematical tools for their research.

Three different lines of approach have contributed to the theory of optimal planning. One approach considers the problem from the view-point of a national government and its adviser, the econometrician planning speci alist. The government can, if this is thought to be desirable, stimulate investment in certain directions and discourage other economic activities. By various fiscal devices, it can influence both the total level and the distribution of investment funds over different sectors of production. Also, in many countries, a public agency plays some kind of coordinat ing role in the formulation of long-term plans for output by the enter prises sector; this may range from administrative direction in so-called centrally planned economies, to persuasion and advice in 'capitalist' economies. Accordingly, the public planner wishes to know what dis tribution of the nation's resources would be 'optimal'. This leads to the construction of various models which may be described under the general heading 'input-output type models'. This type of model has been largely developed by practitioners, among whom Sandee [B2] is probably the most outstanding and the earliest. A later, well-developed example of a model based on this approach is, for example, the Czech model by Cerny et al. [Bl]. A second approach considers the problem from the point of view of the private entrepreneur and his adviser, the manager and financial accountant.

This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.

This book consists of four parts: I. Labour demand and supply, II. Productivity slowdown and innovative activity, III. Disequilibrium and business cycle analysis, and IV. Time series analysis of output and employment. It presents a fine selection of articles in the growing field ofthe empirical analysis of output and employment fluctuations with applications in a micro-econometric or a time-series framework. The time-series literature recently has emphasized the careful testing for stationarity and nonlinearity in the data, and the importance of cointegration theory. An essential part of the papers make use of parametric and non-parametric methods developed in this literature and mostly connect their results to the hysteresis discussion about the existence of fragile equilibria. A second set of macro approaches use the disequilibrium framework that has found so much interest in Europe in recent years. The other papers use newly developed methods for microdata, especially qualitative data or limited dependent variables to study microeconomic models of behaviour that explain labour market and output decisions.

In the modern world of gigantic datasets, which scientists and practioners of all fields of learning are confronted with, the availability of robust, scalable and easy-to-use methods for pattern recognition and data mining are of paramount importance, so as to be able to cope with the avalanche of data in a meaningful way. This concise and pedagogical research monograph introduces the reader to two specific aspects - clustering techniques and dimensionality reduction - in the context of complex network analysis. The first chapter provides a short introduction into relevant graph theoretical notation; chapter 2 then reviews and compares a number of cluster definitions from different fields of science. In the subsequent chapters, a first-principles approach to graph clustering in complex networks is developed using methods from statistical physics and the reader will learn, that even today, this field significantly contributes to the understanding and resolution of the related statistical inference issues. Finally, an application chapter examines real-world networks from the economic realm to show how the network clustering process can be used to deal with large, sparse datasets where conventional analyses fail.