Bøger i Advanced Studies in Theoretical and Applied Econometrics serien

This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. In light of the big data revolution and the emergence of higher dimensional panel data sets, it provides new results to synthesize existing knowledge on the field. The first, theoretical part of the volume is providing the econometric foundations to deal with these new high-dimensional panel data sets. It not only synthesizes our current knowledge, but mostly, presents new research results. The second empirical part of the book provides insight into the most relevant applications in this area. These chapters are a mixture of surveys and new results, always focusing on the econometric problems and feasible solutions.This second extended and revised edition provides an update of all existent chapters to reflect on new developments in the area as well as several new chapters on topics such as machine learning, nonparametric models, networks, and multi-dimensional panels in health economics. The book serves as a standard reference work, a textbook for graduate students in economics, and a source of background material for professionals conducting empirical studies.

This book helps and promotes the use of machine learning tools and techniques in econometrics and explains how machine learning can enhance and expand the econometrics toolbox in theory and in practice. Throughout the volume, the authors raise and answer six questions: 1) What are the similarities between existing econometric and machine learning techniques? 2) To what extent can machine learning techniques assist econometric investigation? Specifically, how robust or stable is the prediction from machine learning algorithms given the ever-changing nature of human behavior? 3) Can machine learning techniques assist in testing statistical hypotheses and identifying causal relationships in 'big data? 4) How can existing econometric techniques be extended by incorporating machine learning concepts? 5) How can new econometric tools and approaches be elaborated on based on machine learning techniques? 6) Is it possible to develop machine learning techniques further and make them even more readily applicable in econometrics?As the data structures in economic and financial data become more complex and models become more sophisticated, the book takes a multidisciplinary approach in developing both disciplines of machine learning and econometrics in conjunction, rather than in isolation. This volume is a must-read for scholars, researchers, students, policy-makers, and practitioners, who are using econometrics in theory or in practice. 

This book provides advanced theoretical and applied tools for the implementation of modern micro-econometric techniques in evidence-based program evaluation for the social sciences.

Chapter 2 deals vii tll the theory of import allocation models, Chapter J treats the problem of defining and interpreting elasticities of substitution, while Chapter 4 is concerned with the econometric problems related to the estimation of mul- tivariate models with linear restrictions, such as import allocation models.

This thorough guide covers the history of macroeconometric model building, summarizes the development and structure of macroeconometric models built in North America, Europe and elsewhere and covers the systematic characteristics of macroeconometric models.

This volume is mainly concerned with methods of estimating income elasticity. It is connected with economic development that can be achieved by reducing income inequality, a highly relevant subject in today's world for a wide range of policy areas.

Offering a complete overview of all econometric software packages available worldwide, this book describes the history of econometric computation from 1950. It is based on an interactive survey of the econometricians who have developed the software.

This book offers insight into international trade and foreign direct investment competitiveness in Africa. It examines two policies frequently used to enhance international competitiveness in Sub-Saharan African economies: exchange rate policy and productivity-related policy.

Regression or a related method is applied to a set of observations on these variables, and the conclusion often emerges that the causa,l variables are indeed "significant" at a certain "level," thereby lending support to the theoretical argument-an argument presumably formulated independently of the observations.

Markov chains have increasingly become useful way of capturing stochastic nature of many economic and financial variables. The main aim of Hidden Markov Models: Applications to Financial Economics is to make such techniques available to more researchers in financial economics.

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.

One cannot exaggerate the importance of estimating how international trade responds to changes in income and prices. With the new estimates of trade elasticities, the book examines how they assist in restoring the consistency between elasticity estimates and the world trade identity.

This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

This book treats the notion of morphisms in spatial analysis, paralleling these concepts in spatial statistics (Part I) and spatial econometrics (Part II).

This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. The last two decades or so, the use of panel data has become a standard in many areas of economic analysis.

This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.

This book treats the notion of morphisms in spatial analysis, paralleling these concepts in spatial statistics (Part I) and spatial econometrics (Part II).

The purpose of this book is to establish a connection between the traditional field of empirical economic research and the emerging area of empirical financial research and to build a bridge between theoretical developments in these areas and their application in practice.

Modeling North American Economic Integration presents descriptions of the models and the central results obtained by four teams of economic modelers who analyze the impact of the North American Free Trade Agreement (NAFTA) on the economies of Canada, Mexico and the USA.

This book is based on an international conference organised by the Applied Econo­ metric Association (AEA) on International Macroeconomic Modelling which was held in Brussels at the Commission of the European Communities in December 1983. On behalf of the Applied Econometric Association, we would like to extend our thanks to all participants and contributors. This conference would not have been possible without the cooperation and support of the Commission of the European Economic Communities and of its Directorate General for Economics and Financial Affairs (DGII) staff, in particular M. Emerson, A. Dramais, and also H. Serbat of the Paris Chamber of Commerce and Industry. Our thanks go also to J.P. Ancot for his constructive comments concerning the structure of this book. We are grateful to M. Russo, R. Maldague and Y. Ullmo for opening the con­ ference with their stimulating review and comments on the use of international macroeconomic models; and to R. Bird, A.M. Costa, A. Crockett, H. Guitton, J.C. Milleron, J. Paelinck, J. Waelbroeck for chairing the scientific sessions. P. Artus F. Gagey O. Guvenen vi INTRODUCTION The main focus of this book is to present recent developments in the construction and use of international macroeconometric models. Four main aspects are selected: (i) analysis of trade linkages and exchange rate determination; (ii) modelling and simulating the international economy; (iii) international policy coordination; (iv) the use of international macroeconomic models.

Figure 1. 4: First order neighbours (a) and second order neighbours (b) of a reference area. a shows the first-order neighbours of a reference area, while Figure 1. While it is clear that the dependence is strongest between immediate neighbouring areas a certain degree of dependence may be present among higher-order neighbours.

The purpose of this book is to establish a connection between the traditional field of empirical economic research and the emerging area of empirical financial research and to build a bridge between theoretical developments in these areas and their application in practice.

Louis Phlips The stabilisation of primary commodity prices, and the related issue of the stabilisation of export earnings of developing countries, have traditionally been studied without reference to the futures markets (that exist or could exist) for these commodities.