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Elsevier

Books in Econometric and statistical methods general

  • Handbook of the Economics of Education

    • 1st Edition
    • Volume 6
    • English
    The Handbook of the Economics of Education describes the research frontier in key topical areas and sets the agenda for further work. Modern analysis in the economics of education has made tremendous strides in understanding fundamental issues related to the production of human capital and the impact of varying institutional features of education systems. By bringing together some of the world’s leading scholars, this volume provides a unique view of scholarship in the area. The international perspectives of the editors – Hanushek at Stanford, Machin at LSE, and Woessmann at Munich – leads to a volume with something for all researchers. Topics range from the economics of early childhood education to inequality in society to cash transfers in developing countries.

  • Handbook of Econometrics

    • 1st Edition
    • Volume 7A
    • English
    Handbook of Econometrics, Volume 7A, examines recent advances in foundational issues and "hot" topics within econometrics, such as inference for moment inequalities and estimation of high dimensional models. With its world-class editors and contributors, it succeeds in unifying leading studies of economic models, mathematical statistics and economic data. Our flourishing ability to address empirical problems in economics by using economic theory and statistical methods has driven the field of econometrics to unimaginable places. By designing methods of inference from data based on models of human choice behavior and social interactions, econometricians have created new subfields now sufficiently mature to require sophisticated literature summaries.

  • Panel Data Econometrics

    Theory
    • 1st Edition
    • Mike Tsionas
    • English
    Panel Data Econometrics: Theory introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illuminate applications for a variety of fields, such as banking, financial markets, tourism and transportation, auctions, and experimental economics. Contributors emphasize techniques and applications, and they accompany their explanations with case studies, empirical exercises and supplementary code in R. They also address panel data analysis in the context of productivity and efficiency analysis, where some of the most interesting applications and advancements have recently been made.

  • Panel Data Econometrics

    Empirical Applications
    • 1st Edition
    • Mike Tsionas
    • English
    Panel Data Econometrics: Empirical Applications introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illuminate applications for a variety of fields, such as banking, financial markets, tourism and transportation, auctions, and experimental economics. Contributors emphasize techniques and applications, and they accompany their explanations with case studies, empirical exercises and supplementary code in R. They also address panel data analysis in the context of productivity and efficiency analysis, where some of the most interesting applications and advancements have recently been made.

  • Applied Time Series Analysis

    A Practical Guide to Modeling and Forecasting
    • 1st Edition
    • Terence C. Mills
    • English
    Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.

  • Computational Economics: Heterogeneous Agent Modeling

    • 1st Edition
    • Cars Hommes + 1 more
    • English
    Handbook of Computational Economics: Heterogeneous Agent Modeling, Volume Four, focuses on heterogeneous agent models, emphasizing recent advances in macroeconomics (including DSGE), finance, empirical validation and experiments, networks and related applications. Capturing the advances made since the publication of Volume Two (Tesfatsion & Judd, 2006), it provides high-level literature with sections devoted to Macroeconomics, Finance, Empirical Validation and Experiments, Networks, and other applications, including Innovation Diffusion in Heterogeneous Populations, Market Design and Electricity Markets, and a final section on Perspectives on Heterogeneity.

  • The Economics and Econometrics of the Energy-Growth Nexus

    • 1st Edition
    • Angeliki Menegaki
    • English
    The Economics and Econometrics of the Energy-Growth Nexus recognizes that research in the energy-growth nexus field is heterogeneous and controversial. To make studies in the field as comparable as possible, chapters cover aggregate energy and disaggregate energy consumption and single country and multiple country analysis. As a foundational resource that helps researchers answer fundamental questions about their energy-growth projects, it combines theory and practice to classify and summarize the literature and explain the econometrics of the energy-growth nexus. The book provides order and guidance, enabling researchers to feel confident that they are adhering to widely accepted assumptions and procedures.

  • Spatial Econometrics

    • 1st Edition
    • Harry Kelejian + 1 more
    • English
    Spatial Econometrics provides a modern, powerful and flexible skillset to early career researchers interested in entering this rapidly expanding discipline. It articulates the principles and current practice of modern spatial econometrics and spatial statistics, combining rigorous depth of presentation with unusual depth of coverage. Introducing and formalizing the principles of, and ‘need’ for, models which define spatial interactions, the book provides a comprehensive framework for almost every major facet of modern science. Subjects covered at length include spatial regression models, weighting matrices, estimation procedures and the complications associated with their use. The work particularly focuses on models of uncertainty and estimation under various complications relating to model specifications, data problems, tests of hypotheses, along with systems and panel data extensions which are covered in exhaustive detail. Extensions discussing pre-test procedures and Bayesian methodologies are provided at length. Throughout, direct applications of spatial models are described in detail, with copious illustrative empirical examples demonstrating how readers might implement spatial analysis in research projects. Designed as a textbook and reference companion, every chapter concludes with a set of questions for formal or self--study. Finally, the book includes extensive supplementing information in a large sample theory in the R programming language that supports early career econometricians interested in the implementation of statistical procedures covered.

  • Asymptotic Theory for Econometricians

    • 1st Edition
    • Halbert White
    • English
    This book is intended to provide a somewhat more comprehensive and unified treatment of large sample theory than has been available previously and to relate the fundamental tools of asymptotic theory directly to many of the estimators of interest to econometricians. In addition, because economic data are generated in a variety of different contexts (time series, cross sections, time series--cross sections), we pay particular attention to the similarities and differences in the techniques appropriate to each of these contexts.

  • Multinomial Probit

    The Theory and Its Application to Demand Forecasting
    • 1st Edition
    • Carlos Daganzo
    • English
    Multinomial Probit: The Theory and Its Application to Demand Forecasting covers the theoretical and practical aspects of the multinomial probit (MNP) model and its relation to other discrete choice models. This text is divided into five chapters and begins with an overview of the disaggregate demand modeling in the transportation field. The subsequent chapters examine the computational aspects of the maximum-likelihood estimation and the statistical aspects of MNP model calibration. These chapters specifically describe the properties of the log-likelihood function and the statistical properties of MNP estimators. These topics are followed by a discussion of the mechanical aspects of the MNP model. The closing chapter examines the errors in the estimation of the true parameter value due to lack of data and how these errors propagate to the final prediction. This book will prove useful to econometricians, engineers, and applied mathematicians.