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OverviewAspects of environmental change are some of the greatest challenges faced by policymakers today. The key issues addressed by environmental science are often empirical, and in many instances very detailed, sizable datasets are available. Researchers in this field should have a solid understanding of the econometric tools best suited for analysis of these data. While complex and expensive physical models of the environment exist, it is becoming increasingly clear that reduced-form econometric models have an important role to play in modeling environmental phenomena. In short, successful environmental modeling does not necessarily require a structural model, but the econometric methods underlying a reduced-form approach must be competently executed. Environmental Econometrics Using Stata provides an important starting point for this journey by presenting a broad range of applied econometric techniques for environmental econometrics and illustrating how they can be applied in Stata. The emphasis is not only on how to formulate and fit models in Stata but also on the need to use a wide range of diagnostic tests in order to validate the results of estimation and subsequent policy conclusions. This focus on careful, reproducible research should be appreciated by academic and non-academic researchers who are seeking to produce credible, defensible conclusions about key issues in environmental science. Full Product DetailsAuthor: Christopher F. Baum , Stan HurnPublisher: Stata Press Imprint: Stata Press Weight: 0.900kg ISBN: 9781597183550ISBN 10: 1597183555 Pages: 416 Publication Date: 10 May 2021 Audience: College/higher education , Postgraduate, Research & Scholarly Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1 Introduction 2 Linear regression models 3 Beyond ordinary least squares 4 Introducing dynamics 5 Multivariate time-series models 6 Testing for nonstationarity 7 Modeling nonstationary variables 8 Forecasting 9 Structural time-series models 10 Nonlinear time-series models 11 Modeling time-varying variance 12 Longitudinal data models 13 Spatial models 14 Discrete dependent variables 15 Fractional integration A Using StataReviewsAuthor InformationChristopher F. Baum is a professor of economics and social work at Boston College. Baum has taught econometrics for many years, using Stata extensively in academic and nonacademic settings. He has over 40 years of experience with computer programming and has authored or coauthored several widely used Stata commands. He is the author of An Introduction to Modern Econometrics Using Stata and An Introduction to Stata Programming, Second Edition. He is an associate editor of the Stata Journal and maintains the Statistical Software Components Archive of community-contributed Stata materials. Stan Hurn is a professor of econometrics at Queensland University of Technology. He held previous positions at the University of Glasgow and at Brasenose College, Oxford. He is a fellow of the Society for Financial Econometrics. His main research interests are in the field of time-series econometrics, and he has been published widely in leading international journals. He is also the coauthor of Econometric Modelling with Time Series: Specification, Estimation and Testing and Financial Econometric Modeling. Tab Content 6Author Website:Countries AvailableAll regions |
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