Aspects 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.

Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.

A Practitioner's Guide to Stochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach. The authors explain in detail how to estimate production, cost, and profit efficiency and introduce the basic theory of each model in an accessible way, using empirical examples that demonstrate the interpretation and application of models. This book also provides computer code, allowing users to apply the models in their own work, and incorporates the most recent stochastic frontier models developed in academic literature. Such recent developments include models of heteroscedasticity and exogenous determinants of inefficiency, scaling models, panel models with time-varying inefficiency, growth models, and panel models that separate firm effects and persistent and transient inefficiency. Immensely helpful to applied researchers, this book bridges the chasm between theory and practice, expanding the range of applications in which production frontier analysis may be implemented.

This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.

This unique graduate textbook offers a compelling narrative of the growing field of environmental economics that integrates theory, policy, and empirical topics. Daniel J. Phaneuf and Till Requate present both traditional and emerging perspectives, incorporating cutting-edge research in a way that allows students to easily identify connections and common themes. Their comprehensive approach gives instructors the flexibility to cover a range of topics, including important issues - such as tax interaction, environmental liability rules, modern treatments of incomplete information, technology adoption and innovation, and international environmental problems - that are not discussed in other graduate-levels texts. Numerous data-based examples and end-of-chapter exercises show students how theoretical and applied research findings are complementary, and will enable them to develop skills and interests in all areas of the field. Additional data sets and exercises can be accessed online, providing ample opportunity for practice. For more information, visit the book's website at http://phaneuf-requate.com/.

This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.