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Providing an introduction to mathematical analysis as it applies to economic theory and econometrics, this book bridges the gap that has separated the teaching of basic mathematics for economics and the increasingly advanced mathematics demanded in economics research today. Dean Corbae, Maxwell B. Stinchcombe, and Juraj Zeman equip students with the knowledge of real and functional analysis and measure theory they need to read and do research in economic and econometric theory. Unlike other mathematics textbooks for economics, An Introduction to Mathematical Analysis for Economic Theory and Econometrics takes a unified approach to understanding basic and advanced spaces through the application of the Metric Completion Theorem. This is the concept by which, for example, the real numbers complete the rational numbers and measure spaces complete fields of measurable sets. Another of the book's unique features is its concentration on the mathematical foundations of econometrics. To illustrate difficult concepts, the authors use simple examples drawn from economic theory and econometrics. Accessible and rigorous, the book is self-contained, providing proofs of theorems and assuming only an undergraduate background in calculus and linear algebra. Begins with mathematical analysis and economic examples accessible to advanced undergraduates in order to build intuition for more complex analysis used by graduate students and researchers Takes a unified approach to understanding basic and advanced spaces of numbers through application of the Metric Completion Theorem Focuses on examples from econometrics to explain topics in measure theory
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
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. The author presents a comprehensive toolbox for designing rigorous and effective ex-post program evaluation using the statistical software package Stata. For each method, a statistical presentation is developed, followed by a practical estimation of the treatment effects. By using both real and simulated data, readers will become familiar with evaluation techniques, such as regression-adjustment, matching, difference-in-differences, instrumental-variables and regression-discontinuity-design and are given practical guidelines for selecting and applying suitable methods for specific policy contexts.
The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
Exploring and understanding the analysis of economic development is essential as global economies continue to experience extreme fluctuation. Econometrics brings together statistical methods for practical content and economic relations. Econometric Methods for Analyzing Economic Development is a comprehensive collection that focuses on various regions and their economies at a pivotal time when the majority of nations are struggling with stabilizing their economies. Outlining areas such as employment rates, utilization of natural resources, and regional impacts, this collection of research is an excellent tool for scholars, academics, and professionals looking to expand their knowledge on today’s turbulent and changing economy.
The Econometric Analysis of Network Data serves as an entry point for advanced students, researchers, and data scientists seeking to perform effective analyses of networks, especially inference problems. It introduces the key results and ideas in an accessible, yet rigorous way. While a multi-contributor reference, the work is tightly focused and disciplined, providing latitude for varied specialties in one authorial voice.
Most of economics takes politics for granted. Through some (often implausible) assumptions, it seeks to explain away political structures by characterizing them as stable and predictable or as inconsequential in understanding what goes on in an economy. Such attempts are misguided, and this book shows how governments and political institutions are composed of people who respond to incentives and whose behavior and choices can be studied through the lens of economics. This book aims to bridge the gap between economics and politics, and in doing so hopes to instill in the reader a deeper appreciation for social scientific thinking. Opening with a refresher on microeconomics and an introduction to the toolkit of political economy, it ensures that the necessary building blocks are in place before building up from the level of the individual and the firm to show how a political–economic equilibrium can be achieved. The text explores how to separate primitives—the external parts of a model that we cannot affect—from outcomes—the internal parts of a model that we can. Moreover, it demonstrates that economic and political issues alike can be studied within the same general framework of analysis. Political Economy and Policy Analysis offers readers the chance to gain a more sophisticated understanding of political processes, economic processes, and the interplay among them. Adopting an applied microeconomics approach, it will be ideal for upper-level undergraduate or postgraduate courses on political economy, public choice, or policy analysis. A complementary workbook with exercises and solutions that accompanies Political Economy and Policy Analysis is available for download under the eResources tab at: https://www.routledge.com/Political-Economy-and-Policy-Analysis/Merlo/p/book/9781138591783.
Coverage has been extended to include recent topics. The book again presents a unified treatment of economic theory, with the method of maximum likelihood playing a key role in both estimation and testing. Exercises are included and the book is suitable as a general text for final-year undergraduate and postgraduate students.
Written by one of the world's leading researchers and writers in the field, Econometric Analysis of Panel Data has become established as the leading textbook for postgraduate courses in panel data. This new edition reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. Featuring the most recent empirical examples from panel data literature, data sets are also provided as well as the programs to implement the estimation and testing procedures described in the book. These programs will be made available via an accompanying website which will also contain solutions to end of chapter exercises that will appear in the book. The text has been fully updated with new material on dynamic panel data models and recent results on non-linear panel models and in particular work on limited dependent variables panel data models.