This text prepares first-year graduate students and advanced undergraduates for empirical research in economics, and also equips them for specialization in econometric theory, business, and sociology.
A Course in Econometrics is likely to be the text most thoroughly attuned to the needs of your students. Derived from the course taught by Arthur S. Goldberger at the University of Wisconsin–Madison and at Stanford University, it is specifically designed for use over two semesters, offers students the most thorough grounding in introductory statistical inference, and offers a substantial amount of interpretive material. The text brims with insights, strikes a balance between rigor and intuition, and provokes students to form their own critical opinions.
A Course in Econometrics thoroughly covers the fundamentals—classical regression and simultaneous equations—and offers clear and logical explorations of asymptotic theory and nonlinear regression. To accommodate students with various levels of preparation, the text opens with a thorough review of statistical concepts and methods, then proceeds to the regression model and its variants. Bold subheadings introduce and highlight key concepts throughout each chapter.
Each chapter concludes with a set of exercises specifically designed to reinforce and extend the material covered. Many of the exercises include real microdata analyses, and all are ideally suited to use as homework and test questions.
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Arthur S. Goldberger was Professor of Economics, Emeritus, at the University of Wisconsin-Madison.
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Hardcover. Zustand: As New. Leichte Kratzer / Abnutzungen / Druckstellen. This text prepares first-year graduate students and advanced undergraduates for empirical research in economics, equipping them for specialization in econometric theory, business, and sociology. Derived from a course taught by Arthur S. Goldberger at the University of Wisconsin-Madison and Stanford University, it is designed for two semesters and provides a thorough grounding in introductory statistical inference along with substantial interpretive material. The text balances rigor and intuition, encouraging students to form their own critical opinions. It covers fundamentals such as classical regression and simultaneous equations, and offers clear explorations of asymptotic theory and nonlinear regression. To accommodate varying levels of preparation, it begins with a comprehensive review of statistical concepts and methods before progressing to the regression model and its variants. Bold subheadings introduce key concepts throughout each chapter, which conclude with exercises designed to reinforce and extend the material. Many exercises involve real microdata analyses and are well-suited for homework and test questions, ensuring that students can apply what they have learned effectively. Artikel-Nr. 5b87408c-b05a-491c-af4f-3dbf42a97fb2
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