An Introduction to Econometric Theory (eBook)

Measure-Theoretic Probability and Statistics with Applications to Economics

A. Ronald Gallant (Autor)

eBook Download: PDF

2018
208 Seiten
Princeton University Press (Verlag)
978-0-691-18623-8 (ISBN)

Infos

Intended primarily to prepare first-year graduate students for their ongoing work in econometrics, economic theory, and finance, this innovative book presents the fundamental concepts of theoretical econometrics, from measure-theoretic probability to statistics. A. Ronald Gallant covers these topics at an introductory level and develops the ideas to the point where they can be applied. He thereby provides the reader not only with a basic grasp of the key empirical tools but with sound intuition as well. In addition to covering the basic tools of empirical work in economics and finance, Gallant devotes particular attention to motivating ideas and presenting them as the solution to practical problems. For example, he presents correlation, regression, and conditional expectation as a means of obtaining the best approximation of one random variable by some function of another. He considers linear, polynomial, and unrestricted functions, and leads the reader to the notion of conditioning on a sigma-algebra as a means for finding the unrestricted solution. The reader thus gains an understanding of the relationships among linear, polynomial, and unrestricted solutions. Proofs of results are presented when the proof itself aids understanding or when the proof technique has practical value. A major text-treatise by one of the leading scholars in this field, An Introduction to Econometric Theory will prove valuable not only to graduate students but also to all economists, statisticians, and finance professionals interested in the ideas and implications of theoretical econometrics.

Autor

A. Ronald Gallant is Henry A. Latané Distinguished Professor of Economics at the University of North Carolina at Chapel Hill. He is a Fellow of the Econometric Society and the American Statistical Association, and a member of the Board of Directors of the National Bureau of Economic Research and the National Institute of Statistical Science. His books include Nonlinear Statistical Models. He is coeditor of the Journal of Econometrics.

Produkt-Details

• Erscheint lt. Verlag: 5.6.2018
• Verlagsort: Princeton
• Sprache: englisch
• Themenwelt: Wirtschaft
• Schlagworte: Accuracy and precision • Almost surely • Alternative hypothesis • Approximation • Asymptote • Asymptotic Distribution • Bayes Estimator • Bayes' Theorem • Bias of an estimator • Binomial Distribution • Borel–Cantelli lemma • Bounded set (topological vector space) • Cartesian Product • central limit theorem • Central moment • Change of variables • chaos theory • Characteristic function (probability theory) • chi-squared distribution • Chi-squared test • commutative property • Computation • conditional expectation • Conditional probability • Confidence interval • conjugate prior • Convergence in measure • Convergence of random variables • Correlation and dependence • correlation coefficient • Degrees of freedom (statistics) • Density Estimation • Dimension • Dimension (vector space) • Empirical distribution function • estimation • Estimation theory • Estimator • Fair coin • Generalized method of moments • Hoeffding's inequality • Hypergeometric distribution • Independence (probability theory) • Indicator function • Inequality (mathematics) • inference • instrumental variable • Interval (mathematics) • Joint probability distribution • Likelihood Function • Likelihood-ratio test • Location parameter • Marginal distribution • Mathematical Analysis • Mathematical Proof • Mathematical Statistics • maximum likelihood estimation • Method of moments (statistics) • Minimum mean square error • Minimum-variance unbiased estimator • Moment-generating function • Normal distribution • optimization problem • Parameter • Parameter Space • Permutation • power function • Probability • probability and statistics • Probability Distribution • Probability mass function • Probability space • Probability Theory • Proportionality (mathematics) • Quantile • Radon–Nikodym theorem • Random Variable • Rational number • Regression Analysis • Representative Agent • Risk Aversion • Sample space • Sampling (Statistics) • scientific notation • Score test • Slutsky's theorem • standard deviation • Statistic • Statistical hypothesis testing • Statistical Inference • step function • subadditivity • Subset • Taylor's theorem • test statistic • Theorem • Type I and type II errors • Union (set theory) • Variance • Wald test
• ISBN-10: 0-691-18623-5 / 0691186235
• ISBN-13: 978-0-691-18623-8 / 9780691186238