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Lancaster for modern economics

Lancaster for modern economics
Author: Helen Youngelson Waehrer
Publisher:
Total Pages: 206
Release: 1973
Genre:
ISBN:

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Modern Consumer Theory

Modern Consumer Theory
Author: Kelvin Lancaster
Publisher: Edward Elgar Publishing
Total Pages: 270
Release: 1991
Genre: Business & Economics
ISBN:

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Professor Lancaster has made a major contribution to consumer theory. His work on the consumer's decision-making process has been particularly influential. This coherent thematic selection of his most important recent essays, some of which are published here for the first time, reflect the major features of Professor Lancaster's work. The essays form a unified collection on consumer choice and product variety and will be essential reading for any economist with an interest in the most recent developments in modern microeconomics.


Introduction to Modern Bayesian Econometrics

Introduction to Modern Bayesian Econometrics
Author: Tony Lancaster
Publisher: Wiley-Blackwell
Total Pages: 401
Release: 2004-06-28
Genre: Business & Economics
ISBN: 9781405117197

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Almost two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events. While his method has extensive applications to the work of applied economists, it is only recent advances in computing that have made it possible to exploit the full power of the Bayesian way of doing applied economics.In this new and expanding area, Tony Lancasters text provides a comprehensive introduction to the Bayesian way of doing applied economics. Using clear explanations and practical illustrations and problems, the text presents innovative, computer-intensive ways for applied economists to use the Bayesian method.The Introduction emphasizes computation and the study of probability distributions by computer sampling, showing how these techniques can provide exact inferences about a wide range of econometric problems. Covering all the standard econometric models, including linear and non-linear regression using cross-sectional, time series, and panel data, it also details causal inference and inference about structural econometric models. In addition, each chapter includes numerical and graphical examples and demonstrates their solutions using the S programming language and Bugs software.


Mathematical Economics

Mathematical Economics
Author: Kelvin Lancaster
Publisher: Courier Corporation
Total Pages: 450
Release: 2012-10-10
Genre: Mathematics
ISBN: 0486145042

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Graduate-level text provides complete and rigorous expositions of economic models analyzed primarily from the point of view of their mathematical properties, followed by relevant mathematical reviews. Part I covers optimizing theory; Parts II and III survey static and dynamic economic models; and Part IV contains the mathematical reviews, which range fromn linear algebra to point-to-set mappings.


Modern Economics: Principles and Policy

Modern Economics: Principles and Policy
Author: Kelvin Lancaster
Publisher:
Total Pages: 776
Release: 1973
Genre: Business & Economics
ISBN:

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The market economy; Problems and policy in the market economy; Distribution; Macroeconomics; Applications of macroeconomic analysis; Money and banks; Macroeconomic policy; International economics; Total economic policy.


The Makers of Modern Economics

The Makers of Modern Economics
Author: Arnold Heertje
Publisher: Edward Elgar Publishing
Total Pages: 168
Release: 1997
Genre: Biography & Autobiography
ISBN:

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This work follows on from the two previous volumes in presenting the intellectual development of some of this century's most influential economists. The careers, education, achievements and views on future research are presented by economists who have made important contributions to the subject.


Introduction to Bayesian Econometrics

Introduction to Bayesian Econometrics
Author: Edward Greenberg
Publisher: Cambridge University Press
Total Pages: 271
Release: 2013
Genre: Business & Economics
ISBN: 1107015316

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This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior distributions are considered, with special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail in the derivation of marginal posterior distributions. The remainder of the book is concerned with applications of the theory to important models that are used in economics, political science, biostatistics and other applied fields. New to the second edition is a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The new edition also emphasizes the R programming language.