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Hayashi's Econometrics promises to be the next great synthesis of modern econometrics. It introduces first year Ph.D. students to standard graduate econometrics material from a modern perspective. It covers all the standard material necessary for understanding the principal techniques of econometrics from ordinary least squares through cointegration. The book is also distinctive in developing both time-series and cross-section analysis fully, giving the reader a unified framework for understanding and integrating results. Econometrics has many useful features and covers all the important topics in econometrics in a succinct manner. All the estimation techniques that could possibly be taught in a first-year graduate course, except maximum likelihood, are treated as special cases of GMM (generalized methods of moments). Maximum likelihood estimators for a variety of models (such as probit and tobit) are collected in a separate chapter. This arrangement enables students to learn various estimation techniques in an efficient manner. Eight of the ten chapters include a serious empirical application drawn from labor economics, industrial organization, domestic and international finance, and macroeconomics. These empirical exercises at the end of each chapter provide students a hands-on experience applying the techniques covered in the chapter. The exposition is rigorous yet accessible to students who have a working knowledge of very basic linear algebra and probability theory. All the results are stated as propositions, so that students can see the points of the discussion and also the conditions under which those results hold. Most propositions are proved in the text. For those who intend to write a thesis on applied topics, the empirical applications of the book are a good way to learn how to conduct empirical research. For the theoretically

This is an excerpt from the 4-volume dictionary of economics, a reference book which aims to define the subject of economics today. 1300 subject entries in the complete work cover the broad themes of economic theory. This extract concentrates on econometrics.

This textbook teaches some of the basic econometric methods and the underlying assumptions behind them. It also includes a simple and concise treatment of more advanced topics in spatial correlation, panel data, limited dependent variables, regression diagnostics, specification testing and time series analysis. Each chapter has a set of theoretical exercises as well as empirical illustrations using real economic applications. These empirical exercises usually replicate a published article using Stata, Eviews as well as SAS. This new sixth edition has been fully revised and updated, and includes new material on limited dependent variables and panel data as well as revision of basic topics like heteroskedasticity, endogeneity, over-identification and specification testing. The author also provides more exercises and empirical examples based on published economic applications.

ECONOMETRICS: THEORY AND APPLICATIONS WITH (...) -- PÁGINA LEGAL -- CONTENTS -- PREFACE -- ACKNOWLEDGMENTS -- PART I. PREPARATORY WORK -- INTRODUCTION TO PART I -- CHAPTER 1. BASIC CONCEPTS OF ECONOMETRIC (...) -- 1.1 SCIENTIFIC QUANTITATIVE ECONOMIC RESEARCH -- 1.2 ECONOMIC AND ECONOMETRIC MODELS -- 1.3 ECONOMIC DATA -- 1.4 VARIABLES OF AN ECONOMIC MODEL -- 1.5 STRUCTURAL AND REDUCED-FORM EQUATIONS -- 1.6 PARAMETERS AND ELASTICITIES -- 1.7 STOCHASTIC MODELS -- 1.8 APPLIED QUANTITATIVE ECONOMIC RESEARCH -- CHAPTER 2. DESCRIPTION OF THE DATA SETS (...) -- 2.1 INTRODUCTION -- 2.2 DATA SET 1: COMMODITY PRICES -- 2.3 DATA SET 2: MACROECONOMIC DATA -- 2.4 DATA SET 3: OIL MARKET-RELATED DATA -- 2.5 DATA SET 4: MONEY MARKET -- 2.6 DATA SET 5: CROSS-SECTION DATA -- 3. BASIC CONCEPTS OF EVIEWS AND STARTING (...) -- 3.1 INTRODUCTION -- 3.2 THE CREATION OF A WORKFILE IN EVIEWS -- 3.3 VIEWING VARIABLES AND SOME PROCEDURES -- 3.4 SOME BASIC CALCULATIONS IN EVIEWS -- 3.5 CASE 1: THE DATA ANALYSIS -- PART II. THE REDUCED-FORM MODEL -- INTRODUCTION TO PART II -- CHAPTER 4. DESCRIPTION OF THE REDUCED-FORM (...) -- 4.1 INTRODUCTION -- 4.2 THE ASSUMPTIONS OF THE CLASSICAL (...) -- 4.3 THE ORDINARY LEAST SQUARES (OLS) ESTIMATOR -- 4.4 RELATIONSHIP BETWEEN DISTURBANCES AND (...) -- 4.5 ESTIMATION OF THE VARIANCE OF THE (...) -- 4.6 DESIRABLE STATISTICAL PROPERTIES OF (...) -- 4.7 THE DISTRIBUTION AND SOME PROPERTIES (...) -- 4.8 MAXIMUM LIKELIHOOD ESTIMATION -- 4.9 REGRESSION ANALYSIS WITH EVIEWS -- CHAPTER 5. TESTING THE DETERMINISTIC ASSUMPTIONS -- 5.1 INTRODUCTION -- 5.2 RELATIONSHIPS AMONG VARIABLES OF THE (...) -- 5.3 THE COEFFICIENT OF DETERMINATION -- 5.4 SURVEY OF SOME USEFUL DISTRIBUTIONS (...) -- 5.5 DISTRIBUTION OF THE RESIDUAL VARIANCE (...) -- 5.6 INTERVAL ESTIMATES AND THE TEST TO (...) -- 5.7 THE WALD F-TEST TO TEST RESTRICTIONS (...)

Bayesian econometrics : past, present, and future / Arnold Zellner -- Fitting and comparison of models for multivariate ordinal outcomes / Ivan Jeliazkov, Jennifer Graves, Mark Kutzbach -- Intra-household allocation and consumption of WIC-approved foods : A Bayesian approach / Ariun Ishdorj, Helen H. Jensen, Justin Tobias -- Causal effects from panel data in randomized experiments with partial compliance / Siddhartha Chib, Liana Jacobi -- Parametric and nonparametric inference in equilibrium job search models / Gary Koop -- Do subsidies drive productivity? A cross-country analysis of Nordic dairy farms / Nadine McCloud, Subal C. Kumbhakar -- Semiparametric Bayesian estimation of random coefficients discrete choice models / Sylvie Tchumtchoua, Dipak K. Dey -- Bayesian econometrics : an introduction / Siddhartha Chib, William Griffiths, Gary Koop, Dek Terrell -- Bayesian two-stage regression with parametric heteroscedasticity / Arto Luoma, Jani Luoto -- Bayesian near-boundary analysis in basic macroeconomic time-series models / Michiel de Pooter, Francesco Ravazzolo, Rene Segers, Herman K. van Dijk -- Forecasting in vector autoregressions with many predictors / Dimitris Korobilis -- Bayesian inference in a cointegrating panel data model / Gary Koop, Roberto Leon-Gonzalez, Rodney Strachan -- Investigating nonlinear purchasing power parity during the post-Bretton Woods era : a Bayesian exponential smooth transition VECM approach / Deborah Gefang -- Bayesian forecast combination for VAR models / Michael K. Andersson, Sune Karlsson -- Bayesian inference on time-varying proportions / William J. McCausland, Brahim Lgui -- Imposing stationarity constraints on the parameters of ARCH and GARCH models / Christopher J. ODonnell, Vanessa Rayner -- Bayesian model selection for heteroskedastic models / Cathy W.S. Chen, Richard Gerlach, Mike K.P. So -- Bayesian student-t / S.T. Boris Choy, Wai-yin Wan, Chun-man Chan -- Bayesian inference using adaptive sampling / Paolo Giordani, Robert Kohn -- Bayesian analysis of the consumption CAPM / Veni Arakelian, Efthymios G. Tsionas -- A Bayesian analysis of the OPES model with a nonparametric component: An application to dental insurance and dental care / Murat K. Munkin, Pravin K. Trivedi

Econometrics can at first appear a highly technical subject, but it can also equip the practitioner with a useful skillset of smart ways to formulate research questions and collect data. Enjoyable Econometrics applies econometric methods to a variety of unusual and engaging research questions, often beyond the realm of economics, demonstrating the great potential of using such methods to understand a wide range of phenomena. Unlike the typical textbook approach, Enjoyable Econometrics follows in the footsteps of Freakonomics by posing interesting questions first before introducing the methodology to find the answers. Therefore, rather than equation-heavy sections based around complex methodologies, the reader is presented with chapters on 'Money' and 'Fashion, Art and Music'. Franses writes in a way that will enthuse and motivate the economics student embarking upon the essential study of econometrics. Indeed, the book shows that econometric methods can be applied to almost anything