Learning and Practicing Econometrics
Designed to promote students' understanding of econometrics and to build a more operational knowledge of economics through a meaningful combination of words, symbols and ideas. Each chapter commences in the way economists begin new empirical projects--with a question and an economic model--then proceeds to develop a statistical model, select an estimator and outline inference procedures. Contains a copious amount of problems, experimental exercises and case studies.
Partial table of contents:
THE FOUNDATIONS OF ESTIMATION AND INFERENCE.
Some Basic Ideas: Statistical Concepts for Economists.
Statistical Inference 1: Estimating the Mean and Variance of a Population.
THE SIMPLE LINEAR STATISTICAL MODEL.
Simple Regression: Economic and Statistical Model Specification and Estimation.
GENERAL LINEAR STATISTICAL MODEL.
Inference in the General Linear Statistical Model.
ECONOMETRIC TOPICS 1.
Dummy Variables and Varying Coefficient Models.
Collinear Economic Variables.
LINEAR STATISTICAL MODELS WITH A GENERAL ERROR COVARIANCE MATRIX.
SPECIFYING AND ESTIMATING ECONOMIC AND STATISTICAL MODELS WITH FEEDBACK MECHANISMS.
Estimation and Inference for the Simultaneous Equations Model.
TIME-SERIES AND DYNAMIC ECONOMIC MODELS.
Bivariate and Multivariate Time-Series Models.
ECONOMETRIC TOPICS 2.
Nonlinear Least Squares.
BAYESIAN ESTIMATION AND INFERENCE.
The Bayesian Approach to Estimation and Inference: Some Basic Definitions, Concepts, and Applications.
ECONOMIC DATA SOURCES AND THE WRITING TASK.
Economic Data Sources, Guidelines for Choosing a Research Project, and the Writing of a Research Report.