Econometrics (+ Data CD)

Description Stephen Schmidt is a superb and dedicated professor at a very good, liberal arts college, (Union in Schenectady, NY). After obtaining a PhD in Economics from Stanford University and teaching for 8 years, he has now written the book he has always wanted to write and use--an econometrics book that excites and motivates students about the value of statistical analysis in economics and gives them all of the tools they will need to do this analysis themselves. The goal of this book is to show students that econometric analysis is the bridge that connects economic theory with economic policy. Key Features A Text for Economics students: Schmidt focuses on the importance of economics in motivating the problems and generating the equations to be estimated rather than on the statistical techniques. Chapters begin with an empirical economic problem that integrates economic ideas directly into the text presentation, making the material relevant to the student and directly relating it to economics. It presents the subject, not as a series of statistical techniques, but as a way of thinking about economic issues that students have confronted in introductory economics or other courses they have taken before taking econometrics. A Text for Economics students: Schmidt focuses on the importance of economics in motivating the problems and generating the equations to be estimated rather than on the statistical techniques. Chapters begin with an empirical economic problem that integrates economic ideas directly into the text presentation, making the material relevant to the student and directly relating it to economics. It presents the subject, not as a series of statistical techniques, but as a way of thinking about economic issues that students have confronted in introductory economics or other courses they have taken before taking econometrics. Use of the Computer is Integrated Throughout the Text: Schmidt contains over 130 econometric exercises, plus computer-based simulation exercises that can be done either in or outside of class. The simulations allow students to see how estimation works when the data generating process is known, helping them understand what estimation does in the traditional exercises where the process is not known. The econometric problems do not stop when the student has calculated the estimated parameter value and tested its significance, but require the student to explain what the estimated value means in the context of the economic model which motivated the problem, and the economic conclusions the student can draw from the results. Emphasis on the role of the economic model in econometric analysis: The importance of economic ideas for selecting models and data are covered at the beginning of the book in chapters 1 and 2, including the use of theory to distinguish real results from spurious correlations, and the problem of choosing data to avoid sample selection bias. This teaches students how to put econometric analysis to practical uses, in a way that does full justice to both statistics and economics. Data Sets Re-applied: Some of the data sets are used in more than one problem in the Schmidt text, and some in more than one chapter. This reapplication of a data set lets students see how the techniques taught in the later chapters help them learn more from the data sets than they could learn with the simpler techniques in the earlier chapters. Integrated one-chapter treatment of modern time-series methods including ARMA modeling, unit root tests, Granger causality, and vector autoregression. An undergraduate-level presentation of material essential for modern macroeconometrics, together with a discussion of why macroeconomists use these techniques. This integrated treatment permits students to grasp quickly the essentials of reading and of performing modern macroeconometrics. Table of Contents Part 1: Econometric Analysis Chapter 1 Introduction Chapter 2 Designing an econometric project Part 2: Probability and Statistics Chapter 3 Random variables Chapter 4 Estimation Chapter 5 Hypothesis testing Part 3: Linear Regression Chapter 6 Least Squares Regression Chapter 7 Properties of the least squares estimator Chapter 8 Multivariate regression Part 4: Topics in Linear Regression Chapter 9 Selecting a Functional Form Chapter 10 Determining the econometric specification Chapter 11 Instability of the regression equation Part 5: Violations of the Regression Model Chapter 12 Autocorrelation Chapter 13 Heteroskedasticity Chapter 14 Estimating multiple equations Part 6: Advanced Topics Chapter 15 Endogenous variables Chapter 16 Forecasting Chapter 17 Time series analysis Chapter 18 Nonlinear models Chapter 19 Dummy dependent variables Chapter 20 General discrete choice models