The intuitive approach of Introduction to Econometrics uses interesting applications to motivate theory and theory to match the applications. Students come away with a thorough understanding of econometrics and of the relationships on which people, businesses, and governments base their decisions. Theory is closely matched to the applications--illuminating the vitality and relevance of econometrics, and the choice of topics--including an introduction to program evaluation; panel data methods; instrumental variables regression; and regression with time series data--reflects the best of contemporary applied econometrics. This text is designed for the Introductory Econometrics course. The goal of Introduction to Econometrics is to provide the most modern treatment of econometrics available, using theory and applications that match real-world theory and data.
87 pages matching binary variable in this book
Results 1-3 of 87
What people are saying - Write a review
Economic Questions and Data
Review of Probability
A Bad Day on Wall Street
36 other sections not shown
Other editions - View all
Introduction to Econometrics, Update, Student Value Edition Plus New ...
James H. Stock,Mark W. Watson
No preview available - 2014
Appendix application autoregressive binary variable central limit theorem Chapter cigarettes computed confidence interval correlated covariance data set dependent variable distributed lag district income earnings econometric economic effect on test English learners error term esti example exogenous external validity F-statistic Figure fixed effects regression forecast formula heteroskedasticity homoskedastic hypothesis test included inflation instrumental variables intercept Key Concept large samples least squares assumptions logarithm logit method multiple regression multiple regression model nonlinear regression normal distribution null hypothesis observations OLS estimator OLS regression omitted variable bias p-value P/I ratio panel data percentage of English population mean population regression function population regression line predicted value probability distribution probit random variable randomly regres regressors rejected sample average sampling distribution scatterplot significance level single regressor slope specification standard deviation standard errors standard normal student-teacher ratio summarized in Key Table test scores tion treatment TSLS estimator variance zero