A thorough understanding of econometrics allows students to better understand the relationships on which people, businesses, and governments base their decisions. And to make econometrics relevant in an introductory course, interesting applications must motivate the theory and the theory must match the applications. This text motivates the need for tools with concrete applications, and then provide simple assumptions that match the application. Because the theory is immediately relevant to the applications, this approach makes econometrics come alive. Real-world questions and data are integrated into the theoretical development, and appropriate coverage is given to the substantive findings of the resulting empirical analysis. And topics presented in the text reflect modern theory and practice.
71 pages matching omitted variable bias in this book
Results 1-3 of 71
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