Econometrics: A Simple Introduction (Simple Introductions, #7) (eBook, ePUB)
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Econometrics: A Simple Introduction offers an accessible guide to the principles and methods of econometrics, with data samples, regressions, equations and diagrams to illustrate the analysis.Examine a linear and multiple regression model, ordinary least squares method, and the Gauss-Markov conditions for a best linear unbiased estimator.Understand hypothesis testing, with a null hypothesis, t, F or chi-square test statistics and distributions, and interpret regression results. Dummy variables model qualitative data and Chow tests assess regression equivalence.Explore heteroscedasticity with t...
Econometrics: A Simple Introduction offers an accessible guide to the principles and methods of econometrics, with data samples, regressions, equations and diagrams to illustrate the analysis.
Examine a linear and multiple regression model, ordinary least squares method, and the Gauss-Markov conditions for a best linear unbiased estimator.
Understand hypothesis testing, with a null hypothesis, t, F or chi-square test statistics and distributions, and interpret regression results. Dummy variables model qualitative data and Chow tests assess regression equivalence.
Explore heteroscedasticity with the White method and with generalized least squares, Goldfeld-Quandt, Breusch-Pagan, and White tests. Assess autocorrelation with Durbin-Watson, Durbin h, and Breusch-Godfrey tests, lagged variables and auxiliary regressions.
Assess the impact of omitted variables, incorrect variables or functional form, and a non-normal distribution with Ramsey RESET and Jarque-Bera tests. Model random variables with the Method of Moments' estimators, instrumental variables and Hausman test.
Examine a linear and multiple regression model, ordinary least squares method, and the Gauss-Markov conditions for a best linear unbiased estimator.
Understand hypothesis testing, with a null hypothesis, t, F or chi-square test statistics and distributions, and interpret regression results. Dummy variables model qualitative data and Chow tests assess regression equivalence.
Explore heteroscedasticity with the White method and with generalized least squares, Goldfeld-Quandt, Breusch-Pagan, and White tests. Assess autocorrelation with Durbin-Watson, Durbin h, and Breusch-Godfrey tests, lagged variables and auxiliary regressions.
Assess the impact of omitted variables, incorrect variables or functional form, and a non-normal distribution with Ramsey RESET and Jarque-Bera tests. Model random variables with the Method of Moments' estimators, instrumental variables and Hausman test.
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