Dieses Lehrbuch basiert auf einem intuitiven Ansatz, bei dem Motivation, Verständnis und Umsetzung im Vordergrund stehen. Renommierte Experten erläutern hier, wie Wirtschaftsdaten eingesetzt werden. In ökonomischen und statistischen Modellen dienen sie als Grundlage für die Ermittlung wichtiger ökonomischer Parameter, zur Prüfung wirtschaftlicher Hypothesen und zur Prognose von Konjunkturergebnissen. Mit Beispielausdrucken von Softwareprogrammen, die dem Studenten helfen sollen, das Wesentliche bei einer Problemstellung zu erkennen.
An Introduction to Econometrics.
Some Basic Probability Concepts.
THE SIMPLE LINEAR REGRESSION MODEL.
The Simple Linear Regression Model: Specification and Estimation.
Properties of the Least Squares Estimators.
Inference in the Simple Regression Model: Interval Estimation, Hypothesis Testing, and Prediction.
The Simple Linear Regression Model: Reporting the Results and Choosing the Functional Form.
THE GENERAL REGRESSION MODEL.
The Multiple Regression Model.
Further Inference in the Multiple Regression Model.
Dummy (Binary) Variables.
Nonlinear Models.
VIOLATIONS OF ERROR ASSUMPTIONS.
Heteroskedasticity.
Autocorrelation.
MODELS WITH RANDOM EXPLANATORY VARIABLES.
Random Regressors and Moment Based Estimation.
Simultaneous Equations.
MODELING DYNAMICS.
Distributed Lag Models.
Regression with Time Series Data.
TOPICS IN ECONOMETRICS.
Pooling Time-Series and Cross-Sectional Data.
Qualitative and Limited Dependent Variable Models.
PRACTICALITIES.
Writing an Empirical Research Report, and Sources of Economic Data.
An Introduction to Econometrics.
Some Basic Probability Concepts.
THE SIMPLE LINEAR REGRESSION MODEL.
The Simple Linear Regression Model: Specification and Estimation.
Properties of the Least Squares Estimators.
Inference in the Simple Regression Model: Interval Estimation, Hypothesis Testing, and Prediction.
The Simple Linear Regression Model: Reporting the Results and Choosing the Functional Form.
THE GENERAL REGRESSION MODEL.
The Multiple Regression Model.
Further Inference in the Multiple Regression Model.
Dummy (Binary) Variables.
Nonlinear Models.
VIOLATIONS OF ERROR ASSUMPTIONS.
Heteroskedasticity.
Autocorrelation.
MODELS WITH RANDOM EXPLANATORY VARIABLES.
Random Regressors and Moment Based Estimation.
Simultaneous Equations.
MODELING DYNAMICS.
Distributed Lag Models.
Regression with Time Series Data.
TOPICS IN ECONOMETRICS.
Pooling Time-Series and Cross-Sectional Data.
Qualitative and Limited Dependent Variable Models.
PRACTICALITIES.
Writing an Empirical Research Report, and Sources of Economic Data.