This course is an introduction to econometric techniques and models, program evaluation, and simultaneous equations based on regression analysis. It covers advanced topics such as linear panel models, nonlinear probability, time series regressions, instrumental variables, limited dependent variable models, censored outcomes models, and measurement error.
- Use sample statistics to estimate the population parameters and to make judgments about the population.
- Analyze a regression model between the response variable and a set of explanatory variables, and predict the response variable using the model.
- Apply econometric methods to differentiate between competing theories.
- Utilize regression analysis to distinguish the relative effects that many different variables (family income, occupation and education, for example) have on a variable of interest (for instance, an individual’s likelihood of being unemployed).
- Discover how to correctly draw conclusions (statistical inferences) from data in this lecture course.
- Study techniques for determining the precision of their results and analyzing time series data as well.