Week 5 Flashcards
Econometrics definition
Econometrics uses a combination of economic theory, math and statistical inferences to quantify and analyze economic theories by leveraging tools such as frequency distributions, probability and probability distributions, statistical inference, simple and multiple regression analysis, simultaneous equations models and time series methods.
Bivariate Linear Regression Model
X is the ______ variable
independent
Y is the _____ variable
dependent
Ordinary least squares (OLS)
The Least Squares Regression Line is the line that makes the vertical distance from the data points to the regression line as small as possible. It’s called a “least squares” because the best line of fit is one that minimizes the variance (the sum of squares of the errors). This can be a bit hard to visualize but the main point is you are aiming to find the equation that fits the points as closely as possible.
The residual of an observed value
the difference between the observed value and the estimated value of the quantity of interest (for example, a sample mean).
Anatomy of the error term
in statistics is a value which represents how observed data differs from actual population data. It can also be a variable which represents how a given statistical model differs from reality. The error term is often written ε.
- Vagueness of the underlying (economic) theory.
- Unavailability of data.
- Intrinsic randomness in economic phenomena.
- Poor proxy variables.
- Principle of parsimony (Occam Razor).
Amount of overall variance, Total Sum of the Square (TTS):
Portion of explained variance, Explained Sum of the Squares (ESS):
a quantity used in describing how well a model, often a regression model, represents the data being modelled. In particular, the explained sum of squares measures how much variation there is in the modelled values and this is compared to the total sum of squares, which measures how much variation there is in the observed data, and to the residual sum of squares, which measures the variation in the modelling errors.
Portion of unexplained variance, Residuals Sum of the Squares (RSS):
describes the overall fit of the estimated model. It falls between 0 < R² < 1
R² is the ratio of the ESS and the TSS:
Fitted values
