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ökonometrie

Functional Form and Time Series

- functional forms as discussed in MLR work as before
- dummy variables work as before

ökonometrie

Directed Acrylic Graph (DAG)

- complete set off all causal relationships in a graph with arrows
- help explain OMV, reverse causality and conditioning on colliders
- arrows represent direct effect

ökonometrie

Reporting Regression Results

- coefficient estimates
- corresponding standard errors
- number of observations
- R-squared

Single equation: Equation Form

Different specifications: Table

ökonometrie

Hypothesis testing Dummy Variables

- same as usual
- perform hypothesis test on coefficients of dummy variables

ökonometrie

Panel/Longitudinal Data

- consists of time series for each cross sectional data in the set

ökonometrie

Dummy Variable Trap

- if the regression model is to have j intercepts for j different groups w need to include j-1 dummy vars.
- otherwise violation of MLR.3
- base group: overall intercept of model
- dummy variable coefficients: differences in intercepts between this group and base group

ökonometrie

Multiplying y or x by a constant

- if y is multiplied by c then intercept and slope estimate are multiplied by c
if x is multiplied by c then slope is divided by c

if y+m intercept changes by m

if m is added to x the intercept changes by m*β1, slope does not change

ökonometrie

Difference Between errors (u)and residuals (u hat)

- errors occur in poulation and are never actually observed
- residuals occur in our model and are computed from the data

ökonometrie

Ceteris Paribus

All other factors fixed

ökonometrie

What is the Relationship between SST,SSE and SSR?

SST = SSE + SSR

- total Variation is the sum of the explained and unexplained variation

ökonometrie

Cross Sectional Data

- consists of random sample taken at a given time
- order of data irrelevant

ökonometrie

OLS Regression Line

- once we have OLS Estimators we form OLS regression line
- estimated version of population regression function
- we now have a predicted value for y for each value of x (fitted value)

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