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18 Cards in this Set

  • Front
  • Back
What is assumption I and what are its violations?
Dependent variable is a linear function of a specific set of independent variables plus a disturbance term.

Y=Xß+Σ

Violations:
Wrong regressors
Nonlinearity
Changing parameters
What is assumption II and what are its violations?
Expected value of a disturbance term is zero.

EΣ=0

Violations:
Biased Intercept
What is assumption III and what are its violations?
Disturbances have a uniform variance and are uncorrelated

EΣΣ'=σ²I

Violations:
Heteroskedasticity
Autocorrelated Errors
What is assumption IV and what are its violations?
Observations on independent variables can be considered fixed in repeated samples.

X is fixed in repeated samples

Violations:
Errors in variables
Autoregression
Simultaneous equations
What is assumption V and what are its violations?
No exact linear relationships between independent variables and more observations than independent variables.

Rank of X=K≤T

Violations
Perfect multicollinearity
What is wrong regressors and what are the consequences?
Violation of assumption I: when you include regressors that should not be included in the model, or you do not include regressors that should be in the model

Consequences:
Omitted variable bias
Parameter inconsistency
What is nonlinearity and what are the consequences?
A violation of assumption I: When the true relationship between the dependent variable and independent variables is non-linear.

Consequences:
Biased parameter estimates
Inflated standard errors
Lower R Square
What are changing parameters and what are the consequences?
Violation of assumption I: any time your parameters do not stay constant during the time period in which they were collected

Consequences:
Biased parameter estimates
Inflated standard errors
Lower R square
What is a biased intercept and what are the consequences?
Violation of assumption II: when the expected value of your error term is not zero.

Consequences:
Biased intercept
Biased parameters
What is heteroskedasticity and what are the consequences?
Violation of assumption III: When the shape of the disturbance term is not constant

Consequences:
Inefficient parameter estimates
Loss of precision
What are autocorrelated errors and what are the consequences?
Violation of assumption III: disturbances are correlated, usually over time

Consequences:
Loss of precision
What are errors in variables and what are the consequences?
Violation of assumption IV: variables are incorrect because they are measured incorrectly from one sample to the next

Consequences:
Biased parameters
Inconsistent parameters
What is autoregression and what are the consequences?
Violation of assumption IV: using the value of the lagged dependent varaible as an independent variable

Consequences:
Biased parameters
Inconsistent parameters
What are simultaneous equations and what are the consequences?
Violation of assumption IV:
phenomena determined by simultaneous interaction of several variables
What is perfect multicollinearity and what are the consequences?
Violation of assumption V:
variables are linearly related to each other

Consequences:
Unstable parameter estimates
Loss of precision
Cross Sectional Data
Multiple economic units for the same time period. (One observation only)

Example: asking about individuals' voting preference for this year, one time only.
Times Series Data
Uses multiple observations with the same economic unit over time

Example: asking one student whether they voted Republican or Democrat in each of the past presidential elections.
Panel Data
Cross sectional time series data (multiple observations on more than one economic unit over time)

Example: asking multiple students whether they voted Republican or Democrat in each of the past presidential elections