Lecture 1 Key Terms Flashcards Preview

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Flashcards in Lecture 1 Key Terms Deck (15)
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1

Conditional mean function

the mean of the outcome y conditional on x , the expected value of y conditional on x, conditional expectation of y given x

2

Population regression function

e( y | x ) = beta0 + beta1x

3

simple linear regression model

y = beta0 + beta1x + u

4

time series

a sequence of data points indexed by time

5

cross sectional data

consists of a sample of units (e.g. individuals, states, households) taken at a given point in time

6

panel data

consists of a time series for each cross sectional member in the set

7

perfect multicollinearity

the matrix X is of full rank if none of the columns are linear transformations of each other

8

unbiased estimator

the difference between the expected value of the estimator and the true value of the parameter is zero

9

consistent estimator

the estimator converges in probability to the true parameter value as the sample size approaches infinity

10

homoskedastic

all random variables in the sequence have the same variance

11

heteroskedastic

at least 1 random variable in the sequence has different variance

12

asymptotically normally distributed

as the number of observations increases to infinity, the distribution of random variables converges to a normal distribution

13

gauss markov theorem

under homoskedasticity the ols estimator is efficient and the best linear unbiased estimator of beta

14

efficiency

the spread / variance of an estimator around a parameter

15

standard error

square root of the variance