Lecture 2 Key Terms Flashcards Preview

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Flashcards in Lecture 2 Key Terms Deck (11)
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1

Static regression model

describes the contemporaneous relationship between variables y and z

2

finite distributed lag model

describes the relationship between past realisations of the variable as well as the present

3

stochastic process

a sequence of random variables indexed by time defined on a common probability space

4

weak stationarity

mean, variance and autocovariances are stable; mean and variance are constant over time and the covariance only depends on the lag between the variables and not the initial starting point

5

autocorrelation function / correlogram

characterises dependencies among observations, and depicts the length and strength of the memory of the process

6

white noise process

a process with zero mean and constant variance

7

serial (un)correlation

zero correlation across time periods

8

strong exogeneity

assumption that the error at time t is uncorrelated with each explanatory variable across every time period

9

stability condition

| theta | < 1 in the ar(1) model. Maintains stationarity in the model and prevents high persistence

10

weak dependence

autocorrelation tends towards zero as the gap between the variables increases

11

Contemporaneous exogeneity

errors and their contemporary explanatory variables are uncorrelated