# Econometricscards

Serial Correlation
The relationship between a variable and itself over various time intervals as a function of the delay
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Trend
An underlying pattern of behaviour
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Stochastic Process
A series of random variables indexed by time
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Sample (time series)
The one realised path of the series out of the many possible paths that it could have taken
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Contemporaneous Relation
The relationship occurs in one period
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Impact Multiplier
The immediate effect of a one unit change in x on y
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Long-run Multiplier
The total effect of a one unit change in x on y. The sum of multipliers on all x variables.
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BLUE
The unbiased estimator with the lowest variance
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Biasedness
The difference between the expected value of an estimator and its true value
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Consistency
An estimator for which the estimate converges in probability to its true value as the number of data points increases indefinitely
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Efficiency
The estimator that attains the true value of a parameter using the fewest observations
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Asymptotic Normality
A parameter that is rescaled to be approximated by a Normal distribution
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Homoskedastcity
The variance of the errors is the same and does not change with the independent variable
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Time Trend
A variable equal to a time index in a given period. Used to control for exogenous increases in dependent variables, usually a proxy for technological progress.
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Order (FDL Model)
The number of previous periods included in the regression
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IID
Independent and Identically Distributed. Each random variable has the same probability distribution as the others and all are mutually independent
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Stationary Process
A stochastic process whose joint probability distribution does not change when shifted in time.
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Weakly Dependent (Time Series)
A time series for which the elements are less correlated the further they are from each other.
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Endogeneity
When an explanatory variable is correlated with the error term.
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Static Model
A model in which only contemporaneous explanatory variables affect the dependent variable.
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Sequentially Exogenous
The error term in the current period has a zero mean, conditional on all current and past explanatory variables.
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Contemporaneously Exogenous
The error term in the current period is uncorrelated with the explanatory variables in the current period.
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Strictly Exogenous
The error term has zero expectation, conditional on the explanatory variables in all time periods.
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Covariance Stationary
A process with constant mean and variance for which the covariance between an two random variables depends only on the distance between them.
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Autoregressive Process Order 1
A process whose current value depends linearly on its most recent value plus a random disturbance.
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Moving Average Process Order 1
A process generated as the linear function of the current value and one lagged value of a zero mean, constant variance uncorrelated process.
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Unit Root Process
A highly persistent process where the current value is equal to the previous value, plus a weakly dependent disturbance.
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Noise Process
A serially uncorrelated, zero-mean, constant variance process.
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Trend-Stationary Process
A process that is stationary and usually weakly dependent once a time trend has been removed.
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Integrated Process Order 0
A stationary, weakly dependent process that satisfies the law of large numbers and central limit theorem.
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Integrated Process Order 1
A process that must be first-differenced in order to produce an I(0) process.
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Asymptotically Uncorrelated
As the distance between two elements increases, their correlation tends to zero. They are almost independent.
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## Other cards in this set

### Card 2

Trend

#### Back

An underlying pattern of behaviour

### Card 3

#### Front

Stochastic Process

#### Back ### Card 4

#### Front

Sample (time series)

#### Back ### Card 5

#### Front

Contemporaneous Relation

#### Back ## Comments

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