1. Intro To Time Series Analysis Flashcards

1
Q

What is time series data?

A

It consists of observations on a given economic unit

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2
Q

Signal

A

The systematically prefictable component of the time series

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3
Q

Noise

A

The component whcuh makes time series difficult to predict

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4
Q

What does the signal consust of?

A

Trend, seasonal and cycle

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5
Q

What is the trend?

A

Thr persistent tendency of the times series to increase or decrease over time

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6
Q

What is the seasonality?

A

A type of cyclicality where the times series has a tendency to increase or decrease in a predictable or regular way

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7
Q

What is a lagged variable

A

If Xt: t=1,2,…,T then Xt-1: t=2,3,…,T is the value of the variable in period t-1 or lagged one period

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8
Q

What is a lead or forward variable?

A

The opposite of a lag variable

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9
Q

Differenced variable

A

The difference between the current value of the variable and its value in period t-1

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10
Q

What is significant of a a log first difference variable?

A

It gives the proportional change % in X between period t-1 and t, it is also known as the rate of return

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11
Q

Stationary variable

A

A variable that isnt explosive, nor trending, nor wandering aimlessly wuthout returning to its mean

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12
Q

What is true of the stationarity of most macro variables?

A

They are non staionary but theut first differences or returns tend to be stationary

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13
Q

When can standard regression analysis be carried out on variables?

A

When variables are stationary or when certain conditions are given

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14
Q

What is the autocorrelation function?

A

Autocorrelation is the correlation involving a variable and its past (lag)

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15
Q

What is the autocorrelation of order 0

A

The correlation between a variable and itself so it is 1

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16
Q

Correlogram

A

A sample ACF

17
Q

Partial Autocorrelation function (PACF)

A

The correlation between two specified points conditional on all other autocorrelations that come in between

18
Q

Cross correlogram

A

The correlations between two time series variables Y and X calculated at various lags

19
Q

When are X and Y not cross correlated

A

When corr(Yt,Xt+k)=0 for all values of k

20
Q

Dynamic relationship

A

A change in a given variable today has an impact on the same variable, or ither variables in future time periods

21
Q

What are dristributed lagged effects

A

Effects which have an impact over many future periods

22
Q

What are the ways of capturing a dynamic relationship?

A
  • distributed lag (DL) model
  • autoregressive model (AR)
  • autoregressive distributed lags model (ARDL)
23
Q

What is the distributed lag (DL) model?

A

A model where the dependent variable y is a function of current and past values of an explanatory variable x

24
Q

What is an autoregressive (AR) model?

A

A model where the dependent variable y is a function of current and past values of y its own lags

25
Q

What is an autoregressive distributed lags (ARDL) model?

A

A model where the dependent variable y is a function of current and past values of an explanatory variable x and its own lags y

26
Q

What is the long run multiplier of a DL model?

A

Bo+B1+B2+…

27
Q

What is necessary for an AR model to be stable?

A

Alpha1 must be between -1 and 1