Part 2 Flashcards

1
Q

Why should we be interested in analyzing unit root/nonstationary processes?

A
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2
Q

What happens when lambda = 1?

A
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3
Q

What is a unit root process?

A

An I(1) process

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4
Q

How can a random walk be rewritten?

A
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5
Q

Why is a random walk non-stationary?

A
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6
Q

Why is the sample mean of a random walk diverging?

A
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7
Q

What does superconsistency imply?

A
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8
Q

When is a process a linear process? (Give the definition)

A
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9
Q

What is the Beverage-Nelson decomposition? (definition)

A
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10
Q

What is the permanent-transitory decomposition (or trend-cycle decomposition)?

A
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11
Q

What is the concept of Brownian motion?

A
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12
Q

Show the following:

A
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13
Q

What is Standard Brownian motion?

A
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14
Q

Give the definition of Standard Brownian motion?

A
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15
Q

What is the definition of Multivariate Brownian motion (or a standard Wiener process)?

A
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16
Q

How can a Wiener process be transformed with matrix P?

A
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17
Q

What is the Functional Central Limit Theorem?

A
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18
Q

What is the multivariate central limit theorem?

A
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19
Q

What is the continuous mapping theorem?

A
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20
Q

What do the O_p and o_p notation mean?

A
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21
Q

What are the six rules of the O_p and o_p notation?

A
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22
Q

What are the two representations for a multivariate root process (of the following process)?

A
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23
Q

What are the three variances of the multivariate unit root process?

A
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24
Q

What is the distribution of?

A

[NOTE: Misschien derivation toevoegen, maar kan me niet voorstellen dat echt boeit]

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25
Q

What is the distribution?

A

This is often called the Dickey-Fuller distribution

26
Q

How is the I(1) hypothesis defined? How is this tested?

A

[Misschien nog derivatie toevoegen]

27
Q

What is the problem that Phillips-Perron tries to solve?

A

Tests for I(1)

28
Q

What should k be for Dicky-Fuller?

29
Q

What is a spurious regression?

30
Q

What happens in case of a spurious regression with the parameter estimate beta hat?

31
Q

What three things do we expect in case of spurious regression and what does actually happen?

32
Q

What is the idea of cointegration?

33
Q

What is the definition of cointegration?

34
Q

What is the variable for cointegrating space? And the cointegrating rank?

35
Q

What is the Lag representation of an MA model? What is a VAR model?

36
Q

When is a random matrix A singluar?

A

r is rank, m is matrix size

37
Q

What is the Lag notation of a VECM model?

38
Q

What is the idea behind the Granger representation thm?

39
Q

What is the simplest method to consistently estimate a unique cointegrating vector?

40
Q

What is the method of static least squares?

41
Q

What is the definition of S_t, Lambda, and Sigma?
[VERWIJDER]

A

[Note: Mogelijk nog dingen van static least squares, maar dat voelt als totaal onnodig]

42
Q

What is the DOLS estimator?

43
Q

Why is the DOLS better than SLS? Which problems remain?

44
Q

What is the ECM approach?

45
Q

When has x_t to be weakly exogenous? When do elements in x_2, t?

46
Q

What is the FMOLS method?

47
Q

What do we need for FMOLS estimation?

48
Q

What is a residual based test for cointegration (Engle-granger)?

49
Q

Show that the residual based tests for cointegration are consistant.

50
Q

What is an assumption of cointegrated systems? (Finite order)

51
Q

What is an assumption of cointegrated systems? (cointegrated)

52
Q

What is a VECM model?

53
Q

What happens to a VECM when r=m, r=0 or any in between?

54
Q

What is the main idea behind Johansen analysis?

55
Q

What are the three steps of Johansen analysis?

56
Q

What are the five steps in ML analysis of a VECM?

57
Q

What is the main idea behind the trace test?

58
Q

What is the LR test statistic of the trace test?

59
Q

How do we select a rank from the trace test?

60
Q

What is the idea and formula behind the maximum eigenvalue test?

61
Q

What are the advantages of FIML estimates?

62
Q

How can we do other test using a VECM?