Econometric - Lecture 2

Econometric - Lecture 2

University

5 Qs

quiz-placeholder

Similar activities

6 DA

6 DA

University

9 Qs

Test on Applied Econometrics

Test on Applied Econometrics

University

10 Qs

DERMATITIS VERMINOSA REPTANTE

DERMATITIS VERMINOSA REPTANTE

University

10 Qs

Econometrics

Econometrics

University

10 Qs

Statistical Methods 1- March quiz

Statistical Methods 1- March quiz

University

10 Qs

Anafilaxia

Anafilaxia

University

10 Qs

Liderazgo

Liderazgo

University

10 Qs

¿Cuánto sabes de psicología social comunitaria?

¿Cuánto sabes de psicología social comunitaria?

University

8 Qs

Econometric - Lecture 2

Econometric - Lecture 2

Assessment

Quiz

Other

University

Medium

Created by

Elya Nabila

Used 2+ times

FREE Resource

5 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is not a diagnostic checking?

Heteroscedasticity

Autocorrelation

Multicollinearity

Demean

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following techniques to test the autocorrelation?

White test

Breusch-Pagan LM test

Ramsey Reset test

Jarque-Bera test

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is the correct inference for log-linear model?

1 unit change in X will induce a β2 unit change in Y

1 percent change in X will induce a β2/100 unit change in Y

1 unit change in X will induce a 100β2 percent change in Y

1 percent change in X will induce a β2 percent change in Y

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is correct about the correlation?

Correlation measures the strength of the linear relationship between two variables.

The correlation between two random variables is a dimensionless number between 1 and -1.

Correlation misses nonlinearities completely.

All of the above.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which one is correct about the causality?

Bidirectional :  ‘x’ being a cause of ‘y” but “y” is not being a cause of “x” (x à y) (y x)

Unidirectional :  ‘x’ being a cause of ‘y” and “y” is being a cause of “x” (x y)

Neutral : ‘x’ is not being a cause of ‘y” and “y” is not being a cause of “x”

Causality cannot be used for time series.