Which of the following statements is true about the Ljung-Box test Q4O it tests whether any of the autocorrelations of order 1 through order 4 are statistically significantO t tests whether the stochastic process is stationaryO Under the null, the Q4 statistic follows an F distribution with (1.4) degrees of freedomO The null hypothesis is that the model can be represented by an MA process

Ljung Box test is used to assess the autocorrelation. The null hpythoses is set that…

Which of the following statements is true about the Ljung-Box test 4 O t tests whether any of the autocorrelations of order 1 through order 4 are statistically significant O it tests whether the stochastic process is stationary O Under the null, the Q4 statistic follows an F distribution with (1.4) degrees of freedom O The null hypothesis is that the model can be represented by an MA process

Which of the following statements is true about the Ljung-Box test 4 O t tests whether any of the autocorrelations of order 1 through order 4 are statistically significant O it tests whether the stochastic process is stationary O Under the null, the Q4 statistic follows an F distribution with (1.4) degrees of freedom O The null hypothesis is that the model can be represented by an MA process

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

See similar textbooks

Related questions

Q: You run the regression y₁ = B₁ + B₁ x ₁₁ + B³ 2 x2i Во 1 1i + ε i • variance of ε turns out to be i…

A: Now, the transformed equation with homoskedasticity is:yi=β0+β1x1i+β2x2i+2xi∗ϵi∗ This…

Q: 1.5 Version B. Consider a panel data regression model Yit = Bo + B1 xit + a; + eit where the…

Q: You have data on the training regime of 100m elite runners. For each runner you observe their best…

A: OLS estimation is a technique of regression that helps in determining the unknown parameter values.…

Q: 4. If you reject the null hypothesis Ho: P₁ = 0, which of the statemen RIGHT? (A) x₁ has impacts on…

A: If you reject the null hypothesis then it means that B1 is not equal to 0 and hence it is…

Q: Suppose you are a manager for a carnival game at the local fair. You want to estimate how many…

A: The standard error of the regression shows how far the observed values deviate from the regression…

Q: When we have an omitted variable, the beta estimated can be written: B₁ =B1 + B₂01 The "bias" (how…

A: If there is an omitted variable, our taken variable will show the effect of the omitted variable.…

Q: A shopper wanted to test whether there was a difference in the average waiting times at the…

A: Here, it is required to write the null and alternative hypotheses:

Q: 5. The null hypothesis to test for heteroskedasticity is HO: homoskedasticity True False

A: The Null Hypothesis to test for heteroskedasticity is H0: homoskedasticity

Q: Consider the binary variable version of the fixed effects model with an additional regressor, D1;…

A: Take into account the fixed effects model with a binary variable, but with an additional regression…

Q: 3. If there are two dummy variables Female and Male, should we include both of them in the…

A: Regression Regression is a technique that relates a dependent variable to one or more independent…

Q: If you are interested in investigating the marginal effect of the percentage change of lot size on…

A: Linear regression equation: Y = β1 + β2 X β2 is the slope coefficient. β2 measures the marginal…

Q: A regression of yt on x+ was conducted and an ADF test on the estimated residuals was performed. The…

A: A regression is a statistical approach for describing the actual connection between one or more…

Q: 4-24 Use the data in Problem 4-22 and develop a regres- sion model to predict selling price based on…

A: 4-24 Regression is an econometric technique that depicts the relationship between the dependent and…

Q: 1.5 Version B. Consider a panel data regression model Yit = Bo + B1 xit + a; + eit where the…

A: ANSWER The panel data regression model is given below Yit= 80+ B1. Xit + alpha i + eit Where…

Q: QUESTION 1 Which one of the following assumptions is known as the spherical disturbance assumption?…

A: "Since you have asked multiple questions, we will solve first question for you .. If you want any…

Q: Suppose you have time series data and estimate the following model y = β0 + β1x1 + ε. When you…

A: The estimated model shows that there are correlated observations that is serial correlation. It…

Q: Consider a linear causal model Ya+BX+yW+u, with cov(X, W) > 0. Suppose we do not observe the…

A: In order to compare B and ß, we need to know more about the relationship between X and u and the…

Q: State whether you made a Type I error, a Type II error, or the correct conclusion. b. Children in…

A: In economics, researchers or economists perform various tests and experiments to know the…

Q: Which of the following statements is true? a) None of the other possible answers are true. b)…

A: In order to assess the relationship between a dependent variable and one or more independent…

Q: 1. Suppose you observe (Y, X1, X2, ..., xk) for N observations. For each observation 2, the model +…

A: In matrix form, it is written in a single equation defined for each sample

Q: A regression analysis of company profits and the amount of money the company spent on advertising…

A: In the context of a regression study between firm earnings and advertising spending, the right…

Q: look at the influence of mileage on the sale price of each brand ofautomobile. Postulate the…

A: The objective of the question is to understand the influence of mileage on the sale price of two…

Q: Suppose that the following binary dependent models. The model is based on the driving test of the…

A: The objective of the question is to calculate the probability of passing the driving test for a…

Question

Which of the following statements is true about the Ljung-Box test Q4
O it tests whether any of the autocorrelations of order 1 through order 4 are statistically significant
O t tests whether the stochastic process is stationary
O Under the null, the Q4 statistic follows an F distribution with (1.4) degrees of freedom
O The null hypothesis is that the model can be represented by an MA process

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Step 1: Define The Ljung Box Test

VIEW

Step 2: Choose the correct answer

VIEW

Solution

VIEW

Trending now

This is a popular solution!

Step by step

Solved in 3 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, economics and related others by exploring similar questions and additional content below.

Similar questions

A static model is postulated when a change in the independent variable at time T is believed to have an effect on the dependent variable at period Da change in the independent variable at time t'is believed to have an effect on the dependent varlable for al successive time periods. Ca change in the independent variable at time tis telieved to have an immediate effect on the dependent variable. da change in the independent variable at time T does not have any effect on the dependent variable
Let wage denote hourly wages, educ denote years of education, and define the dummy variable: if educ > 12 D = if educ < 12 i.e. we can think of D as a dummy variable indicating graduation from high school. Suppose we want to test the null hypothesis that the marginal return to education for every year after high school is the same as the marginal return to education for each year before high school (against the alternative that they are different). Which model and test would accomplish this goal? O a. Estimate wage = B1 + B2 educ + ß3 D + e and test Ho : ß3 = B2 against H1 : ß3 # B2. O b. Estimate wage = ß1 + B2educ + ß3 D + e and test Ho : ß3 = 0 against H1 : ß3 # 0. Estimate wage = B1 + B2educ + B3(educ + D) + e and test Ho : ß3 = 62 against H1 : B3 # B2. O d. Estimate wage = B1 + B2educ + B3(D × (educ – 11)) + e and test Ho : ß3 = B2 against H : B3 # B2. c. O e. Estimate wage = Bi + B2educ + ß3(D × (educ – 11)) + e and test Ho : ß3 = 0 against H1 : ß3 + 0.
= 3+5Z+v, Suppose we have the following causal model Y where cov(Z, v) = 0. However, a precise measure of Z is not available. Instead, we have a noisy measure X of Z, that is, X = Z + w with var(w) > 0. Suppose the error w is a classical measurement error so that cov(w, Z) = cov(w, v) = 0. What can you conclude about the limit of the OLS estimator, namely ß₂2 = cov(X, Y)/var(X)? 0 B² = 0 B 5 OB > 0 U
Question 1) Which of the following can cause the usual OLS t statistics to be invalid (that is, not to have t distribu- tions under HO)? (i) Heteroskedasticity. (ii) A sample correlation coefficient of 95 between two independent variables that are in the model. (iii) Omitting an important explanatory variable Question 2) Which of the following can cause OLS estimators to be biased? (i) Heteroskedasticity. (ii) Omitting an important variable. (iii) A sample correlation coefficient of .95 between two independent variables both included in the model.
The following model studies human welfare using the General Social Survey in the US: happy = 0.014 + 0.209regattend + 0.103occattend + 0.027income + 0.009educ +0.003 female where happy is a dummy variable equal to one if a person is happy, and 0 otherwise: regattend is a dummy variable equal to one if a person regularly attends church, and 0 otherwise: occattend is a dummy variable equal to one if a person occasionally attends church, and 0 otherwise; income is family income in tens of thousands: educ is years of schooling: female = 1 if female. = 0 otherwise Interpret the impact of religion on happiness.
1 Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relating fertility to years of education is kids = Bo + Bjeduc + u, where u is the unobserved error. (i) What kinds of factors are contained in u? Are these likely to be correlated with level of education? Will a simple regression analysis uncover the ceteris paribus effect of education on fertility? Explain. (ii)
Consider the regression model Yi = β0 + β1Xi + ui.a. Suppose you know that β0 = 0. Derive a formula for the least squaresestimator of β1.b. Suppose you know that β0 = 4. Derive a formula for the least squaresestimator of β1?
If you included both time and entity fixed effects in the regression model which includes a constant, then: O a. you have perfect multicollinearity. O b. you can exclude the constant and one entity binary variable to estimate the model. you can exclude the constant and one time binary variable to estimate the model. O d. you can exclude one time binary variable and one entity binary variable to estimate the model. O e. All of the above. Of. None of the above.
3)Suppose we are testing a null hypothesis against a two-sided alternative, then the alternative can be written as: A. E(Y) > μY,0 B. E(Y) = μY,0 C. ≠ μY,0 D. E(Y) ≠ μY,0
Suppose we are interested in evaluating the impact on wages of being a college graduate and of residing in California. To this end we define the following dummy variables if college graduate if not college graduate coll = ncoll = if not college graduate if college graduate 1 cali = if residing in California S 1 if not residing in California ncali = if not residing in California if residing in California and for wages denoting yearly wages, we estimate the following model of returns to education wages = B1 coll+ B2ncoll + B3 cali + B4(coll x cali) + e where E[e|coll, cali] = 0. Which parameter or combination of parameters measures the increase in expected wages from obtaining a college degree (comparing to not having a college degree) when residing California? O a. None of the other options is correct O b. Bi – B2 O c. B1 – B2 + ß4 O d. B4 O e. Bi + B3 – ßi – B4 O f. Bi + B4 – ß2 – B4 Clear my choice
Econometrics Thomas Eisensee and David Stromberg wanted to measure how much news coverage of a foreign disaster impacted the amount of disaster relief provided by the U.S. government. They argue that the simple relationship would be biased. Let X = Minutes of News Coverage and Y= Disaster Aid. Choose a variable X2 that could bias the simple relationship. This variable should impact the amount of coverage and impact the amount of aid for reasons other than purely news coverage. Eisensee and Stromberg introduce an instrument Z = During the Olympics. Explain how Z could satisfy the relevant and exogenous criteria. Explain how you could use Z to estimate the impact of X on Y free from X2 bias. Hint: you should mention two stages.
Suppose the researcher considers the following model : Wage = Bo+B,Female + u, and runs OLS, using wage data on 250 randomly selected male workers and 280 female workers. The researcher has obtained the estimated equation as Wage = 15 (1.00) 3 Female, R = 0.05. (0.5) In the equation, Wage is measured in dollars per hour, Female is a binary variable that is equal to 1 if the person is a female and O if the person is a male. The numbers in the parentheses are the standard errors of the coefficients. Which Statement is NOT correct? The coefficient of Female, -3.00, is statistically significant at 5%. O The p-value for the test that Ho: B = 0, H : B 0 is less than 0.05. This regression may suffer omitted variable bias. R Since insignificant. is too low, the wage difference between men and women is The researcher can increase R- by including more regressors in the model.