Homework Answers
Answer
Option 3
Y=b0+b1X where X=time
The independent variable is x and the dependent variable is y
both of the variables should be linear means should not be log or power of exponential and that is the equation in option 3.
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Question 3 Which of these equations is a linear model? O Y = bo + b1...
Problem 3: Assume that 'nature' behaves according to the following linear additive model: Y = Bo...
Problem 3: Assume that 'nature' behaves according to the following linear additive model: Y = Bo + B1X +€, where ε is a Gaussian random variable N (0,02). Using this model, nature generates the following training dataset: D = {(Li, yi)}}–1 = {(–2, 47/2),(-1, -3), (0,0), (1,3), (2,7/2)}. Please, answer the questions below without the help of any computer software: a. Compute the estimates of Bo and @1 for a linear estimator û = Bo + 1X using the data...
2. For the quadratic model, where Y = Bo + B1 X1 + B2 X1 2...
2. For the quadratic model, where Y = Bo + B1 X1 + B2 X1 2 + ε, set forth the formula used to calculate the elasticity of Y with respect to X1.
Exercise 5 Consider a linear model with n = 2m in which Yi = Bo +...
Exercise 5 Consider a linear model with n = 2m in which Yi = Bo + Bici + Eigi = 1,..., m, and Yi = Bo + B2X1 + Ei, i = m + 1, ...,n. Here €1,..., En are i.i.d. from N(0,0), B = (Bo, B1, B2)' and o2 are unknown parameters, X1, ..., Xn are known constants with X1 + ... + Xm = Xm+1 + ... + Xn = 0. 1. Write the model in vector form...
2. Consider the simple linear regression model: where e1, .. . , es, are i.i.d. N (0, o2), for i= 1,2,... , n. Suppose...
2. Consider the simple linear regression model: where e1, .. . , es, are i.i.d. N (0, o2), for i= 1,2,... , n. Suppose that we would like to estimate the mean response at x = x*, that is we want to estimate lyx=* = Bo + B1 x*. The least squares estimator for /uyx* is = bo bi x*, where bo, b1 are the least squares estimators for Bo, Bi. ayx= (a) Show that the least squares estimator for...
Question 1 Consider the simple regression model (only one covariate): y= BoB1 u Let B1 be the OLS estimator of B1. a) W...
Question 1 Consider the simple regression model (only one covariate): y= BoB1 u Let B1 be the OLS estimator of B1. a) What are the six assumptions needed for B1 to be unbiased, have a simple expression for its variance, and have normal distribution? (3 points) b) Under Assumptions 1-6, derive the distribution of B1 conditional on x\,..., xn. (3 points) In lecture we described how to test the null hypothesis B1 bo against the alternative hypothesis B1 bo, where...
The equation for a straight line (deterministic model) is y = Bo +Byx. If the line...
The equation for a straight line (deterministic model) is y = Bo +Byx. If the line passes through the point (-6,1), then x = -6, y = 1 must satisfy the equation; that is, 1 = Bo +(-6). Similarly, if the line passes through the point (9,2), then x=9, y=2 must satisfy the equation; that is, 2 = Bo + B1(9). Use these two equations to solve for Bo and By; then find the equation of the line that passes...
1. Consider the following regression model: Y; = Bo + B1 * Xi + Ei S&x=21...
1. Consider the following regression model: Y; = Bo + B1 * Xi + Ei S&x=21 SSTx = 10, SST = 90, R2 = 0.6 n = 11 x= 10, y = 30 Where y = output in pounds and x is the amount of labor used measured in hours. a. Estimate a 95% confidence interval for ß, . What is the interpretation of this confidence interval?
Consider the model, Y; = Bo + B1 Xi+Uj, where you suspect Xi is endogenous. You...
Consider the model, Y; = Bo + B1 Xi+Uj, where you suspect Xi is endogenous. You have an exogenous instrument and you estimate the first stage to recover the residuals, Vhatj. You want to test for endogeneity so you estimate the following model using OLS: Y= Bo + B1 Xi + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors Constant 2.63 0.98 X 0.97 0.57 Vhat 0.47 0.10 Please select your...
3. Consider simple linear regression model yi = Bo + B12; + &; and B. parameter...
3. Consider simple linear regression model yi = Bo + B12; + &; and B. parameter estimate of the slope coefficient Bi: Find the expectation and variance of 31. Is parameter estimate B1 a) unbiased? b) linear on y? c) effective optimal in terms of variance)? What will be your answers if you know that there is no intercept coefficient in your model?
Consider the model, Yi = Bo + B1 Xi + Uj, where you suspect Xi is...
Consider the model, Yi = Bo + B1 Xi + Uj, where you suspect Xi is endogenous. You have an exogenous instrument and you estimate the first stage to recover the residuals, Vhati. You want to test for endogeneity so you estimate the following model using OLS: Y; = Bo + B1 Xì + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors constant 2.96 0.47 X 0.75 0.85 Vhat 0.37 0.15...
Problem 3: Assume that 'nature' behaves according to the following linear additive model: Y = Bo + B1X +€, where ε is a Gaussian random variable N (0,02). Using this model, nature generates the following training dataset: D = {(Li, yi)}}–1 = {(–2, 47/2),(-1, -3), (0,0), (1,3), (2,7/2)}. Please, answer the questions below without the help of any computer software: a. Compute the estimates of Bo and @1 for a linear estimator û = Bo + 1X using the data...
2. For the quadratic model, where Y = Bo + B1 X1 + B2 X1 2 + ε, set forth the formula used to calculate the elasticity of Y with respect to X1.
Exercise 5 Consider a linear model with n = 2m in which Yi = Bo + Bici + Eigi = 1,..., m, and Yi = Bo + B2X1 + Ei, i = m + 1, ...,n. Here €1,..., En are i.i.d. from N(0,0), B = (Bo, B1, B2)' and o2 are unknown parameters, X1, ..., Xn are known constants with X1 + ... + Xm = Xm+1 + ... + Xn = 0. 1. Write the model in vector form...
2. Consider the simple linear regression model: where e1, .. . , es, are i.i.d. N (0, o2), for i= 1,2,... , n. Suppose that we would like to estimate the mean response at x = x*, that is we want to estimate lyx=* = Bo + B1 x*. The least squares estimator for /uyx* is = bo bi x*, where bo, b1 are the least squares estimators for Bo, Bi. ayx= (a) Show that the least squares estimator for...
Question 1 Consider the simple regression model (only one covariate): y= BoB1 u Let B1 be the OLS estimator of B1. a) What are the six assumptions needed for B1 to be unbiased, have a simple expression for its variance, and have normal distribution? (3 points) b) Under Assumptions 1-6, derive the distribution of B1 conditional on x\,..., xn. (3 points) In lecture we described how to test the null hypothesis B1 bo against the alternative hypothesis B1 bo, where...
The equation for a straight line (deterministic model) is y = Bo +Byx. If the line passes through the point (-6,1), then x = -6, y = 1 must satisfy the equation; that is, 1 = Bo +(-6). Similarly, if the line passes through the point (9,2), then x=9, y=2 must satisfy the equation; that is, 2 = Bo + B1(9). Use these two equations to solve for Bo and By; then find the equation of the line that passes...
1. Consider the following regression model: Y; = Bo + B1 * Xi + Ei S&x=21 SSTx = 10, SST = 90, R2 = 0.6 n = 11 x= 10, y = 30 Where y = output in pounds and x is the amount of labor used measured in hours. a. Estimate a 95% confidence interval for ß, . What is the interpretation of this confidence interval?
Consider the model, Y; = Bo + B1 Xi+Uj, where you suspect Xi is endogenous. You have an exogenous instrument and you estimate the first stage to recover the residuals, Vhatj. You want to test for endogeneity so you estimate the following model using OLS: Y= Bo + B1 Xi + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors Constant 2.63 0.98 X 0.97 0.57 Vhat 0.47 0.10 Please select your...
3. Consider simple linear regression model yi = Bo + B12; + &; and B. parameter estimate of the slope coefficient Bi: Find the expectation and variance of 31. Is parameter estimate B1 a) unbiased? b) linear on y? c) effective optimal in terms of variance)? What will be your answers if you know that there is no intercept coefficient in your model?
Consider the model, Yi = Bo + B1 Xi + Uj, where you suspect Xi is endogenous. You have an exogenous instrument and you estimate the first stage to recover the residuals, Vhati. You want to test for endogeneity so you estimate the following model using OLS: Y; = Bo + B1 Xì + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors constant 2.96 0.47 X 0.75 0.85 Vhat 0.37 0.15...
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