a bivariate regression of the form:
Y i = β o+β 1X i + u i
What economic meaning, if any, does the coefficient β1 have in your model? What does the estimated value of this parameter indicate about the relationship between X and Y?
Homework Answers
Dependent variable is Consumption :C
Independent variable is disposable income: Yd
So beta 1 is the regression coefficient of C on Yd
Beta1= .959305
It is called marginal propensity to consume MPC
Thus it implies that if disposable income rises by 1 $, then Consumption rises by .959305 $
Thus two variables are positively related
1. Autocorrelation test Given the model Consumption, = a + B.Year + B Disposible Income, +E,...
1. Autocorrelation test Given the model Consumption, = a + B.Year + B Disposible Income, +E, and the estimated model: Model 1: OLS, using observations 1959-1995 (T = 37) Dependent variable: c t-ratio p-value const time Disposable Income Coefficient Std. Error 2707.84 385.254 80.9122 13.6539 0.508123 0.0460444 Mean dependent var Sum squared resid R-squared F(2, 34) Log-likelihood Schwarz criterion rho 11328.65 304975.4 0.998650 12577.63 -219.3165 449.4657 0.551018 S.D. dependent var S.E. of regression Adjusted R-squared P-value(F) Akaike criterion Hannan-Quinn Durbin-Watson...
The following show the results of regression: Housing Sold = b0 + b1 permit +b2 price...
The following show the results of regression: Housing Sold = b0 + b1 permit +b2 price + b3 employment Dependent Variable: SOLD , Method: Least Squares Date: 03/15/20 Time: 14:59 Included observations: 108 Variable Coefficient Std. Error t-Statistic Prob. C -61520.76 167763.0 -0.366712 0.7146 PERMIT 15.98282 .280962 12.47721 0.0000 PRICE ...
1. Propose any one interaction hypothesis among the set of independent variables for each of the ...
1. Propose any one interaction hypothesis among the set of
independent variables for each of the two models and provide
rationales for your proposition.
2. Test whether your proposition is supported by the data
ependent Variable SALARY Method: Least Squares Date: 03/28/19 Time: 17:11 Sample: 1 447 Included observations: 447 Variable Coefficient Std. Error t-Statistic Prob TOTCOMP_MEYU TENURE_MEYU AGE_MEYU SALES_MEYU PROFITS_MEYU ASSETS_MEYU 857.5376 596.2939 1.438112 0.1511 0.014302 0.002179 6.564320 0.0000 27.40055 9.066757 3.022090 0.0027 7.034349 10.952730.642246 0.521 0.013978 0.006320 2.211800...
Consider the regression output below and answer each question. The frequency is quarterly,and the variables are...
Consider the regression output below and answer each question.
The frequency is quarterly,and the variables are defined at annual
rates as follows: INT_RATE_3M is the 3-Month Treasury Bill,
INF_RATE is the inflation rate, UNRATE is the unemployment rate,
and EMP_GROWTH corresponds to the employment growth rate.
a)How is the goodness of fit? How can you tell?
b)For each of the 3 independent variables in the regression,
state if their coefficient is statistically significant at 5%
level.
c)For the same variables...
Predict the value of a traditional style house with 2500 square feet of area, that is 20 years old, with 3 bedrooms and two bathrooms, which is owner occupied at the time of sale, with a fireplace, an...
Predict the value of a traditional style house with 2500 square
feet of area, that is 20 years old, with 3 bedrooms and two
bathrooms, which is owner occupied at the time of sale, with a
fireplace, and not on the waterfront. Provide the “corrected
predictor”. (Prediction in the log-linear model.) need help with
the corrected predictor.
Sample: 1 1080 Included observations: 1080 Variable Coefficient Std. Error t-Statistic Prob 3.971283 0.045870 86.57653 0.0000 0.030016 0.001388 21.62198 0.0000 0.031281 0.016548 1.890282...
I have a model from Gretl which I'm trying to copy the latex code for so l can paste in a web browser. However, when...
I have a model from Gretl which I'm trying to copy the latex
code for so l can paste in a web browser. However, when l submit
the code I'm getting weird results and the table is not coming out
how l would like. How do l get the latex code from the Gretl model
to format exactly the same on this web browser.
Latex Code from copying the output:
\begin{center}
Model 1: OLS, using observations 1--60\\
Dependent variable: l\_Y\\...
Attached are the results of a diagnostic test on an estimated model, autocorrelation, heteoskedasticity and non-normal...
Attached are the results of a diagnostic test on an estimated
model, autocorrelation, heteoskedasticity and non-normality
respectivey, can you please comment on the results and state the
conclusion for each test using a 5% significance level
Breusch-Godfrey Serial Correlation LM Test F-statistic Obs R-squared 0.7659 0.7612 0.458959 Prob. F(4,438) 1.861565 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID Method: Least Squares Date: 05/22/19 Time: 22:02 Sample: 1982M01 2019M02 Included observations: 446 Presample missing value lagged residuals set to zero. Coefficient Std....
We want to look at potential predictors of movie revenues. Model 1: OLS, using observations l-609...
We want to look at potential predictors of movie revenues. Model 1: OLS, using observations l-609 Dependent variable: USGrossM coefficient std. error t-ratio p-value --------------------------------------- ------------------------ const -52.3692 15.4296 -3.394 0.0007 *** BudgetM 0.972348 0.0484576 20.07 4.89e-069 *** RunTimemin 0.387214 0.155146 2.496 0.0128 CriticScoreRotter 0.640257 0.0953758 6.713 4.40e-011 *** Mean dependent var Sum squared resid R-squared F(3, 605) Log-likelihood Schwarz criterion 75.81977 2004759 0.517227 216.0592 -3330.345 6686.337 S.D. dependent var S.E. of regression Adjusted R-squared P-value (F) Akaike criterion Hannan-Quinn...
Consider time series yt , defined as the daily percentage change in SP500 index. A researcher...
Consider time series yt , defined as the daily
percentage change in SP500 index. A researcher estimated the
following model:
(a) There is one partial
autocorrelation coefficient that you can find from the estimation
result. What is the value of it? What is order (k ) of
it?
(b) Test the null hypothesis that the partial autocorrelation
coefficient that you have is zero against the alternative that it
is not zero.
Dependent Variable: GROWTH Method: Least Squares Date: 03/08/15 Time:...
An interpretation is needed for the below E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc...
An interpretation is needed for the below
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: GDPPERCAPITA Method: Least Squares Date: 01/19/19 Time: 21:27 Sample (adjusted): 2 264 Included observations: 142 after adjustments Variable Coefficient Std. Error t-Statistic Prob EDUEXPENSES 3409.799982.7287 3.469726 0.0007 60.62503 50.33194 1.204504 0.2305 248.8894 62.51844 3.981056 0.0001 299.3805 136.4002 2.194869 0.0299 529.2544297.0670 1.781599 0.0771 VALUEADDAGRI 840.2738 141.5672 -5.935512 0.0000 2227.235 7946.208 0.280289 0.7797 EXPORTS FDINFLOWS GSAVING...
1. Autocorrelation test Given the model Consumption, = a + B.Year + B Disposible Income, +E, and the estimated model: Model 1: OLS, using observations 1959-1995 (T = 37) Dependent variable: c t-ratio p-value const time Disposable Income Coefficient Std. Error 2707.84 385.254 80.9122 13.6539 0.508123 0.0460444 Mean dependent var Sum squared resid R-squared F(2, 34) Log-likelihood Schwarz criterion rho 11328.65 304975.4 0.998650 12577.63 -219.3165 449.4657 0.551018 S.D. dependent var S.E. of regression Adjusted R-squared P-value(F) Akaike criterion Hannan-Quinn Durbin-Watson...
1. Propose any one interaction hypothesis among the set of
independent variables for each of the two models and provide
rationales for your proposition.
2. Test whether your proposition is supported by the data
ependent Variable SALARY Method: Least Squares Date: 03/28/19 Time: 17:11 Sample: 1 447 Included observations: 447 Variable Coefficient Std. Error t-Statistic Prob TOTCOMP_MEYU TENURE_MEYU AGE_MEYU SALES_MEYU PROFITS_MEYU ASSETS_MEYU 857.5376 596.2939 1.438112 0.1511 0.014302 0.002179 6.564320 0.0000 27.40055 9.066757 3.022090 0.0027 7.034349 10.952730.642246 0.521 0.013978 0.006320 2.211800...
Consider the regression output below and answer each question.
The frequency is quarterly,and the variables are defined at annual
rates as follows: INT_RATE_3M is the 3-Month Treasury Bill,
INF_RATE is the inflation rate, UNRATE is the unemployment rate,
and EMP_GROWTH corresponds to the employment growth rate.
a)How is the goodness of fit? How can you tell?
b)For each of the 3 independent variables in the regression,
state if their coefficient is statistically significant at 5%
level.
c)For the same variables...
Predict the value of a traditional style house with 2500 square
feet of area, that is 20 years old, with 3 bedrooms and two
bathrooms, which is owner occupied at the time of sale, with a
fireplace, and not on the waterfront. Provide the “corrected
predictor”. (Prediction in the log-linear model.) need help with
the corrected predictor.
Sample: 1 1080 Included observations: 1080 Variable Coefficient Std. Error t-Statistic Prob 3.971283 0.045870 86.57653 0.0000 0.030016 0.001388 21.62198 0.0000 0.031281 0.016548 1.890282...
I have a model from Gretl which I'm trying to copy the latex
code for so l can paste in a web browser. However, when l submit
the code I'm getting weird results and the table is not coming out
how l would like. How do l get the latex code from the Gretl model
to format exactly the same on this web browser.
Latex Code from copying the output:
\begin{center}
Model 1: OLS, using observations 1--60\\
Dependent variable: l\_Y\\...
Attached are the results of a diagnostic test on an estimated
model, autocorrelation, heteoskedasticity and non-normality
respectivey, can you please comment on the results and state the
conclusion for each test using a 5% significance level
Breusch-Godfrey Serial Correlation LM Test F-statistic Obs R-squared 0.7659 0.7612 0.458959 Prob. F(4,438) 1.861565 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID Method: Least Squares Date: 05/22/19 Time: 22:02 Sample: 1982M01 2019M02 Included observations: 446 Presample missing value lagged residuals set to zero. Coefficient Std....
We want to look at potential predictors of movie revenues. Model 1: OLS, using observations l-609 Dependent variable: USGrossM coefficient std. error t-ratio p-value --------------------------------------- ------------------------ const -52.3692 15.4296 -3.394 0.0007 *** BudgetM 0.972348 0.0484576 20.07 4.89e-069 *** RunTimemin 0.387214 0.155146 2.496 0.0128 CriticScoreRotter 0.640257 0.0953758 6.713 4.40e-011 *** Mean dependent var Sum squared resid R-squared F(3, 605) Log-likelihood Schwarz criterion 75.81977 2004759 0.517227 216.0592 -3330.345 6686.337 S.D. dependent var S.E. of regression Adjusted R-squared P-value (F) Akaike criterion Hannan-Quinn...
Consider time series yt , defined as the daily
percentage change in SP500 index. A researcher estimated the
following model:
(a) There is one partial
autocorrelation coefficient that you can find from the estimation
result. What is the value of it? What is order (k ) of
it?
(b) Test the null hypothesis that the partial autocorrelation
coefficient that you have is zero against the alternative that it
is not zero.
Dependent Variable: GROWTH Method: Least Squares Date: 03/08/15 Time:...
An interpretation is needed for the below
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: GDPPERCAPITA Method: Least Squares Date: 01/19/19 Time: 21:27 Sample (adjusted): 2 264 Included observations: 142 after adjustments Variable Coefficient Std. Error t-Statistic Prob EDUEXPENSES 3409.799982.7287 3.469726 0.0007 60.62503 50.33194 1.204504 0.2305 248.8894 62.51844 3.981056 0.0001 299.3805 136.4002 2.194869 0.0299 529.2544297.0670 1.781599 0.0771 VALUEADDAGRI 840.2738 141.5672 -5.935512 0.0000 2227.235 7946.208 0.280289 0.7797 EXPORTS FDINFLOWS GSAVING...
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