a)
To find: The possibility of the cause of autocorrelation.
a)
Explanation of Solution
The causes of autocorrelation are:
1. Bias in the data
2. The data is not reliable there must be some change in the data.
b)
To find: The effect of autocorrelation.
b)
Explanation of Solution
The results are:
1. two or more independent variables are correlated, i.e., multicollinearity.
2. the function might be sometimes non-linear.
c)
To find: the affect of autocorrelation on the accuracy of
c)
Explanation of Solution
- autocorrelation might underestimate the true variance.
- The null hypothesis might be rejected although it is true.
d)
To find: remedial for autocorrelation removal
d)
Explanation of Solution
The remedy is to increase the number of observations, find the missing values and estimators although linear is not the efficient estimator.
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Chapter 4A Solutions
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- A multiple OLS regression of maize output (Y) on improved maize seed (X1) and fertiliser (X2) inputs (all variables in kilograms) produced the following results: Y = -342 + 12.1X1 + 46X2 se = (17.23) (0.912) (8.713) R2 = 0.861 a) Calculate the t statistics associated with the constant, improved maize seed and fertiliser coefficientsarrow_forwardSuppose there are 2 quantitative free variables and 1 variable non free category. Non-free variables have 2 categories, namely 1 for the success category and 1 for the fail category. The method used to create models that describe relationships between variables is a binary logistic regression model. Perform parameter recovery for the model. Explain the stage until the alleged value is obtainedarrow_forwardNumerical Answer Only Type Question Enter the numerical value only for the correct answer in the blank box. If a decimal point appears, round it to two decimal places. Assume that the number of visits by a particular customer to a mall located in downtown Toronto is related to the distance from the customer's home. The following regression analysis shows the relationship between the number of times a customer visits(Y)per month and the distance(X, measured in km) from the customer's home to the mall. \[ Y=15-0.5 X \] A customer who lives30 kmaway from the mall will visi______ who lives10 km away. less times than a customerarrow_forward
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- Managerial Economics: Applications, Strategies an...EconomicsISBN:9781305506381Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. HarrisPublisher:Cengage Learning