A random sampleY1 , Y 2 , ⋯,Yn is drawn from a distribution whose probability density function is given by: f (Y ) = βe − βY , Y 0 & β > 0 a). Obtain the maximum likelihood estimator (MLE) of β. (3 points) 1Econometrics- Assignment I b). Given that ∑ n Y i = 25 , ∑n Yi 2 = 50 , n = 50 calculate the maximum likelihood i =1 i =1 estimate of β. (3 point) c). Using the same data as in part (b), test the null hypothesis that β =1against the alternative hypothesis that β ≠1at 5% level of significance. (3 points) Problem 4 Suppose the production(Y) is determined as a function of labour input in hours (L) and capital input in machine hours (K). Using the Cobb-Douglas function
(a) maximum likelihood estimator.
"\\frac{df}{dy} = \\beta""(\\beta e""-\\beta""Y)-""\\beta"("\\beta""e-\\beta""Y)"
(b)
M= "\\frac{1}{n}\\sum" Xi (from 1to 50)
n= 50
Xi= 1
M="\\frac{1}{50}= 0.02"
(c)T2"=\\frac{1}{n}\\sum"(Xi -M)2
"=0.02(1-0.02)= 0.0196"
Problem 4
the complete question: Suppose the production(Y) is determined as a function of labor input in hours (L) and capital input in machine hours (K). Using the Cobb-Douglas function:
Y= β0 + β1K β1 + ek Write the procedure to estimate the coefficients of this function
fY(y)=c(β)y3(1−y)β10<y<1
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