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YI = β1X I 1 + β 2X I 2 + UI WhereUi ∼ NID (0, σu 2 ) , YI is observable random variable and theXij ' s , j =1, 2 are observable non-random (non-stochastic) variables. The data that follows is based on a sample of size N = 120 and gives the sums of squares and cross-products of the indicated variables Y X1 X2 Y 39 6 2 X1 6 4 0 X2 2 0 4 a). Compute the best linear unbiased estimates of the coefficients. (2 points) b). Give a 95% confidence interval for β1 . (2 points) Test the hypothesis H 0 : β1 + β2 = 1 against the alternative H 0 : β1 + β2 ≠ 1 at the 95% confidence level. 


How will the COVID-19 pandemic crisis affect the natural rate of unemployment? Explain the reasoning behind your answer.


. Demand Curves. ISHO-garment is contemplating a T-shirt advertising promotion. Monthly sales data from T-shirt shops marketing indicate that

            𝑄=1,500–200𝑃


1.   The countries France and Italy produce Perfumes and Leather Coats using only labor as an input. AvailableLabor for France and Italy is 3000 and 1000 respectively. Unit of labor per Leather Coat in France is 6 units and inItaly are 2 units. France needs 2 units of labors to produce 1 bottle of Perfume and Italy needs 4 unit of labor.



a)  Draw the Production Possibility Curve by using relevant information. (1*2=2 marks)


b)  Which country has the comparative advantage in producing Perfume? (3 marks)



From the give table calculate Elasticity of Price, Total Revenue and Marginal Revenue.

Also, explain the relationship between AR and MR?


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:

Y= β0 + β1K β1 + ek

Write the procedure to estimate the coefficients of this function


Show that the test taking the overall significance of regression model using ANOVA table to be expressed as: 

 

𝑹𝟐⁄𝒌−𝟏

 

𝑭=(𝟏−𝑹𝟐)⁄𝒏−𝒌 

 

Where, R be a level of determination and k is the number of parameters in the n sampled regression model.


Consider a k-variables linear regression model, i.e.,

Y = X 1β1 + X 2 β2 + ε,

Where, X1 is (N  k1 ) , X 2 is (N  k2 ) and k = k1 + k2 . As you may recall, adding columns to the X matrix (including additional regressors in the model) gives positive definite increase in R2. The adjusted R2 ( R 2 ) attempts to avoid this phenomenon of ever increase in R2. Show that the additional k2 number of variables (regressors) in this model increases R 2 if the calculated F-statistic in testing the joint statistical significance of coefficients of these additional

regressors (β2 ) is larger than one.


a firm’s demand curve in period 1 is q=25 - p. fixed costs are 20 and marginal costs per unit are 5

At what output will marginal revenue be zero?

At what price will total revenue be maximized? 

At what price and output will profit be maximized?

Calculate the maximum profits the firm makes


the market price is in a perfectly competitive market is 100$. a perfectly competitive firm has a marginal cost given by MC=2+2Q. Find the profit maximizing output and revenue for this firm.


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