Answer Happy

A production function for the U.S. data can be expressed as Yt = AKtb1Ltb2 where A = Total factor productivity
Yt = Real output (in constant 1900 dollars)
Kt = Quantity of capital (in constant 1900 dollars) Lt = Labor hours/week

This expression can be linearized by taking the natural logarithms of each side of this equation. Based on annual data for the U.S. manufacturing sector 1945-1994, a study estimates a production function using the logarithms of the data and obtains the following regression results,
Dependent Variable: lnYt

Intercept (b0) lnKt (b1) lnLt (b2)
Regression
Error
Total
F-statistic
6.745406
p-value
0.010000
Coefficient Value
Standard Error of the Slope
2.81 0.53 0.91
df SS (sum of squares)
2 203693.3 47 181184.1 ___ _______
1.38 0.27 0.14
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What are the degrees of freedom (df) associated with SST (sum of squares total)?


49