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
Coefficient Value
Standard Error of the Slope
1.38 0.27 0.14
Intercept (b0) lnKt (b1) lnLt (b2)
2.81 0.53 0.91
df
SS (sum of squares)
F-statistic p-value
Regression
Error
Total
2 203693.3 6.745406 0.010000 47 181184.1
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What is the r-squared associated with this regression?


0.53