Cobb Douglas production function in excel

Cobb Douglas production function in excel

Yi=a X1i^b1 X2i^b2 X3i^b3 e^ui

Where,
Y= dependent variable
X=explanatory(independent)variable
a=intercept
bi are regression coefficients
e=2.718………….
u=error term Follows N(0,constant variance)
This function is non linear in parameters so to make it linear in parameters apply ln both sides then equation looks like

lnYi=lna+ b1lnX1i +b2lnX2i +b3lnX3i+ui

Steps
1. Open Excel, Give Variable Names and Provide Data
2. Apply Logarithmic Transformation to the Data
3. Go to Data analysis
4. Get Output

1. Estimating COBB–Douglas Production function in Excel Pavan Kumar Thota (M.Sc. Agricultural Statistics), B.C.K.V, Kolkata, WB, INDIA

2. Where, Y= dependent variable X=explanatory(independent)variable a=intercept bi are regression coefficients e=2.718…………. u=error term Follows N(0,constant variance) This function is non linear in parameters so to make it linear in parameters apply ln both sides then equation looks like Y i =a X1i b1 X2i b2 X3i b3 e ui lnY i = lna + b1 lnX1i + b2 lnX2i + b3 lnX3i+ui

3. Steps 1. Open Excel , Give Variable Names and Provide Data 2. Apply Logarithmic Transformation to the Data 3. Go to Data analysis 4. Get Output

4. 1. Open Excel , Give Variable Names and Provide Data

5. 2. Apply Logarithmic Transformation to the Data

6. Provide new columns with names as Ln(variable)

7. Give function to calculate logarithmic transformation of data

8. Go to Data menu check Data analysis tool is present or not

9. If your Excel does not have pre- installed Data analysis package in Data menu then do the following steps Go to File Menu  Options Add-ins Manage select Excel add-ins click go select Analysis tool pack ok

10. FILE

11. Now go to the data menu to check data analysis icon

12. 3. Go to Data analysis

13. Go to Data  Data analysis  Regression  give input Y range and X range  Click OK

14. Select numerical part

15. est (ln(yield))= lna + b1 ln( ferti ) + b2 ln(seed rate) + b3 ln(pesticides) ln a=1.6061 a=4.9833 b1=.3939 b2=.2505 b3=.1165 estimated[ln(yield)]=1.6061+ .3939 ln( ferti ) + .2505 ln(seed rate) + .1165 ln(pesticides) estY i = 4.9833 X1i .3939 X2i .2505 X3i .1165

16. Thank you