Crop. Some of the crop production includes corn silage, corn grain, alfalfa hay and alfalfa silage, soybeans, soybean meal, wheat, oats, etc. Crop production groups recognize the manufacture of crops by evaluating the amount of crop yield, the profit earned, and the ecological consequences. A regression model had been determined to predict the yearly number of hours (in million) worked on crop productions based on the number of employments (in thousand) from the year 1978 to 2019 as below with its scatterplot.

Dependent variable is: Yearly number of hours R-squared = 0.3001, Adjusted R-squared: 0.2775 SE = 149.2867 with 33 observations Variable Coefficient SE(Coeff) t-ratio P-value Intercept 1321.9311 445.3349 2.9684 0.0057 Employment

(000) 0.7947 0.2180 3.6459 0.0010

a) The orange points in the plot are recent 10 years values.
We can construct a variable that is “1” for those values and “0” otherwise. What is such a variable called?
Here’s the regression result after assigning “1” and “0”:
Dependent variable is: Yearly number of hours R-squared = 0.4211 Adjusted R-squared: 0.3826 SE = 138.0103 with 33 observations Variable Coefficient SE(Coeff) t-ratio P-value Intercept 692.9085 482.2569 1.4368 0.1611 Employment (000) 1.1264 0.2411 4.6713 0.0001 Recent Decade -156.6726 62.5553 -2.5045 0.0179

b) What is the interpretation of the coefficient of the constructed variable Recent Decade?

c) What additional assumption is required to include the variable Recent 10 years in this model? Is there reason to believe that it is satisfied?

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Hours worked (in million) 3500.000 Hours Worked vs. Employment 3300.000 3100.000 2900.000 2700.000 2500.000 1800.000 1900.000 2000.000 2100.000 2200.000 2300.000 2400.000 2500.000 2600.000 Employment (000)