Agricultural business investment. A study in the Journal of Management & Agribusiness (Vol. 17, 2020) aimed to identify the factors that influence people’s participation in agricultural business investment with crowdfunding schemes. Data was collected from 468 agricultural projects to estimate the number of crowdfunding investors 1y2 (in persons) by using the independent variables listed below: Type of loan project: x1 = 1 if loans, 0 if profit sharing Field project-fisheries (agriculture, fishery, or livestock): x2 = 1 if fishery, 0 if not Field of project-livestock (agriculture, fishery, or livestock): x3 = 1 if livestock, 0 if not Project risk-moderate (low, moderate, or high): x4 = 1 if moderate, 0 if not Project Risk-high (low, moderate, or high): x5 = 1 if high, 0 if not Dur x6 = Project duration in days IDR x7 = Amount of capital required in IDR Pro x8 = Assumed profit in percent

a. The model E1y2 = b0 + b1x1 + b2x2 + b3x3 + b4x4 + b5x5 + b6x6 + b7x7 + b8x8 was fit to the data with the following results: R2 = .371, Ra 2 = .609, F = 33.833. Interpret the results, practically. Make an inference about the overall adequacy of the model.

b. Refer to part

a. Statistics for the type of loan project variable were reported as follows: bn 1 = 16.558, t = .656, p@value = .512. Use this information to make an inference about the impact of type of loan project on the number of crowdfunding investors

c. Refer to part

a. Statistics for the project duration variable were reported as follows: bn 6 = -.577, t = -3.558, p@value = .000. Use this information to make an inference about the impact of project duration on the number of crowdfunding investors.

d. Write a first-order model for E1y2 as a function of amount of capital required 1x72 and field of project 1x2, x32 that allows for the relationship between number of crowdfunding investors and amount of capital required to vary depending on the field of the project.