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ICAR AICE-JRF/SRF Farm Management: practice questions

ICAR AICE-JRF/SRF (PhD admission and fellowship) · India · National Testing Agency for ICAR

Original practice questions written to the published syllabus · not past papers
8worked here, free
41written to this exam in this subject
14syllabus units

What this subject covers

Making the best use of land, labour, capital and machinery on a farm: measuring efficiency, costing, planning and budgeting, and keeping records.

In the exams: agricultural master's entrance examinations, agricultural economics (heavy); agricultural economics PhD entrance and fellowship examinations, farm management (heavy); cost analysis in agricultural field officer recruitment in banking (present); agricultural scientist eligibility tests (present)

Where the 41 questions fall

How our questions for ICAR AICE-JRF/SRF spread across the units of Farm Management. Difficulty: 3 easy, 18 medium, 20 hard.

Decision-making under certainty, risk and uncertainty8
Linear programming in farm planning8
Measures of farm efficiency5
Management of land, labour, capital and machinery3
Definition and scope of farm management2
Cost concepts in farm management2
Valuation of farm assets and liabilities2
Partial budgeting2
Whole-farm planning and budgeting2
Farm cost accounting2
Farming systems and the systems approach2
Enterprise budgeting1
Farm records and accounts1
Farm inventory1

8 practice questions, worked

Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.

1 · Measures of farm efficiency · hard

Which statement correctly contrasts stochastic frontier analysis (SFA) with data envelopment analysis (DEA) in measuring farm efficiency?

  1. SFA separates noise from inefficiency but needs a functional form; DEA needs none but treats all deviation as inefficiency
  2. Both require a Cobb-Douglas or translog functional form
  3. SFA is non-parametric and solved by linear programming, while DEA is a parametric model estimated by maximum likelihood
  4. DEA separates random noise from inefficiency using a composed error term, while SFA treats all deviation from the frontier as inefficiency
Answer and working

A. SFA separates noise from inefficiency but needs a functional form; DEA needs none but treats all deviation as inefficiency

SFA (Aigner, Lovell and Schmidt; Meeusen and van den Broeck, 1977) is parametric with a composed error: symmetric noise plus a one-sided inefficiency term, usually estimated by maximum likelihood. DEA (from Charnes, Cooper and Rhodes, 1978) is non-parametric, built by linear programming, and deterministic, so bad weather is recorded as inefficiency. The distractors swap these properties.

Further reading: Coelli et al., An Introduction to Efficiency and Productivity Analysis

2 · Valuation of farm assets and liabilities · hard

A farmer owns land worth far more than all his debts but cannot pay a seed dealer's bill due this week. His position is best described as

  1. over-capitalised but profitable
  2. solvent but illiquid
  3. both insolvent and illiquid
  4. insolvent but fully liquid
Answer and working

B. solvent but illiquid

Solvency compares total assets with total liabilities (net worth positive); liquidity is the ability to meet obligations as they fall due from cash or near-cash assets. Valuable land does not pay a bill this week, so the farm is solvent and illiquid, a common cause of distress sales. Nothing given says anything about profitability.

Further reading: Kay, Edwards and Duffy, Farm Management

3 · Decision-making under certainty, risk and uncertainty · medium

A risky crop plan has an expected income of 60,000 currency units. A farmer says he would be equally happy with a sure 52,000 currency units. His risk premium and attitude are

  1. 112,000 currency units; risk averse
  2. 52,000 currency units; risk neutral
  3. 8,000 currency units; risk preferring
  4. 8,000 currency units; risk averse
Answer and working

D. 8,000 currency units; risk averse

The certainty equivalent is 52000. Risk premium = EV − CE = 60000 − 52000 = 8000. A positive premium means the farmer gives up expected income to avoid risk: risk aversion. A risk-neutral farmer's CE equals EV (premium 0); a risk-preferring farmer's CE exceeds EV.

Further reading: Hardaker et al., Coping with Risk in Agriculture

4 · Partial budgeting · medium

A partial budget for buying a new rotavator should enter the machine's cost as

  1. nothing, because capital items are excluded from partial budgets
  2. its salvage value
  3. its annual depreciation plus interest on the investment
  4. its full purchase price in the first year
Answer and working

C. its annual depreciation plus interest on the investment

A partial budget is usually on an annual basis, so a capital purchase enters as its annual ownership cost: depreciation plus interest on the capital tied up (plus insurance and housing if relevant). Charging the full price to one year would overstate the cost of the change.

Further reading: Kay, Edwards and Duffy, Farm Management

5 · Linear programming in farm planning · medium

The shadow price of land in an optimal farm plan is 9,000 currency units per hectare. A neighbour offers to lease a hectare for 11,000 currency units a year. Other things equal, the farmer should

  1. accept, because land is a binding constraint
  2. accept, because a positive shadow price shows that land is scarce on this farm
  3. decline, because the shadow price of a binding resource is always zero
  4. decline, because an extra hectare adds only around 9,000 currency units to gross margin
Answer and working

D. decline, because an extra hectare adds only around 9,000 currency units to gross margin

The shadow price is the most an extra unit of the resource is worth in the current plan (within the range where the basis does not change). Paying 11,000 for something worth 9,000 lowers profit. That land is binding explains why the shadow price is positive; it does not justify paying more than it. Zero shadow prices apply to slack resources.

Further reading: Heady and Candler, Linear Programming Methods

6 · Linear programming in farm planning · medium

For a primal farm LP that maximises gross margin subject to resource limits, the dual problem

  1. minimises gross margin subject to the same resource constraints, and its optimum is the negative of the primal
  2. maximises the total quantity of resources used
  3. has an optimum that is always smaller than the primal optimum, by the value of slack resources
  4. minimises the total imputed value of the resources, and its optimum equals the primal optimum
Answer and working

D. minimises the total imputed value of the resources, and its optimum equals the primal optimum

The dual of a maximisation is a minimisation over resource values (shadow prices), with one dual constraint per activity requiring imputed cost ≥ gross margin. By the duality theorem, the optimal values are equal. At feasible non-optimal points the dual value exceeds the primal, not the reverse.

Further reading: Heady and Candler, Linear Programming Methods

7 · Farming systems and the systems approach · medium

The usual order of stages in farming systems research (FSR) is

  1. design, diagnosis, extension, on-farm testing
  2. extension, design, diagnosis, on-farm testing
  3. on-farm testing, diagnosis, design, extension
  4. diagnosis, design, on-farm testing, extension
Answer and working

D. diagnosis, design, on-farm testing, extension

FSR first describes the farming system and its constraints (diagnosis), then chooses technologies to address them (design), tests them under farmers' conditions (on-farm testing), and spreads the successful ones (extension/diffusion), with feedback to research.

Further reading: Farming systems research literature

8 · Decision-making under certainty, risk and uncertainty · hard

Under expected utility theory, a farmer with a concave utility function of income will

  1. prefer risky prospects to sure incomes of the same expected value
  2. prefer a sure income to a risky prospect with the same expected value
  3. be indifferent to the variance of income
  4. always choose the prospect with the highest expected value regardless of risk
Answer and working

B. prefer a sure income to a risky prospect with the same expected value

A concave utility function means diminishing marginal utility of income, so the utility of the expected value exceeds the expected utility of the gamble (Jensen's inequality): the farmer is risk averse. Choosing by expected value alone describes risk neutrality (linear utility); preferring gambles describes a convex function.

Further reading: Hardaker et al., Coping with Risk in Agriculture

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Farm ManagementThe full study manual, free ICAR AICE-JRF/SRFFormat, sections and how it has changed

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