Package {farmPartial}

farmPartial: Tools for Farm Partial-Budget Analysis

Description

Tools for estimating the incremental economic consequence of a farm-management change. The package implements the four standard partial-budget components: added returns, reduced costs, added costs, and reduced returns. It also supports baseline-alternative comparisons, sensitivity and scenario analysis, break-even analysis, Monte Carlo uncertainty analysis, capital annualization, dominance analysis, and marginal rate-of-return analysis.

Details

The central identity is

\Delta NR = (AR + RC) - (AC + RR),

where AR is added returns, RC is reduced costs, AC is added costs, and RR is reduced returns. Only items that change between the baseline and alternative farm plans belong in a partial budget.

References

CIMMYT (1988). From Agronomic Data to Farmer Recommendations: An Economics Training Manual. Completely revised edition. Mexico: CIMMYT. ISBN 968-6127-19-4.

See Also

partial_budget, compare_budgets, sensitivity_analysis, simulate_partial_budget

Annualize a Farm Capital Investment

Description

Converts a farm capital purchase and terminal salvage value into an equivalent annual cost using the capital-recovery method.

Usage

annualize_investment(purchase, salvage = 0, life, rate = 0)

Arguments

Details

For a positive discount rate, the function first discounts the terminal salvage value to the present and then applies the capital-recovery factor. At a zero discount rate it returns straight-line annual capital consumption, (P-S)/n.

Value

Numeric vector of equivalent annual costs.

Examples

annualize_investment(purchase = 120000, salvage = 20000, life = 8, rate = 0.08)

Break-Even Value for One Partial-Budget Component

Description

Calculates the selected partial-budget component amount required to make net economic change equal zero.

Usage

break_even_component(x, item)

Arguments

Details

All other budget components are held fixed. If the calculated break-even amount is negative, the returned feasible_nonnegative flag is FALSE; this means no non-negative amount for the selected component can make the current budget exactly break even while all other items remain unchanged.

Value

A one-row data frame containing the break-even amount and multiplier.

Examples

pb <- partial_budget(wheat_example("changes"))
break_even_component(pb, "Additional herbicide")

Compare Baseline and Alternative Farm Budgets

Description

Compares baseline and alternative farm budgets and classifies their incremental economic changes.

Usage

compare_budgets(
  baseline,
  alternative,
  currency = NULL,
  unit = NULL,
  zero_tol = sqrt(.Machine$double.eps)
)

Arguments

Details

For return items, an increase is classified as an added return and a decrease as a reduced return. For cost items, an increase is an added cost and a decrease is a reduced cost. An item absent from one budget is assigned value zero there. An item must retain the same return/cost category across both plans.

Value

A farm_partial_budget object. Its comparison element contains the aligned baseline and alternative values and their signed differences.

Examples

base <- wheat_example("baseline")
alt <- wheat_example("alternative")
compare_budgets(base, alt)

Build a Farm Budget Table

Description

Creates a validated farm budget from total values or quantity-price components.

Usage

farm_budget(
  item,
  category,
  value = NULL,
  quantity = NULL,
  unit_price = NULL,
  currency = "INR",
  unit = "per ha"
)

## S3 method for class 'farm_budget'
print(x, ..., row.names = FALSE)

Arguments

Value

A data frame of class farm_budget.

Examples

b <- farm_budget(
  item = c("Grain", "Seed"),
  category = c("return", "cost"),
  value = c(100000, 7000)
)
b

Create and Summarize a Farm Partial Budget

Description

Organizes the four partial-budget components and calculates the expected change in net return.

Usage

partial_budget(
  changes = NULL,
  added_returns = NULL,
  reduced_costs = NULL,
  added_costs = NULL,
  reduced_returns = NULL,
  currency = "INR",
  unit = "per ha"
)

budget_summary(x)

## S3 method for class 'farm_partial_budget'
print(x, digits = 2L, ...)

## S3 method for class 'farm_partial_budget'
summary(object, ...)

## S3 method for class 'farm_partial_budget'
plot(
  x,
  main = "Farm partial budget",
  ylab = NULL,
  col = c("#2E7D32", "#66BB6A", "#C62828", "#EF5350", "#1565C0"),
  ...
)

Arguments

Details

The four accepted change types are added_return, reduced_cost, added_cost, and reduced_return. Amounts are magnitudes and must be non-negative. The estimated net change is favorable changes minus adverse changes. The change benefit-cost ratio is the total favorable changes divided by total adverse changes. The marginal rate of return is reported only when the net change in costs is positive and is calculated as net change divided by the increase in costs, multiplied by 100.

Value

partial_budget() returns a farm_partial_budget object. budget_summary() and summary() return a one-row data frame. The print and plot methods return their input invisibly or the plotting positions invisibly.

Examples

pb <- partial_budget(
  added_returns = c("Extra grain" = 6000),
  reduced_costs = c("Energy saving" = 1800),
  added_costs = c("New input" = 2200),
  reduced_returns = c("Lower straw value" = 500),
  currency = "INR",
  unit = "per ha"
)
pb
budget_summary(pb)

Scenario Analysis for a Farm Partial Budget

Description

Applies item-specific multipliers under named scenarios and recalculates partial-budget outcomes.

Usage

scenario_analysis(x, scenarios, include_base = TRUE)

## S3 method for class 'farm_partial_scenario'
print(x, ..., row.names = FALSE)

## S3 method for class 'farm_partial_scenario'
plot(
  x,
  main = "Partial-budget scenarios",
  ylab = NULL,
  col = NULL,
  ...
)

Arguments

Value

A data frame of class farm_partial_scenario.

Examples

pb <- partial_budget(wheat_example("changes"))
sc <- data.frame(
  scenario = c("Low output price", "High input price"),
  item = c("Higher grain return", "Additional herbicide"),
  multiplier = c(0.8, 1.25)
)
scenario_analysis(pb, sc)

One-Way Sensitivity Analysis for a Partial Budget

Description

Varies one partial-budget component while holding all remaining components constant.

Usage

sensitivity_analysis(x, item, multipliers = seq(0.8, 1.2, by = 0.05))

## S3 method for class 'farm_partial_sensitivity'
print(x, ..., row.names = FALSE)

## S3 method for class 'farm_partial_sensitivity'
plot(
  x,
  main = "One-way sensitivity analysis",
  xlab = "Multiplier",
  ylab = NULL,
  col = "#1565C0",
  ...
)

Arguments

Value

A data frame of class farm_partial_sensitivity.

Examples

pb <- partial_budget(wheat_example("changes"))
s <- sensitivity_analysis(pb, "Higher grain return", c(0.8, 1, 1.2))
s

Monte Carlo Uncertainty Analysis for a Partial Budget

Description

Propagates uncertainty in partial-budget components through Monte Carlo simulation.

Usage

simulate_partial_budget(x, uncertainty, n = 10000L, level = 0.95, seed = NULL)

## S3 method for class 'farm_partial_simulation'
print(x, digits = 2L, ...)

## S3 method for class 'farm_partial_simulation'
summary(object, ...)

## S3 method for class 'farm_partial_simulation'
plot(
  x,
  main = "Uncertainty in partial-budget net change",
  xlab = NULL,
  col = "#90CAF9",
  border = "white",
  ...
)

Arguments

Details

Supported distributions are fixed, normal, lognormal, uniform, and triangular. A normal or lognormal component uses mean (defaulting to its current budget amount) and either sd or cv. Uniform components require min and max; triangular components require min, mode, and max. Component draws are independent. Negative normal draws are truncated at zero. The returned interval describes the simulated uncertainty distribution; it is not a sampling-theory confidence interval.

Value

An object of class farm_partial_simulation. Its draws element contains simulated net changes; component_draws contains the simulated component amounts; and metrics contains mean, median, standard deviation, interval endpoints, and probability of a positive net change.

Examples

pb <- partial_budget(wheat_example("changes"))
u <- data.frame(
  item = c("Higher grain return", "Additional herbicide"),
  distribution = c("normal", "uniform"),
  mean = c(6000, NA),
  sd = c(900, NA),
  min = c(NA, 900),
  max = c(NA, 1500)
)
sim <- simulate_partial_budget(pb, u, n = 500, seed = 123)
summary(sim)

Economic Analysis of Alternative Farm Treatments

Description

Calculates treatment economics and supports dominance and marginal rate-of-return analyses.

Usage

trial_budget(treatment, yield, price, variable_cost, yield_adjustment = 1)

dominance_analysis(x)

marginal_analysis(x, minimum_mrr = NULL)

Arguments

Details

dominance_analysis() marks an alternative as dominated when another has no greater variable cost and no lower net benefit, with at least one strict improvement. marginal_analysis() removes dominated alternatives, sorts the remainder by variable cost, and computes the change in net benefit divided by the change in variable cost between adjacent alternatives, multiplied by 100.

Value

trial_budget() returns a treatment-economics data frame. dominance_analysis() adds a logical dominated column. marginal_analysis() returns only non-dominated alternatives with marginal increments and marginal rates of return.

References

CIMMYT (1988). From Agronomic Data to Farmer Recommendations: An Economics Training Manual. Completely revised edition. Mexico: CIMMYT. ISBN 968-6127-19-4.

Examples

trials <- trial_budget(
  treatment = c("Farmer practice", "Treatment A", "Treatment B"),
  yield = c(3.0, 3.5, 3.7),
  price = 22000,
  variable_cost = c(18000, 23000, 31000),
  yield_adjustment = 0.9
)
dominance_analysis(trials)
marginal_analysis(trials, minimum_mrr = 50)

Two-Way Sensitivity Analysis for a Partial Budget

Description

Varies two partial-budget components simultaneously and calculates the resulting net changes.

Usage

two_way_sensitivity(
  x,
  item_x,
  item_y,
  multipliers_x = seq(0.8, 1.2, by = 0.1),
  multipliers_y = seq(0.8, 1.2, by = 0.1)
)

## S3 method for class 'farm_partial_two_way'
print(x, ..., row.names = FALSE)

## S3 method for class 'farm_partial_two_way'
plot(
  x,
  main = "Two-way sensitivity: net change",
  xlab = NULL,
  ylab = NULL,
  col = c("#A50026", "#D73027", "#F46D43", "#FDAE61", "#FEE08B",
    "#D9EF8B", "#A6D96A", "#66BD63", "#1A9850", "#006837"),
  ...
)

Arguments

Value

A data frame of class farm_partial_two_way.

Examples

pb <- partial_budget(wheat_example("changes"))
two_way_sensitivity(
  pb,
  "Higher grain return",
  "Additional herbicide",
  multipliers_x = c(0.9, 1, 1.1),
  multipliers_y = c(0.9, 1, 1.1)
)

Illustrative Wheat Partial-Budget Data

Description

Returns internally generated per-hectare wheat-management values for package examples. The values are pedagogical and are not survey estimates, official costs, or recommendations.

Usage

wheat_example(type = c("changes", "baseline", "alternative"))

Arguments

Value

For "changes", a data frame accepted by partial_budget(). For the other choices, a farm_budget object accepted by compare_budgets().

Examples

partial_budget(wheat_example("changes"))
compare_budgets(wheat_example("baseline"), wheat_example("alternative"))