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agriME

agriME is an R package for reproducible agricultural marketing-efficiency and price-spread analysis. It works with either channel-level totals or a full stage-by-stage chain such as Producer -> Wholesaler -> Retailer -> Consumer.

What the package calculates

Output Definition used
Price spread Consumer price minus net producer price
Price-spread percentage Price spread divided by consumer price, times 100
Producer’s share Net producer price divided by consumer price, times 100
Total gross marketing margin Same monetary gap as price spread when the producer price is net
Acharya efficiency Net producer price divided by total marketing cost plus net intermediary margin
Shepherd efficiency Consumer price divided by total marketing cost; an optional net-ratio variant subtracts one
Conventional efficiency Value added by marketing divided by total marketing cost

Installation

Install the checked source tarball supplied with the release bundle:

install.packages("agriME_0.1.0.tar.gz", repos = NULL, type = "source")
library(agriME)

After publication on CRAN, installation will be:

install.packages("agriME")
library(agriME)

Quick start: channel-level totals

marketing_metrics(
  producer_price = 1900,
  consumer_price = 3150,
  marketing_cost = 510,
  marketing_margin = 740,
  channel = "Producer-Wholesaler-Retailer"
)

Quick start: complete channel accounts

data(tomato_channels)

fit <- analyse_channels(tomato_channels)
fit
summary(fit)

consumer_rupee(fit)
rank_channels(fit)

plot(fit, type = "decomposition")
plot(fit, type = "efficiency")

The required stage-level fields are:

Field Meaning
channel Channel identifier
stage Integer order within the channel
actor Producer or intermediary name
actor_type producer for exactly one first-stage row; otherwise intermediary
purchase_price Actor purchase price per common unit; use 0 or NA for producer
sale_price Actor sale price per the same unit
marketing_cost Actor marketing cost per the same unit

Use equivalent commodity quality, form, time, location, and quantity across channels. The validator reports broken price links and accounting gaps rather than silently treating inconsistent records as efficiency differences.

Uncertainty from repeated observations

data(market_observations)

ci <- bootstrap_marketing_metrics(
  market_observations,
  channel = "channel",
  R = 499,
  seed = 2026
)

ci
plot(ci, metric = "acharya_efficiency")

Sensitivity and target analysis

sens <- marketing_sensitivity(
  producer_price = 1900,
  consumer_price = 3150,
  marketing_cost = 510,
  marketing_margin = 740,
  producer_change = c(-0.05, 0, 0.05),
  cost_change = c(-0.10, 0, 0.10)
)

sens
plot(sens, metric = "acharya_efficiency")

efficiency_target(
  target = 2,
  method = "acharya",
  solve_for = "marketing_cost",
  producer_price = 1900,
  marketing_margin = 740
)

Interpretation caution

Efficiency ratios are descriptive accounting indicators. A high ratio does not, by itself, prove that a channel is competitive, equitable, causally superior, or socially optimal. Added services, quality transformation, risk bearing, losses, seasonality, and transaction volume must be considered when comparing channels.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.