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Disaggregated CPI: food and core inflation

Source: R/blocks_library.R
block_food_cpi.Rd

Splits headline inflation into food and core. Food is 30-50 percent of the consumption basket across most of sub-Saharan Africa and South Asia, and a single-inflation model is unusable there: supply shocks to food dominate headline, but monetary policy should look through the relative-price component. Practically every technical-assistance engagement rebuilds this split by hand.

Usage

block_food_cpi(
  weight = 0.35,
  persistence = 0.5,
  demand = 0.2,
  passthrough = 0.25,
  correction = 0.1,
  sd = 3
)

Arguments

weight

Food share of the CPI basket (w_food).

persistence

Food inflation persistence (f1).

demand

Output-gap coefficient in food inflation (f2).

passthrough

Real-exchange-rate coefficient in food inflation (f3); normally larger than core's, food being more tradable.

correction

Error-correction speed on the relative food price (f4); must be positive for the relative price to be pinned down.

sd

Standard deviation of the food supply shock.

Value

A qpm_block().

Details

The block replaces headline inflation with an identity and adds:

  • pi_core — the Phillips curve, now for core inflation (it keeps the template's b1, b2, b3 and the eps_pi shock);

  • pi_food — food inflation: its own persistence, expectations of headline, demand, a stronger exchange-rate pass-through than core, and error correction on the relative food price;

  • rp_food — the relative food price gap, which accumulates the food-core inflation differential and mean-reverts through f4.

Headline is pi = w_food * pi_food + (1 - w_food) * pi_core, so everything downstream (the 4-quarter average, the Fisher equation, the policy rule) continues to use headline. To target core instead, replace the policy rule with another block.

Examples

m <- add_block(qpm_template("bkl"), block_food_cpi(weight = 0.45))
sol <- qpm_solve(m)
plot(irf(sol, shock = "eps_pifood"), vars = c("pi_food", "pi", "pi_core", "i"))