View source: R/blocks_library.R
| block_food_cpi | R Documentation |
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.
block_food_cpi(
weight = 0.35,
persistence = 0.5,
demand = 0.2,
passthrough = 0.25,
correction = 0.1,
sd = 3
)
weight |
Food share of the CPI basket ( |
persistence |
Food inflation persistence ( |
demand |
Output-gap coefficient in food inflation ( |
passthrough |
Real-exchange-rate coefficient in food inflation
( |
correction |
Error-correction speed on the relative food price
( |
sd |
Standard deviation of the food supply shock. |
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.
A qpm_block().
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"))
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