Pichler et al. (2022) Dynamic IO#

Dynamic input-output model from Pichler, Pangallo, del Rio-Chanona, Lafond, and Farmer (2022), Forecasting the propagation of pandemic shocks with a dynamic input-output model, Journal of Economic Dynamics & Control.

The model couples a sectoral input-output network to a partial-equilibrium demand block. Each industry chooses output as the minimum of labour capacity, input-based capacity (parameterised by one of five production functions), and realised demand. Inventories evolve from deliveries and technical input usage; households adjust consumption from labour income with a propensity-to-consume that depends on aggregate-shock state.

Default calibration: illustrative, not empirical#

The zero-config default is a 3-sector pedagogical economy (sectors A, B, C) with hand-chosen technical coefficients designed to exhibit production-network amplification under essential-input shocks. It is not a calibration to any real economy and should not be cited as such. The spectral radius of the default TechnicalCoefficients matrix is approximately 0.38; initial output and accounting identities close exactly at the default state.

To reproduce the paper’s UK 2014 results, use the ParametersPichlerEtAl2022DIO.from_wiod_uk classmethod with user-supplied WIOD 2016-release tables and the IHS Markit critical-input matrix from the original paper’s replication archive. Neither dataset is redistributed with this package; users must obtain them under their own licence terms.

Sub-pages#

API#

from macrostat.models.PichlerEtAl2022DIO import (
    PichlerEtAl2022DIO,
    ParametersPichlerEtAl2022DIO,
    VariablesPichlerEtAl2022DIO,
    ScenariosPichlerEtAl2022DIO,
)

# Zero-config: 3-sector illustrative default.
model = PichlerEtAl2022DIO()
result = model.simulate()

# Custom configuration: override hyperparameters as needed.
params = ParametersPichlerEtAl2022DIO(
    hyperparameters={"production_function": "leontief"}
)
custom = PichlerEtAl2022DIO(parameters=params)
custom.simulate()

Production-function variants are selected via the production_function hyperparameter:

  • leontief — all inputs with positive technical coefficient bind.

  • strongly_critical — critical and important inputs bind.

  • half_critical — critical inputs bind; important inputs at half capacity.

  • weakly_critical — only critical inputs bind.

  • linear — perfect substitution across inputs.

Source#

Pichler, A., Pangallo, M., del Rio-Chanona, R. M., Lafond, F. & Farmer, J. D. (2022). Forecasting the propagation of pandemic shocks with a dynamic input-output model. Journal of Economic Dynamics & Control, 144, 104527.