Calibration, Validation and Sensitivity

ECONORIA Model Lab 14 — Calibration, Validation and Sensitivity

EECONORIATHINK · SIMULATE · UNDERSTAND · DECIDE

Model Lab ↗

MODEL LAB · LABORATORY 14

Calibration, Validation
& Sensitivity.

Turn a solvable model into a credible scientific instrument. Reproduce the benchmark, evaluate structural behaviour, vary uncertain parameters and closures, and report how strongly policy conclusions depend on modelling choices.

14 Scientific credibility120 Minutes± Robustness range
82CREDIBILITY SCORE

THREE DISTINCT TESTS

Solve correctly.
Behave credibly.

Calibration, validation and sensitivity answer different questions. None substitutes for the others, and all must be documented before a policy result can be trusted.

C

Calibration

z(θ, z̄) = z̄

Can the model reproduce the benchmark SAM exactly with no policy shock?

V

Validation

Model pattern ≈ evidence

Does the model reproduce historical, structural or stylized empirical behaviour?

S

Sensitivity

R = f(θ, closure, shock)

Do qualitative and quantitative conclusions survive defensible alternative assumptions?

THE CREDIBILITY WORKFLOW

Audit the model
before the headline.

01

Replicate

Confirm benchmark residuals and quantities within tolerance.

02

Diagnose

Inspect identities, market residuals, signs and scale.

03

Validate

Compare model mechanisms with evidence and theory.

04

Stress test

Vary elasticities, closures, shocks and data assumptions.

05

Document

Preserve data, code, parameters and scenario definitions.

A robust policy conclusion is one whose substantive direction survives plausible alternatives—not one that merely emerges from a preferred parameter set.

MODEL CREDIBILITY AUDITOR

Stress-test the
policy conclusion.

Change benchmark error, elasticity uncertainty and closure sensitivity. Complete the documentation checks to calculate a decision-readiness score.

SCIENTIFIC READINESS AUDIT75 / 100
CENTRAL RESULT+2.5%
LOW CASE+1.8%
HIGH CASE+3.2%
QUALITATIVE ROBUSTNESSRobust
−5%0+10%

CREDIBILITY VERDICTThe policy direction is robust, but external validation remains incomplete. Treat the magnitude as conditional.

RESEARCH-GRADE STANDARDS

Credibility is built
through transparency.

01

Traceable data

Document classification, harmonization, balancing and every transformation from source to SAM.

02

Defensible parameters

Use empirical estimates, meta-analysis or transparent assumptions with plausible ranges.

03

Multiple closures

Show whether the main result depends on labour, fiscal, investment or external adjustment rules.

04

Reproducible scenarios

Preserve source code, solver settings, shocks, baselines and result-processing procedures.

SCIENTIFIC CHECKPOINT

What does benchmark
replication establish?

Which conclusion is justified by exact benchmark replication?

Continue to Laboratory 15: Integrated Policy Simulation →