jpam-theory-building

Theory of Change & Mechanism (jpam-theory-building)

JPAM is empirical, but the best policy papers are not atheoretical. The "theory" here is a **theory of

change**: a transparent logic that says why the policy lever should move the outcome, *through what

mechanism, for whom, and under what conditions it would (or would not) transfer* to another

jurisdiction or scale. This frame is what turns a single estimate into evidence a policymaker elsewhere

can use, and it disciplines the cost-benefit and heterogeneity analysis downstream.

When to trigger

• Specifying the logic model / theory of change before or alongside the design
• A reviewer asked "what's the mechanism?" or "why would this generalize?"
• Deciding which heterogeneity and mediation analyses are theory-driven (not fishing)
• Framing scope conditions for external validity and scale-up

Building the theory of change

1. Lever → mechanism → outcome. Write the causal chain explicitly: the policy changes X (incentive,

constraint, information, price, access), which operates through mechanism M, producing outcome Y.

1. Behavioral or institutional micro-foundation. Say who responds and why — incentives,

liquidity, salience, capacity, compliance, take-up. Ground it in the relevant econ / PS / PA theory.

1. Predicted heterogeneity. Whom should the effect be larger or smaller for? Specify before

estimation so subgroup results read as tests, not data-mining.

1. Scope conditions for transfer. What features of this setting (administrative capacity, market

structure, population, complementary policies) does the effect depend on? This governs external

validity and scale-up claims.

1. Unintended effects and general equilibrium. Name plausible offsetting or spillover responses a

policymaker would worry about (displacement, crowd-out, behavioral adaptation).

What the theory buys (JPAM-specific)

• It tells policymakers in other jurisdictions whether the result should travel.
• It pre-commits the heterogeneity and mediation analyses, protecting them from fishing critiques.
• It specifies which costs and benefits enter the cost-benefit analysis and for whom (distribution).
• It distinguishes "the program worked here" from "this kind of program works through this mechanism."

Checklist

• [ ] An explicit lever → mechanism → outcome chain written down
• [ ] A behavioral/institutional micro-foundation for who responds and why
• [ ] Predicted heterogeneity stated before estimation
• [ ] Scope conditions for transfer / scale-up named
• [ ] Plausible unintended effects, spillovers, or GE responses flagged
• [ ] Mechanism tied to specific, testable observable implications

Anti-patterns

• A bare estimate with no mechanism — "the program raised Y" with no account of why
• Post hoc storytelling that fits whatever heterogeneity the data happened to show
• Claiming broad generalizability with no stated scope conditions
• Ignoring unintended consequences a policymaker would immediately ask about
• Borrowing a formal model that adds notation but no testable, policy-relevant implication

Worked micro-example (illustrative)

A team evaluates a tax-credit expansion. The bare version says "the credit raised employment." The

JPAM theory-of-change version writes the chain — *credit raises the after-tax return to work

(mechanism: labor-supply incentive) → larger response for the population facing the steepest

participation tax (predicted heterogeneity: single parents near the phase-in) → effect depends on local

labor demand and on take-up via tax-filing (scope conditions) — and flags a plausible *unintended

effect** (employers capturing part of the credit through wage adjustment). Each link is then a testable

implication the design and heterogeneity analysis must address, and the scope conditions tell a

policymaker in another state whether the result should travel. (Fields/numbers illustrative.)

Calibration anchors (hedged)

• The "theory" JPAM wants is a transparent logic model, not necessarily a formal model; added

notation must buy a testable, policy-relevant implication.

• Scope conditions are a strength, not a hedge: they are how a single evaluation informs decisions

elsewhere, which is JPAM's whole purpose.

• Pre-specify heterogeneity and mechanism tests so they read as confirmatory, not as fishing.

Output format

【Lever → mechanism → outcome】the causal chain in one line
【Micro-foundation】who responds and why
【Predicted heterogeneity】subgroups specified ex ante
【Scope conditions】what the effect depends on for transfer
【Unintended effects】spillovers / GE / displacement flagged
【Next】jpam-research-design

Supplementary resources

• [../../resources/exemplars/library.md](../../resources/exemplars/library.md) — JPAM papers whose mechanism makes the result portable
• [../../resources/external_tools.md](../../resources/external_tools.md) — mediation / mechanism estimation packages