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Feldman–Mahalanobis model

A two-sector development model prioritizing investment in capital-goods capacity to raise the long-run ability to produce both capital and consumer goods.

Version
v2 · 2026-09-19 · History
Domain-specific #
4520
Domain group
Social Sciences
Origin domain
Economics & Finance
Subdomain
Development Economics → Economics & Finance

Core Idea

The model trades near-term consumption against future productive capacity under assumptions about sectoral capital coefficients, savings and closed-economy constraints; historical applications and outcomes require separate evidence. Output is divided between consumption and capital-goods sectors, investment is allocated toward the latter and expanded machine-producing capacity recursively relaxes future investment constraints. The abstraction is therefore identified by a declared carrier, a transformation or constraint over that carrier, and an invariant that tells an analyst whether the named structure is genuinely present.

How would you explain it like I'm…

Machines Before Snacks

Imagine a town that makes two kinds of things: snacks to eat, and machines that build more machines. If the town spends more effort on machines now, there are fewer snacks today. But later the extra machines can help make even more machines and more stuff. The Feldman–Mahalanobis model is about choosing that trade.

Build Machines First Plan

The Feldman–Mahalanobis model is a way economists think about how a country should grow. It splits the economy into two parts: one makes things people use, like food and clothes, and one makes machines. If a country puts more of its savings into machine-making, people get a bit less now, but the extra machines let it build even more machines and goods later. The model depends on its assumptions, like the country not trading much with others, and whether it worked in real life has to be checked separately.

Two-Sector Capital-Goods Growth Model

The Feldman–Mahalanobis model is a development-economics planning model with two sectors: consumption goods and capital goods. It trades near-term consumption against future productive capacity. Investment is directed toward the capital-goods sector, and the extra machine-making capacity loosens future limits on how much can be invested, so growth builds on itself. The model rests on assumptions about how much capital each sector needs per unit of output, the savings rate, and a closed economy with limited trade. It's a specific model, not development economics in general. Whether it describes any real country's history needs separate evidence.

 

The Feldman–Mahalanobis model is a two-sector growth-planning model that divides output between a consumption-goods sector and a capital-goods sector. Its central lever is the allocation of investment: directing a larger share toward capital goods sacrifices consumption in the near term but raises future productive capacity. Because the capital-goods sector produces the means of further investment, expanding it recursively relaxes future investment constraints. Results depend on sectoral capital and output coefficients, the savings rate, capacity constraints, the time horizon, and closed-economy or trade assumptions. Properly applying the model means stating the economy and period, sector definitions, these coefficients, the consumption path, and the empirical comparison. Historical applications and outcomes are a separate empirical question the model itself doesn't settle.

Scope of Application

Feldman–Mahalanobis model belongs to development economics and is useful where the analyst can specify the typed development economics carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, then evaluate the economy and period, sector definitions, output and capital coefficients, savings and investment allocation, capacity constraints, time horizon, consumption path, trade assumptions and empirical comparison are explicit. The scope is broad within that domain but bounded by the need for the economy and period, sector definitions, output and capital coefficients, savings and investment allocation, capacity constraints, time horizon, consumption path, trade assumptions and empirical comparison are explicit. The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.

Clarity

The abstraction clarifies a crowded vocabulary by making the economy and period, sector definitions, output and capital coefficients, savings and investment allocation, capacity constraints, time horizon, consumption path, trade assumptions and empirical comparison are explicit the center of the account. A claim should name the carrier, the governing operation or relation, the applicable assumptions, and the recognition test.

Manages Complexity

Without the abstraction, an analyst must reason directly over many local details: the carrier roles, admissibility assumptions, competing conventions, derived invariants, boundary cases, and proof or validation obligations specific to Feldman–Mahalanobis model. Feldman–Mahalanobis model compresses them into the roles in the structural signature. That compression permits comparison across instances without erasing the variables that determine validity. It also exposes which details may be varied safely and which are constitutive.

Abstract Reasoning

  1. Identify the carrier. State what the elements, states, objects, or observations are: the typed development economics carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets. Reject examples whose alleged carrier belongs to a different problem.
  2. Lock the constitutive rule. Express the economy and period, sector definitions, output and capital coefficients, savings and investment allocation, capacity constraints, time horizon, consumption path, trade assumptions and empirical comparison are explicit independently of one notation or implementation.

Knowledge Transfer

Knowledge transfers strongly among subfields of development economics because they reuse the typed development economics carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, Output is divided between consumption and capital-goods sectors, investment is allocated toward the latter and expanded machine-producing capacity recursively relaxes future investment constraints., and type the carrier, state every parameter and convention in the definition, test that the economy and period, sector definitions, output and capital coefficients, savings and investment allocation, capacity constraints, time horizon, consumption path, trade assumptions and empirical comparison are explicit, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases.

Relationships to Other Abstractions

Local relationship map for Feldman–Mahalanobis modelParents appear above the current abstraction, mutual partners to the right, and children below. Node labels state whether each abstraction is prime or domain-specific; colors identify relation types.Feldman–MahalanobismodelDOMAINPrime abstraction: Latent Realizable Capacity — is a kind ofLatent Realizab…PRIME

Current abstraction Feldman–Mahalanobis model Domain-specific

Parents (1) — outgoing typed relations

  • Feldman–Mahalanobis model is a kind of Latent Realizable Capacity Prime

    It remains its own entry because its identity is fixed by the economy and period, sector definitions, output and capital coefficients, savings and investment allocation, capacity constraints, time horizon, consumption path, trade assumptions and empirical comparison.

Hierarchy path (1) — routes to 1 parentless root

Neighborhood in Abstraction Space

Feldman–Mahalanobis model sits in a crowded region of the domain-specific corpus (9th percentile for distinctiveness): several abstractions share nearly its structure, so a description that fits it tends to fit its neighbors too.

Family — Economic & Financial Indicators (42 abstractions)

Nearest neighbors

Computed from structural-signature embeddings · 2026-10-25