Asad Islam

Professor of Economics, Monash Business School, Monash University, Australia

Part 1: The Family Card Program’s Core Design — Universal or Targeted?

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Why This Matters

The proposed Family Card program could represent the largest shift in social policy in Bangladesh’s history. At Tk 2,500 per month for around 40 million households, the annual cost would be approximately Tk 1.2 trillion—close to 2 percent of GDP.

That scale is comparable to the entire current social protection budget and similar to the national education allocation. It exceeds public health spending.

For context, large targeted cash-transfer programs in comparable countries typically cost around half of one percent of GDP.

This is not simply a campaign pledge. It is a structural commitment that, once introduced, becomes politically and socially difficult to reverse—regardless of future economic conditions.

Before debating whether it is desirable, we must address foundational questions:

Is the program universal or targeted?
How will it be financed—through taxation, borrowing, or reallocating existing spending?
Will it consolidate existing programs (nearly 100 of them) or add another layer?
What are the long-term fiscal implications if growth slows or inflation rises?

These are design questions. Design determines sustainability.

The Program’s Core Design

When a government proposes monthly transfers to millions of families, the first question must be clear: Is it for everyone—or only for those judged to be in need?

This distinction defines the program’s structure, cost, administrative demands, and long-term durability.

Universal and targeted programs operate differently. They create different expectations, require different systems, and generate very different fiscal obligations.

The Universal Path

A universal program means every household qualifies. There is no income testing, no proxy means score, no screening mechanism. The transfer is treated as a basic entitlement—closer to a citizenship dividend than selective welfare.

Arguments in favor of universality include:

Administrative simplicity: In an economy dominated by informal employment, accurately identifying the poor is complex and costly. Universality avoids that challenge.

No exclusion error: Poor households are not left out due to flawed data, outdated lists, or discretionary interference.

Reduced stigma: No one must prove poverty to receive support. This matters for dignity and social cohesion.

Political durability: When broad segments of society benefit, programs tend to be more resilient to future budget cuts.

But universality has a clear fiscal cost. At roughly Tk 1.2 trillion annually—around 2 percent of GDP—it requires explicit trade-offs.

In a country where health, education, infrastructure, and climate resilience remain underfunded, every taka allocated here cannot be allocated elsewhere.

This is not a judgment. It is arithmetic.

The Targeted Path

A targeted program restricts eligibility to households identified as poor or vulnerable. The rationale is poverty efficiency: Tk 2,500 has far greater impact for a household struggling to afford basic necessities than for a middle-income family. Targeting concentrates resources where welfare gains are highest.

It also reduces fiscal cost:

Covering the bottom 30 percent of households would cost roughly 0.6 percent of GDP.
Covering the bottom 40 percent would cost approximately 0.8 percent of GDP.

However, targeting is administratively demanding. It requires determining eligibility in an economy where incomes are informal, seasonal, and difficult to verify. No targeting system eliminates error:

Exclusion errors: Poor households left out due to imperfect data or flawed selection.
Inclusion errors: Non-poor households included, diluting resources meant for the vulnerable.

These errors shape perceptions of fairness and legitimacy.

There is also the “missing middle” issue—households just above eligibility thresholds who may feel excluded while not economically secure.

The Fiscal Reality

Bangladesh’s tax-to-GDP ratio is approximately 9 percent and has dipped lower in recent estimates. This remains well below many peer economies—roughly half that of India (17%) and significantly below Indonesia (12%) or Vietnam (20%).

Fiscal space is therefore constrained.

With such a narrow revenue base, fiscal space is structurally constrained.

A program of this scale must be financed through some combination of:

Reallocation from other sectors: Cutting health, education, or infrastructure or other social safety net programs.
Higher taxation: Expanding the tax base, which requires administrative reform and political will.
Borrowing: Domestic or external, which carries debt sustainability and inflation risks.

Sustainability is not a Year 1 question. It is a Year 10 question.

If growth slows or borrowing costs rise, a large structural transfer can crowd out other priorities or weaken macroeconomic stability.

This is the arithmetic of choice.

The Unit Problem: What Is a “Family”?

An additional design issue concerns the definition of the beneficiary unit.

What counts as a “family”? A female head of household? Or a unit linked to national ID?

In Bangladesh, family structures are fluid—multi-generational living arrangements, temporary migration for work, and shifts due to marriage or economic necessity.

If definitions are unclear, programs may unintentionally create incentives for households to split or reclassify to qualify for additional cards.

These behavioral responses are predictable. They are rational adaptations to policy incentives.

Good policy anticipates them and builds clear, transparent rules to prevent administrative disputes and unintended distortions.

A Foundational Question

We cannot meaningfully evaluate the Family Card—its cost, fairness, or long-term feasibility—until we are clear whether it is universal, targeted, or explicitly hybrid.

That clarity must come first.

In Part 2, I will examine targeting in practice: how beneficiaries are identified, how accurate different methods are, and why digital systems are not a magic solution to weak data.

The goal throughout this series is not advocacy. It is informed reasoning.

Whatever design is chosen, it should be chosen with eyes open—aware of the trade-offs, fiscal implications, and institutional demands.

Tomorrow at 10am: Part 2 — Targeting in Practice: How Do We Pick the Winners, and What Can Go Wrong?