An Asset-Based Approach to Poverty Dynamics and Safety Nets: Research and Policy Questions

Christopher B. Barrett

Cornell University

Michael R. CarterUniversity of

Wisconsin

November 7, 2005 Inter-American Development Bank

Washington, DC

Overview

An Asset-based Perspective on Poverty Poverty Traps and the Dynamic Asset Poverty

Threshold Empirical Evidence on Poverty Traps—What We

Know So Far Bifurcated Asset Dynamics (South Africa) Long-term Effects of Short-term Shocks

(Honduras) Asset Smoothing and Its Human Costs (Zimbabwe) Exclusion from Informal Safety Nets (East Africa)

Cash Transfer Programs & Poverty Traps—What We Don’t Yet Know

Future Directions for Cash Transfer Programs

Evolving Views of Poverty

Successive generations of poverty analysis1st: static income/expenditure analysis

(headcount, poverty gap, FGT measures)

2nd: dynamic income/expenditure analysis (chronic/transitory poverty distinction)

3rd: static asset poverty analysis(structural/stochastic poverty distinction)

4th : dynamic asset poverty analysis(behaviorally-based poverty lines)

Asset-Based View of Poverty

Transitions from poverty:

1) Stochastic churning (B to u(A’’))

2) Structural via accumulation

(A’ to A”)3) Structural via higher returns

(u(A’) to C)

Single Period Income and Asset Poverty Lines

)(ˆ Au

A 'A "A

Pov Line, u

Assets

Util

ity

Asset Poverty Line

)"(ˆ Au

B

C

)'(ˆ Au

ũ(A)

Poverty Traps and the Dynamic Asset Poverty Threshold Will structurally poor move ahead over time?

Depends on underlying dynamics of asset accumulation.

Lessons from empirical macroeconomics – is growth characterized by unconditional convergence, convergence clubs, or threshold-based multiple equilibria?

Key question: do returns to productive assets (land, labor, etc.) increase locally in wealth?

What causes such dynamics and locally increasing returns?

• Increasing returns to scale in income generating process

• Minimum investment levels/indivisibilities• Uninsured risk

Exclusion from opportunities is key

Social exclusion: ethnic/gender barriers

Financial exclusion: credit/insurance access

Two can be reinforcing (Mogues and Carter 2005)

At=A0 (dynamic equilibrium)

AS

Static Asset Poverty Line

Dynamic Asset Poverty Line

A*2A*1 A*

Utility

A

Income Poverty Line

Initial Assets

L1

L2

Next Period’s Assets

U*H

U*L

A 4th Generation View

Poverty TrapDynamic Asset Poverty Line (Micawber Threshold)

Empirical Evidence on Poverty Traps—What We Know So Far Theory thus suggests circumstances in which

poverty traps might exist But what do we know about their actual

existence and importance Brief review now of various empirical studies

that test for different implications of poverty traps

Bifurcated Asset Dynamics(South Africa)

South African data, 1993-1998 (KIDS study) Define and estimate asset index for each household i in each

period t, t(Ait), such that asset weights (‘prices’) depend on asset mix

Index scaled such that it is measured in “poverty line units” (PLUs)—i.e., the index tells us what fraction of the poverty line a household’s bundle of assets would be expected to generate

Non-parametric estimation of asset dynamics Key findings:

Divergent dynamics Repelling ‘Micawber Threshold’ at ~2 PLUs Poverty trap equilibrium at 0.9 PLUs Corroboration by later qualitative and quantitative data

Bifurcated Asset Dynamics

0 1 2 31993 Asset Index, (Poverty Line Units)

0

1

2

3

1998 A

sset In

dex,

(P

ove

rty

Lin

e U

nits

)

Poverty Trap

Expected Asset Dynamics95% Confidence Bands

Micawber Threshold

Source: Adato, Carter and May (2006). “Exploring Poverty Traps and Persistent Poverty In South Africa Using Qualitative and Quantitative Data” JDS

Estimated South African Asset Dynamics

0 1 2 3

Initial Livelihood (normalized by poverty line)

-20

-10

0

10

20

Rate

s of G

row

th (

%)

5 year growthAnnualized growth rate

Poverty Trap Micawber Threshold

Long-term Effects of Short-term Shocks (Post-Mitch Honduras)

Lowest Wealth Quartile Highest Wealth Quartile No Shock 31% Asset Loss No Shock 31% Asset Loss

Poor Market Access

Good Market Access

Poor

Market Access

Good Market Access

Pre-Shock Assets

$650 $650 $650 $76,821 $76,821 $76,821

Post-Recovery Assets

$902 $321 $686 $83,905 $54,951 $64,537

30 Month Growth Rate

39% -50% 5.5% 9% -28% -15%

iizbiibiiAbibi ZKLAKLAAg ),,(),,(

Source: Carter et al. (2005). “The Long-term Impacts of Short-Term Shocks: Poverty Traps and Environmental Disasters in Ethiopia and Honduras”

Asset Smoothing & Its Human Costs(Zimbabwe)

Dependent variable: Sales of oxen

Fixed effects specification

Arellano-Bond one-step

estimator

Arellano-Bond two-

step estimator Negative rainfall shock x dummy for owned 1-2 oxen at t-1

0.043 (1.09)

Negative rainfall shock, x dummy for owned > 2 oxen at t-1

0.151 (3.66)**

Δt, t-1 Negative rainfall shock x dummy for owned 1-2 oxen at t-1

0.109 (2.39)**

0.109 (3.00)**

Δt, t-1 Negative rainfall shock, x dummy for owned > 2 oxen at t-1

0.250 (2.56)**

0.275 (4.27)**

Asset Smoothing & Its Human Costs(Zimbabwe) Those owning >2 oxen liquidated animals at 3.5-6x

rate of those owning 1-2 in response to 1994-95 drought

Drought persistently lowers growth rates of children 12-24 months, temporarily lowers BMI of women, but no effect on men or older pre-schoolers.

The nutritional impact is larger and more persistent in households with lower levels of livestock holdings. Asset portfolio choice – protect human or livestock capital

Temporary shocks, even mild ones, can have long-term consequences

Source: Hoddinott (2006). “Shocks and Their Consequences within and between Households,” JDS

Exclusion from Informal Insurance

There might be holes in informal safety nets: Santos and Barrett (2005) on Ethiopian pastoralists’

social invisibility within the poverty trap: Logit estimates suggest that transfers flow in response to

shocks, but only to those who have not collapsed into the poverty trap.

Those in the trap are significantly less frequently known – smaller networks. Estimated 39% have no effective social insurance network.

Implication: transfers to persistently poor have negligible crowding out effects.

Lybbert et al. (2004), Lentz and Barrett (2005) and McPeak (2006): meager interhousehold transfers among east African pastoralists, no “crowding out” effects

Cash Transfer Programs & Poverty Traps—What We Don’t Yet Know While the empirical is still thin and imperfect,

hopefully it is sufficient to encourage a deeper look at poverty traps and what they might mean for programs like Progressa

To introduce these ideas and implications, I would like to criticize my own study of a South African (unconditional) cash transfer scheme, the Child Support Grant (CSG)

Cash Transfers & Poverty Traps

0.0 0.2 0.4 0.6 0.8 1.0

Extent of CSG Treatment (fraction of 36 month window)

-1.0

-0.5

0.0

0.5

1.0C

ha

ng

e in

z-s

core

0.0

0.5

1.0

1.5

De

nsi

ty

Expected Treatment Effect95% Interval EstimateDistribution of Treatment

Source: Agüero, Carter and Woolard (2005). “From Flows to Stocks: The Impact of Unconditional Cash Transfers on Human Capital”

So what is long-term value of this human capital asset? Assume that:

Maintain z-score gain 2.1 cm gain in adult height Adopt Thomas-Strauss wage-height elasticity estimate of

2.4-3.3 Implies adult monthly wage gain of R190-R262 Wage gain accrues from 25-65 years old with 50\%

unemployment Results

Present value at birth of expected wage gain: R6500-7500 Program cost: R3400 (plus administration costs) Benefit-Cost: 1.6-2.3

But two critical questions to ask of this simple analysis: Sufficient to surmount threshold? Sustainability of human capital gains given probability of

shocks?

Cash Transfers & Poverty Traps

Future Directions for Cash Transfer Programs

Progressa/Opportunidades compelling because targets well-being of current generation & inter-generational transmission of poverty

Yet we would seem to know relatively little about whether the flows and stocks of Progressa create basis for sustained accumulation for some or all beneficiaries

Researchable question, but also one worthy of further experimentation: Levels of support Basic asset grant Remedy exclusion (leverage transfer flows) Protection against shocks (perhaps only common

shocks for incentive compatibility purposes)

Implications for Policy & Policy Experiments

In summary, shocks in the presence of poverty traps imply:

Long run micro (macro?) growth effects Costly chronic poverty Costly avoidance of persistent poverty (asset

smoothing) Social protection policy built around this behavioral

poverty line would appear to be: Cost-effective Imply unpleasant triage?

Would also seem to imply that ex ante insurance/ credible safety nets have behavioral/growth implications

References• Theory and Concepts

• Carter and Barrett (2006). “The Economics of Poverty Traps and Persistent Poverty: An Asset-based Approach,” JDS

• Bifurcated Asset Dynamics• Adato, Carter and May (2006). “Exploring Poverty Traps and Persistent Poverty In South

Africa Using Qualitative and Quantitative Data” JDS• Lybbert, Barrett, Desta and Coppock (2004), “Stochastic Wealth Dynamics and Risk

Management Among A Poor Population,” EJ • Barrett, Marenya, McPeak, Minten, Murithi, Oluoch-Kosura, Place, Randrianarisoa,

Rasambainarivo and Wangila (2006), “Welfare Dynamics in Rural Kenya and Madagascar,” JDS

• Long-term Effects of Shocks• Carter, Little, Mogues and Negatu (2006). “The Long-term Impacts of Short-Term Shocks:

Poverty Traps and Environmental Disasters in Ethiopia and Honduras,” WD• Lybbert et al. (2004), EJ

• Asset smoothing/Consumption destabilization• Hoddinott (2006) “Shocks and Their Consequences within and between Households,” JDS.• Zimmerman and Carter (2003), “Asset smoothing, consumption smoothing and the

reproduction of inequality under risk and subsistence constraints “ JDE• Barrett et al. (2006), JDS

• Exclusion from Informal Insurance• Santos and Barrett (2005), “Poverty traps and informal insurance: Evidence from southern

Ethiopia” Cornell working paper. • Lentz and Barrett (2005), “Food Aid Targeting, Shocks and Private Transfers Among East

African Pastoralists,” Cornell working paper. • Lybbert et al. (2004) EJ• McPeak (2006), "Confronting the Risk of Asset Loss:  What role do livestock transfers in

northern Kenya play?" JDE

Thank you!