consumption smoothing and productive investments in rural zambia

Consumption Smoothing and

Productive Investments in Rural

Zambia

Juan Bonilla – AIR

A. Handa (UNICEF), N. Rai (AIR), D. Seidenfeld (AIR)

November 2015

Copyright © 2015 American Institutes for Research. All rights reserved.

AMERICAN INSTITUTES FOR RESEARCH

The case for Consumption Smoothing

• Rural households in developing countries face substantial risk

• Need to free consumption from income so not to be driven to extremities

when income is low

– LC/PIH: Modigiliani, 1959; Friedman, 1957.

• CS mechanisms: precautionary savings, risk pooling, assets as buffer

stocks, crop diversification.

• but, evidence suggests HHs only partially able to protect consumption

from income shocks

– (Kaziaga & Udri, 2006; Alderman & Paxon, 1994; Jalan and Ravallion, 1999; Townsend, 1994)

• A minimum level of income required?

2


Consumption Smoothing & UCTs

• Cash transfers: potential vehicle for sustaining household consumption

– Settings with limited formal insurance and weak credit markets

– Limited empirical evidence

Research Question:

• Do UCTs for very low income households reduce consumption

variability over time?

– If so, what are the mechanisms used to smooth consumption

3


Zambia’s Child Grant Program

- Started in 2010

- Households with a child under 3 enrolled

- Unconditional

- 55 Kwacha per month (increased over time)

- No differentiation by household size


CGP Districts: Greatest Poverty Levels(Travel Time from Lusaka by Vehicle)

Kaputa

(20 Hrs)

Kalabo

(12 Hrs)

Shangombo

(16 Hrs)


2010: Less than Half the Consumption

Compared to Similar Rural Households

-

20,000

40,000

60,000

80,000

100,000

120,000

140,000

CGP LCMS Rural LCMS RuralChild <5

LCMS 3 districts,Child<5

Kw

per

cap

ita

Total

Food


2010: 96% below extreme poverty line, much

higher than similar rural households

0

10

20

30

40

50

60

70

80

90

100

CGP LCMS Rural LCMS Rural Child <5 LCMS 3 districts, Child<5

Perc

en

t

National Extreme Poverty Line


DATA: 4 Years with 5 Rounds of Data Collection

• Baseline: Sep/Oct 2010 (early Lean Season)

• 24M: Sep/Oct 2012

• 30M: June/July 2013 (Harvest Season)

• 36M: Sep/Oct 2013

• 48M: Sep/Oct 2014


Empirical Strategies (ES)

Use two complementary identification strategies:

1. Changes in consumption for those exposed to

aggregate negative shocks vary by treatment

condition

2. Experimental Design: ∆𝑡 Consumption by

treatment condition


ES 1: DD over shocks and CGP

𝑌𝑖𝑗𝑡 = 𝛼 + 𝛽1𝑆ℎ𝑜𝑐𝑘𝑖𝑗𝑡 + 𝛽2𝐶𝐺𝑃𝑖𝑗 + 𝛽3𝑆ℎ𝑜𝑐𝑘𝑖𝑗𝑡 ∗ 𝐶𝐺𝑃𝑖𝑗+𝜃𝑋𝑖𝑗0 + 𝜂𝑡 + 𝜙𝑗 + 𝜀𝑖𝑗𝑡

𝑌𝑖𝑗𝑡 log of consumption for hh i in district j at time t

𝑠ℎ𝑜𝑐𝑘𝑖𝑗𝑡 = 1 if i affected by shock at time t

𝐶𝐺𝑃𝑖𝑗 = 1 if i is a CGP beneficiary

𝜂𝑡,𝜙𝑗 time and district fixed effects

Test for Consumption Smoothing: 𝐻0 : 𝛽1 + 𝛽3 = 0

Consistency: Shocks ⊥ 𝜀𝑖𝑗𝑡 and CGP ⊥ 𝜀𝑖𝑗𝑡

10


No difference in reporting shocks by T and C

Affected by Affected by Price Changes in

Any Drought Flood Crop Inputs Food

(1) (2) (3) (4) (5) (6)

CGP x Post 0.062 -0.009 0.062 0.010 0.002 -0.009

(0.055) (0.041) (0.045) (0.012) (0.013) (0.043)

Shock Mean 0.55 0.28 0.20 0.05 0.03 0.27

Adj. R2 0.17 0.32 0.13 0.01 0.01 0.06

N 12056 12056 12056 12056 12056 12056


… and no correlation between observables and

reporting a negative shocks

Coefficient SE

CGP recipient -0.003 0.014

Household size 0.001 0.021

Recipient is married 0.010 0.009

Age of recipient -0.000 0.001

Recipient highest grade -0.000 0.001

Number of people ages 0-5 0.001 0.021


Number of people ages 13-18 -0.002 0.022




N 9523


Coefficient SE

Maize grain price -0.000 0.001

Bean price 0.010*** 0.004

Dry fish price -0.003 0.003

Cooking oil price 0.007 0.006

Sugar price -0.006 0.007

Table salt price -0.000 0.002

Toilet soap price -0.001 0.009

Laundry soap price -0.009 0.008

Secondary school fee -0.000 0.000

Total expenditures 0.000 0.001

HH owned any chickens 0.008 0.008

HH owned any cows 0.018 0.019

HH owned any milk cows -0.019 0.014

HH owned any goats 0.014 0.028

HH owned any goats 0.014 0.021

N 9523

… and no correlation between observables and

reporting a negative shocks


Results: CGP insulates recipients against shocks

Log of Total Expenditures

(1) (2) (3) (4)

Negative Shock (𝜷𝟏) -0.07*** -0.07*** -0.06** -0.05**

(0.02) (0.02) (0.02) (0.02)

CGP (𝛽2) 0.27*** 0.26*** 0.24*** 0.20***

(0.05) (0.05) (0.04) (0.03)

CGP x Shock (𝛽3) 0.03 0.04 0.05 0.06*

(0.04) (0.03) (0.03) (0.03)

Shock, CGP -0.037 -0.024 -0.007 0.010

(𝜷𝟏 + 𝜷𝟑) (0.028) (0.029) (0.025) (0.022)

Mean of Shock 0.60 0.60 0.60 0.60

Time FE Yes Yes Yes

Demographics Yes Yes

Food prices Yes

Adj. R2 0.06 0.07 0.19 0.21

N 9541 9541 9541 9539


… regardless of the type of shock

Affected by Affected by Price Changes in

Any Drought Flood Crop Inputs Food

(1) (2) (3) (4) (5) (6)

Shock, CGP:

Total Expenditures 0.010 -0.024 0.006 0.066 -0.026 0.021

(𝛽1 + 𝛽3) (0.022) (0.030) (0.033) (0.043) (0.061) (0.025)

Food Expenditures 0.005 -0.003 0.002 0.017 -0.010 0.006

(𝛽1 + 𝛽3) (0.006) (0.009) (0.010) (0.013) (0.018) (0.007)

Mean of Shock 0.60 0.32 0.16 0.06 0.03 0.30

N 9539 9539 9539 9539 9539 9539


Empirical Strategy 2:

Tracking expenditure levels over time

𝑦𝑖𝑗𝑡 = α + 𝛾1𝐶𝐺𝑃𝑖𝑗 + 𝛾2t𝑑𝑡 + 𝛾3t𝑑𝑡 ∗ 𝐶𝐺𝑃𝑖𝑗 +𝜓𝑋𝑖𝑗0 + 𝜁𝑖𝑗t

𝑌𝑖𝑗𝑡 consumption for household i in district j at time t

𝐶𝐺𝑃𝑖𝑗 = 1 if i is a CGP beneficiary

𝑑𝑡 time fixed effects

Test for Consumption Smoothing:

Control: 𝐻0𝐶: 𝛾2,24 = 𝛾2,30 = 𝛾2,36 = 𝛾2,48

CGP: 𝐻0𝑇: 𝛾2,24 + 𝛾3,24 = 𝛾2,30 + 𝛾3,30 = 𝛾2,36 + 𝛾3,36 = 𝛾2,48 + 𝛾3,48

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𝑆24 𝑆30 𝑆36 𝑆48


CGP recipients show more stable consumption

levels over time

𝛾2,24

𝛾3,24


CGP recipients show more stable consumption

levels over time

Total Food Domestic Health Other

(1) (2) (3) (4) (5)

Baseline Mean 40.48 30.03 2.25 5.18 2.97

Tests (p-values):

𝛾2,24 = 𝛾2,30 = 𝛾2,36 = 𝛾2,48 0.00 0.00 0.04 0.10 0.99

ST,24=ST,30=ST,36=ST,48 0.17 0.12 0.02 0.42 0.23

Adj. R2 0.17 0.16 0.07 0.06 0.07

N 12054 12056 12054 12054 12053


… the control group exhibits more food consumption

volatility as a fraction of total spending


Smoothing consumption shares

Food Domestic Health Other

(1) (2) (3) (4)

Baseline Mean 0.72 0.15 0.06 0.07

Tests (p-values):

𝛾2,24 = 𝛾2,30 = 𝛾2,36 = 𝛾2,48 0.00 0.10 0.00 0.02

ST,24=ST,30=ST,36=ST,48 0.93 0.58 0.00 0.09

Adj. R2 0.04 0.07 0.02 0.09

N 12054 12054 12054 12053


Mechanisms for Consumption

Smoothing

- Use of Livestock as buffer stock

- Build precautionary savings

- Invest in productive activities

- Reduce debt burden


Livestock may be used as buffer stock


CGP HHs own more livestock

Proportion

Chickens Cattle Goats Ducks

(1) (2) (3) (4)

Treat x Post 0.152*** 0.094*** 0.033** 0.027**

(0.035) (0.020) (0.012) (0.008)

Baseline Mean 0.43 0.10 0.02 0.03

Adj. R2 0.13 0.08 0.06 0.02

N 12038 12056 12056 12052


Results consistent with reported coping strategies to

negative shocks

Use

Savings

Sold

Assets

Reduce

Expenses

Work

More

Use

CGP

(1) (2) (3) (4) (5)

Treat x Post 0.032* -0.002 -0.069* -0.115** 0.106***

(0.016) (0.006) (0.036) (0.044) (0.011)

Outcome Mean 0.04 0.01 0.13 0.39 0.00

Adj. R2 0.04 0.01 0.04 0.05 0.17

N 6980 6980 6980 6980 5156


Coping strategies to any negative shock


Conclusions

- CGP beneficiaries insulates against aggregate

negative shocks

- ... By investing in productive activities and engaging in

CS mechanisms

- A minimum income value may be needed for

subsistence HHs to overcome constraints preventing

smooth consumption

Juan Bonilla

[email protected]

1000 Thomas Jefferson Street NW

Washington, DC 20007-3835

General Information: 202-403-5000

www.air.org

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consumption smoothing and productive investments in rural zambia

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