Which Form of Safety Net Transfer is Most Beneficial? Impacts on Income, Food Security, - PowerPoint Presentation

Slide1

Which Form of Safety Net Transfer is Most Beneficial? Impacts on Income, Food Security, and Child Nutrition

Akhter Ahmed, John Hoddinott, Wahid Quabili, Shalini Roy, Fiona Shaba, and Esha SraboniInternational Food Policy Research InstituteStakeholder Workshop3 December 2013, Dhaka

Slide2

TMRI Objectives

The overall objective of the Transfer Modality Research Initiative is to provide evidence that can be used to streamline the social safety net system in Bangladesh. The research will inform policymakers which type of program can best improve the income status and food and nutrition security of the poor and thus be a valuable tool to the government as it prepares its social protection strategy.

The research has the following specific objectives:Measure the impact and cost-effectiveness of transfer methods on these key outcomes:

household incomehousehold food security child nutritionEvaluate the process of delivering benefits (that is, transfers and nutrition knowledge) at the operational level and solicit feedback from program participants

Slide3

Transfer Modalities

TMRI with 5 arms: Only cashOnly food

Food + cashNutrition behavior change communications (BCC) + cashNutrition BCC + food

WFP implements TMRI; IFPRI evaluates itImplemented in 5 upazilas in north-west, 5 upazilas in south

Slide4

Transfer amounts

The value of transfer per household is the same for each of the 5 transfer modalities: 1,500 taka ($18.75) per household per monthCash: transferred to beneficiaries within the first week of every month

through mobile phone money transfer service Food: 30 kg of rice; 2 kg of mosur (lentil) pulse; and 2 kg of micronutrient fortified cooking oil Food-cash combination:

total transfer is a combination of 50% food (15 kg of rice; 1 kg of mosur pulse; and 1 kg of cooking oil) and 50% cash (750 taka)

Slide5

TMRI Participants and control households

For the pilot test evaluation, we use 50 clusters (villages) and 10 households per village for each treatment arm and the control. Thus, each treatment and control includes 500 households 3 transfer modalities, nutrition BCC + cash, and control in the Northern region: 250 clusters (villages) and 2,500 households3 transfer modalities, nutrition BCC + food, and control in the Southern region: 250 clusters (villages) and 2,500 households (10 households per cluster)Total sample size: 500 clusters and 5,000 households4,000 beneficiaries and 1,000 control households

Slide6

TMRI upazilas in the northwest and the southern regions

Slide7

Evaluating Impacts

IFPRI designed a rigorous impact evaluation of the Transfer Modality Research Initiative (TMRI) in the north and the south: Only cash (north & south)

Only food (north & south)Food + cash

(north & south)Nutrition behavior change communication

(BCC) +

cash

(north)

Nutrition BCC +

food

(south)

We developed a randomized controlled trial (RCT) design to evaluate the impact of the 5 transfer modalities

Randomization is often termed as the “gold standard” for impact evaluation because it is the most powerful way to construct a valid counterfactual of what might have happened without the program

We used RCT with “before-and-after” and “with-and-without” differences for estimating the impact of transfers

We used the analysis of covariance (ANCOVA) method of estimating impact

Slide8

RCT impact estimate with difference-in-differences

 

Baseline

(Before)

Follow-up

(After)

P

A

C

A

Program

Control

Impact = (P

A

- C

A

) - (P

B

- C

B

)

P

B

= C

B

Outcome

Slide9

Estimating impact using Analysis of Covariance

(ANCOVA) regression The ANCOVA regression model that we used to estimate impact is the following (example for the north):

With difference-in-differences:

Impact =

[(

Y

t

treat

– Y

t-1

treat

) - (

Y

t

control

– Y

t-1

control

)]

With ANCOVA regression:

Impact =

[(

Y

ttreat – αYt-1treat

) - (Ytcontrol – αYt-1control)]ANCOVA is “more flexible” in the sense that the ANCOVA estimate is equivalent to the diff-in-diff estimate if α = 1.  But ANCOVA allows estimating the autocorrelation rather than imposing it to be 1 

ANCOVA estimates are preferred over diff-in-diff estimates, given the high variability and low autocorrelation of the data at baseline and follow-up (McKenzie 2012, Journal of Development Economics) 

Slide10

Household surveys for impact evaluation

The required quantitative data for impact evaluation come from three household surveys

The first household survey, carried out in April 2012 (just before the start of transfers), provides

the information needed for the baseline study A first follow-up survey was conducted in June 2013, just after completing 12 months of transfer distributions

A second follow-up or endline survey will be conducted in June 2014, after 24 months of transfer distribution

The

surveys include

4,000 TMRI

participants and

1,000 non-participant

control households

Slide11

Results

Slide12

Baseline per capita monthly expenditures (proxy

for income): 19% higher average income in the south

Slide13

Impact of

transfers on per capita monthly expenditure (proxy for income): Absolute change (taka)

Slide14

Impact of transfers on per capita monthly expenditure (proxy for income): Percentage change

Slide15

Impact of transfers on per capita monthly food expenditure: Percentage change

Slide16

Impact of transfers on per capita monthly non-food expenditure:

Percentage change

Slide17

Impact of

transfers on per capita daily food energy (calorie) acquisition: Absolute change (kcal)

Slide18

Impact of transfer on food poverty: Percentage point

reduction in prevalence of <2,122 kcal/person/day

Slide19

Impact of transfer on hard-core food poverty: Percentage point

reduction in prevalence of <1,805 kcal/person/day

Slide20

Aggregate food groups and weights to calculate the Food Consumption Score (Source: WFP)

Group

Food itemsFood groupWeight

1Rice and other cereals

Staples

2

2

Beans, lentils, peas and nuts

Pulses

3

3

Vegetables and fruits

Vegetables and fruits

1

4

Beef, goat, poultry, eggs, and fish

Meat, eggs and fish

4

5

Milk, yogurt, and other dairies

Milk

4

6

Sugar, sugar products, and honey

Sugar

0.5

7

Oils, fats, and butter

Oil0.5

Slide21

Impact of transfer modalities

on diet quality: Absolute change in Food consumption score

Slide22

North: Baseline vs.

EndlineCash+BCC South: EndlineFood

vs. Food+BCC Examples of kernel density functions of

FCS

Slide23

Impact of transfer modalities on diet quality:

Change in dietary diversity (number of food consumed out of 12 food groups)

Slide24

Impact of transfer on child nutritional status: Percentage point

reduction in prevalence of stunting (children 6-59 months <-2 height-for-age Z-score)

Slide25

Summary and Conclusions

Slide26

Summary and conclusions

Our estimation strategy relies on the randomized design, which eliminates systematic differences between participants and non-participants and minimizes the risk of “selection bias”As a result, average differences in outcomes across the groups after the intervention can be interpreted as being truly caused by, rather than simply correlated with, the receipt of transfers and transfers with nutrition

educationMoreover, we take advantage of the baseline survey and estimate the treatment effect using Analysis of Covariance (ANCOVA) regression, which is our preferred method over difference-in-difference

estimates

Slide27

Summary and conclusions

Differences in the size of impact as revealed from the F-tests:Income in the north: “Only cash” has statistically significant higher impact than “Cash+food”.

There are no statistically significant difference between “Only cash” and “Only

food”. “BCC+cash” has higher impact than those of the other 3 treatment arms, and these differences are statistically significant.

Income in the south:

“

BCC+food

” has significantly larger impact than those

of the other 3 treatments

. No statistically significant difference between other treatment arms.

Slide28

Summary and conclusions

Differences in the size of impact as revealed from the F-tests:Calories in the north: “BCC+cash” has significantly larger impact than those of the other 3 treatments. No statistically significant difference between other treatment arms

.Diet quality (FCS) in the north and the south: “Only food” has significantly higher impact than “Only cash” and

“Cash+food”. “BCC+cash” and “BCC+food” have

significantly larger impact than those of the other 3

treatment arms.

Stunting in the north:

“

BCC+cash

”

has significantly larger impact than those of the other 3 treatments. No statistically significant difference between other treatment arms

.

Slide29

Summary and conclusions

In the north, the poorest region in Bangladesh, we found statistically significant positive  impacts of all 4 modalities on (1) income, (2) food expenditure, (3) non-food expenditure, (4) calorie acquisition, (2) food poverty, (5) diet quality, and (6) child stunting, with “Cash+BCC” having the biggest size of impacts on all 6 indicators.

However, in the south, which is a disaster prone, but relatively higher income region than the north, . “Food+BCC

” has statistically significant impacts on income, food and non-food expenditure, calories, and diet quality, but not on stunting. “Food only” has significant impact on income and food and non-food expenditures, and diet quality. “Cash+food” has significant impacts on income, food expenditures and diet quality.

“Cash

only” has statistically significant impact only on diet quality.

Slide30

Summary and conclusions

It is intriguing to find that food and cash transfers have by far the leading impact when they are combined with nutrition BCC. Why does BCC have the largest impact even though the training curriculum does not include non-nutrition livelihoods attributes?  Does participation in BCC activities

raise women’s status/empower them? We will probe into this question in early 2014 through an in-depth qualitative study. Why

do patterns in the north and the south differ?  In the south, participants of “Cash only”, “Food only” and

“

Cash+food

” improved their diet quality rather than quantity. Only

“

Food+BCC

” group shows improvements in both diet quantity and quality.

Our survey results

from the south indicate

that,

the greater the risk of disaster, the less likely a household is to immediately “consume” a transfer –

and,

for example, more likely to use it for precautionary savings given the risk of future bad shocks, or to use it to repair/improve houses that were damaged in a

cyclone.

But

the process of BCC training seems to result

in

enhancing resilience to shocks as the transfer

beneficiaries exposed

to disaster risks manage to balance a nutritional

diet, presumably

with the need to stay prepared for and cope with shocks

. We will test this hypothesis in our 2014 research (quantitative and qualitative).

Slide31

Interim policy options

Integrate nutrition into social safety nets Increase the size of transfers of safety nets to generate sizable impacts on food security and nutritional outcomes

The size of transfer relative to household income is tremendously important when trying to achieve sustainable improvements in the food security and livelihoods of the poor

There are over 90 safety net programs currently operating in Bangladesh. However, benefits of most of these programs

are spread too thinly to have any noticeable impact. Phasing

out ineffective programs

and redistributing funds among the effective ones would enable the government to substantially increase the transfer size without reducing the total coverage with the current level of the safety net budget (US$3.2 billion in fiscal year 2012-2013)