農業・資源経済学ワーキングペーパー
Agricultural and Resource Economics Working Paper
No. 20-F-01

Improving Infant Nutrition through the Market:
Experimental Evidence in Ghana

Satoru Okonogi, Takeshi Sakurai, and Reginald Adjetey Annan

May 2020

東京大学大学院農学生命科学研究科 農業資源経済学専攻
Department of Agricultural and Resource Economics, Graduate School of Agriculturaland Life Sciences, The University of Tokyo

Improving Infant Nutrition through the Market:
Experimental Evidence in Ghana
Satoru Okonogi, Takeshi Sakurai, and Reginald Adjetey AnnanMay 2020

Abstract

We study the impact of introduction of a new complementary food product for infants
into the market in Ghana. To investigate the effect of mother’s purchase of the new
product, Koko-plus, we conduct a sale experiment with randomly selected mother-infant
pairs. We find that the introduction of Koko-plus into the market itself as well as
mother’s purchase of it significantly increase child’s weight. The results imply that thecomplementary food market works for improving infant nutrition. However, the effecton body weight gain seems to be low and could be much higher because the number ofpackages purchased by the treated mothers is still small (less than 1 package per week
on average). In order to obtain sufficient effects, interventions to encourage mothers’
purchase will be required.

Key words –– complementary food product, child nutrition, randomized controlled trial, Ghana

The present study was financially supported by Ministry of Agriculture, Forestry and Fisheries
of Japan through Extramural Research Program for Agricultural, Forestry and Fishery Policy
Research (from 2015 to 2017). We thank kind assistance given by Ajinomoto Co., Inc.
 Satoru Okonogi, Department of Agricultural and Resource Economics, Graduate School of
Agricultural and Resource Economics, The University of Tokyo: satoru.ek9@gmail.com
Takeshi Sakurai, Department of Agricultural and Resource Economics, Graduate School of
Agricultural and Resource Economics, The University of Tokyo: atsakura@mail.ecc.u-tokyo.ac.jp
Reginald Adjetey Annan, Department of Biochemistry and Biotechnology, Faculty of Biosciences,
College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana:reggie@imtf.org

1 Introduction
One of the most important development goals is the end of child undernutrition. The
undernutrition during early childhood has adverse effects on health and socio-economic status in
the long run (Bhaltra et al., 2017; Hoddinott et al., 2008; Hoynes et al., 2016; Malucchio et al.,2009). In developing countries, exclusive breast feeding until 6 months of age is recommended
by WHO. After that, the introduction of complementary feeding is required because breastfeedingalone will result in nutritional deficiencies. However, since infants from 6 months to 2 years oldhave many restrictions on what they can eat, it is difficult to improve their nutrition throughcomplementary feeding. Our study country, Ghana, seems to face typically this problem.
Although stunting rate of children under 5 declined during recent 10 years in Ghana, 35% in 2003
to 19% in 2014 (GSS et al., 2014), the stunting rate tends to increase with the age, 8.0% at lessthan 6 months to 21.9% at 18-23 months old (GSS et al., 2015). This implies that there remains
the problem of complementary feeding during infancy in Ghana.
A popular approach to tackle with this problem has been the use of nutritionally enhanced
complementary or supplements, particularly through free distribution (Lutter, 2003). However,there are some concerns on the free distribution, such as sustainability of the aid and anchoring
effects (Kremmer and Miguel, 2007; Fischer et al., 2019). The sale of commercial complementary
food products, on the other hand, has now become a very common landscape even in developing
countries. Most of them are also nutritionally enhanced 1 . Therefore, if such products prevail
through the market and improve child nutrition, the “market-based approach” will be a sustainable
way to solve the problem of infants’ undernutrition.
There is a body of literature showing that the provision of nutritionally enhanced
complementary foods has positive impacts on child nutrition2. However, since most of the studies
are based on free distribution, little is known “if not free”. The evidence for the positive effectsof the products through free distribution does not necessarily mean that they have any impact ifthey are sold. If mothers buy less than receive the product free and its marginal effect is large, forexample, we may obtain an insignificant effect of product sale even though we observe asignificantly positive effect with free distribution. Economists made an effort to elicit willingness1Masters et al. (2016), however, point out that the quality variance of the commercial products is large indeveloping countries.
2See Dewey and Adu-Afarwuah (2008), which gives a good review on this topic in nutritional science.

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to-pay for complementary food products to estimate their potential market size (Lybbert et al.,2018; Masters and Sanogo, 2002). However, their impact on child nutrition, if they are sold, isstill unclear.
In this study, we investigate the impact of sale of a complementary food product on childnutrition in Ghana. To deal with the endogeneity problem relating to mothers’ purchasing decision,
we adopt a randomized controlled experiment, in which we give opportunities to buy a newcomplementary food product for infants, Koko-plus, to randomly selected mothers. We conduct
the sale experiment every week and record exact number of packages purchased in each week toavoid unreliable retrospective recall data. We continue the weekly experiment for almost half ayear. Then, we find that mother’s purchase of Koko-plus significantly increases child’s weight
but that it has no effect on child’s height.
By adopting a randomized controlled experiment, this study makes a new contribution to theliterature on the role of the market for the improvement of child nutrition in developing countries,
where all the existing studies reply on observational data (Abay and Hirvonen, 2017; Headey etal., 2019; Hirvonen and Hoddinott, 2017；Hirvonen et al., 2017；Hoddinott et al., 2015; Stifel
and Minten, 2017). In addition, as far as we know, this is the first paper evaluating the impact of
the introduction of a new complementary food product into the market based on a randomized
controlled experiment because we conduct the sale experiment in areas where Koko-plus has notbeen introduced.
This study contributes to the literature on the effects of mothers’ nutritional knowledge, as well.
It has been a consensus that such knowledge improves child nutrition (Block, 2004, 2007;
Glewwe, 1999) and educational intervention works well (Bhandari et al., 2004; Penny et al., 2005;
Shi et al., 2010). However, a recent paper of Hirvonen et al. (2017) shows that maternal
knowledge is actually important but how far depends on accessibility to the food market. To takeaccount of this point in our study, we include educational intervention in the sale experiment andanalyze how nutritional education to mothers affects the impact of product sales on child nutrition.
This paper consists of the following structure. First, we explain the detail of Koko-plus (Section2). Then we describe the experimental design and data structure (Section 3). Section 4 presents
the identification strategy and the results are provided in Section 5. Finally, we conclude in
Section 6.
2

2 Backgrounds of Koko-plus
In 2015 a Japanese food company started to sell a new complementary food product for babies
called “Koko-plus” in Ghana. The notable feature of this product is that this is a nutritionallyenhanced food product made from soybeans but used as a sweet taste supplement to other foods,
like a seasoning. By putting it, mothers can make any foods for babies rich in required nutrientsfor a child less than 24 months of age. Sales of complementary food products are common
landscape in Ghana nowadays even in rural areas. However, most of those products are “dishtype”, that is, mothers feed their children with those products as a food. Or others are medical
supplements, e.g. vitamin A, iron, and iodine, which are sold in pharmacies. Therefore, Kokoplus was the first supplementary food product commercialized in Ghana. With respect to theingredient composition and nutrient content as well as the effect on child nutrition, refer to Ghoshet al. (2019). They show that Koko-plus will significantly improve child nutrition if sufficientamount is given to children based on randomized free distribution trial in Ghana.
The company began the sales of Koko-plus in and around Accra, the capital of Ghana in 2015.
Then, in September 2016 they set a branch in Kumasi, the second largest city following Accra
and the capital of Ashanti region, and started their business in Kumasi. Thus, as of January 2016
when we started our project in rural area in Ashanti region, this product was mainly sold in Accra
and its surrounding area in Eastern region. During 2016 when we conducted our study, theirbusiness around Kumasi was very limited.
The market price of Koko-plus was 0.5 GHS.3 This price seems sufficiently low, at least not
so much expensive. For example, since one of the most popular dish type complementary foods
was priced at around 1.2 GHS, the price of Koko-plus is lower than a half of this price. On othercalculation, it is only 5% of the average household cash food expenditure per day in Ghana.4

3 Research Design and Data
3.1 Study Sites and Sampling Frame
We selected two districts in Ashanti region, Ahafo Ano South and Asante Akim South, as ourstudy sites. The two districts are located on opposite sides of and 30 – 50 km away from Kumasi.
3GHS stands for Ghanaian Cedi, the currency in Ghana. 1 GHS = 0.253 USD in January 2016
4The average household cash expenditure on food and non-alcoholic beverages is 3,673 GHS per year (GSS,2014), or 10.06 GHS per day. Thus, 0.5 GHS is about 4.97% of 10.06 GHS.

3

Both districts have a part of major highways, Kumasi-Sunyani Road and Accra-Kumasi Road
respectively. There had been no Koko-plus sale until our research project started and during ourstudy period our experiment was the only chance to buy Koko-plus. We selected 6 study locations
in each district from communities that had a public health facility. Thus, we had 12 study locations
in total. We can assume that accessibility to medical care was almost similar among the 12 study
locations.
We conducted a census survey to make the list of baby-rearing mothers for sampling in eachlocation from January to February 2016. Then, from the list we randomly selected mothers who
has only one child less than 1 year old at the time of baseline survey and conducted a baseline
survey of the households where the sample mothers belonged from March to May 2016. Note that
we dropped mothers whose children were twins or more and mothers with siblings born within ayear. It means that we ensure one-to-one pair between mother and child aged less than 1 year. We
started the sale experiment of Koko-plus in September 2016 and continued for 6 months until
February 2017. Finally, we conducted a follow-up survey from March to May 2017.
The baseline and follow-up surveys consist of two parts: Living Standard Survey (LSS) and
Health and Nutrition Survey (HNS). LLS is a typical household survey. It collects data on
household demography, agricultural production, other income sources, household expenditure,
and asset holdings. HNS is designed to collect anthropometric and health data of targeted children.
The sample size at the baseline is 351 households (i.e. 351 mother-child pairs) but we could follow
up 229 households of them to the end of the study.

3.2 Experimental Design
We conducted the sale experiment of Koko-plus with and without educational component.
There are three treatment arms: sale without education (“Only Sale” for short); sale with education(“With Education” for short); and control. The study locations were stratified and randomly
assigned to one of the three arms: Only Sale (4 locations); With Education (4 locations); andcontrol (4 locations).5

5We have only 12 locations as the units for randomization. Pooling all locations and assigning the treatment status
to the pooled locations may raise biases because of the small number of the clusters. Thus, we used blockrandomization to minimize that concern in advance. We used the following variables collected in the demographic
survey to create the strata: age of the mother, educational attainment of the mother, and household size.

4In all the treatment arms, including the control, we conducted weekly interview during the 24
week study period. In the weekly interview we asked whether the child had any symptoms in thelast seven days, and how and how many packages of Koko-plus the mother used only for treatedgroups. We measured the weight of the child every week and the height of the child three times
during the study period: at the beginning, in the middle, and at the end. The weekly interviews
were conducted by health workers who worked at the health center located in each study location.
The reason why we also conducted weekly interview in control locations is that frequent visitingby the health workers or weekly weight measurement itself may affect parents’ behaviors.6 To
minimize this concern, we conducted the interview and measurement with almost the sameframing in both control and treatment groups.
In both Only Sale and With Education groups, we provided opportunities for mothers to buy
Koko-plus. The sales were also conducted by the same health workers. 7 We started the sale
experiment from the second week of September 2016 and continued for 24 weeks, almost for halfa year. From the viewpoint of feasibility, the sale experiments were conducted at the healthfacilities where the weekly interviews were done. Only when the mothers did not come to thehealth facilities, the salespersons visited their houses and conducted the interview and sale.
We basically sold Koko-plus at the market price, 0.5 GHS. But every week we randomly
selected mothers and offered a discount price: 40% discount (i.e. 0.3 GHS) for three mothers ineach location and 20% discount (i.e. 0.4 GHS) for six mothers in each location. Since the random
selection for discounting was done every week, mothers could not predict when they would beoffered the discount price. We limited the maximum number of packages that a mother can buy
in a week to 7 packages because one package per day was the recommended amount. By thisrestriction, we intended to avoid over-purchasing in a discounted week. Thus, we assume mothers
generally used all the packages within the week when they purchased them.
Mothers in With Education group received educational intervention consisting of lecture and

6It is pointed out that frequent personal contacts of a health promoter have an influence on the adoption of healthtechnologies. See Ritter et al. (2017).
7No one had known about Koko-plus before the intervention in our study sites because there had been no sale andour project introduced this product for the first time. Because of this, we were afraid that mothers might have a doubt
or a concern about the quality and/or the effectiveness of the product and become reluctant to buy it. To minimize thisstranger effect, we asked the health workers to sell the product to mothers. The health workers had been working at
the local health facility before the intervention, and hence they were known to mothers well and were trusted by
them.

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practice session. They were called to educational meetings held three times per month at the healthfacility. In the first and third weeks of each month we had lectures on nutritional knowledge,
where lecturers from Kwame-Nkrumah University of Science and Technology gave information
about nutrition and good feeding practices. In the final week of each month we had practicesessions, where the lecturers demonstrated how to prepare good complementary foods for a baby
by using locally available materials, e.g. egg, fish, and beans. As such, our educational
intervention was not only informative but also practical. Note that the contents were very generaland did not include any advertising messages about Koko-plus.

3.3 Data and Descriptive Statistics
We use data of child weight and height as variables indicating child nutrition. We convert themeasurements into Z-scores, weight for age Z-score (WAZ) and height-for-age Z-score (HAZ),
by following WHO’s definition. We use the difference between initial Z-score value and final Zscore value as the outcome variable so that we evaluate the impact of the treatment in terms ofchild growth. The initial value is obtained from the data collected in the baseline survey and thefinal value is obtained from the follow-up survey.8
Table 1 presents summary statistics on child nutrition and household characteristics. The
following three points are found salient in the table. First, the nutritional status of the sample
children is bad at the baseline: the averages of WAZ and HAZ are -0.768 and -0.828. Second, thenutritional status becomes worse from the baseline to the follow-up: the means of the difference
between the baseline and the follow-up are -0.177 for WAZ and -0.498 for HAZ. Third, thisworsening trend is larger for HAZ than WAZ. This negative trend in child nutrition is not apeculiar case in our study, but common in Ghana as discussed in Introduction.9 The total numberof packages of Koko-plus purchased by a mother in the treatment groups is 21.1 on average during
the 24 weeks of the sale experiment. This means that the mothers on average bought less than one
package per week.10
8Some mothers were not available for the follow-up survey. In such cases, we use the measurements done during
the final weekly interview instead. Since the follow-up survey was done shortly after the final weekly interview, we
believe that the substitution does not cause any bias.
9See also GSS et al. (2015) Chapter 11.
10The purchase is not evenly distributed over the experimental period. Many mothers bought Koko-plus in the earlystage of the experiment, but the number of mothers buying it declined over time. The details of the purchasing pattern
and their analysis are found in Okonogi et al. (2020).

6

Table 2 presents baseline summary statistics for each treatment group and the results of balance
check. Columns 1, 3, and 5 show means and standard deviations for each group: Control, Only
Sale, and With Education. Columns 2, 4, and 6 show the number of observations. Columns 7, 8,
and 9 show the p-values for t-test on difference in the sample means between the groups. Thereis no statistically significant difference in the baseline characteristics even at the 10% level.
Therefore, we can say that our randomization worked well.

4 Identification Strategy
First, we estimate an intention to treatment (ITT) effect of the sale experiment and theeducational intervention. The econometric model is as follows:∆𝑌
where ∆𝑌

=𝛽 𝑇

+𝛽 𝑇

+𝐗

𝛃 +𝛿 +𝜖（1）

is the difference of outcome between the baseline and the follow-up for the child ofhousehold i in study location j of district d. As mentioned in Section 3, we use the weight-for-age
Z-score (WAZ) and the height-for-age Z-score (HAZ) as the outcome of child nutrition. 𝑇
is a dummy variable whose value is 1 if the household i lives in the treated location of the sale
experiment and belongs to either Only Sale group or With Education group, otherwise 0. 𝑇
is a dummy variable whose value is 1 if the household i belongs to With Education groupotherwise 0. Therefore 𝛽 and 𝛽 are the difference-in-difference estimators and they can beinterpreted as the ITT effect of the treatment. 𝐗

is a vector of exogenous household

characteristics at the time of the baseline survey, such as household size, age and education ofhousehold head and mother, gender and age of the child. It is included in the model to control forthe effects of the difference in initial conditions. 𝛿 is an intercept by district. 𝜖

is an errorterm.
The ITT effect of the sale, 𝛽 , can be interpreted as the impact of the emergence of the newcomplementary food product in the market, but it does not mean the impact of the use of the
product itself. For the latter impact, we estimate a local average treatment effect (LATE) of thepurchase of the product by using treatment status as an instrumental variable. The econometricspecification is given as below:

7∆𝑌
where 𝐾𝑜𝑘𝑜𝑝𝑙𝑢𝑠= 𝛾 𝐾𝑜𝑘𝑜𝑝𝑙𝑢𝑠

+𝛾 𝑇

+𝐗

𝛄 +𝛿 +𝜖

is the total number of packages of Koko-plus purchased by household i instudy location j of district d during the experiment period11. We use 𝑇
𝐾𝑜𝑘𝑜𝑝𝑙𝑢𝑠. 𝛾（2）indicates the LATE of Koko-plus purchase. 𝛾

as an instrument foris the ITT effect of theeducational intervention. The difference in the ITT effect of the nutrition education between 𝛽
in equation (1) and 𝛾 in equation (2) is that the latter does not include an indirect effect of 𝑇
through product purchase since it is captured by 𝐾𝑜𝑘𝑜𝑝𝑙𝑢𝑠. As explained above, we gave

information about how to prepare nutritious complementary foods by using locally available foodmaterials to mothers in the nutrition education and it did not include any advertising messages
about Koko-plus. Therefore, the mothers at least theoretically can improve complementary
feeding without using Koko-plus. However, Okonogi et al. (2020) shows this educational
intervention increases the purchase of Koko-plus packages as well. If Koko-plus has an impact
on child nutrition, a part of the impact of educational intervention in equation (1) is from Kokoplus use. Such an indirect effect is separated in equation (2) because 𝑇
model of the first stage. Therefore 𝛾

is also included in thecan be interpreted as the ITT effect of the nutrition

education other than Koko-plus consumption.

5 Results
Table 3 is the estimation results of equation (1) showing the ITT effect of the intervention.
Columns 1 and 2 show the results when we use the difference of WAZ as the dependent variable
and columns 3 and 4 show the results with the difference of HAZ as the dependent variable. The
results in columns 2 and 4 include the exogenous household characteristics at the baseline, 𝐗,

to control for the initial condition. The coefficient for the sale experiment in column 2 is positiveand statistically significant at 10% level when we control for the observable household
heterogeneity, although it is not significant without controlling for the initial condition as shownin column 1. This suggests that the introduction of the new complementary food product into the
11We use the number of packages “purchased” rather than “consumed”. We admit that “consumed” is ideal, but it isvery hard to obtain reliable data as to “actual” amount consumed through interviews. Moreover, we cannot observe
whether the mothers resell Koko-plus or not. In such a situation, it is most likely that the number of packages actuallyconsumed is equal or less than the number of packages purchased. Therefore, if Koko-plus consumption has apositive impact on child nutrition, the estimated 𝛾 is biased to downward and can be interpreted as the lower boundof the impact of Koko-plus consumption.

8

market increases child’s weight. In contrast to the significant effect on child’s weight, there is no
significant effect of the sale experiment on child’s height regardless of including the household
characteristic variables as shown in columns 3 and 4. As for the nutrition education, neither child’s
weight nor height is influenced by it significantly as shown in Table 3. This non-significant resultof the nutrition education is consistent with Bhandari et al. (2004), who show nutrition education
through trained health workers improves parental feeding practices but there is no significant
impact on physical growth of children. Following their findings, our nutrition education may alsochange mothers’ feeding practices. Unfortunately, however, we did not collect data about feedingpractices.
The results of the first stage estimation for equation (2) are given in Table 3. Because sample
size is not the same for WAZ and HAZ due to missing height measurements, we show theestimation result for each case. The two results are very similar and the treatment variable, 𝑇,

is found to work well as an instrument.
Table 5 shows the local average treatment effect (LATE) of mother’s purchase of Koko-plus
on child growth. Column 1 gives the result for WAZ and column 2 is that for HAZ. The coefficientfor total number of packages of Koko-plus purchased is positive and statistically significant at the
5% level in the case of WAZ, but it is not significant in the case of HAZ. This result suggests that
Koko-plus consumption increases child’s weight but may not affect child’s height.
The estimated impact of Koko-plus on WAZ is 0.012 per package purchased, which means thatthe average change in WAZ will be 0.252 per 21 packages per 24 weeks since average number
purchased within the treatment groups is 21 packages as shown in Table 1. This much effect seems
to be low as it is only one quarter of standard deviation. However, considering that no change in
WAZ or HAZ indicates that the growth of weight or height is following the trend of global
standard, the positive effect on WAZ, even if it is small, is a sign of improving. But we do notmean that the improvement is large enough. Although we do not have any criteria to determine
how much improvement is sufficient in general, we think that if WAZ becomes close to 0 or the
global mean, it will be good enough. To achieve that much gain in WAZ, a simple conjecturesuggests that a child should be given at least 3 packages of Koko-plus per week: the change in
WAZ must be three times larger than the current estimate, i.e. 0.252 x 3 = 0.756, because average
WAZ at the baseline is -0,768.
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6 Conclusions
In this study, we evaluate the impact of the introduction of a new nutritionally enhanced
complementary food product, Koko-plus, into the market on child growth in Ghana. There is
growing literature examining the role of the market for the improvement of child nutrition.
However, since most of the existing studies rely on observational data, randomized controlled
experiment is required to identify the causal impacts. Our study precisely does it to fill theknowledge gap. Our randomized controlled experiment is a weekly sale experiment of Koko-plus
that lasts for 24 weeks. By using the treatment status as an instrumental variable, we estimate thelocal average treatment effects of mother’s purchase of Koko-plus on child nutrition, and find it
increases child’s weight significantly but not child’s height. We conduct educational intervention
to mothers at the same time. But we do not observe any significant effect of the nutrition education
on child’s physical growth.
Our result provides the evidence that the market does work for the improvement of childnutrition in a rigorous way for the first time. However, the average effect on WAZ we estimate is
not so large and there is a room to increase the effect size. We consider that this small impact isdue to the insufficient amount of purchase of Koko-plus: less than 1 package per week. Therefore,
further work is required to investigate how to encourage mothers to buy the product more undervarious constraints. One of the most typical constraints is budget. But our other work, Okonogi etal. (2020), suggests that the budget is not restricting so much in our case. Or a subsidy policy may
induce purchasing behavior in the long run (Dupas, 2014). Nutrition education to mothers is also
considered as one of the promising policies to induce mothers’ purchase. In fact, Okonogi et al.
(2020) show that the nutrition education increases the number of Koko-plus packages that mothers
buy on average. Similar results are shown by Bhandari et al. (2004). In the present study, however,there is no evidence of direct impact of the educational intervention on child’s physical growth.
We have some limitations in the analysis. First, we use purchased amount rather than consumed
amount. The amount purchased by mothers cannot always be the same as the amount consumed
by children. But since we can reasonably assume that actual amount consumed must be less than
the amount purchased, we consider that our positive and statistically significant estimation
indicates at least the lower bound of the impact of Koko-plus consumption. Second, the attrition
is relatively large. It was difficult to stop dropping out from our experiment because having
10

interviews with anthropometric measurements every week and/or attending educational sessions
are tedious for some mothers. We include exogenous household characteristics in the model tocontrol for it, but sample selection bias may still remain.

11

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14

Table 1. Summary statistics of whole sample
Mean

Std. Dev.

N

WAZ at the baseline-0.768

1.275

271

WAZ at the follow-up-0.945

1.114

271

Difference in WAZ-0.177

1.125

271

HAZ at the baseline-0.828

1.413

245

HAZ at the follow-up-1.326

1.277

245

Difference in HAZ-0.498

1.387

245

21.1

22.4

197

Child age in month at the baseline

7.9

3.2

288

Gender of the child (Girl = 1)

0.545

0.499

288

Age of mother at the baseline

28.1

7.0

288

Number of years in school of mother

6.8

3.5

288

Age of household head at the baseline

42.8

14.7

288

Number of years in school of household head

7.2

4.4

288

Household size at the baseline

6.4

3.2

288

Child nutrition

Household and child characteristics
Total number of Koko-plus packages purchased
during the experiment†

Notes : WAZ means weight-for-age Z-socre. HAZ means heght-for-age Z-score.
†In the control group, the total purchased amount of Koko-plus is 0 for all households. Therefore
we only show the value among the treatment groups (Only Sale and With Education ).

15

Table 2. Baseline summary statistics by treatment groups and balance check
Treatment groups

WAZ at the baseline
HAZ at the baseline
Child age in month at the baseline
Gender of the child (Girl = 1)
Age of mother at the baseline
Number of years in school of mother
Age of household head at the baseline
Number of years in school of household head
Household size at the baseline

Control (C)Mean
N(Std. Dev.)(1)(2)-0.72684(1.343)-0.78575(1.309)
7.6
91
(3.3)
0.549
91
(0.500)
27.8
91
(7.6)
6.7
91
(3.5)
42.3
91
(15.5)
7.5
91
(4.4)
6.5
91
(3.3)

Only Sale (T1)
Mean
N
(Std. Dev.)(3)(4)-0.70591(1.348)-0.69480(1.586)
7.6
96
(3.1)
0.573
96
(0.497)
28.6
96
(6.7)
6.9
96
(3.5)
43.2
96
(14.3)
6.8
96
(4.3)
6.5
96
(3.4)

16

With Education (T2)
Mean
N
(Std. Dev.)(5)(6)-0.86696(1.144)-0.98290(1.331)
8.3
101
(3.2)
0.515
101
(0.502)
28.0
101
(6.7)
6.8
101
(3.7)
42.8
101
(14.3)
7.4
101
(4.4)
6.3
101
(2.8)

p -Value
H0: C = T1
(7)
0.918

p -Valuep -Value
H0: C = T2 H0: T1 = T2
(8)
(9)
0.456
0.381

0.697

0.339

0.204

0.998

0.129

0.107

0.748

0.634

0.416

0.428

0.856

0.501

0.691

0.848

0.838

0.687

0.801

0.870

0.293

0.838

0.383

0.921

0.664

0.586

Table 3. The ITT effect of the sale and nutrition education on child growth
ΔWAZ

Dependent variable
(1)
sale

ΔHAZ

(2)
*

(3)

(4)

0.008

0.018

0.210

0.205

(0.143)(0.108)(0.237)(0.227)-0.118-0.199

0.307

0.241

(0.139)(0.138)(0.300)(0.286)

Household characteristics: Xijd

No

Yes

No

Yes

Observations

271

271

245

245

0.006
0.142
0.014
R
Notes : Standard errors clustered at the study location level in parentheses.

0.073

Sale experiment: T

Nutrition education: T

edu

2

***

**

*

P < 0.01, P < 0.05, P < 0.1. WAZ means weight-for-age Z-socre. HAZ means
heght-for-age Z-score.

17

Table 4. First stage regression results for the LATE estimation model
Dependent Variable:
Number of Koko-plus packages purchased
Sale experiment: T

sale

Nutrition education: T

edu

First Stagefor WAZ
(1)
***
16.53
(3.239)8.636(9.084)First Stagefor HAZ
(2)
***
16.67
(3.040)8.698(9.378)Household characteristics: Xijd
Age of child-0.354-0.370(0.348)(0.367)
Gender of the child (Girl = 1)
-0.724-1.198(2.069)(2.572)Age of mother
0.164
0.168
(0.107)(0.126)
Number of years in school of mother
0.038-0.121(0.500)(0.498)Age of head
0.047
0.061
(0.076)(0.056)
Number of years in school of household head
0.311
0.528 *
(0.246)(0.301)
Household size
0.011
0.198
(0.425)(0.521)
2
0.224
0.231
R
F
52.74
95.48
***
***
p -Value
0.000
0.000
Observations
271
245
Notes : Standard errors clustered at the study location level in parentheses.
***

**

*

P < 0.01, P < 0.05, P < 0.1. WAZ means weight-for-age Z-socre.
HAZ means heght-for-age Z-score.

18

Table 5. The LATE of Koko-plus purchase on child growth
Dependent variable

ΔWAZ
(1)
**
Number of Koko-plus packages purchased: Kokoplus ijd
0.012(0.006)edu-0.306
Nutrition education: T(0.220)Household characteristics: Xijd
Yes
F
52.74
p -Value
0.000 ***
Observations
271
Notes : Standard errors clustered at the study location level in parentheses.
***

**

*

ΔHAZ
(2)
0.001
(0.013)0.231(0.318)Yes
95.48
0.000 ***
245

P < 0.01, P < 0.05, P < 0.1. WAZ means weight-for-age Z-socre. HAZ means
heght-for-age Z-score.

19