00074918.2015.1104410
Bulletin of Indonesian Economic Studies
ISSN: 0007-4918 (Print) 1472-7234 (Online) Journal homepage: http://www.tandfonline.com/loi/cbie20
Urban Shopping Patterns in Indonesia and Their
Implications for Small Farmers
Nicholas Minot, Randy Stringer, Wendy J. Umberger & Wahida Maghraby
To cite this article: Nicholas Minot, Randy Stringer, Wendy J. Umberger & Wahida Maghraby
(2015) Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers, Bulletin
of Indonesian Economic Studies, 51:3, 375-388, DOI: 10.1080/00074918.2015.1104410
To link to this article: http://dx.doi.org/10.1080/00074918.2015.1104410
Published online: 29 Nov 2015.
Submit your article to this journal
Article views: 60
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=cbie20
Download by: [Universitas Maritim Raja Ali Haji]
Date: 17 January 2016, At: 23:17
Bulletin of Indonesian Economic Studies, Vol. 51, No. 3, 2015: 375–88
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
URBAN SHOPPING PATTERNS IN INDONESIA AND
THEIR IMPLICATIONS FOR SMALL FARMERS
Nicholas Minot*
International Food Policy Research Institute
Randy Stringer*
University of Adelaide
Wendy J. Umberger*
University of Adelaide
Wahida Maghraby*
University of Adelaide
In developing countries, the expansion of supermarkets and other modern food
retailers has raised concerns about the potential impact on traditional retailers and
fruit and vegetable farmers. Will small farmers, in particular, be squeezed out of
this growing, remunerative market by the quality standards imposed by supermarkets? In an attempt to answer this question, we analyse data from a stratiied
random sample of 1,180 urban households in Indonesia. We ind that only a small
share of fruits and vegetables are purchased from modern outlets, even among
high-income urban households. On the basis of the relation between income and
shopping patterns in our data, we project that even after 15 years of income growth,
supermarkets will account for less than 40% of urban food spending. The impact of
supermarket standards on small farmers may be less dramatic than has been feared.
Keywords: food demand, supermarkets, traditional markets, small farmers
JEL classiication: D12, F63, O13, Q13
INTRODUCTION
In recent decades, in most developing countries, the food-retail sector has transformed. Modern food outlets such as hypermarkets, supermarkets, and convenience stores (mini-marts) have proliferated, while rising incomes have increased
consumer demand for better food quality and safety, greater product diversity,
and an improved shopping experience. In addition, urbanisation has helped make
these advancements accessible to much of the population (Reardon et al. 2003).
Indonesia is no exception to these trends. Real per capita income in Indonesia
has grown at 4.5% annually over the past 10 years, one of the highest rates in
the region (World Bank 2015). The number of modern food-retail outlets in the
country increased from 1 in 1977, to more than 1,000 in 1999, to 11,000 in 2009.
According to Euromonitor surveys, the share of food spending at such outlets
* This article was made possible by inancial support from the Australian Centre for International Agricultural Research. All views, interpretations, and conclusions expressed are
those of the authors and not necessarily those of the supporting or cooperating institutions.
ISSN 0007-4918 print/ISSN 1472-7234 online/15/000375-14
http://dx.doi.org/10.1080/00074918.2015.1104410
© 2015 Indonesia Project ANU
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
376
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
increased from 5% in 1999 to 11% in 2009 (Dyck, Woolverton, and Rangkuti 2012).
Another report cited industry sources in estimating that the share of Indonesia’s
modern food-retail sector was 30% in 2007 (World Bank 2007).
The rapid rise of this sector has generated a number of concerns, including
whether the sector’s growth is displacing traditional retailers, causing hardship
among traders and shop owners, and whether the expansion of modern foodretail outlets is squeezing small farmers out of the supply chain. Supermarkets
often establish structured supply chains with quality and quantity requirements
that small farmers have dificulty meeting (Chowdhury, Gulati, and GumbiraSa’id 2005; World Bank 2007).
In the case of horticulture, there are also concerns about import competition.
The share of imports in the volume of domestic supply is small but growing, having risen, for vegetable imports, from 5.1% in 2005 to 7.1% in 2012. Over the same
period, the import share of fruits rose from 3.6% to 5.0% (FAO 2015). In 2012, the
government of Indonesia began to impose restrictions on the imports of horticulture and meat products, leading to disputes being iled by the United States and
New Zealand at the WTO (WTO press release, 8 May 2014). The issue of import
competition is linked to the transformation of the retail sector because large, modern retailers often facilitate the distribution of imported goods.
In this article, we examine shopping patterns in urban Indonesia, focusing on
the household-level determinants of the use of modern food-retail outlets. We
generate projections of the share of urban food expenditure allocated to such outlets over time, and we discuss the implications of the patterns and pace of growth
in the sector for traditional retailers and small farmers. We are interested, in particular, in testing the view that the growth of modern retail outlets, with their
quality and quantity standards, threatens the livelihoods of small farmers by limiting their access to this remunerative, growing market.
DATA AND METHODS
Data
From November 2010 to February 2011, we coordinated a survey of 1,180 urban
households in three cities in Indonesia: Surabaya, Bogor, and Surakarta (Solo),
chosen to represent large, medium, and small cities, respectively. In each city,
we used stratiied random sampling to select households, while oversampling
higher-income neighbourhoods and areas close to supermarkets. The sample
design varied by city because of different amounts of information in each. We
calculated sampling weights on the basis of the inverse of the probability of selection, and used these weights in calculating the results presented here.
Cities in Indonesia are divided, from largest to smallest, into kecamatan (subdistricts), kelurahan (neighbourhoods), and the neighbourhood administrative
units rukun warga (RW) and rukun tetangga (RT). In Surabaya, we selected 20
neighbourhoods at random and stratiied to oversample those within one kilometre of a supermarket. In each of these neighbourhoods, we selected two RTs at
random but oversampled high-income RTs. We then chose 15 households from
lists of resident households in each of these RTs, making a total of 600 households
in Surabaya. In Bogor, we selected 20 neighbourhoods at random, stratifying to
oversample those with a supermarket. In each, we chose two RTs at random but
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
377
again oversampled high-income RTs. We then chose 7 households at random,
for a sample of 280 households in Bogor. In Surakarta, using area sampling, we
selected 15 RWs at random. Of these, we selected 25 RTs at random, oversampling
high-income areas by choosing a larger share of RTs in the two higher-income
RWs. In each of the 25 RTs, we chose a random sample of 12 households, for a
sample of 300 households in Surakarta.
The survey questionnaire covered household composition, housing and asset
ownership, shopping behaviour at different types of outlets, food expenditure
patterns, perceptions of each type of food retailer, and perceptions of organic
food. Following categories used by Dyck, Woolverton, and Rangkuti (2012), we
deine eight types of food retailer:
• Hypermarkets: Very large, modern stores with 10 or more cash registers.
Examples include multinational chains such as Carrefour, Giant, and Makro,
and Indonesian chains such as Hypermart.
• Supermarkets: Large, modern stores with between three and nine cash
registers. Examples include chains such as Hero, Matahari, Asia, and Yogya,
although independent supermarkets exist as well.
• Mini-marts, or convenience stores: Small, modern stores with one or two
cash registers. Alfamart and Indomart are two large chains of mini-marts in
Indonesia.
• Warung, or small shops: Family-owned stores in any building, often in
residential areas. They typically sell snacks, beverages, and dry goods.
• Semi-permanent stands: Vendors who sell from a table, stand, cart, or stall that
can be moved but often stays in one place during the day. They often sell fresh
fruits and vegetables.
• Traditional wet markets: Places where a large number of vendors can set up
shop at tables or in stalls under a common roof. These markets are generally
managed by the city.
• Peddlers: Vendors who move their products around the city on foot, by bicycle,
or in a motorised cart. They often bring perishable goods into residential
neighbourhoods or busy public areas.
• Other: Any source of food not listed above, most notably restaurants.
The irst three types are considered modern food retailers, while the last ive are
considered traditional retailers.
Methods
In this article, we examine the determinants of the share of urban food expenditure
allocated to modern food outlets, as deined above. About 23% of the households
in our sample did not report any spending at such outlets, so the dependent variable has a large number of zero values. An ordinary least-squares model would
predict negative expenditure shares for low-income households, but, since shares
cannot be negative, the error term will be positive for low-income households.
The correlation between the error term and an independent variable implies that
the income coeficient estimated using this model would be biased.
One alternative is to use Tobin’s (1958) probit, or Tobit, model, which assumes
that the independent variables estimate a latent variable. The observed variable
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
378
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
is truncated at zero whenever the latent variable is negative. One limitation of the
Tobit model is that the same process is used to estimate both the probability that
the dependent variable is positive and the conditional value of the dependent
variable.
The Cragg (1971) double-hurdle model is based on the idea that there are two
distinct decisions, each with its own determinants. The irst ‘hurdle’ is the decision on whether to participate or, in this case, whether to shop at a modern outlet.
The second ‘hurdle’ is the decision on how much to purchase, or, in this case, how
much of the food budget to allocate to modern outlets. We estimate these decisions simultaneously, using maximum likelihood methods, though the irst decision is equivalent to a probit model of the decision to participate. Unlike the Tobit
model, the Cragg model allows the parameter estimates explaining participation
and quantity to differ. The explanatory variables include per capita expenditure,
household characteristics, travel time to the nearest modern food-retail outlet,
and ownership of a refrigerator or motor vehicle. The z-statistic determines the
statistical signiicance of each coeficient.
We also project urban food spending at modern retail outlets from 2010 (when
the survey was carried out) to 2025. We base our projections on a simpliied version of the Cragg model—that is, we limit the explanatory variables to per capita
expenditure and per capita expenditure squared—as well as projections of income
growth and urban population growth, and our estimates of the relation between
income and food share. It is preferable not to control for asset ownership, education, and the other explanatory variables, since these will change over time. The
implicit assumption is that each of these variables has the same relationship with
income over time as it does across income groups in the survey. Our projections
assume that per capita income grows by 4.5% per year, the average growth rate
over the most recent decade (2003–14) for which data are available (World Bank
2015). They also assume that the urban population will grow by 2.1% per year, on
the basis of UN DESA (2011) projections for 2010–25. We determine projections
of the food share by using projected income growth and the estimated relation
between income and food share in the survey data. We also test the sensitivity of
the projections to changes in selected assumptions.
RESULTS
Urban Shopping Patterns
The survey collected information on household expenditure on 67 types of food
products, and the retailer where the household buys most of each type. Here,
we calculate the share of aggregate food spending at each type of retailer, not
the mean share across households, so these igures give greater weight to higherincome households that spend more on food. In spite of the rapid expansion of
supermarkets in Indonesia, warung continue to be the most important source of
food, accounting for 31% of urban food expenditure. Traditional wet markets are
second, responsible for 24% of urban food spending. Urban consumers spend
about 19% of their food budget at modern food outlets, roughly split among
hypermarkets, supermarkets, and mini-marts. This is considerably lower than the
World Bank’s (2007) estimate of 30% overall, which is based on industry sources
and includes urban and rural areas, but roughly in line with more recent estimates
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
379
FIGURE 1 Share of Spending at Each Type of Retail Outlet on Each Type of Food (%)
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Hypermarkets
Supermarkets
Mini-marts
Warung
Semi-permanent stands
Traditional wet markets
Peddlers
Other
Grains
Roots &
tubers
Pulses
Dairy
Meat &
fish
Other
60 0
60 0
Consumed
outside home
Total
Hypermarkets
Supermarkets
Mini-marts
Warung
Semi-permanent stands
Traditional wet markets
Peddlers
Other
0
60 0
Vegetables
Fruit
60 0
60
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
by the US Department of Agriculture (Dyck, Woolverton, and Rangkuti 2012).
Peddlers are surprisingly important, accounting for 11% of urban food expenditure, which is almost as much as hypermarkets and supermarkets combined.
Figure 1 demonstrates how sharply this pattern varies for different types of
food products. For roots and tubers, pulses, and vegetables, the three modern
outlets account for less than 5% of urban expenditure. Again, this is lower than
previous estimates of 10%–15%, which were based on industry sources (World
Bank 2007). Yet for dairy products, ‘other food’ (which includes many processed
foods), and fruit, modern outlets account for more than 30% of urban expenditure. Traditional wet markets attract about 50% of urban spending on vegetables,
meat and ish, and roots and tubers, while warung handle about 50% of the urban
demand for grains (mainly rice) and meals consumed outside the home. Semipermanent stands are relatively important sources of fruit and of meals consumed
outside the home.
Looking at the disaggregated food products gives an idea of the types of products purchased at each type of outlet. Modern retail outlets account for more than
half the spending on infant formula, spreads, butter and margarine, apples, alcoholic beverages, breakfast cereal, processed meat, and other processed food. They
account for less than 5% of the spending on rice, potatoes, poultry, ish, onions,
tofu, tomatoes, garlic, chillies, shallots, leafy vegetables, and green beans. In general, households tend to buy processed foods at modern retail outlets, and meat,
ish, and vegetables at traditional outlets.
Apples are the only fresh produce to be purchased mostly at modern retailers
(67%). Slightly less than half the oranges and other citrus fruit are purchased from
380
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
FIGURE 2 Share of Spending at Each Type of Retail Outlet by the Decile of per Capita
Expenditure of the Household (%)
100
Other
90
Peddlers
80
70
Traditional wet markets
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
60
50
Warung
40
SPS
30
20
Mini-marts
Supermarkets
Hypermarkets
10
0
1
2
3
4
5
6
7
8
9
10
Decile of per capita expenditure
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Note: The shaded area denotes modern food retailers. SPS = semi-permanent stands.
modern retailers. For most tropical fruit, such as mangoes, papayas, bananas,
mangosteens, and pineapples, modern retailers account for less than 10% of urban
demand. These patterns may be related to the import share: almost all apples
in Indonesia are imported, about 14% of oranges are imported, but virtually all
tropical fruits in Indonesia are locally produced (FAO 2015).
The share of food spending at modern retail outlets is also strongly related to
household income. The survey included modules to collect information on food
and non-food expenditure, as well as rent, which were used to calculate per capita
expenditure (a proxy for income). Figure 2 shows that the share of food spending
at modern retailers rises consistently across the per-capita-expenditure deciles.
The households in the poorest decile, for example, spend just 4% of their food
budget at modern food outlets, but this rises to 8% in the ifth decile and 33% in
the richest decile.
From the poorest decile to the richest, the market share of warung falls from
58% to 21%, while that of traditional wet markets falls from 26% to 15% (though it
exceeds 30% in three of the intermediate deciles). In contrast, the market share of
two ‘traditional’ retailers—peddlers and semi-permanent stands—rises gradually
across the deciles. Although peddlers are considered a traditional retail outlet,
they provide a time-saving service and presumably sell at a somewhat higher
price than other outlets. This makes peddlers appealing to households with a high
opportunity cost of time. It is less clear why semi-permanent stands become more
important in higher-income categories; it may be related to the demand for meals
consumed outside the home, which account for about one-third of the spending
at semi-permanent stands.
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
381
TABLE 1 Descriptive Statistics of Dependent and Independent Variables
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Variable
Shops at modern outlet
Share of food bought at modern outlet
Log of per capita expenditure
(Log of per capita expenditure)2
Household size
Age of household head
Education of household head (years)
Female-headed household
Wife works outside home
Weekly hours worked by wife outside home
Owns refrigerator
Owns motorbike, car, or truck
Travel time to nearest modern outlet (mins)
Lives in Surabaya
Lives in Bogor
Weighted
mean
Unweighted
mean
Standard
deviation
0.71
0.13
15.89
252.88
4.49
48.57
9.94
0.12
0.10
2.02
0.63
0.72
7.94
0.60
0.22
0.77
0.16
16.12
260.60
4.41
49.80
11.05
0.14
0.07
1.38
0.72
0.77
7.65
0.51
0.24
0.42
0.17
0.80
26.09
1.76
13.24
4.55
0.34
0.26
5.44
0.45
0.42
4.94
0.50
0.43
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Determinants of Food Spending at Modern Outlets
The explanatory variables in our Cragg double-hurdle model are the log of per
capita expenditure, the square of the log of per capita expenditure, household
size, the age of the household head, a dummy for a female-headed household, a
dummy for a working wife, the interaction of a working wife and the number of
hours she works per week, a dummy for refrigerator ownership, a dummy for
vehicle ownership, travel time to a modern outlet, a dummy for households living in Surabaya, and a dummy for households living in Bogor. Table 1 shows the
weighted and unweighted means of the dependent and independent variables
in the model. The weighted means take into account the sampling weights, so
they describe the urban populations of the three cities. The unweighted means
describe the sample itself, which over-represents households in high-income
neighbourhoods near supermarkets.
The average share of food purchased at modern retailers is 13% (table 1).1
The average household size is about 4.5 members, 12% of households have a
female head, and the average household head has about 10 years of education.
Refrigerators are fairly common, owned by 63% of urban Indonesian households.
Vehicles (most of which are motorbikes) are more common, owned by 72%. About
10% of wives work outside the home, and they work 20 hours a week, on average.
1. This igure differs from the igure in the previous section (19%) because this igure is the
average of household shares, while the earlier igure was the share of overall food expenditure allocated to modern outlets. The latter igure gives more weight to households with
higher food expenditure.
382
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
TABLE 2 Determinants of the Share of Food Spending Allocated to Modern Retailers
Coeficients (z–statistics)
Independent variables
Log of per capita expenditure
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
(Log of per capita expenditure)2
Household size
Age of household head
Education of household head (years)
Female-headed household
Wife works outside home
Weekly hours worked by wife outside home
Owns refrigerator
Owns motorbike, car, or truck
Travel time to nearest modern outlet (mins)
Lives in Surabaya
Lives in Bogor
Constant
Sigma
Observations
(1)
(2)
4.686
(2.27)**
–0.127
(2.00)**
0.185
(4.96)***
–0.002
(0.40)
0.084
(5.75)***
0.118
(0.80)
0.208
(0.37)
–0.004
(0.13)
0.441
(3.87)***
0.320
(2.69)***
0.005
(0.46)
0.179
(1.47)
0.146
(1.03)
1.686
(2.99)***
–0.048
(2.83)***
0.029
(4.85)***
–0.003
(3.21)***
0.016
(5.09)***
0.014
(0.41)
0.136
(1.28)
–0.007
(1.46)
0.121
(2.77)***
0.032
(0.74)
–0.002
(0.71)
0.063
(2.45)**
0.076
(2.50)**
–43.744
(2.62)***
0.200
(20.72)***
–15.107
(3.20)***
1,117
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Note: (1) Dependent variable = share of households that shop at a modern outlet. (2) Dependent variable = share of the food budget spent at a modern outlet among those that shop at modern outlets.
* p < 0.1; ** p < 0.05; *** p < 0.01.
The travel time to a modern retailer is just 8 minutes, on average, although the
travel time to a supermarket (not shown) is close to 20 minutes.
Table 2 shows the results of the Cragg double-hurdle model. The irst column
shows the model of the probability of shopping at a modern outlet, while the second shows the model of the share of food purchased at a modern outlet among
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
383
those who use modern food retailers. Although table 2 identiies the independent
variables that are signiicant predictors of shopping behaviour, it does not provide useful information on the size of the effect (because the coeficients do not
have intuitive interpretations). We therefore provide the average partial effect,
deined as the impact of a one-unit change in the independent variable on the
unconditional share of food expenditure allocated to modern retail outlets. This
partial effect takes into account the effect of the independent variable on both
the probability that the household shops at modern outlets and the share of the
food budget spent at modern outlets among those households. Because the partial
effect is a non-linear function of the independent variables, we give the average
partial effect across the households in the sample. We calculate the standard error
of the partial effect by using bootstrap methods, with 500 replications, and we use
the variation across replications to estimate the standard error of the partial effect.
The results in table 2 suggest that per capita expenditure has a statistically signiicant and positive effect on both the probability of shopping at a modern outlet
and the share of food purchased there (conditional on shopping at a modern outlet). This is not surprising, given the higher costs and greater amenities provided
by supermarkets and other modern retailers. In both models, the quadratic term
is negative and statistically signiicant; the coeficients suggest that both curves
level off near the upper end of the range of per capita expenditure.
The partial effect of log per capita expenditure, which incorporates the effects
of the linear and quadratic coeficients, is 0.06. This means that a 1% increase in
per capita expenditure is associated with an increase of 0.06 percentage points in
the share of the food budget spent at modern outlets. The share of food spending at modern outlets is therefore rising with income, but only slowly. The small
partial effect relects the fact that, from the poorest decile to the richest, per capita
expenditure rises 12-fold, while the share of spending at modern outlets rises
from 4% to 28%.
The coeficients on household size in the two models are positive and statistically signiicant. This implies that, after controlling for other household characteristics, larger households are more likely both to shop at a modern outlet and
to spend a larger share of their food budget there. Since supermarkets tend to be
farther than traditional retailers from the average household, the higher ixed cost
of getting to a supermarket may be easier to justify if the household is planning to
buy a large quantity of food.
The shopping patterns of female-headed households and households in which
the wife works outside the home do not seem to differ from those of other households, after taking into account income, education, and other variables. Nor is
the age of the household head a statistically signiicant factor in the decision to
shop at a modern outlet, although it does have a signiicant effect on the share of
food purchased at a modern outlet among those shopping there. The coeficient
is negative, indicating that younger shoppers spend a larger share of their food
budget at modern outlets than older shoppers. The education of the household
head, however, is positively and signiicantly related to both the probability of
shopping at a modern outlet and the share of the food budget spent there, even
after holding income and other variables constant. This outcome could relect a
greater awareness of food quality and safety, or perhaps different social norms,
among more educated consumers.
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
384
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
Owning a refrigerator is another positive and signiicant predictor of both the
likelihood of shopping at a modern retailer and the share of food purchased there.
This is not surprising, given that having a refrigerator allows the household to
make larger and less frequent shopping trips, which reduces the relative cost of
shopping at more distant supermarkets. Owning a vehicle (such as a motorbike,
car, or truck), on the other hand, is positively associated with the probability of
using modern food retailers—having a vehicle presumably makes it easier to
travel longer distances to a supermarket or hypermarket, for example—but not
with greater spending at these retailers.
Somewhat surprisingly, travel time to the nearest modern outlet is not a statistically signiicant predictor of either the probability of using a modern outlet or the
share of the food budget spent at modern outlets. Similar results were obtained
with travel time to speciic types of modern outlets such as a supermarket or a
hypermarket. Travel time may not be a good measure of accessibility: a supermarket may be close to, or on the way to, a common destination, such as a workplace
or school, making it easily accessible even if it is far from the home.
Households in Surabaya or Bogor are no more likely to shop at a modern outlet than those in Surakarta, but if they do shop at a modern outlet they are more
likely to spend a larger share of their food budgets there. This may relect the
size of the city (Surakarta is the smallest of the three) or the fact that municipal
authorities in Surakarta have sought to improve standards at traditional wet markets. After controlling for other factors, we ind that households in Surabaya and
Bogor allocate three percentage points more of their food budget to modern retailers than those in Surakarta.
Projections of the Share of Urban Food Expenditure at Modern Retailers
To project the growth of the urban modern food sector in Indonesia, we re-estimate the Cragg model in table 2 and limit the explanatory variables to per capita
expenditure and per capita expenditure squared. We then estimate the share of
food purchased at modern retail outlets on the basis of 4.5% annual growth in
income (expenditure) for each household. Table 3 shows that the share of urban
food purchased at modern retailers rises from 18% in 2010 to 24% in 2025. Given
the projections of urban population growth and the decline in the food share in
household budgets, this implies that aggregate urban food expenditure at modern retailers rises from Rp 81 trillion in 2010 to Rp 234 trillion in 2025, implying
an annual growth rate of 7.3%. Over this period, food expenditure at traditional
retailers grows more slowly, at 4.8% annually, but aggregate spending at traditional food retailers more than doubles.
Given the uncertainty about the assumptions behind these projections, we
examine the sensitivity of the results to different assumptions (table 3). We irst
assume annual growth in per capita income to be 9.0%, rather than 4.5%. This is
an extreme assumption, given that Indonesia has achieved this rate of growth
only three times in the past 50 years, but it serves as an upper bound on the speed
of transformation of the modern retail sector. If per capita income were to grow at
9.0% annually between 2010 and 2025, the modern food share would rise to 28%
in 2025, compared with 24% in the base scenario. Yet the overall demand for food
would also grow faster, implying higher growth in food demand at both modern
retailers (11.0%) and traditional retailers (6.9%).
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
385
TABLE 3 Projections of Urban Food Spending at Traditional
and Modern Retail Outlets (Rp trillion)
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Year
2010 (estimated)
2015
2020
2025
Sensitivity analysis
2025 with 9% income growth
2025 with 2 × modern share
elasticity
2025 with 9% income growth &
2 × modern share elasticity
Total
urban food
spending
Urban food
spending at
traditional
outlets
Urban food
spending at
modern
outlets
Share of
urban food
spending
at modern
outlets (%)
457
595
772
991
376
478
604
757
81
118
168
234
18
20
22
24
1,410
1,019
390
28
991
689
302
30
141,094
871
538
38
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Note: The base scenario assumes per capita income growth of 4.5% and urban population growth of
2.1%. The urban food spending at traditional and modern outlets and the urban food share are based
on the relation between income and these variables in the survey data, combined with the projected
income growth. See the text for additional information.
If we doubled the elasticity of the modern retailer share with respect to income,
the modern food share would rise to 30% in 2025. This would dampen the growth
of traditional food retailers, but it would still increase by an average rate of 4.1%
per year. If we combined higher (9.0%) income growth and the greater elasticity
of modern food share with respect to income, the share of the modern food sector
would reach 38% in 2025. Under these assumptions, urban food demand would
grow by 13.5% per year for modern retailers and by 5.8% per year for traditional
retailers.
IMPLICATIONS FOR SMALL FARMERS AND POLICY
Our results have several implications for the future of small farmers in Indonesia and
the traditional market channel. Small-scale vegetable growers are barely affected
by the growth of supermarkets and other modern food retailers; urban consumers still prefer to buy fresh vegetables from traditional wet markets and peddlers,
which account for almost 80% of the vegetable purchases in larger cities. Warung
and semi-permanent stands account for most of the remainder, leaving hypermarkets, supermarkets, and mini-marts with a combined market share of less than 2%.
This small share, combined with the demand for vegetables in smaller urban settlements and rural areas, where the share of modern retailers is even smaller, suggests
that modern retailers play a negligible role in vegetable marketing.
This pattern is conirmed by the results of two farm surveys carried out by the
authors. One survey covered 596 chilli farmers in the main chilli surplus zone in
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
386
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
the highlands of Java. Just 3% of the farmers interviewed reported that their chillies were being sold in a supermarket (Sahara et al. 2015). Another survey covered
662 randomly selected shallot growers in the highly commercial north coast of
Java near Brebes (Wahida 2015). Among these farmers, just 3% reported that their
shallots were being sold in a supermarket.
The impact of supermarkets on farmers is sometimes described as a doubleedged sword: it gives farmers the opportunity to sell into a growing and more
lucrative market, but it also threatens to exclude farmers if they cannot meet the
quality and quantity requirements imposed by supermarkets. Our indings, however, suggest that vegetable farmers in Indonesia are not at risk of being squeezed
out of growing modern channels any time soon. Yet very few of these farmers are
likely to beneit from the opportunity to increase the quality of their produce and
earn a better price by selling into the modern channel.
The story for fruit growers is similar. About 30% of fruit in urban areas is purchased from modern retailers. Yet the two fruits with the highest share purchased
at modern retailers are apples, almost all of which are imported, and citrus fruit,
which are both imported and locally produced. On the other hand, more than 90%
of the urban demand for tropical fruit (including mangoes, papayas, bananas,
mangosteens, and pineapples) is channelled through traditional retailers—wet
markets, semi-permanent stands, and peddlers, in particular. Like vegetable
growers, hardly any local fruit growers have much contact or experience with
supermarkets. This does not mean that the fruit sector is static; there is evidence
of technical change and market transformation, but they are driven by competitive forces within the traditional marketing channel rather than by the growth of
supermarkets and other modern retailers.
The growth of supermarkets may pose a threat to Indonesian fruit growers, not
by taking over domestic supply chains but by developing and expanding international supply chains that bring imported fruit into the country. Supermarkets
facilitate consumer access to high-quality imports of citrus fruit, for example, thus
challenging domestic producers. And although there are virtually no domestic
apple producers, increased access to imported apples may replace some of the
demand for locally grown tropical fruits.
There is also a concern that the growth of supermarkets and other modern retailers in Indonesia could squeeze out traditional retailers, including warung owners,
wet-market vendors, and peddlers. This could create hardships for vendors in the
short- to medium-term, until they ind new employment. To the extent that supermarkets are less capital-intensive than retailers in the traditional market channel,
the growth of supermarkets could gradually decrease the demand for labour.
These concerns, however, are based on the assumption that the modern channel
is large enough and growing fast enough to cause the traditional channel to contract. Our analysis suggests that the traditional channel will continue to expand,
although at a slower rate than the modern channel. More speciically, we expect
urban food expenditure at supermarkets and other modern retailers to expand by
about 7% per year over 2010–25. Over the same period, we project that urban food
expenditure at traditional retailers will grow by slightly less than 5% per year. In
other words, although the traditional food channel is declining in market share, it
will continue to grow at a healthy rate, thanks to rising income and an expanding
urban population.
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
387
CONCLUSIONS
The effect of the growth of supermarkets on traditional retailers and fruit and
vegetable farmers, and particularly on small farmers, has been the topic of some
debate. Modern retailers often impose strict quality standards that may be dificult for small farmers to meet, and often favour larger growers in order to reduce
transaction costs (thus squeezing small farmers out of these growing modern supply chains). At the same time, supermarkets provide an opportunity for small
farmers to raise their incomes by supplying the modern channel, particularly if
they can get inputs, credit, and technical assistance to help them meet the necessary quality standards. Another concern is that the rapid growth of supermarkets
will displace traditional retailers, such as warung owners and wet-market vendors
(Chowdhury, Gulati, and Gumbira-Sa’id 2005).
According to our survey of 1,180 randomly selected urban households in three
large cities of Indonesia, urban consumers spend about 31% of their food budget
at warung, 24% at traditional wet markets, and 19% at modern outlets. This pattern varies greatly across income deciles: poor households spend little at modern outlets (3% in the poorest decile) while high-income households spend much
more (30% in the top deciles).
Our Cragg double-hurdle regression analysis indicates that the share of food
purchased at modern outlets is determined by a combination of income, household size, the age and education of the household head, and whether the household has a refrigerator. Surprisingly, distance and travel time to a modern outlet
do not have statistically signiicant effects on retailer choice.
The share of vegetables purchased at modern retail outlets is very small (less
than 5%), suggesting that current supermarket standards or efforts to organise
supply chains have a negligible effect on vegetable farmers. The share of fruit
bought at modern outlets is somewhat higher (30%), though it is concentrated on
a few imported fruits. The impact of supermarkets on local fruit growers has more
to do with facilitating fruit imports than with forcing quality requirements on
local farmers. In general, local fruit and vegetable growers are not at risk of being
squeezed out of the market by the growth of supermarkets and other modern
retailers, but, at the same time, few of them are likely to beneit from this growth
in the medium term.
Urban food demand at modern retail outlets is growing rapidly, but not rapidly enough to result in an absolute decline in food demand at traditional retail
outlets. On the basis of the results of the survey and our plausible assumptions,
urban food demand will grow by about 7% per year at modern retailers and by
slightly less than 5% per year at traditional retailers. This suggests that the transition from traditional to modern food retailing may be less disruptive than has
been feared.
REFERENCES
Chowdhury, Shyamal K., Ashok Gulati, and E. Gumbira-Sa’id. 2005. ‘The Rise of Supermarkets and Vertical Relationships in the Indonesian Food Value Chain: Causes and
Consequences’. Asian Journal of Agriculture and Development 2 (1–2): 39–48.
Cragg, John. G. 1971. ‘Some Statistical Models for Limited Dependent Variables with
Application to the Demand for Durable Goods’. Econometrica 39 (5): 829–44.
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
388
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
Dyck, John, Andrea E. Woolverton, and Fahwani Yuliati Rangkuti. 2012. Indonesia’s Modern Food Retail Sector: Interaction with Changing Food Consumption and Trade Patterns.
Economic Information Bulletin 97. Washington, DC: Economic Research Service, US
Department of Agriculture.
FAO (Food and Agriculture Organization). 2015. ‘Food Balance Sheet’. http://faostat3.fao.
org/download/FB/FBS/E.
Reardon, Thomas, C. Peter Timmer, Christopher B. Barrett, and Julio Berdegué. 2003. ‘The
Rise of Supermarkets in Africa, Asia, and Latin America’. American Journal of Agricultural Economics 85 (5): 1140–46.
Sahara, Sahara, Nicholas Minot, Randy Stringer, and Wendy Umberger. 2015. ‘Determinants and Effects of Small Chilli Farmers’ Participation in Supermarket Channels in
Indonesia’. Bulletin of Indonesian Economic Studies 51 (3): 445–60.
Tobin, James. 1958. ‘Estimation of Relationships for Limited Dependent Variables’. Econometrica 26 (1): 24–36.
UN DESA (United Nations Department of Economic and Social Affairs). 2011. World
Urbanization Prospects: The 2011 Revision. New York: United Nations.
Wahida. 2015. ‘Food System Transformation in Indonesia: Factors Inluencing Demand
and Supply for Alternative Pest Management Farming Systems’. PhD diss., Global
Food Studies, University of Adelaide.
World Bank. 2007. Horticultural Producers and Supermarket Development in Indonesia. Report
38543-ID. Jakarta: World Bank.
———. 2015. World Development Indicators. Washington, DC: World Bank.
ISSN: 0007-4918 (Print) 1472-7234 (Online) Journal homepage: http://www.tandfonline.com/loi/cbie20
Urban Shopping Patterns in Indonesia and Their
Implications for Small Farmers
Nicholas Minot, Randy Stringer, Wendy J. Umberger & Wahida Maghraby
To cite this article: Nicholas Minot, Randy Stringer, Wendy J. Umberger & Wahida Maghraby
(2015) Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers, Bulletin
of Indonesian Economic Studies, 51:3, 375-388, DOI: 10.1080/00074918.2015.1104410
To link to this article: http://dx.doi.org/10.1080/00074918.2015.1104410
Published online: 29 Nov 2015.
Submit your article to this journal
Article views: 60
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=cbie20
Download by: [Universitas Maritim Raja Ali Haji]
Date: 17 January 2016, At: 23:17
Bulletin of Indonesian Economic Studies, Vol. 51, No. 3, 2015: 375–88
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
URBAN SHOPPING PATTERNS IN INDONESIA AND
THEIR IMPLICATIONS FOR SMALL FARMERS
Nicholas Minot*
International Food Policy Research Institute
Randy Stringer*
University of Adelaide
Wendy J. Umberger*
University of Adelaide
Wahida Maghraby*
University of Adelaide
In developing countries, the expansion of supermarkets and other modern food
retailers has raised concerns about the potential impact on traditional retailers and
fruit and vegetable farmers. Will small farmers, in particular, be squeezed out of
this growing, remunerative market by the quality standards imposed by supermarkets? In an attempt to answer this question, we analyse data from a stratiied
random sample of 1,180 urban households in Indonesia. We ind that only a small
share of fruits and vegetables are purchased from modern outlets, even among
high-income urban households. On the basis of the relation between income and
shopping patterns in our data, we project that even after 15 years of income growth,
supermarkets will account for less than 40% of urban food spending. The impact of
supermarket standards on small farmers may be less dramatic than has been feared.
Keywords: food demand, supermarkets, traditional markets, small farmers
JEL classiication: D12, F63, O13, Q13
INTRODUCTION
In recent decades, in most developing countries, the food-retail sector has transformed. Modern food outlets such as hypermarkets, supermarkets, and convenience stores (mini-marts) have proliferated, while rising incomes have increased
consumer demand for better food quality and safety, greater product diversity,
and an improved shopping experience. In addition, urbanisation has helped make
these advancements accessible to much of the population (Reardon et al. 2003).
Indonesia is no exception to these trends. Real per capita income in Indonesia
has grown at 4.5% annually over the past 10 years, one of the highest rates in
the region (World Bank 2015). The number of modern food-retail outlets in the
country increased from 1 in 1977, to more than 1,000 in 1999, to 11,000 in 2009.
According to Euromonitor surveys, the share of food spending at such outlets
* This article was made possible by inancial support from the Australian Centre for International Agricultural Research. All views, interpretations, and conclusions expressed are
those of the authors and not necessarily those of the supporting or cooperating institutions.
ISSN 0007-4918 print/ISSN 1472-7234 online/15/000375-14
http://dx.doi.org/10.1080/00074918.2015.1104410
© 2015 Indonesia Project ANU
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
376
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
increased from 5% in 1999 to 11% in 2009 (Dyck, Woolverton, and Rangkuti 2012).
Another report cited industry sources in estimating that the share of Indonesia’s
modern food-retail sector was 30% in 2007 (World Bank 2007).
The rapid rise of this sector has generated a number of concerns, including
whether the sector’s growth is displacing traditional retailers, causing hardship
among traders and shop owners, and whether the expansion of modern foodretail outlets is squeezing small farmers out of the supply chain. Supermarkets
often establish structured supply chains with quality and quantity requirements
that small farmers have dificulty meeting (Chowdhury, Gulati, and GumbiraSa’id 2005; World Bank 2007).
In the case of horticulture, there are also concerns about import competition.
The share of imports in the volume of domestic supply is small but growing, having risen, for vegetable imports, from 5.1% in 2005 to 7.1% in 2012. Over the same
period, the import share of fruits rose from 3.6% to 5.0% (FAO 2015). In 2012, the
government of Indonesia began to impose restrictions on the imports of horticulture and meat products, leading to disputes being iled by the United States and
New Zealand at the WTO (WTO press release, 8 May 2014). The issue of import
competition is linked to the transformation of the retail sector because large, modern retailers often facilitate the distribution of imported goods.
In this article, we examine shopping patterns in urban Indonesia, focusing on
the household-level determinants of the use of modern food-retail outlets. We
generate projections of the share of urban food expenditure allocated to such outlets over time, and we discuss the implications of the patterns and pace of growth
in the sector for traditional retailers and small farmers. We are interested, in particular, in testing the view that the growth of modern retail outlets, with their
quality and quantity standards, threatens the livelihoods of small farmers by limiting their access to this remunerative, growing market.
DATA AND METHODS
Data
From November 2010 to February 2011, we coordinated a survey of 1,180 urban
households in three cities in Indonesia: Surabaya, Bogor, and Surakarta (Solo),
chosen to represent large, medium, and small cities, respectively. In each city,
we used stratiied random sampling to select households, while oversampling
higher-income neighbourhoods and areas close to supermarkets. The sample
design varied by city because of different amounts of information in each. We
calculated sampling weights on the basis of the inverse of the probability of selection, and used these weights in calculating the results presented here.
Cities in Indonesia are divided, from largest to smallest, into kecamatan (subdistricts), kelurahan (neighbourhoods), and the neighbourhood administrative
units rukun warga (RW) and rukun tetangga (RT). In Surabaya, we selected 20
neighbourhoods at random and stratiied to oversample those within one kilometre of a supermarket. In each of these neighbourhoods, we selected two RTs at
random but oversampled high-income RTs. We then chose 15 households from
lists of resident households in each of these RTs, making a total of 600 households
in Surabaya. In Bogor, we selected 20 neighbourhoods at random, stratifying to
oversample those with a supermarket. In each, we chose two RTs at random but
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
377
again oversampled high-income RTs. We then chose 7 households at random,
for a sample of 280 households in Bogor. In Surakarta, using area sampling, we
selected 15 RWs at random. Of these, we selected 25 RTs at random, oversampling
high-income areas by choosing a larger share of RTs in the two higher-income
RWs. In each of the 25 RTs, we chose a random sample of 12 households, for a
sample of 300 households in Surakarta.
The survey questionnaire covered household composition, housing and asset
ownership, shopping behaviour at different types of outlets, food expenditure
patterns, perceptions of each type of food retailer, and perceptions of organic
food. Following categories used by Dyck, Woolverton, and Rangkuti (2012), we
deine eight types of food retailer:
• Hypermarkets: Very large, modern stores with 10 or more cash registers.
Examples include multinational chains such as Carrefour, Giant, and Makro,
and Indonesian chains such as Hypermart.
• Supermarkets: Large, modern stores with between three and nine cash
registers. Examples include chains such as Hero, Matahari, Asia, and Yogya,
although independent supermarkets exist as well.
• Mini-marts, or convenience stores: Small, modern stores with one or two
cash registers. Alfamart and Indomart are two large chains of mini-marts in
Indonesia.
• Warung, or small shops: Family-owned stores in any building, often in
residential areas. They typically sell snacks, beverages, and dry goods.
• Semi-permanent stands: Vendors who sell from a table, stand, cart, or stall that
can be moved but often stays in one place during the day. They often sell fresh
fruits and vegetables.
• Traditional wet markets: Places where a large number of vendors can set up
shop at tables or in stalls under a common roof. These markets are generally
managed by the city.
• Peddlers: Vendors who move their products around the city on foot, by bicycle,
or in a motorised cart. They often bring perishable goods into residential
neighbourhoods or busy public areas.
• Other: Any source of food not listed above, most notably restaurants.
The irst three types are considered modern food retailers, while the last ive are
considered traditional retailers.
Methods
In this article, we examine the determinants of the share of urban food expenditure
allocated to modern food outlets, as deined above. About 23% of the households
in our sample did not report any spending at such outlets, so the dependent variable has a large number of zero values. An ordinary least-squares model would
predict negative expenditure shares for low-income households, but, since shares
cannot be negative, the error term will be positive for low-income households.
The correlation between the error term and an independent variable implies that
the income coeficient estimated using this model would be biased.
One alternative is to use Tobin’s (1958) probit, or Tobit, model, which assumes
that the independent variables estimate a latent variable. The observed variable
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
378
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
is truncated at zero whenever the latent variable is negative. One limitation of the
Tobit model is that the same process is used to estimate both the probability that
the dependent variable is positive and the conditional value of the dependent
variable.
The Cragg (1971) double-hurdle model is based on the idea that there are two
distinct decisions, each with its own determinants. The irst ‘hurdle’ is the decision on whether to participate or, in this case, whether to shop at a modern outlet.
The second ‘hurdle’ is the decision on how much to purchase, or, in this case, how
much of the food budget to allocate to modern outlets. We estimate these decisions simultaneously, using maximum likelihood methods, though the irst decision is equivalent to a probit model of the decision to participate. Unlike the Tobit
model, the Cragg model allows the parameter estimates explaining participation
and quantity to differ. The explanatory variables include per capita expenditure,
household characteristics, travel time to the nearest modern food-retail outlet,
and ownership of a refrigerator or motor vehicle. The z-statistic determines the
statistical signiicance of each coeficient.
We also project urban food spending at modern retail outlets from 2010 (when
the survey was carried out) to 2025. We base our projections on a simpliied version of the Cragg model—that is, we limit the explanatory variables to per capita
expenditure and per capita expenditure squared—as well as projections of income
growth and urban population growth, and our estimates of the relation between
income and food share. It is preferable not to control for asset ownership, education, and the other explanatory variables, since these will change over time. The
implicit assumption is that each of these variables has the same relationship with
income over time as it does across income groups in the survey. Our projections
assume that per capita income grows by 4.5% per year, the average growth rate
over the most recent decade (2003–14) for which data are available (World Bank
2015). They also assume that the urban population will grow by 2.1% per year, on
the basis of UN DESA (2011) projections for 2010–25. We determine projections
of the food share by using projected income growth and the estimated relation
between income and food share in the survey data. We also test the sensitivity of
the projections to changes in selected assumptions.
RESULTS
Urban Shopping Patterns
The survey collected information on household expenditure on 67 types of food
products, and the retailer where the household buys most of each type. Here,
we calculate the share of aggregate food spending at each type of retailer, not
the mean share across households, so these igures give greater weight to higherincome households that spend more on food. In spite of the rapid expansion of
supermarkets in Indonesia, warung continue to be the most important source of
food, accounting for 31% of urban food expenditure. Traditional wet markets are
second, responsible for 24% of urban food spending. Urban consumers spend
about 19% of their food budget at modern food outlets, roughly split among
hypermarkets, supermarkets, and mini-marts. This is considerably lower than the
World Bank’s (2007) estimate of 30% overall, which is based on industry sources
and includes urban and rural areas, but roughly in line with more recent estimates
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
379
FIGURE 1 Share of Spending at Each Type of Retail Outlet on Each Type of Food (%)
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Hypermarkets
Supermarkets
Mini-marts
Warung
Semi-permanent stands
Traditional wet markets
Peddlers
Other
Grains
Roots &
tubers
Pulses
Dairy
Meat &
fish
Other
60 0
60 0
Consumed
outside home
Total
Hypermarkets
Supermarkets
Mini-marts
Warung
Semi-permanent stands
Traditional wet markets
Peddlers
Other
0
60 0
Vegetables
Fruit
60 0
60
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
by the US Department of Agriculture (Dyck, Woolverton, and Rangkuti 2012).
Peddlers are surprisingly important, accounting for 11% of urban food expenditure, which is almost as much as hypermarkets and supermarkets combined.
Figure 1 demonstrates how sharply this pattern varies for different types of
food products. For roots and tubers, pulses, and vegetables, the three modern
outlets account for less than 5% of urban expenditure. Again, this is lower than
previous estimates of 10%–15%, which were based on industry sources (World
Bank 2007). Yet for dairy products, ‘other food’ (which includes many processed
foods), and fruit, modern outlets account for more than 30% of urban expenditure. Traditional wet markets attract about 50% of urban spending on vegetables,
meat and ish, and roots and tubers, while warung handle about 50% of the urban
demand for grains (mainly rice) and meals consumed outside the home. Semipermanent stands are relatively important sources of fruit and of meals consumed
outside the home.
Looking at the disaggregated food products gives an idea of the types of products purchased at each type of outlet. Modern retail outlets account for more than
half the spending on infant formula, spreads, butter and margarine, apples, alcoholic beverages, breakfast cereal, processed meat, and other processed food. They
account for less than 5% of the spending on rice, potatoes, poultry, ish, onions,
tofu, tomatoes, garlic, chillies, shallots, leafy vegetables, and green beans. In general, households tend to buy processed foods at modern retail outlets, and meat,
ish, and vegetables at traditional outlets.
Apples are the only fresh produce to be purchased mostly at modern retailers
(67%). Slightly less than half the oranges and other citrus fruit are purchased from
380
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
FIGURE 2 Share of Spending at Each Type of Retail Outlet by the Decile of per Capita
Expenditure of the Household (%)
100
Other
90
Peddlers
80
70
Traditional wet markets
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
60
50
Warung
40
SPS
30
20
Mini-marts
Supermarkets
Hypermarkets
10
0
1
2
3
4
5
6
7
8
9
10
Decile of per capita expenditure
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Note: The shaded area denotes modern food retailers. SPS = semi-permanent stands.
modern retailers. For most tropical fruit, such as mangoes, papayas, bananas,
mangosteens, and pineapples, modern retailers account for less than 10% of urban
demand. These patterns may be related to the import share: almost all apples
in Indonesia are imported, about 14% of oranges are imported, but virtually all
tropical fruits in Indonesia are locally produced (FAO 2015).
The share of food spending at modern retail outlets is also strongly related to
household income. The survey included modules to collect information on food
and non-food expenditure, as well as rent, which were used to calculate per capita
expenditure (a proxy for income). Figure 2 shows that the share of food spending
at modern retailers rises consistently across the per-capita-expenditure deciles.
The households in the poorest decile, for example, spend just 4% of their food
budget at modern food outlets, but this rises to 8% in the ifth decile and 33% in
the richest decile.
From the poorest decile to the richest, the market share of warung falls from
58% to 21%, while that of traditional wet markets falls from 26% to 15% (though it
exceeds 30% in three of the intermediate deciles). In contrast, the market share of
two ‘traditional’ retailers—peddlers and semi-permanent stands—rises gradually
across the deciles. Although peddlers are considered a traditional retail outlet,
they provide a time-saving service and presumably sell at a somewhat higher
price than other outlets. This makes peddlers appealing to households with a high
opportunity cost of time. It is less clear why semi-permanent stands become more
important in higher-income categories; it may be related to the demand for meals
consumed outside the home, which account for about one-third of the spending
at semi-permanent stands.
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
381
TABLE 1 Descriptive Statistics of Dependent and Independent Variables
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Variable
Shops at modern outlet
Share of food bought at modern outlet
Log of per capita expenditure
(Log of per capita expenditure)2
Household size
Age of household head
Education of household head (years)
Female-headed household
Wife works outside home
Weekly hours worked by wife outside home
Owns refrigerator
Owns motorbike, car, or truck
Travel time to nearest modern outlet (mins)
Lives in Surabaya
Lives in Bogor
Weighted
mean
Unweighted
mean
Standard
deviation
0.71
0.13
15.89
252.88
4.49
48.57
9.94
0.12
0.10
2.02
0.63
0.72
7.94
0.60
0.22
0.77
0.16
16.12
260.60
4.41
49.80
11.05
0.14
0.07
1.38
0.72
0.77
7.65
0.51
0.24
0.42
0.17
0.80
26.09
1.76
13.24
4.55
0.34
0.26
5.44
0.45
0.42
4.94
0.50
0.43
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Determinants of Food Spending at Modern Outlets
The explanatory variables in our Cragg double-hurdle model are the log of per
capita expenditure, the square of the log of per capita expenditure, household
size, the age of the household head, a dummy for a female-headed household, a
dummy for a working wife, the interaction of a working wife and the number of
hours she works per week, a dummy for refrigerator ownership, a dummy for
vehicle ownership, travel time to a modern outlet, a dummy for households living in Surabaya, and a dummy for households living in Bogor. Table 1 shows the
weighted and unweighted means of the dependent and independent variables
in the model. The weighted means take into account the sampling weights, so
they describe the urban populations of the three cities. The unweighted means
describe the sample itself, which over-represents households in high-income
neighbourhoods near supermarkets.
The average share of food purchased at modern retailers is 13% (table 1).1
The average household size is about 4.5 members, 12% of households have a
female head, and the average household head has about 10 years of education.
Refrigerators are fairly common, owned by 63% of urban Indonesian households.
Vehicles (most of which are motorbikes) are more common, owned by 72%. About
10% of wives work outside the home, and they work 20 hours a week, on average.
1. This igure differs from the igure in the previous section (19%) because this igure is the
average of household shares, while the earlier igure was the share of overall food expenditure allocated to modern outlets. The latter igure gives more weight to households with
higher food expenditure.
382
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
TABLE 2 Determinants of the Share of Food Spending Allocated to Modern Retailers
Coeficients (z–statistics)
Independent variables
Log of per capita expenditure
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
(Log of per capita expenditure)2
Household size
Age of household head
Education of household head (years)
Female-headed household
Wife works outside home
Weekly hours worked by wife outside home
Owns refrigerator
Owns motorbike, car, or truck
Travel time to nearest modern outlet (mins)
Lives in Surabaya
Lives in Bogor
Constant
Sigma
Observations
(1)
(2)
4.686
(2.27)**
–0.127
(2.00)**
0.185
(4.96)***
–0.002
(0.40)
0.084
(5.75)***
0.118
(0.80)
0.208
(0.37)
–0.004
(0.13)
0.441
(3.87)***
0.320
(2.69)***
0.005
(0.46)
0.179
(1.47)
0.146
(1.03)
1.686
(2.99)***
–0.048
(2.83)***
0.029
(4.85)***
–0.003
(3.21)***
0.016
(5.09)***
0.014
(0.41)
0.136
(1.28)
–0.007
(1.46)
0.121
(2.77)***
0.032
(0.74)
–0.002
(0.71)
0.063
(2.45)**
0.076
(2.50)**
–43.744
(2.62)***
0.200
(20.72)***
–15.107
(3.20)***
1,117
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Note: (1) Dependent variable = share of households that shop at a modern outlet. (2) Dependent variable = share of the food budget spent at a modern outlet among those that shop at modern outlets.
* p < 0.1; ** p < 0.05; *** p < 0.01.
The travel time to a modern retailer is just 8 minutes, on average, although the
travel time to a supermarket (not shown) is close to 20 minutes.
Table 2 shows the results of the Cragg double-hurdle model. The irst column
shows the model of the probability of shopping at a modern outlet, while the second shows the model of the share of food purchased at a modern outlet among
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
383
those who use modern food retailers. Although table 2 identiies the independent
variables that are signiicant predictors of shopping behaviour, it does not provide useful information on the size of the effect (because the coeficients do not
have intuitive interpretations). We therefore provide the average partial effect,
deined as the impact of a one-unit change in the independent variable on the
unconditional share of food expenditure allocated to modern retail outlets. This
partial effect takes into account the effect of the independent variable on both
the probability that the household shops at modern outlets and the share of the
food budget spent at modern outlets among those households. Because the partial
effect is a non-linear function of the independent variables, we give the average
partial effect across the households in the sample. We calculate the standard error
of the partial effect by using bootstrap methods, with 500 replications, and we use
the variation across replications to estimate the standard error of the partial effect.
The results in table 2 suggest that per capita expenditure has a statistically signiicant and positive effect on both the probability of shopping at a modern outlet
and the share of food purchased there (conditional on shopping at a modern outlet). This is not surprising, given the higher costs and greater amenities provided
by supermarkets and other modern retailers. In both models, the quadratic term
is negative and statistically signiicant; the coeficients suggest that both curves
level off near the upper end of the range of per capita expenditure.
The partial effect of log per capita expenditure, which incorporates the effects
of the linear and quadratic coeficients, is 0.06. This means that a 1% increase in
per capita expenditure is associated with an increase of 0.06 percentage points in
the share of the food budget spent at modern outlets. The share of food spending at modern outlets is therefore rising with income, but only slowly. The small
partial effect relects the fact that, from the poorest decile to the richest, per capita
expenditure rises 12-fold, while the share of spending at modern outlets rises
from 4% to 28%.
The coeficients on household size in the two models are positive and statistically signiicant. This implies that, after controlling for other household characteristics, larger households are more likely both to shop at a modern outlet and
to spend a larger share of their food budget there. Since supermarkets tend to be
farther than traditional retailers from the average household, the higher ixed cost
of getting to a supermarket may be easier to justify if the household is planning to
buy a large quantity of food.
The shopping patterns of female-headed households and households in which
the wife works outside the home do not seem to differ from those of other households, after taking into account income, education, and other variables. Nor is
the age of the household head a statistically signiicant factor in the decision to
shop at a modern outlet, although it does have a signiicant effect on the share of
food purchased at a modern outlet among those shopping there. The coeficient
is negative, indicating that younger shoppers spend a larger share of their food
budget at modern outlets than older shoppers. The education of the household
head, however, is positively and signiicantly related to both the probability of
shopping at a modern outlet and the share of the food budget spent there, even
after holding income and other variables constant. This outcome could relect a
greater awareness of food quality and safety, or perhaps different social norms,
among more educated consumers.
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
384
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
Owning a refrigerator is another positive and signiicant predictor of both the
likelihood of shopping at a modern retailer and the share of food purchased there.
This is not surprising, given that having a refrigerator allows the household to
make larger and less frequent shopping trips, which reduces the relative cost of
shopping at more distant supermarkets. Owning a vehicle (such as a motorbike,
car, or truck), on the other hand, is positively associated with the probability of
using modern food retailers—having a vehicle presumably makes it easier to
travel longer distances to a supermarket or hypermarket, for example—but not
with greater spending at these retailers.
Somewhat surprisingly, travel time to the nearest modern outlet is not a statistically signiicant predictor of either the probability of using a modern outlet or the
share of the food budget spent at modern outlets. Similar results were obtained
with travel time to speciic types of modern outlets such as a supermarket or a
hypermarket. Travel time may not be a good measure of accessibility: a supermarket may be close to, or on the way to, a common destination, such as a workplace
or school, making it easily accessible even if it is far from the home.
Households in Surabaya or Bogor are no more likely to shop at a modern outlet than those in Surakarta, but if they do shop at a modern outlet they are more
likely to spend a larger share of their food budgets there. This may relect the
size of the city (Surakarta is the smallest of the three) or the fact that municipal
authorities in Surakarta have sought to improve standards at traditional wet markets. After controlling for other factors, we ind that households in Surabaya and
Bogor allocate three percentage points more of their food budget to modern retailers than those in Surakarta.
Projections of the Share of Urban Food Expenditure at Modern Retailers
To project the growth of the urban modern food sector in Indonesia, we re-estimate the Cragg model in table 2 and limit the explanatory variables to per capita
expenditure and per capita expenditure squared. We then estimate the share of
food purchased at modern retail outlets on the basis of 4.5% annual growth in
income (expenditure) for each household. Table 3 shows that the share of urban
food purchased at modern retailers rises from 18% in 2010 to 24% in 2025. Given
the projections of urban population growth and the decline in the food share in
household budgets, this implies that aggregate urban food expenditure at modern retailers rises from Rp 81 trillion in 2010 to Rp 234 trillion in 2025, implying
an annual growth rate of 7.3%. Over this period, food expenditure at traditional
retailers grows more slowly, at 4.8% annually, but aggregate spending at traditional food retailers more than doubles.
Given the uncertainty about the assumptions behind these projections, we
examine the sensitivity of the results to different assumptions (table 3). We irst
assume annual growth in per capita income to be 9.0%, rather than 4.5%. This is
an extreme assumption, given that Indonesia has achieved this rate of growth
only three times in the past 50 years, but it serves as an upper bound on the speed
of transformation of the modern retail sector. If per capita income were to grow at
9.0% annually between 2010 and 2025, the modern food share would rise to 28%
in 2025, compared with 24% in the base scenario. Yet the overall demand for food
would also grow faster, implying higher growth in food demand at both modern
retailers (11.0%) and traditional retailers (6.9%).
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
385
TABLE 3 Projections of Urban Food Spending at Traditional
and Modern Retail Outlets (Rp trillion)
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Year
2010 (estimated)
2015
2020
2025
Sensitivity analysis
2025 with 9% income growth
2025 with 2 × modern share
elasticity
2025 with 9% income growth &
2 × modern share elasticity
Total
urban food
spending
Urban food
spending at
traditional
outlets
Urban food
spending at
modern
outlets
Share of
urban food
spending
at modern
outlets (%)
457
595
772
991
376
478
604
757
81
118
168
234
18
20
22
24
1,410
1,019
390
28
991
689
302
30
141,094
871
538
38
Source: Analysis of data from the authors’ 2010–11 survey of urban consumers.
Note: The base scenario assumes per capita income growth of 4.5% and urban population growth of
2.1%. The urban food spending at traditional and modern outlets and the urban food share are based
on the relation between income and these variables in the survey data, combined with the projected
income growth. See the text for additional information.
If we doubled the elasticity of the modern retailer share with respect to income,
the modern food share would rise to 30% in 2025. This would dampen the growth
of traditional food retailers, but it would still increase by an average rate of 4.1%
per year. If we combined higher (9.0%) income growth and the greater elasticity
of modern food share with respect to income, the share of the modern food sector
would reach 38% in 2025. Under these assumptions, urban food demand would
grow by 13.5% per year for modern retailers and by 5.8% per year for traditional
retailers.
IMPLICATIONS FOR SMALL FARMERS AND POLICY
Our results have several implications for the future of small farmers in Indonesia and
the traditional market channel. Small-scale vegetable growers are barely affected
by the growth of supermarkets and other modern food retailers; urban consumers still prefer to buy fresh vegetables from traditional wet markets and peddlers,
which account for almost 80% of the vegetable purchases in larger cities. Warung
and semi-permanent stands account for most of the remainder, leaving hypermarkets, supermarkets, and mini-marts with a combined market share of less than 2%.
This small share, combined with the demand for vegetables in smaller urban settlements and rural areas, where the share of modern retailers is even smaller, suggests
that modern retailers play a negligible role in vegetable marketing.
This pattern is conirmed by the results of two farm surveys carried out by the
authors. One survey covered 596 chilli farmers in the main chilli surplus zone in
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
386
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
the highlands of Java. Just 3% of the farmers interviewed reported that their chillies were being sold in a supermarket (Sahara et al. 2015). Another survey covered
662 randomly selected shallot growers in the highly commercial north coast of
Java near Brebes (Wahida 2015). Among these farmers, just 3% reported that their
shallots were being sold in a supermarket.
The impact of supermarkets on farmers is sometimes described as a doubleedged sword: it gives farmers the opportunity to sell into a growing and more
lucrative market, but it also threatens to exclude farmers if they cannot meet the
quality and quantity requirements imposed by supermarkets. Our indings, however, suggest that vegetable farmers in Indonesia are not at risk of being squeezed
out of growing modern channels any time soon. Yet very few of these farmers are
likely to beneit from the opportunity to increase the quality of their produce and
earn a better price by selling into the modern channel.
The story for fruit growers is similar. About 30% of fruit in urban areas is purchased from modern retailers. Yet the two fruits with the highest share purchased
at modern retailers are apples, almost all of which are imported, and citrus fruit,
which are both imported and locally produced. On the other hand, more than 90%
of the urban demand for tropical fruit (including mangoes, papayas, bananas,
mangosteens, and pineapples) is channelled through traditional retailers—wet
markets, semi-permanent stands, and peddlers, in particular. Like vegetable
growers, hardly any local fruit growers have much contact or experience with
supermarkets. This does not mean that the fruit sector is static; there is evidence
of technical change and market transformation, but they are driven by competitive forces within the traditional marketing channel rather than by the growth of
supermarkets and other modern retailers.
The growth of supermarkets may pose a threat to Indonesian fruit growers, not
by taking over domestic supply chains but by developing and expanding international supply chains that bring imported fruit into the country. Supermarkets
facilitate consumer access to high-quality imports of citrus fruit, for example, thus
challenging domestic producers. And although there are virtually no domestic
apple producers, increased access to imported apples may replace some of the
demand for locally grown tropical fruits.
There is also a concern that the growth of supermarkets and other modern retailers in Indonesia could squeeze out traditional retailers, including warung owners,
wet-market vendors, and peddlers. This could create hardships for vendors in the
short- to medium-term, until they ind new employment. To the extent that supermarkets are less capital-intensive than retailers in the traditional market channel,
the growth of supermarkets could gradually decrease the demand for labour.
These concerns, however, are based on the assumption that the modern channel
is large enough and growing fast enough to cause the traditional channel to contract. Our analysis suggests that the traditional channel will continue to expand,
although at a slower rate than the modern channel. More speciically, we expect
urban food expenditure at supermarkets and other modern retailers to expand by
about 7% per year over 2010–25. Over the same period, we project that urban food
expenditure at traditional retailers will grow by slightly less than 5% per year. In
other words, although the traditional food channel is declining in market share, it
will continue to grow at a healthy rate, thanks to rising income and an expanding
urban population.
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
Urban Shopping Patterns in Indonesia and Their Implications for Small Farmers
387
CONCLUSIONS
The effect of the growth of supermarkets on traditional retailers and fruit and
vegetable farmers, and particularly on small farmers, has been the topic of some
debate. Modern retailers often impose strict quality standards that may be dificult for small farmers to meet, and often favour larger growers in order to reduce
transaction costs (thus squeezing small farmers out of these growing modern supply chains). At the same time, supermarkets provide an opportunity for small
farmers to raise their incomes by supplying the modern channel, particularly if
they can get inputs, credit, and technical assistance to help them meet the necessary quality standards. Another concern is that the rapid growth of supermarkets
will displace traditional retailers, such as warung owners and wet-market vendors
(Chowdhury, Gulati, and Gumbira-Sa’id 2005).
According to our survey of 1,180 randomly selected urban households in three
large cities of Indonesia, urban consumers spend about 31% of their food budget
at warung, 24% at traditional wet markets, and 19% at modern outlets. This pattern varies greatly across income deciles: poor households spend little at modern outlets (3% in the poorest decile) while high-income households spend much
more (30% in the top deciles).
Our Cragg double-hurdle regression analysis indicates that the share of food
purchased at modern outlets is determined by a combination of income, household size, the age and education of the household head, and whether the household has a refrigerator. Surprisingly, distance and travel time to a modern outlet
do not have statistically signiicant effects on retailer choice.
The share of vegetables purchased at modern retail outlets is very small (less
than 5%), suggesting that current supermarket standards or efforts to organise
supply chains have a negligible effect on vegetable farmers. The share of fruit
bought at modern outlets is somewhat higher (30%), though it is concentrated on
a few imported fruits. The impact of supermarkets on local fruit growers has more
to do with facilitating fruit imports than with forcing quality requirements on
local farmers. In general, local fruit and vegetable growers are not at risk of being
squeezed out of the market by the growth of supermarkets and other modern
retailers, but, at the same time, few of them are likely to beneit from this growth
in the medium term.
Urban food demand at modern retail outlets is growing rapidly, but not rapidly enough to result in an absolute decline in food demand at traditional retail
outlets. On the basis of the results of the survey and our plausible assumptions,
urban food demand will grow by about 7% per year at modern retailers and by
slightly less than 5% per year at traditional retailers. This suggests that the transition from traditional to modern food retailing may be less disruptive than has
been feared.
REFERENCES
Chowdhury, Shyamal K., Ashok Gulati, and E. Gumbira-Sa’id. 2005. ‘The Rise of Supermarkets and Vertical Relationships in the Indonesian Food Value Chain: Causes and
Consequences’. Asian Journal of Agriculture and Development 2 (1–2): 39–48.
Cragg, John. G. 1971. ‘Some Statistical Models for Limited Dependent Variables with
Application to the Demand for Durable Goods’. Econometrica 39 (5): 829–44.
Downloaded by [Universitas Maritim Raja Ali Haji] at 23:17 17 January 2016
388
Nicholas Minot, Randy Stringer, Wendy J. Umberger, and Wahida Maghraby
Dyck, John, Andrea E. Woolverton, and Fahwani Yuliati Rangkuti. 2012. Indonesia’s Modern Food Retail Sector: Interaction with Changing Food Consumption and Trade Patterns.
Economic Information Bulletin 97. Washington, DC: Economic Research Service, US
Department of Agriculture.
FAO (Food and Agriculture Organization). 2015. ‘Food Balance Sheet’. http://faostat3.fao.
org/download/FB/FBS/E.
Reardon, Thomas, C. Peter Timmer, Christopher B. Barrett, and Julio Berdegué. 2003. ‘The
Rise of Supermarkets in Africa, Asia, and Latin America’. American Journal of Agricultural Economics 85 (5): 1140–46.
Sahara, Sahara, Nicholas Minot, Randy Stringer, and Wendy Umberger. 2015. ‘Determinants and Effects of Small Chilli Farmers’ Participation in Supermarket Channels in
Indonesia’. Bulletin of Indonesian Economic Studies 51 (3): 445–60.
Tobin, James. 1958. ‘Estimation of Relationships for Limited Dependent Variables’. Econometrica 26 (1): 24–36.
UN DESA (United Nations Department of Economic and Social Affairs). 2011. World
Urbanization Prospects: The 2011 Revision. New York: United Nations.
Wahida. 2015. ‘Food System Transformation in Indonesia: Factors Inluencing Demand
and Supply for Alternative Pest Management Farming Systems’. PhD diss., Global
Food Studies, University of Adelaide.
World Bank. 2007. Horticultural Producers and Supermarket Development in Indonesia. Report
38543-ID. Jakarta: World Bank.
———. 2015. World Development Indicators. Washington, DC: World Bank.