Religion, food choices, and demand seasonality: Evidence from the Ethiopian milk market
E. D'Haene¹; S. Desiere²; M. D'Haese¹; W. Verbeke³; K. Schoors³
1: Ghent University, Agricultural Economics, Belgium, 2: Leuven University, , Belgium, 3: Ghent University, , Belgium Corresponding author email: [email protected] Abstract: This paper addresses the role of religious practices on market outcomes. We study the Ethiopian milk market what amounts to a natural experiment influenced by different Christian, Islamic and traditional faiths. Focal point of this article are the fasting rituals characterized by the abstinence of animal products, a fundamental pillar of Orthodox Christianity, the dominant religious group within Ethiopia. Employing country-wide data collected by the Living Standards Measurement Studies, we find, much to our surprise, that the fasting rituals of the Orthodox Christian society adversely affects both milk demand in Orthodox and local Muslim communities alike. The direct effect on Orthodox groups and the spillovers to Muslim networks create important market inefficiencies. The religion-related demand cycles are particularly challenging to government policies that aim to develop the livestock sector. Keywords: Consumer behavior, Collective fasting rituals, Intentional demand seasonality, Livestock sector development and policies, Religion, Market inefficiencies Acknowledegment: JEL Codes: Q11, D12
#2086
Religion, food choices, and demand seasonality: Evidence from the Ethiopian milk market
Abstract
This paper addresses the role of religious practices on market outcomes. We study the Ethiopian milk market what amounts to a natural experiment influenced by different Christian, Islamic and traditional faiths.
Focal point of this article are the fasting rituals characterized by the abstinence of animal products, a fundamental pillar of Orthodox Christianity, the dominant religious group within Ethiopia. Employing country- wide data collected by the Living Standards Measurement Studies, we find, much to our surprise, that the fasting rituals of the Orthodox Christian society adversely affects both milk demand in Orthodox and local
Muslim communities alike. The direct effect on Orthodox groups and the spillovers to Muslim networks create important market inefficiencies. The religion-related demand cycles are particularly challenging to government policies that aim to develop the livestock sector.
Keywords: Consumer behavior, Collective fasting rituals, Intentional demand seasonality, Livestock sector development and policies, Religion, Market inefficiencies
1 Introduction
1 The term ‘Livestock Revolution’ was introduced by Delgado et al. (1999) to point to the unprecedentedly
2 rapid increase in demand for livestock produce noted in the developing world since the 1970s. Population
3 growth, progressive urbanization and growing per capita income levels are thought to be the revolution’s
4 driving forces (Delgado et al. 1999). While individual intake of livestock produce indeed exploded in some
5 transforming and urbanized economies of Asia and Latin-America (particularly in China, India, and Brazil),
6 the ‘revolution’ surpassed the majority of developing countries including sub-Saharan Africa (SSA). Annual
7 growth rate of per capita milk, meat and egg consumption in SSA was -0.2, 0.2, and 0.3% respectively for
8 the period 1987-2007 (Gerosa & Skoet 2013). Problems of structural supply, poorly developed local
9 markets, low income, and consumer preferences have been discussed to explain this stagnating progress
10 (e.g. Staal et al. (2008), Rae and Nayga (2010), and USAID (2013)). Yet, within this literature on
11 consumption of animal-source foods (ASF), the impact of cultural values in general, and religion in particular,
12 has been largely neglected; a research gap we address in this paper.
13 The significance of including an appropriate level of ASF in diets to improve dietary quality and diversity has
14 been underpinned by an abundant number of studies (Murphy and Allen 2003; Jin and Iannotti 2014). ASF
15 are valuable and dense sources of several micro- and macronutrients which are hard to retrieve in adequate
16 amount from plant source foods only (Murphy and Allen 2003). Livestock-based interventions are deemed
17 to be a decisive strategy to reduce malnutrition, especially in SSA where half of the world’s malnourished
18 population is residing, and where diets predominantly consists of cereal- or root staple crops (Hetherington
19 et al. 2017).
20 Within SSA, Ethiopia has the largest estimated livestock herd (Tilahun and Schmidt 2012), still Ethiopian
21 diets contain little ASF; animal produce account for only 1.7 and 3% of the total energy intake of rural and
22 urban households respectively (Hirvonen 2015). In August 2015, the Ethiopian government launched the
23 national Livestock Master Plan to boost livestock production and productivity. Roadmaps were developed
24 for different key livestock value chains. Albeit the plan stipulates the importance of promoting livestock
25 produce consumption, the proposed policy interventions mainly focus on improving livestock production and
2 26 productivity through enhanced herd management, genetic resources, feed, and health care (Shapiro et al.
27 2015).
28 This study emphasizes the demand side of the livestock market. Where numerous studies generally assume
29 a rise in per capita consumption of ASF in the African continent, we challenge this conception. Cultural and
30 religious values and practices are known to slow down the substitution of starchy staples in African food
31 baskets by high-value foods such as ASF (Robinson and Pozzi 2011). Religious traditions are deeply
32 embedded in SSA’s societies. These traditions are very diverse and are fundamentally influencing everyday
33 life. Christianity and Islam are particularly important and represent 62.9 and 30.2% of people’s affiliations in
34 the continent (Pew Research Center 2014). Both traditions have been co-existing for centuries and are
35 amongst the fastest growing religious faiths in SSA (Schulz and Janson 2016). Ethiopia, the second most
36 populous of the continent, is home to Orthodox (44% of the population), Muslim (34%), Protestant
37 (19%),Catholic (1%) and traditional faiths (3%) (CSA 2010).The country resides the second largest
38 community of Orthodox Christians (which numbers to 39 million), out of the 138 countries where this sub-
39 group is represented (Brill n.d.). This paper focuses on the fasting rituals traditionally embedded in the
40 dominant Ethiopian Orthodox Church (EOC). During fasting events, which are scattered throughout a
41 religious year, Orthodox followers are presumed to pursue a vegan diet, hence abstaining from consuming
42 any animal product. With around half of the Ethiopian population being member of the EOC and a total sum
43 of about 200 Orthodox fasting days a year, religion clearly influences demand for animal produce in the
44 country (Hirvonen et al. 2015). Although several studies mention that fasting undeniably impacts livestock
45 consumption patterns as it is causing a seasonal demand cycle (Hirvonen et al. 2015; Bachewe et al. 2017;
46 USDA-FAS 2017)), none but one (Negassa (2009)) has attempted to quantify this effect on raw milk and
47 butter purchase within two Ethiopian towns.
48 Our aim is to evaluate the economic and societal impact of religion on food systems by specifically focusing
49 on the milk value chain. Milk is the largest source of animal-based protein in developing countries,
50 accounting for 60% of total per capita consumption of primary livestock products (i.e. meat, milk and eggs)
51 (Gerosa and Skoet 2013). It is a promising ASF in developing countries as it has been associated with one
52 of the lowest production costs when compared to other plant and animal protein sources (Drewnowski
53 2010). Based on our findings, we argue that religious values and practices (amongst other factors) lay at
3 54 the root of low and stationary consumer demand for animal produce and contribute to the so-called
55 intentional demand seasonality. Moreover, the impact of religious rituals is not limited to demand, as they
56 cause important shifts in production decisions at household-level. The impact of collective fasting rituals is
57 also not restrained to the practicing group. Important spillover effects are detected for other groups within
58 society, especially the Muslim community.
59 Our research adds to literature on economics of religion in different ways: (1) because of religious group it
60 focuses on and (2) the location. The scholarship of this subdomain of economics is predominately one of
61 economics on Islam and still has a biased research focus on Western countries (neglecting both Asia, but
62 particularly Africa) (Iyer 2016). Additionally, the impact of religion in shaping food choices has been
63 understated within the scholarship on consumer behavior (Heiman et al. 2017). Hence, we contribute to this
64 literature on consumer behavior and religiously-inspired consumption rituals.
2 Background
2.1 Linking religion and consumer behavior
65 Religion influences consumers both directly via explicit instructions laid out in holy texts and/or by religious
66 leaders and indirectly through beliefs and attitudes established within the larger religious group (Harrell
67 1986). Despite this apparent relation between religion and consumer behavior, this area is vastly
68 understudied. Quantitative analyses on the impact of specific religious beliefs and practices on consumer
69 behavior and associated market outcomes remain scarce and scattered (Mathras et al. 2016; Heiman et al.
70 2017). A large majority of the studies done so-far unravel behavioral intentions rather than revealed
71 behavioral actions, and have a predominant focus on Islamic traditions. Furthermore, the available empirical
72 research is rather business-oriented. These studies are highly informative for advertising strategies, store-
73 and brand image building, product decisions, and establishing (new) market channels. As such Fam et al.
74 (2004) and Putrevu and Swimberghek (2013) find that offensiveness vis-à-vis advertising controversial
75 product groups (like gender related produce) differs significantly across religious denominations and
76 devoutness. Other research observes divergent values attached to various store attributes (e.g reputation,
77 shopping efficiency, and friendliness of personnel) (McDaniel and Burnett 1990; Mokhlis 2009), discrepancy
78 in preferred store types (Mokhlis 2009), store- and brand loyalty (Shachar et al. 2011; Swimberghe et al.
4 79 2014), frequency of Sunday and in-town shopping (Siguaw and Simpson 1997) and consumer
80 characteristics such as quality and price consciousness, and impulsiveness (Mokhlis 2006). Likelihood to
81 purchase specific products also differs amongst religious denominations (e.g. environmentally-friendly
82 produce (Felix and Braunsberger 2016), Fairtrade products (Doran and Natale 2011), genetically modified
83 products (Hossain and Onyango 2004), whole fresh chicken versus cut or frozen chicken (Heiman et al.
84 2004). Finally, some studies reveal valuable insights that can guide the establishment of particular market
85 channels e.g. Verbeke et al. (2013), and Heiman et al. (2017) who focus on different Halal and Kosher
86 certification channels and accompanying supply channels.
2.2 Costly religious rituals
87 Rules and restrictions are inherent to religious institutions and often relate to dietary practices. These food
88 restrictions give rise to distinct consumption patterns and are either temporally (such as fasting) and/or
89 permanently established (e.g. restriction to Kosher and Halal food in Jewish and Islamic traditions
90 respectively) and require abstinence from all (e.g. Ramadan from dawn to sunset) or certain foods
91 (commonly applied to ASF) (Sabaté 2004; Meyer-Rochow 2009; Trepanowski and Bloomer 2010).
92 Fasting is a fundamental pillar within different religious denominations. Many studies focus on the Islamic
93 fasting month, Ramadan, and how participation affects various divergent outcomes such as dietary and
94 nutrient intake (Gharbi et al. 2003; Maughan et al. 2008; Norouzy et al. 2013), mental and physical health
95 (Kadri et al. 2000; Chtourou et al. 2017; Nugraha et al. 2017), educational performance (Oosterbeek and
96 van der Klaauw 2013; Majid 2013), physical performance (Reilly and Waterhouse 2007; Meckel et al. 2008;
97 Chaouachi et al. 2012), fetal development (Almond and Mazumder 2011; Majid 2013; Daley et al. 2017),
98 and output growth (Campante and Yanagizawa-Drott 2013).
99 The existing literature on Orthodox Christians mainly concentrates on the Greek community and examines
100 how fasting impacts food and nutrient intake, as well as physical and biochemical body parameters (Sarri
101 et al. 2009; Karras et al. 2017; Koufakis et al. 2017). Only two studies could be retrieved that address the
102 Ethiopian Orthodox Church; one by Knutsson and Selinus (1970) that elaborates on the Easter fasting and
103 how it impacts food intake amongst families and factory workers in the capital, Addis Ababa, and one village
104 in the Oromia region. For small children between six and 36 months old, they detect a crucial drop in total
5 105 protein intake and quality which orginates from the exclusion of milk and other ASF alike. Given the modest
106 appearance of animal produce in non-fasting periods, fasting resulted in a deficiency of 25% compared to
107 recommended total protein intake, which might be harmful for children’s growth and development. The
108 second study we recovered by Negassa (2009) evaluates the determinants of purchasing raw milk and
109 butter within two towns of the Oromia region, accomodating 200 urban households. They observe that
110 quantity of milk purchased declined significantly during fasting, but not so for butter.
2.3 Abstinence from animal products within the Orthodox Church
111 As early as the fourth century, a Christian dynasty settled in Ethiopia. Only three centuries later, Prophet
112 Mohammad’s first followers emigrated to Ethiopia (Brown 1972; Steen-Johnsen 2017). Religious
113 coexistence and interreligious relations have a long history in Ethiopia and are “as old as the Islam itself”
114 (Feyissa 2011, pg 5).
115 Fasting is a ritual commonly practiced within the Orthodox Church. It is seen as an integral part of religious
116 identity, and serves as a measure of piousness (Knutsson and Selinus 1970). As Boylston (2013) witnessed,
117 Ethiopian people would rather ask a person first whether he would fast instead of asking this person whether
118 he/she is Christian. Unique within the EOC (and broad Christian Orthodox Church by extension) is that
119 fasting is performed during different periods throughout a year. Orthodox traditions prescribe their members
120 not to eat any food from animal origin and to consume their first meal after noon or Mass. The fasts
121 performed differ in duration and can be categorized into two main types: one-day fasts occurring on
122 Wednesdays and Fridays all year round (except for the two months after Ethiopian Easter) and longer
123 fasting seasons around or preceding holy events. The Easter fast, also known as Lent, is the longest
124 continuous and most important of all fasts (55 days). Other major fasting periods occur in December-
125 January (40 days) and August (16 days). Besides commonly imposed fasts, a large variety of spontaneous
126 individual fasts are applied which make it very difficult to assess the exact number of fasting days. A
127 literature review revealed that an average of 200 days in a year is common Although the fasting rules are
128 strict, pregnant and lactating women, severely ill or weak persons, as well as children below the age of
129 seven can be exempted. Children between seven and 12 years old should abstain from animal sourced
6 130 foods but they can take their first meal before noon (Knutsson and Selinus 1970; Ficquet 2006; Ayenew et
131 al. 2009; Zellelew 2014).
3 Material and Method
3.1 Data
132 We use data from the Living Standard Measurement Studies (LSMS) conducted by the Central Statistical
133 Agency of Ethiopia in close collaboration with the World Bank. The empirical analysis is based on data
134 collected from a total of 5262 households in 2013/14. The data set covers all regional states including the
135 capital, Addis Ababa. Respondents were selected by means of a stratified two-stage cluster sample design
136 (CSA and World Bank 2015). A minimum number of primary sampling units (PSUs) was set per regional
137 state, using the Probability Proportional to Size (PPS) sampling method. The PSUs correspond to (parts of)
138 municipalities or kebeles, the smallest administrative divisions in Ethiopia. Kebeles were partitioned in one
139 or more enumeration areas (EAs) depending on their terrain and population density. In total, 433 PSUs were
140 obtained. Within each EA, households were randomly selected1.
141 The LSMS questionnaire provides information on basic demographics, including religious affiliation, and
142 households’ consumption of selected food items using a seven days recall period. The interviews were done
143 between February-April 2014, which was before, during and after Lent, the longest continuous fast of the
144 Orthodox church (February 24-April 19) resulting in one third of the interviews being conducted during
145 Orthodox fasting. This allows us to compare consumption patterns outside and during the fasting season.
146 Muslims’ Ramadan took place later that year outside the data collection period (June 28 – July 28 2014)
3.2 Econometric models
147 Our variable of interest, the amount of milk consumed by a household over the past seven days, is censored
148 and equals zero for quite a large number of observations. Using Ordinary Least Square (OLS) regression
149 to analyze these data is hence not appropriate (Long 1997). Instead, a Tobit model is used. Developed by
150 Tobin (1958), it estimates effects of explanatory variables on the dependent outcome variable using a single
151 equation. Our model assumes that the likelihood to consume milk and the actual value of consumption are
1 More information can be found on the LSMS website.
7 152 determined by the same set of coefficients and variables. However, we have no reason to expect that,
153 ceteris paribus, religious affiliation as such influences the level of consumption, indeed conditional on the
154 household consuming milk. We start from the premise that religious denomination influences the decision
155 of a household to consume milk. Especially during Orthodox fasting, the likelihood to consume animal
156 produce within an Orthodox family diminishes. Alternative models are Heckman (Heckman 1976) and/or
157 double hurdle models (Cragg 1971), which both models relax the key assumption of Tobit, by allowing a
158 two-step procedure in which households have to overcome a first hurdle that relates to the decision whether
159 or not to consume (participation hurdle), and a second, the consumption hurdle reflects how much milk to
160 consume. The advantage of Heckman and double hurdle models is they allow to consider non-economic
161 reasons (such as the occurrence of Orthodox fasting) as a decisive variable to stop consuming milk, while
162 Tobit models presume that only economic factors (such as income and milk prices) result in zero
163 consumption levels. Heckman and double hurdle models account for cases in which a household may
164 decide not to consume milk due to reasons that are independent of prices and income. The primary
165 distinction between both approaches, is that the Heckman model presumes that no zero observations are
166 present after passing the first-stage equation. The double hurdle model acknowledges that household can
167 still not to consume milk in the second stage due to random circumstances or because they deliberately
168 decide not to consume anymore. One could however argue that instead of using Heckman and double
169 hurdle models, we could manually run an independent Probit/Logit regression, followed by an OLS/Tobit
170 regression. However, unmeasured household-level variables could affect both the first and second hurdle
171 decision thereby leading to the correlation of the error terms in the Probit/Logit and OLS/Tobit regressions,
172 which is selectivity bias. Heckman and double hurdle models allow to control for this bias (Wooldridge 2002).
173 The econometric specifications of the Tobit, Heckman and double hurdle models are given in Table 1.
* ** 174 Yi represents the observed quantity of milk consumed by a household i, y en y are latent variables,
175 representing the desired or optimal quantity consumed by the household and 푧∗ is an unobservable variable
176 representing the households decision whether or not to consume milk; 푧 is the observed dependent variable
177 which takes on the value of 1 if the household consumes milk and 0 otherwise, 푤 and 푥 are vectors of
178 explanatory variables which are assumed to affect the households’ decision to consume milk and the level
179 of consumption, respectively, whereas α and 훽 are vectors of coefficients measuring the effects of the
8 180 different vectors of explanatory variables 푤 and 푥 respectively. 휀 and 휇 are normally distributed error terms
181 with zero mean and standard deviation of 휎휇 and 휎휀 respectively.
182 When examining our variable of interest (quantity of milk consumed by a household in the week prior to the
183 interview) we found no zero-observation for the consumption hurdle, conditional on a household consuming
184 milk. Running a double hurdle model is hence not appropriate as this procedures runs a Probit regression
185 in the participation hurdle, followed by a Tobit model in the consumption hurdle. We thus only ran a Tobit
186 and Heckman model.
187 Based upon the findings of empirical studies focusing on determinants of milk consumption and the available
188 data within the LSMS, we include the following explanatory variables in our analyzes: gender, age, marital
189 status, educational background, and religious affiliation of the household head, household income, number
190 of infants (six years and younger), younger children (between seven and 12 years old), older people (above
191 the age of 60) and remaining household members2, refrigerator ownership, milk price (Bai et al. 2008;
192 Negassa 2009; Njarui et al. 2011; Trung et al. 2014; Kusiluka et al. 2015). We also consider milk cow
193 ownership and the households’ residence (be it in a rural village, a small town or a large town) to control for
194 the household’s direct access to milk. Finally, a regional state dummy was included to adjust for variations
195 in milk consumption across the regions due to differences in livestock population densities (Tilahun and
196 Schmidt 2012) and tribal practices (CSA and WFP 2014).
4 Descriptive results and discussion
4.1 Consumption of animal source foods
197 ASF are not widely included in Ethiopian diets; only half of the Ethiopian families consume some livestock
198 product (Table 3). When households consume animal products, most of them (59%) stick to only 1 ASF
199 course, which in more than half of the cases is milk. When detailing consumption estimates, families
200 consume fairly more milk compared to meat, eggs, and cheese. Average milk consumption equals one liter,
201 which raises to almost four liters if non-consuming households are excluded. Of the milk consumed, the
2 By incorporating number of infants, young children, elderly people and remaining household members we account for household size and composition. We specifically target vulnerable groups such as infants, younger children, and elderly people as these groups are often prioritized when it comes to milk intake at household level (Negassa 2009; Dorp 2014).
9 202 largest average share comes from home production (three liters or 70%), followed by purchases and gifts.
203 Having livestock that produces milk is thus important to meet households’ demand. In preparation of the
204 Livestock Master Plan, a preparatory study phases found that 85% of milk produced in Ethiopia is consumed
205 by milk producing households, only 7% of it is sold (MoARD 2007).
4.2 Dynamics of Orthodox fasting behavior affecting milk consumption
206 When average milk consumption volumes were calculated irrespective of a household’s religious affiliation,
207 volumes said to be consumed during the past week significantly decrease during Lent: from 1.26
208 liters/household during a non-fasting week to 0.90 liters/household in fasting time. Figure 1 gives a
209 comparison of the consumption patterns across the different religions (i.e. Orthodox, Protestant, Muslim and
210 other).
211 Overall Orthodox families seem to consume less milk compared to other religious communities (part a
212 Figure 1), which can partly be explained by the smaller proportion of Orthodox households that consume
213 milk (part b Figure 1). Part a of Figure 1 shows that Orthodox Christians consumed almost 30% less milk
214 during Lent compared to their religious peers outside the fasting season. Although this drop might seem
215 small, the proportion of Orthodox households that consumes milk remains fairly constant outside and during
216 Lent. Comparing the household characteristics of Orthodox families that consumed milk during fasting with
217 those that abstained from milk, revealed that those households that kept on consuming milk during Lent had
218 significantly larger families in which infants were significantly higher represented.
219 Not only Orthodox families see their consumption reduced, the difference in milk consumption levels outside
220 and during Lent across Muslim households is notable (part a Figure 1). Part b of Figure 1 reveals that the
221 proportion of Muslim households drinking milk reduces from 56 to 47%, which could partially explain this
222 drop. However, an opposite trend is observed amongst Protestant families (Part b Figure 1). Avery (2004),
223 Aklilu et al. (2007), Tewodros (2008), Boylston (2013) and Hirvonen et al. (2015) observed limited availability
224 of ASF and altering markets during Orthodox fasting. Avery’s study among supermarkets and butcheries
225 in the Addis Ababa area revealed that 85% of the butcheries close on traditional Wednesday and Friday
226 Orthodox fasting days and 43% of the supermarkets report a drop in meat sales. If the market for dairy
227 produce is dissolving during Orthodox fasts, we would expect that milk consumption would drop for both
10 228 Protestants and Muslims. This is not what we observe. As most of the household’s milk consumption comes
229 from home production, we looked into changes in the share of consumed milk coming from home production
230 during and outside fasting. We find that an average household drinking milk significantly reduces the share
231 of consumed milk coming from home production by one-fifth during fasting (from 72 to 56%). But Figure 2
232 reveals that only Orthodox and Muslim families significantly reduce producing milk during Lent. As we have
233 no detailed data on milk production during the week prior to the interview, we could not look further in this
234 finding, but this definitely requires further investigation. A potential hypothesis could be that Orthodox
235 families who continue consuming milk during Lent, start purchasing milk from Protestant producers, albeit
236 ceasing their own production because of fasting3. As Protestants are members of the broad class of
237 Christianity, Orthodox might preferably trade with Protestant milk producers. For meat, because of the
238 different religious slaughtering rituals, exclusionary meat trading practices are evident (Ficquet 2006;
239 Zellelew 2015). If this Christian-Muslim hurdle exists for milk, we might expect that overall Muslims’ milk
240 production and hence consumption (as almost 80% of the produced milk is consumed at home) decrease
241 much more in Orthodox dominated areas. Likewise the effect of fasting on milk consumption amongst
242 Orthodox Christians may be stronger in Orthodox dominated areas, and perhaps less strong when the
243 Orthodox group is smaller compared to Muslim or Protestant communities. The strength by which milk
244 consumption behavior is affected by religious peers is tested by introducing an interaction term of religion
245 and the concentration of EOC members at zone level4.
5 Modelling milk consumption at household level
246 Based on the results of the Heckman model, we suspect selection bias, which is why we prefer only present
247 the results of the model in Table 3. Overall it appears that the included explanatory variables mainly affect
248 the household’s likelihood to consume milk; household income seems to be the main determinant for the
249 quantity of milk consumed, conditional on the household consuming milk. Holding all other variables at their
250 mean values, average milk consumption (which was determined at 1.16 liter/household/week) increased
251 with 1.02 liters/household when total annual expenditure doubles. This implies that the income elasticity of
3 Knutsson and Selinus (1970) witnessed that “even touching the forbidden food … is considered as a break in the fasting rules”. 4 Data were aggregated at zone-level, the smallest geographical unit for which we had sufficient numerical figures.
11 252 milk in Ethiopia is close to one Similarly, Worku et al. (2017) found that a doubling of income nearly doubles
253 expenditures on animal-source foods. As a low-income country, Ethiopia’s income levels limit the demand
254 of milk. The remaining part of this paper will specifically focus on the independent variables affecting the
255 participation hurdle.
5.1 Religion matters
256 Three variables were incorporated to assess the impact of religious affiliation on household’s milk
257 consumption. Religious affiliation as such has a statistically significant impact on the probability of families
258 to consume milk, especially Muslim families and households with affiliations other than Orthodox, Protestant
259 or Muslim are more likely to consume milk compared to Orthodox households. When religious affiliation was
260 interacted with the period of the consumption records, both Orthodox and Muslim families are significantly
261 less likely to consume milk during Orthodox fasting. As mentioned in Section 4, we lack detailed figures to
262 unravel the underlying cause(s) for this surprising observation. Milk consumption of Orthodox and Muslim
263 families fall by 50 and 30% respectively, which is economically highly important, an effect attributed to
264 households abstaining from drinking milk during fasting and its spillover effects. Since the Orthodox and
265 Muslim community jointly represent 80% of the Ethiopian population this observation implies a tremendous
266 impact on national milk demand. Interacting religious affiliation with the relative share of Orthodox
267 households within a zone, had no significant impact, although the coefficient for Muslim households is
268 marginally significant (p=0.052), suggesting that Muslims are less inclined to consume milk when
269 surrounded by many EOC members.
5.2 Insufficient supply and low demand
270 The results for all other controlling variables are as expected. The presence of infants increasingly raises
271 the likelihood to consume milk. When the household heads is female, and/or has above primary education,
272 families are more likely to consume milk. Moreover, rising expenditure level and number of cows owned by
273 the household increases the probability of consuming milk, while fridge ownership does not have a
274 significant impact. However, the effect of cow ownership on the probability to consume milk is smaller with
275 increasing expenditure (negative interaction), and vice-versa, which suggests that having cows is important
276 to have access to milk for poor(er) households. High milk prices are found to curtail the demand for milk.
12 277 Average milk prices in Ethiopia during spring 2014 (i.e. timing of the interviews) equaled 11.90 birr/L or
278 €0.43/L. This price is very similar to the price of milk in Europe (raw milk price in February 2014 was
279 €40.1/100kg) (European Commission n.d.), confirming that dairy products in Ethiopia are expensive, caused
280 by both insufficient production and high marketing costs. According to Staal et al. (1996), these costs arise
281 from milk’s perishable nature, its high water content, and its variable composition and quality. High
282 transaction costs limit margins for farmers rendering them less incentivized to generate milk surpluses.
283 Moreover, location matters. We find that families residing in urban towns show higher probabilities to
284 consume milk, and tend to rely more on local milk markets than on home milk production (suggested by the
285 negative interaction term between milk price and location in Table 3) compared to their rural counterparts.
286 Densely populated areas are known to ease the establishment of local markets as they face lower
287 transaction costs (Staal et al. 2008; Melesse and Beyene 2009). Local markets serve as a substitute for
288 cow ownership, also shown by Hoddinott et al. (2014). Moreover, conditional on a household consuming
289 milk, having additional dairy cows for household residing in urban towns does not increase household’s milk
290 consumption. Instead, we observe an opposite trend. As milk markets tend to be more developed in urban
291 areas, the incentive for households to own cows for sale purposes rather than household nutrition needs
292 increases. The above observations were however only significant for small urban towns. Possibly high
293 transaction costs still persist in large urban areas, hampering development of milk markets which, combined
294 with the (more) limited space for keeping milking cows, poses difficulties in accessing milk for urban
295 households. This is also suggested by Ayenew et al. (2009).
6 Conclusion and policy implications
296 Using country-wide data from the Living Standard Measurement Studies, we accentuate the so-far
297 unexplored impact of religiously-inspired collective consumption rituals on national market development.
298 We demonstrate that poor performance of the dairy sector in Ethiopia is unmistakably intertwined with its
299 large Orthodox community. Yet, our study faces some limitations. As we did not have information about
300 household’s actual involvement in fasting rituals, we matched dates of the fasting period (Lent) with the
301 period of LSMS data collection to determine whether or not consumption data were gathered during or
302 outside Orthodox fasting. Moreover, the households interviewed during fasting are not the same as those
13 303 interviewed outside Lent. Therefore, we recommend that further study focuses on following the same
304 households before, during and after fasting and incorporates a variable of household involvement in
305 religiously inspired rituals, such as fasting.
306 Aggregated milk demand is expected to increase in Ethiopia, as income, population, and urbanization are
307 growing. While factors such as income, population, and urbanization are dynamic, religion is a rather static
308 parameter and we can expect that religious values and related fasting practices will persist in the future. In
309 our analysis we show that fasting dramatically reduces household’s milk demand. Moreover, as fasting
310 periods are spread throughout the year, religion causes a pattern of seasonality in milk demand, which is
311 difficult to cope with for milk farmers and the dairy supply chain. Investing in the establishment of processing
312 plants and adequate storage capacity, facilities, and technology will be extremely important to overcome
313 this systematic religious seasonal supply/demand mismatch and reduce losses and spoilage. Till today, only
314 35 active dairy processors are operative in the country (although often below capacity), and these are
315 located principally around Addis Ababa (Zijlstra et al. 2015).
316 The present study underscores the need of addressing both supply- and demand-side inefficiencies and
317 accounting for religiously inspired cultural differences in order to promote the offtake of the Ethiopian dairy
318 sector. This requires attaching the necessary political weight and effort to the processing and promotion
319 component of initiatives such as the Livestock Master Plan to come to coherent and more inclusive policy
320 interventions. 4Awareness raisign campaigns, focusing e.g. on nutritional benefits of dairy products, are
321 crucial in this context. Moreover, the government might contribute through creating a permanent demand
322 for example via the establishment of school milk programs. Since children below the age of seven are
323 exempted from fasting, such programs could be a very effective policy action to improve food security and
324 adequate nutrition and as a side-effect allow to increase milk demand in Ethiopia.
14 References
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Tobit model Heckman model Double hurdle model Observed consumption Observed consumption Observed consumption
* * * ** yi = y if y > 0 yi = y if z=1 yi = y if z=1 0 otherwise Participation hurdle Participation hurdle y*= xβ + ε z* = wα + μ z* = wα + μ z = 1 if z* > 0 z = 1 if z* > 0 0 otherwise 0 otherwise Consumption hurdle Consumption hurdle y*= xβ + ε y*= xβ + ε y** = y* if y* > 0 0 otherwise
Table 1 Overview of the econometric specifications of Tobit, Heckman and double hurdle models
Mean Proportion of households consuming (%) 0 ASF products 46.05 (0.7) 1 ASF products 31.30 (0.6) 2 ASF products 15.43 (0.5) 3 ASF products 5.97 (0.3) 4 ASF products 1.25 (0.2) Household’s meat consumption (g/week) 481.80 (60.32) Household’s cheese consumption (g/week) 131.05 (10.43) Household’s egg consumption (number/week) 1.57 (0.06) Household’s milk consumption (L/week) 1.39 (0.05) Household’s milk consumption excluding non-consuming households (L/week) 4.13 (0.11) Quantity of consumed milk coming from purchase (L/week) 1.24 (0.06) Quantity of consumed milk coming from own production (L/week) 2.75 (0.12) Quantity of consumed milk coming from gifts and other sources (L/week) 0.25 (0.03)
Table 2 Weighted descriptive statistics on ASF consumption by Ethiopian households, with confidence intervals at α=0.05
20 Coefficient (α) Coefficient (β) participation hurdle consumption hurdle (linearized S.E.) (linearized S.E.) Location (rural omitted) Small town (urban) 1.67 (0.65)** -2.70 (2.48) Large town (urban) 0.14 (0.34) -1.74 (1.49) Interaction (location*milk price) Small town (urban) -0.16 (0.06)*** 0.22 (0.21) Large town (urban) -0.00 (0.03) 0.07 (0.12) Interaction (location*number of cows owned) Small town (urban) 0.20 (0.14) -0.94 (0.30)*** Large town (urban) 0.13 (0.19) 0.15 (0.63) Region Yes Yes Milk price -0.07 (0.02)*** 0.05 (0.09) Logarithm of total expenditure 0.66 (0.04)*** 1.06 (0.24)*** Number of cows owned that gave milk in the past 12 months 2.74 (0.44)*** -2.49 (1.39)* Interaction (logarithm of total expenditure*number of cows) -0.23 (0.04)*** 0.25 (0.14)* Fridge ownership (no fridge omitted) 0.06 (0.08) -0.15 (0.37) Number of infants 0.09 (0.02)*** 0.16 (0.10) Number of young children -0.00 (0.02) 0.09 (0.10) Number of elderly people 0.05 (0.06) -0.35 (0.26) Number of remaining household members -0.04 (0.02)*** 0.09 (0.07) Sex household head (female omitted) -0.18 (0.06)*** 0.14 (0.29) Age household head 0.00 (0.00) 0.01 (0.01) Marital status household head (not-married omitted) 0.02 (0.07) -0.16 (0.31) Educational background household head (below primary education omitted) Primary education -0.03 (0.06) -0.12 (0.26) Above primary education 0.24 (0.08)*** -0.15 (0.36)
Religion (Orthodox omitted) Protestant 0.10 (0.13) Muslim 0.54 (0.12)*** Other 0.51 (0.24)** Interaction (period of consumption records*religion) (Non- fasting omitted) Fasting*Orthodox -0.38 (0.07)*** Fasting*Protestant 0.05 (0.11) Fasting*Muslim -0.26 (0.08)*** Fasting*Other 0.25 (0.27) Interaction (religion* relative share of Orthodox HHs within a zone) Orthodox -0.14 (0.15) Protestant -0.30 (0.21) Muslim -0.36 (0.19)* Other -1.02 (0.56)* Constant -6.63 (0.48)*** -7.49 (2.72)*** Athrho -0.32 (0.11)*** Number of obs = 5012 Censored obs = 3365 Wald chi2(30) = 568.92 Prob > chi2 = 0.0000 Log likelihood= -6875.933 a The dependent variable of participation hurdle is a dummy variable which takes on the value 1 if the household consumed milk in the last 7 days prior to the interview and 0 otherwise. The dependent variable of consumption hurdle is the quantity of milk consumed per household during those 7 days in liters. Significant variations in milk consumption quantity were found across regions, but not represented in the table. Linearized standard errors are given between brackets. ***,**and * represent statistical significance at a probability of less than 1, 5 and 10% respectively.
Table 3 Results from the Heckman modela
21 Interaction (period of consumption records*religion) Mean predicted consumption (L/household/week) Non-fasting*Orthodox 0.76 (0.07)*** Fasting *Orthodox 0.38 (0.06)*** Non-fasting *Protestant 0.79 (0.11)*** Fasting *Protestant 0.86 (0.14)*** Non-fasting *Muslim 1.41 (0.13)*** Fasting*Muslim 1.00 (0.12)*** Non-fasting *Other 0.84 (0.26)*** Fasting *Other 1.21 (0.38)***
Table 4 Predicted milk consumption from the Heckman model for different religious groups at Orthodox fasting and non-fasting days, with confidence intervals at α=0.05
22 a b
3,5 100% 90% 3 80% 2,5 70% 60% 2 50% 1,5 40%
1 30% 20% 0,5
10%
during week prior to the interview the to prior week during to the interview (L/household) interview the to
0 0%
Proportion of households consuming milk consuming households of Proportion Mean observed consumption during week prior prior week during consumption observed Mean
Non-fasting Fasting Non-fasting Fasting
Figure 1 Part a: Average observed milk consumption during February-April 2014 among religious groups at Orthodox fasting and non-fasting; part b: proportion of the households consuming milk among religious groups; confidence intervals drawn are at α=0.05
100% 90% 80% 70% 60% 50% 40% 30% 20%
10% in household's milk intake milk household's in 0% Average share of own production own of share Average Orthodox Protestant Muslim Other
Non-fasting Fasting
Figure 2 Average quantitative contribution of home production to total milk consumption among milk consuming religious households at Orthodox fasting and non-fasting during February-April 2014, with confidence intervals at α=0.05
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