Demand for Selected Fruits Among Students of A Tertiary Institution in Southwest Nigeria

ABSTRACT

Increased demand for fruits among students is pivotal to healthier lifestyles and better learning abilities. However, there is a paucity of information on elasticity of university students’ demand for fruits in Nigeria. The demand for selected fruits among students of University of Ibadan, Nigeria, was therefore assessed in this study. A multistage sampling technique was used to collect primary data from 300 respondents using a questionnaire. Data were analyzed using descriptive statistics and Quadratic Almost Ideal Demand System model. A majority (65.3%) of the respondents were females, less than 20 years of age (51%), and were in either their first or second year of study. Only 40% of the students with less than N10,000 monthly stipends demanded for fruits daily. Own prices, age, sex, and stipends explained fruit demand among the students. Expenditure elasticities for pineapple (1.30), orange (1.21), banana (1.07), apple (1.38), and cucumber (1.16) indicated that the selected fruits were luxury goods while watermelon was a necessity good (0.67). Own-price elasticity of demand for all the selected fruits was inelastic while the cross-price elasticity revealed that most fruits complemented one another except for watermelon which was the only substitute to other fruits. The study therefore recommended increased students’ stipends in order to drive daily fruit demand among the students of the tertiary institution.

KEYWORDS:

• Fruits
• budget share
• demand elasticities
• Quadratic Almost Ideal Demand System
• university students

Introduction

Dietary guidelines throughout the world are increasing the emphasis on consuming more fruits because fruits and vegetables as part of daily diet could help prevent poor health and risk of noncommunicable diseases (WHO, 2014). Increase in the consumption of fruits and vegetables is being promoted because of the health benefits of micronutrients and phytochemicals associated with health maintenance and prevention of chronic diseases (Olufolaji, 2014). Demand for fruit has thus increased, in recent years, due to increased awareness for healthier lifestyles. However, per capita consumption of fruits in Africa is below the recommended 400 g of fruits and vegetables per day (146 kg per person per year) (Hall et al., 2009).

The importance of fruits consumption among university students cannot be overemphasized. This is because fruits are the most sustainable sources of micronutrients that play significant roles in human nutrition and development, especially as sources of vitamins, minerals, and dietary fiber (Oyedele et al., 2014). Also after transition from secondary school to university, when independency increases, students are continuously challenged to make healthy food choices because college or university is a critical period with respect to unhealthy changes in eating behaviors of students (Deliens et al., 2014). Students’ diets are considered imbalanced without the recommended daily intake of fruits. Fruits containing a high amount of anthocyanins, flavonols, and procyanidins, such as berries, grapes, and pomegranate, are effective at decreasing cardiovascular risk while citrus fruits and apples had a moderate effect on blood pressure and blood lipid level (Habauzit et al., 2013). Nutrients in fruits and vegetables help protect the body from infections and reduce the risk of nutrient deficiencies, which could lead to fewer missed days of school and more time spent learning (WHO, 2014; MyPlate, 2011). Also, fruits and vegetables provide fiber to prevent constipation, which may distract students from learning because of discomfort and crankiness (Rajindrajith et al., 2013; Wang et al., 2013).

Despite the available information on the health benefits of fruits, most students of tertiary institutions do not eat the recommended serving of fruits in a day (Alsunni and Badar, 2014; Mintah et al., 2012). This situation promotes health threats in the long run. Understanding the demand for fruits among university students is imperative to agribusiness, educational, and health policy makers in assessing the effectiveness of health education in promoting college students’ health, decreasing the trends to obesity, and preventing diseases (Schroeter et al., 2007). Several studies have investigated the fruit consumption pattern of students of higher institution (Adenegan and Adeoye, 2011; Layade and Adeoye, 2014; Mintah et al., 2012; Perera and Madhujith, 2012). Students’ income, sex, parent’s income, availability of fruits, and taste (Adenegan and Adeoye, 2011; Layade and Adeoye, 2014) influenced tertiary students’ expenditure on fruits in Nigeria. Similarly, Mintah et al. (2012) found that price scores and satiety scores significantly explained students’ fruit intake in a private university in Ghana. However, Kpodo et al. (2015) observed that students’ choice of fruit was influenced by availability, convenience, and attractiveness of fruit in a Ghanaian polytechnic. Perera and Madhujith (2012) also found that gender, income, taboos, and knowledge score had significant effect on fruit and vegetable consumption among undergraduate students of University of Peradeniya. However, little is documented on demand elasticities for fruits among student.

Some authors had used parametric tools (Adenegan and Adeoye, 2011; Perera and Madhujith, 2012; Layade and Adeoye, 2014; Ilesanmi et al., 2014) to identify determinants of food consumption pattern among tertiary students while others used nonparametric tests (Mintah et al., 2012; Alsunni and Badar, 2014; Kpodo et al., 2015; Silva et al., 2017). This study investigated demand elasticities using Quadratic Almost Ideal Demand System (QUAIDS) approach to estimate demand elasticities for fruits among students of the foremost tertiary institution in Nigeria. The QUAIDS model is preferred in demand analysis because it provides a unified framework for analyzing the combined effects of changes in prices, income, and demographic characteristics on demand in a systematic fashion (Ashagidigbi et al., 2012). Based on the aforementioned, it becomes imperative for this study to estimate the demand for selected fruits among students of University of Ibadan. The specific objectives of the study were to identify factors influencing student’s demand for selected fruits and to estimate the demand expenditure elasticities for the selected fruits.

Methodology

Study area

Ibadan is the third largest metropolitan area, by population, in Nigeria, after Lagos and Kano. The city’s total area is 1190 sq. mi (3080 km²). The University of Ibadan is located in Ibadan North Local Government Area of Oyo State, situated 5 mi (8 km) from the center of the major city of Ibadan in Southwestern Nigeria. It is the oldest university in Nigeria, founded in 1948. University of Ibadan is a federally controlled public university consisting of both undergraduate and postgraduate students. The University has 12 halls of residence (10 undergraduate and 2 postgraduate). University of Ibadan is the first and foremost university in Nigeria. It ranked first in Google web metric ranking in 2017. Owing to the transparent admission process, the university admits students from different economic strata, unlike private universities which admit students from wealthy homes. The selection of the university therefore eliminates selectivity bias which would not make the results of the study representative of university students in Nigeria.

Method of Data Collection

A multistage sampling technique was used to select the respondents. The first stage was the purposive selection of all the 10 undergraduate halls of residence in the University of Ibadan. Two blocks were randomly selected from each hall to make a total of 20 blocks. The final stage involved the random selection of 300 respondents proportionate to population size of each block. The study was conducted among the undergraduate students of the university. Data were collected using questionnaire which were given to the randomly sampled students to fill. Undergraduate students were selected because it is a reflection of household welfare in Nigeria since a majority of them were sponsored by their parents. Thus, their expenditure pattern could reflect their economic background. Information were collected on the students’ socioeconomic characteristics, fruits consumption pattern, price, and expenditure on fruits consumed.

Method of Data Analysis

Descriptive statistics and the QUAIDS analysis were used to analyze the data collected. The QUAIDS which is derived from a generalization of the Price-Independent Generalized Logarithmic (PIGLOG) preferences starts from an indirect utility function of the form

(1) $lnV={\left\{{\left[\frac{lnm-lna(\mathrm{p})}{b(\mathrm{p})}\right]}^{-1}+\lambda (\mathrm{p})\right\}}^{-1}$(1)

where the term [ln m − ln a(p)] is the indirect utility function of the PIGLOG demand system (i.e., a system with budget shares linear in log total expenditure), m is the total expenditure, and a(p), b(p), and $\lambda (p)$ are functions of the vector prices p. To ensure the homogeneity property of the indirect utility function, it is required that a(p) is homogenous of the degree one in prices, b(p) and $\lambda (\mathrm{p})$ are homogenous of the degree zero in prices. The lna(p) given in Equation 2 has the translog form:

(2) $lna(\mathrm{p})={\alpha }_0+\sum _{i=1}^j{\alpha }_{i}ln{P}_i+\frac{1}{2}\sum _{i=1}^j\sum _{i=1}^j{\gamma }_{ij}ln{P}_J$(2)

and b(p) is the simple Cobb–Douglas price aggregator defined as

(3) $b(\mathrm{p})=\prod _{i=1}^j{P}_i^{{\beta }_i}$(3)

(4) $\lambda (\mathrm{p})=\sum _{i=1}^k{\lambda }_{i}ln{P}_i;\mathrm{W}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\sum _{i=1}^k{\lambda }_i=0$(4)

where i = 1, … K denotes the number of goods entering the demand model. Application of Roy’s identity or Shephard’s Lemma to the indirect utility function (Equation 1) gives the QUAIDS model budget shares as

(5) ${\omega }_i={\alpha }_i+\sum _{j=1}^k{\gamma }_{ij}ln{P}_J+{\beta }_{i}ln\left[\frac{m}{a(\mathrm{p})}\right]+\frac{{\lambda }_i}{b(\mathrm{p})}{\left\{ln\left[\frac{m}{a(\mathrm{p})}\right]\right\}}^2$(5)

To control for varying preference structures and heterogeneity across students’ demand for fruit, the demographic variables (z) were incorporated into the QUAIDS model (Equation 5). The demand equation then becomes

(6) ${\omega }_i={\alpha }_i+\sum _{j=1}^k{\gamma }_{ij}ln{P}_J+{\beta }_{i}ln\left[\frac{m}{a(\mathrm{p})}\right]+\frac{{\lambda }_i}{b(\mathrm{p})}{\left\{ln\left[\frac{m}{a(\mathrm{p})}\right]\right\}}^2+\sum _{s=1}^L{\delta }_{is}{Z}_s+u_i$(6)

For theoretical consistency and to reduce the number of parameters to be estimated adding-up, homogeneity and symmetry restrictions are commonly imposed. The fact that ${\sum }_i{w}_i=1$ is often called the adding-up condition and this condition is satisfied if

(7) $\sum _{i=j}^k{\alpha }_i=1;=\sum _{i=1}^k{\beta }_i=0;\sum _{i=j}^k{\lambda }_i=0;\sum _{i=j}^k{\gamma }_{ij}=0{\mathrm{\forall }}_j$(7)

Since demand functions are homogeneous of degree 0 in (p,m),

(8) $\sum _{j=1}^k{\gamma }_{ij}=0{\mathrm{\forall }}_j$(8)

Slutsky symmetry implies that

(9) $\sum _{j=1}^k{\gamma }_{ij}=0{\mathrm{\forall }}_j$(9)

The budget share for each selected exotic fruit i is defined as

(10) ${\omega }_i=\frac{{\mathrm{p}}_i{q}_i}{m}$(10)

where w_i = Budget share for each selected fruit i

p_i = Price of each selected fruit i (Naira/kg)

q_i = Quantity of each selected fruit i (Naira/kg)

m = Total expenditure on all the selected fruits (Naira)

$z_i$= Socioeconomic variables

where z₁ = Age (years)

z₂ = Sex (male = 0; female = 1)

z₃ = Marital status (single = 1; marred = 0)

z₄ = Income/allowance (Naira)

The expenditure and price elasticities were obtained by partially differentiating the budget share Equation (5) with respect to lnm and lnp_j, respectively (Banks et al., 1997).

(11) ${\mu }_i\equiv \frac{\mathrm{\partial }{\omega }_i}{\mathrm{\partial }lnm}={\beta }_i+\frac{2{\lambda }_i}{b\left(\mathrm{p}\right)}\left\{ln\left[\frac{m}{a\left(\mathrm{p}\right)}\right]\right\}$(11)

(12) ${\mu }_{ij}\equiv \frac{\mathrm{\partial }{\omega }_i}{\mathrm{\partial }ln{\mathrm{p}}_j}={\gamma }_{ij}-{\mu }_i\left({\alpha }_j+\sum _k{\gamma }_{jk}ln{\mathrm{p}}_k\right)-\frac{{\lambda }_i{\beta }_j}{b\left(\mathrm{p}\right)}{\left\{ln\left[\frac{m}{a\left(\mathrm{p}\right)}\right]\right\}}^2$(12)

The expenditure and the uncompensated/Marshallian price elasticities are computed as

(13) $e_i={\mu }_i/{\omega }_i+1$(13)

(14) $e_{ij}^u=\mu /{\omega }_i-{\delta }_{ij}$(14)

respectively. ${\delta }_{ij}$ represents Kronecker delta taking value 1 if i = j and 0 otherwise. Using the Slutsky equation, the compensated/Hicksian price elasticities is given by

(15) $e_{ij}^c=e_{ij}^u+e_i{\omega }_j$(15)

Results and Discussion

Socioeconomic Characteristics of Respondents

About half of the respondents were below 20 years of age and were in their first or second year of study (Table 1). They were mostly females (65.3%) with about half of them having a monthly income/stipend of less than N10,000 and expenditure of less than N2000 on fruits suggesting that younger students received more stipends from their parents and had more money to purchase fruits. The fact that only 40% of the respondents demanded for fruits daily to support their diet implied that students who consumed fruits daily might have fewer missed days of school due to illness, thereby spending more time in learning than those who consumed fruits occasionally.

Table 1. Distribution of respondents by socioeconomic characteristics.

Socioeconomic variables	Frequency	Percentage
Age (years)
<20	153	51.0
21–25	100	33.3
>25	47	15.7
Level of study
100–200	153	51.0
300–400	108	36.0
500–600	39	13.0
Sex
Male	104	34.7
Female	196	65.3
Marital status
Single	278	94.9
Married	22	5.1
Monthly income
<10,000	150	50.0
10,000–19,999	70	23.3
20,000–29,999	55	18.3
≥30,000	25	8.4
Monthly expenditure
<2000	135	45.0
2000–3999	60	20.0
4000–5999	40	13.3
6000–7999	35	11.7
8000–9999	28	9.3
≥10,000	2	0.7
Frequency of fruit demand
Daily	120	40.0
Weekly	85	28.3
Occasionally	95	31.7

Determinants of Fruit Demand Among Students of University Of Ibadan

Out of the numerous fruits consumed in Nigeria, the following fruits namely pineapple, orange, banana, pawpaw, apple, cucumber, and watermelon were selected because they are common in the food basket of most Nigerians (Ogundari and Arifalo, 2013). The coefficients of the squared term (λ) of the per capita fruit expenditure were significant in the budget share equations for pineapple, orange, banana, apple, and watermelon (Table 2). This suggested that the response of the demand for these fruit items to increase in expenditure was nonlinear. This unveiled the suitability of the QUAIDS model over the traditional AIDS model.

Table 2. Determinants of demand for some selected fruits among students of University of Ibadan.

Variables	Pineapple	Orange	Banana	Pawpaw	Apple	Cucumber	Watermelon
Constant	0.1234***	0.0409	1.5102***	0.1632***	0.0372	0.3607	−0.9109***
	(0.0617)	(0.0923)	(0.1124)	(0.4990)	(0.6835)	(0.1150)	(0.1150)
Ln Expenditure^2	−0.0102*	−0.0025***	0.0068***	0.0003	−0.0016**	0.0002	−0.0018**
	(0.0006)	(0.0009)	(0.0007)	(0.0005)	(0.0007)	(0.0005)	(0.0008)
Ln expenditure	−0.0025	−0.0693	0.2354***	−0.0039***	−0.0104	−0.0037	−0.1454***
	(0.0196)	(0.0304)	(0.0349)	(0.0150)	(0.2162)	(0.1524)	(0.3647)
Ln price pineapple	0.0421***
	(0.0054)
Ln price orange	−0.0115**	0.0992***
	(0.0056)	(0.1080)
Ln price banana	−0.1619	−0.6917***	0.2705***
	(0.0103)	(0.1640)	(0.0263)
Ln price pawpaw	0.0005	−0.0071	−0.0039	0.3281***
	(0.0035)	(0.0047)	(0.0083)	(0.0045)
Ln price apple	0.0000	−0.0076	−0.3321***	0.0292	0.053***
	(0.0043)	(0.0062)	(0.0119)	(0.0038)	(0.0069)
Ln price cucumber	−0.0008	0.0026	−0.0118	−0.0494	−0.0103***	0.2233***
	(0.0033)	(0.0045)	(0.0868)	(0.382)	(0.0371)	(0.0045)
Ln price watermelon	−0.0142	−0.0411	−0.1362***	−0.0203	−0.0528	0.0053	0.1748***
	(0.0091)	(0.1327)	(0.0187)	(0.0073)	(0.0097)	(0.0074)	(0.0254)
Age	0.0050	0.0028	−0.0002	0.0009*	0.0005	0.0002	−0.0033*
	(0.0007)	(0.0011)	(0.0013)	(0.0005)	(0.0007)	(0.0005)	(0.0038)
Sex	−0.0040	−0.0086	0.0031	0.0022	−0.0044	−0.0004	0.0148*
	(0.0038)	(0.0060)	(0.0081)	(0.0042)	(0.0028)	(0.0083)	(0.0051)
Marital status	−0.0004	0.0006	−0.0010	−0.0012	0.0002	−0.0001	0.0008
	(0.0005)	(0.0009)	(0.0011)	(0.0004)	(0.0006)	(0.0004)	(0.0008)
Income	0.0148	0.0414*	0.0312	0.0162	−0.0460***	0.0793	−0.0302
	(0.0145)	(0.0023)	(0.0023)	(0.0107)	(0.0016)	(0.1070)	(0.0272)

***, ** and * represent significance level at 1%, 5% and 10%, respectively.

²Signifies  square of natural log of expenditure.

Further, the budget shares for pineapple, orange, banana, pawpaw, apple, cucumber, and watermelon were significantly and positively influenced by their own prices (Table 2). The result indicated that a unit increase in the price of each of the selected fruits caused an increase in their respective budget shares. An increase in the price of banana caused a decrease in the budget shares for orange and apple, thereby suggesting a complementary relationship among them. Further, age had positive and negative influence on budget shares of pawpaw and watermelon, respectively. This indicated that older students demanded more of pawpaw, while the younger ones demanded more of watermelon. This may be due to differences in preferences and tastes. Sex had a positive influence on watermelon budget share suggesting that female students demanded more of watermelon than their male counterparts. This agreed with the findings of Adenegan and Adeoye (2011) and Layade and Adeoye (2014) that sex is a key determinant of fruit demand among students of tertiary institutions in Oyo state, Nigeria.

Furthermore, student income (stipend) had a positive relationship with the budget share for orange and a negative influence on the demand for apple. This implied that an increase in student’s income increased the demand for orange but reduced the demand for apples. The reason could be that students preferred locally grown fruits to the imported ones (such as apple) owing to their meager stipend.

Expenditure Elasticities of Demand for Selected Fruits Among Students

Expenditure elasticity captures the percentage change in the quantity demanded of a good with respect to a percentage change in total expenditure (Tomek and Robinson, 2003). The expenditure elasticities are reported in the context of economic theory, where an expenditure elasticity in the range of 0 and 1 signifies a commodity to be a “necessary good,” greater than 1 implies a “luxury good,” and less than 0 (negative) implies an “inferior good” (Adegeye and Dittoh, 1985). As shown in Table 3, the expenditure elasticities for pineapple (1.30), orange (1.21), banana (1.07), pawpaw (1.38), apple (1.19), and cucumber (1.16) indicated that they were luxury goods; suggesting that expenditure increased with demand for these fruits at a higher rate than the increase in expenditure. This is consistent with the findings of Musyoka et al. (2010) that fruit expenditure elasticity was greater than one in Kenya. On the other hand, the expenditure elasticity for watermelon was less than 1 (0.67) indicating that watermelon was a necessity good. Thus, 1% increase in students’ income/stipend led to a less than proportionate increase (0.67%) in the quantity demanded of water melon by the students.

Table 3. Expenditure, own and cross-price elasticities of demand for selected fruits.

Variable	Pineapple	Orange	Banana	Pawpaw	Apple	Cucumber	Watermelon
Expenditure elasticities	1.30	1.21	1.07	1.38	1.19	1.16	0.67
Uncompensated/Marshallian elasticities
Pineapple	−0.4305	0.0392	−0.0984	−0.0046	0.1278	0.0082	0.3583
Orange	0.0147	−0.3193	−0.0744	−0.0209	0.0584	0.0024	0.3391
Banana	−0.0260	−0.0399	−0.1444	−0.0428	−0.0189	−0.0247	0.2916
Pawpaw	0.0057	−0.1253	−0.4086	0.3696	0.1030	−0.1374	0.2044
Apple	0.0642	0.0744	−0.0492	0.0175	−0.3554	−0.0217	0.2701
Cucumber	0.0267	0.0237	−0.2425	−0.1453	−0.1218	−0.0009	0.4600
Watermelon	0.0663	0.1561	0.2197	0.0150	0.1027	0.0325	−0.5924
Compensated/Hicksian elasticities
Pineapple	−0.5215	−0.1858	−0.3915	−0.0381	−0.0544	−0.0235	−0.0890
Orange	−0.0698	−0.5281	−0.3464	−0.0520	−0.1108	−0.0270	−0.0761
Banana	−0.0960	−0.2252	−0.3858	−0.0704	−0.1690	−0.0507	−0.0769
Pawpaw	−0.1019	−0.3629	−0.7182	0.3343	−0.0896	−0.1709	−0.2682
Apple	0.0187	−0.1304	−0.3160	−0.0129	−0.5213	−0.0506	−0.1371
Cucumber	−0.0545	−0.1767	−0.5036	−0.1751	−0.2842	−0.00291	0.0615
Watermelon	0.0197	0.0409	0.0696	0.0021	0.0093	0.0163	−0.8216

Bold values are own-price elasticity.

Uncompensated and Compensated Own-Price Elasticity of Demand

The uncompensated demand also known as the Marshallian demand represents the conventional market or individual demand. Marshallian demand implicitly combines both income and substitution effects and in this case, income is held constant. An alternative approach to demand is the compensated or Hicksian demand which compensates a consumer for price change. That is, when the price changes, consumers receive compensation that allows them to remain on their original indifference curve. Generally, Marshallian estimates provide better measure of the responsiveness for any particular good to changes in its own price than to the changes in the price of other goods (Alam, 2011). The Hicksian elasticities provide better estimates of substitution effects between two food categories, devoid of the income effect (Bundi et al., 2013).

Both compensated and uncompensated own-price elasticity estimates in the diagonal matrix for most of the fruits (except pawpaw) had expected negative signs except for pawpaw (Table 3). This implied that the prices of each of the selected fruits had inverse relationship with their demand. This is consistent with economic theory (law of demand) which states that all things being equal, the higher the price of a commodity, the lower the quantity demanded and vice versa. However, own-price elasticity for pawpaw was positive (0.3696) indicating that it was a “giffen” good. The implication of this was that demand for pawpaw would decrease with a decrease in own price. Furthermore, the own-price elasticity of demand for pineapple, orange, banana, pawpaw, apple, cucumber, and watermelon was less than 1 (in absolute terms) indicating that they were price inelastic. This implied that demand for these fruits was less responsive to changes in own price.

Uncompensated and Compensated Cross-Price Elasticity of Demand

Positive cross-price elasticity indicates substitutability implying that an increase in the price of fruit commodity i increases the quantity demanded of fruit j, while negative cross-price elasticity indicates complementary relationship implying that an increase in the price of fruit i decreases the quantity demanded of fruit j. Results revealed that the uncompensated cross-price elasticity estimates were mostly positive (Table 3), indicating substitution relationship among the fruits for example, pineapple and apple (0.1278) and cucumber and watermelon (0.4600). On the other hand, compensated cross-price elasticity estimates revealed complementary relationship among the fruits. For example, pineapple and orange (−0.1858) and orange and banana (−0.3464) complemented one another. Finally, watermelon behaved as a substitute to all other fruits, suggesting that an increase in the price of watermelon would increase the demand for the other fruits.

Conclusion and Recommendation

The study assessed the demand for selected fruits (pineapple, orange, banana, pawpaw, apple, cucumber, and watermelon) among students of university of Ibadan, Nigeria. Less than half of the sampled students consumed fruits on daily basis suggesting that their consumption fell below the WHO recommendation. There is therefore the need to promote awareness on the importance of adequate consumption of fruits among the students. Own-prices, age, sex, and income significantly influenced students’ demand for fruits. Reduction in prices of fruits and increase in students’ income/stipends could enhance the consumption of fruits among students. Most of the fruits were expenditure elastic (luxury goods) but price-inelastic; therefore, a combination of income and price policies would have a positive effect on students’ demand for the selected fruits. Measures to boost production of these commodities, reduce their prices, and enhance students’ stipends are therefore recommended.