- Email: [email protected]
Consumption of dairy products in the UAE: A comparison of nationals and expatriates
Journal of the Saudi Society of Agricultural Sciences (2011) 10, 121–125
King Saud University
Journal of the Saudi Society of Agricultural Sciences www.ksu.edu.sa www.sciencedirect.com
ORIGINAL ARTICLE
Consumption of dairy products in the UAE: A comparison of nationals and expatriates q Kamaleldin Ali Bashir Department of Agricultural Economics, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia Received 15 June 2010; accepted 24 April 2011 Available online 17 May 2011
KEYWORDS Consumption; Dairy products; Income; Expenditure elasticity; Marketing
Abstract The variables: age, income, education, number of children, and a dichotomous dummy variable for nationality were used to explain the consumption behavior of dairy products: fresh milk, butter, cheese, yoghurt, powdered milk, condensed milk, cream, and ice cream in the urban centers of Al-ain, Dubai, and Abu Dhabi. Results suggest different determinants for consumption behaviors of nationals and expatriates as well as different determinants along the income range of the sample. Estimates for the expenditure elasticity were relatively higher for lower income groups when unreported income is taken into consideration in interpreting the results. Differences in consumption behavior bear an important implication to marketing and promotion of dairy products: different strategies that incorporate the different consumption determinants are perhaps necessary for the different ethnic groups. ª 2011 King Saud University. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
q This work was financially supported by the Research Affairs at the UAE University under Contract No. 03-03-6-11/03. I appreciate comments by two anonymous reviewers as well as the efforts of Mr. Shallal Musa Shallal who conducted the field survey. E-mail address: [email protected]
1658-077X ª 2011 King Saud University. Production and hosting by Elsevier B.V. All rights reserved. Peer review under responsibility of King Saud University. doi:10.1016/j.jssas.2011.04.002
Production and hosting by Elsevier
Consumption of dairy products (milk, laban (butter milk), cheese, powdered milk, cream, ice cream, yogurt, and butter) in the GCC countries has grown at an average rate of 4% during the 90’s and the UAE with 15% of the region’s consumption leads other countries in per capita share (O’brien, 1998). Dairy products have been a major component of the UAE diet since prehistoric times (Iddison, 1999). A higher income level may have contributed to increased consumption and variety but little may have changed in consumption patterns through the years. The theory of demand uses price as a major predictor of consumption and a typical demand study will report price elasticities (Deaton and Muellbauer, 1980; Johnson et al., 1992; Sapsford and Morgan, 1994). However in countries with high income levels, such as the UAE, non-price factors play a major role in allocating products. According to the UAE’s Ministry
122
K.A. Bashir
of Economy (2010), the price of most dairy products changed by less than 3% during 2008, only laban and some types of cheese changed by 5–8%. With such changes, cross-sectional consumption data would not warrant inclusion of prices as independent variables. The consumers’ tastes and preferences become more pronounced as affluence increases and hence variables, such as demographics, education, and ethnicity have more influence on demand. In this study a survey was conducted to elicit information to analyze and understand some aspects of UAE consumers’ behavior and to estimate expenditure elasticities for the above major dairy products for different income levels; possible differences between nationals and expatriates will also be highlighted.
likely because of multicollinearity problems. It is expected that education, income, and age are correlated. One variable that was expected to explain expenditure on dairy products in general and on milk in particular was the number of children between the age of 2 and 3 years. However, the variable (child) which represents the number of (all) children was found to do a better job and hence was included instead.
2. Methodology
ESij ¼ b0j þ b1j Agei þ b2j Educationi þ b3j ln Incomei
4. The regression model A linear expenditure specification is utilized to explain the consumers’ expenditure on dairy products. The specified equations were estimated through regression techniques, namely OLS. The equations are defined as follows:
þ b4j childi þ b5j D þ eij The research methods involved conducting a survey to collect household consumption data on a random sample of supermarket shoppers. Descriptive statistics were then used to decipher consumer characteristics. A statistical model of linear expenditure equations was defined for the main dairy products; the model was estimated using ordinary least squares (OLS). 3. The data The sample included 212 households from the three major urban centers of Abu Dhabi, Dubai, and Al-ain. Consumers were intercepted at random and interviewed at selected major supermarkets in the three cities. About 58% of respondents were from Al-ain, 29% from Abu Dhabi, and 13% from Dubai. Nationals represented about 24% of the sample while expatriates represented 76%, a distribution that closely mimics that of the country’s population. As is the case with households’ on-the-spot surveys, there are issues of memory bias. When households’ leaders are asked about expenditures, quantities, and frequencies they could easily under/over-estimate. Since the surveys are on the spot, enumerators will sometime talk to a ‘‘chance’’ shopper and not the person who usually does the shopping who might have a better idea on the household consumption habits. As for milk and some other dairy products, when applicable, no attention was paid to fat contents; previous surveys reveal that less than 1 in 5 Emiratis consume low or no fat milk (Badrinath et al., 2002). The education levels of the participants are relatively high where: 21% had a secondary school degree, 46% a university degree, and 29% a post university degree. Table 1 shows the means and the distribution of some variables including consumers’ expenditure on different dairy products and frequency of consumption. A quick glance at the means and standard deviation values reveals the high relative dispersion of the data. The correlation matrix of selected variables is shown in Table 2. The correlation coefficients were generally low to moderately high (<0.50), but were for the most part significant at the conventional levels of significance. The variables age, income, education, and number of children were the ones that showed potential as explanatory variables for the dependent variable, expenditure. Education, however, does not seem to be highly or significantly related to expenditure and that is
ð1Þ
where: ESij, the dependent variable, is the expenditure share of the jth dairy product in the income of the ith household. The Beta’s are regression coefficients associated with the jth dairy product. The explanatory variables: age, education, income, child, and D are as defined in Table 1. ejj is the regression error term assumed to satisfy the classical assumptions of OLS. Elasticity of expenditure (gj ) for expatriates and nationals at the two income categories of low and high shall be calculated using this formula: b3j gj ¼ 1 þ ESj where the bar over ESj indicates the mean value of expenditure shares. Eq. (1) was estimated for six dairy products, namely fresh milk, yoghurt, condensed milk, powdered milk, cheese, and ice cream; additionally the equation was also estimated for dairy products as an aggregate. The equation was estimated for the whole sample, and for certain income strata of interest in the sample. In a country like the UAE, where there is a diverse group of ethnicities, perceivably with different consumption habits, it is interesting to see if Eq. (1) will behave differently for different ethnic groups/nationalities. Therefore, the dummy variable (D) was included in the equation to gauge any difference between the two groups: nationals and expatriates, for selected dairy products. By its design the dummy variable gives the differential impact of expatriates over nationals on expenditure shares. 5. Results and discussion Table 3 shows the OLS estimation results for dairy products as a group and for six individual dairy products. All seven equations were statistically highly significant as indicated by the significance levels under the F-values. One equation, namely that of milk was particularly better in terms of explanatory power as indicated by the R2 value of (0.41); for the other equation R2 ranged between (0.20) for ice cream and (0.26) for dairy, condensed milk, and cheese.
Consumption of dairy products in the UAE: A comparison of nationals and expatriates Table 1
123
Descriptive statistics of selected variables (N = 212).
Variable label
Variable name
Minimum
Maximum
Mean
Std. deviation
Age of household leader in years Weekly expenditure on butter in AED Weekly expenditure on cheese in AED Number of children Weekly expenditure on condensed milk in AED Weekly expenditure on cream in AED Total weekly expenditure on dairy products Weekly expenditure on ghee in AED Weekly expenditure on ice cream in AED Monthly income in thousand AED Weekly expenditure on laban in AED Weekly expenditure on milk in AED Weekly expenditure on powdered milk in AED Weekly expenditure on yoghurt in AED Frequency of milk consumption per week Frequency of laban consumption per week Frequency of cheese consumption per week Frequency of butter consumption per week Frequency of yoghurt consumption per week Dummy for nationality (expatriates=1, nationals =0)
Age Butter Cheese Child Cond. milk Cream Dairy Ghee Ice cream Income Laban Milk Powd. milk Yoghurt Milk freq. Laban freq. Cheese freq. Butter freq. Yog. freq. D
18 0 0 0 0 0 12.00 0 0 0 0 0 0 0 0 0 0 0 0 0
65 350 300 7 100 140 745.00 290 270 20 150 250 100 80 8 7 7 12 7 1
37.70 12.44 21.90 1.77 6.61 10.50 147.26 16.27 8.53 8.12 13.21 28.06 17.57 12.63 5.71 3.13 4.26 2.72 4.23 0.23
10.01 27.74 27.69 1.73 12.48 13.61 107.32 26.75 20.26 4.26 18.21 23.75 14.82 12.10 2.012 2.63 2.12 2.32 2.52 0.43
Table 2
Pearson’s correlation matrix of selected variables.
Variable
Age
Age Income Education Child Milk Yoghurt Powd. milk Cheese Butter D *
1
Income **
0.469 1
Education **
Child *
0.276 0.444** 1
0.149 0.124 0.069 1
Milk
Yoghurt
0.133 0.240** 0.078 0.297** 1
**
0.179 0.194** 0.089 0.327** 0.290** 1
Powd. milk
Cheese
Butter
D
**
0.115 0.067 0.054 0.170* 0.381** 0.459** 0.221** 1
0.128 0.243** 0.083 0.043 0.024 0.023 0.034 0.010 1
0.155* 0.217** 0.254** 0.061 0.190** 0.173* 0.066 0.078 0.059 1
0.181 0.157* 0.109 0.281** 0.119 0.468** 1
Correlation is significant at the 0.05 level (2-tailed). Correlation is significant at the 0.01 level (2-tailed).
**
Table 3
OLS estimates for expenditure equations for various dairy products.
Dependent variable
Constant
Age
Education
Income
Child
D
Dairy Milk Yoghurt Cond. milk Powd. milk Cheese Ice cream
25.829 (0.000)a 0.006 (0.976) 3.000 (0.000) *** 2.595 (0.000) *** 3.600 (0.000) *** 5.541 (0.000) *** 10.398 (0.000) ***
0.398 (0.000) *** 0.005 (0.156) 0.045 (0.001) *** 0.038 (0.000) *** 0.055(0.001) *** 0.086 (0.000) *** 0.150 (0.001) ***
5.200 (0.000) *** 0.109 (0.006)** 0. 594 (0.000) *** 0. 498 (0.000) *** 0.705 (0.000) *** 1.095 (0.000) *** 1.918 (0.000) ***
13.877 (0.000) *** 0.057 (0.000)*** 1.541 (0.000) *** 1.298 (0.000) *** 1.802 (0.000) *** 3.005 (0.000) *** 4.534 (0.000) ***
0.490 (0.389) 0.050 (0.004)** 0.050 (0.444) -.057 (0.291) -.055 (0.506) 0.099 (0.420) 0. 243 (0.285)
6.802 0.225 0.699 0.724 0.710 1.351 1.932
a * ** ***
(0.006) ** (0.003)** (0.015) * (0.002) ** (0.051) (0.012) * (0.052)
R2
F
0.26 0.43 0.23 0.26 0.22 0.26 0.20
14.589 (0.000) *** 30.772 (0.000)*** 13. 63 (0.000) *** 14.32 (0.000) *** 11.66 (0.000) *** 14.269 (0.000) *** 10.236 (0.000) ***
Numbers between parentheses are p-values. Coefficient is significant at the 0.05 level. Coefficient is significant at the 0.01 level. Coefficient is significant at the 0.001 level.
The coefficients for the variables: age, income, and education were highly significant in all six equations with minor
exceptions such as the variable age in the milk equation. Both age and education were positively related to expenditure as
124
K.A. Bashir tions: while it was about 0.62 for the yogurt, condensed milk, powdered milk, cheese, and ice cream low income equations, it ranged between 0.02 and 0.19 for the same equations at higher income levels. It is, therefore, evident that the same set of explanatory variables did a much better job in explaining consumers’ expenditure of dairy products at lower incomes than at higher incomes. As the low–high income demarcations could likely reflect expatriate–national demarcations, then one could attribute the R2 differences to different consumption habits that could reflect cultural differences. This finding echoes the results for the dummy variable in Table 3, and it bears an important implication to marketing and promotion of dairy products: different strategies are perhaps necessary for the different ethnic groups. In light of the rather low R2 values for the low income group, an in depth analysis would be needed to determine those other specific factors which explain consumers’ expenditure decisions. As for the significance of the explanatory variables across the low–high income equations, almost all variables were not significant for both the low and high income subsets in the dairy equation. However, results were mixed for the six dairy products. Generally, age, education, and income seem to be good determinants of expenditure for the low income group while income and number of children are more important determinants for the high income groups. It appears that some interaction exists between sets of the variables: age, education, and income; for instance older age could indicate more income and more education over some range of these variables. However, inclusion of such interaction terms did not prove to add the significance of the results and as such they were not shown in the final results of Tables 3 and 4. Estimates of expenditure elasticities for the different income and ethnic groups are shown in Table 5. Elasticities were generally close to unity for most product categories in the ‘‘all’’ and the ‘‘high income’’ subsets; for the ‘‘low income’’ subset elasticities ranged between (0.36) for cheese and (0.95) for milk aside from the negative value (0.36) for ice cream. It appears that, counter to expectations, the elasticities for the high income groups are relatively higher. This could be due to exclusion of some relevant explanatory variables in the low income equations. However, upon further investigation,
would be expected. The variable, child, was significant with a positive sign for only the milk equation probably due to the fact that children are generally expected to consume milk more readily than other dairy products. Moreover, advertisements and promotional campaigns are more focused on milk as a good source of calcium and vitamin D for children. It is generally expected that children in the age group 2–5 years are more dependent on milk, however, a variable representing this age group (number of children between 2 and 5 years) was not significant in all equations and was not included in the final results. The coefficient of income was negative and highly significant for all equations in Table 3. This indicates that at higher levels of income the share of dairy products in consumers’ income will decrease. In general, this is expected at relatively higher levels of income. The sample has a mean monthly income level of about AED 8000, a relatively high figure which explains the negative income coefficients. Therefore, it was of interest to see the income coefficient for lower income levels. Table 4 shows estimation results for the same equations in Table 3 at two levels of income for each equation; so for milk, for instance, the equation was estimated for low income (62000 AED/month) and for high income (>2000 AED/ month) households. With a few exceptions, all equations were significant at better than conventional significance levels. The coefficient of income maintained its negative signs at lower income levels. This could mean that even at lower income levels, households are approaching their sufficiency levels and have good access to dairy products. As such the dairy industry may not benefit, in terms of sales, from subsequent income raises in UAE; therefore, more direct efforts through advertising and promotions are necessary to realize that end. The coefficient of the dummy variable, D was positive and significant at the (0.05) level or higher for all equations except the powdered milk and ice cream equations where it was virtually significant at the (0.05) level. This variable measures the differential impact on expenditure shares of expatriates over nationals and as such results indicate higher reservation level of expenditure (intercept) for expatriates. The values of the coefficient of determination (R2) in Table 4 are generally much higher for low than high income equa-
Table 4
OLS estimates for expenditure equations at different income levels.
Dependent variable a
Dairy (I < 2k) Dairy (I > 2k) Milk (I < 2k) Milk (I > 2k) Yoghurt (I < 2k) Yoghurt (I > 2k) Cond. milk (I < 2k) Cond. milk (I > 2k) Powd. milk (I < 2k) Powd. milk (I > 2k) Cheese (I < 2k) Cheese (I > 2k) Ice cream (I < 2k) Ice cream (I > 2k) a b
Constant
Age b
0.361 (0.015) 0.078 (0.337) 0.59 (0.208) 0.024 (0.000) 0.111 (0.448) 0.014 (0.000) 0.155 (0.218) 0.003 (0.177) 0.053 (0.771) 0.022 (0.000) 0.334 (0.254) 0.024 (0.000) 0.204 (0.680) 0.008 (0.000)
0.000 0.000 0.000 0.000 0.004 0.000 0.003 0.000 0.005 0.000 0.007 0.000 0.014 0.000
(0.907) (0.585) (0.420) (0.944) (0.004) (0.590) (0.007) (0.561) (0.003) (0.479) (0.005) (0.407) (0.002) (0.120)
Education
Income
0.022 0.016 0.004 0.000 0.026 0.000 0.018 0.000 0.037 0.000 0.042 0.000 0.094 0.000
0.024 0.002 0.010 0.002 0.040 0.001 0.039 0.000 0.041 0.002 0.089 0.002 0.118 0.001
(0.061) (0.006) (0.258) (0.365) (0.050) (0.796) (0.096) (0.025) (0.030) (0.973) (0.102) (0.336) (0.040) (0.483)
(I < 2k) ” income 6 2000 AED/month; (I > 2k) ” income > 2000 AED/month Numbers between parentheses are p-values.
Child (0.142) (0.823) (0.088) (0.000) (0.040) (0.000) (0.019) (0.636) (0.084) (0.000) (0.023) (0.000) (0.066) (0.002)
0.005 0.002 0.002 0.000 0.001 0.000 0.001 0.000 0.002 0.000 0.001 0.000 0.006 0.000
(0.330) (0.414) (0.344) (0.000) (0.815) (0.000) (0.850) (0.218) (0.785) (0.000) (0.911) (0.041) (0.750) (0.000)
R2
F
0.170 0.037 0.225 0.204 0.625 0.178 0.615 0.022 0.625 0.191 0.62 0.120 0.629 0.134
1.817 2.866 2.165 13.882 7.678 11.493 7.381 2.095 7.671 12.426 7.326 7.640 7.791 8.534
(0.190) (0.025) (0.135) (0.000) (0.003) (0.000) (0.003) (0.083) (0.003) (0.000) (0.004) (0.000) (0.002) (0.000)
Consumption of dairy products in the UAE: A comparison of nationals and expatriates Table 5 Expenditure elasticities for different income and ethnic groups. Variable
All
Low income High Nationals Expatriates income
Dairy Milk Yoghurt Cond. milk Powd. milk Cheese Ice cream
0.96 0.99 0.95 0.94 0.96 0.95 0.92
0.77 0.95 0.62 0.38 0.66 0.35 0.36
a
0.99 0.99 0.99 1.00 0.98 0.99 0.98
0.23 –a – – – – 1.08
0.56 – – – – – 0.74
Results for these equations did not warrant useful comparisons.
it turned out that the average income for the expatriates’ subset of the sample was relatively higher than that of the national subset. Conceivably national are eligible to additional sources of unreported income such as the various types of government assistance and grants. In surveys, respondents tend to interpret income as monthly salary and as such it is more likely that the reality is counter to what appears in the sample: nationals’ income is more likely higher than expatriates’, on average. Consequently, the ‘‘low income’’–‘‘high income’’ columns in Table 5 may actually be reversed if additional unreported income is taken into consideration. The elasticity estimates for dairy were 0.23 for nationals and 0.56 for expatriates which could be attributable to differences in income levels (the estimates are comparable to previous studies (El-Eraky and Al-Muhairi, 2004). 6. Conclusions In this study the consumption behavior for dairy products was investigated. Products examined included: fresh milk, yoghurt, butter, cheese, ice cream, cream, and condensed and powdered milk in the major urban centers of Al-ain, Dubai, and Abu Dhabi. Linear expenditure equations along different income and ethnic groups were estimated. All estimated equations were statistically significant. However, the explanatory power of some was particularly low,
125
namely the equations for the high income subset of the sample. This suggests that some important variables may have been omitted. Possible candidates include: expenditure on other drinks such as juices, and additional income for nationals. The study detected significant differences in consumption behavior between the nationals and expatriates subsets of the sample. An important implication here is that marketing endeavors should bear such differences in mind and that different marketing strategies need to be devised for these subsets. Moreover, culture-specific factors should be included in future studies to explain consumption behavior. Expenditure elasticity estimates for the ‘‘low’’ and ‘‘high’’ income subsets were relatively higher for the ‘‘high’’ than the ‘‘low’’ income subsets. While this is apparently counter to expectations, yet when viewed in light of expected actual rather than reported income these results seem sensible.
References Badrinath, P., Al-Shboul, Q.A., Zoubeidi, T., Gargoum, A.S., Ghubash, R., El-Rufaie, O.E. (Eds.), 2002. Measuring the Health of the nation: United Arab Emirates Health and Lifestyle Survey 2000. Faculty of Medicine and Health Sciences and College of Business and Economics, UAE University, Al-ain, UAE. Deaton, A., Muellbauer, J., 1980. American Economic Review 70, 312–326. El-Eraky, M., Al-Muhairi, T., 2004. Consumer demand for food in the United Arab Emirates: a pilot study. In: Proceedings of the Fifth Annual UAE University Research Conference, vol. 2, UAE University, Al-ain, UAE. Iddison, P., 1999. Dairy food in the UAE. Available from:, a paper presented at the Oxford University Symposium. Johnson, S.R., Stonehouse, P., Hassan, Z. (Eds.), 1992. Market Demand for Dairy Products. Iowa State University Press, Ames, IA. Ministry of Economy, UAE, 2010. Available from: , downloaded. O’brien, K., 1998. Key features of dairy consumption in the six GCC countries. Gulf Marketing Review. Sapsford, D., Morgan, W. (Eds.), 1994. The Economics of Primary Commodities: Models, Analysis and Policy. Elgar, Aldershot, UK.
King Saud University
Journal of the Saudi Society of Agricultural Sciences www.ksu.edu.sa www.sciencedirect.com
ORIGINAL ARTICLE
Consumption of dairy products in the UAE: A comparison of nationals and expatriates q Kamaleldin Ali Bashir Department of Agricultural Economics, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia Received 15 June 2010; accepted 24 April 2011 Available online 17 May 2011
KEYWORDS Consumption; Dairy products; Income; Expenditure elasticity; Marketing
Abstract The variables: age, income, education, number of children, and a dichotomous dummy variable for nationality were used to explain the consumption behavior of dairy products: fresh milk, butter, cheese, yoghurt, powdered milk, condensed milk, cream, and ice cream in the urban centers of Al-ain, Dubai, and Abu Dhabi. Results suggest different determinants for consumption behaviors of nationals and expatriates as well as different determinants along the income range of the sample. Estimates for the expenditure elasticity were relatively higher for lower income groups when unreported income is taken into consideration in interpreting the results. Differences in consumption behavior bear an important implication to marketing and promotion of dairy products: different strategies that incorporate the different consumption determinants are perhaps necessary for the different ethnic groups. ª 2011 King Saud University. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
q This work was financially supported by the Research Affairs at the UAE University under Contract No. 03-03-6-11/03. I appreciate comments by two anonymous reviewers as well as the efforts of Mr. Shallal Musa Shallal who conducted the field survey. E-mail address: [email protected]
1658-077X ª 2011 King Saud University. Production and hosting by Elsevier B.V. All rights reserved. Peer review under responsibility of King Saud University. doi:10.1016/j.jssas.2011.04.002
Production and hosting by Elsevier
Consumption of dairy products (milk, laban (butter milk), cheese, powdered milk, cream, ice cream, yogurt, and butter) in the GCC countries has grown at an average rate of 4% during the 90’s and the UAE with 15% of the region’s consumption leads other countries in per capita share (O’brien, 1998). Dairy products have been a major component of the UAE diet since prehistoric times (Iddison, 1999). A higher income level may have contributed to increased consumption and variety but little may have changed in consumption patterns through the years. The theory of demand uses price as a major predictor of consumption and a typical demand study will report price elasticities (Deaton and Muellbauer, 1980; Johnson et al., 1992; Sapsford and Morgan, 1994). However in countries with high income levels, such as the UAE, non-price factors play a major role in allocating products. According to the UAE’s Ministry
122
K.A. Bashir
of Economy (2010), the price of most dairy products changed by less than 3% during 2008, only laban and some types of cheese changed by 5–8%. With such changes, cross-sectional consumption data would not warrant inclusion of prices as independent variables. The consumers’ tastes and preferences become more pronounced as affluence increases and hence variables, such as demographics, education, and ethnicity have more influence on demand. In this study a survey was conducted to elicit information to analyze and understand some aspects of UAE consumers’ behavior and to estimate expenditure elasticities for the above major dairy products for different income levels; possible differences between nationals and expatriates will also be highlighted.
likely because of multicollinearity problems. It is expected that education, income, and age are correlated. One variable that was expected to explain expenditure on dairy products in general and on milk in particular was the number of children between the age of 2 and 3 years. However, the variable (child) which represents the number of (all) children was found to do a better job and hence was included instead.
2. Methodology
ESij ¼ b0j þ b1j Agei þ b2j Educationi þ b3j ln Incomei
4. The regression model A linear expenditure specification is utilized to explain the consumers’ expenditure on dairy products. The specified equations were estimated through regression techniques, namely OLS. The equations are defined as follows:
þ b4j childi þ b5j D þ eij The research methods involved conducting a survey to collect household consumption data on a random sample of supermarket shoppers. Descriptive statistics were then used to decipher consumer characteristics. A statistical model of linear expenditure equations was defined for the main dairy products; the model was estimated using ordinary least squares (OLS). 3. The data The sample included 212 households from the three major urban centers of Abu Dhabi, Dubai, and Al-ain. Consumers were intercepted at random and interviewed at selected major supermarkets in the three cities. About 58% of respondents were from Al-ain, 29% from Abu Dhabi, and 13% from Dubai. Nationals represented about 24% of the sample while expatriates represented 76%, a distribution that closely mimics that of the country’s population. As is the case with households’ on-the-spot surveys, there are issues of memory bias. When households’ leaders are asked about expenditures, quantities, and frequencies they could easily under/over-estimate. Since the surveys are on the spot, enumerators will sometime talk to a ‘‘chance’’ shopper and not the person who usually does the shopping who might have a better idea on the household consumption habits. As for milk and some other dairy products, when applicable, no attention was paid to fat contents; previous surveys reveal that less than 1 in 5 Emiratis consume low or no fat milk (Badrinath et al., 2002). The education levels of the participants are relatively high where: 21% had a secondary school degree, 46% a university degree, and 29% a post university degree. Table 1 shows the means and the distribution of some variables including consumers’ expenditure on different dairy products and frequency of consumption. A quick glance at the means and standard deviation values reveals the high relative dispersion of the data. The correlation matrix of selected variables is shown in Table 2. The correlation coefficients were generally low to moderately high (<0.50), but were for the most part significant at the conventional levels of significance. The variables age, income, education, and number of children were the ones that showed potential as explanatory variables for the dependent variable, expenditure. Education, however, does not seem to be highly or significantly related to expenditure and that is
ð1Þ
where: ESij, the dependent variable, is the expenditure share of the jth dairy product in the income of the ith household. The Beta’s are regression coefficients associated with the jth dairy product. The explanatory variables: age, education, income, child, and D are as defined in Table 1. ejj is the regression error term assumed to satisfy the classical assumptions of OLS. Elasticity of expenditure (gj ) for expatriates and nationals at the two income categories of low and high shall be calculated using this formula: b3j gj ¼ 1 þ ESj where the bar over ESj indicates the mean value of expenditure shares. Eq. (1) was estimated for six dairy products, namely fresh milk, yoghurt, condensed milk, powdered milk, cheese, and ice cream; additionally the equation was also estimated for dairy products as an aggregate. The equation was estimated for the whole sample, and for certain income strata of interest in the sample. In a country like the UAE, where there is a diverse group of ethnicities, perceivably with different consumption habits, it is interesting to see if Eq. (1) will behave differently for different ethnic groups/nationalities. Therefore, the dummy variable (D) was included in the equation to gauge any difference between the two groups: nationals and expatriates, for selected dairy products. By its design the dummy variable gives the differential impact of expatriates over nationals on expenditure shares. 5. Results and discussion Table 3 shows the OLS estimation results for dairy products as a group and for six individual dairy products. All seven equations were statistically highly significant as indicated by the significance levels under the F-values. One equation, namely that of milk was particularly better in terms of explanatory power as indicated by the R2 value of (0.41); for the other equation R2 ranged between (0.20) for ice cream and (0.26) for dairy, condensed milk, and cheese.
Consumption of dairy products in the UAE: A comparison of nationals and expatriates Table 1
123
Descriptive statistics of selected variables (N = 212).
Variable label
Variable name
Minimum
Maximum
Mean
Std. deviation
Age of household leader in years Weekly expenditure on butter in AED Weekly expenditure on cheese in AED Number of children Weekly expenditure on condensed milk in AED Weekly expenditure on cream in AED Total weekly expenditure on dairy products Weekly expenditure on ghee in AED Weekly expenditure on ice cream in AED Monthly income in thousand AED Weekly expenditure on laban in AED Weekly expenditure on milk in AED Weekly expenditure on powdered milk in AED Weekly expenditure on yoghurt in AED Frequency of milk consumption per week Frequency of laban consumption per week Frequency of cheese consumption per week Frequency of butter consumption per week Frequency of yoghurt consumption per week Dummy for nationality (expatriates=1, nationals =0)
Age Butter Cheese Child Cond. milk Cream Dairy Ghee Ice cream Income Laban Milk Powd. milk Yoghurt Milk freq. Laban freq. Cheese freq. Butter freq. Yog. freq. D
18 0 0 0 0 0 12.00 0 0 0 0 0 0 0 0 0 0 0 0 0
65 350 300 7 100 140 745.00 290 270 20 150 250 100 80 8 7 7 12 7 1
37.70 12.44 21.90 1.77 6.61 10.50 147.26 16.27 8.53 8.12 13.21 28.06 17.57 12.63 5.71 3.13 4.26 2.72 4.23 0.23
10.01 27.74 27.69 1.73 12.48 13.61 107.32 26.75 20.26 4.26 18.21 23.75 14.82 12.10 2.012 2.63 2.12 2.32 2.52 0.43
Table 2
Pearson’s correlation matrix of selected variables.
Variable
Age
Age Income Education Child Milk Yoghurt Powd. milk Cheese Butter D *
1
Income **
0.469 1
Education **
Child *
0.276 0.444** 1
0.149 0.124 0.069 1
Milk
Yoghurt
0.133 0.240** 0.078 0.297** 1
**
0.179 0.194** 0.089 0.327** 0.290** 1
Powd. milk
Cheese
Butter
D
**
0.115 0.067 0.054 0.170* 0.381** 0.459** 0.221** 1
0.128 0.243** 0.083 0.043 0.024 0.023 0.034 0.010 1
0.155* 0.217** 0.254** 0.061 0.190** 0.173* 0.066 0.078 0.059 1
0.181 0.157* 0.109 0.281** 0.119 0.468** 1
Correlation is significant at the 0.05 level (2-tailed). Correlation is significant at the 0.01 level (2-tailed).
**
Table 3
OLS estimates for expenditure equations for various dairy products.
Dependent variable
Constant
Age
Education
Income
Child
D
Dairy Milk Yoghurt Cond. milk Powd. milk Cheese Ice cream
25.829 (0.000)a 0.006 (0.976) 3.000 (0.000) *** 2.595 (0.000) *** 3.600 (0.000) *** 5.541 (0.000) *** 10.398 (0.000) ***
0.398 (0.000) *** 0.005 (0.156) 0.045 (0.001) *** 0.038 (0.000) *** 0.055(0.001) *** 0.086 (0.000) *** 0.150 (0.001) ***
5.200 (0.000) *** 0.109 (0.006)** 0. 594 (0.000) *** 0. 498 (0.000) *** 0.705 (0.000) *** 1.095 (0.000) *** 1.918 (0.000) ***
13.877 (0.000) *** 0.057 (0.000)*** 1.541 (0.000) *** 1.298 (0.000) *** 1.802 (0.000) *** 3.005 (0.000) *** 4.534 (0.000) ***
0.490 (0.389) 0.050 (0.004)** 0.050 (0.444) -.057 (0.291) -.055 (0.506) 0.099 (0.420) 0. 243 (0.285)
6.802 0.225 0.699 0.724 0.710 1.351 1.932
a * ** ***
(0.006) ** (0.003)** (0.015) * (0.002) ** (0.051) (0.012) * (0.052)
R2
F
0.26 0.43 0.23 0.26 0.22 0.26 0.20
14.589 (0.000) *** 30.772 (0.000)*** 13. 63 (0.000) *** 14.32 (0.000) *** 11.66 (0.000) *** 14.269 (0.000) *** 10.236 (0.000) ***
Numbers between parentheses are p-values. Coefficient is significant at the 0.05 level. Coefficient is significant at the 0.01 level. Coefficient is significant at the 0.001 level.
The coefficients for the variables: age, income, and education were highly significant in all six equations with minor
exceptions such as the variable age in the milk equation. Both age and education were positively related to expenditure as
124
K.A. Bashir tions: while it was about 0.62 for the yogurt, condensed milk, powdered milk, cheese, and ice cream low income equations, it ranged between 0.02 and 0.19 for the same equations at higher income levels. It is, therefore, evident that the same set of explanatory variables did a much better job in explaining consumers’ expenditure of dairy products at lower incomes than at higher incomes. As the low–high income demarcations could likely reflect expatriate–national demarcations, then one could attribute the R2 differences to different consumption habits that could reflect cultural differences. This finding echoes the results for the dummy variable in Table 3, and it bears an important implication to marketing and promotion of dairy products: different strategies are perhaps necessary for the different ethnic groups. In light of the rather low R2 values for the low income group, an in depth analysis would be needed to determine those other specific factors which explain consumers’ expenditure decisions. As for the significance of the explanatory variables across the low–high income equations, almost all variables were not significant for both the low and high income subsets in the dairy equation. However, results were mixed for the six dairy products. Generally, age, education, and income seem to be good determinants of expenditure for the low income group while income and number of children are more important determinants for the high income groups. It appears that some interaction exists between sets of the variables: age, education, and income; for instance older age could indicate more income and more education over some range of these variables. However, inclusion of such interaction terms did not prove to add the significance of the results and as such they were not shown in the final results of Tables 3 and 4. Estimates of expenditure elasticities for the different income and ethnic groups are shown in Table 5. Elasticities were generally close to unity for most product categories in the ‘‘all’’ and the ‘‘high income’’ subsets; for the ‘‘low income’’ subset elasticities ranged between (0.36) for cheese and (0.95) for milk aside from the negative value (0.36) for ice cream. It appears that, counter to expectations, the elasticities for the high income groups are relatively higher. This could be due to exclusion of some relevant explanatory variables in the low income equations. However, upon further investigation,
would be expected. The variable, child, was significant with a positive sign for only the milk equation probably due to the fact that children are generally expected to consume milk more readily than other dairy products. Moreover, advertisements and promotional campaigns are more focused on milk as a good source of calcium and vitamin D for children. It is generally expected that children in the age group 2–5 years are more dependent on milk, however, a variable representing this age group (number of children between 2 and 5 years) was not significant in all equations and was not included in the final results. The coefficient of income was negative and highly significant for all equations in Table 3. This indicates that at higher levels of income the share of dairy products in consumers’ income will decrease. In general, this is expected at relatively higher levels of income. The sample has a mean monthly income level of about AED 8000, a relatively high figure which explains the negative income coefficients. Therefore, it was of interest to see the income coefficient for lower income levels. Table 4 shows estimation results for the same equations in Table 3 at two levels of income for each equation; so for milk, for instance, the equation was estimated for low income (62000 AED/month) and for high income (>2000 AED/ month) households. With a few exceptions, all equations were significant at better than conventional significance levels. The coefficient of income maintained its negative signs at lower income levels. This could mean that even at lower income levels, households are approaching their sufficiency levels and have good access to dairy products. As such the dairy industry may not benefit, in terms of sales, from subsequent income raises in UAE; therefore, more direct efforts through advertising and promotions are necessary to realize that end. The coefficient of the dummy variable, D was positive and significant at the (0.05) level or higher for all equations except the powdered milk and ice cream equations where it was virtually significant at the (0.05) level. This variable measures the differential impact on expenditure shares of expatriates over nationals and as such results indicate higher reservation level of expenditure (intercept) for expatriates. The values of the coefficient of determination (R2) in Table 4 are generally much higher for low than high income equa-
Table 4
OLS estimates for expenditure equations at different income levels.
Dependent variable a
Dairy (I < 2k) Dairy (I > 2k) Milk (I < 2k) Milk (I > 2k) Yoghurt (I < 2k) Yoghurt (I > 2k) Cond. milk (I < 2k) Cond. milk (I > 2k) Powd. milk (I < 2k) Powd. milk (I > 2k) Cheese (I < 2k) Cheese (I > 2k) Ice cream (I < 2k) Ice cream (I > 2k) a b
Constant
Age b
0.361 (0.015) 0.078 (0.337) 0.59 (0.208) 0.024 (0.000) 0.111 (0.448) 0.014 (0.000) 0.155 (0.218) 0.003 (0.177) 0.053 (0.771) 0.022 (0.000) 0.334 (0.254) 0.024 (0.000) 0.204 (0.680) 0.008 (0.000)
0.000 0.000 0.000 0.000 0.004 0.000 0.003 0.000 0.005 0.000 0.007 0.000 0.014 0.000
(0.907) (0.585) (0.420) (0.944) (0.004) (0.590) (0.007) (0.561) (0.003) (0.479) (0.005) (0.407) (0.002) (0.120)
Education
Income
0.022 0.016 0.004 0.000 0.026 0.000 0.018 0.000 0.037 0.000 0.042 0.000 0.094 0.000
0.024 0.002 0.010 0.002 0.040 0.001 0.039 0.000 0.041 0.002 0.089 0.002 0.118 0.001
(0.061) (0.006) (0.258) (0.365) (0.050) (0.796) (0.096) (0.025) (0.030) (0.973) (0.102) (0.336) (0.040) (0.483)
(I < 2k) ” income 6 2000 AED/month; (I > 2k) ” income > 2000 AED/month Numbers between parentheses are p-values.
Child (0.142) (0.823) (0.088) (0.000) (0.040) (0.000) (0.019) (0.636) (0.084) (0.000) (0.023) (0.000) (0.066) (0.002)
0.005 0.002 0.002 0.000 0.001 0.000 0.001 0.000 0.002 0.000 0.001 0.000 0.006 0.000
(0.330) (0.414) (0.344) (0.000) (0.815) (0.000) (0.850) (0.218) (0.785) (0.000) (0.911) (0.041) (0.750) (0.000)
R2
F
0.170 0.037 0.225 0.204 0.625 0.178 0.615 0.022 0.625 0.191 0.62 0.120 0.629 0.134
1.817 2.866 2.165 13.882 7.678 11.493 7.381 2.095 7.671 12.426 7.326 7.640 7.791 8.534
(0.190) (0.025) (0.135) (0.000) (0.003) (0.000) (0.003) (0.083) (0.003) (0.000) (0.004) (0.000) (0.002) (0.000)
Consumption of dairy products in the UAE: A comparison of nationals and expatriates Table 5 Expenditure elasticities for different income and ethnic groups. Variable
All
Low income High Nationals Expatriates income
Dairy Milk Yoghurt Cond. milk Powd. milk Cheese Ice cream
0.96 0.99 0.95 0.94 0.96 0.95 0.92
0.77 0.95 0.62 0.38 0.66 0.35 0.36
a
0.99 0.99 0.99 1.00 0.98 0.99 0.98
0.23 –a – – – – 1.08
0.56 – – – – – 0.74
Results for these equations did not warrant useful comparisons.
it turned out that the average income for the expatriates’ subset of the sample was relatively higher than that of the national subset. Conceivably national are eligible to additional sources of unreported income such as the various types of government assistance and grants. In surveys, respondents tend to interpret income as monthly salary and as such it is more likely that the reality is counter to what appears in the sample: nationals’ income is more likely higher than expatriates’, on average. Consequently, the ‘‘low income’’–‘‘high income’’ columns in Table 5 may actually be reversed if additional unreported income is taken into consideration. The elasticity estimates for dairy were 0.23 for nationals and 0.56 for expatriates which could be attributable to differences in income levels (the estimates are comparable to previous studies (El-Eraky and Al-Muhairi, 2004). 6. Conclusions In this study the consumption behavior for dairy products was investigated. Products examined included: fresh milk, yoghurt, butter, cheese, ice cream, cream, and condensed and powdered milk in the major urban centers of Al-ain, Dubai, and Abu Dhabi. Linear expenditure equations along different income and ethnic groups were estimated. All estimated equations were statistically significant. However, the explanatory power of some was particularly low,
125
namely the equations for the high income subset of the sample. This suggests that some important variables may have been omitted. Possible candidates include: expenditure on other drinks such as juices, and additional income for nationals. The study detected significant differences in consumption behavior between the nationals and expatriates subsets of the sample. An important implication here is that marketing endeavors should bear such differences in mind and that different marketing strategies need to be devised for these subsets. Moreover, culture-specific factors should be included in future studies to explain consumption behavior. Expenditure elasticity estimates for the ‘‘low’’ and ‘‘high’’ income subsets were relatively higher for the ‘‘high’’ than the ‘‘low’’ income subsets. While this is apparently counter to expectations, yet when viewed in light of expected actual rather than reported income these results seem sensible.
References Badrinath, P., Al-Shboul, Q.A., Zoubeidi, T., Gargoum, A.S., Ghubash, R., El-Rufaie, O.E. (Eds.), 2002. Measuring the Health of the nation: United Arab Emirates Health and Lifestyle Survey 2000. Faculty of Medicine and Health Sciences and College of Business and Economics, UAE University, Al-ain, UAE. Deaton, A., Muellbauer, J., 1980. American Economic Review 70, 312–326. El-Eraky, M., Al-Muhairi, T., 2004. Consumer demand for food in the United Arab Emirates: a pilot study. In: Proceedings of the Fifth Annual UAE University Research Conference, vol. 2, UAE University, Al-ain, UAE. Iddison, P., 1999. Dairy food in the UAE. Available from: