Citation of this paper

Factors affecting fresh milk consumption of Vietnamese households

Hoang Vu Quang

Institute of Policy and Strategy for Agriculture and Rural Development, No. 16, Tay Ho, Ha Noi, Vietnam
hoangvuquang@hotmail.com

Abstract

This paper presents a study on the factors affecting fresh milk consumption of Vietnamese households using Cragg’s double-hurdle model with time series and cross section data from VHLSSs 2008 to 2016. Several socio-economic, demographical and place variables affected household consumption of fresh milk. The variables that have most important and positive effect on household consumption of fresh milk are number of children of 6 years old or under, the education level, household living in urban area, the household of Kinh and Hoa ethnics, and households using a fridge.

Keywords: demographical, double-hurdle model, socio-economic factors

Introduction

In the last two decades, the dairy product consumption in Vietnam has been dramatically increasing. The dairy consumption increased by not only the increase of number of households using dairy products, but also by increased volume per household. The consumption of dairy products is influenced by several factors, in particular increased knowledge of people on positive effects of milk consumption.

Several studies have identified positive effects of dairy product consumption on growth, development, human health and disease prevention (Kurajdova et al 2015; Alwis et al 2009; Deakin University Australia 2013; The Dairy Council 2014; William Reed Business Media SAS 2013; Dallmeier 2012; Dror et Allen 2011). The positive effects of milk on children (Do et al 2009) and pregnant women (Hoa et al 2005) found in Vietnam supported positive behavior of Vietnamese in increasing dairy product consumption.

Several studies identified the factors affecting the dairy product consumption of households. The positive impact of income on dairy product consumption has been found in studies of Alwis et al (2009), Phuong et al (2015), Uzunoz and Akcay (2012) and Cornick et al (1994). The demographical and personal characteristics as household size, number of children, the ethnicity, the gender, the age, the educational level of household’s head are used in several studies and found that they have significant impact on dairy product consumption (Phuong 2015; Bonaventure et Umberger 2012; Alwis et al 2009; Mennebro and Wallin 2007; Uzunoz and Akcay 2012; Kresic et al 2010; Kurajdova et al 2015). The third factor influencing milk consumption is the characteristics of living place of households as region and urban/rural ratio (Phuong et al 2015; Cornick et al 1994; Dong et al 2004). The knowledge and the perception of consumers also impact the behavior in milk purchase and consumption (Kurajdova et al 2015; Bonaventure and Umberger 2012). The studies of Alwis et al (2009), and Bonaventure and Umberger (2012) indicated that milk price impacts on the purchase behavior of consumers, and consequently on consumption.

The data at household level was used in several studies to examine the impact of socio-economic and demographic factors on volume and expenditure on food products (Su and Yen 2006; Phuong et al 2015; Bittencourt et al 2007). Some studies used data from Vietnam Household Living Standard Survey (VHLSS) to analyze the factors effecting consumption patterns of Vietnamese households (Minot and Goletti 2000; Le 2008; Phuong et al 2014). Phuong (2015) also used VHLSS 2010 to measure the impact of socio-economic and demographic factors on the expenditure for dairy products (including condensed and powdered milk, fresh milk, and other dairy products) in Vietnam.

In the period 2008-2016, while condensed and powdered milk consumption have had little change. The fresh milk consumption registered a strong increase in terms of proportion of household consuming milk and the consumed volume. This study focuses on the examination of the factors influencing the fresh milk consumption volume of Vietnamese households by using time-series and cross-sectional data from several studies (VHLSS 2008, 2010, 2012, 2014 and 2016). This facilitated the capture of the tendency of the change of the consumer’s perception and effect of advertising and disseminating program and their positive impact on milk cosumption.

Methodology, data and variables

Model

The data used in the model came from household surveys in which an important proportion of households do not consume fluid milk. Therefore, the Tobit model is normally used to address the problem of zero consumption. However, many studies found that the double-hurdle model outperforms the Tobit model (Dong and Gould 2000; Cragg 1971; Yen et Huang 1996; Keelan et al 2009; Chi 2017). One of the limitations is that the Tobit model is very restrictive in its parameterization because the variables and parameters determining the probability of consumption determine also the level of consumption. To overcome the restrictive parameterization of the Tobit model, Cragg (1971) proposed a double-hurdle model. In this paper, the double-hurdle model was used to measure the impact of different factors on fluid milk consumption of Vietnamese households. The double-hurdle model assumes that the households make two decisions on fluid consumption. Firstly, a Probit model is used to determine the decision of participation of whether a household consumes fluid milk or not. Secondly, a regression model is used to measure how much fluid milk each household consumes. The double-hurdle model allows to separate the stochastic variables dealing with both participation and volume decision. The same variables can be used in both estimations and in this case, Tobit model is nested to double-hurdle model. The double-hurdle model is used by several studies (Phuong 2015; Chi 2017; Haines et al 1988; Yen et Huang 1996).

The double-hurdle model has a participation equation

And a consumption equation

D_i^* is latent participation and Y_i ^* is latent consumption. Y_i is the observed dependent variable. Z_i and X_i are vectors of explanatory variables and α and β are vectors of estimated parameters. η and ε are the error terms and independent and normally distributed such as η~ N(0,1) and ε ~ N(0,δ). ε is truncated at – Xβ. The observed consumption (Y) relates to latent consumption (Y^*) such as:

From (1), (2) and (3), likelihood function for a double-hurdle model can be constructed as:

Where d is binary indicator equal to 1 if Y is positive and 0 otherwise. The model is run by the MLE method. The command craggit in Stata 14 is used to estimate simultaneously ε and β for favoring the calculation of post-estimation (Burke 2009).

From Cragg’s model, there are 3 expected values and 3 marginal effects that are of interest. The probability of positive observation is:

The expected value of Y, conditional on Y>0 is

Where λ is the inverse Mills ratio

Where f and F are respectively the probability density function and the cumulative density function. And the “unconditional” expected value of Y is

The marginal effect of an independent variable on probability that Y>0, on the expected value of conditional Y and unconditional Y are given in (7), (8) and (9), respectively

From (9) we can see that if X_j only determines the probability of Y>0, then β_j = 0 and the second term on the right-hand side of (9) is canceled. If X_j determine only Y, given Y>0, then α_j = 0 and the first right hand side of (7) is canceled.

Data

In this study, we use the data from Vietnam Household Living Standard Survey (VHLSS) of years 2008, 2010, 2012, 2014, 2016, collected by Vietnam General Statistical Office (GSO). The VHLSS was conducted nation-wide and it is structured in sub-samples. One subsample collects the data on income, expenditure, consumption, and others. The surveys were representative for the whole country, 8 regions, rural and urban area, coast, delta, midland and mountain area, and provincial level. The method of face to face interview with household’s head was conducted. The collected data include volume and expenditure of condensed and powdered milk and fluid milk; for yoghourt, only data on expenditure is collected.

Because of missing data, not all data from households in subsamples of every VHLSS are used. So, number of observations in each VHLSS used in this study is presented in Table 1.

Table 1. Structure of sample
Year of VHLSS	Total number of observations used in study	Number of households use fresh milk	Number of households do not use fresh milk

2008	7338	1937	5401
2010	7804	2123	5681
2012	4050	1196	2854
2014	8024	1993	6031
2016	8594	3397	5197
Total	35810	10646	25164
Source: from VHLSS 2008, 2010, 2012, 2014, 2016.

Variables

The variables reflecting socio-economic and demographical characteristics and living place of households are used to determine the impact on fluid milk consumption (Table 1). All variables are used in both equations of participation and consumption.

Table 2. Descriptive statistics of variables
Variable	Definition	Mean	Std. Dev

D	=1 if household consumes fresh milk; 0 otherwise	0.236	0.425
Y	Volume (liter) of fresh milk consumed by household	13.4	41.0
income	Annual income of household (Million VND)	71.4	106
price	Average price of fluid milk (1000 VND/kg)	21.7	13.6
age	Age of household head	49.8	14.2
nperson	Number of household members	4.05	1.66
nbaby	Number of children of 6 years old or under	0.426	0.677
nold	Number of elderly persons (>=65 years old)	0.197	0.472
areaSH	Red delta area (base category)	0.230
areaDB	North-East mountain area (1/0)	0.116
areaTB	North –West mountain area (1/0)	0.0417
areaBTB	North Central Coast area (1/0)	0.104
areaNTB	South Central Coast area (1/0)	0.124
areaTN	Central Highland (1/0)	0.0633
areaDNB	South-East-South area (1/0)	0.140
areaSCL	Mekong delta (1/0)	0.182
urban	Household in urban area (1) and 0 rural	0.313
placeVB	Household in coast commune (base category)	0.055
placeDB	Household in delta commune (1/0)	0.413
placeTD	Household in midland commune (1/0)	0.173
placeMN	Household in mountainous commune (1/0)	0.0942
ethnic	Household belonging to Kinh or Hoa ethnicity (1/0)	0.885
educ2	Educational level of household’s head at secondary (base category)	0.783
educ3	Educational level of household’s head at high school or occupational training certificate (1/0)	0.154
educ4	Educational level of household’s head at college or university (1/0)	0.059
educ5	Educational level of household’s head at graduate (1/0)	0.00421
female	Household with female head (1/0)	0.262
fridge	Household is using the fridge (1/0)	0.457

Result

Fresh milk consumption of Vietnamese households

In the last 10 years, about 60% of Vietnamese households consume dairy products. There is a difference in the proportion of households in consuming 3 categories of dairy products as condensed and powdered milk, fresh milk and other dairy products (yoghourt, cream). However, it is obvious that there is an increasing trend in consuming condensed and powdered milk and fresh milk. In 2008, only 21.1% of households consumed fresh milk, in 2016 this proportion achieved 36.4%. The numbers consuming condensed and powdered milk are 26.4 and 39.5 respectively. But in term of consuming volume, the only strong increase is registered in fresh milk. The consumption of fresh milk has increased from 11.7 liters/household to 29.0 liters in 2016. The increased dairy products consumption contributed to increase the expenditure for dairy products, both in terms of absolute value and the share of household annual income. The household expenditure for dairy products that represented 1.17% of total income in 2008 achieved 1.96% of total income in 2016.

Table 3. Household’s consumption of dairy products
Indicator	Kind of dairy product	2008	2010	2012	2014	2016

Proportion of household consumes (%)	Total (dairy products)	64.7	53.0	55.0	59.2	60.0
	Condensed and powdered milk	26.4	27.2	29.5	24.8	39.5
	Fresh milk	21.1	22.6	26.5	21.5	36.4
	Other dairy products	36.8	26.8	26.5	13.8	24.3

Volume of consumption (kg)	Condensed and powdered milk	4.4	4.9	5.0	3.4	4.9
Volume of consumption (kg)	Fresh milk	11.7	20.7	18.6	15.5	29.0

Expenditure for milk products (000 VND)	Total (dairy products)	592	1306	1668	1514	2743
	Condensed and powdered milk	369	692	882	840	1396
	Fresh milk	156	382	511	516	1015
	Other dairy products	66.4	232	276	158	332

Annual income (million VND)		50.7	70.4	92.3	112	140
Source: Calculated from VHLSS 2008, 2010, 2012, 2014, 2016.

The statistical analysis of VHLSS indicated that the fresh milk consumption is affected by socio-economic, demographic factors and living place of households (Table 4): the higher the income the household, the higher the fresh milk consumption. The households in urban areas consume more fresh milk than those in rural areas. The households in the mountainous areas consume less than those in the delta and midland areas. The educational level of household’s head has strong effect on fresh milk consumption such as the higher educational level household achieves the higher fresh milk consumed. The households belong to Kinh and Hoa ethnics consume more fresh milk than ethnic minority groups. There is no impact of the gender of household head on the volume of fresh milk consumption. Finally, the use of a fridge facilitates the preservation of fresh milk, so it increases the fresh milk consumption.

Table 4. Fresh milk consumption by household characteristics (liters/household)
Variable		2008	2010	2012	2014	2016

Quintiles of income	Quintile 1	2.4	3.4	1.7	3.9	5.5
	Quintile 2	4.5	9.5	6.2	10.9	15.3
	Quintile 3	6.1	14.9	10.0	17.6	25.2
	Quintile 4	10.8	23.2	17.9	20.9	36.6
	Quintile 5	23.3	43.2	33.8	25.3	59.8

Household in urban or rural	Urban	20.5	30.4	27.4	18.8	37.6
Household in urban or rural	Rural	6.0	13.9	13.2	14.3	23.8

Household in area of commune	Coast commune	5.4	12.7	6.4	19.5	25.1
	Delta commune	6.1	15.7	15.2	16.4	26.2
	Midland commune	5.8	12.7	15.0	14.2	23.7
	Mountain commune	5.7	10.0	10.3	9.4	16.3

Household in region	Red delta	9.7	21.1	18.0	14.2	27.8
	North East mountain	7.5	13.8	9.7	11.1	18.9
	North West mountain	8.3	8.0	5.6	9.2	16.0
	North Central Coast	5.1	14.4	13.6	15.5	31.4
	South Central Coast	14.3	26.5	25.8	23.3	34.9
	Central Highlands	10.2	16.6	20.9	15.0	24.7
	South East	19.6	27.1	23.0	17.6	36.3
	Mekong delta	6.0	14.8	15.9	16.6	26.9

Level of education	Secondary	7.8	14.6	14.8	14.9	24.8
	High school	16.4	29.9	20.9	17.0	33.6
	College, university	27.8	43.1	42.8	22.0	51.3
	Graduate	37.7	56.5	61.8	22.0	63.9

Household's ethnicity	Minority ethnic	3.9	5.5	5.6	8.4	14.9
Household's ethnicity	Kinh & Hoa	10.9	20.9	19.5	16.9	30.3

Gender	Male	9.8	18.9	17.1	16.3	28.8
Gender	Female	11.2	19.1	19.1	13.9	26.2

Having fridge or not	No fridge	4.9	8.8	10.1	10.2	14.1
Having fridge or not	Having fridge	20.6	21.8	25.8	19.2	34.3
Source: Calculated from VHLSS 2008, 2010, 2012, 2014, 2016.

Analysis of estimation result of double-hurdle model

The result of parameter estimates of double-hurdle model for fresh milk consumption of Vietnamese households (Tables 5 and 6) shows the partial (marginal) effect of each variable on the probability and the volume of fresh milk consumption. Most variables included in the model are significant in both equations, participation and consumption. Some variables have impact on probability, but not on consumption (eg: number of elderly people and the gender of household head).

The income of household has a positive impact on probability and volume of fresh milk consumption; the coefficient of the income is significant and positive in both equations. The impact of the income on probability is very small as if the income of household increases by more than 1 million VND, the probability that a household consume fresh milk increases only 0.02% point. If the income of household increases 10%, the unconditional consumption of fresh milk will increase 0.79%.

The price of fresh milk impacts negatively on probability and the level of consumption. Accordingly, an increase of 10% of the price of fresh milk can reduce only 0.04 percent point of the probability but reduces 5.6% of volume of fresh milk consumed by household.

The household size has a positive impact on both probability and consumption of fresh milk. This result is like several previous studies that have confirmed the impact of household size on dairy product consumption (Phuong et al 2015; Uzunoz and Akcay 2012). When the household has one more person, the probability that this household consumes fresh milk increase 0.019 percent and consumed volume of fresh milk increases 1.59 liters. We also found an impact of the composition of household on fresh milk consumption. The number of children of 6 years old or under has a strong impact in both equations. Accordingly, an increase of one child equal or under 6 years old increases 0.51 percent point of the probability of participation and increase 12.9 liters of fresh milk consumed by household. Alwis et al (2009) and Phuong et al (2015) also found out the impact of children on the consumption of dairy products.

The number of elderly people in the household has positive impact on the probability of participation, but not on the level of consumption. An increase of one elderly person increases 0.029 percent point of the probability of participation.

Table 5. Estimates of double hurdle mode for fresh milk consumption
Variable	Participation		Consumption
Variable	Parameter	Std. Err	Parameter	Std. Err

year	0.0443	[0.00355]*	149	[28.6]*
income	0.000757	[0.000078]*	0.295	[0.0659]*
price	-0.00429	[0.000772]*	-281	[5.70]*
age	-0.0121	[0.000650]*	-10.9	[2.59]*
nperson	0.0649	[0.00591]*	49.4	[16.6]*
nbaby	0.513	[0.0126]*	428	[80.5]*
nold	0.0992	[0.0183]*	17.1	[45]
areaDB	-0.0633	[0.0317]**	-184	[98]***
areaTB	-0.199	[0.0431]*	-295	[149]**
areaBTB	0.0992	[0.0279]*	-13.7	[72.6]
areaNTB	0.147	[0.0264]*	455	[102]*
areaTN	-0.0257	[0.0379]	291	[110]*
areaDNB	-0.0541	[0.0260]**	439	[97.3]*
areaSCL	-0.273	[0.0244]*	600	[123]*
urban	0.250	[0.0279]*	208	[82]**
placeDB	0.0591	[0.0271]**	67.1	[74.6]
placeTD	0.116	[0.0315]*	-146	[94]
placeMN	-0.0417	[0.0409]	-112	[125]
ethnic	0.336	[0.0306]*	467	[133]*
educ3	0.140	[0.0211]*	106	[50.5]**
educ4	0.333	[0.0309]*	311	[76.9]*
educ5	0.455	[0.109]*	415	[170]**
sexnu	0.136	[0.0180]*	-11.3	[41.9]
fridge	0.264	[0.0176]*	621	[131]*
Constant	-90.2	[7.125]*	-302303	[58011]*
Number of observations	35810
Log likelihood	-72544
Wald chi2(24)	5407
Probability.	P< 0.0001
* p<0.01, p<0.05, * p<0.1 Source: Based on VHLSS 2008, 2010, 2012, 2014, 2016

Several studies have measured the impact of gender on the consumption of dairy products. Phuong (2015) found out that the gender of household head had significant and positive impact on the consumption of dairy products as a whole in Vietnam. In this study on fresh milk, we found only impact of gender on the probability of participation, but not on the level of consumption. The household with a woman as head has a higher probability of 0.04 percent points to consume fresh milk than the household with a man as head.

The age of household head has a negative effect on both probability of participation and volume of fresh milk consumed. When the age of household head is higher by one, the volume of fresh milk consumed by household reduces 0.31 liters. This result suggests that fresh milk is more important to young households than aged households. Some previous studies found significant impact of age on the consumption of dairy products (Phuong 2015; Bonaventure and Umberger 2012; Alwis et al 2009).

An interesting finding in this study is the significant effect of the possession of the fridge on both the probability and the level of consumption of fresh milk. Accordingly, the households with a fridge consume 11.0 liters more fresh milk than the households without a fridge. The possession of the fridge allows the household to keep fresh milk in good condition.

The level of education of household head has an important effect on probability and level of fresh milk consumption. The higher the educational level, the higher are the probability and the level of consumption. Concretely, the household at high school level consumes 3.4 liters more than the household at secondary level. The household at graduate level consumes 3.1 liters more than households at university level. And the latter consume 4.3 liters more than households at high school level.

This study also find that the living place of households has significant impact on fresh milk consumption. The regions are different by living condition (transport system, electricity), demographical structure (density, ethnicity). Generally, the households living in difficult regions as mountainous consume less fresh milk than more favorable regions as delta and midland. The result of this study is similar to several studies that found significant impact of characteristics of living place on the consumption of dairy products (Nguyen 2015; Cornick et al 1994; Dong et al 2004; Phuong et al 2015).

Another interesting finding of this study is that the variable “tendency” is significant and positive on both probability and the level of consumption. According to the result, each year, the probability of number of households consuming fresh milk increases 0.013 percent point and each households increase their consumption volume of fresh milk by 2.32 liter. This variable included in the model to capture the impact of other factors such as advertisement and propaganda programs on the benefit of the consumption of dairy products.

Table 6. Partial effect of variables on fresh milk consumption
Variable	Probability	Conditional level	Unconditional level	Elasticity on unconditional level

year	0.0131	5.34	2.33
income	0.000223	0.0106	0.0155	0.0793
price	-0.00127	-1.04	-0.382	- 0.556
age	-0.00355	-0.391	-0.313
nperson	0.0191	1.77	1.58
nbaby	0.151	15.3	12.9
nold	0.0293	0.612	1.79
areaDB	-0.0187	-6.6	-3.01
areaTB	-0.0586	-10.6	-6.41
areaBTB	0.0293	-0.492	1.46
areaNTB	0.0434	16.3	7.29
areaTN	-0.00758	10.4	2.72
areaDNB	-0.0160	15.7	3.86
areaSCL	-0.0806	21.5	2.04
urban	0.0738	7.47	6.30
placeDB	0.0174	2.41	1.68
placeTD	0.0341	-5.23	0.301
placeMN	-0.0123	-4.03	-1.89
ethnic	0.0992	16.7	10.5
educ3	0.0413	3.79	3.41
educ4	0.0981	11.1	8.75
educ5	0.134	14.9	11.9
sexnu	0.0400	-0.406	2.08
fridge	0.0778	22.3	11.0
Source: Based on VHLSS 2008, 2010, 2012, 2014, 2016

Conclusions

This study used the Cragg’s double-hurdle model to analyze the impact of socio-economic, demographic and living place factors on the decision of Vietnamese households whether to consume fresh milk and the volume of consumption. The series time and cross section data of households from VHLSS in years of 2008, 2010, 2012, 2014 and 2016 was used.
The study found that most variables included in the model were significant in both equations, participation and volume of consumption. However, some variables as gender of household head, number of elderly persons have only impact on one equation. That confirms the hypothesis that the Cragg double hurdle model is more flexible than zero left censored Tobit model as in Tobit model the variables and parameters determining the probability of consumption determine also the level of consumption.
Several variables capturing socio-economic and demographical characteristics of households have significant impact on the probability of and the volume of fresh milk consumption. The variables include: income, price of fresh milk, household size, number of children, and educational level of household head, the ethnics of household.
The characteristics of living place (region, urban/rural) of households have also impact on fresh milk consumption.
The variables that have more impact on fresh milk consumption are the number of children, the ethnics of households, the educational level, urban area and using the fridge.

References

Alwis A, Edirisinghe J and Athauda A 2009 Analysis of Factors Affecting Fresh Milk Consumption Among the Mid-Country Consumers. Tropical Agricultural Research and Extension. 12(2): 103-109.

Bittencourt Mauricio V L, Ratapol P Teratanavat and Wen S Chern 2007 Food consumption and demographics in Japan: Implications for an aging population. Agribusiness. Vol. 23, No. 4, pp. 529–551.

Bonaventure B and Umberger W J 2012 Factors Influencing Malaysian Consumers´ Consumption of Dairy Products. Australian Agricultural and Resource Economics Society. Access online in Sept 18th 2018 at: http://ageconsearch.umn.edu/bitstream/124243/2/2012AC%20Boniface%20CP.pdf.

Burke William J 2009 Fitting and interpreting Cragg’s Tobit alternative using Stata. The Stata Journal. Vol. 9, No 4, pp 588-592.

Chi Yeong Nain 2017 An Application of the Double Hurdle Model to U.S. Saltwater Recreational Fishing Expenditures. Journal of Applied Business and Economics. Vol. 19, No 6, pp 74-85.

Cornick Jorge, Cox T L and Gould B W 1994 Fluid Milk Purchases: A Multivariate Tobit Analysis. American Journal of Agricultural Economics. Vol. 76, No.1, 74-82.

Cragg John G 1971 Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods. Econometrica. Vol. 39, No. 5, pp. 829- 844.

Dallmeier Lorraine 2012 Milk - Natural Beauty throughout History. Online access in 20/9/2018 at: http://www.herbhedgerow.co.uk/milk-natural-beauty-throughout-history/

Deakin University, Australia 2013 Milk - Facts and Fallacies. Access online in September 25^th 2018 at: http://www.betterhealth.vic.gov.au/bhcv2/bhcarticles.nsf/pages/Milk_the_facts_and_fallacies.

Do Thi Kim Lien, Bui Thi Nhung, Nguyen Cong Khan, Le Thi Hop,Nguyen Thi Quynh Nga, Jeroen Kiers, Yamamoto Shigeru and Rob te Biesebeke 2009 Impact of Milk Consumption on Performance and Health of Primary School Children in Rural Vietnam. Asia Pacific Journal of Clinical Nutrition. 18(3): 326 – 334.

Dong D and Gould B W 2000 Quality versus quantity in Mexican household poultry and pork purchase. Agribusiness. 16(3):333-355.

Dror Daphna K and Lindsay H Allen 2011 The Importance of Milk and other Animal-Source Foods for Children in Low-Income Countries. Food and Nutrition Bulleting. Vol.3, No 3, pp 227-243.

Haines Pamela S, Guilkey D K and Popkin B M 1988 Modeling Food Consumption Decisions as a Two-Step Process. American Journal of Agricultural Economics . 70(3):543-553.

Hoa P T, Nguyen Cong Khan, van Beusekom C, Gross R, Conde E L and Ha Dui Khoi 2005 Milk fortified with iron and iron supplementation to improve nutritional status of pregnant women: An intervention trial from rural Vietnam. Food and Nutrition Bulletin. 26(1):31-38.

Keelan C D, Henchion M M and Newman C F 2009 A Double-Hurdle Model of Irish Households' Food Service Expenditure Patterns. Journal of International Food & Agribusiness Marketing. 21(4):269-285.

Kresic G, Herceg Z, Lelas V and Režek Jambrak A 2010 Consumers´ Behaviour and Motives for Selection of Dairy Beverages in Kvarner Region: a Pilot Study. Mliekajstvo. 60(1): 50-58.

Kurajdova Klaudia, Janka Taborecka-Petrovicova and Alena Kascakova 2015 Factors influencing milk consumption and purchase behavior – evidence from Slovakia. Procedia Economics and Finance. No 34(2015): 573-580.

Le C Q 2008 An empirical study of food demand in Vietnam. Journal of Southeast Asian Economies. 25(3): 283-292.

Mannerbro C and Wallin G 2007 Determinants of the Demand for Eco-labelled Milk and Fair Trade Coffee. Online access in September 20, 2018 at http://arc.hhs.se/download.aspx?MediumId=323.

Minot N and Goletti F 2000 Rice Market Liberalization and Poverty in Viet Nam. IFPRI Research Report No 114. Washington, D.C.

Phuong N V, Cuong T H and Mergenthaler M 2014 Effects of Socio-economic and Demographic Variables on Meat Consumption in Vietnam. Asian Journal of Agriculture and Rural Development. 4(1): 972-987.

Phuong N V, Cuong T H and Mergenthaler M 2015 Effect of Household Characteristics on Expenditure for Dairy Products in Vietnam. International Journal of Research Studies in Agricultural Sciences. 1(5): 1-13.

Su S J B and Yen S 1996 Microeconometric models of infrequently purchased goods: An application to household pork consumption. Empirical Economics. 21(4):513-533.

The Dairy Council 2014 Macro-nutrients in Milk. Access online in 25/9/2018 at: http://www.milk.co.uk/page.aspx?intPageID=70.

Uzunoz M and Yasar Akcay 2012 A Case Study of Probit Model Analysis of Factors Affecting Consumption of Packed and Unpacked Milk in Turkey. Economics Research International. Vol. 2012, Article ID 732583, 8 pages.

William Reed Business Media SAS 2013 Milk Drinkers Win Nobel Prizes. Researchers Claim. Access online in 25/9/2018 at: http://www.dairyreporter.com/R-D/Milk-drinkers-win-Nobel-Prizes-researchers-claim.

Yen S T and Huang C L 1996 Household demand for finfish: a generalized double-hurdle model. Journal of Agricultural and Resource Economics - Western Agricultural Economics Association – WAEA. 21(2): 220-234.

Received 4 January 2019; Accepted 10 January 2019; Published 4 March 2019

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