# **4. Data**

We use the VHLSS conducted by the Vietnamese GSO in 2016 (VHLSS 2016). This survey has national coverage and a sample size of 9,399 households from a multi-stage stratified random sampling design. The sample is representative at national, regional, urban, rural and provincial levels. Information was collected in four quarters of 2016 through face-to-face interviews with household heads and using an household questionnaire divided into the following sections: household members characteristics; education; health care; income (employment, salaries, wages, agro-forestry and aquaculture activities); expenditure and consumption of food and non-food goods and services; participation in aid schemes.

Before estimations, the VHLSS 2016 data set was cleaned. We considered outliers those households with variables value five times the sample’s standard deviation. After removing outliers and missing values, the remaining sub-sample counts 1,461 households. From the VHLSS 2016 we derive prices and expenditure for 10 groups of goods and services. Table 3 reports the groups and the goods of which they are composed. The households’ expenditure of the first seven groups – i.e. food, foodstuff, beverages and tobacco, household equipment, clothing and accessories, transport, and post and communication; was calculated summing up the individual values in Vietnamese dongs (VND) of each item in the group. The survey did not collect items prices, therefore for each group we calculated a unit value dividing expenditure by the number of items. Unit values are then used in the demand system as proxies for prices. As expenditure for education we used the total expenditure on education over the past 12 months for compulsory subjects in school, and the unit value was calculated dividing this for the number of household members attending school in last 12 months. For medical and health expenditure we used the total expenditure for medical check and treatment provided in the VHLSS 2016, calculating the unit value dividing by the total number of resident and non-resident medical visits in the household. For electricity, we used the household expenditure on electricity for daily activities in the last 12 months and unit values were obtained dividing the expenditure on electricity in the last 30 days by the kilowatts (KW) consumed in the last 30 days. The last five columns of table 3 provide summary statistics of expenditure for each group.

The demand system includes also socio-economic variables to account for households heterogeneity. Socio-economic characteristics can affect households’ consumption patterns and decisions, especially with respect the cross substitution between goods and quality levels. There are three main factors potentially affecting consumption patters, namely the decision making behavior of the household head which is driven by her/his individual profile; the economic situation of the household which is defined by the earnings and the sector of employment; the dimension and composition of the household that might drive consumption towards certain goods and services rather than others. We therefore include four variables on the household head characteristics which are age, gender and education level (either primary or tertiarty, being secondary education the baseline alternative). Three variables describe the income source of the household head, distinguishing between salary from a hired job, income from selfemployment in agriculture, aquaculture or forestry and income from self-employment in other sectors. Finally, four variables describe the household size and composition in terms of number of household members and share of children, young adults and elders among the household members. These socioeconomic variables are reported in table 4 with their description and summary statistics.

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