Micro-determinants of Household Welfare, Social Welfare, and Inequality in Vietnam

According to the approximation in (2), change of return to characteristics equals to (ßMt+1-ßMt)X tM , and thus change of return to a characteristic during period 1993-1998 equals to the coefficient of that characteristic in 1998
minus the coefficient of that characteristic in 1993 and multiplied by the meanof that characteristic in 1993 (as shown in Table 1). Moreover, based on (2) wecan see that the change due to change in characteristic equals to ßMt(XMt+1-X tM) ,and thus change in characteristic of a characteristic during the period 19931998 equals to the mean of that characteristic in 1998 minus the mean of thatcharacteristic in 1993 multiplied by the coefficient of that characteristic in
1993. Calculations for other characteristics of period 1998-2002 are made in thesame way.
From Table 2, some important things are noted. Most changes in
expenditure per capita in eight regions were due to changes in the returns to living in different regions in both periods.
The same story held for education and occupation. Most changes in
expenditure per capita associated with education and occupation of the household head were attributed to the change in returns to these characteristics rather
than the changing of those characteristics. The results are understandable sinceover time more household heads completing a higher degree of schooling will
put pressure on the wage market.
Similarly, the change in expenditure attributed to gender and ethnicity
also came mostly from changes in the returns to those characteristics
3.5. Pooling data for analysis
From the regressions of cross-sectional data, we can only examine thedeterminants of household expenditure in a single year. By pooling samples
collected from the same population at different periods, we can earn more accurate estimators and test statistics with more power when compared to samplesof single cross-sectional data because we can take advantage of the large sample size at different points in time. The VLSS9293, VLSS9798, andVHLSS2002 covered 4,799, 5,999, and 29,532 households, respectively, so thatthe pooled sample covers 40,330 households in three years, which is a large
sample for deriving more precise estimators.
As can be seen in Table 3, which reports the results of the regres-161

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sions, the findings are consistent with those obtained in cross-sectional regressions in terms of the sign as well as the magnitude of each categorical variable:
occupation, education of the household heads, and geographical locations were
important determinants of expenditure deriving from economic growth. The162

Micro-determinants of Household Welfare, Social Welfare, and Inequality in Vietnam

type of occupation and level of education of the head defined the degree towhich the household gained benefits from economic growth.
There is only difference in that households headed by males had
lower standards of living compared to those headed by females. This result differs from the finding in the cross-sectional regressions with no statistical significance for this variable, suggesting that the returns to this category fluctuatedover time.
3.6. Which characteristics determine the consumption of households in different socio-economic groups?
By using an econometric method, we are able to find out which characteristics determine the differences of expenditure between the poor and therich households, or in other words, among socio-economic groups during theperiod.
Since VLSS9293 contains communal characteristics of the rural areas
only, there is no such data on the urban areas and thus we cannot take advantage of the panel data. In the VLSS9798 commune data were collected in bothrural and urban areas, so in this section only data from the VLSS9798 are used
to investigate the determinants of household welfare of different socio-economic households. The regression results with the addition of communal characteristics4 are put in the same table for analysis.
Table 4 reports the results of the regressions of each quintile. One
important finding is that for poor households (households belonging to the 1stand 2nd quintiles) and the middle class (the 3rd quintile), factors, such as thelevel of education of the head and the region where the household resides, aswell as communal facilities, such as market and electricity, are important for
determining its living standard. For rich households (households belonging toCommune near a factory (apply value 1 for a commune which has at least one factory nearby; 0 if
there no factory near the commune); Commune having traditional handicraft (apply value 1 for acommune which has traditional handicraft; 0 if there is no traditional handicraft); Road passable bycars (apply value 1 for a commune if there is a road that cars can use; 0 if there is a road but cars cannot use it); Electricity (apply value 1 if commune has electricity; 0 if electricity is not supplied in thecommune); Market (apply value 1 if there is at least one market in the commune; 0 if there is nomarket in the commune); and Water-way transportation (apply value 1 if the commune has waterway transportation; 0 if there is no water-way transportation).

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Micro-determinants of Household Welfare, Social Welfare, and Inequality in Vietnam

the 4th and 5th quintiles) the level of education and type of job of the head are
more important in defining their living standards. Communal characteristics,
such as the availability of a market or electricity, play no role in affecting theirexpenditure because most of the rich are living in urban areas, so facilities,
such as electricity and market, are common, while in rural area those facilities
are important. For example, in the poorest quintile, households headed by anindividual who has completed high school spent 7 percent more than households with the head completing only primary school. Interestingly, in the poorest quintile households headed by someone having a university or higher
degree had a lower standard of living compared to those of households headed
by someone having only a primary school degree. Similarly, households livingin areas where there was a market and electricity spent 4.6 percent and 8.1 percent more, respectively, than households residing in areas without such facilities.
Regarding ethnicity, most quintiles show that households with thehead being of an ethnic minority had lower standards of living when comparedto those headed by Vietnamese. For all quintiles, gender and religion of thehead show no impact on the expenditure of the households.
Importantly, when one looks at the results, one may notice that insome cases, the R-squared values are somewhat small. Statistically, the value ofR-squared represents how much variance of the dependent variable can be collectively explained by the independent variables. Since the number of households included in VLSS9798 is 5,999 households, but only 4,818 households
qualified for the test, these households were divided into 5 small samples basedon expenditure quintiles and then the regressions were done with each sample.
This way of regression further lowered the number of households involved in165

Tran Duy Dongeach regression, which then obviously affected the precision of the regressions.
This suggests that a more adequate answer about the determinants of expenditure per capita of each expenditure quintile can only be obtained from muchlarger datasets, which we can obtain in the cross-sectional regressions (Vijverberg, 1998 and Tran, 2000).
3.7. Who benefits from economic growth?
For a poor country like Vietnam where the disparity of development
between rural and urban areas is huge, it is expected that some determinants ofexpenditure in rural areas will differ from those of urban areas. For example, inurban areas, facilities like electricity, roads and telecommunications are common, but for rural areas, especially for mountainous areas, accessing thosekinds of facilities is not easy, not only because of their limited financial capacity but also because of the shortage of those facilities, which is likely affected by
the policies of the government. Therefore, it is essential to find out which characteristics determine the consumption of the rural areas (in which most of thepoor reside), which then will help us to draw up policy suggestions. Moreover,in previous sections, we can only indicate the determinants of consumption ofhouseholds or in other words, we could only state that the living standard ofhouseholds attached to certain characteristics of the heads was higher or lower
when compared to other households. One thing we have not still investigated iswhat kind of households gained more benefit from economic growth (or inother words, enjoyed improved consumption) when compared to other households during the period. Since 4,302 households were interviewed in both
VLSS9293 and VLSS9798, this question can be answered by regressing thechange of real expenditure per capita between two years 1993 and 1998 on thepre-determined characteristics of households in 1993. In order to have a moreinsightful image, some different variables from the previous sections are added
into regressions including:166