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Source: Table 3.1 in Brassley P., 1997 From table 3.1, we can see that, although rice is the main staple food in all selected countries, annual per capita quantity of rice consumption varies greatly across different countries. It is highest at 256 in Laos and lowest at 120 in India. This variation in quantity of rice consumption may result from the difference in the age structures and food diet of these countries.
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|
Products |
(Own) Price elasticity |
|
Corn and cassava |
-0.26 |
|
Spices |
-0.25 |
|
Rice |
-0.63 |
|
Coconut |
-0.88 |
|
Tea and coffee |
-0.90 |
|
Vegetables and fruits |
-0.97 |
|
Prepared food |
-1.01 |
|
Fish |
-1.04 |
|
Sugar |
-1.15 |
|
Drinks |
-1.71 |
|
Livestock and livestock products |
-1.73 |
Source: Table 2.3 in Duong, 2000
It is clear from table 3.3 that peas, eggs, oranges, milk, and pork are luxury goods for the poor but they are necessities for the rich. This is a good illustration for the point that when income increases consumers tend to switch to buy higher quality foods. And the table also verifies the argument that food price elasticities will decrease when people become richer.
Demand for a good depends not only on its price, but also on prices of related goods defined as substitutes and complements. Consumer may change demand for a food when there are changes in prices of other foods. We review results about cross price elasticities of demand for some foods in next section.
Table 3.3: Estimated (own) price elasticity of demand by income groups, Cali, 1969-1970[1]
|
Products |
Low income |
|
High income |
|
||
|
|
I |
II |
III |
IV |
V |
Average |
|
Cassava |
-0.23 |
-0.28 |
-0.25 |
-0.00 |
-0.00 |
-0.19 |
|
Potatoes |
-0.41 |
-0.42 |
-0.31 |
-0.00 |
-0.00 |
-0.26 |
|
Rice |
-0.43 |
-0.40 |
-0.40 |
-0.26 |
-0.18 |
-0.35 |
|
Maize |
-0.63 |
-0.55 |
-0.44 |
-0.00 |
-0.00 |
-0.44 |
|
Bread/pastry |
-0.65 |
-0.56 |
-0.32 |
-0.24 |
-0.00 |
-0.31 |
|
Beans |
-0.82 |
-0.78 |
-0.64 |
-0.45 |
-0.25 |
-0.60 |
|
Peas |
-1.13 |
-1.13 |
-0.76 |
-0.59 |
-0.52 |
-0.70 |
|
Eggs |
-1.34 |
-1.23 |
-1.26 |
-0.75 |
-0.35 |
-0.92 |
|
Oranges |
-1.39 |
-0.96 |
-0.79 |
-0.64 |
-0.29 |
-0.69 |
|
Milk |
-1.79 |
-1.62 |
-1.12 |
-0.64 |
-0.20 |
-0.77 |
|
Pork |
-1.89 |
-1.61 |
-1.12 |
-0.82 |
-0.70 |
-1.01 |
Source: Table 2.4 in Duong, 2000.
Cross price elasticity of demand for a food can be positive or negative depending on the relation in consumption between goods. Unlike changes in the own price that induce movements along the demand schedule, changes in other foods’ prices lead to switch of the demand curve for a food. Table 3.4 below shows that “Mutton and Lamb” and “Pork” are substitutes for “Beef and Veal”.
|
Products |
Elasticity with respect to the price of beef and veal |
|
Beef and veal |
-1.25 |
|
Mutton and lamb |
0.36 |
|
Pork |
0.08 |
Source: Table 3.2 in Brassley 1997
The second factor that is demand for goods is the change in incomes. Like changes in other food prices, Changes in incomes will lead to shift of the demand curve for a food.
The amount each person wants to eat is limited. When people have enough to eat, they will spend little or even no more extra income on food, although they may buy more expensive (higher quality) foods. Moreover, people may reduce the quantity of some foods consumed when incomes increase. Engel’s Law states that as people get richer, the proportion of their income spent on food declines.
|
Gross weekly income of head of household (£) |
Expenditure on food per person per week (v£) |
Percentage of food expenditure on total |
|
Over 560 |
15.68 |
2.8 |
|
290-559 |
13.37 |
3.15 |
|
140-289 |
12.58 |
5.86 |
|
Under 140 |
11.53 |
8.24 |
Source: Table 3.3 in Brassley, 1997.
We can see from table 3.5 (previous page) the fact that expenditure on food in absolute term increased from 11.53 to 15.68 but the proportion of expenditure on food declined from 8.24% to 2.8%.
The above argument is also relevant in the national sense. As the national income increases we would expect the percentage of total expenditure on food to reduce (Brassley, 1997, p. 30). Tables 3.6 will illustrates the argument.
|
Year |
Percentage of household food expenditure on total |
|
1978-80 |
17.6 |
|
1985 |
14.1 |
|
1990 |
11.9 |
|
1992 |
11.9 |
|
1995 |
11.0 |
Source: Table 3.4 in Brassley , 1997.
Table 3.6 shows that, from 1978 to 1993, when GDP of UK grew, the share of expenditure on foods in UK fell gradually from 17.6% to 11.0%. It supports the above argument.
Income elasticities of demand vary between commodities, income levels, groups of people within a country, and between countries. Estimated income elasticities of demand for food in some countries to verify this argument are presented in table 3.7.
|
Country |
Income elasticity of demand for food |
|
India |
0.78 |
|
Hungary |
0.61 |
|
Israel |
0.58 |
|
UK |
0.48 |
|
Germany |
0.43 |
|
USA |
0.37 |
Source: extracted from Table 2.1 in Kooreman, 1996.
Economists often argue that income elasticities of demand for foods are likely to reduce when people become richer. This argument is true no matter we compare at the individual or nation level. Table 3.7 verifies this argument. Income elasticity of demand for food is highest in India (0.78) and lowest in USA (0.37).
The scope of quality effects can be examined by running regressions of the logarithm of unit value on the logarithm of total expenditure and the usual list of household demographics and other characteristics (Deaton, 1998, p. 288) in such a model described in Appendix I in full version of the thesis. Table 3.8 and 3.9 below will show results from a recent study in Vietnam.
Table 3.8 shows that rice is a staple food with an expenditure elasticity of quantity at about 0.3. Noodles and meats are luxuries. All expenditure-quality elasticities are positive except for noodles. This show the positive relation between expenditure and quality of foods consumed.
Table 3.8: Within-cluster regressions for unit values and quantity of different food in Vietnam in 1998
|
Food |
Expenditure elasticities[2] of |
Household size coefficients |
||
|
|
Quantity |
Quality |
Budget share |
Unit value |
|
Rice |
0.2972 |
0.0626 |
0.1436 |
-0.0570 |
|
Noodles |
1.2022 |
-0.0642 |
-0.0034 |
(-0.0226) |
|
Meat |
1.2339 |
0.0240 |
-0.0333 |
-0.0238 |
|
Fish |
0.6747 |
0.1490 |
(0.0014) |
-0.1475 |
|
Vegetables |
0.3521 |
0.1720 |
0.0037 |
-0.1628 |
|
Fruit |
0.9996 |
0.1773 |
-0.0066 |
-0.1061 |
|
Oil |
0.7607 |
0.0690 |
(-0.0004) |
-0.0626 |
|
Sugar |
(0.9325) |
0.0557 |
-0.0019 |
-0.0574 |
Note: Coefficients in brackets are not significant. All other coefficients are significant at 1% level.
Source: Table 4 in Youdi, 2002.
The effect of household size on unit values is negative in all foods. The increase in household size tends to reduce unit values.
The effect of household size on the budget share is negative for luxury goods and it is positive for necessities. That can be explained by the fact that, keeping total household expenditure constant, when the number of people in a household increases per capita expenditure level must fall, people must give up luxury foods to maintain the consumption of necessities, such as rice.
In table 3.9 (next page), own-price elasticities, printed in bold, are significant except for oil and sugar. Rice has the lowest own-price elasticity, confirming that it is a necessity as the main staple food in Vietnam.
Some cross-price elasticities are significant, implying that the change in price of one food may affect consumption of other foods. Some foods are substitutes, whereas some other foods are complements. In food demand analysis we should deal with the interaction in consumption between different food categories.
|
Food |
Rice |
Noodles |
Meat |
Fish |
Vegetables |
Fruit |
Oil |
Sugar |
Others |
|
Rice |
-0.39 (3.76) |
0.11 (1.61) |
-0.11 (2.09) |
-0.11 (2.46) |
0.03 (1.04) |
-0.11 (2.77) |
0.00 (0.16) |
-0.17 (3.79) |
0.45 (3.84) |
|
Noodles |
2.48 (1.49) |
-1.06 (5.81) |
-0.19 (0.29) |
-0.83 (2.24) |
-0.19 (1.10) |
0.10 (0.72) |
-0.16 (1.10) |
0.52 (2.70) |
-1.86 (1.20) |
|
Meat |
-0.53 (3.41) |
-0.02 (0.32) |
-1.72 (8.20) |
0.37 (4.54) |
0.12 (2.54) |
0.10 |