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A welfare measure of consumer vulnerability to rising prices of food imports in the UAE
Food Policy 37 (2012) 554–560
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A welfare measure of consumer vulnerability to rising prices of food imports in the UAE Azzeddine M. Azzam a,b,c,⇑, Belaid Rettab d a
Department of Economics, University of Dubai, Dubai, United Arab Emirates Dubai Chamber, Dubai, United Arab Emirates c Department of Agricultural Economics, University of Nebraska, Lincoln, NE, USA d Economic Research & Sustainable Business, Dubai Chamber, Dubai, United Arab Emirates b
a r t i c l e
i n f o
Article history: Received 15 June 2011 Received in revised form 25 April 2012 Accepted 20 May 2012
Keywords: Food imports Vulnerability Welfare Compensating variation Price caps United Arab Emirates
a b s t r a c t The recent and expected continuing rise in food prices has re-ignited concern and discussion in the United Arab Emirates about the country’s vulnerability to food supply shocks. Defining vulnerability as the compensating variation relative to household income, we find that although UAE households in the lowest income quintile spend on food on average less than a quarter of what households in the highest income quintile spend, the former are 3.5 times more vulnerable to rising prices of food imports than the latter. Ó 2012 Elsevier Ltd. All rights reserved.
Introduction The recent and expected continuing surge in food prices has reignited concern among oil-rich but agriculture-poor GCC1 countries about their vulnerability to food supply shocks. In the United Arab Emirates (UAE)2, the focus of this paper, some of the countermeasures being taken include increasing domestic agricultural production, building food stocks, and buying more farmland in other countries (Gulf Newsa, 2011). For its part, the UAE Ministry of Economy’s Consumer Protection Department regulates food prices by requiring retailers to get permission from the Ministry prior to raising them. In May 2011, the Ministry introduced plans to cap or reduce prices of more than 400 food items until December 2011 (The National, 2011). As one official put it, ‘‘It is a social responsibil-
⇑ Corresponding author at: Department of Agricultural Economics, University of Nebraska, Lincoln, NE, USA. E-mail address: [email protected] (A.M. Azzam). 1 GCC stands for Gulf Cooperating Council. The Council’s members are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates. 2 UAE is a federation comprised of seven Emirates: Abu Dhabi, Dubai, Sharjah, Ra’s Al Kaimah, Umm al-Qaiwain, and Fujairah. The seat of the federal government is in Abu Dhabi. Total UAE population is estimated at 8.9 million, of which less than 15% are native Emiratis. Although each Emirate enjoys considerable autonomy, several areas, including food pricing policy, remain under the purview of the federal government. 0306-9192/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foodpol.2012.05.003
ity towards the country they [food suppliers] live in to bear some of the cost’’ (Gulf Newsb, 2011).3 Concern about food supply shocks in the UAE is not unfounded. First, due to harsh desert conditions and consequent scarcity of water, domestic agricultural production is limited and miniscule compared to food imports. Based on most recent FAO estimates, agricultural production in the UAE was valued at 463 million USD in 2008, with dates accounting for almost half of the value (Table 1). On the other hand, the average value of food imports between 2005 and 2010 was over 7 billion USD (Table 2) and projected to increase to 9 billion by 2013 (BMI, 2011). Second, with the exception of the lull in food commodity prices between 2008 and 2009, believed to be largely driven by declining world demand due to the financial crisis, the year-to-year changes in commodity prices since 2003 suggest a structural break from the pre-2003 period of declining food prices. Not only have the yearto-year increases in prices become more frequent between 2003 and 2010, the magnitudes of the increases have also become higher (Table 3). Cereals, oils, and sugar registered some of the largest increases.
3 In addition to imposing food price controls, UAE also subsidies gasoline and several basic services for the benefit of expatriates as well as native Emiratis. However, other subsidies (water, electricity, and education, to mention a few) are targeted specifically to native Emiratis.
A.M. Azzam, B. Rettab / Food Policy 37 (2012) 554–560 Table 1 UAE agricultural production – 2008. FAO-Statistics. Rank
Commodity
Value (mil US $)
Output (Metric tons)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Dates Tomatoes Indigenous chicken meat Vegetables fresh nes Indigenous camel meat Indigenous cattle meat Indigenous goat meat Hen eggs, in shell Camel milk, whole, fresh Goat milk, whole, fresh Indigenous sheep meat Sheep milk, whole, fresh Onions (Inc. shallots), green Eggplants (aubergines) Pumpkins, squash and gourds Lemons and limes Cow milk, whole, fresh Cucumbers and gherkins Cauliflowers and broccoli Cabbages and other brassicas
217.86 50.94 39.59 26.27 23.61 19.20 13.94 12.85 12.78 10.85 6.57 4.07 3.73 3.54 3.52 3.21 3.19 2.90 2.60 2.57
755,000 215,000 33,938 140,000 16,848 9284 9152 17,200 40,000 36,000 3321 12,000 16,500 22,000 20,000 12,300 12,000 17,200 11,500 17,500
Total
463.79
Table 2 UAE food imports (2005–2010). Source: Compiled from Dubai Customs Data. Rank
Food group
Value (U$ million)
Share (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Cereals Edible fruits, nuts Coffee, tea, mate and spices Meat and edible meat offal Dairy produce, honey and edible Edible vegetables Oil seeds Sugars and sugar confectionery Miscellaneous edible preparations Preparations of cereals, flour Animal or vegetable fats, oils Preparations of vegetables Tobacco and manufactured tobacco Cocoa and cocoa preparations Beverages, spirits and vinegar Fish, crustaceans, molluscs Preparations of meat and fish Live animals Products of the milling industry Residues and waste of food industries Live trees, plants and their products Lac, gums, resins Vegetable plaiting materials Products of animal origin n.e.s
6310 4241 3103 2989 2558 2488 2226 2090 2068 1269 1193 1192 1183 1052 897 792 553 329 218 218 160 50 18 12
16.96 11.40 8.34 8.03 6.88 6.69 5.98 5.62 5.56 3.41 3.21 3.20 3.18 2.83 2.41 2.13 1.49 0.88 0.59 0.59 0.43 0.13 0.05 0.03
Total
37,208
By some accounts (Nomura, 2010), the world is in for a long period of rising food prices. The reason is that while global demand for food will continue to increase because of growing population and income, shifting diets from grains to meats, and diversion of grains to biofuels, global supply of food will continue to lag behind because of declining agricultural productivity, increasing water scarcity, and diversion of land to biofuels. The rise in food prices is also exacerbated by climate change, increased speculation in commodity markets, rising oil prices, and depreciation of the dollar, border protection, and agricultural subsidies. How vulnerable the UAE actually is to food supply shocks is an issue that has, to our knowledge, not been addressed using formal economic analysis and measurement. The most we could find are broad government statements from the different Emirates; state-
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ments not dissimilar to the following excerpt from the Annual Economic Report on Commodity Activities issued by the Department of Economic Development in the Emirate of Abu Dhabi: ‘‘There is no doubt that agriculture plays an important role in the stability of food prices in the domestic markets; as inadequate agricultural production makes the emirate vulnerable to fluctuations in food prices in global markets; and consequently impinges on inflation rates a result of depending on importing from abroad. The relative importance of food, beverages and tobacco amounted to about 16% of the total consumer basket in the Emirate of Abu Dhabi in 2009; and consequently, the low-income groups would be affected by increases in prices of food commodities, in comparison to high-income groups. This is attributed to the high proportion of spending on food commodities, where expenditure on food commodities relative to income, amounted to 28.7% for low-income groups, compared to about 14.8% for the high-income groups, according to the income and household expenditure survey, conducted in 2007/2008’’ (UAE-Interact, 2010). In essence, the central concern is vulnerability to fluctuations in food prices and consequent effect on consumers, especially consumers in low income brackets. In the light of this concern, the objective of this paper is to provide an analytical framework for measuring UAE consumer vulnerability to price increases of multiple imported food products. We define vulnerability as the change in consumer welfare, measured by the Hicksian compensating variation (CV), relative to income.4 Consideration of multiple price increases within the CV framework requires estimates of compensated food-import demand elasticities. We obtain the elasticities by estimating an Almost Ideal Demand System (AIDS) model of UAE food imports of 7 commodity groups using monthly import data from 2005 to 2010. The rest of the paper is structured as follows. The next section derives the CV model. The third section presents the AIDS estimates of the compensated elasticities. The fourth section presents results for a 7 commodity CV model. Estimates of welfare changes by food group and by income group are in the fifth section. The sixth section lays out some implications of our results for UAE food pricing policy. Summary, conclusions, and limitations are in the last section. CV with multiple price changes: theory It is well established in economic theory that while the change in Marshallian surplus in the case of multiple price changes is not well defined because of the path dependence problem, the change in Hicksian surplus is unique because it is not affected by the order in which prices are reduced or increased (Just et al., 2004, pp. 141– 150). The Hicksian surplus can be measured using either CV or equivalent variation (EV). In our context of rising food prices, CV is the minimum amount UAE consumers are willing to accept (WTA) to tolerate higher food prices and EV is the maximum amount UAE consumers are willing to pay (WTP) to avoid higher food prices. The focus of CV is on the welfare level prior to the increase in prices. The focus of EV is on the subsequent welfare level after the increase in prices. In the absence of income effects, both CV and EV are equivalent to the change in Marshallian surplus, so the choice between the two measures is immaterial. In the presence of income effects, as 4 At a more intuitive level, CV can be interpreted in three different ways: the Income taken away from a consumer that is equivalent to a rise in food prices, the tax equivalent of a rise in food prices, or what we would have to give the consumer after the increase in food prices to make him/her just as well off as he/she was before the price change.
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A.M. Azzam, B. Rettab / Food Policy 37 (2012) 554–560
Table 3 Yearly percent changes in FAO food commodity price indices. Date
Meat price index
Dairy price index
Cereals price index
Oils price index
Sugar price index
6.33 19.89 11.36 2.69 33.19 0.19 3.90 5.75 12.87 10.56 12.17 23.19 15.66 28.94 10.36 5.46 65.99 3.38 35.53 41.60 14.03
0.68 5.58 2.82 5.04 14.26 17.90 20.37 10.93 9.58 6.33 1.96 9.72 3.70 9.49 3.67 17.47 37.32 42.58 26.97 5.12 37.87
7.02 6.48 1.99 31.98 10.18 11.02 1.17 15.46 29.51 25.94 0.31 28.71 15.85 11.27 7.60 8.05 50.98 33.32 33.48 28.70 41.11
28.58 1.01 10.68 20.82 9.68 9.99 4.87 21.54 29.74 30.45 5.65 20.27 2.87 1.12 38.00 49.35 31.76 26.98 41.71 17.37 33.61
%change 1990–1991 1991–1992 1992–1993 1993–1994 1994–1995 1995–1996 1996–1997 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011
1.14 0.16 5.68 2.61 2.98 8.43 4.08 16.22 5.26 2.02 0.72 7.20 8.07 17.48 5.69 1.37 5.57 22.49 13.24 14.34 10.11
is most certainly to be the case in food demand, the change in Marshallian surplus resulting from a rise in food prices is bounded from below by EV and from above by CV. One approach in this case is to invoke Willig’s (1976) argument and assume the difference between CV and EV is too small to have practical relevance and use Marshallian surplus. Willig argued that ‘‘in most applications the error of approximation will be very small. In fact, the error will be overshadowed by the errors involved in estimating the demand curve.’’ (p. 689). Willig’s point, however, is not valid for multiple price changes. The other approach is to base the choice between CV and EV on the ‘‘property right’’ implied by the two measures (Freeman, 1993, p. 58). The property right implied by EV is in the price increase, so EV is interpreted as the WTP to avoid the price increase. The property right implied by CV is in the status quo, so CV is interpreted as the WTA compensation for the price increase. We argue in this paper that the appropriate measure of welfare change in the context of food price increases is CV rather than EV, implying that consumers have the ‘‘right’’ (are entitled) to the initial level of well-being (the status quo or the level before the price rise) and therefore must be compensated for the deterioration in well-being caused by the rise in food prices. Had the UAE government felt their citizens and residents are not entitled to food availability at affordable prices, food security would not be such a concern and neither would be the effect of rising food prices on the welfare of low income groups. Moreover, the UAE government would not go as far as declaring that it is the retailers’ social responsibility to lower food prices. The starting point of the CV model with multiple price changes is the consumer problem of minimizing expenditures on N food commodities subject to a utility level U0. Substitution of the resulting optimal Hicksian quantities into the expenditure equation yields the minimized expenditure function:
Denoting the initial and the subsequent periods by superscripts ‘‘0’’ and ‘‘1’’, respectively, consumer WTA to tolerate higher prices is given by 5 o o 0; 1 0 0 CV ¼ Eðp11 ; p1; 2 . . . ; pN ; U Þ Eðp1 ; p2 . . . ; pN ; U Þ
Using (1), we can expand (2) as follows: o o 1; 1 0 0 1 H 1 1 CV ¼ p11 qH1 ðp11 ; p1; 2 . . . ; pN ; U Þ p1 q1 þ p2 q2 ðp1 ; p2 . . . ; pN ; U Þ o 1 0 0 p02 q02 þ þ p1N qHN ðp11 ; p1; 2 . . . ; pN ; U Þ pN qN
dpi ¼ p1i p0i H
dqi ¼ qHi q0i
¼
for i ¼ 1; 2; . . . ; N for i ¼ 1; 2; . . . ; N
and substituted into (3), CV can be approximated by H
CV ¼ p01 q01
H
dp1 dq1 dp1 dq1 þ 0 þ 0 p01 q1 p1 q01 H
þ
p02 q02
E ¼ Eðp1 ; p2 ; ; pN ; U Þ þ
þ pN qHN ðp1 ; p2 ; ; pN ; U 0 Þ
!
H
dp2 dq2 dp2 dq2 þ 0 þ 0 p02 q2 p2 q02 H
þ p0N q0N
p2 qH2 ðp1 ; p2 ; ; pN ; U 0 Þ
ð3Þ
Note the following. Since the Hicksian demand function and the Marshallian demand function intersect in the initial period, the Hicksian quantity demanded and the Marshallian quantity demanded are the same and are given by the observed quantities consumed in the initial period, i.e., q0i for i = 1, 2, , N. In the subsequent period, however, the two functions diverge. As a consequence, the Hicksian quantity in the subsequent period is located on the Hicksian demand function. Direct measurement of CV using (3) is not possible because the Hicksian demand functions qHi ðÞ for i = 1, 2, , N depend on the utility level U0, which is unobservable. However, as shown by Huang (1993), if the respective changes in prices and Hicksian quantities are defined as
0
p1 qH1 ðp1 ; p2 ; ; pN ; U 0 Þ
ð2Þ
!
H
dpN dqN dpN dqN þ 0 þ 0 p0N qN pN q0N
þ ... ! ð4Þ
ð1Þ
where pi for i = 1, 2, , N are the respective prices of the N commodities, and the superscript H stands for Hicksian.
5 Graphically, CV is the vertical distance between the budget line tangent to the initial utility level U0 and the parallel budget line tangent to the subsequent utility level U1. The vertical distance is what is known as the income effect.
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A.M. Azzam, B. Rettab / Food Policy 37 (2012) 554–560 Table 4 Hicksian elasticities of UAE food import demand (2005–2010).
Cereals Meats Fish Dairy Oils Fruits Vegetables
Cereals
Meats
Fish
Dairy
Oils
Fruits
Vegetables
0.874 0.226 0.194 0.128 0.628 0.404 0.449
0.115 0.521 0.179 0.255 0.863 0.262 0.193
0.027 0.050 0.782 0.010 0.108 0.060 0.121
0.048 0.187 0.028 0.554 0.196 0.142 0.417
0.109 0.296 0.133 0.091 1.436 0.028 0.097
0.364 0.465 0.378 0.343 0.146 1.334 0.731
0.151 0.127 0.287 0.375 0.187 0.272 1.345
Table 5 Compensating variation estimate using Eq. (4). A Imports in December 2010 (mil US $) Cereals Meats Fish Dairy Oils Fruits Vegetables
41.681 21.424 6.182 13.621 4.393 38.126 19.994
Total a
B Change in pricesa (%)
C Change in quantities (%)
D Compensating variation (mil US $)
9.00 4.00 0.00 6.00 13.00 0.00 0.00
5.70 2.68 2.59 2.01 8.39 5.90 4.51
1.161 1.453 0.160 0.527 0.155 2.249 0.902
18 22 2 8 2 34 14
6.608
100
145.421
E Proportion of CV (%)
For December 2010 to January 2011.
The approximation shows that CV is a proportional sum of expenditures on the N commodities in the initial period. Each proportion consists of the sum of the percentage change in prices, the percentage change in Hicksian quantities, and the product of the two percentage changes. Expenditures on the N commodities in the initial period are observable, and so are the percentage changes in prices. The percentage change in Hicksian quantities is not observed. However, an approximation of the change is obtained though the total differential of the Hicksian demand functions qHi ðÞ for i = 1, 2, , N, i.e.,
ð5Þ
H
dqN dp dp dp HN1 1 þ HN2 2 þ þ HNN N p1 p2 pN q0N where Hij is the Hicksian price elasticity for i = 1, 2, N and j = 1, 2, N. Estimation of Hicksian price elasticities of demand To estimate the Hicksian price elasticities as shown in (5), we proceed in two steps. First, we estimate an Almost Ideal Demand System (AIDS) model for N commodities by imposing the usual restrictions: adding-up, homogeneity, and symmetry (Deaton and Muelbauer, 1980). Second we compute the elasticities from the estimated parameters of the AIDS model.The AIDS model is N X
cij lnpj þ bi ln
j¼1
X P
The respective formulas for computing the Hicksian own- and cross-price elasticities for the N food groups are:
ð7Þ
and
H
W i ¼ ai þ
P P P Adding up: Ni¼1 ai ¼ 1; Ni¼1 bi ¼ 0; Ni¼1 cij ; for j = 1, 2, , N; PN Homogeneity of degree zero: j¼1 cij ¼ 0; for i = 1, 2, , N; and Symmetry: cij = cji.
Hii ¼ 1 þ ðcii =W i Þ þ W i
H
dq1 dp dp dp H11 1 þ H12 2 þ þ H1N N p1 p2 pN q01 dq2 dp dp dp H21 1 þ H22 2 þ þ H2N N p1 p2 pN q02 .. .
N; X isthe xpenditure on the N food groups and P is the Stone price PP P index defined by ln P ¼ a0 þ aj ln pj þ 12 cij ln pi pj . The restrictions are:
ð6Þ
where Wi is the Share of food group i in total expenditure on the N food groups, for i = 1, 2, , N; pj is the of food group j, j = 1, 2, ,
Hij ¼ ðcij =W i Þ þ W j
ð8Þ
We estimated Eq. (6) using monthly import data from 2005 to 2010 for the following 7 food groups: Cereals, meats, fish, dairy, edible oils, fruits, and vegetables. The price and quantity data was compiled by the Dubai Chamber of Commerce and Industry from The Dubai External Trade Statistics database (DETC, 2005– 2010). The computed elasticities using formulas (7) and (8) are in Table 4. The 7 diagonal elements in the table represent the ownprice elasticities computed using (7). The 42 cross-price elasticities off-diagonal are computed using Eq. (8).6 CV with multiple price changes: Application As shown in the previous section, implementation of Eq. (4) requires data on expenditures by commodity, percent price changes between an initial period and a subsequent period, and percent changes in Hicksian quantities as approximated by (5). We designate December 2010, the last month in our data set, as the initial 6 Note that while total expenditure or income is deflated by the Stone price index in the AIDS model (equation 6), prices remain in nominal terms. Deflating prices, by the CPI or any other deflator, for example, is unnecessary when homogeneity of degree zero is imposed (see Lee and Brown, 1996). Besides, even if deflating prices was necessary, the UAE has no monthly deflators available.
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Table 6 Welfare losses by food group and income group and vulnerability by income group. Income group Lowest 20%
Second quintile
Third quintile
Fourth quintile
Highest 20%
Cereals Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
40.09 18.99 18.00 7.22
47.80 18.43 18.00 8.60
60.34 17.45 18.00 10.86
70.47 16.58 18.00 12.68
126.52 15.24 18.00 22.77
Meats Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
46.53 22.04 22.00 10.24
58.47 22.55 22.00 12.86
83.55 24.16 22.00 18.38
107.74 25.35 22.00 23.70
259.11 31.20 22.00 57.00
Fish Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
18.32 8.68 2.00 0.37
23.56 9.08 2.00 0.47
34.76 10.05 2.00 0.70
45.08 10.61 2.00 0.90
93.91 11.31 2.00 1.88
Dairy Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
36.05 17.07 8.00 2.88
44.61 17.20 8.00 3.57
56.78 16.42 8.00 4.54
68.47 16.11 8.00 5.48
118.71 14.30 8.00 9.50
Oils Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
9.06 4.29 2.00 0.18
10.68 4.12 2.00 0.21
13.71 3.96 2.00 0.27
16.15 3.80 2.00 0.32
27.63 3.33 2.00 0.55
Fruits Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
22.62 10.71 34.00 7.69
29.45 11.36 34.00 10.01
41.54 12.01 34.00 14.12
55.28 13.01 34.00 18.80
107.86 12.99 34.00 36.67
Vegetables Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $) Total household monthly expenditure (US $) Total welfare loss (CV in US $) Average monthly household income (US $) Expenditure relative to income (%) Vulnerability (total welfare loss relative to income) (%)
38.46 18.22 14.00 5.38 211.13 33.96 984.74 21.44 3.45
44.76 17.26 14.00 6.27 259.32 42.00 2076.93 12.49 2.02
55.16 15.95 14.00 7.72 345.83 56.60 3352.05 10.32 1.69
61.85 14.55 14.00 8.66 425.03 70.54 5581.10 7.62 1.26
96.62 11.64 14.00 13.53 830.36 141.90 14799.73 5.61 0.96
Food group
period and January 2011 as the subsequent period. Column A in Table 5 lists the December 2010 expenditures by commodity. Expenditure on each commodity is equal to the value of imports of that commodity. The percentage changes in commodity prices between December 2010 and January 2011 (Table 5, column B) are equal to the percentage changes in the FAO commodity price index between the two months. Since the FAO commodity indices do not include fish, fruits, and vegetables, we initially set their respective price changes to zero. Column C lists the changes in respective commodities’ Hicksian quantities, and column D gives the CV for each commodity. Results show that the welfare losses from the price increases in cereals, meats, dairy, and oils, amount to 6.608 million USD. The losses represent 5.54% of the value of imports of all 7 commodities in December 2010 (145.421 million USD). It is worth nothing that although we assumed no price increases for fish, fruits, and vegetables, CV from the 3 commodities were non-zero because of the cross-effects between the 7 commodities. Assuming a uniform price increase of 10% for the 3 commodities yielded a welfare loss of 12.162 million USD, about 8.36% of the total December 2010 value of imports. Suppression of cross-effects lowers CV from 6.609 to 1.005 million USD, a mere 0.69% of the total value of imports in December 2010.
Vulnerability of UAE consumers to rising food prices by income group The income groups we use for analysis are the same as those published in the 2007–2008 UAE household income and expenditure survey, the most recent survey conducted by the UAE National Bureau of Statistics. There are 5 groups: the lowest 20%, the second, third, and fourth quintiles, and the highest 20%. For each income group, we extract from the survey the average monthly expenditure for each of the 7 commodities for which we calculated CV in the previous section. Referring to Table 6, the first row under each food-group heading gives the average monthly expenditure in USD by income group and the second row the share of each food group in total expenditure on all food groups. For cereals, for example, the respective income groups’ per-capita monthly expenditures are 40.09, 47.80, 60.34, 70.47, and 126.52 USD. Note that the expenditure share increases with declining monthly income for cereals, dairy, oils, and vegetables; and increases with rising monthly income for meats fish, and fruits. The third row after each food-group heading is the proportion of CV attributed to the food group. The proportions, which are taken from column E in Table 5, are identical for the different income
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groups within each food group. The fourth row after each foodgroup is the proportion of CV attributed to that food-group by income group. Multiplication of each income group’s respective monthly expenditures by the welfare weight yields the respective amounts of CV attributed to the food group. For dairy, for example, the weight is 8% and the respective CV amounts for the income groups are 2.88, 3.57, 4.54, 5.48, and 9.50 USD, respectively. The last five rows of Table 6 are total monthly expenditure on the 7 food groups, total CV, average monthly household income, household expenditure relative to income, and the welfare measure of vulnerability (total CV relative to income) by income group. Clearly, while absolute expenditure on the 7 food groups rises with rising income, the proportion of income spent on food declines with rising income. The highest 20% income group spends almost four times as much on food as does the lowest 20% group. Average expenditure on food by the top 40% of households is 1.5 times the average expenditure on food by the bottom 60%. However, the proportion spent by the highest 20% income group is 0.26% the proportion spent by the lowest 20% income group. Also, the relative spending of the latter group is only 2% points below the relative spending of the top 60% of the households. The 5 income groups’ respective CVs are 33.93, 42.00, 56.60, 70.54, and 141.90 USD. The CVs represent the income equivalent of 5 income groups’ respective deterioration in well-being (welfare loss) caused by the price increases as shown in Table 5, column B. Though the welfare loss rises with rising income, the loss relative to income increases with declining income, making the least well-off the most vulnerable to rising food prices. The income groups’ respective measures of vulnerability are 3.45%, 2.02%, 1.69%, 1.26%, and .96%. Households in the lowest income group are 3.5 times more vulnerable to rising food imports than household in the highest income group.
starting point for a conversation about how to devise ‘‘targeted solutions for people who are in need.’’ rather than ‘‘keeping prices artificially low.’’ Although the quoted editorial does not spell out exactly what those costs are7, a recent report summarizing the key points of roundtable discussion between meat traders and retailers at the Dubai Chamber of Commerce and Industry gives a glimpse of some of the undesirable consequences of prices caps:
Some implications for UAE food pricing policy
Defining vulnerability as the change in consumer welfare from multiple price changes relative to income, this paper uses the Hicksian compensating variation (CV) to measure the welfare change by food group and by income group in the UAE. Using estimates of compensated own- and cross-elasticities of 7 food groups (cereals, meats, fish, dairy, oils, fruits, and vegetables) imported by the UAE, we estimate CV based on changes in international food prices between December 2010 and January 2011. The CV suggests a consumer welfare loss of 6.6 million USD, approximately 4.5% of the total value of the 7 food groups imported by the UAE in December 2010. The respective CVs of the 5 income groups we considered are 33.93, 42.00, 56.60, 70.54, 141.90 USD. Though the absolute welfare loss increases with rising income, the loss relative to income increases with declining income, making the least well-off
To gage some of the policy implications of our findings it is helpful to interpret CV as the (indirect) income tax equivalent of a rise in food prices (see footnote 3). With that interpretation, the measure of vulnerability is the same as the income tax-rate equivalent of the (percentage) increase in food prices shown in Table 5. So being most vulnerable is the same as bearing the heaviest ‘‘tax burden’’. It follows that the concern in the UAE about the vulnerability of low income groups to rising food prices can be translated into a concern about the regressivity of the ‘‘tax burden’’. The compensating variation estimates gives an idea of how much ‘‘food allowance’’ or ‘‘supplementary income’’ in dollars the government could transfer to low income groups to mitigate the burden. Based on our results in this paper, if, for example, the target for assistance are the lowest income households, then each household should receive a government check for 33.93 USD. As described earlier in the paper, the current food pricing policy in the UAE is to place price caps on food items with the expectation that retailers, not the government, bear the cost. The food retailing business perspective on the policy is best summarized by excerpts from a recent editorial in The National (2011): ...The policy is ‘‘right for the population’’ but ‘‘has had an effect on our [food retailer] margins’’. . .Price caps are blunt economic tools, benefitting every one – from the wealthy executive to the street sweeper – rather than offering targeted solutions for people who are actually in need. Cheap food is popular. But in economics terms, it’s worth remembering that there are costs to keeping prices artificially low. With further refinements, as we discuss in the next section, the approach and results we lay out in this paper could serve as a
‘‘Price caps enacted in May 2011 on over 400 staple goods by the Ministry of the Economy have led to isolated shortages. According to participants of the roundtable, it has also led to: an immediate degradation in quality of the nation’s food supply, changes in package sizes, and retailers’ business models. Package sizes have diminished considerably in light of price caps. Hamburger patties that previously contained 75% meat now sell with only 50%. What manufacturers would have sold in a 250 gram package is now sold in 150 grams, at the same price. Higher grade meat imports that fit the controlled categories ceased almost instantaneously. Meat products that were superior by type of feed or method of rearing were no longer brought into the country given that importers were no longer able to recoup costs. Traders started to favor meat from Africa and other less developed markets in order to match established price points. The quality of available meat was therefore downgraded on an aggregate level, while only products destined to high-end outlets continued unhindered given a lack of price controls. Catering establishments and low-end restaurants serving frozen meat were the first to be negatively affected.’’ (Malesa, 2011, pp. 7–8).8
Summary, conclusions, and limitations
7 An anonymous reviewer, citing the study by Ng et al. (2011), suggested that ‘‘given that a large proportion of Emiratis (natives) are overweight or obese, . . .could it be possible that food price increases might actually be ’good’ for the health (and potentially long-term wealth) of the country despite being ’bad’ for the pocket in the short-term? While plausible, it is also plausible that higher food prices may actually induce consumers to substitute unhealthy foods (like burgers and fries) for healthy foods (like vegetables). Moreover, our study is not restricted to Emiratis only. It encompasses the expatriate population also. 8 The deterioration in product quality reported by retailers in the roundtable discussion is consistent with the prediction of economic theory when a price cap is imposed on perfectly competitive firms (Raymon, 1983). When a price cap is imposed on a firm with monopoly power, the firm is predicted to improve quality only at the low end of the market (Besanko et al., 1987). Abstracting from quality issues, it is well known in economic theory that while price caps lead to shortages in perfectly competitive markets, they can lead to increased output when firms have market power and, under certain conditions, to an output level equivalent to that produced in a perfectly competitive markets without price caps (Browning and Browning, 1986, p. 367)
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household the most vulnerable to rising food prices. The income groups’ respective measures of vulnerability are 3.45%, 2.02%, 1.69%, 1.26%, and .96%. This reveals that although the poorest households spend on food less than a quarter of what the wealthiest households spend, the former are 3.5 times more vulnerable to rising prices food imports than the latter. By re-interpreting the measures of vulnerability as tax-rate equivalents of the assumed food price increases, we have suggested that CV represents the dollar amount of ‘‘food allowance’’ or ‘‘supplementary income’’ the government could provide households in the low income group(s) as compensation for higher food prices. In light of the some potentially undesirable economic consequences of imposing price caps, both in theory and in practice, we believe that our approach and results could serve as a starting point for a conversation about considering targeting compensation to low income consumers as an alternative to imposing price caps. There are, however, two limitations of our study that should be addressed in order to add more precision to our results. First and foremost is the assumption that compensated elasticities apply to all income groups and ethnic groups. The assumption is dictated by availability of aggregate data only. To estimate group specific elasticities and use the elasticities to approximate CVs for, say, native Emiratis and expatriates by income group would require panel household data. This will go a long way in rationalizing ‘‘offering targeted solutions for people who are actually in need’’ be they Emiratis, expatriates, or both. A second limitation is use of aggregate food groups rather than individual food items. The ideal set of food items would be those that are currently the candidates for price caps. However, since the items number in the hundreds, estimating their respective own- and cross-price elasticities would exhaust degrees of freedom quickly whether one uses aggregate data, as we did, or panel household data.
References Besanko, D., Donnelfeld, S., While, L.J., 1987. Monopoly and quality distortion: effects and remedies. Quarterly Journal of Economics 102, 747–767. Browning, E.K., Browning, J.M., 1986. Microeconomic Theory and Applications. Little, Brown, and Company, Boston. (BMI) Business Monitor International, 2011. United Arab Emirates Food and Drink Report. Q1 Report. Deaton, A., Muelbauer, J., 1980. An almost ideal system. American Economic Review 70, 312–326. DETC (Dubai External Trade Statistics), 2005–2010. Purchased in CD-ROM by the Dubai Chamber of Commerce and Industry from the Ports, Customs and Free Zone Corporation for 2005–2010. Food and Agriculture Organization (FAO) Statistics.. Willig, R.D., 1976. Consumer’s surplus without apology. American Economic Review 66, 589–597.
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Food Policy journal homepage: www.elsevier.com/locate/foodpol
A welfare measure of consumer vulnerability to rising prices of food imports in the UAE Azzeddine M. Azzam a,b,c,⇑, Belaid Rettab d a
Department of Economics, University of Dubai, Dubai, United Arab Emirates Dubai Chamber, Dubai, United Arab Emirates c Department of Agricultural Economics, University of Nebraska, Lincoln, NE, USA d Economic Research & Sustainable Business, Dubai Chamber, Dubai, United Arab Emirates b
a r t i c l e
i n f o
Article history: Received 15 June 2011 Received in revised form 25 April 2012 Accepted 20 May 2012
Keywords: Food imports Vulnerability Welfare Compensating variation Price caps United Arab Emirates
a b s t r a c t The recent and expected continuing rise in food prices has re-ignited concern and discussion in the United Arab Emirates about the country’s vulnerability to food supply shocks. Defining vulnerability as the compensating variation relative to household income, we find that although UAE households in the lowest income quintile spend on food on average less than a quarter of what households in the highest income quintile spend, the former are 3.5 times more vulnerable to rising prices of food imports than the latter. Ó 2012 Elsevier Ltd. All rights reserved.
Introduction The recent and expected continuing surge in food prices has reignited concern among oil-rich but agriculture-poor GCC1 countries about their vulnerability to food supply shocks. In the United Arab Emirates (UAE)2, the focus of this paper, some of the countermeasures being taken include increasing domestic agricultural production, building food stocks, and buying more farmland in other countries (Gulf Newsa, 2011). For its part, the UAE Ministry of Economy’s Consumer Protection Department regulates food prices by requiring retailers to get permission from the Ministry prior to raising them. In May 2011, the Ministry introduced plans to cap or reduce prices of more than 400 food items until December 2011 (The National, 2011). As one official put it, ‘‘It is a social responsibil-
⇑ Corresponding author at: Department of Agricultural Economics, University of Nebraska, Lincoln, NE, USA. E-mail address: [email protected] (A.M. Azzam). 1 GCC stands for Gulf Cooperating Council. The Council’s members are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates. 2 UAE is a federation comprised of seven Emirates: Abu Dhabi, Dubai, Sharjah, Ra’s Al Kaimah, Umm al-Qaiwain, and Fujairah. The seat of the federal government is in Abu Dhabi. Total UAE population is estimated at 8.9 million, of which less than 15% are native Emiratis. Although each Emirate enjoys considerable autonomy, several areas, including food pricing policy, remain under the purview of the federal government. 0306-9192/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foodpol.2012.05.003
ity towards the country they [food suppliers] live in to bear some of the cost’’ (Gulf Newsb, 2011).3 Concern about food supply shocks in the UAE is not unfounded. First, due to harsh desert conditions and consequent scarcity of water, domestic agricultural production is limited and miniscule compared to food imports. Based on most recent FAO estimates, agricultural production in the UAE was valued at 463 million USD in 2008, with dates accounting for almost half of the value (Table 1). On the other hand, the average value of food imports between 2005 and 2010 was over 7 billion USD (Table 2) and projected to increase to 9 billion by 2013 (BMI, 2011). Second, with the exception of the lull in food commodity prices between 2008 and 2009, believed to be largely driven by declining world demand due to the financial crisis, the year-to-year changes in commodity prices since 2003 suggest a structural break from the pre-2003 period of declining food prices. Not only have the yearto-year increases in prices become more frequent between 2003 and 2010, the magnitudes of the increases have also become higher (Table 3). Cereals, oils, and sugar registered some of the largest increases.
3 In addition to imposing food price controls, UAE also subsidies gasoline and several basic services for the benefit of expatriates as well as native Emiratis. However, other subsidies (water, electricity, and education, to mention a few) are targeted specifically to native Emiratis.
A.M. Azzam, B. Rettab / Food Policy 37 (2012) 554–560 Table 1 UAE agricultural production – 2008. FAO-Statistics. Rank
Commodity
Value (mil US $)
Output (Metric tons)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Dates Tomatoes Indigenous chicken meat Vegetables fresh nes Indigenous camel meat Indigenous cattle meat Indigenous goat meat Hen eggs, in shell Camel milk, whole, fresh Goat milk, whole, fresh Indigenous sheep meat Sheep milk, whole, fresh Onions (Inc. shallots), green Eggplants (aubergines) Pumpkins, squash and gourds Lemons and limes Cow milk, whole, fresh Cucumbers and gherkins Cauliflowers and broccoli Cabbages and other brassicas
217.86 50.94 39.59 26.27 23.61 19.20 13.94 12.85 12.78 10.85 6.57 4.07 3.73 3.54 3.52 3.21 3.19 2.90 2.60 2.57
755,000 215,000 33,938 140,000 16,848 9284 9152 17,200 40,000 36,000 3321 12,000 16,500 22,000 20,000 12,300 12,000 17,200 11,500 17,500
Total
463.79
Table 2 UAE food imports (2005–2010). Source: Compiled from Dubai Customs Data. Rank
Food group
Value (U$ million)
Share (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Cereals Edible fruits, nuts Coffee, tea, mate and spices Meat and edible meat offal Dairy produce, honey and edible Edible vegetables Oil seeds Sugars and sugar confectionery Miscellaneous edible preparations Preparations of cereals, flour Animal or vegetable fats, oils Preparations of vegetables Tobacco and manufactured tobacco Cocoa and cocoa preparations Beverages, spirits and vinegar Fish, crustaceans, molluscs Preparations of meat and fish Live animals Products of the milling industry Residues and waste of food industries Live trees, plants and their products Lac, gums, resins Vegetable plaiting materials Products of animal origin n.e.s
6310 4241 3103 2989 2558 2488 2226 2090 2068 1269 1193 1192 1183 1052 897 792 553 329 218 218 160 50 18 12
16.96 11.40 8.34 8.03 6.88 6.69 5.98 5.62 5.56 3.41 3.21 3.20 3.18 2.83 2.41 2.13 1.49 0.88 0.59 0.59 0.43 0.13 0.05 0.03
Total
37,208
By some accounts (Nomura, 2010), the world is in for a long period of rising food prices. The reason is that while global demand for food will continue to increase because of growing population and income, shifting diets from grains to meats, and diversion of grains to biofuels, global supply of food will continue to lag behind because of declining agricultural productivity, increasing water scarcity, and diversion of land to biofuels. The rise in food prices is also exacerbated by climate change, increased speculation in commodity markets, rising oil prices, and depreciation of the dollar, border protection, and agricultural subsidies. How vulnerable the UAE actually is to food supply shocks is an issue that has, to our knowledge, not been addressed using formal economic analysis and measurement. The most we could find are broad government statements from the different Emirates; state-
555
ments not dissimilar to the following excerpt from the Annual Economic Report on Commodity Activities issued by the Department of Economic Development in the Emirate of Abu Dhabi: ‘‘There is no doubt that agriculture plays an important role in the stability of food prices in the domestic markets; as inadequate agricultural production makes the emirate vulnerable to fluctuations in food prices in global markets; and consequently impinges on inflation rates a result of depending on importing from abroad. The relative importance of food, beverages and tobacco amounted to about 16% of the total consumer basket in the Emirate of Abu Dhabi in 2009; and consequently, the low-income groups would be affected by increases in prices of food commodities, in comparison to high-income groups. This is attributed to the high proportion of spending on food commodities, where expenditure on food commodities relative to income, amounted to 28.7% for low-income groups, compared to about 14.8% for the high-income groups, according to the income and household expenditure survey, conducted in 2007/2008’’ (UAE-Interact, 2010). In essence, the central concern is vulnerability to fluctuations in food prices and consequent effect on consumers, especially consumers in low income brackets. In the light of this concern, the objective of this paper is to provide an analytical framework for measuring UAE consumer vulnerability to price increases of multiple imported food products. We define vulnerability as the change in consumer welfare, measured by the Hicksian compensating variation (CV), relative to income.4 Consideration of multiple price increases within the CV framework requires estimates of compensated food-import demand elasticities. We obtain the elasticities by estimating an Almost Ideal Demand System (AIDS) model of UAE food imports of 7 commodity groups using monthly import data from 2005 to 2010. The rest of the paper is structured as follows. The next section derives the CV model. The third section presents the AIDS estimates of the compensated elasticities. The fourth section presents results for a 7 commodity CV model. Estimates of welfare changes by food group and by income group are in the fifth section. The sixth section lays out some implications of our results for UAE food pricing policy. Summary, conclusions, and limitations are in the last section. CV with multiple price changes: theory It is well established in economic theory that while the change in Marshallian surplus in the case of multiple price changes is not well defined because of the path dependence problem, the change in Hicksian surplus is unique because it is not affected by the order in which prices are reduced or increased (Just et al., 2004, pp. 141– 150). The Hicksian surplus can be measured using either CV or equivalent variation (EV). In our context of rising food prices, CV is the minimum amount UAE consumers are willing to accept (WTA) to tolerate higher food prices and EV is the maximum amount UAE consumers are willing to pay (WTP) to avoid higher food prices. The focus of CV is on the welfare level prior to the increase in prices. The focus of EV is on the subsequent welfare level after the increase in prices. In the absence of income effects, both CV and EV are equivalent to the change in Marshallian surplus, so the choice between the two measures is immaterial. In the presence of income effects, as 4 At a more intuitive level, CV can be interpreted in three different ways: the Income taken away from a consumer that is equivalent to a rise in food prices, the tax equivalent of a rise in food prices, or what we would have to give the consumer after the increase in food prices to make him/her just as well off as he/she was before the price change.
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Table 3 Yearly percent changes in FAO food commodity price indices. Date
Meat price index
Dairy price index
Cereals price index
Oils price index
Sugar price index
6.33 19.89 11.36 2.69 33.19 0.19 3.90 5.75 12.87 10.56 12.17 23.19 15.66 28.94 10.36 5.46 65.99 3.38 35.53 41.60 14.03
0.68 5.58 2.82 5.04 14.26 17.90 20.37 10.93 9.58 6.33 1.96 9.72 3.70 9.49 3.67 17.47 37.32 42.58 26.97 5.12 37.87
7.02 6.48 1.99 31.98 10.18 11.02 1.17 15.46 29.51 25.94 0.31 28.71 15.85 11.27 7.60 8.05 50.98 33.32 33.48 28.70 41.11
28.58 1.01 10.68 20.82 9.68 9.99 4.87 21.54 29.74 30.45 5.65 20.27 2.87 1.12 38.00 49.35 31.76 26.98 41.71 17.37 33.61
%change 1990–1991 1991–1992 1992–1993 1993–1994 1994–1995 1995–1996 1996–1997 1997–1998 1998–1999 1999–2000 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2006–2007 2007–2008 2008–2009 2009–2010 2010–2011
1.14 0.16 5.68 2.61 2.98 8.43 4.08 16.22 5.26 2.02 0.72 7.20 8.07 17.48 5.69 1.37 5.57 22.49 13.24 14.34 10.11
is most certainly to be the case in food demand, the change in Marshallian surplus resulting from a rise in food prices is bounded from below by EV and from above by CV. One approach in this case is to invoke Willig’s (1976) argument and assume the difference between CV and EV is too small to have practical relevance and use Marshallian surplus. Willig argued that ‘‘in most applications the error of approximation will be very small. In fact, the error will be overshadowed by the errors involved in estimating the demand curve.’’ (p. 689). Willig’s point, however, is not valid for multiple price changes. The other approach is to base the choice between CV and EV on the ‘‘property right’’ implied by the two measures (Freeman, 1993, p. 58). The property right implied by EV is in the price increase, so EV is interpreted as the WTP to avoid the price increase. The property right implied by CV is in the status quo, so CV is interpreted as the WTA compensation for the price increase. We argue in this paper that the appropriate measure of welfare change in the context of food price increases is CV rather than EV, implying that consumers have the ‘‘right’’ (are entitled) to the initial level of well-being (the status quo or the level before the price rise) and therefore must be compensated for the deterioration in well-being caused by the rise in food prices. Had the UAE government felt their citizens and residents are not entitled to food availability at affordable prices, food security would not be such a concern and neither would be the effect of rising food prices on the welfare of low income groups. Moreover, the UAE government would not go as far as declaring that it is the retailers’ social responsibility to lower food prices. The starting point of the CV model with multiple price changes is the consumer problem of minimizing expenditures on N food commodities subject to a utility level U0. Substitution of the resulting optimal Hicksian quantities into the expenditure equation yields the minimized expenditure function:
Denoting the initial and the subsequent periods by superscripts ‘‘0’’ and ‘‘1’’, respectively, consumer WTA to tolerate higher prices is given by 5 o o 0; 1 0 0 CV ¼ Eðp11 ; p1; 2 . . . ; pN ; U Þ Eðp1 ; p2 . . . ; pN ; U Þ
Using (1), we can expand (2) as follows: o o 1; 1 0 0 1 H 1 1 CV ¼ p11 qH1 ðp11 ; p1; 2 . . . ; pN ; U Þ p1 q1 þ p2 q2 ðp1 ; p2 . . . ; pN ; U Þ o 1 0 0 p02 q02 þ þ p1N qHN ðp11 ; p1; 2 . . . ; pN ; U Þ pN qN
dpi ¼ p1i p0i H
dqi ¼ qHi q0i
¼
for i ¼ 1; 2; . . . ; N for i ¼ 1; 2; . . . ; N
and substituted into (3), CV can be approximated by H
CV ¼ p01 q01
H
dp1 dq1 dp1 dq1 þ 0 þ 0 p01 q1 p1 q01 H
þ
p02 q02
E ¼ Eðp1 ; p2 ; ; pN ; U Þ þ
þ pN qHN ðp1 ; p2 ; ; pN ; U 0 Þ
!
H
dp2 dq2 dp2 dq2 þ 0 þ 0 p02 q2 p2 q02 H
þ p0N q0N
p2 qH2 ðp1 ; p2 ; ; pN ; U 0 Þ
ð3Þ
Note the following. Since the Hicksian demand function and the Marshallian demand function intersect in the initial period, the Hicksian quantity demanded and the Marshallian quantity demanded are the same and are given by the observed quantities consumed in the initial period, i.e., q0i for i = 1, 2, , N. In the subsequent period, however, the two functions diverge. As a consequence, the Hicksian quantity in the subsequent period is located on the Hicksian demand function. Direct measurement of CV using (3) is not possible because the Hicksian demand functions qHi ðÞ for i = 1, 2, , N depend on the utility level U0, which is unobservable. However, as shown by Huang (1993), if the respective changes in prices and Hicksian quantities are defined as
0
p1 qH1 ðp1 ; p2 ; ; pN ; U 0 Þ
ð2Þ
!
H
dpN dqN dpN dqN þ 0 þ 0 p0N qN pN q0N
þ ... ! ð4Þ
ð1Þ
where pi for i = 1, 2, , N are the respective prices of the N commodities, and the superscript H stands for Hicksian.
5 Graphically, CV is the vertical distance between the budget line tangent to the initial utility level U0 and the parallel budget line tangent to the subsequent utility level U1. The vertical distance is what is known as the income effect.
557
A.M. Azzam, B. Rettab / Food Policy 37 (2012) 554–560 Table 4 Hicksian elasticities of UAE food import demand (2005–2010).
Cereals Meats Fish Dairy Oils Fruits Vegetables
Cereals
Meats
Fish
Dairy
Oils
Fruits
Vegetables
0.874 0.226 0.194 0.128 0.628 0.404 0.449
0.115 0.521 0.179 0.255 0.863 0.262 0.193
0.027 0.050 0.782 0.010 0.108 0.060 0.121
0.048 0.187 0.028 0.554 0.196 0.142 0.417
0.109 0.296 0.133 0.091 1.436 0.028 0.097
0.364 0.465 0.378 0.343 0.146 1.334 0.731
0.151 0.127 0.287 0.375 0.187 0.272 1.345
Table 5 Compensating variation estimate using Eq. (4). A Imports in December 2010 (mil US $) Cereals Meats Fish Dairy Oils Fruits Vegetables
41.681 21.424 6.182 13.621 4.393 38.126 19.994
Total a
B Change in pricesa (%)
C Change in quantities (%)
D Compensating variation (mil US $)
9.00 4.00 0.00 6.00 13.00 0.00 0.00
5.70 2.68 2.59 2.01 8.39 5.90 4.51
1.161 1.453 0.160 0.527 0.155 2.249 0.902
18 22 2 8 2 34 14
6.608
100
145.421
E Proportion of CV (%)
For December 2010 to January 2011.
The approximation shows that CV is a proportional sum of expenditures on the N commodities in the initial period. Each proportion consists of the sum of the percentage change in prices, the percentage change in Hicksian quantities, and the product of the two percentage changes. Expenditures on the N commodities in the initial period are observable, and so are the percentage changes in prices. The percentage change in Hicksian quantities is not observed. However, an approximation of the change is obtained though the total differential of the Hicksian demand functions qHi ðÞ for i = 1, 2, , N, i.e.,
ð5Þ
H
dqN dp dp dp HN1 1 þ HN2 2 þ þ HNN N p1 p2 pN q0N where Hij is the Hicksian price elasticity for i = 1, 2, N and j = 1, 2, N. Estimation of Hicksian price elasticities of demand To estimate the Hicksian price elasticities as shown in (5), we proceed in two steps. First, we estimate an Almost Ideal Demand System (AIDS) model for N commodities by imposing the usual restrictions: adding-up, homogeneity, and symmetry (Deaton and Muelbauer, 1980). Second we compute the elasticities from the estimated parameters of the AIDS model.The AIDS model is N X
cij lnpj þ bi ln
j¼1
X P
The respective formulas for computing the Hicksian own- and cross-price elasticities for the N food groups are:
ð7Þ
and
H
W i ¼ ai þ
P P P Adding up: Ni¼1 ai ¼ 1; Ni¼1 bi ¼ 0; Ni¼1 cij ; for j = 1, 2, , N; PN Homogeneity of degree zero: j¼1 cij ¼ 0; for i = 1, 2, , N; and Symmetry: cij = cji.
Hii ¼ 1 þ ðcii =W i Þ þ W i
H
dq1 dp dp dp H11 1 þ H12 2 þ þ H1N N p1 p2 pN q01 dq2 dp dp dp H21 1 þ H22 2 þ þ H2N N p1 p2 pN q02 .. .
N; X isthe xpenditure on the N food groups and P is the Stone price PP P index defined by ln P ¼ a0 þ aj ln pj þ 12 cij ln pi pj . The restrictions are:
ð6Þ
where Wi is the Share of food group i in total expenditure on the N food groups, for i = 1, 2, , N; pj is the of food group j, j = 1, 2, ,
Hij ¼ ðcij =W i Þ þ W j
ð8Þ
We estimated Eq. (6) using monthly import data from 2005 to 2010 for the following 7 food groups: Cereals, meats, fish, dairy, edible oils, fruits, and vegetables. The price and quantity data was compiled by the Dubai Chamber of Commerce and Industry from The Dubai External Trade Statistics database (DETC, 2005– 2010). The computed elasticities using formulas (7) and (8) are in Table 4. The 7 diagonal elements in the table represent the ownprice elasticities computed using (7). The 42 cross-price elasticities off-diagonal are computed using Eq. (8).6 CV with multiple price changes: Application As shown in the previous section, implementation of Eq. (4) requires data on expenditures by commodity, percent price changes between an initial period and a subsequent period, and percent changes in Hicksian quantities as approximated by (5). We designate December 2010, the last month in our data set, as the initial 6 Note that while total expenditure or income is deflated by the Stone price index in the AIDS model (equation 6), prices remain in nominal terms. Deflating prices, by the CPI or any other deflator, for example, is unnecessary when homogeneity of degree zero is imposed (see Lee and Brown, 1996). Besides, even if deflating prices was necessary, the UAE has no monthly deflators available.
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Table 6 Welfare losses by food group and income group and vulnerability by income group. Income group Lowest 20%
Second quintile
Third quintile
Fourth quintile
Highest 20%
Cereals Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
40.09 18.99 18.00 7.22
47.80 18.43 18.00 8.60
60.34 17.45 18.00 10.86
70.47 16.58 18.00 12.68
126.52 15.24 18.00 22.77
Meats Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
46.53 22.04 22.00 10.24
58.47 22.55 22.00 12.86
83.55 24.16 22.00 18.38
107.74 25.35 22.00 23.70
259.11 31.20 22.00 57.00
Fish Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
18.32 8.68 2.00 0.37
23.56 9.08 2.00 0.47
34.76 10.05 2.00 0.70
45.08 10.61 2.00 0.90
93.91 11.31 2.00 1.88
Dairy Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
36.05 17.07 8.00 2.88
44.61 17.20 8.00 3.57
56.78 16.42 8.00 4.54
68.47 16.11 8.00 5.48
118.71 14.30 8.00 9.50
Oils Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
9.06 4.29 2.00 0.18
10.68 4.12 2.00 0.21
13.71 3.96 2.00 0.27
16.15 3.80 2.00 0.32
27.63 3.33 2.00 0.55
Fruits Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $)
22.62 10.71 34.00 7.69
29.45 11.36 34.00 10.01
41.54 12.01 34.00 14.12
55.28 13.01 34.00 18.80
107.86 12.99 34.00 36.67
Vegetables Monthly expenditure (US $) Expenditure share (%) Welfare weight (%) Welfare loss (US $) Total household monthly expenditure (US $) Total welfare loss (CV in US $) Average monthly household income (US $) Expenditure relative to income (%) Vulnerability (total welfare loss relative to income) (%)
38.46 18.22 14.00 5.38 211.13 33.96 984.74 21.44 3.45
44.76 17.26 14.00 6.27 259.32 42.00 2076.93 12.49 2.02
55.16 15.95 14.00 7.72 345.83 56.60 3352.05 10.32 1.69
61.85 14.55 14.00 8.66 425.03 70.54 5581.10 7.62 1.26
96.62 11.64 14.00 13.53 830.36 141.90 14799.73 5.61 0.96
Food group
period and January 2011 as the subsequent period. Column A in Table 5 lists the December 2010 expenditures by commodity. Expenditure on each commodity is equal to the value of imports of that commodity. The percentage changes in commodity prices between December 2010 and January 2011 (Table 5, column B) are equal to the percentage changes in the FAO commodity price index between the two months. Since the FAO commodity indices do not include fish, fruits, and vegetables, we initially set their respective price changes to zero. Column C lists the changes in respective commodities’ Hicksian quantities, and column D gives the CV for each commodity. Results show that the welfare losses from the price increases in cereals, meats, dairy, and oils, amount to 6.608 million USD. The losses represent 5.54% of the value of imports of all 7 commodities in December 2010 (145.421 million USD). It is worth nothing that although we assumed no price increases for fish, fruits, and vegetables, CV from the 3 commodities were non-zero because of the cross-effects between the 7 commodities. Assuming a uniform price increase of 10% for the 3 commodities yielded a welfare loss of 12.162 million USD, about 8.36% of the total December 2010 value of imports. Suppression of cross-effects lowers CV from 6.609 to 1.005 million USD, a mere 0.69% of the total value of imports in December 2010.
Vulnerability of UAE consumers to rising food prices by income group The income groups we use for analysis are the same as those published in the 2007–2008 UAE household income and expenditure survey, the most recent survey conducted by the UAE National Bureau of Statistics. There are 5 groups: the lowest 20%, the second, third, and fourth quintiles, and the highest 20%. For each income group, we extract from the survey the average monthly expenditure for each of the 7 commodities for which we calculated CV in the previous section. Referring to Table 6, the first row under each food-group heading gives the average monthly expenditure in USD by income group and the second row the share of each food group in total expenditure on all food groups. For cereals, for example, the respective income groups’ per-capita monthly expenditures are 40.09, 47.80, 60.34, 70.47, and 126.52 USD. Note that the expenditure share increases with declining monthly income for cereals, dairy, oils, and vegetables; and increases with rising monthly income for meats fish, and fruits. The third row after each food-group heading is the proportion of CV attributed to the food group. The proportions, which are taken from column E in Table 5, are identical for the different income
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groups within each food group. The fourth row after each foodgroup is the proportion of CV attributed to that food-group by income group. Multiplication of each income group’s respective monthly expenditures by the welfare weight yields the respective amounts of CV attributed to the food group. For dairy, for example, the weight is 8% and the respective CV amounts for the income groups are 2.88, 3.57, 4.54, 5.48, and 9.50 USD, respectively. The last five rows of Table 6 are total monthly expenditure on the 7 food groups, total CV, average monthly household income, household expenditure relative to income, and the welfare measure of vulnerability (total CV relative to income) by income group. Clearly, while absolute expenditure on the 7 food groups rises with rising income, the proportion of income spent on food declines with rising income. The highest 20% income group spends almost four times as much on food as does the lowest 20% group. Average expenditure on food by the top 40% of households is 1.5 times the average expenditure on food by the bottom 60%. However, the proportion spent by the highest 20% income group is 0.26% the proportion spent by the lowest 20% income group. Also, the relative spending of the latter group is only 2% points below the relative spending of the top 60% of the households. The 5 income groups’ respective CVs are 33.93, 42.00, 56.60, 70.54, and 141.90 USD. The CVs represent the income equivalent of 5 income groups’ respective deterioration in well-being (welfare loss) caused by the price increases as shown in Table 5, column B. Though the welfare loss rises with rising income, the loss relative to income increases with declining income, making the least well-off the most vulnerable to rising food prices. The income groups’ respective measures of vulnerability are 3.45%, 2.02%, 1.69%, 1.26%, and .96%. Households in the lowest income group are 3.5 times more vulnerable to rising food imports than household in the highest income group.
starting point for a conversation about how to devise ‘‘targeted solutions for people who are in need.’’ rather than ‘‘keeping prices artificially low.’’ Although the quoted editorial does not spell out exactly what those costs are7, a recent report summarizing the key points of roundtable discussion between meat traders and retailers at the Dubai Chamber of Commerce and Industry gives a glimpse of some of the undesirable consequences of prices caps:
Some implications for UAE food pricing policy
Defining vulnerability as the change in consumer welfare from multiple price changes relative to income, this paper uses the Hicksian compensating variation (CV) to measure the welfare change by food group and by income group in the UAE. Using estimates of compensated own- and cross-elasticities of 7 food groups (cereals, meats, fish, dairy, oils, fruits, and vegetables) imported by the UAE, we estimate CV based on changes in international food prices between December 2010 and January 2011. The CV suggests a consumer welfare loss of 6.6 million USD, approximately 4.5% of the total value of the 7 food groups imported by the UAE in December 2010. The respective CVs of the 5 income groups we considered are 33.93, 42.00, 56.60, 70.54, 141.90 USD. Though the absolute welfare loss increases with rising income, the loss relative to income increases with declining income, making the least well-off
To gage some of the policy implications of our findings it is helpful to interpret CV as the (indirect) income tax equivalent of a rise in food prices (see footnote 3). With that interpretation, the measure of vulnerability is the same as the income tax-rate equivalent of the (percentage) increase in food prices shown in Table 5. So being most vulnerable is the same as bearing the heaviest ‘‘tax burden’’. It follows that the concern in the UAE about the vulnerability of low income groups to rising food prices can be translated into a concern about the regressivity of the ‘‘tax burden’’. The compensating variation estimates gives an idea of how much ‘‘food allowance’’ or ‘‘supplementary income’’ in dollars the government could transfer to low income groups to mitigate the burden. Based on our results in this paper, if, for example, the target for assistance are the lowest income households, then each household should receive a government check for 33.93 USD. As described earlier in the paper, the current food pricing policy in the UAE is to place price caps on food items with the expectation that retailers, not the government, bear the cost. The food retailing business perspective on the policy is best summarized by excerpts from a recent editorial in The National (2011): ...The policy is ‘‘right for the population’’ but ‘‘has had an effect on our [food retailer] margins’’. . .Price caps are blunt economic tools, benefitting every one – from the wealthy executive to the street sweeper – rather than offering targeted solutions for people who are actually in need. Cheap food is popular. But in economics terms, it’s worth remembering that there are costs to keeping prices artificially low. With further refinements, as we discuss in the next section, the approach and results we lay out in this paper could serve as a
‘‘Price caps enacted in May 2011 on over 400 staple goods by the Ministry of the Economy have led to isolated shortages. According to participants of the roundtable, it has also led to: an immediate degradation in quality of the nation’s food supply, changes in package sizes, and retailers’ business models. Package sizes have diminished considerably in light of price caps. Hamburger patties that previously contained 75% meat now sell with only 50%. What manufacturers would have sold in a 250 gram package is now sold in 150 grams, at the same price. Higher grade meat imports that fit the controlled categories ceased almost instantaneously. Meat products that were superior by type of feed or method of rearing were no longer brought into the country given that importers were no longer able to recoup costs. Traders started to favor meat from Africa and other less developed markets in order to match established price points. The quality of available meat was therefore downgraded on an aggregate level, while only products destined to high-end outlets continued unhindered given a lack of price controls. Catering establishments and low-end restaurants serving frozen meat were the first to be negatively affected.’’ (Malesa, 2011, pp. 7–8).8
Summary, conclusions, and limitations
7 An anonymous reviewer, citing the study by Ng et al. (2011), suggested that ‘‘given that a large proportion of Emiratis (natives) are overweight or obese, . . .could it be possible that food price increases might actually be ’good’ for the health (and potentially long-term wealth) of the country despite being ’bad’ for the pocket in the short-term? While plausible, it is also plausible that higher food prices may actually induce consumers to substitute unhealthy foods (like burgers and fries) for healthy foods (like vegetables). Moreover, our study is not restricted to Emiratis only. It encompasses the expatriate population also. 8 The deterioration in product quality reported by retailers in the roundtable discussion is consistent with the prediction of economic theory when a price cap is imposed on perfectly competitive firms (Raymon, 1983). When a price cap is imposed on a firm with monopoly power, the firm is predicted to improve quality only at the low end of the market (Besanko et al., 1987). Abstracting from quality issues, it is well known in economic theory that while price caps lead to shortages in perfectly competitive markets, they can lead to increased output when firms have market power and, under certain conditions, to an output level equivalent to that produced in a perfectly competitive markets without price caps (Browning and Browning, 1986, p. 367)
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household the most vulnerable to rising food prices. The income groups’ respective measures of vulnerability are 3.45%, 2.02%, 1.69%, 1.26%, and .96%. This reveals that although the poorest households spend on food less than a quarter of what the wealthiest households spend, the former are 3.5 times more vulnerable to rising prices food imports than the latter. By re-interpreting the measures of vulnerability as tax-rate equivalents of the assumed food price increases, we have suggested that CV represents the dollar amount of ‘‘food allowance’’ or ‘‘supplementary income’’ the government could provide households in the low income group(s) as compensation for higher food prices. In light of the some potentially undesirable economic consequences of imposing price caps, both in theory and in practice, we believe that our approach and results could serve as a starting point for a conversation about considering targeting compensation to low income consumers as an alternative to imposing price caps. There are, however, two limitations of our study that should be addressed in order to add more precision to our results. First and foremost is the assumption that compensated elasticities apply to all income groups and ethnic groups. The assumption is dictated by availability of aggregate data only. To estimate group specific elasticities and use the elasticities to approximate CVs for, say, native Emiratis and expatriates by income group would require panel household data. This will go a long way in rationalizing ‘‘offering targeted solutions for people who are actually in need’’ be they Emiratis, expatriates, or both. A second limitation is use of aggregate food groups rather than individual food items. The ideal set of food items would be those that are currently the candidates for price caps. However, since the items number in the hundreds, estimating their respective own- and cross-price elasticities would exhaust degrees of freedom quickly whether one uses aggregate data, as we did, or panel household data.
References Besanko, D., Donnelfeld, S., While, L.J., 1987. Monopoly and quality distortion: effects and remedies. Quarterly Journal of Economics 102, 747–767. Browning, E.K., Browning, J.M., 1986. Microeconomic Theory and Applications. Little, Brown, and Company, Boston. (BMI) Business Monitor International, 2011. United Arab Emirates Food and Drink Report. Q1 Report. Deaton, A., Muelbauer, J., 1980. An almost ideal system. American Economic Review 70, 312–326. DETC (Dubai External Trade Statistics), 2005–2010. Purchased in CD-ROM by the Dubai Chamber of Commerce and Industry from the Ports, Customs and Free Zone Corporation for 2005–2010. Food and Agriculture Organization (FAO) Statistics.