Forecasting food demand in Tunisia under alternative pricing policies

Food Policy 28 (2003) 167–186 www.elsevier.com/locate/foodpol

Forecasting food demand in Tunisia under alternative pricing policies B. Dhehibi a,∗, J.M. Gil b a

b

Unidad de Economı´a Agraria, Servicio de Investigacio´n Agroalimentaria, P.O.Box. 727. 50080 Zaragoza, Spain Escuela Juperior de Agricultura de Barcelona-UPC, Comte d’Urgell, 187; 08036 Barcelona, Spain

Abstract Food policy in Tunisia employs mainly consumer price subsidies and programs, all directed to the reduction of poverty. In the new environment of globalization and trade liberalization these consumer subsidies are being questioned. Inefficiency and self-generated inequalities have increased pressure to remove or reduce subsidies. The objective of this paper is to assess the impact of two alternative schemes of price subsidies management. Food demand forecasts are based on estimated parameters from an AIDS model together with some assumptions about the exogenous variables and population projections. Results indicate that a gradual subsidies removal will not affect substantially food expenditure structure. Non subsidized food products would increase their relative position while traditional products would lose slightly. In terms of welfare implications, changes in the subsidy policy would mainly affect low-income groups.  2003 Elsevier Science Ltd. All rights reserved. Keywords: Food demand forecasts; Dynamic demand systems; Subsidy removal; Tunisia

Introduction In recent decades the increasing concern, in many developing countries, about the nutritional intake and the welfare of the poor has generated food policies in which the consumption of a wide range of basic foodstuffs is subsidized. The impact of such policies on consumer welfare and government budgets has been analyzed in many papers.1 Nasser and Gomaa (1998); Lo¨fgren and Kherallah (1998); Ahmed et al. ∗

1

Corresponding author. Tel.: ++34 93 4137523; fax: ++34 93 4137444. E-mail addresses: [email protected] (B. Dhehibi); [email protected] (J.M. Gil). See Farrar (2000) for a complete review of the existing literature.

0306-9192/03/$ - see front matter  2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0306-9192(03)00027-7

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(1998, 1999); Ahmed and Bouis (1998); and Gutner (1999) have analysed the structure, performance and political economy of the Egyptian food subsidy system. Pinstrup-Andersen et al. (1983) and Shugeiry (1990), for Sudan; Tuck and Lindert (1996), for Tunisia; Garcı´a and Pinstrup-Andersen (1987); Heaver and Hunt (1995); and Subbarao et al. (1996), for the Philippines; Lustig (1986), for Mexico; Bhalla et al. (1999), for India; Adams (1998) and Babu (1999), for Bangladesh; and Islam and Garrett (1997), for Pakistan, among others, are clear examples of this growing body of research. Tunisia is not an exception among developing countries and since the 1970s the food policy has been oriented to what has been called “food security”. The main objectives of this policy have been: to achieve national self-sufficiency in basic foodstuffs, to stabilize prices of staples, to maintain the purchasing power of the poor, and to improve the nutritional status of the most vulnerable people groups. The main food policy instruments, from the consumer’s point of view, have been food subsidies and programs to reduce poverty. Food subsidies are managed through the Caisse Ge´ ne´ rale de Compensation (CGC), although many other institutions have been involved both in the payment of subsidies and in the distribution of subsidized food. In most agricultural sub-sectors, there exist official institutions that control the marketing channels. Prices paid by consumers are fixed below market prices and the distributors are compensated by the CGC.2 At its inception, the Tunisian food subsidy program had extensive commodity coverage and was universal, benefiting anyone purchasing any quantity of subsidized products. During the eighties, it became apparent that the food subsidy program was very costly and inefficient. Subsidies started to represent an increasing share of the public budget. Criticisms arose against universal subsidies, since they mostly benefited the wealthier component of the population. In spite of this criticism, proponents of food subsidies still argued that some kind of subsidies were necessary to guarantee the supply of basic foods to the poor. In 1991, a self-targeted program was implemented in which subsidies were limited to selected products, those mainly consumed by the poor. At present, the Tunisian subsidy system includes only five foods: durum-wheat, bread-wheat, cooking oils, pasteurized-reconstituted milk and sugar, and accounts for less than 6% of total government expenditures (Khaldi and Naı¨li, 1995; and Tuck and Lindert, 1996). While the first two commodities are locally produced, the rest are imported. In the new environment of globalization and trade liberalization, the efficiency of food subsidies is increasingly being questioned. Tuck and Lindert (1996) evaluated ex-post the implementation of the self-targeted program from 1991–1994. They showed that a product quality differentiation policy could be an effective tool for 2 Although CGC expenditures were considered as consumer subsidies they were also used to support producer prices above opportunity costs. In other words, the CGC expenditures have simultaneously subsidised producers and consumers for the same commodities. In the case of commodities which were not locally produced, subsidies only benefited consumers. According to Tuck and Lindert (1996), around 40% of CGC expenditures were technically producer subsidies, which have increased their importance as producer prices here diverged increasingly from comparable CIF prices.

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reducing the fiscal costs and improving the self-targeting of food subsidies. In any case, it is most likely that subsidies will continue to be reduced in the following years but, until now, there have not been many attempts to evaluate the impact of possible subsidy reductions on Tunisian food demand. The objective of this paper is to assess the impact, at the consumer level, of two alternative food subsidies scenarios. In the first one, the status quo is maintained, while in the second, food subsidies are gradually removed. Forecasts of food demand are usually based on estimated per capita food consumption and on projections of population size. In this paper, the per capita consumption of the main food categories is estimated using a dynamic demand system while population size estimates are taken from projections made by policy makers. Finally, an attempt is made to assess the impact of the two alternative policies on population welfare by examining the projected changes in the structure of food expenditure for various income groups. This paper is organized as follows. Section 2 contains some descriptive statistics on the evolution of food consumption in Tunisia, along with some comments about the food subsidy program. In section 3, the structural model used to estimate per capita food consumption is outlined, paying special attention to the dynamic nature of demand relationships (technical details are presented in two appendices). Section 4 presents the main results, including the selection of the appropriate dynamic specification model and a discussion of estimated elasticities. In section 5, forecasts of food demand are presented with and without the price subsidy reduction. Finally, some concluding remarks are presented.

Food consumption in Tunisia The food subsidies policy In Tunisia, there are three main instruments which are used to implement the food security policy: 1) the agricultural policy; 2) food price subsidies; and 3) programs to reduce poverty. We will concentrate in the second instrument. Two periods can be distinguished when analyzing the food price subsidies (Khaldi and Naı¨li, 1995). The first period covers the seventies and half of the eighties. In 1971, the Caise Ge´ ne´ rale de Compensation (CGC) was created to subsidize selected food products. The objective of these subsidies was to limit consumer price increases to a maximum of 6% per year in an environment of increasing producer and import prices. The CGC compensated losses suffered by the various institutions in charge of managing the marketing channels of subsidized products. CGC funds came from special taxes placed on petroleum derivatives. Cereals, milk, oils, sugar, imported beef, corn, tea and coffee were the main products subsidized, with 70% of total subsidies allocated to cereals. At the beginning of the eighties, due to the stabilization of petroleum prices, the CGC started to accumulate deficits and, as a consequence, the government started to implement adjustments in some of the subsidized cereals (bread, pastes and semolina). By the mid 1980s, some policy makers started questioning the effectiveness of

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the price subsidies system and the role of the CGC. In 1985, the program accounted for about 10% of total government expenditures, 4% of GDP. Moreover, some people thought that the price subsidies system preserved inequalities, in the sense that consumers with higher income received greater benefits from the system. In 1990, the poorest income group (13% of the population according to data from National Institute of Statistics, INS) received 17% of total subsidies, whereas the wealthiest income group (12% of the population) received around 20%. However, differences in expenditure shares, as we will mention below, led to the outcome that for the higherincome group the value of the subsidy represented a lower share of their total expenditures. In fact, in 1990, for the poor, food subsidies accounted for 8.7% of total expenditures, while, for the richest, this percentage was 1.6% (Tuck and Lindert, 1996). Starting in 1986, the Tunisian economy fell into recession. In response, the government designed and implemented a structural adjustment program which affected the subsidies system. Meat subsidies were eliminated, while those for sugar, cereals for animal consumption and feed were gradually reduced. Cereals for human consumption, vegetable oils (olive oil was not included) and milk maintained their level of subsidization. In the case of cereals, subsidies accounted for almost 40% of the final consumer price, while for vegetable oils and milk, subsidies reached up to 60% and 67%, respectively. However, the effectiveness of both the system and the CGC was still in question and many were calling for the total removal or progressive reduction of subsidies. As a result of these tensions, a reform program was incorporated into the VIII Development Plan (1991–96), aiming to reduce CGC expenditures while minimizing the impact on lower-income households. Amongst the various alternatives, a selftargeting subsidies program was chosen. In this system, subsidized products were available to all, but subsidies were limited to items that were primarily consumed by lower-income groups (durum wheat products, generic oil, less-refined sugar and pasteurized reconstituted milk).3 Additionally, a quality differentiation was defined for specific products (bread wheat products, olive oil, cube sugar and locally produced sterilized milk). Higher-quality varieties of these products were unsubsidized, those mainly consumed by the higher-income groups, who then consume less of the subsidized varieties. As a result of this reform, the Tunisian subsidy system accounted for less than 6% of total government expenditures in 1995. In the same year, the lower-income group received 21% of total subsidies while the wealthier group received around 17%. Evolution of food consumption in Tunisia In Tunisia, daily per capita calorie intake has substantially increased in the last 25 years, following an annual growth rate of 1.6% (2278 kcal, in 1970, and

3 See Appendix A for a description of absolute values and relative importance of food subsidies from 1986–1995.

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3191 kcal, in 1994). The proportion of calories coming from animal products is still very low and hardly reaches 10% of total calorie intake, due to the null consumption of pork and the relatively high price of meat products in comparison to other food products. As in most developing countries, food expenditure represents a high percentage of the total family expenditure. In 1980, Tunisian households allocated 41.7% of their budget to food products. Fifteen years later, this percentage had slightly decreased, reaching 37.7% (Table 1). However, the food expenditure structure has suffered important changes during the analyzed period. The relative importance of bread and cereals decreased from 21.4% of total food expenditure in 1980, to 13.0% in 1995. Something similar took place in the case of vegetable oils; their relative importance decreased by 50%. The consumption of animal products (meat, milk and eggs) substantially increased during the period 1980–1995. In 1980, both food groups represented around 25% of total food expenditure while in 1995 this percentage reached 31.7%. The structure of food expenditure in Tunisia is quite representative of an Arab Mediterranean country, in which cereals, fruit, vegetables and fish still play an important role while pork consumption is null. It is noteworthy that the importance of animal products appears higher when considering expenditure values rather than using calorie intakes, since the price per calorie of animal products is higher than the other calorie sources. In spite of this general pattern, several differences exist when comparing the food expenditure structure of different income groups (Table 2).4 In the lower-income Table 1 Evolution of the food expenditure structure in Tunisia (% on total food expenditure) Food products Cereals Meat Fish Milk, dairy and eggs Fruits Vegetables Potatoes Oils and fats Other foods

1980 21.4 15.2 5.9 10.23 16.4 11.9 1.9 9.0 8.0

1985 13.66 20.7 7.73 11.65 14.97 14.42 2.2 8.0 6.6

1990 13.5 19.4 8.02 11.55 16.29 14.53 2.41 8.66 5.6

1995 13.02 20.44 7.15 11.25 17.29 15.12 2.72 6.73 6.24

Source: Elaborated from INS and FAO data.

4

Due to data availability, while in Table 1 expenditure values are obtained by multiplying per capita apparent consumption from FAO database and weighted prices for food categories collected from the Institut National de la Statistique (INS), in Table 2 expenditure values for different income groups are directly obtained from the Enqueˆ te Nationale sur le Budget et la Consommation de Me´ nages published by the INS. The two data sets are not directly comparable as the first one refers to per capita apparent consumption while the second refers to per capita consumption using household expenditure data (only available for 1990 and 1995). As a result, in some cases (milk and dairy products, vegetables and potatoes) the mean levels in Table 1 for 1995 lie outside the range of data for the respective means in Table 2, although in such cases percentages are not very different.

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Table 2 Food expenditure structure at various income levels in 1995 (% on total food expenditure) Food products

Less than 250 Between 250 Between 350 Between 500 More than and 350 TND and 500 TND and 700 TND 700 TND TNDa

Cereals Meat Fish Milk, dairy and eggs Fruits Vegetables Potatoes Oils and fats Other foods

32.42 11.18 1.95 6.14 8.39 24.65 1.81 8.42 5.04

21.10 17.04 3.51 7.46 14.5 22.12 2.18 7.53 4.58

16.25 21.38 4.90 8.72 16.26 19.71 2.09 6.18 4.11

13.11 23.41 6.63 9.44 15.55 19.61 2.07 6.51 3.67

8.69 27.08 7.72 10.43 19.00 15.89 2.14 5.84 3.22

Source: Elaborated from INS data (Enqueˆ te Nationale sur le Budget et la Consommation de Me´ nages). a 1 TND = 0.07751 Euros = 0.682 $.

group, the percentage of food expenditure allocated to cereals is quite high, reaching 32%. Vegetables represent 25% of total food expenditure, followed by meat products (11%). In general terms, it can be concluded that, as the income level increases, the relative importance of the most traditional food products (mainly domestically produced) decreases (cereals, vegetables and oils) while the consumption of more expensive products increases (meat, fish, dairy products and fruits). These patterns in consumption over time and across income categories have implications for the impact of subsidy removal, as we will discuss below.

The structural model In many studies, demand forecasts are based upon a set of elasticities. However, in this study, projections are based on estimated parameters of an econometric model, as in Goungetas et al. (1993), as well as on assumptions regarding the evolution of population, income and prices. The structural model used in this paper is the well-known Deaton and Muellbauer (1980) Almost Ideal Demand System (AIDS); a widely adopted model in demand analysis due to its desirable properties: it is based on the consumer demand theory, it is a flexible functional form model, and its results are consistent when aggregated over consumers. Moreover, by applying linear restrictions on the estimated parameters, homogeneity and symmetry restrictions can be imposed. A brief description of the model is given in Appendix B. Dynamics Economic studies of food demand often show that consumers do not adjust instantaneously to changes in prices, income and other determinants of demand. When

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such changes take place, consumer adjustment towards a new equilibrium is spread over several time periods (Brown, 1952; Houthakker and Taylor, 1970; Blundell, 1988; Kesavan et al., 1993, among others). The main source of these lags is habit persistence. Habit persistence means that consumers make their decisions about current consumption by taking into account consumption in previous periods. In other words, past consumption exerts an important effect on current consumption because some habits have been developed. A partial adjustment model accounts for this hypothesis: changes in consumption depend on current values of exogenous variables and on past consumption levels. On the other hand, in some cases, the specification of a static model can lead to autocorrelation problems generated by the omission of some variables which change slowly, or, at least, non-randomly, over time. In these cases, dynamics are introduced by the specification of an autoregressive model, where changes in the endogenous variables depend on both current and past values of exogenous variables. Dynamics have been incorporated in demand analysis in different ways. Some authors have estimated models in first or fourth differences (Eales and Unnevehr, 1988 and Moschini and Meilke, 1989, using USA data; and Reynolds and Goodard, 1991, in the case of Canada). Other authors deal with dynamic structures by assuming an adjustment process (such as a partial adjustment) and modifying, accordingly, the constant terms in the demand system equations. However, these models only provide information about short-run coefficients, while long-run parameters are based on the ratio of short-run and adjustment coefficients. Moreover, the standard deviation error of long-run parameters is difficult to calculate. Instead, we have chosen a more generalized model, which is able to incorporate various dynamic structures and allows for the direct estimation of long-run coefficients. It is assumed that changes in endogenous variables correspond to anticipated and unanticipated changes in exogenous variables so as to maintain a long-run relationship between them. This approach was proposed by Anderson and Blundell (1983a) and applied to food demand analysis by Burton and Young (1992) and Kesavan et al. (1993), among others. A description of this procedure is outlined in Appendix C.

Data sources, estimation and food demand elasticities The data comes from a number of sources. Annual consumption data for each commodity group are from the Food Balance Sheet prepared by the Food and Agricultural Organisation (FAO) and are representative of national consumption. In order to get per capita data, population figures were collected from the International Monetary Fund (IMF). Annual consumer price series for each commodity are found in the Bulletin Mensuel de Statistique (Monthly Statistical Bulletin) published by the Institut National de la Statistique (National Statistics Institute, or INS). Food products have been aggregated into nine broad categories: 1) cereals; 2) meat; 3) fish; 4) milk,

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dairy products and eggs; 5) fruits; 6) vegetables; 7) potatoes; 8) oils and fats; and 9) other foods. The sample period covers yearly data from 1973–1996.5 To assess the impacts on different income groups, data on household expenditure has been obtained from the Enqueˆ te Nationale sur le Budget et la Consummation de Me´ nages (Household Budget Survey) published by the INS. Food groups have been also aggregated into the nine categories mentioned above. The information is only available for 1990 and 1995. As a first step, a diagonal version of models (C.1), (C.2) and (C.3) was estimated using the Full Information Maximum Likelihood (FIML) procedure. The “other foods” equation was deleted to avoid a singularity in the variance and covariance matrix of residuals due to the adding-up restriction. Restrictions imposed by economic theory (homogeneity and symmetry) were tested. A two-step procedure is followed. First, homogeneity is tested against the unrestricted model. A likelihood ratio test statistic is used. Since the sample is too short, the Bewley’s (1986) correction factor is included to approximate asymptotic distributions for finite samples. The results in Table 3 demonstrate that the homogeneity restriction is rejected at the 5% level of significance, both in the diagonal error correction and partial adjustment models, while it is not possible to reject it in the autoregressive model. As a second Table 3 Testing theoretical restrictions for ECM, autoregressive and partial adjustment models Log L

Error correction model Unrestricted model Homogeneity Homogeneity and symmetry Autoregressive model Unrestricted model Homogeneity Homogeneity and symmetry Partial adjustment model Unrestricted model Homogeneity Homogeneity and symmetry

LR

LR∗

D.F

Critical value (5%)

841.273 793.930 783.195

– 94.686 116.15

– 36.07 44.24

– 8 36

– 15.507 50.964

847.579 831.803 781.467

– 31.552 122.224

– 12.01 46.54

– 8 36

– 15.507 50.964

829.698 803.493 771.644

– 52.41 116.108

– 19.96 44.23

– 8 36

– 15.507 50.964

Log L: Log of Likelihood Functions; LR : Likelihood Ratio; LR∗ : Adjusted Likelihood Ratio (Bewley, 1986); D.F : Degrees of Freedom.

5

Prices refer to specific consumed products (i.e. couscous) while FAO statistics refer to commodities. To calculate a single price for each food group we have adopted the following process. The price for cereals, for instance, has been calculated as a weighted average of prices from specific cereal products. Weights are calculated taking into account the relative importance of each single product (i.e. couscous) on total expenditure on the corresponding food group (i.e. cereals). Expenditure data are published by the INS every five years. Thus, weights have been kept constant during that period and are updated when new information is available.

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step, both restrictions are tested again using the unrestricted model. We fail to reject the null hypothesis in all cases, indicating that the three dynamic specifications are consistent with economic theory. Several tests have been performed in order to get the appropriate dynamic specification. A Likelihood Ratio test has been used to discriminate among the alternative models (Partial Adjustment, First Order Autoregressive, and Static). Results indicate that the hypothesis of first autoregressive form is not rejected, at the 5% level of significance (Table 4). The autoregressive specification implies that changes in food demand not only depend on actual income and prices but also on lagged values of these variables. The estimated coefficients of the autoregressive model (AR/AIDS) with homogeneity and symmetry are presented in Table 5. The negativity condition has been analyzed by calculating the eigenvalues of matrix C in (B3). Results indicate that this condition is satisfied.6 All income and own price parameters are statistically significant at the 5% level. The λ parameter, which introduces lagged values in the model, is highly significant, indicating that it is an important determinant in food consumer demand. Finally, cross-price parameters are significant in most cases. The most interesting economic parameters for policy analysis are the elasticities. No distinction can be made between the long and short-run in the AR/AIDS model. Table 6 presents the estimated food expenditure and own- and cross-price elasticities calculated at mean values. In general terms, animal products can be considered as luxury goods from the food expenditure point of view. Expenditure increases for such products are more than proportional when total food expenditure rises. Vegetable products, on the other hand, are necessities. All the uncompensated own-price elasticities are negative; that is, changes in own prices have inverse impacts on quantities demanded. All of the estimated own-price elasticities are less than unity, while meat, fish and milk, dairy and eggs are the most elastic. Most of the compensated cross-price elasticities are not significantly different from zero. The most important complementary relationships are between potatoes Table 4 Testing for alternative dynamic specifications Log L ECM Autoregressive Partial Adjustment Static

783.195 781.467 771.644 770.840

LR – 3.456 23.102 24.91

LR∗

D.F.

Critical Value (5%)

– 1.316 8.80 9.48

– 1 1 2

– 3.841 3.841 5.991

Log L: Log of Likelihood functions; LR : Likelihood Ratio; LR∗ : Adjusted Likelihood Ratio (Bewley, 1986); D.F. : Degrees of Freedom.

6 The calculated eigenvalues were: 0, ⫺0.16025, ⫺0.012159, ⫺0.067899, ⫺0.10616, ⫺0.20429, ⫺0.35583, ⫺0.57951, and –0.84781.

1.11∗∗ (3.55) ⫺0.13∗ (⫺2.37) 0.108∗∗ (10.71) ⫺0.028∗∗ (⫺3.27) ⫺0.62∗∗ (⫺3.14) ⫺0.0075 (⫺0.78) ⫺0.014∗∗ (⫺4.29) ⫺0.6138 (⫺1.40) ⫺0.008∗∗ (⫺3.254) ⫺0.0079 (⫺1.79) ⫺0.0054 (⫺0.53) 0.267 (2.28)

aI

0.188 (1.73) 0.0044 (0.46) ⫺0.0041 (⫺1.41) 0.0148 (1.64) 0.01∗∗ (3.92) ⫺0.0024 (⫺0.52) 0.0034 (0.29) 0.267 (2.28)

–

⫺0.74∗∗ (⫺2.61) 0.137∗∗ (2.75) –

⫺0.365 (⫺0.66) 0.051 (0.54) –

0.14∗∗ (9.01) ⫺0.023∗ (⫺2.51) ⫺0.03∗∗ (⫺3.67) ⫺0.02∗∗ (⫺2.86) ⫺0.017 (⫺1.88) 0.0005 (0.196) ⫺0.0063 (⫺1.2) ⫺0.0095 (⫺0.96) 0.267 (2.28)

Fish

Meat

0.055∗∗ (3.08) ⫺0.0068∗ (⫺2.04) ⫺0.00695 (⫺0.49) 0.124 (0.362) 0.00247 (0.51) ⫺0.00502 (⫺0.28) 0.267 (2.28)

–

–

⫺0.239 (⫺0.75) 0.069 (1.24) –

Milk, and eggs

0.08∗∗ (10.7) ⫺0.01∗∗ (⫺3.5) 0.0005 (0.68) ⫺0.13∗∗ (⫺7.2) ⫺0.012 (⫺1.8) 0.267 (2.28)

–

–

–

0.028 (0.06) 0.017 (0.23) –

Fruits

0.094∗∗ (6.82) ⫺0.0217∗∗ (⫺6.89) ⫺0.022∗∗ (⫺4.93) ⫺0.0128 (⫺1.5) 0.267 (2.28)

–

–

–

–

0.408 (1.25) ⫺0.039 (⫺0.59) –

Vegetables

t-ratios are in parentheses; ∗∗: Indicates significance at 1% level; ∗: Indicates significance at 5% level.

λ

gi9

gi8

gi7

gi6

gi5

gi4

gi3

gi2

gi1

bI

Cereals

Estimated parameters

0.018∗ (13.15) ⫺0.3E-3 (⫺0.02) ⫺0.0003 (⫺0.13) 0.267 (2.28)

–

–

–

–

–

0.059 (0.74) ⫺0.010 (⫺0.74) –

Potatoes

0.064∗∗ (2.36) ⫺0.014∗∗ (⫺7.70) 0.267 (2.28)

–

–

–

–

–

–

0.405∗ (2.09) ⫺0.057 (⫺1.68) –

Oils and fats

Table 5 Maximum Likelihood estimated parameters for the Autoregressive AIDS model with homogeneity and symmetry restrictions imposed

0.056∗ (2.52) 0.267 (2.28)

–

–

–

–

–

–

–

0.33∗∗ (2.45) ⫺0.04∗ (⫺1.8) –

Other foods

176 B. Dhehibi, J.M. Gil / Food Policy 28 (2003) 167–186

0.172 (2.78) 0.494 (4.57)

0.064 (1.00)

⫺0.191 (⫺1.75) 0.205 (1.93)

0.109 (1.76)

0.053 (1.063)

Vegetables0.069 (1.24)

0.071 (1.37)

0.0893 (2.39)

Potatoes

Oils and fats Other foods

0.065 (0.689) 0.04 (1.4)

0.166 (4.57)

7.33

Other foods

⫺0.01 (⫺0.82) ⫺0.065 (⫺2.15) 0.083 (1.40)

0.107 (2.55)

0.055 (0.95)

⫺0.187 (⫺7.84)

⫺0.09 (⫺2.7)

⫺0.01 (⫺0.12) 0.060 (0.75)

⫺0.01 (⫺0.2)

0.028 (0.28)

0.122 (1.38)

0.021 (0.33)

0.039 (2.39)

0.326 (0.816) 0.385 (1.17)

8.53

Oils and fats

⫺0.191 (⫺5.33) 0.0197 (1.63) ⫺0.115 (⫺4.42)

⫺0.125 (⫺5.79) ⫺0.223 (⫺4.07) 0.023 (1.40)

0.027 (4.77)

0.084 (0.689) 0.034 (1.14)

⫺0.41 (⫺4.3) 0.042 (1.45)

0.08 (2.6)

0.08 (1.9)

⫺0.317 (⫺3.14) 0.166 (1.45) 0.13 (4.7) ⫺0.772 (⫺5.79) 0.142 (2.55) ⫺0.01 (⫺0.8) ⫺0.112 (⫺2.15) 0.044 (1.078) ⫺0.02 (⫺1.1) ⫺0.0307 (⫺0.798)

⫺0.586 (⫺3.21) 0.06 (2.67)

0.356 (2.78)

⫺0.0855 (⫺1.57) 0.177 (1.29) 0.03 (0.7)

0.556 (0.92)

2.37

Potatoes

⫺0.027 0.037 (1.37) (⫺1.75) 0.0566 (1.002) 0.0263 (1.93) 0.05 (1.76)

0.767 (0.92)

14.58

0.061 (1.24)

1.12 (1.9)

13.99

Vegetables

0.0677 (1.16) 0.05 (2.7)

1.61 (3.28)

11.36

Milk and eggs Fruits

Italicised values correspond to Marshallian own price elasticities. t-ratios are in parentheses.

0.117 (3.3)

0.045 (0.96)

0.041 (1.99)

0.037 (0.73)

⫺0.869 (⫺4.99) ⫺0.138 (⫺1.57) 0.109 (1.29)

⫺0.156 (⫺1.53) 0.141 (1.09)

0.009 (0.17)

Milk and 0.097 (1.16) eggs Fruits 0.063 (2.72)

Fish

2.95 (4.168)

1.28 (2.47)

⫺0.066 (⫺1.53) ⫺0.282 (⫺1.96) 0.053 (1.09)

7.04

(%) 18.40

Average food budget share 16.40 Expenditure elasticities 0.206 (0.616) Price elasticities Cereals ⫺0.209 (⫺4.313) Meat 0.0087 (0.17)

Fish

Meat

Cereals

Table 6 Food expenditure and compensated price elasticities for Tunisia (at mean values)

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and cereals, vegetables and potatoes, and between dairy products and meat. Fish is a net substitute for most products, and dairy products substitute oils and fats.

Forecast of food demand in Tunisia The introduction of the self-targeted food subsidy program in 1991 has proved to be successful in reducing the budgetary costs of the CGC. In spite of this relative success, there still exists a considerable debate about the effectiveness and efficiency of food subsidies. As mentioned in section 2, changes between 1990 and 1995 in relation to the distribution of food subsidies among various income groups were not very substantial. Both proponents and critics of food subsidies argued their cases based on the welfare implications of these programs. However, little has been done in Tunisia in order to estimate the effect on food demand of changes in subsidies. The aim of this paper is, precisely, to assess the future impact, at the consumer level, of two alternative scenarios of food subsidies. The first scenario assumes that the food subsidy program remains unchanged as it was in the last year when information was available, 1996. The second hypothesis supposes a gradual reduction of such subsidies during a ten year period. A comparison of the results under the two alternative scenarios is made for the year 2006. Two main issues are addressed in this paper. The first one is to analyze changes in total food consumption of various products under the two food subsidy scenarios. The aim is to assess the future need for increasing domestic production and reducing dependence on foreign countries. Demand projections for Tunisia are done using the following procedure. The starting point is the food consumption data for the last year when information is available, 1996. From estimated parameters in Table 5, and making some assumptions about the evolution of certain exogenous variables,7 future values of budget shares wi are projected. From these variables, per capita consumption is obtained. Finally, total consumption is determined by multiplying per capita values by population projections.8 Under the two scenarios, the projected changes in total consumption for 2006 are

7 The following assumptions are adopted: 1) Population: following previsions made by the INS, it is expected a population annual growth rate of 1.7 and 1.5% for 1997–2001 and 2002–2006, respectively. 2) A constant real price and income scenario is assumed taking into account an expected average inflation rate around 6%. 3) Food expenditure is assumed to grow 5% annually as it has been considered that food is inelastic with respect to total expenditure. It implies an expenditure elasticity of 0.9 which is consistent with calculations made by the INS in the last published Consumption Survey (1995). 4) In the gradual reduction of food subsidies scenario, and taking into account how price series have been constructed (see footnote 4) only the compound price index for cereals, oils and fats, and milk and dairy products are modified. 8 To assess the forecast accuracy of the modelling exercise a historical simulation for period 1991– 1996, taking into account the information until year 1990, has been made. The Mean Square Errors of budget shares for the forecasting period were quite low (less than 0.01 for all food groups).

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shown in Table 7 for each food product category, as well as the resulting food expenditure structure. If subsidies were maintained as they were in 1996, assuming constant real prices and income, budget shares for 2006 would follow the same pattern as in the past. Fish, meat and dairy products would exhibit a downward trend in relation to their relative importance on total food expenditure, being more significant in the case of fish. Most traditional food products would slightly improve their relative position. In terms of future production needs, fish is the only case where total consumption would decrease. The relative fall in real food expenditure, the projected decrease of fish budget share and the high expenditure elasticity contribute to explain this result. In the other two food groups, in which budget shares decrease (meat and milk and dairy), total consumption would slightly increase. In the other food groups, total consumption would be expected to increase between 10 and 15% by the year 2006. The projected situation under a gradual reduction of subsidies shows a certain degree of stabilization in terms of budget shares. Prices would increase for some cereal products, while milk and oils seem to contribute to an increasing demand for non-subsidized products (meat, fish and fruits). In comparison to the first scenario, these food products would raise their relative position within total food expenditure while traditional products would lose slightly. Total food expenditure would increase while non-food consumption would decline significantly, suggesting that consumers would reallocate expenditures to defend the consumption of necessities. As can be observed in Table 7, total food consumption of traditional products would decrease slightly in relation to a “subsidies maintenance” scenario. The consumption of meat, fruits and milk and dairy products would increase in relation to scenario 1 but growth Table 7 Forecasts of average budget share and food consumption changes in Tunisia under alternative policy scenarios

Food products

Cereals Meat Fish Milk, dairy and eggs Fruits Vegetables Potatoes Oils and fats Other foods a b c

Scenario 1a

Scenario 2b

Budget share 2006 Variation in total consumption (1996–2006)c

Budget share 2006 Variation in total consumption (1996–2006)c

15.68 19.80 5.33 10.29 14.99 15.96 2.54 8.73 6.52

15.56 4.08 ⫺14.0 0.36 5.45 8.72 10.79 13.45 13.77

14.36 20.45 6.34 10.74 15.37 16.06 2.52 8.11 5.89

Scenario 1: Subsidies unchanged. Scenario 2: Subsidies gradually removed from 1997–2006. Percentage change in total quantity consumed over the 1996 base year.

14.52 9.08 ⫺3.72 8.34 8.95 11.48 9.34 11.03 11.10

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rates would be still lower than those of traditional products. Finally, in the case of fish, total consumption would decrease slightly. We now want to give an approximate idea of the welfare implications of both scenarios. Some projections have been done to determine the future structure of food expenditure for the various income groups considered in this paper. Mainly, we want to analyze the impact of the two food subsidy alternative policies on the budget shares of subsidized products for each income level. This is not, however, an easy task since available information is very limited. Official statistics from the INS in relation to food consumption by income group is only available for 1990 and, partially, for 1995. The projection has been made following several steps. First, from the estimated model, budget shares are generated over the period 1997–2006 under the two scenarios. Secondly, per capita consumption has been calculated. Third, to get a projection of per capita consumption by income group, it has been assumed that deviations of quantities consumed by each income group in relation to average values are kept constant.9 Fourth, assuming that all income groups face the same prices, the projected expenditure in each food group is calculated and budget shares are obtained. The results are shown in Table 8.10 The table reveals that changes in food demand structure between the two scenarios are not very different. For the lower-income group, if subsidies remain unchanged, the proportion of food expenditure allocated to cereals would decrease by 4 percentage points. The relative importance of potatoes and oils and fats would decrease slightly, while the budget shares of the rest of the products would increase, fish and vegetables having the greatest increase. Under a gradual removal of subsidies, as mentioned before, the situation would change slightly. The negative impact on cereals and oils and fats would be marginally higher. On the other hand, the positive impact on the meat budget share would also be a little bit higher. As the income level increases, changes would mainly affect cereals—in a negative way, and fish—in a positive way. Comparing both scenarios, subsidy reduction would have a positive impact on fish and meat and a negative one on cereals and oils and fats. A final interesting result is that any policy implemented would affect mainly the lower-income groups. As shown in Table 8, changes in budget shares are less important as the income level increases. Concluding remarks A considerable debate has arisen in Tunisia about the importance of maintaining consumer price subsidies for basic foods (cereals, milk and vegetable oils). This is 9 This is not a strong assumption as such deviations are more or less the same when comparing 1990 and 1995. In any case, we recognise that holding deviations constant does not capture the differential effects of targeting on the poor but at least it can give some approximation of the effects. 10 Following a similar reasoning to that in footnote 4, results from Tables 7 and 8 are not directly comparable. Projections in Table 7 are generated from data in Table 1 while results shown in Table 8 are generated from data in Table 8. This would explain how, in the milk and dairy products, potatoes, oils and fats and other food, projected values in Table 7 lie outside the range of projections for the respective income groups in Table 2.

Between 250 and 350 TND

Between 350 and 500 TND

Between 500 and 700 TND

More than 700 TND

28.17 11.62 3.27 7.27 8.38 27.53 1.66 7.66 4.46

27.51 12.80 3.00 7.38 9.14 26.80 1.76 7.25 4.37

19.80 17.47 4.59 7.97 14.59 21.76 2.11 7.36 4.36

18.18 18.39 5.20 7.79 15.22 22.48 2.14 6.57 4.03

15.01 21.81 6.16 9.27 16.28 19.24 2.01 6.35 3.86

13.72 22.75 6.69 8.98 16.85 19.79 2.03 5.64 3.55

12.36 23.68 7.55 9.82 15.47 19.23 2.00 6.38 3.51

11.20 24.60 8.16 9.49 15.99 19.71 2.02 5.63 3.21

8.11 27.31 8.53 10.80 18.90 15.54 2.09 5.68 3.05

7.31 28.24 8.91 10.37 19.41 15.93 2.07 4.98 2.78

Scenario 1 Scenario 2 Scenario 1 Scenario 2 Scenario 1 Scenario 2 Scenario 1 Scenario 2 Scenario 1 Scenario 2

Less than 250 TND

Scenario 1: Subsidies unchanged.Scenario 2: Subsidies gradually removed from 1997–2006.

Cereals Meat Fish Milk, dairy and eggs Fruits Vegetables Potatoes Oils and fats Other foods

Food products

Table 8 Forecasts of average budget share at various income levels (%) B. Dhehibi, J.M. Gil / Food Policy 28 (2003) 167–186 181

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one of the first attempts to model food demand in Tunisia. Food consumption patterns have been projected up to the year 2006 using two alternative policy scenarios. In most cases, elasticities used in the past were based on subjective judgments and were not supported by empirical evidence. In recent years, some single regression models have been estimated pooling cross-section and time series data. In this paper, a flexible demand model is presented in which economic theory restrictions are held. Alternative dynamic specifications have been tested and an autoregressive model has been chosen. The estimated model is used to calculate demand elasticities and to examine the effects of two policy scenarios on demand trends: no changes and gradual removal of subsidies. In general terms, meat and fish products are more food expenditure elastic, showing a negative trend in recent years. Results indicate that maintaining consumer price subsidies could distort incentives towards the consumption of subsidized products, reinforcing the negative evolution of fish, meat, milk and fruits consumption. Independently of the chosen scenario, total food consumption increases due to population growth. However, when subsidies are gradually removed, it is possible to keep the demand for most food products growing, except for fish. We have also tried to shed some light on the effectiveness of food subsidies in terms of the welfare of various income groups. Results indicate that a gradual subsidy removal would not generate significant changes in food expenditure structure. However, taken into account that real income is assumed to remain constant and, according to 1995 data, the lower-income group would need to increase food expenditure by 5 or 6 percentage points, in order to get similar consumption levels than those existing in 1995. In any case, these results should be interpreted with caution as income elasticities for food products are likely to vary substantially by income group, supposition that can not be considered in this study as no data were available to calculate such elasticities. The impact on the higher-income group is less significant, since subsidized products are relatively less important for them. Policy makers should take into account not only the economic but also the political consequences of any reform on food subsidies, as past experience has shown that social reaction can be quite explosive. Gradual subsidy reform has been proved to be useful, politically. In relation to food consumption, the generated income losses for the lower income group should be compensated in some way. Alternative agricultural policies based on a deficiency payments system could be implemented to increase self-sufficiency for retail staples and other traditional food products that are domestically produced without affecting too much consumer prices. On the other hand, prices should be kept at a reasonable level by promoting competition at all stages of the food supply chain. Finally, food stamp programs designed to compensate income losses could benefit lower-income groups. Further research is needed to project the cost of these alternatives.

Appendix A Table A1.

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Table A1 Unit subsidies by product Value

Share of product value

1986 Gros pain (DT/500 grams) Baguette (DT/250 grams) Flour (DT/Kg) Semolina (DT/Kg) Pasta (DT/Kg) Couscous (DT/Kg) Cooking oil (DT/liter) Sterilized milk (DT/liter) White sugar (DT/kg)

1995

0.057 0.016 0.064 0.11 0.16 0.17 0.17 0.1 0.90

0.05 0 0 0.25 0.26 0.27 0.46 0.19 0.40

1986

1995

41% 19% 25% 42% 38% 38% 36% 25% 79%

25% 0% 0% 52% 37% 38% 52% 26% 41%

Note. DT = Tunisian dinar. Source: Tuck and Lindert (1996).

Appendix B The linearised AIDS model in budget share terms is defined as follows: yt wit ⫽ ai ⫹ biln( ) ⫹ Pt

冘 n

gij lnpjt ⫹ uit

(B1)

j⫽1

where wit is the average budget share of the i-th good during period t (t = 1,2,T); yt is the total expenditure during period t; Pjt is the price of the j-th during period t and Pt is the price index during period t where

冘 n

lnpt

wilnpit

(B2)

i⫽1

and where wi is the average budget share of the i-th good. Adding-up implies that ⌺ni = 1ai = 1; Σni = 1bi = 0 and Σni = 1gij = 0 while homogeneity and symmetry imply that Σnj = 1gij = 0 and gij = gji, respectively. The negativity condition implies that the matrix C with elements Cij defined as Cij ⫽ gij ⫺ dijwi ⫹ wiwj

(B3)

is negative semi-definite, where dij is 1 if i = j and 0 otherwise. Terms wi, wj are the average budget shares of food group i and j, respectively. Since the rank of the C matrix is (n ⫺ 1), the negative semi-definite condition will be satisfied if one eigenvalue is zero while the rest are negative. Price and total food expenditure elasticities were computed using the estimated model parameters and the sample average values of budget shares (Deaton and Muellbauer, 1980).

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Appendix C Following Anderson and Blundell (1983b), the general dynamic AIDS model assuming a first-order autoregressive distributed lag model can be expressed in an error correction form as follows: ⌬ Wt ⫽ ⌬Xt ⌽A⫺(Wt⫺1 ⫺⌽Xt⫺1)l ⫹ Ut

(C1)

where wt is a vector of budget shares; Xt is a matrix of exogenous variables (real food expenditure and prices); A is a matrix that relates short- and long-run coefficients; l is the adjustment coefficients matrix; and ⌽ is the long-run coefficients matrix. Equation (C1) can be reduced to other dynamic specifications such as the partial adjustment model (PA), the first-autoregressive model (AR) and the static model, depending on the parameter restrictions imposed. If A = l is imposed, the model (C1) yields the partial adjustment model: ⌬ Wt ⫽ (Xt ⌽⫺Wt⫺1)l ⫹ Ut

(C2)

If A = I, the result is the first autoregressive model: Wt ⫽ Xt ⌽⫺(Wt⫺1 ⫺⌽Xt⫺1)r ⫹ Ut

(C3)

where r = I⫺l Finally, if A = l = I is imposed, the following static model is obtained: Wt ⫽ Xt ⌽ ⫹ Ut

(C4)

The model defined in (C1) is still too general for estimation purposes. To avoid the large number of parameters which has to be estimated using a relatively small sample, a diagonal adjustment is assumed; that is, the matrices A and l must be scalar. Hence, all equations in the system adjust in the same way to deviations from the long-run equilibrium. In any case, the adding-up condition is guaranteed.

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