Incorporating nutrients into meat demand analysis using household budgets data

Transcription

1 1 Incorporatng nutrents nto meat demand analyss usng household budgets data Ana María Angulo Correspondng author Departamento de Análss Económco Facultad de Cencas Económcas y Empresarales, Gran Vía, 2, Zaragoza (Span) Phone: Fax: E-mal: aangulo@posta.unzar.es José María Gl CREDA-UPC-IRTA Edfc ESAB- Parc Medterran de la Tecnologa Av. del Canal Olmpc, s/n Castelldefels (Barcelona-Span) Phone: Fax: E-mal: chema.gl@upc.edu Abstract The objectve of ths paper s to analyze the Spansh demand for meat takng nto account the consumer s concern about the relatonshp between food det and health. Ths concern s forcng food demand analysts to assume that consumer utlty s a functon of nutrents nstead of smply the food products themselves. Nevertheless, these utlty functon arguments are not produced n the marketplace but rather at home. As a consequence, n ths paper household producton theory s followed n order to analyze Spansh demand for meat usng the Quarterly Natonal Expendture Survey for Demands for several meat products (the nput n the model) are derved from the translog cost functon. Censored regresson models are used n the estmaton process, snce many zero responses are reported. Fve broad categores, eght nutrents and the most relevant soco-economc varables are consdered. Fnally, a set of elastctes s calculated wth respect to all the varables ncluded n the analyss. JEL Classfcaton: D13, C24, I12 Key words: Spansh meat demand; Nutrent ntakes; Health awareness; Household producton theory; Zero expendtures. Submtted Revsed receved Accepted

2 2 1. Introducton In recent years there has been a general concern about the relatonshp between health and food det. In most developed economes the ncdence of cancer, cardovascular dsease and other mortal dseases s growng at an alarmng rate. Wllet (1994) has ponted out that an unbalanced food det could explan ths trend. In the last twenty years a number of papers have analyzed ths relatonshp. Capps and Schmtz (1991), Burton and Young (1996), Knnucan et al. (1997), Km and Chern (1999), and Ben Kaaba et al. (2001), among others, ncorporate so-called health nformaton ndexes nto food demand systems n order to take nto account the effect of the consumer s knowledge about the relaton between nutrents and health. As regards cross-sectonal data analyzes, most of the lterature ncorporatng nutrtonal nformaton measures the mpact of ncome, prces and soco-demographc varables on nutrent ntakes. Two dfferent measurement technques are typcally used. Drect measurements are obtaned through a regresson of nutrent ntake on relevant varables (Adran and Danel, 1976; Nayga, 1994; Ramezan, 1995; Subramanan and Deaton, 1996; Chesher, 1998; among others). Alternatvely, ndrect measurements are made n two steps. Frst, the relevant varable effects on the demand for food products are calculated by estmatng a demand system. Then, nutrent ntake effects are obtaned by applyng nutrent converson factors to these food effects (Xao and Taylor, 1995; Ramezan et al., 1995; and Huang, 1999). Nevertheless, most studes that use cross-sectonal data analyze the demand for nutrents more than the demand for food. The applcablty of such results s lmted, snce nutrents are not drectly avalable n the market. It would be more useful to ncorporate the new nutrent ntake awareness nto a demand model that enables us to make conclusons about food demand (n terms of changes n quanttes consumed of dfferent products) rather than nutrent demand. The am of ths paper s to use such an approach to analyze the Spansh demand for meat. Apart from other nutrtonal characterstcs, meat products, together wth eggs, cow s mlk and fsh, are often referred as hgh-qualty proten provders for human health. Although from the standpont of nutrton, the human body does not requre protens per se, t requres essental amno acds that are present n detary protens. They are called essental as they

3 3 cannot be syntheszed by mammals, at least n the amounts needed, and are therefore essental consttuents of a balanced det for humans. 1 From the methodologcal pont of vew t s assumed that the consumer utlty functon s a functon of nutrents and not of the goods themselves. It s not unrealstc to assume that consumers are startng to thnk more n terms of food nutrents than n terms of food products, whle also takng nto account prces and dsposable ncome. Also, t s assumed that these utlty functon arguments are best obtaned through a household producton technology, usng the consumed food products as the man nputs. Once a functonal form for the obtaned cost functon s adjusted, the analyss of food demand can be carred out as an analyss of nput demand. Fnally, the model s mproved ncorporatng certan soco-economc varables. The model s estmated usng the Quarterly Natonal Expendture Survey for Snce a large number of zero purchases are reported, several models takng ths problem nto account are estmated and tested. The paper s organzed as follows. The next secton presents some descrptve data on meat demand n Span. Afterwards, the theoretcal model s explaned. Next, the data are descrbed and then the man results are presented. The paper ends wth some concludng remarks. 2. The demand for meat n Span Spansh food demand structure has stablzed n the last few years. Accordng to data from the Quarterly Household Natonal Expendture Survey for 1999, the average budget shares of dfferent types of meat, fsh and eggs n relaton to total food expendture were: beef, 9.12%; pork, 6.42%; poultry, 6.71%; fsh, 11.54%; and, fnally, eggs, 2.66%. 2 However, mportant famly dfferences appear n relaton to certan household characterstcs, as shown n Table 1. Fsh has the largest share for all categores of household lsted, except when the educaton level s secondary school, when the age of the household head s under 30 and when the percentage of members between 14 and 29 years old exceeds 75%; n each of these cases the share of beef s the largest. Pork has the second largest share only n rural areas and the egg expendture share s the lowest for all products. As the level of educaton of the head of the household ncreases, fsh expendture shares ncrease, whle pork, poultry and

4 4 egg shares decrease. Smlarly, as the sze of the town of resdence ncreases, beef and fsh expendture shares ncrease and the pork share decreases. As regards household sze, t s observed that whle n the cases of pork, poultry and eggs the hghest expendture share corresponds to relatvely large households (5 or more members), n the cases of beef and fsh t corresponds to smaller households (4 and 2 members for beef and fsh, respectvely). Fnally, regardng age, t s observed that as the percentage of members under 14 years old ncreases, more of the food budget s spent on pork and poultry. (Insert Table 1) Table 2 presents nformaton on the contrbuton of meat products to total nutrent ntake. Nutrents have been aggregated nto the followng eght broad categores: energy, protens, carbohydrates, lpds, vtamns, fbre, calcum and other mnerals. Jontly consdered, meats, fsh and eggs provde 16% of the total energy ntake, 44% of the total proten ntake, 27% of the lpd ntake as well as an mportant percentage of other mnerals and vtamns. (Insert Table 2) 3. Methodology The basc assumpton of the model s that, at least n more developed countres, nutrent ntake s becomng a more mportant determnant of food demand. In ths paper t s assumed that the consumer's preferences are nfluenced by food characterstcs. Ths approach s n lne wth the consumer goods characterstcs model ntroduced by Ladd and Suvannunt (1976) and the hedonc model dscussed by Nerlove (1995) 3. In ths scheme, consumers have complete quas-orderng over the set of all possble characterstc collectons, whch requres that preference orderng s transtve and complete. Furthermore, contnuty and strct convexty assumptons are also satsfed. 4 Nevertheless, n ths framework, assumptons of non-sataton and postve desre of all characterstcs cannot be satsfed n all cases. 5 That s, there s nothng to guarantee that consumers reacton to all characterstcs are always postve, n the sense that everyone prefers more rather than less of each characterstc, other thngs beng equal. Due to ths fact, n ths approach, t s necessary to

5 5 determne how to deal wth negatve characterstcs. Followng Lancaster (1971), the approprate strategy depends on the unversalty of such negatve reactons. That s, f the reacton to a characterstc s unversally negatve (everyone prefers less of a certan characterstc), the general structure of the analyss s preserved by smply takng the negatve of that characterstc. But t may be the case that some ndvduals can react to the same characterstc postvely whle others react negatvely, or even that a partcular ndvdual can react postvely at certan levels and negatvely at others. In such cases, the effcency crtera are no longer unversal. Whether to adopt the sgn change technque when there are dvded reactons to a gven characterstc s a matter of choce on an ad hoc bass. If the dstrbuton of preferences were such that most consumers vewed the characterstcs negatvely, t would presumably be convenent to change ts sgn; otherwse, t would be better to preserve t. Followng household producton theory (Becker, 1965; Lancaster, 1971), we assume that the vector a = [a 1,...,a r, a r+1,...,a p ] represents the levels of r nutrents and p-r characterstcs provded by food products (taste, smell, appearance, etc.). Of course, the components of a are not drectly sold n the market but they must be obtaned usng dfferent types of nputs. Furthermore, let q=[q 1,...,q n, l 1,...,l s ] represent the total set of nputs needed n the producton process whch can be decomposed nto a vector of n food nputs (q f, f=1,...,n) and s labour nputs (l b, b=1,...,s) whch can be bought n the market at prces p=[p 1,...,p n, s 1,...,s s ]. Correspondngly, p f represents the prces of food nputs and s b the wages of labour nputs. In ths study, the vector a represents the new argument of the consumer utlty functon. Households purchase market goods n quanttes q wth the purpose of jontly producng non-market commodtes a whch yeld utlty accordng to U = U (a), where U ( ) s assumed to be quas-concave. Let the jont producton functon be F(q, a) = 0. 6 It s assumed that F ( ) s neoclasscal ; that s, gven q, the producton possblty fronter n a s concave, and the soquants n q gven a are convex. In addton, the tradtonal budget constrant y = p q holds. Ths optmsaton problem can be solved n two stages: In the frst stage, the household tres to mnmse the cost (C = p q) of producng any gven bundle a. From the Lagrangan: l 1 = p q + π (F (q,a)), the followng cost functon s obtaned, whch represents the mnmal short-run cost of obtanng a bundle a at gven prces

6 6 p: C = C (p, a). (1) In the second stage of the procedure, the household tres to maxmze the utlty functon U = U (a) subject to the constrant y = C (p, a). Solvng the frst order condtons derved from the Lagrangan, l 2 = U (a) + λ ( y - C (p, a) ), demand functons for the commodtes ncluded n bundle a are obtaned: a k = a k (y, π) k=1,..., p, (2) where y s the total budget and π =(π,..., π p ) s the vector of the shadow prces. Once the theoretcal foundaton s establshed, and takng nto account that the man nterest of ths study s to present the fnal conclusons n terms of products avalable n the market, we wll only concentrate on the frst stage of the procedure. Ths wll enable us to form conclusons about food products, consdered as the man necessary nputs that enable food consumers to get those commodtes they consder valuable. To attan ths objectve, a functonal form for (1) has to be chosen. The translog cost functon s adopted, snce t has been wdely used n related lterature. Formally, ths cost functon can be wrtten as: ln C = α / 2 α ln p k h kh + β ln a k k β k ln a h ln a k + 1/ 2 θ + 1/ 2 k k j j α ln p ln p ln a k ln p j, (3) Dfferentatng (3) wth respect to each of the nput prces and applyng Shephard s lemma, nput budget share equatons can be derved as follows: lnc / ln p = w = α α ln p 1/ 2 θ ln a, (4) + + j j j k k k where w = q p /C s the th nput budget share. The α and θ parameters show the effect of changes n p and a on factor shares, respectvely. If θ k equals zero for all and k, the household producton technology s

7 7 homothetc, meanng that the nput shares are not affected by the levels of varous nutrents or food characterstcs. Fnally, dfferences n the expendture allocaton explaned by the relevant socoeconomc household characterstcs are gathered through the ntroducton of all these varables (denoted by SE g, g = 1,...,z), thought the ndependent term. Then, n (4) substtuted by (Pollak and Wales, 1981): α z * = α + ϕ g g= 1 SE g α s. (5) 4. Data and prelmnary analyzes Data come from the Spansh Quarterly Household Natonal Expendture Survey, whch provdes quarterly nformaton on the expendture and quantty of varous classes of food products consumed by a stratfed random sample of 3,200 households. Each quarter, nformaton s collected from each household durng one week. Theoretcally, one household stays n the survey for eght quarters. However, n practce, only a few households stay n the sample for the maxmum perod. So, for ths study, we only nclude those households that partcpated throughout the year n queston, Ths strategy leads to a fnal sample of 1657 households. Consumpton s aggregated n order to obtan yearly food consumpton. The survey gathers nformaton on a lmted number of household characterstcs ncludng the level of educaton and man actvty of the head of the household, household ncome, household sze, age and sex of famly members and town sze, among others. Nevertheless, no nformaton s provded ether n relaton to labour nputs n meal preparaton or wth respect to the wage pad to meal preparers. As a consequence, the labour varables and the wages are deleted from vectors q and p, respectvely. In a smlar way, whle t s possble to measure nutrent ntakes by applyng converson factors to the consumed quanttes, t s mpossble to measure the rest of the perceved food characterstcs such as taste, smell or appearance. To be consstent wth prevous lterature 7, we assume that dfferences n tastes and n other non-observable attrbutes are manly represented by, and are determned by, the dfferences n household characterstcs gathered n (5).

8 8 Usng ths household nformaton and the model defned n the prevous secton, we must now solate meat demand from other food groups. If weak separablty of preferences apples, then multstage budgetng would allow us to focus only on meat products wthout consderng the rest, thereby obtanng condtoned demand elastctes. If not, another soluton must be found. Let us consder ths queston. As the model stands, the consumer utlty functon depends on attrbutes obtaned from goods nstead of dependng on the goods themselves. Usng ths scheme, we suppose that, n general, a food group wll be analyzed separately from other types of goods such as clothes, footwear, etc., due to the fact that the margnal substtuton relatonshp between any par of nutrents (or any other characterstc) wll be, n general terms, ndependent from any type of attrbute, as mght characterze clothes, footwear, etc. 8 Nevertheless, does the same statement apply n comparng dfferent food groups such as cereals, meat, fats, vegetables...? In other words, s the margnal substtuton relatonshp between calores and protens comng from cereals ndependent from calores comng from meat, for nstance? In our vew the answer s generally no, because a ratonal consumer tres to get a nutrtonally balanced det wthout consderng the orgn of the nutrents. That s, consumers do not dstrbute ther purchases n order to obtan a concrete percentage of total nutrents from a certan food group. They are nterested n total nutrent ntake. Hence, we can conclude that the second stage of multstage budgetng does not apply to the case under study. Takng nto account the habts of Spansh food consumers as mentoned n Secton 2, we analyze the dfferent types of meat for whch data are avalable -beef, pork and poultry- as well as fsh and eggs. One of the followng two alternatves must be chosen: 1) specfy a food demand system wth varous classes of food products (dfferent types of cereals, meat, fats, vegetables...); or 2) specfy a system that ncludes the meat categores under study together wth one last category that covers the rest of the food groups. Although ths last category represents a qute heterogeneous aggregate, ts equaton could be the one deleted from the system to avod the sngularty of the resdual matrx due to the addng-up condton of a demand system. The frst strategy, although theoretcally accurate, results n a less parsmonous model. In addton, the second alternatve allows us to concentrate our attenton on the demand for anmal products. Hence, the second alternatve s preferred, although

9 9 separablty tests wll be carred out to check whether ths decson s supported by the data. Many concepts of separablty have been used, ncludng the dstncton as to whether there s weak or strong separablty, separablty of the utlty functon (drect), separablty of the ndrect utlty functon (ndrect), separablty of the cost or dstance functon (quas), separablty of an mplct representaton of the drect utlty functon (drect pseudo), and, fnally, separablty of an mplct representaton of the ndrect utlty functon (ndrect pseudo). Pudney (1981) provdes a formal defnton of each and uses them to mpose and test separablty n a smple constant elastcty model. Although each defnton requres a dfferent set of parametrc restrctons, Pudney shows that the varous defntons avalable make lttle dfference to the emprcal results. Consequently, followng Hayes et al. (1990), only the quas-separablty of our cost functon wll be tested. be wrtten as: Generally, preferences are quas-separable f the cost functon defned n (1) can also C ( p a) G[ g ( p, a),..., g ( p, )], 1 1 d d a =, (6) where goods are portoned nto d groups wth the prce subvector p,..., 1 pd, G s nterpreted as a macro cost functon and g d s nterpreted as a prce ndex for group d. Followng Deaton and Muellbauer (1980a, p. 134), the group budget shares ( w = C C ) may be derved from: dc d / w dc ln G =. (7) ln g d Intragroup budget shares ( w = p q / C ) may be derved from: d d w d ln g ( p ln p d d =, (8) d, a) where each vector group d. p d s composed of the prces of the ndvdual commodtes wthn the

10 10 Then, from Shephard s lemma, the share of subgroup wthn the total expendture ( w = p q C ) may be derved from: / ln = G g ln g d w = ln d ln pd w dc w d. (9) Dfferentatng (9) wth respect to the prce of good j n group e, we get: w ln G ln g ln g 2 d e α dje = =. (10) p je ln g d ln ge ln pd ln p je Takng each varable on the rght-hand sde of (10) n turn: ln G = ) wdc ln g d ) ln ln p g d = d w d ln w ) ln g v) dc ln ln p e je = α g e = w de je, where α de s the estmated cross-prce parameter between groups d and e, whch can be estmated from an aggregate model that has shares w dc and w ec as dependent varables. Hence, the restrcton that s mpled by the quas-separablty of the cost functon may be wrtten n terms of known shares and estmated parameters as: α = w w α. (11) dje d je de In other words, two groups, d and e, may be consdered separable f the compensated cross-prce effects between the share of good n group d and the prce of good j n group e ( e d ), satsfy the restrcton n (11). In order to mplement ths procedure, we must frst decde whch explanatory varables to nclude n the system. Takng equatons (4) and (5) nto account, the followng varables are ncluded: 1) the logarthm of the prces of the types of meat under consderaton as well as the logarthm of a prce for the rest of the food groups; 9 2) the logarthm of total nutrent ntake (klocalores, carbohydrates, lpds, vtamns, protens, fbre, calcum and other mnerals); and fnally, 3) the followng soco-economc characterstcs of households to capture dfferences n non-observable food attrbutes: total per capta food expendture (as an

11 11 approxmaton of per capta ncome), the sze of the town n whch the household lves, the level of educaton of the head of the household, the household sze and the percentage of household members wthn several age ntervals. The categores consdered for the last three varables are those ndcated n Table 1. Of these varables, total per capta food expendture and/or nutrent ntakes may not be exogenous 10. Furthermore, regardng consumers reacton to nutrents, t s supposed that although there could be dvded reactons to some of them (manly klocalores and lpds), reactons are far from beng unversal. 11 Therefore, followng Lancaster, the sgn change technque s not adopted n any case. Next, separablty tests are carred out n order to determne whether our prevous assumptons are confrmed by the data. The sequental procedure s straghtforward. To test the null hypothess of quas-separablty between meat (beef, pork and poultry) and fsh, the followng procedure has been followed. Frst, an estmate of α de s obtaned by usng a twogood model to explan the shares of meat and fsh. A second model s then estmated n whch ndvdual meat and fsh group shares are dependent varables. The predcted shares of the ndvdual meats are multpled by α de to obtan a set of parametrc restrctons that are then placed on the cross-prce terms between each meat prce and the fsh group prce. A lkelhood rato test s then performed to determne f the restrctons are accepted by the data. The calculated lkelhood rato s 26.42, whch s hgher than the crtcal value at the 5% level of sgnfcance, χ 2 (3) = Hence, at mean values, the null of separablty s rejected and, as a consequence, the dfferent types of meat and fsh must be ncorporated nto a sngle system. Takng ths nto account, we next determne whether these meat products and eggs can be jontly consdered n the system. Followng an analogous procedure, we obtan a lkelhood rato of 51.73, whch also s greater than the crtcal one at the 5% level, 2 χ (4) = Hence, beef, pork, poultry, fsh and eggs form part of the same demand system. Fnally, the analogous procedure s carred out to check the separablty of prevous products and the aggregate rest of food products. In ths case, the lkelhood rato takes a value of 62.96, hgher than the crtcal value of χ 2 (5) = , at the 5% level. Hence, we conclude that the chosen alternatve to meet our objectve of analysng the demand for dfferent meat products s not rejected by the data. 5. Estmaton results

12 12 Zero expendture problem When cross-sectonal data are used for the demand analyzes of specfc products, a large number of zero purchases can be reported durng short survey perods. For nstance, for the Spansh data we are usng, households have recorded ther consumpton durng only one week. 12 For ths knd of data, an ordnary least squares estmaton that s ether based on all, or on only the postve responses, generates based parameter estmates (Amemya, 1984). In addton, excludng the null responses also causes effcency losses and, n most cases, nconsstency. Therefore, a model that takes nto account the censored nature of the data must be specfed. In early studes, the Tobt model was wdely used, but ths s only approprate f the zero observaton s a corner soluton (t assumes that all households potentally consume the product). In recent studes, other models that take nto account dfferent explanatons for zero purchases have been used. Generally, there are three reasons for a zero expendture: 1) the survey perod s too short to allow consumers to report the purchase of a specfc product (nfrequency of purchase), 2) consumers are not wllng to buy the product (abstenton) and, 3) consumers do not purchase the product at current prces and ncome levels (corner soluton). Censored demand models can be classfed nto two broad categores: 1) doublehurdle models and 2) nfrequency models. One advantage of these models s that both decsons, whether to buy and how much to buy, may depend on dfferent sets of explanatory varables. In addton, these decsons can be jontly or ndependently modelled, dervng, respectvely, the smultaneous and the ndependent versons of the models. Let u and v be the error terms correspondng to the decsons to buy and how much to buy, respectvely. The jont dstrbuton of both error terms n the smultaneous versons of the two broad model categores s gven by: 1 ρσ ( u, v ) ~ BVN(0, Γ) where Γ = 2, (12) ρσ σ where BVN denotes bvarate normal and ρ s a correlaton coeffcent.

13 13 On the other hand f u and v are assumed to be ndependent (that s, ρ = 0 ) and u N(0,1), and v N(0,σ 2 ), the ndependent versons of two model categores s obtaned. Behnd the Double-Hurdle Model (DH) s the dea that a consumer has to overcome two hurdles before makng a purchase: 1) to decde to partcpate n the market (potental consumer); and 2) to actually buy. A zero expendture s recorded n those cases where consumers ether decde not to partcpate n the market, or havng decded to partcpate, they eventually do not buy. In the frst decson, any value of the explanatory varables (prce, ncome, etc.) s rrelevant, so non-purchase s due to conscentous abstenton. In the second one, potental consumers do not buy the product due to the exstng levels of the explanatory varables. Therefore, the DH specfcaton s approprate when zero expendtures result from true non-purchase responses that are based ether on conscentous abstentons or economc factors. The Infrequent Purchase Model also assumes that a consumer faces two decsons before a postve expendture s recorded. The frst decson s whether to purchase or not (purchase decson), and the second decson, to actually buy. As regards zero expendtures, n ths model a zero expendture results from one of two followng stuatons. On one hand, consumers have not purchased because as a habt the tem s purchased nfrequently (and not because of conscous abstenton as n the DH model). On the other, there are consumers who, havng decded to purchase, do not buy, basng ther decson on economc factors (corner soluton). In these cases the nterpretaton s smlar to that n the DH model. Ths s called the Tobt-Infrequency of Purchase (TIP) model. There s a partcular case n whch, havng decded to purchase, consumers always buy a postve amount of product (there are no corner solutons). Then the smultaneous/ndependent TIP model reduces to the smultaneous/ndependent Infrequency of Purchase Model (IP) defned by Blundell and Meghr (1987). Many versons of these models have been used n recent years (Blundell and Meghr, 1987; Gao et al., 1995; Burton et al., 1996; Su and Yen, 1996; Yen and Jones, 1997; and Angulo et al., 2001, among others).

14 14 Model selecton Frst, the three models defned above, n both versons, smultaneous and ndependent, are estmated for the fve man categores (beef, pork, poultry, fsh and eggs) usng Tme Seres Processor software (TSP Internatonal, 2005). 13 The maxmum lkelhood procedure and Newton s estmaton method for parameter covarance matrces are followed. Snce heteroscedastcty s lkely to be present n the dfferent models, models wth heteroscedastc errors are estmated by allowng the standard devaton, σ, to vary across observatons. In partcular, σ has been reparametrzed as follows: σ = exp ( H γ ), (13) where H represents the set of varables that generates the heteroscedastc problem. The exponental specfcaton has the desred property that the standard devaton, σ, s strctly postve. In Table 3 we present the maxmum lkelhood estmaton results for the dfferent models, together wth lkelhood rato values for testng the null hypotheses of homoscedastc errors. 14 As can be observed, n all cases the null hypothess s rejected and, consequently, heteroscedastcty s ntroduced n all models. (Insert Table 3) Second, a statstcal test for non-nested models (Vuong, 1989) s mplemented n order to determne whch model best fts the actual consumer purchasng decsons. Results are shown n Table 4. The model selecton process s dvded n three steps. Frst, the ndependent versus the dependent verson of each type of model s tested for all products. In all cases, the ndependent versons of the models seems to better ft the data. In a second step, the ITIP model s tested aganst the IIP one, snce, as mentoned above, IIP s a specal case of ITIP. As can be observed, n all cases the ITIP model s preferred. Fnally, the ITIP models are tested aganst the IDH models. The last two rows of Table 4 summarse the results. Whle for beef, poultry and fsh both models yeld smlar results, n the case of pork and eggs the ITIP models outperforms the IDH models. (Insert Table 4)

15 15 As the Voung test cannot dstngush between ITIP and IDH models for three out of fve products, the test for non-nested models proposed by Clarke (2003) s mplemented. Results are shown n Table 5 and ndcate that the ITIP model outperforms the IDH model for all products but beef for whch, as for the Voung test, ITIP and IDH models are not sgnfcantly dfferent. (Insert Table 5) Thrd, we test whether total per capta food expendture and/or nutrent ntakes can be consdered ndependent from the error term (exogenety) usng the Hausman test (Hausman, 1978). An nstrument for total per capta food expendture frequently used n lterature s per capta ncome, whch s not avalable here. In addton, nutrent ntakes are also qute dffcult to nstrument. We have decded to follow Wald (1940), and defne each nstrument as a dummy varable, whch equals 1 when the value of the respectve varable s over ts mean, and 0 otherwse. The Hausman tests yeld the followng values: beef, 23.20; pork, 15.91; poultry, 25.42; fsh, 41.78; and eggs, As all these values are less than the crtcal value at the 5% level of sgnfcance [χ 2 (57)= 75.62], the null hypothess of exogenety cannot be rejected. Fnally, the homothetcty hypothess s tested applyng a lkelhood rato test for each equaton. The null hypothess s clearly rejected snce all the obtaned values ( for beef; for pork; for poultry; for fsh; and for eggs) are well above the crtcal value at the 5% level of sgnfcance [ χ 2 (8) = ]. Hence, we conclude that the levels of nutrents consdered n ths study do affect nput shares. Summng up, two man conclusons are obtaned from these tests. Frst, the Spansh meat consumer makes two ndependent decsons: to purchase or not, and how much to purchase. Independency s an mportant economc concluson snce t mples that consumers decde whether to buy a product wthout consderng how much they are gong to purchase. Second, snce the ITIP model s never domnated, we conclude that Spansh zero expendture responses are due to a decson of no consumpton based on man economc determnants (ncome or prces) or purchasng habts (some goods are bought monthly or every ffteen days

16 16 and, then, t s possble that no record has been regstered by the household durng the week t was surveyed). 15 Elastctes The selected ITIP models can be specfed as follows: Purchasng decson: PD * = α + α ln p j j j + 1/ 2 3 ln a + ς PC + ν PY + ψ PA + ι E + µ STt k θ k 3 e e= 1 t= 1 + γ FE + ξ HS + u, (14) where * PD represents the latent partcpaton varable for the th product; FE represents the total per capta food expendture; HS, the household sze; PC, the percentage of members below the age of 14; PY, the percentage of members aged between 14 and 29; PA, the percentage of members aged between 30 and 59; E e represents the three levels of educaton; and fnally, ST t represents the three varables ntroduced to dstngush the sze of the town n whch the household lves. Expendture decson: * ' w = α + ' ' α ln p j j ' + 1/ 2 ' + ς PC + ν PY + ψ PA + j k θ ' k ln a 3 3 ' ι E + e e= 1 t= 1 + γ FE + ξ HS ' ' t ' µ ST + v, (15) where w * s the latent th product budget share, and the other varables are as defned above. Fnally, the error terms are ndependently and normally dstrbuted: 2 u ~ N(0,1) and v ~ N(0, σ ). The models are estmated by Maxmum Lkelhood. Estmated parameters (Table 6) have the expected sgns and most of them are sgnfcant at the 5% level. In any case, and for

17 17 nterpretaton purposes, the most nterestng ndcators are the dfferent demand elastctes that can be obtaned from estmated parameters. (Insert Table 6) The frst such elastcty s the so-called elastcty of partcpaton. It measures the effect that a percentage change n one explanatory varable has on the lkelhood of partcpatng n the market. 16 The second elastcty relates to the probablty of consumpton. It reflects the effect that a percentage change n one explanatory varable has on the probablty of consumpton. Next, we have the elastcty of the condtonal level of consumpton, whch measures the effect that a percentage change n a varable has on consumpton once the decson to consume has been made. Fnally, we calculate the elastcty of the uncondtonal level of consumpton or total elastcty, whch provdes an overall assessment of the effect changes n one varable on consumpton. All elastctes wth respect to all contnuous varables, together wth ther respectve standard errors, are calculated for all products at sample means. Results are presented n Table 7. (Insert Table 7) Prce and Income effects Although all own-prce elastctes are negatve, magntudes dffer consderably for the dfferent types of elastctes. The elastctes of partcpaton are much lower than the elastctes of the uncondtonal level of consumpton. In other words, changes n own prces do not affect very much the decson to partcpate n the market. They manly affect the quantty purchased. In ths case, the demand for pork and poultry are the most elastc. Wth regard to cross-prce effects, Table 7 shows that most of the elastctes of partcpaton are nsgnfcant. The man exceptons are the postve relatonshps between changes n fsh and pork prces and the probablty of purchasng beef. The elastctes of the uncondtonal level of consumpton show that fsh and eggs are complementary goods whereas some substtutablty exsts between poultry wth respect to beef and fsh, as well as fsh wth respect to beef. The elastcty of partcpaton wth respect to total food expendture s postve for all

18 18 products, reflectng the fact that when total food expendture ncreases (decreases), the probablty of purchase also ncreases (decreases). Consderng now the elastcty of the uncondtonal level of consumpton, beef and fsh can be consdered luxury products; the expendture elastcty for pork s around unty; and fnally, poultry and eggs are necesstes. The decomposton of the elastctes of the uncondtonal level of consumpton nto ts two components shows that changes n total food expendture affect consumpton manly through the condtonal level and not through the probablty of consumpton. That s, an ncrease n total food expendture s not lkely to nduce many margnal consumers to consume meat, but addtonal sales wll lkely come from exstng consumers. Nutrtve value effects Table 7 shows that the probabltes of purchasng all consdered products generally ncrease (decrease) when total proten, lpd and vtamn ntake also ncreases (decreases). The opposte takes place wth respect to total energy ntake. In general terms, most of the elastctes are rather small, ndcatng that ncreasng total nutrent ntake has a rather small mpact on the probablty of buyng meat products. For the elastctes of the uncondtonal level of consumpton, results are as expected. As mentoned n the ntroducton, meat products are the man supplers of a hgher-qualty proten ntake. Thus, the hghest postve elastcty corresponds to proten. From ths pont of vew an ncrease n the total proten ntake wll manly beneft beef and poultry. Analyzng the two components of ths elastcty we can conclude that the ncreasng consumpton of meat products due to an ncrease of the total proten ntake wll manly come from exstng consumers but also a sgnfcant ncrease of margnal consumers wll take place. The elastctes of calcum and other mnerals ntake are negatve, ndcatng that when the total ntake of such nutrents ncreases consumers buy food products wth a hgher content of calcum and other mnerals, and decrease meat consumpton. Negatve elastctes do not mean that meat products are undesrable. On the contrary, t means that other food products are more mportant supplers of these specfc nutrents, nducng consumers to ncrease the consumpton of these products. Demographc effects The elastctes of partcpaton are postve wth respect to the sze of the household for all products. Moreover, as the number of members wthn a household ncreases, the

19 19 uncondtonal level of beef consumpton also ncreases, whle the consumpton of the rest of the products do not sgnfcantly react to household sze changes. As regards the elastctes of famly composton (measured as the percentages of household members n several age categores), Table 7 shows that as the percentage of members between 14 and 59 ncreases, the probablty of purchasng poultry also ncreases, whle the probablty of purchasng fsh decreases. Smlarly, the older the members of a household are, the lower the level of pork consumpton and the hgher the level of fsh consumpton. Fnally, the effects of the level of educaton and town sze are analyzed. Snce dummy varables have been defned to take these effects nto account, margnal effects are calculated. The prncpal results from these analyzes are shown n Table 8. The level of educaton s postvely related to the probablty of purchasng beef and negatvely related to the probablty of purchasng pork. Households wth hgher level of educaton consume larger quanttes of beef and fsh, and less pork, poultry and eggs. Results also ndcate that those lvng n the smallest towns (less than 50,000 nhabtants) are the least lkely to purchase beef. Beef and fsh consumpton s hgher n large towns (between 50,001 and 500,000 nhabtants) whle more pork, poultry and eggs are consumed n smaller towns. (Insert Table 8) Implct prces As a fnal step n our study, and followng Nerlove (1995), we derve mplct prces that Spansh consumers attach to the margnal unt of the dfferent nutrents contaned n the dfferent products. Usng calculated total prce and nutrent elastctes together wth sample mean values for per capta nutrent ntake and prces, mplct prces adopt the followng expresson 17 : E ( q ) E ( q ) ak ak ak E ( q ) p π k = = k=1,..., r, (16) E ( q ) E ( q ) p ak p p E ( q ) where E ( q ) represents the uncondtonal level of consumpton.

20 20 Results are shown n Table 9. Not that negatve margnal prces are consstent wth the Consumer Goods Characterstc Model as some products attrbutes may be undesrable (Ladd and Suvannunt, 1976). Addng more of one of these characterstcs to a specfc product may reduce ts value to consumers. In any case, n ths study most negatve values are close to zero and are related to nutrents, whch are only contaned margnally n meat products. As mentoned n the ntroducton, meat products are man provders of hgh qualty protens. From ths pont of vew, Spansh consumers perceve beef as the hghest qualty meat n terms of proten ntake and eggs as the lowest qualty proten source. Implct prces for protens are smlar for the other meat products. (Insert Table 9) Fnally, to measure to what extent the demand elastctes are affected by the ncluson of nutrent values, we estmate a tradtonal Almost Ideal System (AIDS) model (Deaton and Muellbauer, 1980b), n the form of a ITIP model for comparson purposes, only ncludng ncome, prces and household characterstcs as man food demand determnants. Table 10 shows obtaned results of the elastcty of partcpaton and the elastcty of the uncondtonal level of consumpton. Several tests have been performed n order to check f sgnfcant dfferences exst between these elastctes and those shown n Table 7. As can be observed n Table 11, the dfferences are sgnfcant n most cases. From the comparson of magntudes obtaned for both types of elastctes, t can be observed that greatest dfferences are observed wth respect to expendture elastctes. The elastcty of partcpaton wth respect to total food expendture s substantally lower when nutrent values are ncluded. Fnally, the elastcty of the uncondtonal level of consumpton ncreases for beef and fsh when nutrents are ncluded and decreases for the other products. (Insert Tables 10 and 11) 6. Concludng remarks In ths paper, the demand for meat s analyzed takng nto account ts nutrtonal characterstcs based on the assumpton that, at least n more developed countres, nutrent ntake s an ncreasngly mportant determnant of food demand. The model s constructed so that the consumer s utlty functon does not depend on meat quanttes but s a functon of

21 21 nutrent ntakes and other prepared food characterstcs. Snce these new utlty functon arguments are not drectly avalable n the market, they are derved from several nputs usng household producton theory. Fnally, non-observable characterstcs such as taste or smell are ndrectly consdered n the fnal model by ntroducng the most relevant household socoeconomc characterstcs. In order to valdate the model obtaned, the Spansh demand for meat s analyzed usng mcro level data. Snce a large number of zero responses were obtaned, several censored regresson models are used and formal tests have been carred out to select the model that best fts the data. From the estmated parameters, meat demand elastctes wth respect to prce, nutrent content, expendture and the rest of the ncluded demographc varables are derved. Two man sets of results are obtaned. Frst, from the selected models, we deduce that zero responses are manly due to a ratonal decson not to consume, based ether on economc factors or on purchasng habts. Second, from the calculated elastctes, the followng prncpal mplcatons are obtaned: ) changes n own prces manly affect the quantty of meat purchased and not the decson to purchase or not; ) the probablty of purchasng beef s postvely related to changes n fsh and pork prces; ) fsh and eggs are complementary goods whle some substtutablty exsts between poultry wth respect to beef and fsh, as well as between fsh and beef; v) as regards nutrent ntake, the hghest postve uncondtonal elastcty corresponds to total proten ntake; v) all consdered products are more lkely to be purchased as total food expendture ncreases; v) beef, fsh and, less clearly, pork are luxures whle poultry and eggs are necesstes; v) the probablty of purchasng all products as well as beef consumpton ncrease wth household sze; v) fsh consumpton ncreases as the members of a household get older; x) there s a postve relatonshp between the educaton level of the head of household and the probablty of purchasng beef as well as the consumpton of beef and fsh; and fnally, x) households lvng n large towns tend to consume more beef and fsh. The approach we employ can provde new nsghts nto food consumpton behavor. Moreover, t s mportant to note that the man advantage of the model that we propose, n comparson wth alternatves presented n the lterature, s not the possblty to obtan nutrent ntake elastctes but to offer a new framework n whch demand elastctes (ncome

22 22 and prces) are determned by nutrent content. As demonstrated n last secton, estmated demand elastctes dffer substantally dependng on whether or not nutrent varables are ntroduced. Future research could be drected towards refnng some of the econometrc ssues rased here. One of these ssues concerns the exogenety of the total expendture and nutrent ntake varables. Although n ths paper the null of exogenety s not rejected, t s not entrely clear that approprate nstruments have been used. Other nstruments could be desgned n the form of ndexes to better cope wth ths problem. Achnowledgements We thank to the project SEC of the Plan Naconal de Investgacón Centífca, Desarrollo e Innovacón Tecnológca, for fnancal support. REFERENCES Adran, J., Danel, R., Impact of the Soco-economc Factors on Consumpton of selected Food Nutrents n the Unted States. Amercan Journal of Agrcultural Economcs 58, Amemya, T., Tobt models: a survey. Journal of Econometrcs 24, Angulo, A.M., Gl, J.M., Graca, A., The demand for alcoholc beverages n Span. Agrcultural Economcs 26, Becker, G.S., A theory of the allocaton of tme. Economc Journal 75, Ben Kaaba, M., Angulo, A.M., Gl, J.M., Health Informaton and the Demand for Meat n Span. European Revew of Agrcultural Economcs 28(4), Blundell, R., Meghr, C., Bvarate Alternatves to the Tobt Model. Journal of Econometrcs 34, Burton, M., Dorsett, R., Young, T., Changng Preferences for Meat: Evdence from UK household data, European Revew of Agrcultural Economcs 23, Burton, M., Young, T., The mpact of BSE on the demand for beef and other meats n Great Brtan. Appled Economcs 28, Capps, O., Jr. Schmtz, J.D., A recognton of health and nutrton factors n food demand analyss. Western Journal of Agrcultural Economcs 16, Clarke, K.A., Nonparametrc Model Dscrmnaton n Internatonal Relatons. Journal of Conflct Resoluton 47(1),

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25 25 APPENDIX Assume that the purchase and expendture decson components of the ITIP model are specfed, respectvely, as follows: PD = z α + u where PD = 1 f * PD > 0, * * w = x β + v where w w Φ ( z α ) f PD = * * w > 0 and > 0, wth ~ N(0,1) * 2 u and v ~ N(0, σ ). 1. The elastcty of partcpaton s calculated from the margnal response of the partcpaton probablty and, based on the ITIP structure and normalty assumptons of the error terms, t s equal to: P ( PD = 1) zj zj = φ (zα) α j. zj P ( PD = 1) P ( PD = 1) 2. The elastcty of the probablty of consumpton s calculated from the margnal effect of x j on the probablty of consumpton as follows: xβ Φ ( zα ) Φ ( ) P ( w > 0) xj σ xj =. xj P ( w > 0) xj P ( w > 0) 3. The elastcty of the condtonal level of consumpton s calculated as follows: E ( q q> 0 ) xj, xj E ( q q > 0 ) where C E ( q q> 0 ) = E ( w w > 0 ), P and 1 xβ 1 0 ( ( Φ(z α ) w - x β E( w w > ) = Φ z α ) Φ ) w 0 ϕ d w σ. σ σ 4. The elastcty of the uncondtonal level of consumpton or total elastcty s calculated as