Nutrition transition in two emerging countries: A comparison between China and Russia

Transcription

1

2 Nutrton transton n two emergng countres: A comparson between Chna and Russa Chrstne Burggraf 1, Lena Kuhn 1, Qran Zhao 1, 2, Ramona Teuber 1, Thomas Glauben 1 1 Lebnz Insttute of Agrcultural Development n Transton Economes IAMO, 06120, Halle, Germany 2 College of Economcs and Management, Chna Agrcultural Unversty, Beng , P.R. Chna Abstract: Ths study provdes emprcal evdence on the lnk between economc growth, nutrton, and health n two emergng economes, Chna and Russa. Both countres have experenced rsng average ncomes, accompaned by an ncreasng rate of nutrton-related chronc dseases n recent years. Thereby, the hgher growth rate of the occurrence of obesty n Chna suggests a certan catchng-up effect and tremendously ncreasng problems wth chronc dseases n the longer run, especally n urban areas of Chna. Further, our results ndcate that wth ncreasng household ncomes over tme the demand for carbohydrates decreases, whle the demand for meat and dary products, as well as fruts ncreases. Ths s a development generally known as nutrton transton. Fnally, our estmaton results of a Quadratc Almost Ideal Demand System QUAIDS underscore the fndng that ncome growth n Chna and Russa tends to ncrease the demand for anmal-based products much stronger than the demand for carbohydrates. Keywords: nutrton transton; food demand; QUAIDS; Chna; Russa 1 Introducton Epdemologcal experences n western socetes show that wth economc growth, detary patterns shft towards a det that s hgh n fat, especally saturated fats, cholesterol, sugar and other refned carbohydrates, but low n unsaturated fats and fber Popkn These maor detary changes, usually referred to as nutrton transton, are often characterzed by an ncreasng share of anmal food products Popkn Such a shft n detary patterns s consdered to be a maor mpact factor of the ncreasng prevalence of obesty, cardovascular dseases Hu et al. 2000; Popkn 2007; Shepard et al. 2001, type 2 dabetes melltus Montonen et al. 2005, and varous forms of cancer Beydoun and Wang 2008; Popkn However, nutrton transton s certanly not exclusvely takng place n developed countres. Over the last few decades, many emergng and developng countres have experenced the same trends n detary patterns and ther consequences on publc health Popkn For example, n Chna, where polcy makers stll prmarly focus on the allevaton of malnutrton, ncreases n det-related, non-communcable dseases such as obesty can be noted Tan and Yu In Russa, cardovascular dseases, dabetes melltus or chronc respratory dseases sgnfcantly contrbute to the country s worryng morbdty and mortalty rates Sedk et al Accordng to the World Health Organzaton 2014, wth rsng ncomes dseases connected to excessve or unbalanced dets lke cardovascular dseases, dabetes or certan knds of cancer gradually replace 1

3 undernourshment and hygene-related factors as maor causes of death. Ths steadly ncreasng ncdence of nutrton-related chronc dseases seems to be caused, at least partally, by rapd shfts n food systems, food prcng and marketng. Thus, for desgnng and mplementng effectve publc nterventon programs, t s mportant to understand the maor drvers of these dynamcs Popkn As Popkn 2001 ponts out, epdemologcal shfts often dffer across countres and regons snce an ongong nutrton transton s closely connected to a country s partcular hstorc and cultural characterstcs, whch are clearly not transferrable to any other country. Even though an extensve body of lterature on food demand and nutrton transton n Chna exsts e.g. Huang and Rozelle 1998; Gould 2002; Yen et al. 2004; Gould and Vllarreal 2006; Lao and Chern 2007; Gale and Huang 2007; Huang and Gale 2009; Zheng and Henneberry 2009; Hovhannsyan and Gould 2011; Hovhannsyan and Gould 2014; Zhou et al. 2015; Wang et al. 2014, only two comparatve studes on ths topc are avalable Montero et al. 1995; Delgado However, both studes use rather old data and do not estmate a food demand system. Our research addresses the ssue of economc growth and nutrton transton n a comparatve way by focusng on two large emergng economes, namely Russa and Chna. A comparson of Chnese and Russan food demand controls for a consderably wde range of cultural, economc and geographcal dfferences. Both countres have experenced rather hgh growth rates of percapta GDP between 1997 and Even though the growth rates n 2009 were sgnfcantly hgher n Chna 15.4 % p.a. than that n Russa 6.4 % p.a., the per-capta GDP was stll twce as hgh n Russa compared to Chna 13,616 PPP-USD and 6,207 PPP-USD, respectvely; World Bank In terms of ncome dstrbuton, the two countres are rather smlar, whch s reflected n a GINI Index of 40.1 for Russa and 42.1 for Chna n In contrast, the rato of rural to urban populaton s sgnfcantly dfferent between these two countres. In Russa, 73.7% of the populaton s lvng n urban areas, whle n Chna ths share amounts to 49.2 % Unted Natons Gven these smlartes as well as dfferences, we analyze n whch way expendture growth as a maor drver of nutrton transton has sgnfcantly changed the consumpton of dfferent food aggregates, as well as how these effects dffer between Chnese and Russan consumers. Therefore, we estmate the expendture elastctes of nne dfferent food aggregates and fve dfferent meat aggregates for Chna and Russa by applyng a Quadratc Almost Ideal Demand System QUAIDS. Moreover, consderng the strong rural-urban nexus n both countres, we also dsplay results for urban and rural areas separately. The remander of ths paper s structured as follows. In secton two, we descrbe the two employed data sets. Secton three dscusses recent trends n nutrton-related health outcomes. Secton four ncludes a descrptve analyss of food consumpton trends. In secton fve we present the estmaton procedure and our emprcal results. We conclude n secton sx

4 2 Data For our descrptve and emprcal analyss, we use data from the Chnese Health and Nutrton Survey CHNS; see CHNS and the Russa Longtudnal Montorng Survey RLMS-HSE; see RLMS- HSE Both the CHNS and the RLMS-HSE are prmarly organzed and coordnated by the Carolna Populaton Centre. Both data sets provde a wde range of nformaton on socoeconomc characterstcs, food expendtures, and food producton at the household level, as well as health status ndcators and detary ntakes at the ndvdual level. Furthermore, both data sets are representatve for the respectve country. The RLMS-HSE data set contans nformaton on more than 4,000 households wth about 11,000 ndvduals lvng n them. The CHNS data set was conducted n nne waves between 1989 and 2011, and gradually ncreased over that tme; by 2011, the sample covered more than 14,000 ndvduals n over 5,800 households. In order to use both prce and consumpton data for each year of our analyss, the tme perod for the CHNS analyss of the Chnese food consumpton patterns s restrcted to For a comparable transton perod of 13 years, we employ the RLMS-HSE Phase II data from n the Russan case. Thereby, our calculatons are based on both household food consumpton data and communty prce data after the deleton of severe outlers. A comparson of the food consumpton data wth addtonal sources,.e. data from the Russan Government Commttee of Statstcs GKS for 2008 Government Commttee of Statstcs 2011 or 2009 data from the Natonal Bureau of Statstcs Chna NBS; Natonal Bureau of Statstcs 2010 yelds comparable average consumpton trends and values for both countres across most food tems. We only notced consderable dfferences between the Russan data set and the GKS data regardng the amounts of consumed potatoes. Ths dfference can be explaned by the fact that potatoes are heavly harvested by Russan famles, and only the RLMS-HSE drectly keeps track of the exact amount of potatoes harvested for famly use n the accordng year. 2 Ths underscores the representatveness of the RLMS-HSE and CHNS food consumpton data. Accordng to Rozelle et al. 2006, we base our estmatons on communty prces nstead of unt vales. Mssng communty prces were mputed frst by multple mputatons of chaned equatons usng the bootstrap opton. Afterwards, mssng prces were mputed by regonal medans. Despte ther rchness and representatveness, both data sets have certan lmtatons. Frst, for the consdered tme perod the CHNS offers only fve waves, whle the RLMS-HSE offers eleven waves. Hence, the waves of the Chnese and Russan surveys do not always exactly match. However, the length of the observed transton perods, 13 years, s equal for both countres. Second, the RLMS-HSE food consumpton data s only collected durng wnter months and s therefore not seasonally representatve. Lkewse, CHNS nutrton data s collected between August and December. However, the survey rounds 2 GKS per-capta consumpton of food tems ncludes food tems bought, prvate consumpton of food tems wthn 14 days whch are free of cash costs e.g. presents, household producton, wage equvalents, and food tems stored on the frst and last day of the observaton perod, but not produced wthn the year GKS. 3

5 are comparable, whch allows us to examne yearly changes durng the wnter perod, as well as populaton level changes Jahns et al Thrd, we do not take nto account food eaten away from home FAFH because of the followng reasons. Even though the CHNS provdes consumed quanttes of FAFH, t does not offer the respectve expendture or prce data. CHNS prce data avalable n the Chnese dataset s based on market prces of basc foods but does not reflect restaurant prces, whch also nclude servce costs. In the RLMS-HSE data, FAFH expendtures are only provded at an aggregated level of total FAFH expendtures wthout nformaton on specfc food products for FAFH consumpton or respectve prce data. Therefore, n order to provde comparable and unbased estmaton results, our analyss s based on food eaten at home. 3 Health and health expendtures Although parts of the Chnese socety are stll affected by malnutrton see e.g., Wang 2005, n ths study we focus on the growng prevalence of obesty and chronc dseases durng nutrton transton. 3 Several studes attest an ncreasng prevalence of obesty and chronc dseases n both countres Kalchman et al. 2006; Wu 2006; Wang et al. 2007; Abegunde and Stancole 2008; Nugent 2008; Yang et al Accordng to the WHO 2015, obesty s expected to rse at an alarmng rate, whch s descrbed as one of the greatest publc health challenges of the 21st century. Therefore, ths secton gves an overall vew of the current stuaton and trends regardng obesty and other det-related chronc dseases n Chna and Russa, consderng dfferences between rural and urban areas. In Russa, more than 50% of the populaton can be consdered overweght or obese, wth obesty prevalence rsng from % n 1996 to % n 2008 see Fgure 1. Furthermore, Fgure 1 shows that n 2000/2001,.e. shortly after the year of a stark economc crss n 1998, the prevalence of overweght or obesty was lower compared to the tme perods before and thereafter. Durng ths perod of tremendous economc stress, a large reducton n the energy densty of the average Russan det occurred Wang et al Ths reduced energy densty of the average Russan det resulted n a lagged lowerng of overweght and obesty occurrence. These fndngs are n accordance wth the results of Stllman and Thomas 2008, who state that transtory changes n expendtures are postvely and sgnfcantly assocated wth total calorc ntake and fat ntake, as well as a delayed adult BMI. Addtonally, Fgure 2 shows that even though obesty rates are stll consderably low n Chna, there s a rapd shft towards ncreased obesty among the Chnese populaton, whch s n lne wth the fndngs of Popkn 2001 and Du et al Accordng to our data, Chnese obesty prevalence ncreased from 0.19% n 1997 to 4.01% n Furthermore, our data suggests that obesty n Chna was hgher n urban than n rural areas, whle n Russa t was lower n urban areas compared to rural areas 2011 and 2008, respectvely. 3 The World Health Organzaton 2013 defnes overweght as an BMI>25 and obesty as an BMI>30. 4

6 Obesty prevalence Obesty prevalence 25% Chna 25% Russa 20% 20% 15% 15% 10% 10% 5% 5% 0% % Obesty urban Obesty rural Obesty urban Obesty rural Fgure 1: Prevalence of overweght or obesty [n % of sample] Source: Own calculatons based on RLMS-HSE and CHNS Note: Wth a sgnfcantly postve trend for total obesty rates over tme at the 5% level. Besdes physcal as well as psychologcal problems, obesty s known to drastcally ncrease a person s rsk of det-related chronc dseases, ncludng dabetes, cardovascular dseases, and cancer WHO Several studes show that the ncdence of chronc dseases such as dabetes, gallstones, hypertenson and heart dsease ncreases wth the degree of overweght or obesty Feld et al. 2001; Mokdad et al. 2003; Sowers 2003; Hedley et al Therefore, chronc dseases analyzed n ths study are dabetes and cardovascular dseases such as hypertenson, heart attacks, and stroke. We do not consder cancer due to data lmtatons. 5

7 Chna - Hgh blood pressure Russa - Hgh blood pressure 40% 40% 30% 30% 20% 20% 10% 10% 0% % Hgh blood pressure urban Hgh blood pressure rural Hgh blood pressure urban Hgh blood pressure rural Chna - Dabetes Russa - Dabetes 6% 6% 5% 5% 4% 4% 3% 3% 2% 2% 1% 1% 0% % Dabetes urban Dabetes rural Dabetes urban Dabetes rural Chna - Heart attack Russa - Heart attack 4 % 4 % 3 % 3 % 2 % 2 % 1 % 1 % 0 % % Heart attack urban Heart attack rural Heart attack urban Heart attack rural Chna - Stroke Russa - Stroke 3% 3% 2% 2% 1% 1% 0% % Stroke urban stroke rural Stroke urban Stroke rural Fgure 2: Prevalence of nutrton-related dseases [n % of sample] Source: Own calculatons based on RLMS-HSE and CHNS Note: Wth a sgnfcantly postve trend n total prevalence rates over tme at the 5% level, except for heart attacks n Russa. 6

8 Accordng to the WHO 2003, 60% of the burden of chronc dseases wll occur n developng or emergng countres such as Chna. In total, 71% of deaths due to schaemc heart dsease IHD, 75% of deaths due to stroke, and 70% of deaths due to dabetes occur n these countres. For a graphcal llustraton of the development of these nutrton-related chronc dseases see Fgure 2. Nevertheless, nterpretng the trends n the prevalence of these consdered chronc dseases s not as straghtforward as the ncdence of obesty, due to a lagged ncdence of nutrton-related chronc dseases. However, as presented n fgure 2, there s a consderable annual ncrease n prevalence rates of these chronc dseases, whch s especally pronounced n Chna. We can also observe that prevalence rates n Russa stll exceed those n Chna. Only for dabetes, prevalence rates n urban Chna caught up and overtook Russa at an alarmng speed. Generally, foodrelated chronc dseases were hgher n urban than n rural areas except of the prevalence rates of hgh blood pressure n Russa, whch were hgher n rural than n urban areas snce In summary, hgher growth rates of the occurrence of obesty n Chna suggest a certan catchng-up effect and ncreasng problems wth chronc dseases n the longer run, whch s supported by studes of Du et al. 2002, Kelly et al and Popkn Such an epdemologc transton to the predomnance of non-communcable dseases, especally n urban Chna, requres mmedate and effectve nterventon polces wth changes n health care strateges Rozenfeld 1996; WHO Det-related chronc dseases cause tremendous costs to both countres health care system as well as ther natonal productvty. Accordng to the World Bank data, Russan s per capta health care expendture PPP, defned as the sum of publc and prvate health expendtures and covers the provson of health servces, famly plannng actvtes, nutrton actvtes, and emergency ad, ncreased from constant 2011 nternatonal $ n 1995 to 1, constant 2011 nternatonal $ n Chna s per capta health care expendture PPP ncreased somewhat slower, from constant 2011 nternatonal $ n 1996 to constant 2011 nternatonal $ n 2012 see Fgure 3. Whereas ths ncrease manly reflects ncreasng ncome and welfare levels, nutrton-related dseases of affluent socetes certanly contrbute to ths effect. 1,600 1,400 1,200 1, Fgure 3: Health expendture per capta, PPP [n constant 2011 nternatonal $] Source: Own presentaton based on World Bank Russan health expendture per capta, PPP constant 2011 nternatonal $ Chnese health expendture per capta, PPP constant 2011 nternatonal $

9 Besdes publc health care costs t s especally nterestng to focus on prvate fnancal health expendture n order to consder arsng fnancal problems for Chnese and Russan households. Possbly due to the development of a publc health care system ncludng a comprehensve health nsurance, the Chnese prvate health expendture share n percent of total health expendture has decreased from % n 1996 to % n Russan prvate health expendture share on the other hand has ncreased from % n 1996 to 51.95% n Especally worrsome s that out-of-pocket health expendture any drect outlay by households n percent of prvate health expendture s especally hgh n both countres. In Chna however, out-of-pocket health expendture decreased from % n 1996 to % n 2013, whle t ncreased n Russa from % n 1996 to % n 2013 see Fgure 4. Ths s problematc as wth hgher rates of prvate health expendtures, the qualty of health servces could vary wth household ncomes, even though the access to basc publc health care s publcly provded Densova 2010: 347. Especally nformal payments for health care are deeply embedded n the health care system n transton countres Ensor Russan health expendture, prvate % of total health expendture Chnese health expendture, prvate % of total health expendture Fgure 4: Prvate health expendture [n % of total health expendture] Source: Own presentaton based on World Bank Nutrton transton n Chna and Russa The ncrease of chronc dseases connected to an unbalanced and excessve eatng behavor has become a maor concern to polcy-makers n emergng countres, too. Nevertheless, emergng countres such as Chna are yet laggng behnd n mplementng related nterventons WHO, 2003, 2015; Mazzocch et al., To understand potental polcy leverage, t s necessary to analyze the extent and features of nutrton transton n these countres. Therefore, n ths secton, we start by provdng nsghts nto tradtonal eatng habts of the Chnese and Russan populatons as well as current trends n ther consumpton patterns. 8

10 4.1 Chnese trends n food consumpton patterns Throughout Chnese hstory, nutrton scarcty has been a maor ssue for the maorty of the rural populaton, and even parts of the urban populaton. Whle total energy ntake ncreased after the foundaton of the People s Republc of Chna n 1949, t dropped consderably durng a seres of poltcal and economc upheavals n the late-1950s and early-1960s Du et al. 2014; Kantha The subsequent ncrease n energy ntake s generally seen as a drect result of economc reforms and subsequent rse of the general lvng standard Tan and Yu Snce 1978, Chna's remarkable economc development has sgnfcantly mproved people's lvng standards, ncludng food consumpton and nutrtonal status Feng and Sh Tradtonal Chnese meals usually nclude rce n southern regons and pasta n northern regons, along wth vegetables and a small amount of meat L Ths det has a low energy densty and s hgh n carbohydrates and detary fber. Intake of non-meat protens s low, as Chnese tradtonally rarely consume mlk or other dary products. Although mlk consumpton has rapdly ncreased durng recent years and s supplemented by the consumpton of beans especally soy beans, ncluded n other protens as an alternatve source of protens, the total consumpton of non-meat protens s stll low compared to Russa or western countres such as the Unted States Zha et al Table 1: Chnese average per-capta food consumpton by food groups kg/year Households of urban settlement type Food groups Carbohydrates Mlk and dary Meat Fsh Other Protens Fruts Vegetables Fats and ols Other foods Households of rural settlement type Food groups Carbohydrates Mlk and dary Meat Fsh Other Protens Fruts Vegetables Fats and ols Other foods Source: Authors calculatons based on CHNS

11 Average consumpton of unprocessed meat n kg/year Average consumpton of procesed meat n kg/year As shown n Table 1, our data ndcates sgnfcant changes of Chnese households detary patterns between 1997 and 2009, especally n rural areas. In the consdered tme perod, the per-capta consumpton of carbohydrates remaned more or less stable n urban areas, but ncreased sgnfcantly n rural areas from 71.7 to 95 kg/year. The consumpton of meat, dary, fsh, and other protens lke beans also steadly ncreased, agan especally n rural areas. Moreover, dary products from 2.2 to 9.2 kg n urban areas and from 0.1 to 2.2 kg n rural areas became a more mportant part of Chnese dets. As we would expect, the ntake of ols and fats also ncreased from 12.3 to 13.0 kg n urban areas and from 9.2 to 13.2 kg n rural areas. Frut ntake nearly trpled n urban areas, and we even observe a sevenfold ncrease of frut consumpton n rural households. Vegetable consumpton ncreased slghtly over the consdered tme perod from 98.6 to kg n urban areas and 80.5 to 95.0 kg n rural areas, respectvely. For 2009, we fnd an annual average per-capta meat consumpton of 32.7 kg n urban and 23.2 kg n rural households. Fgure 5 further llustrates the development of consumpton of processed and unprocessed meat. Processed meat consumpton, whch ncludes, among others, the consumpton of sausages and smoked meat, rose consderably faster than unprocessed meat consumpton. However, the ntake of processed meat n Chna s stll extremely low and accounted for only 6.6 % urban areas and 5.5 % rural areas of total meat consumed at home. Takng nto account meat eaten away from home 57% of processed meat s consumed away from home n the 2009 ndvdual-level survey lfts ths rato, but only slghtly snce also the consumpton of unprocessed meat ncreases by addng away-from-home food Urban unprocessed Rural unprocessed Urban processed Rural processed Fgure 5: Per-capta consumpton of unprocessed and processed meat n Chna Source: Authors calculatons based on CHNS Whle the changes n detary patterns n absolute quanttes llustrated n Table 1 already ndcate an ongong nutrton transton, we addtonally provde Chnese expendture shares, agan separated between rural and urban households. Ths decomposton of food expendtures by rural and urban households further supports our above mentoned results Table 2. Whle carbohydrate consumpton n klograms ncreased n both urban and rural areas, the total food expendture on carbohydrates steadly declned between 1997 and 2009 n both urban and rural areas from 19.1 % to 14.9 %, and from 24.3 to 18.7 %, respectvely. The expendture share of dary products s stll rather low, but constantly rsng n both rural and urban areas. 10

12 Even though households used a sgnfcant share of ther food expendture for meat products, nether rural nor urban resdents further ncreased relatve expenses for ths tem. 4 Instead, the expendture for other food products, manly consstng of convenence foods, sweets, and drnks ncreased tremendously. Table 2: Chnese mean expendture shares of food groups Households of urban settlement type Food groups Carbohydrates 19.1% 17.0% 18.7% 17.3% 14.9% Mlk and dary 2.8% 3.2% 3.2% 5.2% 6.8% Meat 32.9% 31.1% 29.2% 25.3% 27.1% Fsh 7.2% 7.6% 6.7% 7.4% 6.2% Other Protens 10.1% 8.8% 9.1% 7.5% 7.4% Fruts 10.3% 10.4% 9.1% 9.4% 9.3% Vegetables 11.9% 11.0% 9.5% 12.1% 12.6% Fats and ols 1.5% 4.5% 2.1% 2.5% 1.6% Other foods 3.8% 6.2% 12.0% 11.8% 13.0% Households of rural settlement type Food groups Carbohydrates 24.3% 24.5% 23.3% 22.2% 18.7% Mlk and dary 0.5% 1.4% 1.0% 2.5% 3.4% Meat 23.6% 22.5% 21.7% 20.1% 22.7% Fsh 6.6% 5.8% 4.6% 4.9% 4.4% Other Protens 15.5% 14.5% 12.2% 10.0% 9.5% Fruts 10.9% 11.5% 9.7% 9.9% 10.2% Vegetables 14.0% 12.5% 11.4% 12.8% 13.0% Fats and ols 0.2% 0.6% 0.8% 0.8% 0.8% Other foods 4.1% 6.6% 15.2% 15.7% 16.1% Source: Authors calculatons based on CHNS The dynamcs between urban and rural areas are especally noteworthy. For many food tems, a convergence seems to have taken place durng the observed tme perod. On the one hand, the share of rural household expendture spent on vegetables and carbohydrates slowly approached the lower urban level. On the other hand, a dstnct catch-up effect n per-capta consumpton can be observed for meat, as well as other proten sources, ols and fats, and other foods manly sweets, drnks and convenence foods. For other tems lke dary products, consumpton rose far slower n rural areas. Ths ndcates that the nutrton transton mght consst of two steps n the Chnese case: Wth economc development, frst non-dary proten such as meat, eggs, soy bean products and fat ntake ncreases, replacng a det domnated by vegetables and carbohydrates. After havng reached a certan welfare level, people seem not to further ncrease non-dary proten consumpton, but rather enrch ther det wth frut and dary products, the latter 4 In ths context, t s agan mportant to add that there s emprcal evdence that as ncome ncreases especally urban households ncrease ther expendture on meat eaten away from home Ba et al In ths lne, Mn et al report that especally results for meat consumpton mght be based by excludng foods eaten away from home. 11

13 not beng part of the tradtonal det. Moreover, people ncreasngly consume convenence foods, snacks and other products, whch are usually hgh n fats and sugar, thus ncreasng the rsk of above-mentoned det-related dseases. 4.2 Russan trends n food consumpton patterns In general, the base ntake level of most food product categores n Russa s completely dfferent from other emergng economes, such as Chna. Durng the former Sovet Unon, the consumpton of meat and dary tems was promoted n the offcal fve-year plans by subsdzng these sectors. Furthermore, the Sovet Unon s medcal and nutrtonal establshments created detary standards that called for hgh levels of proten ntake. Whle these nutrton gudelnes ceased beng ssued n the late-1980s, the practce seems to preval snce no counter-educaton has been provded yet Dellava et al Indeed, we fnd already relatvely hgh ntake levels of anmal-based products n 1996, wth ncreasng levels over tme Table 3. Ths comples wth the results of a study on eatng habts n Russa Honkanen and Voldnes In terms of the dynamcs of consumpton, Dellava et al conclude that steep prce ncreases for meat and dary products n years of economc crss dd not result n long-term detary shfts. In fact, after a decrease n meat consumpton by 27 % from due to the collapse of the managed economy, accompaned by a reducton of the Russan GDP by 40 %, Russan households reverted to pror consumpton patterns as ncomes ncreased. Hence, after the Russan fnancal crss n 1998, average Russan per-capta consumpton of meat and meat products ncreased from kg n 2000 to kg n 2008, wth ncreasng ncomes per capta. Thereby the average per-capta ntake of meat products n urban areas s consderably hgher kg/year n 2008 than n rural areas kg/year n Ths s n lne wth Lefert 2004, who states that Russans consder a heavy ntake of lvestock products as necessary for a healthy det. Furthermore, per-capta consumpton of carbohydrates decreased from 230 kg to 175 kg n urban areas, and from 272 kg to 230 kg n rural areas from 1996 to The average ntake of fruts and vegetables s hgher n urban than n rural areas, whch mght be due to ncreased food avalablty and the fact that even the urban populaton generally possesses a dacha prvate garden plot to grow ther own fruts and vegetables. Over tme, frut ntake ncreased n both rural from kg to kg and urban kg to kg areas, whle the consumpton of vegetables decreased from 72.6 kg to 58.4 kg n urban households, and from 64.1 kg to 59.9 kg n rural households, respectvely. Yet after the fnancal crss n 1998, the sum of frut and vegetable consumpton ncreased both n urban as well as rural areas untl Compared to Chnese per-capta consumpton, the average per-capta consumpton of fruts s sgnfcantly hgher n Russa than n Chna, whle the opposte s true for vegetables. Compared to the Unted States or many European countres, we fnd a comparatvely low consumpton level of fruts and vegetables, whch s n lne wth results of Paalanen et al Ths mght be due to the dffculty of growng fruts and vegetables n the Russan clmate Branerd and Cutler

14 Table 3: Russan average per-capta food consumpton by food groups kg/year Households of urban settlement type Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Households of rural settlement type Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Source: Authors calculatons based on RLMS-HSE Note: Consderng total household consumpton data and household producton of food tems. Average per-capta meat consumpton kg n 2008 s notceably hgher n Russa than n Chna kg n The dfference between actual meat ntakes n Chna and Russa s also reflected n the dfference between offcally recommended meat ntakes for these two countres. Offcal Chnese sources suggest a per-capta ntake of kg per year Yang In contrast, the Mnstry of Health and Socal Development of the Russan Federaton 2010 recommends a per-capta consumpton of kg meat and meat products per year. The suggested mnmum meat consumpton for adults les between 54 kg and 70.4 kg per year, dependng on the geographcal area n Russa Government of the Russan Federaton Russan recommendatons not only exceed Chnese recommendatons, but also nutrtonal ntake recommendatons gven n the Unted States or Germany. For comparson, U.S. detary gudelnes recommend a maxmum per-capta ntake of 62 kg per year, whle n Germany, an annual maxmum meat ntake of about 31.3 kg per capta s recommended German Assocaton of Nutrton The World Cancer Research Fund advses that the consumpton of meat, especally processed meat, should not exceed 26 kg per year. Ths recommendaton s based on the evdence that hgh ntake levels of processed meat,.e. meats preserved by smokng, curng, or saltng, or through the addton of chemcal preservatves, ncreases the rsk of colon cancer World Cancer Research Fund & Amercan Insttute for Cancer Research

15 Average per-capta consumpton n kg/yea Although the ntake of red meat s expected to prevent ron defcency, frequent meat consumpton, especally of processed meat, s assumed to not only be assocated wth an ncreased rsk for colorectal cancer, but also wth cardovascular dseases, dabetes, and chronc kdney dseases World Cancer Research Fund & Amercan Insttute for Cancer Research 2007; Savva and Kafatos 2014; Tárraga López et al. 2014; Cho and Km 2014; Marckmann et al Furthermore, fgure 5 llustrates that Russans consume more unprocessed meat than processed meats, wth hgher consumed amounts of unprocessed and processed meat n urban areas Urban processed Urban unprocessed Rural processed Rural unprocessed Fgure 6: Per-capta consumpton of unprocessed and processed meat n Russa Source: Authors calculatons based on RLMS-HSE Smlar to Chna, the absolute quanttatve changes n detary patterns llustrated n Table 3 ndcate an ongong nutrton transton n Russa. Absolute consumpton data s also mrrored n the development of expendture shares over the observed tme perod Table 4. The expendture shares of anmal proten sources ncreased, whle the expendture shares of carbohydrate consumpton decreased over the observed tme perod. 5 Further, evdence suggests that even n dets wth lttle consumpton of whte or red meat, ron status may not be adversely affected Savva and Kafatos

16 Table 4: Russan expendture shares of food groups Households of urban settlement type Carbohydrates 28.5% 26.0% 28.2% 24.6% 23.0% 22.9% 23.1% 21.2% 21.0% 20.7% 21.8% Mlk and dary 11.0% 11.3% 11.1% 12.3% 12.7% 12.8% 12.9% 13.8% 14.3% 14.7% 14.8% Meat 30.5% 29.5% 30.2% 32.3% 34.6% 34.3% 34.8% 37.1% 36.7% 36.6% 36.0% Fsh 3.5% 3.2% 3.2% 3.4% 3.3% 3.4% 3.5% 3.3% 3.4% 3.2% 2.9% Other protens 4.1% 4.6% 4.3% 3.9% 3.7% 3.7% 3.8% 3.4% 3.4% 3.9% 3.9% Fruts 5.1% 4.3% 5.0% 5.6% 5.5% 6.8% 6.5% 6.6% 6.8% 6.7% 7.2% Vegetables 4.4% 2.7% 3.0% 3.3% 3.2% 2.8% 2.7% 2.6% 2.5% 2.1% 1.9% Fats and ols 7.2% 11.2% 7.7% 7.0% 6.9% 6.2% 5.7% 5.3% 4.7% 5.8% 5.5% Other foods 5.8% 7.3% 7.3% 7.5% 7.2% 7.2% 7.0% 6.7% 7.2% 6.4% 5.9% Households of rural settlement type Carbohydrates 54.3% 52.5% 49.4% 46.6% 40.1% 41.5% 40.8% 35.8% 32.9% 31.5% 32.7% Mlk and dary 5.4% 5.0% 5.2% 5.3% 7.0% 7.3% 7.6% 8.6% 9.0% 9.8% 10.0% Meat 18.4% 17.1% 18.7% 21.3% 24.0% 23.6% 25.2% 28.2% 31.5% 31.6% 30.8% Fsh 3.0% 2.6% 3.6% 3.3% 3.9% 3.8% 3.9% 4.1% 4.0% 3.5% 3.6% Other protens 0.8% 1.5% 1.8% 1.7% 1.8% 1.8% 1.8% 2.2% 2.3% 2.7% 2.4% Fruts 1.8% 1.7% 2.7% 3.5% 4.3% 4.1% 4.4% 4.8% 5.5% 5.9% 6.3% Vegetables 1.1% 0.3% 0.7% 0.8% 1.2% 1.0% 1.2% 1.1% 1.0% 0.8% 0.7% Fats and ols 8.7% 10.9% 9.2% 8.8% 9.4% 8.7% 8.3% 7.8% 6.5% 7.5% 7.4% Other foods 6.6% 8.5% 8.8% 8.8% 8.4% 8.2% 6.9% 7.5% 7.3% 6.8% 6.2% Source: Authors calculatons based on RLMS-HSE Note: Consderng total of household consumpton data and household producton of food tems. 5 Emprcal Analyss To analyze trends n expendture and prce elastcty of food demand, we apply the Quadratc Almost Ideal Demand System QUAIDS of Banks et al The QUAIDS provdes more flexblty than the standard Lnear Approxmaton Almost Ideal Demand System LA/AIDS of Deaton and Muellbauer QUAIDS allows expendture share Engel curves that are quadratc n the logarthm of expendtures. Smlar to the LA/AIDS model, the QUAIDS s derved as a generalzaton of the prce-ndependent generalzed logarthmc PIGLOG demand system. Demographc scalng used n ths study s based on the work of Ray 1985 and Po 2002; For more detals on the estmaton model see Appendx A. Based on the assumpton of weak separablty of preferences and an aggregaton of products based on smlar nutrent compostons, we employ a two-stage budgetng model accordng to Deaton and Muellbauer Estmaton procedure and elastcty calculaton Expendture elastctes are estmated by terated feasble generalzed nonlnear least squares va STATA 13. In the frst stage, the model reproduces the allocaton of total expendture on foods and non-foods. Due to mssng Chnese consumpton data of non-foods, we estmate the frst stage food elastctes by a sngle OLS equaton. Our frst stage regresson of food at home demand n Chnese rural and urban areas s based 15

17 on ncome data, reduced by savngs rate, whle our frst stage estmaton of the Russan demand for food consumed at home s based on total expendtures consderng, next to food consumed at home, food away from home FAFH, housng, utltes, hygene, educaton and other non-food goods such as clothes. At the second stage, we dstngush between nne food aggregates of food at home consumpton: carbohydrates; mlk and dary products; meat and meat products; v fsh; v eggs and other proten sources; v fruts; v vegetables; v ols and fat; and x other foods 6. The problem of zero observatons s controlled for by applyng the consstent generalzed Heckman procedure Tauchman In order to provde uncondtonal expendture and prce elastctes for the second stage, we follow Carpenter and Guyomard We evaluate expendture, own-prce and cross-prce elastctes at sample means. Thereby, expendture elastctes of food and meat aggregates are taken as ndcators to measure the effect of expendture growth on food demand n both Chna and Russa. Through demographc scalng, we control for fve socodemographc varables: land use, household sze, number of chldren aged 0-14, settlement type, and geographc regon. We do not nclude a tme trend varable snce we are partcularly nterested n changes over tme. 5.2 Emprcal results We frst provde uncondtonal expendture elastctes for our nne food aggregates. To analyze changes over tme, we provde yearly demand elastctes for each of the food aggregates. Subsequently, we present the calculated own-prce elastctes, agan on a yearly bass. Due to a mxture of dfferent foods n the other food aggregate, we wll not dscuss the results concernng ths food aggregate. As presented n Table 5 and Table 6, our estmates of the Russan and Chnese expendture elastctes for our food aggregates are all plausble, consderng the magntude, order and relatve magntude among the nne food aggregates wth consderably hgher food expendture elastctes n rural areas. All food aggregates n both countres are postve and normal goods, meanng that demand ncreases decreases wth ncreasng decreasng expendture and constant prces. Products of basc demand such as fats and carbohydrates, ncludng cereals and potatoes, or other protens sources consstng nter ala of soy beans and tofu products have the lowest expendture elastctes. In both countres, the hghest elastctes can be found for the meat and fsh groups. 6 We wll not nterpret our results of the other foods and the other meats aggregates snce these groups compostons are not consstent across both countres. 7 Shonkwler and Yen 1999 pont out that the generalzed Heckman procedure by Heen and Wessells 1990 s nconsstent and propose an alternatve consstent estmaton procedure. Tauchmann 2005 compares the performance of Shonkwler and Yen estmators and Heckman estmators accordng to ther mean squared devaton of the estmated condtonal mean from ts true counterpart. Tauchmann shows that gven certan parameter constellatons, the Shonkwler and Yen estmators perform qute poorly. Based on the crtques of Shonkwler and Yen 1999 and Tauchmann 2005, Tauchmann 2010 ntroduces a consstent generalzed Heckman estmator. 16

18 Table 5: Uncondtonal expendture elastctes of Chnese households Total household sample Frst stage OLS estmaton Food Second stage QUAIDS estmaton Carbohydrates Mlk and dary Meat Fsh Other protens Fruts a Vegetables Fat and Ols Other foods Urban households only Frst stage OLS estmaton urban Food Second stage QUAIDS estmaton urban Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fat and Ols Other foods Rural households only Frst stage OLS estmaton rural Food Second stage QUAIDS estmaton rural Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fat and Ols Other foods Observatons Share of urban households 34 % 35% 35% 36% 38% Source: CHNS, Note: a Prce data on fruts for 1997 and 2000 s mssng n the CHNS. Therefore, we aggregated fruts and vegetables n 1997 and 2000 n the vegetables group. All numbers sgnfcant at the 5%-level are prnted n bold letters. The category other meat was not ncluded n Chnese analyss due to ths food s low consumpton share among the meat aggregate less than 1%. 17

19 Table 6: Uncondtonal expendture elastctes of Russan households Total household sample Frst stage OLS estmaton Food Second stage QUAIDS estmaton Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Urban households only Frst stage OLS estmaton urban Food Second stage QUAIDS estmaton urban Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Rural households only Frst stage OLS estmaton rural Food Second stage QUAIDS estmaton rural Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Observatons Share of urban households 77% 77% 74% 76% 76% 76% 76% 75% 72% 76% 77% Source: RLMS-HSE, Note: All numbers sgnfcant at the 5%-level are prnted n bold letters. The category mutton was not ncluded n Russan analyss due to ths food s low consumpton share among the meat aggregate less than 5%. 18

20 Compared wth the results of other studes on Chnese food demand Huang and Rozelle 1998; Gould 2002; Yen et al. 2004; Gould and Vllarreal 2006; Dong and Gould 2007; Lao and Chern 2007; Gale and Huang 2007, Zheng and Henneberry 2009; Zhou et al. 2015, we fnd that meat, fsh and dary products exhbt the hghest expendture elastctes, whch s n lne wth the maorty of the comparson studes ndcatng dary products as havng the hghest expendture elastctes see Table B 1 n Appendx B. Our Russan expendture elastctes are farly comparable to the Russan food demand estmatons of Elsner 1999 for 1996 and Muhammad et al for However, whle Elsner 1999 shows uncondtonal meat expendture elastctes of 0.77 and uncondtonal dary expendture elastctes of 1.10 for 1996, n our study meat and meat products have hgher expendture elastcty than dary products. Ths means that n our study Russans tend to consder meat and meat products more luxury than dary products. Ths s n lne wth our expectatons and the results of Staudgel and Schröck 2014, who ndcate meat as the food product wth the hghest expendture elastcty uncondtonal meat expendture elastcty 1.16; dary 0.80 for Our results are also n lne wth the results of other studes on BRIC countres. For example, n ther study on food consumpton n Brazl 2002/2003, Coelho et al fnd expendture elastctes of beef and pork between 1.13 and These authors estmate the expendture elastcty for flud mlk of Further, for Indan food demand between 1983 and 2000, Mttal 2006 estmates expendture elastctes of 1.30 for meat, fsh and eggs, and an expendture elastcty of 1.19 for flud mlk. Comparng our Chnese results wth the Russan results, we can state that whle the relatve order for the food aggregates s very smlar for both countres, the magntude of expendture elastctes s not equvalent. Followng Muhammad et al. 2011, we expect expendture elastctes to be hgher n countres wth lower average ncome, apart from carbohydrates. Indeed, n 2008 all food aggregates n Russa are necessty goods wth uncondtonal expendture elastcty below 1. Analyzng the trend over the consdered perod, we can state that for Russa expendture elastctes decreased for all food groups. In Chna, meat, fsh and dary products are stll luxury products n For these three product groups, we derve expendture elastctes slghtly larger than one, meanng that the demand for these food tems ncreases dsproportonally wth rsng household expendture. 19

21 Table 7: Uncondtonal prce elastctes of Chnese households Total household sample Frst stage OLS estmaton Food Second stage QUAIDS estmaton Carbohydrates Mlk and dary Meat Fsh Other protens Fruts a Vegetables Fat and Ols Other foods Urban households only Frst stage OLS estmaton urban Food Second stage QUAIDS estmaton urban Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fat and Ols Other foods Rural households only Frst stage OLS estmaton rural Food Second stage QUAIDS estmaton rural Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fat and Ols Other foods Observatons Share of urban households 34 % 35% 35% 36% 38% Source: CHNS, Note: a Prce data on fruts for 1997 and 2000 s mssng n the CHNS. Therefore, we aggregated fruts and vegetables n 1997 and 2000 n the vegetables group. The category other meat was not ncluded n Chnese analyss due to ths food s low consumpton share among the meat aggregate less than 1%. All numbers sgnfcant at the 5%-level are prnted n bold letters. 20

22 Table 8: Uncondtonal prce elastctes of Russan households Total household sample Frst stage OLS estmaton Food Second stage QUAIDS estmaton Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Urban households only Frst stage OLS estmaton urban Food Second stage QUAIDS estmaton urban Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Rural households only Frst stage OLS estmaton rural Food Second stage QUAIDS estmaton rural Carbohydrates Mlk and dary Meat Fsh Other protens Fruts Vegetables Fats and ols Other foods Observatons Share of urban households 77% 77% 74% 76% 76% 76% 76% 75% 72% 76% 77% Source: RLMS-HSE, Note: All numbers sgnfcant at the 5%-level are prnted n bold letters. The category mutton was not ncluded n Russan analyss due to ths food s low consumpton share among the meat aggregate less than 5%. Table 7 and Table 8 show the uncompensated own-prce elastctes, whch are calculated as uncondtonal elastctes. In general, the own-prce elastctes n absolute values are lower for Chna than Russa. Further, overall meat prce elastctes do not suggest a trend n Russa. In Chna, we can make out a clearer trend: 21