Consumption analysis and the effect of price development in SR

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1 Journal of Theoretcal and Appled Computer Scence Vol. 10, No. 1, 2016, pp ISSN (prnted), (onlne) Consumpton analyss and the effect of prce development n SR Bran Köng Unversty of Economcs n Bratslava, Faculty of Economc Informatcs, Department of Operatons Research and Econometrcs, Slovak Republc Insttute of Economc Research SAS, Slovak Republc bran.kong@savba.sk Abstract: The artcle deals wth the development of consumpton expendtures (luxury and necessty goods) n SR over tme. For ths purpose the QUAIDS (Quadratc Almost Ideal Demand System) model was adopted whch enabled us to calculate the expendture elastctes of nne relatvely homogeneous commodty groups. Based on these results commodty groups were splt nto luxury and necessty goods and ther evoluton was tracked over tme. In the next step, resultng from luxury and necessty groups, weghted prce ndces were calculated. Results suggest that movement n prces has postve effect on the wllngness to buy more expensve luxury goods compared to the essental goods. Keywords: consumpton behavour, the QUAIDS model, luxury and necessty goods, prce development 1. Introducton Household consumpton represents one of the key ndcators of the lvng condtons whch n trustworthy manner reflects ncome stuaton n partcular countres. Nowadays, at the tme of economc growth necessty, aggregate consumpton as a key determnant of GDP (gross domestc product) come more often to the fore. Although, accordng to Eurostat data, Slovaka belongs to the group of the poorest Eurozone countres n term of ndvdual consumpton. As a problematc s consdered persstently low share of luxury goods compared to the essental goods whch may ponts out on not mprovng ncome stuaton n vast majorty of Slovak households. Although consumpton s a better tool to measure lvng condtons than ncome, lot of research papers deal wth ncome structure and nequaltes (Domonkos, Ostrhoň (2015)) or consumpton on macroeconomc level (Ivančová, Ostrhoň (2014)) nstead of consumpton dstrbuton on ndvdual data n case of SR (Slovak Republc). Wth regard to the Slovak data, demand analyss based on HBS data (Household Budget Survey) s consderably less elaborated. Cupák et al. (2015) appled the QUAIDS model to Slovak HBS data focusng on food consumpton and showng the nequalty n households det. Expendture elastctes n Slovaka on the bass of the mcrodata and the same method were also calculated by Lchner et al. (2014). Income and consumpton nequaltes between low-ncome and hgh-ncome households n SR were analysed by Köng, Dováľová (2016). There are lot of especally foregn papers dealng wth demand behavour based on the QUAIDS model, for that reason we menton just few of them. As a fundamental work whch the QUAIDS model s based on s an almost deal demand system (AIDS) devsed by Deaton et al. (1980). They appled the

2 Consumpton analyss and the effect of prce development n SR 39 AIDS model on Brtsh data and they concluded that the model s able to explan hgh proporton of the varance of the commodty expendture shares. Later on, Blanks et al. (1997) adjusted the model by usng a quadratc term n the expendture share equaton whch allows for quadratc shape of the Engel curve. Janda et al. (2010) examned the nfluences of tax nterventons made by fscal polcy on the alcohol beverages market by usng QUAIDS model on the Czech Republc data. The effects of changes n value added tax (VAT) rates n the Czech Republc on household consumpton were nvestgated by Janský (2013). Janský estmated the behavoural responses of consumers to prce changes resultng from VAT changes based on the QUAIDS model. Prce and ncome elastctes based on the HBS data were also nvestgated by Dybczak et al. (2014). These authors focused on the determnaton of luxury and necessty goods n Czech households. One of the artcle man goals s to pont out on consumpton behavour n SR based on expendture elastctes and on the resultng development of the expendture spent on luxury and necessty goods over tme. As a next step we analyse nfluence of the prce evoluton on the consumpton of luxury and necessty goods. In order to fulfl these tasks we adopt HBS data and data on prce ndces from Slovak Statstcs Offce whch were employed n the QUAIDS model. The paper s structured as follows: frst secton deals wth ntroducton and lterature revew. Next we focus on the methodology the QUAIDS demand system s based on. Secton three s focused on the data used and the process of aggregaton and mputaton of new prce ndces. In chapter four we deal wth the ssues regardng the model estmaton process. The fnal part nvestgates the fndngs n the area of expendture elastctes, resultng development of the expendture spent on luxury and necessty goods over tme and the effect of prce trends on the consumpton structure. 2. Methodology In order to dentfy the consumpton behavour of Slovak households and to reflect expendture elastctes, we use the QUAIDS model devsed by Banks et al. (1997). The QUAIDS model s an extenson of the model called AIDS by Deaton and Maellbauer (1980), whch addtonally allows for the consderaton of quadratc Engel curves. As a result of the quadratc form, a good may be luxurous at a certan level of ncome, but t may become an essental good f ncome changes. The QUAIDS model consders consumer demand for a set of n goods that the consumer purchases for m monetary unts. In our case, the n goods express aggregate expendture categores dvded accordng to the classfcaton of ndvdual consumpton by purpose (COICOP) such as food, alcoholc beverages, clothng and footwear etc. and m expresses total expendture of ndvdual household ncurred on the varous expendture categores. Generally, the QUAIDS model s based on the ndrect utlty functon V(p, m) expressed as 1 : ln V, lnm ln a( p) b( p) 1 p m p where p s a prce vector and functons lna (p), b (p), λ (p) are expressed as follows: 1 (1) 1 More detaled model descrpton can be found n Banks et al. (1997).

3 40 Bran Köng 1 ln a p lnp ln p lnp (2) 0 n n n j j j1 b n p p (3) 1 n 1 p lnp (4) where p and p j are the prces of the -th and j-th good respectvelly 2, and b(p) represents the Cobb-Douglas prce aggregator. Furthermore, the QUAIDS model defnes the expendture shares of the partcular expendture as a proporton of the product of the number of tems q n the expendture category and related prces p dvded by total amount of household money ncurred on the expendture categores m as w pq / m. After applcaton of Roy's dentty 3 to the equaton (1), expendture share w s gven as: n m m w j lnp j ln ln, 1,, n j1 a( p) b( p) a( p) Based on mcroeconomc theory, the model mposes addtonal restrctons on parameters expressed as follows: n n n n 1, 0, 0, 0, and j j j 1 1 j1 1 (6) Expendture elastctes are n the model of Banks et al. (1997) expressed through the dervatve of functon (5) wth respect to lnm to obtan: w 2 m ln lnm b( p) a p Followng expresson (7), the related expendture elastcty can be defned as: 1 / w. 2 (5) (7) 3. Data For the purpose of the parameter estmaton process of the QUAIDS model two datasets were used. Key mcrodata were receved from the HBS data (namely data for years and ) whch cover consumpton and ncome structure of ndvdual households on yearly bass. HBS data contan around households each year. Snce the vast majorty of households are changed each year t s not possble to treat them as panel data or 2 In our case, good represents -th expendture category. 3 Generally, Roy s dentty says that consumer demand for good can be expressed as a partal dervatve of the ndrect utlty functon wth respect to the prce of the.th good dvded by the partal dervatve of the ndrect utlty functon wth respect to ncome. 4 Years 2013 and 2014 are excluded from the analyss snce HBS survey was not conducted n SR durng these years.

4 Consumpton analyss and the effect of prce development n SR 41 to track partcular household durng the years. On the other hand, expendture data are collected on relatvely detaled level and for that reason certan data aggregaton s necessary. Aggregaton process s quet often procedure n consumpton analyss, however there s no general rule how to mplement t. For the purpose of our analyss we grouped expendture based on COICOP classfcaton nto the followng nne groups: 1. Food and non-alcoholc beverages; 2. Alcoholc beverages, tobacco; 3. Clothng and footwear; 4. Housng, water, electrcty, gas and other fuels + furnshngs, household equpment and routne household mantenance (except household applances); 5. Health; 6. Transport (except purchase of vehcles) 5 + Communcaton and postal servces (except telephone and telefax equpment); 7. Recreaton and culture (except audo-vsual, photographc and nformaton processng equpment) + Restaurants and hotels; 8. Household applances + telephone and telefax equpment + other major durables for recreaton and culture 6 ; 9. Other goods and servces. Snce the HBS dataset does not contan nformaton regardng commodty prces or nformaton on physcal amounts consumed we adopt prce ndces data from Slovak Statstcal Offce. Based on the prce ndces we mpute the ndvdual prces of each commodty group for every household as a result of dfferent amount of expendture spent n ndvdual subgroups. 7 In order to avod the based results caused by extreme values we dd some data adjustments. As frst we removed data connected wth expendtures n aggregate commodty groups hgher than 99 th percentle and lower than 1 st percentle wthn each year. As a next step we dropped observatons where commodty prces exceeded 99 th percentle of prces n partcular commodty groups and those whch were less than 1 st percentle wthn each year. After mentoned adjustments there remaned 40,608 observatons n total. 4. Estmaton In order to conduct the emprcal analyss of consumpton behavour and to calculate expendture elastctes the QUAIDS model desgned by Banks et al. (1997) was used. In the parameter estmaton procedure, we followed an approach desgned by Po (2012), who constructed software code n STATA whch can be used to estmate the QUAIDS model through an teratve nonlnear generalzed least squares method. The desgned program also allows for post-estmaton analyss whch enables the computaton of prce and expendture elastctes. When the code devsed by Po (2012) s adopted, t s necessary to specfy the value of parameter 0. In our analyss, we followed the approach desgned by Deaton et al. (1980) and Blanks et al. (1997), who set the 0 parameter slghtly below the mnmum value of the logarthm of total household expendture (lnm). Partcular expendture elastctes are calculated ndvdually for each household usng the expendture shares w. Such computaton allows the quantfcaton of elastctes as the average value of each household s elastctes, also enablng to calculate the medan value of ndvdual elastctes. The estmated parameters of the QUAIDS model are shown n Appendx 1. 5 Category Purchase of vehcles was excluded because t s obvous that these expendtures represent luxury goods and snce the prces of commodtes n ths category are pretty bg, n case of purchases t could resulted n potental overestmatng of prce elastcty of whole group. 6 Ths group conssts of applances and durables whch could potentally overestmate prce elastcty of ndvdual commodty group where they belong. 7 We matched weghted CPI ndexes from the Slovak Statstcal Offce wth each commodty subgroup and we calculated the aggregate prce ndex of an expendture group as a weghted average of CPI ndexes, whereby weghts were computed ndvdually for every sngle household as the expendture share of an ndvdual expendture subgroup on the total expendture group.

5 42 Bran Köng 5. Results and Dscusson Based on QUAIDS estmates we calculated expendture elastctes, whch serve as a tool to nvestgate the type of commodty group (necessty/luxury good). Results depcted n Table 1 suggest that only three of selected commodty groups can be consdered as necessty goods: 1. Food and non-alcoholc beverages; 4. Housng, water, electrcty, gas and other fuels + Furnshngs, household equpment and routne household mantenance; 5. Health. The remanng sx groups are luxury goods: 2. Alcoholc beverages, tobacco; 3. Clothng and footwear; 6. Transport + Communcaton; 7. Recreaton and culture + Restaurants and hotels; 8. Household applances + Telephone and telefax equpment + Audo-vsual, photographc and nformaton processng equpment; 9. Other goods and servces. 8 Expendture group Table 1. Medans of Expendture Elastctes Expendture elastcty 1. Food and non-alcoholc beverages 0, Alcoholc beverages, tobacco 1, Clothng and footwear 1, Housng, water, electrcty, gas and other fuels+furnshngs, household equpment and routne household mantenance 0, Health 0, Transport+Communcaton 1, Recreaton and culture + Restaurants and hotels 1, Household applances+telephone and telefax equpment+audo-vsual, photographc and nformaton processng equpment 1, Other goods and servces 1, Source: Author, based on HBS data and prces ndces data from Slovak Statstcs Offce Resultng from the expendture elastctes we construct commodty bundles of necessty and luxury goods. Development of necessty and luxury goods s depcted on the Fgure 1. There can be seen that n pre-crss perod (up to 2009) there was present an ncreasng trend n the expendture share of luxury goods (from 36.5 % n 2004 to 40.5 % n 2009 n average) and at the same tme proportonally lowerng share of necessty goods (from 63.5 % n 2004 to 59.5 % n 2009 ). Ths evolvement was nfluenced by more aspects for nstance by: fast GDP growth, favourable development on the labour market assocated wth hgh employment level and relatvely hgh ncome growth etc. In 2010 there was two percentage ponts change n luxury goods (from 40.5 % to 38.6 %) as well as n necessty group (from 59.5 % to 61.4 %). Households moved ther consumpton towards the cheaper essental goods especally because of worsenng economc stuaton (economc crss) and uncertan future development (manly n area of GDP, employment, salares etc.). From 2011 on, there s relatvely stable share of luxury and necessty goods (40:60). 8 Commodty s consdered a luxury good f ncome elastcty s hgher than one and as a necessty good f ncome elastcty s n the nterval from zero to one.

6 December 2000=100 Expendture share Consumpton analyss and the effect of prce development n SR 43 0,6500 0,6000 0,5500 0,5000 0,4500 lux nec 0,4000 0, Years Fgure 1. Expendture shares of Luxury and Necessty Goods over tme ( , 2015) Source: Author, based on HBS data Another mportant aspect whch favourably contrbuted to decrease n the share of necessty goods n favour of the ncrease n the share of luxury goods was prce development. Based on the aggregated commodty bundles (necessty and luxury goods) we computed weghted prce ndces for both commodty groups, whle partcular weghts are represented by the average value of ndvdual commodty groups. The prces of luxury goods were movng up n much slower manner than those of the luxury goods (see Fgure 2) nec lux Years Fgure 2. Development of weghted prce ndces of luxury and necessty goods over tme ( , 2015) Source: Author, based on HBS data and prces ndces data from Slovak Statstcs Offce

7 44 Bran Köng 6. Concluson The papers man purpose was to dentfy the development of expendture shares of Slovak households over tme and to fnd out how the prce evoluton contrbutes to ths change. For the purpose of our analyss based on the QUAIDS model estmaton we computed expendture elastctes. These help us to nvestgate whch commodty group s consdered as luxury and whch as necessty goods. The results suggest that necessty goods are represented by groups 1, 4 and 5 respectvely, and luxury goods consst of groups 2, 3, 6, 7, 8 and 9. Another fndng s that economc crss had negatve effect on the evoluton of luxury goods share n term of shft of luxury goods towards hgher rato of essental goods n The analyss also showed that movement n prces has postve effect on the wllngness to buy more expensve luxury goods compared to the essental goods, snce prces of luxury goods ncreased n much slower manner compared to necessty goods. On the other hand, ths could unfavourably affected low-ncome households whch vast majorty of consumpton expendture consst especally of necessty goods. Further research n ths area could be focused on the consumpton analyss of partcular household groups dfferentated by dfferent socal and economc characterstcs as: economc actvty, age, regon etc. References [1] Banks, J., Blundell, R., Lewbel, A.: Quadratc Engel Curves and Consumer Demand. Revew of Economcs and Statstcs, 79, No. 4, pp , [2] Cupák, A., Pokrvčák, J., Rzov, M.: Food Securty and Household Consumpton Patterns n Slovaka. [Dscusson Paper 360/2014.] Lueven: LICOS centre for Insttutons and Economc Performance, [3] Cupák, A., Pokrvčák, J., Rzov, M.: Food Demand and Consumpton Patterns n the New EU Member States: The Case of Slovaka. Ekonomcký Časops/Journal of Economcs, 63, No. 4. pp , [4] Deaton, A. S., Muellbauer, J.: An Almost Ideal Demand System. Amer-can Economc Revew, 70, No. 3, pp , [5] Domonkos, T., Ostrhoň, F.: Inclusve Growth n Selected Central Euro-pean Countres. In Ekonomcký časops, 2015, roč. 63, č. 9, s , [6] Dybczak, K., Tóth, P., Voňka, D.: Effects of Prce Shocks to Consumer Demand: Estmatng the QUAIDS Demand System on Czech Household Budget Survey Data. Fnance a úvěr/czech Journal of Economcs and Fnance, 64, No. 6, pp , [7] Ivančová, Z., Ostrhoň, F.: Consumpton Smoothng And Rsk Sharng Across The Regons (Fscal Effects Panel Data Approach). In Quanttatve methods n economcs. Multple crtera decson makng XVII: proceedngs of the nternatonal scentfc conference. Vrt, Slovaka Reff Maran, Pavel Gežík., Bratslava: Ekonóm, 2014, p ISBN [8] Janda, K., Mkolášek, J., Netuka, M.: Complete Almost Ideal Demand System Approach to the Czech Alcohol Demand. Agrcultural Economcs-UZEI, 56, No. 9, pp , [9] Janský, P.: Consumer Demand System Estmaton and Value Added Tax Re-forms n the Czech Republc. [Workng Paper W13/20.] Prague: Insttute of Economc Studes, [10] Lchner, I., Petríková, K.: Odhad výdavkových elastcít pomocou modelu QUAIDS prípad Slovenska. Slovenská štatstcká demografcká spoločnosť/forum statstcum Slovacum, 10, No. 3, pp , [11] Radvanský, M., Dováľová, G.: Impact of Ageng on Curatve Health Care Workforce Country Report Slovaka. [NEUJOBS Workng Paper: Supplement F.] [Onlne.], No. D12.1, pp. 1-64, 2013.

8 Consumpton analyss and the effect of prce development n SR 45 Appendx: The QUAIDS coeffcents Coef. Std. Err. Coef. Std. Err. alpha gamma alpha_1 0,0765 0,0113 gamma_9_1-0,1012 0,0105 alpha_2-0,0242 0,0041 gamma_2_2 0,0821 0,0008 alpha_3 0,1963 0,0067 gamma_3_2-0,0151 0,0012 alpha_4 0,0683 0,0130 gamma_4_2-0,0127 0,0017 alpha_5 0,0087 0,0046 gamma_5_2-0,0135 0,0008 alpha_6 0,0872 0,0078 gamma_6_2 0,0072 0,0010 alpha_7 0,3436 0,0090 gamma_7_2-0,0219 0,0014 alpha_8 0,0861 0,0045 gamma_8_2-0,0010 0,0006 alpha_9 0,1575 0,0073 gamma_9_2-0,0077 0,0013 beta gamma_3_3 0,0707 0,0050 beta_1-0,1376 0,0080 gamma_4_3 0,0041 0,0042 beta_2-0,0432 0,0029 gamma_5_3-0,0046 0,0029 beta_3 0,0699 0,0047 gamma_6_3 0,0094 0,0021 beta_4-0,0633 0,0094 gamma_7_3-0,0138 0,0029 beta_5 0,0025 0,0033 gamma_8_3-0,0093 0,0013 beta_6-0,0656 0,0056 gamma_9_3-0,0196 0,0055 beta_7 0,1553 0,0065 gamma_4_4 0,0376 0,0074 beta_8 0,0463 0,0032 gamma_5_4 0,0119 0,0033 beta_9 0,0355 0,0049 gamma_6_4 0,0155 0,0031 lambda gamma_7_4 0,0517 0,0045 lambda_1-0,0124 0,0014 gamma_8_4 0,0027 0,0018 lambda_2-0,0082 0,0005 gamma_9_4-0,0515 0,0054 lambda_3 0,0064 0,0008 gamma_5_5 0,0488 0,0035 lambda_4 0,0082 0,0017 gamma_6_5 0,0006 0,0015 lambda_5 0,0032 0,0006 gamma_7_5-0,0226 0,0021 lambda_6-0,0197 0,0010 gamma_8_5 0,0016 0,0009 lambda_7 0,0170 0,0012 gamma_9_5-0,0266 0,0051 lambda_8 0,0064 0,0006 gamma_6_6-0,1114 0,0027 lambda_9-0,0009 0,0009 gamma_7_6 0,0531 0,0026 gamma gamma_8_6-0,0089 0,0011 gamma_1_1 0,2310 0,0147 gamma_9_6 0,0012 0,0023 gamma_2_1-0,0175 0,0020 gamma_7_7 0,0106 0,0049 gamma_3_1-0,0218 0,0066 gamma_8_7-0,0027 0,0014 gamma_4_1-0,0592 0,0073 gamma_9_7 0,0166 0,0033 gamma_5_1 0,0044 0,0050 gamma_8_8 0,0094 0,0008 gamma_6_1 0,0333 0,0036 gamma_9_8 0,0060 0,0014 gamma_7_1-0,0710 0,0053 gamma_9_9 0,1826 0,0144 gamma_8_1 0,0021 0,0021