Price and Quality Effects of Generic Advertising: The Case of Norwegian Salmon

Transcription

1 Natonal Instute for Commody Promoton Research & Evaluaton October 2003 NICPRE R.B Prce and Qualy Effects of Generc Advertsng: The Case of Norwegan Salmon by: Øysten Myrland Unversy of Tromsø, Norway Dansheng Dong and Harry M. Kaser Cornell Unversy Department of Appled Economcs and Management College of Agrculture and Lfe Scences Cornell Unversy, Ithaca, New York 14853

2 The Natonal Instute For Commody Promoton Research and Evaluaton The Natonal Instute for Commody Promoton Research and Evaluaton was nally funded by a CSRS Specal Grant n Aprl The Instute s an offshoot of The Commtee on Commody Promoton Research (NEC-63). A component of the Land Grant commtee structure to coordnate research n agrculture and related felds, NEC-63 was establshed n 1985 to foster qualy research and dalogue on the economcs of commody promoton. The Instute s msson s to enhance the overall understandng of economc and polcy ssues assocated wh commody promoton programs. An understandng of these ssues s crucal to ensurng contnued authorzaton for domestc checkoff programs and to fund export promoton programs. The Instute supports specfc research projects and faclates collaboraton among admnstrators and researchers n government, unverses, and commody promoton organzatons. Through s sponsored research and complatons of related research reports, the Instute serves as a centralzed source of knowledge and nformaton about commody promoton economcs. The Instute s housed n the Department of Appled Economcs and Management at Cornell Unversy n Ithaca, New York as a component of the Cornell Commody Promoton Research Program. Instute Objectves Support, coordnate, and conduct studes to dentfy key economc relatonshps and assess the mpact of domestc and export commody promoton programs on farmers, consumers, and the food ndustry. Develop and mantan comprehensve databases relatng to commody promoton research and evaluaton. Faclate the coordnaton of mult-commody and mult-country research and evaluaton efforts. Enhance both publc and prvate polcy maker s understandng of the economcs of commody promoton programs. Faclate the development of new theory and research methodology. It s the Polcy of Cornell Unversy actvely to support equaly of educatonal and employment opportuny. No person shall be dened admsson to any educatonal program or actvy or be dened employment on the bass of any legally prohbed dscrmnaton nvolvng, but not lmed to, such factors as race, color, creed, relgon, natonal or ethnc orgn, sex, age or handcap. The Unversy s commted to the mantenance of affrmatve acton programs whch wll assure the contnuaton of such equaly of opportuny.

3 Prce and Qualy Effects of Generc Advertsng: The Case of Norwegan Salmon Øysten Myrland Dansheng Dong Harry M. Kaser October 2003 Myrland s an assocate professor n the Department of Economcs and Management, Unversy of Tromsø, Norway. Dong and Kaser are respectvely research assocate and professor n the Department of Appled Economcs and Management, Cornell Unversy, Ithaca, USA. Ths research was funded n part by the Norwegan Seafood Export Councl and the Research Councl of Norway. All statements n ths paper are the conclusons of the authors; GfK Norge does not support or confrm any of the conclusons that the authors base on GfK Norge nformaton.

4 Prce and Qualy Effects of Generc Advertsng: The Case of Norwegan Salmon Abstract In ths paper, a two-equaton sample selecton model s used to estmate a household demand functon for salmon ncorporatng domestc generc advertsng. The twoequaton estmaton procedure, based on purchase and un value equatons, allows us to handle heavly censored panel data for salmon purchases by Norwegan households and the qualy effects smultaneously. Un values of the aggregated salmon commody calculated from the observed expendures and quantes are hypotheszed to represent the average qualy of the purchased commody. Advertsng effects on both purchases and un values are nvestgated. The model also allows us to separate the effects of condonal purchases and purchase probables. Results ndcate that most (78%) of the advertsng effect s through the change of non-purchase occasons to purchase occasons, and that generc salmon advertsng nduces Norwegan households to spend more money on salmon. However, advertsng causes households to select more expensve products rather than ncreasng ther purchased quantes.

5 Prce and Qualy Effects of Generc Advertsng: The Case of Norwegan Salmon Generc advertsng and promoton has become an mportant marketng tool for many agrcultural commodes n the Uned States and other countres, and has been wdely nvestgated n the agrcultural economcs lerature (Ferrero et al; Hurst and Forker). These studes typcally can be dvded nto two types: posve or normatve. The posve studes have focused on evaluatng the mpact of generc advertsng and promoton on markets. The normatve studes have generally examned the optmal allocaton of checkoff funds. The majory of these studes have reled upon hghly aggregated market-level data for econometrc estmaton. However, more recently, there have been several studes that have utlzed mcro-level household data. For example, Schm et al. (2002; 2003) used household data on flud mlk and cheese purchases to estmate the mpact of generc dary advertsng on the household demand for dary products. Ward measured the mpact of the U.S. beef checkoff program usng household data. Rchards used purchase occason household data to measure the mpact of fru advertsng. A key advantage of household data relatve to market data s the former allows one to examne the mpact of demand factors on household behavor, whch s more consstent wh the theory of consumer utly maxmzaton. For example, the use of household data allows the researcher to nvestgate whether the mpact of advertsng prmarly ncreases households purchase ncdence, or purchase amount. Ths cannot be done usng marketlevel data. Ths type of nformaton s valuable for marketng polcy makers for craftng advertsng strateges. 1

6 The purpose of ths study s to demonstrate how the mpacts of advertsng can be decomposed nto effects on the quanty and qualy of purchases. Ignorng the dstncton between qualy and quanty of purchases may lead to erroneous nferences wh respect to advertsng n cross-sectonal datasets. 1 The data are drawn from a panel survey of 1,516 Norwegan households provded by GfK Norge, a marketng research company. Unlke prevous household-level advertsng studes, we adopt an econometrc model developed by Dong, Shonkwler, and Capps to account for selectvy bas arsng from non-consumng households and the resultng unobserved un values (descrbed n detal n the followng secton). The model allows the mpact of advertsng to be decomposed nto s effect on quanty purchased and on the qualy of products purchased by households. In addon, the model provdes a measurement of the mpact of advertsng on household purchase ncdence and quanty purchased. Norwegan fsh farmers have operated a mandatory checkoff program amed at ncreasng fsh consumpton both domestcally and abroad snce Snce Norway s a net exporter of seafood, ths checkoff program s funded through a mandatory levy on all seafood exports, whch have an annual gross value of approxmately $4 bllon. The annual advertsng and promoton budget from the export levy s about $41 mllon, wh the majory (97%) allocated to export promoton. However, snce 1999, the Norwegan Seafood Export Councl (NSEC), who manage the seafood checkoff program, has run an extensve domestc generc advertsng campagn for salmon compared to earler levels of advertsng. 1 There are arguments on how to defne qualy n the lerature. Followng Deaton, Thel, Houthaker, and Dong, Shonkwler, and Capps, we use the term qualy as a euphemsm for product aggregaton bas. Davs and Hewt provde a good summary dscusson of the relaton between the dfferent notons of qualy. 2

7 There have been several economc studes conducted to evaluate the economc mpacts of NSEC promoton actves, all of whch have used market-level data. Economc evaluatons of Norwegan salmon promoton have been conducted by Bjorndal et al., Knnucan and Myrland (2000; 2002), and Myrland and Knnucan. However, all of these studes have focused on export promoton actves snce export markets are substantally more mportant than the domestc market n terms of producer revenue. Consequently, no emprcal estmates of advertsng effects exst for the domestc market. Data Issues and Implcatons Before ntroducng the econometrc model, s helpful to clarfy some ssues related to household demand estmaton. In general, goods are purchased by households n elementary products and each product has s unque prce. The consumer s utly maxmzaton theory s based on the elementary products. However, n many crcumstances, the research nterest s only on consumer s choce of a broad commody category rather than a specfc elementary product. For example, we may want to model household demand for meat whout dstngushng how much s beef, poultry, pork, etc. Under ths suaton, one must deal wh the ssue of product aggregaton. There has been extensve work on product aggregaton and s consequences n the lerature. Product aggregaton nvolves the separably concept that, n general, contans two suatons: Hcksan separably, whch mposes constrants on prce movements, and functonal separably, whch mposes constrants on the structure of preferences. Snce the dscusson of ths ssue s beyond the scope of ths study, we focus only on the 3

8 justfcaton of the use of the un value to replace the unobserved prce n the aggregated household demand estmaton when usng household purchase data. Suppose x j s an ndvdual salmon product j demanded by household, and pj s s assocated observable market prce, where j = 1, 2, 3,, n, and n represents the total number of ndvdual salmon products that can be chosen by the households. Under the condon of functonal (weak) separably of salmon products from others, the consumer s utly maxmzaton problem s gven by: (1) max U ( x, x, L, x ) s. t. n 1 j=1 p 2 j x j n = E where E s total expendures on salmon products. In ths study, we are nterested n the aggregated salmon commody not on any specfc product. The aggregated salmon commody demanded by household s: (2) Q = x j. n j= 1 However, the prce of the aggregated commody Q s not observable. In practce, researchers use the un value of the aggregated commody as a substute for s prce, whch s derved by dvdng expendures by the aggregated quanty: (4) E V =, Q where: E s the expendure of salmon devoted by household, whch equals p j x j. As dscussed below, ths derved un value of the commody vares not only wh the n j= 1 4

9 genune prce of the commody, but also wh the composon of the quantes of the elementary products chosen by the household. Assumng prces of all ndvdual products n the salmon commody vary proportonally (Hcksan separably) as proposed by Deaton, they can be expressed as (3) p = P, j p j where: P can be thought of as the level of salmon prces of Q, and p j s a qualy ndcator of xj, the ndvdual salmon product j, whch s determned by s attrbutes. 2 The larger p the hgher the qualy of xj. Both P and are unobservable and j exogenous to consumers. Snce P s the genune prce ndex of the salmon commody, vares only across tme and regons based on transfer costs. If two households purchase salmon products n the same regon at the same tme, they wll face the same P, even p j though they may purchase dfferent salmon products. However, p j s dependent on ndvdual salmon products. For example, p j for the fresh salmon s hgher than that for frozen salmon, but they both have the same P. If we rewre (3) by takng nto account (2) and (4), we have: (5) V = P, W where W n j= 1 = n p j= 1 j x x j j, whch s the measure of the aggregated commody s qualy, and depends on the composon of household s purchases of the ndvdual salmon products 2 As ponted out by Nelson, P s actually the prce level of the Hcksan compose commody defned as Q c = n j= 1 c p x. Snce Q s not observable, we follow Deaton usng Q. j j 5

10 (x s). Ths mples that W s endogenous and determned by households purchasng choce. By expressng equaton (5) n logarhmc form, the un value becomes the sum of the prce and qualy ndex,.e.: (6) ln V = ln P + ln, W Assumng that the salmon commody forms a separable branch of preferences, the soluton to the household utly maxmzaton problem yelds the demand for the ndvdual salmon products as a functon of the total salmon budget, the prces of the ndvdual products, and the household specfc characterstc varables. Consequently, the household demand for the aggregated salmon commody from all the ndvdual salmon products s also a functon of total salmon expendure E, all the prces of ndvdual salmon products, and household characterstc varables H: (7) Q = Q p, p, L, p, E, H ). ( 1 2 n By consderng (3) and (5), (7) can be wrten as: (8) Q = Q(lnV, E, H ). In equaton (7), all the varables are observed and the endogenous un value V, accordng to (6), can be defned as: (9) lnv = f ( H, C ), where: C s a vector of proxy varables for the unobserved prce P, whch can be regons, and H s used as a vector of proxy varables for the unobserved qualy ndex W. Due to selectvy bas and the fact that un value s endogenous, (8) and (9) must be estmated smultaneously. 3 3 Deaton clams that there s no selectvy problem nvolved n estmatng the un value equaton usng only those households that make a market purchase However, accordng to Wales and Woodland ths clam s ncorrect. 6

11 From the estmaton of (8) and (9), one can obtan the un value elastcy of Q V quanty (η ), the ncome elastcy of un value (η ), and the ncome elastcy of V Q quanty (η ). From these elastces, Deaton (1988) demonstrated how the prce Y Q elastcy (η ) could be retreved: P Y (10) η Q P Q ηv =. Q V Q 1 η ( η / η ) V Y Y From the above analyss, s clear that the commody prce (P) affects not only the demand quanty, but also the un value. For example, f an ncrease n market prces moves the household to purchase less expensve salmon products, the change n the un value wll be smaller than the change n the prce. Thus, f un values are used as prces n the demand estmaton, the same quanty dfference wll be ascrbed to a smaller un value dfference due to the qualy effect, and hence the prce elastcy wll be exaggerated (Deaton). Econometrc Model An emprcal verson of equaton (8) s specfed as the followng: (11) Q lnv α + Z α + ε, = 1 2 where: Q s h household purchase of salmon at tme t, Z, the combnaton of H and E, s a vector of exogenous varables of household characterstcs, demographc, socoeconomc, and advertsng, and lnv s the natural logarhm of the salmon un value pad by household at tme t. Greek letters α1 and α 2 are parameters to be estmated, and ε s the error term. There s no restrcton mposed on equaton (11), so Q can take 7

12 eher posve or negatve values. However, n household survey data, the observed purchases take only non-negatve values. We map the unrestrcted latent varable Q to the non-negatve observed purchase Q as below (Tobn): (12) Q Q ; f Q > 0 = 0 ; otherwse. The un value equaton defned n (9) can be specfed as below: (13) lnv lnv ; f = X β + e Q ; > 0 otherwse, where V s the latent un value; V s the observed un value; X s a vector of varables consstng of C and H ; β s a vector of parameters, and e s the error term. The error terms, ε and e n equatons (11) and (13), are assumed to have a jont normal dstrbuton wh a mean vector zero and varance-covarance matrx as: σ εε σ εe (14) Ω =. σ eε σ ee Followng Dong, Shonkwler, and Capps, the lkelhood functon of ths model can be wrten as: (15) L Q, lnv; α, β, Ω) = φ( ε, e ;0, Ω) Φ( θ ( + 0 ) where: φ(.) s the bvarate normal pdf of ε and e wh zero mean and varancecovarance matrx of Ω. Note e = lnv X β for purchased occasons wh un values beng observed. The + and 0 below the product symbols ndcate purchase and nonpurchase occasons respectvely. Factor Φ θ ( ) s the standard unvarate normal cdf evaluated at θ = [( X β ) α1 Z α 2 ]/( σ εε + 2α 1 σ ε e + α1 σ ee ) +, whch s the 8

13 probably of zero-purchase for household at tme t. Model parameter estmates thus can be obtaned by maxmzng equaton (15) or the logarhm of ths equaton. Data The data used n ths paper are drawn from a panel survey of Norwegan households provded by GfK Norge, a marketng research company. The panel survey ncludes 1,516 Norwegan households, whch s representatve of the country. These households report on a weekly bass every shoppng trp that s done whn the gven week. The data report the expendure and quanty of each em. In addon to household demographcs such as sze, age, locaton and ncome, the type of store the purchase was made, day of purchase, and whether the em was on sale are also reported by each household. The data used for estmaton contans household purchase nformaton for 12 salmon products categorzed as fresh, frozen, smoked, slced etc., on a weekly bass, ncludng total expendures and quantes. Snce generc fsh advertsng data are recorded as monthly expendures, the fnal purchase data are reformulated on a monthly bass and merged wh the advertsng data. The man objectve of ths analyss s to nvestgate the effects of advertsng on Norwegan household salmon purchases. The total salmon commody category s aggregated from many varetes n the data. The fnal data cover the years 1999 through Snce not all the households partcpated n the survey n all the years, and about 80% of the observatons (on a monthly bass) are non-purchase occasons for salmon, there s not enough nformaton to conduct a formal panel structure analyss. However, the data can be pooled to provde enough observatons to handle the heavly censored problem. 9

14 Advertsng s consdered to be a demand shfter n the marketng and economcs lerature. In ths analyss, s based on total monthly generc seafood advertsng expendures. To capture the carry-over effect of advertsng, advertsng expendures are lagged nne months and a polynomal dstrbuted lag model s adopted as follows (Clarke 1976): (16) ADV _ X t = ω A, L = 0 t where: A t- s the th lag of advertsng at tme t, L s the total lag length, whch s nne n 2 ths case, and ω = γ + γ + γ ( = 0, 1,, L) are the quadratc weghts of lagged advertsng. Two restrctons are mposed on ω: () current advertsng has the maxmum weght, whch s defned as one (ω 0 = 1 as the maxmum); () the weght of the tenth lag s zero (ω 10 = 0 ), that s, the effect of advertsng ends at the tenth month (.e., has nne month lags effect). After mposng restrctons () and (), we have ω = 1 1 ( L+ 1) 2 2. ADV_X t, the sum of weghted advertsng over the current and all the lags, s used as an explanatory varable n the demand and un value equatons. The coeffcent of ADV_X t then represents the long-run effect of advertsng. Income and age are recorded as group categores and are transformed nto dummy varables. Table 1 provdes an overvew of the varables used n the emprcal model. Estmaton Results Maxmum lkelhood estmates of the model are obtaned usng the GAUSS software system. The optmzaton algorhm proposed by Berndt et al. s used for the estmaton. The standard errors of the estmated coeffcents are obtaned from the nverse of the 10

15 negatve numercally evaluated Hessan matrx of (15). The estmated coeffcents are presented n Table 2. As dscussed above, the data are pooled to gan enough observatons for the heavly censored problem. However, n order to capture the temporal effects, a tme trend s ncluded n each equaton as suggested by Wooldrdge. The tme trends are sgnfcant n both equatons. The covarance of the errors n the two equatons s nsgnfcant. Ths does not mply that the purchase and the un value have no correlaton. The correlaton between the two varables was ntroduced through the sgnfcant estmates of α 1, the coeffcent of the un value n the purchase equaton. From these coeffcents, the elastces of each explanatory varable can be computed. The use of un value and the smultaney ssue makes the evaluaton of elastces complcated because the exogenous varables of household characterstcs, demographc and socal-economcs not only have drect effects on household salmon purchases, but also have ndrect effects through the changes n un value. For example, an ncrease n household ncome gves the household more money to spend whch may result n ncreased salmon purchases. However, the ncrease n household ncome may also allow the household to buy hgher prced (.e., hgher qualy) salmon products. The fnal effect of ncome on salmon purchases would depend upon the net of these two effects. The expected values of purchase and un value, based on how the elastces are calculated, are derved as follows: (17) E Q ) = Φ( θ )[( X β ) α + Z α ] + ω ϕ( θ ), ( (18) E (lnv ) = X β, 11

16 where: E(.) s expectaton operaton, Φ(.) s the standard normal cdf, and ϕ(.) s the 1 1 ( εε 1 εe + 1 ee ) 2 2 standard normal pdf, ω = σ + 2α σ α σ. Factor Φ θ ) s the probably of posve purchase for household at tme t. To compute the un value effect on purchase, the expected value condonal on a gven un value s calculated as: (19) E Q V ) = Φ( δ )[lnv α + Z α ] + ω ϕ( δ ), ( σ εe σ εe 2 where: δ = [lnvα1 + Zα 2 + (lnv X β )]/ ω 2, and ω 2 = ( σ εε ). Factor σ σ ee ( ee 1 Φ( δ ) s the probably of posve purchase for household at tme t gven un value V. Note the dfference between Φ δ ) and Φ θ ). ( Elastces of explanatory varables evaluated at the sample mean wh respect to equatons (17)-(19) are presented n Table 3. A detaled explanaton of how these elastces are calculated s provded n the Appendx. The columns of E(Q V), E(V), and E(Q) are the results wh respect to equatons (19), (18), and (17), respectvely. Elastces of E(Q) n column 3 can be vewed as a combned or total of the results from E(Q V) (column 1) and E(V) (column 2). A detaled dscusson on these elastces s presented below. ( Marketng Related Varables The un value elastcy s only avalable for the purchase equaton when the un value s gven as ndcated n equaton (19). 4 Under ths suaton, the un value elastcy s found to be negatve (-1.84), statstcally sgnfcant, and elastc as expected. A 1% 4 Un value s gven can be nterpreted as the un value s fxed and the household s not allowed to adjust s purchase composon for qualy. 12

17 ncrease n un value reduces salmon purchases by 1.84%. As defned above, an ncrease n the salmon un value can come from eher the real ncrease of salmon market prce, or by the choce made by households to buy hgher prced or hgher qualy salmon products. Unfortunately, we are not able to dentfy the two sources of changes. However, the effect of the two types of change on demand can be treated as the same. The results of advertsng are que nterestng because of the separate qualy and quanty effects. A 1% ncrease n advertsng sgnfcantly ncreases salmon purchases by 0.17% when the un value s gven,.e., when the qualy effect s not taken nto account. At the same tme advertsng ncreases the un value of salmon by 0.06%. Ths ncrease n un value, n turn, decreases the quanty of salmon purchases. Hence, the ncrease n un value offsets the purchase effect nduced by advertsng. Thus the eventual ncrease n purchases becomes small and nsgnfcant (0.04). Therefore, the total effect of advertsng s found to be posve (but statstcally nsgnfcant) on quanty purchased, but advertsng stll has a statstcally sgnfcant mpact on ncreasng the salmon un value or qualy purchased by households. Consequently advertsng ncreases total household expendures on salmon. For nstance, a 1% ncrease n advertsng ncreases salmon purchase by 0.04% (nsgnfcantly) and ncreases the un value by 0.06% (sgnfcantly). As a result, the change n salmon expendures s (1+0.04)(1+0.06) 1 = 0.10%. Ths result mples that salmon advertsng nduces Norwegan households to spend more money on salmon. Salmon purchases made n specal fsh shops or n other stores are found to have no sgnfcant dfference on eher quanty or un value. However, store on sale promotons are found to play an mportant role n salmon purchases. The sgnfcant 13

18 negatve effect on un value (-4.71) s because the stores on sale program s always related to prce reducton promoton. Thus the overall effect on salmon purchase s found to be posve and sgnfcant (0.02). However, the effect on purchase when un value s gven s found surprsngly to be negatve and sgnfcant (-0.12). Ths unntuve result may be nterpreted as follows. A store s on sale actvy ncreases salmon purchase only through the decrease n un value. Under the on sale program, f the un value s not allowed to change (.e., no prce reducton) and no qualy adjustment s allowed, consumers would then reduce ther wllngness to purchase salmon. Household Characterstcs Household ncome and age of the household head were collected as group categores, and ther effects were estmated by dummy varables. Relatve to households wh ncome over 600,000, we found the ncomes below 200,000, and between 250,000 and 300,000 have negatve and sgnfcant effects on salmon purchases, whle the ncomes between 500,000 and 600,000 have sgnfcant posve effects. Relatve to the age of 45-59, younger head households are found to purchase less salmon, whle households wh older heads purchase more. Household sze s found to have posve effects, whle the proporton of persons under 16 years of age have negatve effect on salmon purchase. In contrast to E(Q) n whch all the effects are sgnfcant, the effects of HSIZE on E(Q V) are nsgnfcant. Wh respect to the un value equaton, ncomes are nsgnfcant. Household sze s negatve, as expected, mplyng that a large household would sacrfce qualy for quanty of salmon purchases to satsfy the needs of addonal people lvng n the 14

19 household. Relatve to the age of 45-59, younger head households purchase hgher prced salmon, whle older head households purchase lower prced products. The proporton of chldren under 16 years old n the household has a posve, but nsgnfcant coeffcent. Regonal Varables Metropolan and regonal varables are not ncluded n the purchase equaton snce they do not affect purchases when the un value s gven. However, they can ndrectly affect the uncondonal purchase through the change n the un value. Indeed, whout un value gven, METRO s found to sgnfcantly ncrease salmon purchases because has a negatve and sgnfcant effect on un value. Ths result mples that resdents n metropolan areas eher pay lower salmon prces or purchase lower qualy products. Purchases are also found to be sgnfcantly dfferent among regons. No sgnfcant effects are found for regons n both purchase and un value equatons. Extensve and Intensve Responses of Salmon Purchases The elastces n Table 3 wh respect to purchases can be decomposed nto two parts: ntensve and extensve responses. The ntensve response of purchase s the contnuous adjustments n purchased quanty when the explanatory varables change after a posve purchase occurs. The extensve response s the dscrete change between purchase and non-purchase occasons. The two types of responses for several key varables are provded n Table 4. Column 1 gves the elastces of condonal purchase when un values are gven, whch represent the ntensve effects. Column 2 lsts the elastces of 15

20 the probably of posve purchases when un values are gven, whch represent the extensve effects. Columns 3 and 4 are the results when un values are not gven. The overall advertsng elastcy whout gven un values s Ths can be decomposed nto an ntensve elastcy of 0.01 (column 3 n Table 4) and an extensve elastcy of 0.03 (column 4 n Table 4). The results ndcate that most of the advertsng effects on salmon purchases (78%) are through extensve effects,.e., through the change of non-purchase occasons to purchase occasons. Indeed, ths pattern s found for all other varables n Table 4, whch s consstent wh the household data that about 80% of the observatons are non-purchase occasons. Concludng Comments In ths study, the mpact of generc salmon advertsng on household demand n Norway was evaluated. The data ncluded 1,516 Norwegan households on a monthly tme nterval from provded by GfK Norge, a marketng research company. Unlke prevous household-level advertsng studes, we used an econometrc model desgned to account for selectvy bas arsng from non-consumng households and the resultng unobserved un values. One advantage of the model was provded for a decomposon of advertsng mpacts on both qualy and quanty demanded by households. In addon, the model provded a measurement of the mpact of advertsng on household purchase ncdence and quanty purchased. The fndngs n ths paper are nterestng both from a marketng perspectve, and from commody polcy perspectve. Whle domestc salmon advertsng appears to not have a sgnfcant mpact on ncreasng demand, does have a posve effect on qualy. That s, advertsng nduces Norwegan households to purchase more expensve, hgher 16

21 qualy salmon products. A 1% ncrease n advertsng ncreased the un value of salmon by 0.06%. Consequently, salmon advertsng ncreased total household expendures on salmon. A 1% ncrease n advertsng resulted n a 0.10 percent ncrease n household salmon expendures. The ntensve and extensve mpacts of advertsng were also estmated. The overall advertsng elastcy of household purchases whout gven un values was Ths elastcy was decomposed nto an ntensve elastcy (ncrease n purchase quanty) of 0.01 and an extensve elastcy (ncrease n purchase occasons) of Thus, the results ndcated that most of the advertsng effects on salmon purchases (78%) are through extensve effects. Indeed, ths pattern was found for all other varables n the demand model. 17

22 Table 1. Explanatory Varables Used n Purchase and Un Value Equatons Name Descrpton (un) Means Marketng Related Varables QUANTITY Monthly purchase of salmon (gram) PRICE log of prce ADV_X polynomal dstrbuton lag of advertsng (1,000,000) FISHSHOP dummy of fsh shop (0/1) ONSALE dummy of prce on sale (0/1) Household Characterstcs INCOME1 hh ncome between (0/1) INCOME2 hh ncome between (0/1) INCOME3 hh ncome between (0/1) INCOME4 hh ncome between (0/1) INCOME5 hh ncome between (0/1) INCOME6 hh ncome between (0/1) INCOME7 hh ncome between (0/1) INCOME8 hh ncome between (0/1) INCOME9 hh ncome between (0/1) INCOME10 hh ncome between 600+ (0/1) HSIZE log of hh sze AGE_HEAD1 head age between (0/1) AGE_HEAD2 head age between (0/1) AGE_HEAD3 head age between (0/1) AGE_HEAD4 head age between 65+ (0/1) KID16_PROP proporton of persons under Regons METRO dummy versus rural (0/1) NORTH regon dummy (0/1) CENTRAL regon dummy (0/1) WEST regon dummy (0/1) OSLO regon dummy (0/1) Tme Trend MONTHNUM Tme trend of month -- 5 The number s the average over all the households. The average among purchase household s 1,044 G. These numbers are que consstent wh the measurement from other data. 18

23 Table 2. Maxmum Lkelhood Estmates of Model Parameters Demand Equaton (Q) Prce Equaton (lnv) Varable Coeffcent Std. Error Coeffcent Std. Error CONSTANT Marketng Related Varables PRICE (α 1 ) ADV_X FISHSHOP ONSALE Household Characterstcs INCOME INCOME INCOME INCOME INCOME INCOME INCOME INCOME INCOME HSIZE AGE_HEAD AGE_HEAD AGE_HEAD KID16_PROP Regons METRO NORTH CENTRAL WEST OSLO Tme Trend MONTHNUM Varances Matrx ε e ε E Goodness of f measures (R2) ndcates sgnfcance at the 0.05 level or hgher. These measures are calculated through the squared correlaton of actual and predcted values. 19

24 Table 3. Elastces wh respect to the Demand and Un Value Varable E ( Q V ) (1) E ( V ) (2) E ( Q ) (3) Elastcy T-rato Elastcy T-rato Elastcy T-rato Marketng Related Varables PRICE ADV_X FISHSHOP ONSALE Household Characterstcs INCOME INCOME INCOME INCOME INCOME INCOME INCOME INCOME INCOME HSIZE AGE_HEAD AGE_HEAD AGE_HEAD KID16_PROP Regons METRO NORTH CENTRAL WEST OSLO The t-statstcs are based on the standard errors derved from the Delta Method (Rao, 1973). 20

25 Table 4. Intensve and Extensve Responses of Salmon Purchases Varable E ( Q Q>0, V ) (1) Prob ( Q Q>0, V ) (2) E ( Q Q>0 ) (3) Prob ( Q>0 ) (4) Elas. T-rato Elas. T-rato Elas. T-rato Elas. T-rato PRICE ADV_X HSIZE The t-statstcs are based on the standard errors derved from the Delta Method (Rao, 1973). 21

26 Appendex: Elastcy Evaluaton If S s a functon of a, say, S = g(a), the elastcy of S wh respect to a s the percentage change of S gven a percentage change of a. It can be expressed as S S S S a (A1) η a = = ( )( ), a a S a where S ndcates a small change. However, the precsely defnon of η can be gven a as: S S a (A2) η a = ( )( ), a S where S a s the dervatve of S wh respect to a. If a s a dchotomous varable, the elastcy then defned as: η S a = g( 1) g(0), where g(1) s the value of S when a = 1, and g(0) s the value of S when a = 0. to us. Gven equatons (17)-(19), we can calculate several elastces that are nterested Quanty Elastces Equaton (17) represents the uncondonal expected value of the quanty purchased by households, whch can be expressed as: (A3) E( Q ) = Prob( Q = Φ( θ ){[( X > 0) E( Q β ) α 1 + Z Q 2 > 0) α ] + ω 1 ϕ( θ Φ( θ ), } ) where, (A4) Prob > 0) = Φ( θ ), ( Q 22

27 the probably of posve purchase, and (A5) ϕ( θ ) E( Q Q > 0) = [( X β ) α1 + Zα 2] + ω1, Φ( θ ) the condonal expected value of the quanty gven a posve purchase. Accordng to (A2), the elastcy of uncondonal quanty gven n (A3) wh respect to a partcular exogenous varable c n Z or X, can be derved as: Q E( Q ) c (A6) η c = ( )( ). c E( Q ) To get (A6), we need the dervatves of Φ θ ) and ϕ θ ), whch can be found n ( Maddala (1983). (A6) gves the results of Column (3) n Table 3, whch are evaluated at the sample means. Smlarly, we can derve the elastcy of the probably of posve purchase based on (A4), whch gves the results of column (4) n Table 4, and the elastcy of condonal quanty based on (A5), whch gves the results of column (3) n Table 4. Snce (A3) s the product of (A4) and (A5), mples that the elastcy of (A3) s the sum of the elastces of (A4) and (A5). That s, the sums of the results n columns (3) and (4) n Table 4 are the results of column (3) n Table (3). Snce the un value (V) s endogenzed n ths study, the expected value of the quanty purchased n (A3) does not depend on V drectly. In order to compute the drect effect of the un value on the quanty purchased, we need the expected value of quanty condonal on a gven un value, whch s gven by equaton (19): ( (A7) E( Q V ) = Prob( Q = Φ( δ Q ){[(lnv α > 0, V 1 + Z ) E( Q 2 α ] + ω Q 2 ϕ( δ Φ( δ > 0, V ) } ) ). 23

28 Then, the elastcy of quanty condonal on a gven un value wh respect to a partcular exogenous varable c (V or any varable n Z ) can be derved as: QV E( Q V ) c (A8) η c = ( )( ). c E( Q V ) (A8) gves the results of Column (1) n Table 3. Smlarly, we can derve the elastcy of the probably of posve purchase condonal on a gven un value, whch gves the results of column (2) n Table 4, and the elastcy of quanty condonal on a posve purchase and a gven un value, whch gves the results of column (1) n Table 4. Smlarly, the sums of the results n columns (1) and (2) n Table 4 are the results of column (1) n Table (3). Accordng to (A1), we can numercally evaluate (A6) and (A8). Take (A6) as an example. We calculate E(Q ) usng (A6) at the orgnal value a (usually the mean value) of a partcular varable, say household sze. Then, after gven a small change n the varable, say a = 0.001, we calculate the new value of E(Q) usng (A6). Accordng to (A1), the elastcy can be evaluated as: η Q a = E( Q ) E( Q ) a a. Smlarly, ths approach can be appled to (A8). Ths approach has been used wdely snce one does not need to analytcally calculate the dervatves of (A3) and (A5). The results reported n Tables 3 and 4 are computed from ths numercal procedure. Un Velue Elastces The expected value of the logarhm un value s gven by (18),.e., (A9) E (lnv ) = X β. The elastcy of V wh respect to X then s: 24

29 (A10) V β η X =. E V ) ( (A10) gves the results of column (2) n Table 3. In ths two-equaton model, the margnal effects on the quanty (captured by (A6)) of a varable that s common n both equatons can be vewed as the sum of the drect effects of the un value (captured by (A8)) on the quanty and the ndrect effects of the varable through the change of the un value (captured by (A10)). 25

30 References Berndt, E., Hall, B., Hall, R., and Hausman, J. (1974). Estmaton and Inference n Nonlnear Structural Models. Annals of Economc and Socal Measurement, 3, Bjørndal, T., Salvanes, K. G., and Andreassen, J. H. (1992). The demand for salmon n France: the effects of marketng and structural change. Appled Economcs, 24, Clarke, D. G. (1976). Econometrc Measurement of the Duraton of the Advertsng Effect on Sales. Journal of Marketng Research, 13, Davs, G., and Hewt E. (1996). Measurng the Qualy of Imported Tobacco. Journal of Agrcultural and Appled Economcs, 22(1), Deaton, A. (1988). Qualy, Quanty, and Spatal Varaton of Prce. The Amercan Economc Revew, 78(3): Dong, D., Shonkwler, J. S., and Capps, O. J. (1998). Estmaton of Demand Functon Usng Cross-Sectonal Household Data: The Problem Revsed. Amercan Journal of Agrcultural Economcs, 80, Ferrero, J., Boon, L., Kaser, H. M., and Forker, O. D. (1996). Annotated Bblography of Generc Commory Promoton Research (revsed). NICPRE , Natonal Instute for Commody Promoton Research & Evaluaton, Dep. of Ag. Econ., Cornell Unversy, Ithaca, New York. Forker, Olan D. and Ronald W. Ward. (1993) Commody Advertsng: The Economcs and Measurement of Generc Programs. Lexngton Books, New York. Hurst, Susan and Olan D. Forker. (1991) Annotated Bblography of Generc Commody Promoton Research. A.E. Res 91-7, Department of Agrcultural Economcs, Cornell Unversy. Knnucan, H. W., and Myrland, Ø. (1988). Producer Welfare Impacts of the Norway-EU Salmon Agreement: A Model and Some Inal Results., The Norwegan College of Fshery Scence, Tromsø. 26

31 Knnucan, H. W., and Myrland, Ø. (2000). Optmal advertsng leves wh applcaton to the Norway-EU Salmon Agreement. European Revew of Agrcultural Economcs, 27(1), Knnucan, H. W., and Myrland, Ø. (2001). Optmal promoton expendures for salmon: the mportance of nternatonal prce lnkages. Aquaculture Economcs & Management, 5(5/6), Knnucan, H. W., and Myrland, Ø. (2002). The Relatve Impact of the Norway-EU Salmon Agreement: A Mdterm Assessment. Journal of Agrcultural Economcs, 53(2), Maddala, G.S. (1983). Lmed-Dependent and Qualatve Varables In Econometrcs, Cambrdge Unversy Press, New York. Myrland, Ø., and Knnucan, H. W. (2001). Drect and ndrect effects of generc advertsng: a model wh applcaton to salmon. Aquaculture Economcs and Management, 5(5/6), Rao, R. C. (1973). Lnear Statstcal Inference and Its Applcatons, Wley, New York. Rchards, Tmothy J. (2000) A Dscrete/Contnuous Model of Fru Promoton, Advertsng, and Response Segmentaton. Agrbusness: An Internatonal Journal. 16: Schm, Todd M., Bran W. Gould, Dansheng Dong, Harry M. Kaser, and Chanjn Chung. (2003) The Impact of Generc Advertsng on Household Cheese Purchases: A Censored Autocorrelated Regresson Approach. Canadan Journal of Agrcultural Economcs. Forthcomng. Schm, Todd M., Dansheng Dong, Chanjn Chung, Harry M. Kaser, and Bran Gould. (2002) Identfyng the Effects of Generc Advertsng on the Household Demand for Flud Mlk and Cheese: A Two-Step Panel Data Approach. Journal of Agrcultural and Resource Economcs. 27: Tobn, J. (1958). Estmaton of Relatonshps for Lmed Dependent Varables. Econometrca, 26, Wales, T. J., and Woodland, A. D. (1980). Sample Selectvy and The Estmaton of Labor Supply Functons. Internatonal Economcs Revew, 21(June),

32 Ward, Ronald W. (1999) Evaluatng the Beef Promoton Checkoff: The Robustness of Conclusons. Agrbusness: An Internatonal Journal. 15: Wooldrdge, J. (2002). Econometrc Analyss of Cross Secton and Panel Data, MIT Press. 28

33 OTHER A.E.M. RESEARCH BULLETINS RB No Tle (If applcable) Author(s) 0...., ~~..:'c':'! Fee Coupon Redempton and Its Effect on Household Dong, D. and Kaser, H. Cheese Purchases Dary Farm Management Busness Summary, New ($15.00) Knoblauch, W., Putnam, L. and York State, 2002 Karszes, J Fru Consumpton, Detary Gudelnes, and Peters, C., Blls, N., Wlkns, J., and Agrcultural Producton n New York Smh, R.D. State--Implcatons For Local Food Economes Future Structure of the Dary Industry: Hstorcal LaDue, E., Gloy, B. and Cuykendall, Trends, Projectons and Issues C Prospects for the Market for Locally Grown Organc (12.00) Conner, D. Food n the Northeast US Dary Farm Management Busness Summary: New ($15.00) Knoblauch, W. A., L. D. Putnam, York State, 2001 and J. Karszes Needs of Agrculture Educators for Tranng, C. A. Schlough and D. H. Streeter Resources, and Professonal Development n Busness Management and Marketng Fnancal Management Practces of New York Dary Gloy, B. A., E. L. LaDue, and Farms K. Young blood Rural, Suburban and Urban Sngle Mothers' AFDC Ranney, C. K. and FSP Partcpaton and Labor Supply: Lessons for Welfare Reform Vegetable Consumpton, Detary Gudelnes and Peters, C., N. Blls, J. Wlkns and Agrcultural Producton n New York R. D. Smh State-Implcatons for Local Food Economes Measurng the Impacts of Generc Flud Mlk and Schm, T. M. and H. M. Kaser Cheese Advertsng: A Tme-Varyng Parameter Relatonshp between Partal and Total Responses Knnucan, H. and 0. Myrland to Advertsng wh Applcaton to U.S. Meats Paper copes are beng replaced by electronc Portable Document Fles (PDFs). To request PDFs of AEM publcatons, wre to (be sure to Include your e-mall address)' Publcatons, Department of Appled Economcs and Management, Warren Hall, Cornell Unversy, Ithaca, NY 1~ If.a fee s ndcated, please nclude a check or money order made payable to Cornell Unversy for the amount of your purchase VIS our Web se (http.llaem.cornell.edu/research/rb.htm) for a more complete lst of recent bulletns.