Innovation, Integration and Product Proliferation - Empirical Evidence for the Agri-Food Industry

Transcription

1 Innovaton, Integraton and Product Prolferaton - Emprcal Evdence for the Agr-Food Industry Kostas Karantnns Insttute for Food and Resource Economcs, Unversty of Copenhagen, Denmark Johannes Sauer Kent Busness School, Unversty of Kent, Imperal College at Wye, Unted Kngdom and Unversty of Copenhagen, Denmark (j.sauer@mperal.ac.uk) Wllam Hartley Furtan Unversty of Saskatchewan, Saskatoon, Canada Selected Paper for presentaton at the Amercan Agrcultural Economcs Assocaton Annual Meetng, Orlando, FL, July 27-29, 2008 Copyrght 2008 by [K. Karantnns, J. Sauer and H. Furtan]. All rghts reserved. Readers may make verbatm copes of ths document for non-commercal purposes by any means, provded that ths copyrght notce appears on all such copes.

2 INNOVATION, INTEGRATION AND PRODUCT PROLIFERATION EMPIRICAL EVIDENCE FOR THE AGRI-FOOD INDUSTRY [DRAFT VERSION 30/04/2008] Abstract Whle mergers, both horzontal and vertcal, have been shapng the landscape of the agr-food ndustry n Europe, the mplcatons of the changng market structure on the level of nnovaton has not been studed yet. In ths paper we deal wth the lnk between nnovaton and market structure usng the emprcal example of the Dansh agr-food ndustry. The purpose of ths paper s two-fold. Frst we test for the mportance of vertcal ntegraton on nnovaton. Whle there exst several studes on ths lnkage, to our knowledge, ths s the frst that deals wth the agr-food ndustry. Secondly, we examne both product prolferaton and nnovaton. To our knowledge, there are no other smlar studes that examne both aspects usng the same data set. We follow the hypothess put forward by Armour and Teece (1980) that vertcal ntegraton enhances technologcal nnovaton, manly because vertcal ntegraton may resolve hold-up problems. Our paper s related also to recent work by Wess and Wtkopp (2005) on the German food ndustry, although ther work s mostly related to the role of the retal sector. We are able to examne both nnovaton (measured as nvestment on R&D) as well as product prolferaton (measured as number of new products). We also examne the effects of network relatonshps and the mportance of countervalng power. We use data from an extensve survey of 444 Dansh frms over two years, 2000 and 2005 to estmate two dfferent models: a bootstrapped zero-nflated Posson regresson and a robust Heckman sample selecton model. The results verfy the hypotheses formulated for both models wth varous degrees of sgnfcance. Keywords: Innovaton, Vertcal Integraton, Product Prolferaton, Agrbusness 2

3 INNOVATION, INTEGRATION AND PRODUCT PROLIFERATION EMPIRICAL EVIDENCE FOR THE AGRI-FOOD INDUSTRY 1. INTRODUCTION A major source of economc growth s nnovaton. Economc compettveness s lnked to the ablty of frms to nnovate. Wth much of the economy hangng on the ablty of frms to nnovaton both ndustry and governments have placed the understandng of the process nnovaton very central to ther polcy. In the agr-food ndustry n partcular, market forces and to a great extend the globalzaton process, have been drvng the ndustry towards more nnovatons n order to address market needs and face ncreased competton. At the same tme, however, the level of research and development expendtures (R&D) n the food ndustry s rather low compared to total manufacturng (EU, 2007). In ths paper we examne some of the determnants of nnovaton n the agr-food ndustry. Organzaton gves pre-emnence to the frm and the dfferent types of organzaton. Organzatonal models or organzatonal choce s often what gves frms comparatve advantage. In partcular, t must be ponted out that the boundares of the frm are an mportant strategc varable for nnovatng frms (Teece, 1986, p. 304). What s not known s how the governance choce and the overall organzaton of the frm affect the process of nnovaton. We specfcally examne n ths paper the role of the choce of governance (spot market, vertcal ntegraton, contracts) on the level of nnovaton of agr-food frms. Insttutons are also mportant n understandng the process of nnovaton. Insttutons carry at least two meanngs. Frst, nsttutons provde drecton to research and development (R&D) and are expressed n the form of natonal research nsttutons. The analyss focuses on the economc returns 3

4 to nvestment n R&D actvtes. Ths framework usually treats nnovaton as a black box. Second, nsttutons also refer to the rules of the game as descrbed by nsttutonal theorsts (North, 1990). In ths case emphass s placed on property rghts and the ablty of frms to patent the new nnovatons. Ths creates the ncentve for nvestment n research and development. Most of the research on nnovaton n the agrculture and food sector places greater emphass on nsttutons than on the organzaton of frms. In ths paper we examne the role of the organzaton of the agrfood frms on ther level of nnovaton. Very often nnovatons lead to new product development. Ths s not always true, however, especally n the case of process nnovaton (as opposed to product nnovaton). In ths case, one needs to examne both the level of nnovaton, as well as the ntroducton of new products by frms. We examne both ssues separately by testng two dstnct models, one usng R&D actvty, and another usng new product ntroducton, as two dstnct measures of nnovaton for agr-food frms. The study of nnovaton from an organzatonal vew pont has ts roots n the work of Schumpeter (1943). There are two man conjectures that come out of ths work. Frst, larger frms are central to nnovaton. Large frms have the captal base to be capable of conductng the research and brngng the new products or processes to the market. Second, how frms are organzed s the key to understandng the nnovaton process (Corat and Wensten, 2002). Innovaton s a process that s lnked wth dfferent dvsons wthn the frm or between frms - that makes the organzaton the crtcal varable. We focus on frm sze and market power, as well as how the frm s organzed n terms of vertcal ntegraton, contractual arrangements, market power, relatonshp to foregn nvestment, ownershp and other sector specfc varables. The purpose of ths paper s to buld models to test these conjectures usng a unque set of data collected on the Dansh food ndustry. The Dansh food sector has been a world leader n organzaton and nnovaton (World Economc Forum, 2007). There exst numerous cooperatves 4

5 and prvate frms that are vertcally and horzontally ntegrated. Ths dversty n the type of organzaton makes the Dansh food sector an deal lab to examne the relatonshp between the organzaton of frms and the process of nnovaton. The thrust of ths paper and ts man contrbuton to the lterature s the emprcal study of the role of the organzaton of the frm on nnovaton. To our knowledge no such study exsts partcularly for the agr-food ndustry. The paper tes to the vast lterature on the theory of the frm that dates back to Coase (1932) and hs descendants. In ths paper, we study emprcally how the boundares of the frm affect ts ablty to nnovate. Ths seems to be mportant as nnovaton s one of the man vehcles for growth and proftablty of frms. Hence, ths study contrbutes to a better understandng of the lnk between frm organzaton and the dynamcs of growth and proftablty of frms and ndustres. We develop two models to test the effect of organzatonal varables along wth other explanatory varables on two proxes for nnovaton, respectvely: the number of new products and secondly the R&D expendture. We apply approprate econometrc technques n each case: a bootstrapped zero nflated Posson regresson (ZIP) followng the count data characterstcs of the frst dependent varable and a robust Heckman sample selecton model to account for the truncated second dependent varable. The paper s organzed as follows: secton 2 gves a theoretcal revew of the relevant lterature and secton 3 descrbes the survey and the data set used. Secton 4 outlnes the modellng and estmaton procedures used, secton 5 reports and dscusses the results and secton 6 fnally concludes. 2. THEORY For many years, the dscusson on nnovaton was domnated by the Schumpeteran argument of the mportance of monopoly power as a prerequste for nvestment on nnovaton (Schumpeter, 5

6 1942). However, the vrtues and benefts of monopoly and competton are not the only factors determnng nnovaton. It s now well-known that nnovaton s among other thngs a result of management and organzaton decsons (Teece, 1989; Trall and Grunert, 1995). It s useful to dstngush between two types of nnovaton (Grunert, et. al., 1995; Trole, 1988) 1 : a. Product nnovaton refers to the development of new products and servces; and b. Process nnovaton whch reduces producton costs or enables the producton of new products. The dstncton between product and process nnovaton s not always clear and very often creates confuson n emprcal research. We can approxmate the level of nnovaton actvty of a frm ether by measurng the output of, or the nput to nnovaton. As an output proxy the number of new products ntroduced each year s usually used. As nput to nnovaton the level of R&D expendtures s usually used. Thus, product prolferaton and nnovaton are two closely lnked actvtes of frms. It can be argued that nnovaton s a pre-requste (suffcent but not necessary) for product prolferaton: Technologcal change, [ ] can expand the product space by makng addtonal dmensons possble, by addng more classfcatons on exstng dscrete axes, or by extendng the range of contnuous axes. Thus, technologcal change can be sad to be a suffcent condton for product prolferaton. It s not a necessary condton, however, because some physcal dfferentaton (e.g. changes n package sze) can occur wth a statc technology (Connor, 1981, p. 609). There are several reasons why product prolferaton may be a dfferent process and frm strategy than nnovaton. Frst, not all new products are a result of nnovaton. There may be smple product dfferentaton that has lttle to do wth nnovaton, research and development actvtes. Hence, the number of new products may not be drectly related to the amount and efforts nvested. Large and long-term amounts may result nto a small number of new products, whereas 1 Another very mportant category s organzatonal nnovaton, we do not deal wth ths here (See Damanpour, 1991 for a revew) 6

7 frms pursung aggressve product dfferentaton strateges may not be nnovators at all. Secondly, even f we assume that all new products are a result of nnovatve actvtes by the frm, they only capture the success stores. There s a lot of uncertanty nvolved n the outcomes of nnovaton and not all nnovaton results n new products. Hence, frms that nvest n nnovaton and dd not launch new products n the tme perod covered by the study wll appear as not nnovatng at all. Thrdly, the R&D nvestment may smply be on pure process nnovatons amed at reducng costs of producng exstng products. Hence, although there s nvestment n nnovaton t wll not materalze nto new products. For the above reasons, new products as a proxy for nnovaton can create two types of emprcal fallaces: Type A Falacy: Measurng new products the researcher may over-estmate nnovaton snce part of t s mere product prolferaton or smply product of past nvestments 2. In Fgure 1, f the researcher observes new product t s not possble to dfferentate between nodes D and F. The frm may be an nnovator (nodes A-D) or non-nnovator (nodes B-F). Type B Falacy: Investment on nnovaton may not result nto new products, hence, new products may actually under-estmate nnovaton 3. In Fgure 1, ths corresponds to not beng able to dfferentate between nodes A-C and B-E. <FIGURE 1 HERE> It s dffcult to dstngush the two types of fallaces emprcally. Also, as our focus s on the effects of market structure, we need to dstngush between the two. Therefore, we chose to use both measures: new products, and nnovaton expendtures (as percentage of total frm s expendtures) 2 Also, gven the lags between nvestment n research and results, new products durng the samplng perod may be a result of nnovaton n prevous perods. 3 Furthermore, gven that some research and nnovaton actvtes take long to produce results, we may not observe any new products durng the samplng perod, whle large nvestments on nnovaton are under-taken. 7

8 and estmate two separate models wth dfferent control varables and estmaton technques. The methodology s outlned n secton 3. The ncentves for nnovaton (and/or product prolferaton) may vary between manufacturers and retalers. Whle manufacturers vew product varety as a booster for ther demand, retalers may fear addtonal nventory costs and therefore may prefer fewer products. Therefore the type of the agrfood frm and ts place n the agr-food chan are very mportant varables. Our focus and man hypothess s that market structure determnes both nnovaton and product prolferaton. More specfcally, we frstly hypothesze that vertcal ntegraton, the exstence of networks and retal market power determne nnovaton and prolferaton of products. Secondly, we hypothesze that economes of sze are a determnant of nnovaton and product prolferaton. Thrdly, we hypothesze that as we move down the chan frms wll tend to ntroduce more new products, whle frms upstream wll tend to nnovate more. Below we dscuss the theoretcal and conceptual foundaton of these hypotheses. Vertcal ntegraton The lnk between nnovaton and vertcal ntegraton s well known. Frankel (1955) attrbutes the slow rate of dffuson of nnovatons n the Brtsh ndustry n the late 1800s/early 1900s to the absence of vertcal ntegraton n the textle and ron frms. Smlarly, Kndleberger (1964) argued that Japan and W. Germany had surpassed G. Brtan because Brtsh manufacturng lacked vertcally ntegrated frms. Ths, argues Kndleberger (1964), curbs ncentves for frms to nnovate snce the benefts are scattered to other frms. Marx (1976) attrbutes the domnance of General motors n the electrc locomotve ndustry to the fact that, contrary to ts compettors, GM was ntegrated nto electrcty generaton. Economdes (1997) shows that ntegrated monopolsts wll provde hgher qualty and wder varety of products. In a study of the musc ndustry Allan and Woelbroek (2004) fnd that vertcal 8

9 ntegraton ncreases product varety. The man reason s that vertcal ntegraton reduces double margnalzaton and the fxed costs of nnovaton are better nternalzed by the vertcally ntegrated entty than a chan of separated monopoles. They also show that competton at the downstream market ncreases product varety upstream. Innovaton s a very specal process. Both the resources requred to producng t and ts outcome are not drectly measurable and hence not easly contractble. Resources such as knowledge - partcularly organzatonal knowledge and the product of nnovaton and know-how are not easly transferable. As a result, markets are not always the approprate form for the governance of nnovaton transactons. Instead frms nvolved n such actvtes rely on a varety of herarchcal (vertcal ntegraton) or hybrd organzatonal forms such as networks, strategc allances, cooperatves, etc. The approprablty of the benefts from nnovaton actvtes s key for frms to nvest n R&D. Hence property rghts, patents, and overall transacton cost arguments are crucal. Armour and Teece (1980) study systematcally the hypothess that vertcal ntegraton enhances technologcal nnovaton, manly because vertcal ntegraton may resolve hold-up problems (Wllamson, 1985). Also, because a clearer defnton of goals exstst snce communcaton between R&D and other departments s better facltated n vertcally ntegrated frms (Armour and Teece, 1980). The results from an econometrc study on the US petroleum ndustry support ther man hypothess. Usng a dfferent (ex ante) chan of logc, Balakrshnan and Wernerfeldt (1986) argue that the rsk of technologcal obsolescence wll curb the frms ncentves to vertcally ntegrate. Our frst hypothess then can be stated as: Hypothess 1: Vertcal ntegraton s assocated wth hgher levels of nnovaton and product prolferaton by frms. 9

10 Networks Quas ntegraton, through contracts and other network arrangements, s key to nnovaton 4. One reason s economes of scale and scope whch can be captured through nter-frm arrangements (Teece, 1996, p. 198). Robertson and Langlos (1994) conclude that nether organzatonal form (vertcal ntegraton versus network) s clearly better than the other, the choce depends on the nature and scope of the nnovaton and on the product lfe cycle. 5 Hypothess 2: Smlar to vertcal ntegraton, network relatons contrbute to hgher levels of nnovaton and product prolferaton. Hence contractual relatons (as a proxy of networks) are expected to be postvely related to nnovaton and product prolferaton. Countervalng power The debate s old and started wth Galbrath s (1952) hypothess on countervalng power 6 assertng that frms wll develop economc power on one sde of the market n order to counterval the market power exercsed by frms on the other sde of the market. Galbrath uses examples such as trade unons (developed to counterval power of employers), and cooperatves (to counterval power of buyers of farm products). Also, the retal chans were created, accordng to Galbrath, n order to counterval the power exercsed by supplers and hence to reduce prces pad to wholesalers and processors. The welfare mplcatons of the countervalng power hypothess are however somewhat controversal, snce a revew of the lterature suggests that the results depend on market structure. There are two effects of countervalng power wth opposte effects on consumer welfare: a potental consumer prce decrease and a reducton on product varety. Von Ungern- 4 More and more of the work n Amerca s project orented, wth a begnnng, a mddle and an end. Projects lend themselves to a blend of tradtonal employees, contract workers and consultants, who combne nto teams, do a job and then usually break up, wth most of the players lookng for ther next gg. Flyng Solo: Hgh Tech Nomads Wrte New Program for Future of Work, The Wall Street Journal, August 19, 1996, p. A1. 5 For a recent survey on networks of nnovators see Powell and Grodal (2005) 6...prvate economc power s held n check by the countervalng power of those who are subject to t. The frst begets the second. The long trend towards concentraton of ndvdual enterprse n the hands of a relatvely few frms has brought nto exstence not only strong sellers, as economsts have supposed, but also strong buyers as they fal to see. The two develop together, not n precse step but n such manner that there can be no doubt that the one s n response to the other. (Galbrath, 1952) 10

11 Sternberg (1994) suggests that only f retal competton s strong, a concentraton n ths market wll result n lower consumer prces. Chen (2004) ponts out that a monopolst faced by countervalng power by retalers wll tend to reduce product dversty. The negatve mpact on consumers welfare may domnate the reduced prce effect. Smlarly Inderst and Shaffer (2007) show that horzontal mergers by retalers tend to reduce product varety. Further on, Inderst and Wey (2002) examne how downstream frms wth market power may force supplers nto exclusve contracts and thus reduce ncentves to nnovate. Smlarly Stefanads (1997), shows that potental downstream foreclosure may force upstream manufacturers to wthhold nnovaton actvtes. In a comprehensve study of the European retal sector, Dobson, et. al. (2001) pont to the effect that large retalers may nvolve n a loss leader polcy, where certan products are sold at prces below costs. Ths rases concerns by manufacturers who may refran from nnovaton actvtes fearng that consumers may perceve ther products as beng of lower qualty f they are sold at too low prces. Usng a dfferent (ex ante) chan of logc, Balakrshnan and Wernerfeldt (1986) argue that the rsk of technologcal obsolescence wll curb the frms ncentves to vertcally ntegrate. Wess and Wttcopp (2005) show that n Germany, market power by retalers has negatve effects on food manufacturng frms nnovaton actvty (as measured by number of new products). Most of these studes look exclusvely on downstream power (usually retalers) and do not examne upstream market power (nput supplers). We can expect the effects to be smlar: Hypothess 3: Countervalng power, upstream or downstream, wll decrease nnovaton and product prolferaton. Economes of sze One nterpretaton of the Schumpeteran hypothess s that large frms wll nnovate more than small frms. The overall evdence supports ths hypothess. Scherer (1991) for example, found that 90% of the R&D n the USA was conducted by the 400 largest corporatons. More careful 11

12 measurement of nnovaton, however, casts doubt on the Schumpeteran argument. If one accounts for patents, for partcpaton n research, etc. the evdence tlts towards that there are no economes of scale wth respect to frm sze n the nventon process (Kamen and Schwartz, 1985, p.3). More careful analyses show a u-shaped effect, where medum-szed frms tend to be more effcent nnovators (Kamen and Schwartz, 1985; Manfeld, 1963). More recent studes also fnd evdence that small- and medum-sze frms place a lot of effort on nnovaton (Rothwell, 1989; Grunert, et. al. 1997; Avermaete, et. al., 2004; Rothwell (1989). The effect of frm sze on nnovaton s therefore one relatonshp that needs to be nvestgated further: Hypothess 4: Innovaton and product prolferaton are expected to be hgher for md-szed frms. Exports Innovaton and exports s of great nterest to economc research. Some trade theorsts (Krugman, 1979; Vernon, 1966) attrbute exports to nnovatve behavour of frms. At the frm level, however, the export orentaton of nnovatve frms s ambguous n the lterature. Some fnd a postve relatonshp (e.g. Oszek and Taymaz (2004); Basle (2001); Lachenmaer and Wosmann, 2006)) whle others fnd that non-nnovatve frms may export more (e.g. Wakeln, 1998), or that no sgnfcant dfferences exst per se (Bleaney and Wakeln, 2002; Gerosk, 1990). Consequently, we formalze the followng hypothess: Hypothess 5: Export-orented frms tend to nnovate more and have a wder range of products.. Innovaton and product prolferaton n the agr-food ndustry Several studes have dealt wth nnovaton n the food ndustry. In a comprehensve study of the European retal sector, Dobson et. al (2000) argue that ncreased power by retalers may decrease prces but also reduces product varety and nnovaton efforts by agr-food frms. Connor (1981; and Röder, et. al., 2000) study the effect on market structure on nnovaton of agr-food frms n the USA. A strong correlaton between market concentraton and nnovaton s found, although t 12

13 s rather of a U-shape. Also a recent study by the Federal Trade Commsson (FTC, 2000) suggests strong negatve correlaton between market concentraton and nnovaton. The most relevant to our work s a recent study based on a survey of the German food ndustry by Wess and Wttkopp (2005). They fnd that retal power decreases nnovaton by manufacturers, however, ths negatve mpact s mtgated when manufacturers have market power. In ther emprcal model, Wess and Wttkopp (2005) use number of new products ntroduced as an ndcator of nnovaton by the frms. Although n the rght drecton, ths ndcator may be measurng product prolferaton rather than product nnovaton. As we ndcate above, ths may lead to a certan bas. None of the studes we have revewed has looked exclusvely on the mportance of vertcal ntegraton on nnovaton. Also, n our vew, the fact that these studes measure nnovaton as number of new products ntroduced, may be based. We deal wth both these ssues n our paper. Contrbuton Hence, we am to contrbute to the lterature n three dstnct ways: Frst, we test for the mportance of vertcal ntegraton for nnovaton. Whle there exst several studes on ths lnkage, to our knowledge, ths s the frst that deals wth the agr-food ndustry. Secondly, by usng two dfferent emprcal models wth two dfferent dependent varables (number of new products ntroduced and nvestment on nnovaton) we examne both product prolferaton and nnovaton. To our knowledge, there are no other studes that examne both aspects usng the same data set. Fnally, t s the frst study that examnes the effects of vertcal ntegraton on nnovaton and product prolferaton for the agr-food ndustry n a comprehensve and analytcal way. 13

14 3. METHODOLOGY Data The data set used n the followng analyss s based on a survey of 444 food ndustry frms n Denmark (see Baker, 2006). The survey questonnare addressed several elements of the frms organzaton, strategy and behavour wth respect to the year 2000 and The ntervew-based survey was conducted between November 2005 and March 2006 resultng n 131 vald responses (.e. about 30% response rate and a total sample of 262 observatons). Descrptve statstcs for the data set employed n the models are shown n Table 1. There has been substantal consoldaton n the Dansh food sector n the perod (Baker, 2003). The reducton n number of food processng frms has been much faster n Denmark than n other parts of Europe. Smlarly the reducton n wholesale frms n the food ndustry has reduced faster n Denmark than most other EU countres. In terms of concentraton the Dansh food sector s smlar to other parts of Europe. Denmark has CR5 of about 56% whle the CR4 n the US s about 27% at the natonal level. However, when buyng power s consdered the Dansh effectve CR s around 70% whch s representatve for the rest of the EU. One strong trend that has occurred n the Dansh food marketng chans s the ncrease n the share of the wholesale market controlled by non-specalzed stores. Ths trend s apparent n most EU countres, but Denmark shows the largest ncrease. In contrast the US has shown a strong ncrease n all types of food retalng outlets. The Dansh economy has been rated as one of the most nnovatve n the world by agences lke the World Economc Forum (2007). Agrculture and food make up a sgnfcant porton of the Dansh economy whch leads us to the expectaton that the food sector yelds robust conclusons on our tests for nnovatve actvty. <TABLE 1 HERE> 14

15 Modellng and Estmaton To generate emprcal evdence on the above stated hypotheses we formulate and estmate two dfferent regresson models dependng on the choce of the dependent varable: Model I. Number of new products (np t ); Model II: Investments on nnovaton as percentage of total sales (rexpnno t ). They are presented analytcally below. Model I: Number of Products Innovated (np t ) - A Bootstrapped Zero Inflated Posson Regresson (ZIP) We frst consder the number of new products launched by the frm as an ndcator for the level of nnovaton. Although, as dscussed earler, the number of new products as a proxy for nnovaton has several shortcomngs, by the use of ths measure we wll be able to compare the results wth other smlar studes as well as to examne the determnants of product prolferaton. The number of products ntroduced by frm at tme t - np - s used as a proxy for the relatve t nnovaton behavour of the frms n the sample. By defnton ths varable s censored by zero. Ths varable exhbts features smlar to count data suggestng the use of a Posson dstrbuton to model ts varaton. The latter s wdely used to descrbe models for count datasets, however, s often found to provde an nadequate ft due to the presence of many zeros n the data set. Ths s the case for the data set used n ths study where more than 30% of the observatons take the value zero for np mplyng no product nnovated at all. To account for such excessve zeros n a dscrete t count varable, a zero-nflated Posson dstrbuton (ZIP) has been suggested n the lterature (Lambert, 1992; Greene, 1994). A ZIP dstrbuton s a mxture of a standard Posson dstrbuton and a degenerated dstrbuton at zero, wth a mxng probablty p. The dependent dscrete count response varable np follows a zero-nflated Posson dstrbuton descrbed by t 15

16 ψ + (1 ψ )exp( µ ) np = 0 np Pr( np,, ) t x µ ψ = exp( µ ) µ [1] (1 ψ ) np > 0 np! Falure to account for the extra zeros may result n based parameter estmates and msleadng nferences. By applyng a ZIP regresson model based on [1] we modfy the mean structure to ncrease the condtonal varance and the probablty of zero count. By addng the lnk functons ln( µ ) = x ' β [2] and ψ logt( ψ ) = ln = x ' γ [3] 1 ψ where β and γ represent the coeffcent vectors of the covarates x ' servng as the log functon of the mean µ and the logt functon of the probablty ψ nstead. The jont log-lkelhood functon for the ZIP regresson s gven by n = 1 ' ' { } L( β, γ np, x ) = 1( y = 0)ln exp( x γ ) + exp[ exp( x β )] + n n ' ' ' y = y + = 1 = 1 [1 1( 0)][ x γ exp( x β )] ln[1 exp( x γ )] [4] where 1( y = 0) s a functon takng the value 1 as y = 0 and 0 otherwse. [4] s estmated by a maxmum lkelhood procedure. The fnal estmaton model specfcaton s gven by np = (exp( β + β sales + β sales + β sales + β pc exp + β emplun + β nosell t 0 1 t 2 t 3 t 4 t 5 t 6 t + β nobuy 75 + β pcconraw + β pcconrawth + β pcconsret + β pcconsws 7 t 8 t 9 t 10 t 11 t + β ownup + β owndown + β ownbyup + β15ownbydown + β16stageret 12 t 13 t 14 t t t + β stagews + β sec frveg + β sec pork + β sec dary + u )) /((1+ exp( γ + γ sales 2 17 t 18 t 19 t 20 t t γ sales γ nosell 75 γ nobuy 75 γ pcconraw γ pcconrawth t + 3 t + 4 t + 5 t + 6 t γ ownup + γ sec frveg + γ sec pork + γ sec dary + u )) 8 t 9 t 10 t 11 t 2 γ pcconsret t [5] where denotes the observaton, t = 2000, 2005; pcexp refers to the percentage of sales orgnatng from exports, emplun s the percentage of employees wth unversty degree, nosell75 as the number of frms sellng 75% of all food-based nputs to the frm, nobuy75 as the number of frms 16

17 buyng 75% of all food-based sales from the frm, pcconraw refers to percentage of raw materals covered by contracts, pcconrawth as the percentage of other nputs covered by contracts, pcconsret as the percentage of sales to retalers covered by contracts, pcconsws as percentage of sales to wholesalers covered by contracts, ownup denotes f the frm has ownershp n frms up the chan, owndown denotes f the frm has ownershp n frms down the chan, ownbyup refers to f the frm s owned by frms up the chan, ownbydown refers to f the frm s owned by frms down the chan, stageret measures the effect of the frm belongng to the retal stage, stagews measures the effect of the frm belongng to the wholesale stage, and secfrveg, secpork, secdary denotes f the frm produces frut and vegetables, pork, or dary products. Asssumng that the over dsperson of zeros does not arse from heterogenety n the data set but from the nature of the frms nnovaton decsons, we have to test for whether there s a regme splttng mechansm at work or not (Greene, 1994). Hence, we use the test statstc developed by Vuong (1989) for non-nested models based on the assumpton that the alternatve dstrbuton (here: f ( ) 2 np x as the standard Posson model) can be specfed and ( 1 x 2 x ) m log f ( np x ) / f ( np x ) wth f 1 as the null hypothess dstrbuton descrbed by [1] = v n 1 m 1 = n n m m n n 2 / ( ) = 1 [6] = 1 testng for E [ m ] equals zero, omttng t for smplcty and usng the fact that v has a lmtng standard normal dstrbuton. To test further for small-sample bas we nvestgate the robustness of our estmates obtaned by [5] by applyng a smple stochastc re-samplng procedure based on bootstrappng technques (see Efron and Tbshran 1993). Ths seems to be necessary as our data set conssts of a (rather) lmted number of observatons and tme unts. If we suppose that ˆω s an estmator of the parameter vector ω ncludng all parameters β, γ obtaned by estmatng [5] based on our orgnal observatons X, then we are able to approxmate the statstcal propertes of ˆω by 17

18 studyng a sample of C = 1000 bootstrap estmators ω ˆ ( c), c= 1,..., C. These are obtaned by resamplng wth replacement from X and re-computng ˆω by usng each generated sample. The fnal samplng characterstcs of our vector of parameters s obtaned from k ωˆ ωˆ ω ˆ [7] = (1) k,..., (1000) k As s extensvely dscussed by Horowtz (2001) or Efron and Tbshran (1993), the bas of the bootstrap as an estmator of ω ˆ k, B ω ˆ = ω% k ω ˆ kn, s tself a feasble estmator of the bas of the asymptotc estmator of the true populaton parameter ω k. 7 Ths holds also for the standard devaton of the bootstrapped emprcal dstrbuton provdng a natural estmator of the standard error for each ntal parameter estmate. By usng a bas corrected bootstrap we am to reduce the lkely small sample bas n the ntal estmates. To examne the valdty of the fnal model specfcaton we fnally test for a jont as well as a group wse nsgnfcance of the parameters n [5] by a generalzed lkelhood rato testng procedure. Further dagnoss tests were conducted to test for possble seral correlaton (followng Wooldrdge, 2002) as well as heteroscedastcty (followng Whte, 1980). Both were rejected. Model II: Investments on nnovaton as percentage of total sales (rexpnno t ) - A Robust Heckman Sample Selecton Model As suggested earler, new products may over- or under-estmate nnovaton actvtes by frms. Agr-food frms nnovaton behavour can be further approxmated by the decson to nvest n nnovaton at all (.e. the partcpaton decson) as well as the relatve amount of expenses devoted to nnovaton n a partcular perod of tme (.e. the expendture decson). Accordngly, only a subsample of frms are able to report nnovaton expendtures. It s lkely that the sectoral and organzatonal characterstcs of the frms engaged n nnovaton are dfferent from those not 7 Hence the bas-corrected estmator of ω can be computed by k ωˆ % = 2ωˆ ω %. kn B ω 18

19 engaged n nnovaton. Unobservable characterstcs affectng the decson to nvest n nnovaton are correlated wth the unobservable characterstcs affectng nnovaton expendture. Selectvty bas would be the case, therefore, f we were to draw nferences about the determnants of nnovaton expendtures for all agr-food frms based on the observed expendtures of the subset whch s engaged n nnovaton. Heckman s sample selecton model copes wth such a selecton problem by assumng that the frms make two decsons wth regard to nvestng n nnovaton, each of whch s determned by a dfferent set of explanatory varables (see Heckman, 1979). Hence, t s based on two latent dependent varables models, where the nnovaton expendture decson s descrbed as rexpnno * t = β'x + u [8] t 1 wth rexpnno as the amount of total expendtures spend on nnovaton (as % of total sales) and the nnovaton nvestment decson as nno * t = γ'z + u [9] t 2 where nno s a bnary varable takng the value 1 as the frm decdes to nvest n nnovaton, and the value 0 otherwse. Where x and z are vectors of regressors, possbly contanng common components ncludng ntercepts, and the errors u 1 and u 2 are condtonal on x and y and are jontly bvarate normally dstrbuted wth zero mean. The model n [8] s only observable f the observed dependent varable s nno * t > 0 and rexpnno = rexpnno f nno > 0 rexpnno * * t t t t = * mssng value f nnot = 0 [10] and hence, z s observable f rexpnno t s a mssng value and x s observable f rexpnnot s. Asymptotcally effcent estmators of [8] and [9] are obtaned by maxmzng the log-lkelhood functon 19

20 [ γ z ] ln (,,,, ρ, σ ) + ln Φ( ' ) (,, ρ, σ ) = n D h Y x z β γ D Lβ γ = 1 + (1 + D ) ln[ 1 Φ( γ ' z )] [11] where D s defned as a dummy varable takng the value 0 f rexpnno t s a mssng value and the value 1 f not, Φ s the cumulatve dstrbuton functon of the standard normal dstrbuton, σ as the standard error of u 1, ρ as the correlaton between u 1 and u 2, h denotes the condtonal densty of rexpnno gven nno > 0, x and z (see also Berens, 2002). The fnal estmaton model t t specfcaton s gven by * rexpnno = β + β pc exp + β emplun + β ownup + β owndown + β ownbyup + β ownbydown t 0 1 t 2 t 3 t 4 t 5 t 6 t + β stagews * owndown + β stagews * ownup + β pcconraw * ownup + β 7 t t 8 t t 9 t t 10 pcconraw * owndown + β pcconrawth * ownup + β pcconrawth * owndown t t 11 t t 12 t t + β pcconsret * ownup + β pcconsret * owndown + β pcconsret * ownbyup 13 t t 14 t t 15 t t + β pcconsret * ownbydown + β pcconsws * ownup + β pcconsws * owndown + u 16 t t 17 t t 18 t t 1t * 2 3 nno = γ + γ sales + γ sales + γ sales + γ empl + γ stageproc + γ stagews t 0 1 t 2 t 3 t 4 t 5 t 6 t + γ stagengr + u 7 t 2t where denotes the observaton, t = 2000, 2005; stageproc measures the effect of the frm belongng to the processng stage, stagengr measures the effect of the frm belongng to the ngredents stage, and the rest of the varables are defned as outlned above. We further use cross term varables to explan the varaton n the level of nnovaton expendtures by takng nto account the cross effects between dfferent aspects of organzatonal ntegraton (.e. contractual and ownershp). To address the lkely problem of small sample bas as well as heteroscedastcty because of survey data we estmate the robust covarance matrx usng the Huber-Whte sandwch estmator (see Huber, 1967 and Whte, 1980). The latter provdes consstent estmates of the covarance matrx for parameter estmates even when the ftted parametrc model fals to hold [12] 20

21 because of msspecfcaton or volaton of the error related assumptons. 8 Puhan (2000) showed that the full-nformaton ML estmaton of the Heckman selecton model s preferable n the case where collnearty problems are absent. Despte several cross varables terms used n the model, the auxlary regressons performed showed no severe collnearty n the explanatory varables. To examne the valdty of the fnal model specfcaton we test for a group wse nsgnfcance of the parameters n [5] by a generalzed lkelhood rato testng procedure. Fnally a Wald test of ndependence s used to obtan evdence on the accuracy of the specfcaton based on dependent equatons, as well as varous dagnostc tests were conducted to test for possble seral correlaton (followng Wooldrdge, 2002) as well as heteroscedastcty (followng Whte, 1980). 4. RESULTS Tables 2 to 3 summarze the results for the estmated models. The dagnostc tests conducted ndcate no severe seral correlaton, no rejecton of the normalty hypothess wth respect to the resduals, and a rejecton of the hypothess of model msspecfcaton at the 1% level of sgnfcance for all models: the Vuong test statstc rejects a standard Posson model specfcaton n favor of the ZIP specfcaton (model 1), and the Wald test statstc rejects the specfcaton based on ndependent probt and tobt models n favor of the chosen Heckman selecton specfcaton (model 2). All models estmated show a satsfactory overall model sgnfcance, gven the modest sample sze and the use of survey data (see adjusted McFadden s R 2 values, the Maxmum Lkelhood R 2 s, and the McKelvey/Zavona s R 2 values). These conclusons are backed up by the bootstrapped bascorrected standard errors as well as the robust estmaton technque appled for the Heckman selecton specfcaton whch confrm the robustness of the varous estmates. The conducted lnear 8 Here the estmate s calculated as the product of three matrces: the matrx formed by takng the outer product of the observatonlevel lkelhood/pseudolkelhood score vectors s used as the mddle of these matrces, and ths matrx s n turn pre- and postmultpled by the usual model-based varance matrx (see n detal e.g. Greene, 2000). 21

22 hypotheses tests wth respect to the sgnfcance of the explanatory varables composton fnally ndcate the relevance of sze related effects, employee based factors, ntegraton relevant effects (.e. contractual and ownershp based), as well as retal and wholesale stage related factors for all three specfcatons (see lnear hypotheses tests performed). Both models verfy the basc hypothess (Hypothess 1) put forward n ths paper: Vertcal ntegraton s a sgnfcant determnant of nnovaton. Specfcally, n both models, the organzaton varables related to vertcal ntegraton and contractual characterstcs are sgnfcant and wth the expected sgn (see tables 2 and 3). We dscuss each hypothess below. <TABLE 2> <TABLE 3> Hypothess 1. Vertcal ntegraton. The coeffcents for both ownershp upstream and downstream varables are postve and sgnfcant. Frms that ndcated that they have some degree of vertcal ntegraton tend to nnovate more. The drecton of ntegraton does not matter n general, both upstream and down-stream ntegraton tend to ncrease nnovaton and product prolferaton. However, downstream ntegraton s more mportant than upstream. In Model I, Ownershp Downstream shows a larger coeffcent than Ownershp Upstream (0.964 versus 0.621). Whereas Owned by Upstream shows a larger effect (2.014 versus 0.705). In Model II, Ownershp Downstream and Owned by Downstream are both more sgnfcant than ther Upstream counterparts. It s more mportant that the nnovatng frm owns another frm upstream or downstream, than f another frm has shares n t. Ownershp of another frm (both upstream and downstream) s sgnfcant and by a large order of magntude more mportant than Owned By (Owned by upstream s not sgnfcant). 22

23 Hypothess 2. Networks (proxed by contracts) play also an mportant role n nnovaton actvty. In Model I the three contract varables used (purchase contracts for raw materals and other nputs; sales contracts to retalers) were sgnfcant and wth postve sgn. In Model II, the effect of contractual relatons are combned wth vertcal ownershp: buyng contracts of raw materals or other nputs combned wth vertcal ntegraton (upstream or downstream). All but two coeffcents were sgnfcant and postve. Hypothess 3. Countervalng power. Ths s captured by the number of frms sellng to- or buyng from- the frm more than 75% of the frm s nputs or fnal product respectvely. The larger the number of frms the lower the degree of countervalng power. These varables (one for upstream and one for downstream) was sgnfcant only n the frst equaton (number of new products). The larger the number of frms that the frm deals wth, the larger the number of new products the frm tends to ntroduce. It ndcates, thus, that countervalng power may have detrmental effects on the ntroducton of new products by frms, snce the number of new products ntroduced ncreases wth the number of frms that the frm buys from, or sells to. One should pont out, however, that the number of frms s a weak proxy of market power, snce concentraton s very mportant. Snce we do not exclusvely use concentraton rato, or other measures of market power, we should vew ths result wth cauton. One possble nterpretaton of the result s ths: Frms who sell to a large number of frms may have to dfferentate ther product n order to cater to each customer s needs. Therefore, large number of frms downstream may ncrease the demand for a large number of products. On the other hand, f a frm tends to ntroduce a large number (and varety) of new products t may need a large varety of nputs, hence the need to procure from large number of nput supplers (large number of frms upstream). 23

24 Hypothess 4. Economes of sze. Sze appears sgnfcant n both equatons n Model I. Both the squared and cubc terms are postve and sgnfcant, ndcatng that product prolferaton has strong economes of sze. Larger frms wll supply a wder range of products. In Model II, however, sze s only sgnfcant n the selecton equaton, wth the squared term negatve and sgnfcant. None of the sze varables were sgnfcant n the Logt equaton. Ths s a weak ndcaton of a U-shaped effect, ndcatng that md-szed frms may be more lkely to nnovate as found elsewhere n the lterature (Kamen and Schwartz, 1985; Manfeld, 1963; Rothwell, 1989; Grunert, et. al. 1997; Avermaete, et. al., 2004). Hypothess 5. Export orentaton. Frms wth export orentaton tend to nnovate more as the varable pct Sales From Exports s sgnfcant and postve n both models. Our results tends to agree wth that of trade theorst s (Krugman, 1979; Vernon, 1966), and emprcal results from other ndustres (Oszek and Taymaz (2004); Basle (2001); Lachenmaer and Wosmann, 2006). Hypothess 6. Sectoral and stage varables. We ntroduced several sectoral and stage dummes to control for sectoral and stage effects on nnovaton. The results are not consstent between the two models. In Model I, the Fruts and vegetables Sector has a postve sgn, whereas pork and dary are negatve. Recall that the dependent varable n ths model s Number of New Products, and t ndcates that t s more dffcult for pork and dary frms to ntroduce new products compared to fruts and vegetables. None of the sectoral dummes were sgnfcant n Model II. Ths s perhaps due to the fact that all frms n the sample are from the same ndustry (agr-food) ndcatng that they are all affected by smlar overall market structure and ndustry regulaton and they all have access and draw from the same pool of technologcal and scentfc knowledge (Kamen and Schwartz 1984). The stage dummes, however, ndcate that both wholesaler and retaler frms are more lkely to ntroduce new products (Model I). Ths s an nterestng result. Here, we most lkely measure 24

25 product prolferaton, rather than nnovaton. The results n Model II ndcate that frms n the processng, wholesale and ngredents stages of the chan, wll tend to nvest more n nnovaton, as expected. 5. CONCLUSIONS We have used a unque data set based on an extensve survey of more that 400 Dansh agrfood frms and analyzed what determnes nnovaton actvtes of these frms. Specfcally, we were nterested to see the effects of organzaton, vertcal ntegraton, contractual and other network agreements. We also tested for the effects of other varables, such as market power, sze, and stage n the chan. We used two dfferent measures of nnovaton and appled two dfferent models. Frst, we used as a dependent varable the number of new products ntroduced and used a ZIP model to estmate the mpacts of the hypotheszed varables. Second, we used nvestment on R&D as a proxy for nnovaton nput and used a Heckman sample selecton model. Both models performed reasonably well and although there were slght dfferences n the varables that turned out to be sgnfcant between the two models, the results were farly consstent for the man hypotheses. The frst and most sgnfcant result s that organzaton matters. Vertcal ntegraton as well as contractual arrangements were sgnfcant for both models. Both upstream and downstream ownershp (vertcal ntegraton) were sgnfcant, however, ownershp by an upstream frm had a larger effect on nnovaton than ownershp by downstream frms. Also, t was more mportant to own a frm than to be owned by one. Contractual arrangements had postve effects on nnovaton for both models. Other hypotheses concerned the effect of market power. The degree of countervalng market power upstream or downstream s sgnfcant and has detrmental effects for a frm s nnovaton actvty. Economes of sze seem to play an mportant role and t was sgnfcant n both equatons. Smlarly, the export orentaton of the frm was a sgnfcant determnant of 25

26 nnovaton. Whereas the sector was not sgnfcant n any of the equatons, the stage n the chan was mportant. Wholesalers and retalers tend to have a larger number of new products (Model I), whereas manufacturng frms tend to nvest more n R&D (Model II). In general, the results of ths research were satsfactory. We confrmed the hypotheses that organzaton, sze and market power are mportant determnants of nnovaton. REFERENCES xxx 26

27 Table 1 Descrptve Statstcs Varable Mean Stdev Mn Max n u m b e r o f n e w p r o d u c t s n t r o d u c e d ( n ) nvestment n R&D and/or product nnovaton (1 - yes, 0 - no) expendture on R&D and product nnovaton (mll DKK) relatve share of expendtures for R&D and product nnovaton (%) sales (mll DKK) number of employees (n) sales per employee (mll DKK) percentage of employees wth unversty degree (%) foregn drect nvestment n the frm (1 - yes, 0 - no) percentage of sales orgnatng from exports (%) percentage of raw materals covered by contracts (%) percentage of other nputs covered by contracts (%) percentage of sales to retalers covered by contracts (%) percentage of sales to wholesalers covered by contracts (%) ownershp upstream (1 - yes, 0 no) ownershp downstream (1 - yes, 0 - no) owned by upstream (1 - yes, 0 - no) owned by downstream (1 - yes, 0 - no) stage of prmary (1 - yes, 0 - no) stage of wholesaler (1 - yes, 0 - no) stage of retaler (1 - yes, 0 - no) stage of processor (1 - yes, 0 - no) stage of ngredents (1 - yes, 0 - no) Sector of the feedng ndustry (1 - yes, 0 - no) Sector of the beef ndustry (1 - yes, 0 - no) Sector of the frut and vegetables ndustry (1 - yes, 0 - no) Sector of the pork ndustry (1 - yes, 0 - no) Sector of the dary ndustry (1 - yes, 0 - no) Sector of the poultry ndustry (1 - yes, 0 - no) Sector of the meat ndustry (1 - yes, 0 - no) Sector unspecfed (1 - yes, 0 - no) number of frms sellng 75% of all food-based nputs to the frm (n) number of frms buyng 75% of all food-based sales from the frm (n) Note: all monetary values have been deflated to the base year 2000 usng the general producer prce ndex (sources: Danmark Statstc). 27

28 Table 2 Bootstrapped ZIP Regresson Estmates (n = 132) Independents coeffcent 1 z-value zp model - posson Dependent: Number of Products Innovated bas-corrected standard error 95% confdence nterval sales 1.28e-03*** 7.63 [1.37e-04; 1.88e-04] sales e-07*** 3.04 [8.78e-08; 1.16e-07] sales e-12*** [1.83e-12; 2.41e-12] pct of sales from exports 0.032*** [9.37e-04; 1.72e-03] pct of employees wth unversty educaton -7.51e-03** [1.43e-03; 2.64e-03] number of frms sellng 75% of all food-based nputs to the frm 5.25e-03*** 5.31 [6.36e-04; 2.66e-03] number of frms buyng 75% of all food-based sales from the frm 1.02e-05*** 7.29 [1.03e-06; 1.77e-06] pct of purchases of raw materals covered by contracts 8.67e-03*** [6.18e-04; 1.07e-03] pct of purchases of other nputs covered by contracts 6.43e-03*** 7.12 [7.16e-04; 9.98e-04] pct of sales to retalers covered by contracts 8.67e-03*** 7.03 [9.13e-04; ] pct of sales to wholesalers covered by contracts 2.55e-04* 0.23 [8.54e-04; 1.20e-03] ownershp upstream 0.621*** 2.66 [0.01; 0.35] ownershp downstream 0.964*** [0.06; 0.10] owned by upstream 2.014*** [0.32; 0.65] owned by downstream 0.705*** [0.04; 0.07] stage of the wholesaler 2.122*** [0.06; 0.12] stage of the retaler 0.539** 2.14 [0.17; 2.57] sector of the frut and vegetables ndustry 0.638*** 4.82 [0.09; 0.18] sector of the pork ndustry *** [2.07; 3.41] sector of the dary ndustry *** [0.07; 0.11] constant 1.679*** [0.08; 0.14] nflaton model - logt sales e-06** 1.89 [ ;1.01e-05] sales e-10** 1.89 [2.97e-11; 5.77e-10] number of frms sellng 75% of all food-based nputs to the frm 0.05*** 2.63 [0.07; 0.04] number of frms buyng 75% of all food-based sales from the frm 0.01*** 2.74 [0.009; 0.011] pct of purchases of raw materals covered by contracts 0.03*** 3.06 [6.35e-03; 0.06] pct of purchases of other nputs covered by contracts 0.02* 1.61 [0.008; 0.016] pct of sales to retalers covered by contracts 0.04*** 3.01 [6.57e-03; 0.04] ownershp upstream 4.08*** 2.40 [1.56; 4.54] sector of the frut and vegetables ndustry 4.33*** 2.84 [3.44; 5.83] sector of the dary ndustry -3.13*** [0.52; 4.37] constant *** [0.18; 0.23] logll AIC zero observatons / non-zero observatons 41/91 Adj. McFadden s R Vuong test of zp vs. standard Posson 2.34*** (standard rejected) Maxmum Lkelhood R Wooldrdge test LR ch 2 (1) (H 0 : no seral correlaton) (not rejected) LR ch 2 (20) *** Whte s test ch 2 (110) (H 0 : homoscedastc errors) (not rejected) Bootstrap Replcatons 1000 lnear hypotheses tests on model specfcaton (ch 2 (x)) - zp specfcaton H 0 : sze related varables have no sgnfcant effect (ch 2 (2)) H 0 : contract related varables have no sgnfcant effect (ch 2 (4)) H 0 : ownershp related varables have no sgnfcant effect (ch 2 (4)) H 0 : retal stage related varables have no sgnfcant effect (ch 2 (2)) H 0 : wholesale stage related varables have no sgnfcant effect (ch 2 (2)) *** (rejected) *** (rejected) *** (rejected) 54.89*** ( rejected) *** (rejected) 1: * - 10%-, ** - 5%-, *** - 1%-level of sgnfcance. 28