Productivity in EU agriculture - slowly but steadily growing

Transcription

1 EU Agrcultural Markets Brefs No 1 December 216 Productvty n EU agrculture - slowly but steadly growng Contents 1. Introducton 2. Why montorng productvty growth? 3. What s TFP? 4. TFP growth n the EU 5. Comparng growth and level 6. Factors explanng TFP growth Agrcultural productvty has ganed renewed nterest. Productvty growth has enabled food to become less scarce (and hence cheaper) n the 2 th Century. One ueston s whether t can do so agan n the 21 st Century, as ths s seen as one prereuste to meet the challenge of feedng more than 9 bllon people by 25, by achevng more wth less. Agrculture and the envronment wthn whch t operates can dffer substantally between Member States. Thus the ueston about how productve agrculture s and how to breach the gap between those laggng behnd and the frontrunners remans pertnent. In ths Bref, we analyse how productvty, as measured by Total Factor Productvty (TFP) growth, evolved n the EU-28 and n the Member States, and dentfy the dfferent drvers assocated wth t. 7. MS wth dfferent growth 8. TFP n the world 9. Some caveats 1. Conclusons Annex Methodology Fotola EU Agrcultural Markets Brefs are avalable on Europa: Agrculture and Rural Development

2 1. Introducton For a number of reasons, agrcultural productvty ncrease has ganed renewed nterest. Productvty growth has enabled food to become less scarce (and hence cheaper) n the 2 th Century. The ueston s whether t can do so agan n the 21 st Century. The pressure on our agrcultural resource base has ncreased, due to growng food and ndustral demand drven by demographc and dsposable ncome changes. On the supply sde there s growng competton from outsde agrculture for the same producton factors (land, labour, captal). The European Commsson has launched an ambtous program towards a resource effcent Europe n 22. As a conseuence, the agrcultural sector s challenged to acheve more wth less. Whle there s a general belef n the progress of technology to mprove resource effcency, ths s challengng n agrculture, as workng wth lvng organsms n outsde condtons ntroduces varablty and lmts to growth. To montor progress made towards hgher productvty, whch ndcates an mproved output over nput rato, Total Factor Productvty (TFP) offers an nterestng startng pont. After ntroducng the TFPndex and ts potental use, ths bref nvestgates the TFP-scores for the EU as a whole and ts dfferent Member States from 1995 onwards and tres to explan some of the man trends. The bref ends wth some key lessons from Member States or perods wth growng or declnng TFP measurement. 2. Why montorng productvty growth? Whle n the past man gans s agrcultural output were acheved by ncreasng resource ntensty (more land, captal and ntermedary nputs brought nto producton), the last decades productvty ncrease has led producton growth, allowng for the savng of resources whle output grew further. The ncrease n agrcultural productvty allowed for a sustaned decrease n real agrcultural prces, and hence food prces, contrbutng to a decreasng share of food n the overall consumer expenses. Productvty growth s of nterest as t s often argued that our world s shftng from demand constraned to supply constraned. One of the reasons mentoned for the recent food prce spkes was the nablty of supply to keep up wth demand growth. Demand s growng due to populaton ncrease, ncreases n GDP and hence dsposable ncome and the gradual shft towards the Western, more proten rch det. FAO projects a necessary 6% ncrease n food producton by 25 to feed our growng and more demandng populaton. At the supply sde, further area growth s constrant by competton from other users (afforestaton, urbansaton, lesure, nfrastructure etc.), whle also polluton and eroson are puttng a brake on the avalable land. Lkewse, other agrcultural nputs experence ncreasng competton, become more scarce and are subject to envronmental and clmate constrants. Therefore, the majorty of the reured ncrease should be reached by productvty growth. At the same tme, envronmental sustanablty concerns, clmate change (and the possble contrbuton of agrculture to ts mtgaton), as well as competton wth other economc actvtes for scarce resources, are expected to lmt the potental to further accelerate productvty growth. There are already frst sgns of productvty growth slowng down n some hghly productve regons. Montorng productvty growth s of nterest as t s seen as the man answer to cope wth the challenge of feedng the world sustanably, but t s at the same tme affected by the challenges posed by t. 3. What s TFP? TFP s the man ndcator to measure changes n productvty, as t s consdered more encompassng than partal productvty ndcators such as labour or land productvty. TFP 1 growth can be defned as the rato between the change n producton volumes over a consdered perod and the correspondng change n nputs (or factors) used to produce them and hence measures the growth n productvty over a gven tme span. An ncrease n TFP reflects a gan n output uantty whch s not orgnatng from an ncrease n nput use. TFP reveals the jont effects of many factors ncludng new technologes, effcency gans, economes of scale, manageral skll, and changes n the organzaton of producton. Graph 1 shows possble pathways to mprove productvty. One way s to shft the producton fronter upwards by mplementng new technologes (movng from f to f'). Another way s to ncrease the techncal effcency by better applyng exstng technologes (catchng-up 1 OECD refers to MultFactor Productvty (MFP) acknowledgng that not all nput factors (nor all type of outputs) are accounted for n the calculaton Productvty n EU agrculture 2

3 22 through better management, gong from A to B). Economes of scale refer to optmzng the scale of operatons to acheve a better output over nput rato (from B to C). Graph 1 Pathways for productvty growth Source: Latruffe () There s much debate n the scentfc communty on how to measure productvty and effcency, as ths poses major challenges both from a methodologcal and data avalablty perspectve. Man dstncton can be drawn between the ndex methods based on agrcultural economc accounts and the fronter-based methods whch explctly take the appled producton technologes nto account. As ths bref attempts a frst exploraton of TFP-measurement for the EU and ts Member States, the ndex methods are best suted, gven ther relatvely straghtforward calculaton procedure and the absence of assumptons on appled technologes, whch could dffer substantally between regons and sectors, as well as over tme. Ths Bref makes use of the Fsher-ndex of TFP, whch combnes both the Laspeyres and the Paasche Indces. As both output and nputs are expressed n term of volume ndces, the ndcator measures TFP growth. The change n producton and nput volumes s measured over a defned perod (=). To aggregate the dfferent output (and nput) volume ndces, the producton (and nput) values are used as weghts. Ths allows capturng the relatve mportance between output or nput. More nformaton on the calculaton of TFP and data necessty can be found n annex 1. TFP s one of the three mpact ndcators 2 for the general CAP objectve of promotng a vable food 2 Quantty of outputs y Commsson Implementng Regulaton (EU) No 834/ of 22 July layng down rules for the applcaton of the common montorng C Economes of scale y/x B A f' f Techncal effcency ncrease Quantty of nputs x Technologcal progress producton. Impact ndcators measure the outcome of an nterventon beyond the mmedate effects. It s also used to evaluate the European Innovaton Partnershp for Agrcultural Productvty and Sustanablty (EIP-Agr 3 ). 4. TFP growth n the EU Productvty n the EU has ncreased over tme, albet at a slower rate n recent years then n the past. Whle the growth rate surpassed 1% per year between 1995 and, t slowed down to around.8% between and. TFP grew wth 9% n compared to (Graph 2). In and TFP growth accelerated, gven the favourable crop condtons boostng crop and anmal producton. manly drven by labour reducton When comparng TFP growth to partal productvty ndcators over the longer run, t becomes clear that labour productvty growth has contrbuted most to productvty gans. Graph TFP and partal productvty growth n the EU-28 (3-year movng average, MA 4 ) TFP Labour Land Captal Int. cons. Output growth has been acheved n a context of a shrnkng workforce. Snce the volume of agrcultural output has ncreased by about 6%, but ths number s ute volatle gven the economc, agronomc and clmatc uncertantes characterzng agrculture. Between and the total workforce n agrculture declned wth about 25% to around 9,6 mllon full tme euvalents, n lne wth and evaluaton framework of the common agrcultural polcy, OJ L 23, 1.8., p Productvty n EU agrculture 3

4 Index (=) the restructurng n the drecton of fewer, but larger farms (Graph 3). Labour has to a large extend been substtuted by captal. Wth captal nvestments ncreasng, productvty per unt of captal decreased (Graph 1Graph 2). Captal productvty shows an overall decreasng trend pror to the fnancal crss, ndcatng that nvestments n machnery, buldngs and alke have played a major role n the realzaton of output growth and the substtuton of labour. Ths s also vsble from the development of captal 5, whch ncreased at an average growth rate of 4% per year pror to the crss to fall back afterwards (Graph 3). As a conseuence, after the fnancal crss captal productvty growth s recoverng, manly lnked to ths slowdown n nvestment growth. Graph Evoluton of labour force and captal formaton n the EU These countres are stll undergong a stronger transton and restructurng compared to the EU-15 Member States. Increased nvestments n farm technology, logstcs, R&D, accompanyng servces and nfrastructure all contrbuted to ths strong growth rate. The access to EU CAP subsdes undoubtedly helped. Rght after accesson and pror to the crss, TFP growth contracted, especally n the EU-N13, due to a major crop falure manly n Romana, Bulgara and Hungary. Ther overall output volume dropped consderably n to recover agan n. Graph TFP-ndex grows faster n the EU-N13 compared to EU-15 (=) labour EU-15 captal EU-15 Source: DG AGRI based on EAA The growth n ntermedate nputs use has remaned largely n lne wth overall output growth, wth the excepton of bad harvest year, whle land productvty growth also mproved, as outputs grew whle utlsed agrcultural area declned by around 5%. and by the EU-N13 labour EU-28 captal EU-28 Both n the EU-15 and the EU-N13 TFP growth has ncreased compared to (Graph 4). Over a longer tme horzon, mportant dfferences are however notceable. Member States whch joned the EU after have gven an mpetus to overall EU TFP growth. 4 To smoothen out the effect of weather varablty, the 3-year movng average TFP s taken. See Annex 2 also for more explanaton. 5 Gross Fxed Captal Formaton EU-15 EU-N13 EU-28 When analysng the TFP annual growth rates pror and post (Table 1), t s remarkable that the hgh growth rate n the EU-N13 s n fact offset by the lower growth rate n EU-15. Although EU-N13 growth rates are relatvely hgh (over 1.6%/y), the share of EU-N13 n overall EU agrcultural output s stll lmted. EU TFP growth therefore remans manly drven by developments n the EU-15. Especally between 1995 and 2 EU-15 experenced mportant gans n productvty, after whch a perod of coolng down started. In terms of productvty growth catchng-up takes place between newer and older Member States. Table 1 TFP annual growth EU % +.6% EU-N % EU % Hgher labour productvty growth s the man reason for TFP ncrease n the EU-N13, at the expense of Productvty n EU agrculture 4

5 Index (=) Bllon EUR 22 captal productvty growth, whch evolved negatvely (Graph 5). Graph 5 Evoluton of total and partal factor productvty n the EU-N13 (3-year MA) Durng the ongong restructurng n the drecton of more technology ntensve and larger farms, labour s substtuted by captal. Between and, the total labour force reduced by 33%, whle total captal use (n volume terms) ncreased by 1%. Total output only ncreased by 5%, explanng the downward path of captal productvty. Graph 6 Evoluton of machnery captal formaton n the EU-13 compared to EU TFP Labour Land Captal Int. cons Graph 6 shows a further strong ncrease n machnery nvestment n the EU-N13 after the drop due to the fnancal crss as compared to stablzaton n the EU- 15. Investments n absolute terms however reman small compared to the EU-15. Wth output growth volatle and close to zero, man gans n the EU-N13 are acheved by nput contracton and substtuton. In TFP growth was slghtly negatve, as opposed to the strong growth n the prevous perods. Ths s due to the combned effect of a drop n output of nearly 8% compared to the prevous year (due to drought) and a temporary stop n labour force declne. Whle labour productvty growth was stll slghtly postve, ts relatve decrease was strongest compared to the other factors. Afterwards, TFP resumed ts growth path as dd the labour outflow. Interestngly, there s a strong correlaton between the growth n ntermedate nput and output volume 6, ndcatng the mportance of nput use for output growth n the EU- N13. Compared to EU-N13, the TFP growth n the EU-15 s lower n the last 1 years (Graph 7). Graph 7 Evoluton of total and partal factor productvty n the EU-15 (3-year MA) TFP Labour Land Captal Int. cons. EU-15 GFCF EU-15 ndex EU-28 ndex EU-N13 GFCF EU-N13 ndex Durng the ongong restructurng n the drecton of more technology ntensve and larger farms, labour s substtuted by captal. Between and, the total labour force reduced by 33%, whle total captal use (n volume terms) ncreased by 1%. Total output only ncreased by 5%, explanng the downward path of captal productvty. Total output grew wth about 16% between 1995 and. TFP growth s also drven by labour productvty gans due to the contnued outflow of workforce. Total workforce reduced wth a steady pace from 7.2 mllon n 1995 to 4.9 mllon n, or an annual reducton of 1.5%. Total captal consumpton showed a more volatle path. In the early nnetes producton grew faster than captal consumpton, wth slght gans n captal productvty as a conseuence, to reverse Productvty n EU agrculture 5

6 kg/ cow year t/ha agan n the years 2 untl the economc crss, after whch captal nflow decreased whle output grew further, mprovng captal productvty once more. The jont realzaton of output ncrease, nput contracton and nput substtuton offer frst ndcatons of a movement along the producton fronter towards a new mx of nputs, whle the hgher growth numbers of the EU-N13 also hnt towards more effcency gans (and hence a movement towards the producton fronter of the EU-15) Comparng growth and level EU-15 EU-N13 Our current TFP methodology does not allow assessng dfferences n productvty level between the dfferent Member States, for that a fronter approach s better suted 7. The strong growth numbers n the EU-N13 can be explaned by effcency gans due to a larger dstance from the technology fronter. The closer to the fronter the more dffcult t s to further mprove. A combned effect of structural change, fnancal ad through the CAP, nvestments and the adopton of technologes wth proven effect from the frontrunners, explans the catchng-up takng place. Partal ndcators help to show the dfference n productvty level. In the EU-15, cereal yelds steadly ncreased from 5 t/ha n 1993 to over 6 t/ha n, wth outlers such as Belgum reachng 9.6 t/ha. The EU-N13 stll lags behnd and reaches only a lttle over 4 t/ha, although also here the gap s closng, especally after (Graph 8). EU-N13 frontrunners Latva and Estona show yeld growth of more than 4% per year between and. Graph 8 Cereal yeld 6 Intermedate nput and output volume follow a smlar volatle growth path, whle the other factors are more on trend 7 Ths comes wth caveats as well On average, the EU-N13 also lags behnd wth respect to mlk yeld (Graph 9), wth a dfference of 2 tonnes per dary cow per year, but annual growth outperforms the EU-15 (1.7% compared to 1.1% between and ). Estona and Czech Republc combne hgh yelds (over 77 kg/cow) wth hgh annual growth rates (4% and 2.6%), whle also Latva and Lthuana have hgh yeld growth (3%/y) startng from a lower base. Pg carcass weght, another partal productvty ndcator, shows decreasng absolute dfferences and a dfferent growth path between the EU-N13 and the EU-15, wth growth slowng down n the EU-15 whle t s acceleratng n the EU-N13 after a perod of stablzaton. Graph 9 Mlk yeld from dary cows EU-15 EU-N13 Graph 1 Pg carcass weght Productvty n EU agrculture 6

7 Poland Germany UK Portugal Ireland Fnland Belgum Austra Sweden Denmark All EU28 France Netherlands Italy Czech Rep. Span Greece Hungary Estona Slovena Lthuana Bulgara Latva Romana Croata Slovaka kg feed/ kg pgmeat Fnland Germany Sweden Luxembourg Austra Slovena Czech Republc Belgum Denmark France Netherlands Unted Kngdom Ireland Croata Poland Italy Portugal Slovaka Estona Span Latva Lthuana Greece Hungary Bulgara Romana kg/head Hungary, Bulgara and especally Romana laggng consderably behnd (Graph 12). Graph 12 Share of holdngs wth a tractor n % % 6% 4% 2% % EU-15 EU-N13 The Feed Converson Rato (Graph 11) also confrms the gap stll exstng between the new and old Member States, wth the new spendng consderably more feed per kg of pgmeat compared to the old, except for Poland, an mportant pg producng country. Not enterng nto the debate of feed composton, Romana, Croata and Slovaka even spent 3 tmes the EU-28 average, so mportant effcency gans can stll be made. Graph 11 Pg feed converson rato n / Also wth respect to nputs and mechansaton dfferences are stll huge, the latter already demonstrated n Durng the ongong restructurng n the drecton of more technology ntensve and larger farms, labour s substtuted by captal. Between and, the total labour force reduced by 33%, whle total captal use (n volume terms) ncreased by 1%. Total output only ncreased by 5%, explanng the downward path of captal productvty. Graph 6. Whle n the EU-15 (especally n the North) on average more than % of the farms possess a tractor, ths s far from the case n the EU-N13, wth Source: FSS A thorough analyss of TFP wthn the FP7 research project Compete 8, based on FADN data and followng a metafronter approach 9 consderng cereal, mlk and pork producton n 24 EU member countres, allows comparng TFP levels between Member States and regons. In lne wth the above, the metafronter analyss showed that despte a perod of almost 1 years after accesson the productvty dfferences n the agrcultural sector among as well as wthn countres are substantal 1. For cereals the lowest TFP level ndexes were estmated for regons n the Unted Kngdom, south France, east Germany, the north Czech Republc, west Austra, central and east Slovaka, Latva and most of regons n Bulgara and Romana. The most productve regons can be especally found n Span, Italy, Germany and Denmark. For mlk, the lowest TFP level ndexes were estmated for regons stuated especally n new Member States (Latva, Slovaka, Romana and Bulgara). The most productve regons can be found n Span, Italy, the Netherlands and Denmark. For pork, most productve regons can be found n Denmark. 6. Factors explanng TFP-growth But what does actually stmulate productvty growth. As explaned n the ntroducton, productvty mprovements can be realzed through applcaton of better technologes and/or more effcent 8 Cechura, L. et al. (). Total Factor Productvty n European Agrcultural Producton. Compete workng paper N9. 9 meanng that one fronter producton technology s estmated for all farms across the EU 1 Unlke us, the authors dd not observe catchng up takng place between the regons. Note that the followed approach and dataset (FADN farms versus EAA) dffer consderably Productvty n EU agrculture 7

8 Annual growth rate ( - ) management, ether techncal, allocatve or scale 11. Some of the factors are at the dscreton of the farm manager and depend on hs/her management sklls, such as some effcency mprovements, whle others go beyond the ndvdual farm manager, such as the natural envronment, the technology development, nvestment n R&D, the advsory system and nfrastructure, avalablty of smlar farms and value chans, appled polcy framework etc. Whle an ndepth analyss of the degree to whch these factors explan changes n TFP s beyond the scope of ths Bref, we do provde some basc nsghts below. Investments n R&D and knowledge sharng The most mportant factor determnng productvty growth n the long run s nnovaton, whch, n turn, s drven by research nvestment. Most studes fnd a sgnfcant postve effect on productvty of nvestments n nnovatve technologes. New technologes such as Bg Data, ether open source or not, Plant breedng technologes, Mult-Actor busness models, precson farmng and alke could shft the technology fronter upwards. In a fronter-based analyss, the adopton of new technologes can be verfed ute straghtforward by an upward shft of the entre producton fronter (see Graph 1). For accountng-based TFP-growth measures such as the Fsher-ndex appled here, ths s not straghtforward. In the FP7 project Compete the analyss revealed techncal change as the most mportant factor contrbutng to TFP development (compared to effcency change). The technologcal change apparently results n labour and land savngs and captal and materal ncreases. The technologcal change where labour s substtuted by captal correspond to general expectatons and s also confrmed when we analyse Member States' partal productvtes. One proxy 12 for the technology development n agrculture could be the Total ntramural R&D expendture on agrcultural scences 13. Fugle and Hesey () estmate the mean rates of return to publc nvestments n agrcultural research rangng from 2 to 6 percent, dependng on the methodology 11 Techncal effcency mprovement refers to a movement towards the technology fronter by reducng nputs at constant output or expandng outputs whle mantanng nputs constant or even decreasng them. Allocatve effcency refers to changng the nput and/or output mx to optmze cost/benefts. Scale effcency refers to changng the scale of the enterprse to the pont of optmal returns to scale 12 Another proxy s the share of nnovatve frms n agrculture (nn_cs7_type), data are however scarce 13 Eurostat varable rd_e_gerdsc and data used. As shown n Graph 13, on average n the EU-28 the publc expendture on R&D n agrculture s stablzng. Graph 13 Per capta publc expendture on R&D n agrculture n 4% 3% 2% 1% % -1% -2% -3% -4% HR LU PL HU DE Per capta publc expendture on agrcultural R&D (n ppp) = EU-15 MS wth hgh TFP growth = EU-15 MS wth low TFP growth = EU-N13 MS wth hgh TFP growth = EU-N13 MS wth low TFP growth = MS wth medum TFP growth = EU-28 average Source: DG AGRI based on Eurostat gba_nabsfn7 From the graph, there s no obvous lnk between the per capta publc expendture on R&D n agrculture and a hgh or low TFP growth. Also the lnk wth the growth of ths expendture over tme and TFP growth s not straghtforward. More advanced analyss s reured to show ths. There s always a tme lag between technology development and adopton, whle other factors are at play as well, such as extenson servces, avalable fnancal nstruments, nsttutonal settng etc. Accordng to Yu et al. () 14, the knowledge stock of R&D n agrculture 15 s consdered to be a better ndcator of technologcal progress than R&D nvestment. Ths s because there are often long lags before farmers begn accessng the outputs of R&D nvestment. To speed up the uptake of nnovaton, the European Innovaton Partnershp for Agrcultural productvty and Sustanablty (EIP-AGRI) was launched by the European Commsson n. It ams at fosterng a compettve and sustanable agrculture and forestry sector that "acheves more from less". To acheve ths 14 Yu Sheng et al. (). Comparng Agrcultural Total Factor Productvty between Australa, Canada and the Unted States, Internatonal Productvty Montor (29). 15 Obtanng consstent data seres per Member State for ths proxy s even more cumbersome due to data lacks FI IE Productvty n EU agrculture 8

9 am, the EIP-AGRI brngs together nnovaton actors (farmers, advsors, researchers, busnesses, NGOs, etc) and helps to buld brdges between research and practce. Va a dedcated workng group on Agrcultural Knowledge and Innovaton Systems (AKIS), the Standng Commttee for Agrcultural Research (SCAR) asssts the EIP through the development of nnovatve Horzon 22 nstruments. A recent JRC-study 16 nvestgated nvestment behavour of farmers n 6 EU countres 17. The study revealed that 56% of the farmers surveyed ntend to nvest n the perod -22. Overall, 4% of the farms planned to nvest n machnery and eupment, whle nvestment ntentons n land, buldngs, tranng, and uotas and producton rghts are less freuent (see Graph 14 also). Increase n producton uantty s however not often cted as man beneft 18. Many of them admt to applyng for nvestment support. Amongst the surveyed countres, they found that Italan farmers stated they were less lkely to ntend to nvest than others n -22 (28%), whle French and German farmers are the most lkely to nvest (67% and 76%, respectvely). Largest farms (.e. those above 5 hectares or 5 lvestock unts (LSU) for lvestock and mxed farms) have a greater ntenton to nvest. They also observed dfferences n the ntentons to nvest by specalsaton, mostly for arable crops. Farm nvestment strateges are also path dependent: farmers ntendng to nvest are largely the same as those who nvested recently. Graph 14 % of farmers ntendng to nvest n each asset type n proporton of the farmers ntendng to nvest n -22* CZ (55%)DE (76%)ES (57%) FR (67%) IT (28%) PL (62%) n tranng n land n buldngs n machnery * The number between brackets ndcates the percentage of farmers ntendng to nvest 16 Lefebre et al. (). European farmers ntentons to nvest n -22: survey results. JRC-report. 17 Czech Republc, Germany, Span, France, Italy and Poland 18 Improvng of workng condtons s Manageral sklls In order for new technologes to be pcked up by farmers and appled to ther ntended use, farmers' management sklls are mportant. Good management practces also help to mprove the techncal effcency,.e. to produce more wth the same set of nputs. Whle not self-evdently measurable, proxes such as age, educaton/tranng and full-tme farm employment are often ndcatve. The effect of age s dual as elderly farmers are more experenced but at the same tme more reluctant to change. The age dstrbuton of farmers s smlar n the EU-15 and the EU-N13, wth about 3% of farms havng a manager older than 65 (FSS, ), whle a lttle over 5% of the farms have a farm manager younger than 35. If we however consder the farm sze by age, farmers less than 35 have sgnfcantly larger farms (3 ha on average versus 7 for the 65+ and 16 on average). Of the Member States wth hgh TFP growth, only Austra has more young managers compared to the 65+. In Denmark, Ireland and the UK, MS wth low TFP growth, we see the share of young farmers declnng over tme. Educaton and tranng s another proxy for new technology uptake and better farm management. As ndcated n Graph 14, between 2 to 4% of the farmers ntendng to nvest, consder nvestments n tranng. 7% 19 of all farm managers dd not receve any tranng, whle only 8% has had a full agrcultural tranng. Ths ncreases to 2% for the farm managers under 35 years old. Member States 2 wth hgh TFP growth tend to have more managers wth full agrcultural tranng. Luxemburg, also wth hgh TFP growth, performs best wth 5% of managers havng followed a full agrcultural tranng. Romana s the excepton, wth more than 96% of farm managers only havng practcal experence. Managers of small farms tend to put n less workng tme than those of bgger farms. One out of fve farmers wth less than 5 ha of agrcultural land spends less than a uarter of hs or her workng tme on the farm. Ths number declnes wth ncreasng farm sze: 82% of farmers wth ha or more work full tme. Wth the drve toward larger farms and more specalsaton, full tme employment s also ncreasng (even n absolute terms for the largest farms n the majorty of MS). Ths leads to economes of scale. 19 CAP context ndcator C24 Agrcultural tranng of farm managers 2 Poland, Latva, Czech Republc, Austra, Belgum Productvty n EU agrculture 9

10 Polces Whether polcy reform enables or dsables productvty growth depends on the polcy objectves pursued and the polcy nstruments chosen. Whle ncreased market orentaton for example can be assocated wth a drve towards more effcency, ncreased regulaton mght generate the opposte effect. Rzov et al. () 21 nvestgated the mpact of subsdes from the Common Agrcultural Polcy on the total factor productvty of farms n the EU. As they explan, there are varous channels through whch subsdes mpact on (aggregate) productvty. They may ether ncrease or decrease productvty and thus the net effect may be ether postve or negatve. The negatve mpact of subsdes on productvty may result from allocatve (and techncal) effcency losses owng to dstortons n the producton structure and factor use, some budget constrants and the shft of subsdes to less productve enterprses. The postve mpact may stem from nvestment-nduced productvty gans caused by the nteracton of credt and rsk atttudes wth subsdes (subsdy-nduced credt access, a lower cost of borrowng, a reducton n rsk averson and an ncrease n productve nvestment). The authors emprcally study the effects of subsdes on productvty usng samples from the Farm Accountancy Data Network for EU-15 countres. Ther man fndngs are clear: subsdes had a negatve mpact on farm productvty n the perod before the decouplng reform was mplemented; after decouplng the effect of subsdes on productvty was more nuanced, as n several countres t turned postve. Man reason s that the negatve effect of subsdes (allocatve effcency loss) s lkely negatvely and the postve effect (nvestment-nduced productvty gan) s lkely postvely correlated wth decouplng; thus one can expect that coupled subsdes wll have a smaller postve or a larger negatve mpact on productvty relatve to decoupled subsdes. Mary () 22 nvestgated the effect of Pllar 1 and Pllar 2 CAP subsdes on French crop farms usng a panel data approach. The results show that set-asde, LFA payments and lvestock payments have a sgnfcantly negatve effect on productvty. Mnvel 21 Rzov, M., et al. (). CAP subsdes and productvty of the EU farms. Journal of Agrcultural Economcs, 64(3), Mary, S. (). Assessng the mpacts of pllar 1 and 2 subsdes on TFP n French crop farms. JoAE, 64(1), and Latruffe () 23 analysed n a meta-analyss 195 results about effect of subsdes, extracted from a set of 68 studes carred out from 1972 to. The authors conclude that aggregatng all subsdes receved by farmers nto total subsdes ncreases the probablty of a negatve effect of subsdes on farms techncal effcency and, when solated, nvestment subsdes are postvely related to farms techncal effcency. Rural and supply chan development An enablng envronment s also essental to come to productvty gans. Investments n rural nfrastructure, access to nformaton (e.g. nternet), presence of a well-developed supply chan and clusters of farmers all have spll-over effects on the farm. In the - Rural Development polcy ths was manly realzed through axs 1 (compettveness of agrculture and forestry), axs 3 (ualty of lfe n rural areas) and Leader (cross-cuttng). Axs 1 receved more than 4% of all EAFRD fundng n Belgum, Hungary and Portugal (44%), Span, Lthuana and n Poland (42%), countres wth hgh TFP growth, whereas t accounted for less than 15% n Austra (13%), Fnland, the Unted Kngdom (12%) and Ireland (1%), the latter 3 havng relatvely low TFP growth. The EAFRD contrbuton allocated to axs 3 was hghest n Malta (33%), followed by Bulgara (3%) and the Netherlands (3%). The allocaton to ths axs was at or below 1% n France (1%), Ireland and Luxembourg (8%) 24. A well-functonng food chan has spll-over effects to the agrcultural sector. Cechura et al. () 25 performed a comparatve analyss among dfferent EU countres n four food processng ndustres to measure the productvty level of ndvdual countres, sectors, and companes. Hgh TFP was found n Germany, France, Italy, and the Netherlands n all sectors. TFP has a postve trend n the majorty of EU member countres; only Bulgara s an excepton. The authors observed that some countres wth average or low TFP levels n the processng ndustry are catchng up but also countres wth hgh productvty are mprovng ther performance. Large dfferences n 23 Mnvel, J. J., & Latruffe, L. (). Meta-regresson analyss of the mpact of agrcultural subsdes on farm techncal effcency. EAAE Congress Agr-Food & Rural Innovatons for Healther Socetes 24 Note that measures mplemented va Leader can contrbute to all axes but manly to axs 3 (for example n Ireland where axs 3 s mplemented manly va Leader). 25 Cechura et al. (). Productvty and Effcency of European Food Processng Industry. EU FP7 Compete project, Workng paper N7. Productvty n EU agrculture 1

11 LV EE LT CZ RO PT NL ES PL FI DE SK AT SE HU LU BE FR DK UK EL IT SI IE EU-15 EU- EU-28 LV LT EE RO BE PL ES PT FI AT LU SK CZ NL SE HU FR DE EL IE UK IT SI DK EU-15 EU-N13 EU-28 productvty also exst between sectors and between companes wthn countres. Structural change EU agrculture s undergong a contnuous process of structural change, wth decreasng numbers of farms whch are ncreasng n sze. Relatve changes between sectors also take place. Farm numbers are contnuously decreasng. Between and, the average annual rate of declne stood at -3.7%, wth greater losses n the countres that joned the EU n and (EU-N12: -4% per year) than n the older Member States (EU-15: -3.4% per year). At the same tme, between and, the average standard output per farm ncreased by 5.7% per year n the EU-27. Ths growth rate was hgher n the EU- N12 (+7.2% per year) than n the EU-15 (+5.1% per year). A JRC-project on structural change shows the (relatve) dsappearance of mxed croppng and lvestock farms n favour of more specalzed farms and the drve towards larger farms. The frst development mproves techncal and allocatve effcency, whle the latter contrbutes to scale effcency. 7. Member States wth dfferent growth Havng dscussed some of the man trends n EU TFP development and the possble drvers whch can explan these, we now turn our attenton to the Member State level. TFP growth on average Whle the TFP growth path s of man nterest, a frst analyss of the average annual TFP growth for the dfferent Member States across the perod - already reveals mportant nsghts (Graph 15). Several Member States jonng after are clearly ahead. Latva, Lthuana, Estona and Poland are best performng, wth growth rates above 2% per annum, whle also Romana reaches an average above 1%. Germany s the worst performng wth a TFP whch s on average contractng by.7% per year snce, manly to be related to a decrease n (anmal) output volume 26 whle nput volume remaned largely stable. 26 As ths s aganst expectatons, a thorough data check shows nconsstences between the ndex-evoluton and actual reported producton numbers. Also Intermedate nput consumpton ndces demonstrate data ssues. Graph 15 Average annual TFP growth n EU Member States between and 27 5% 4% 3% 2% 1% % -1% As for the EU-N13 and the EU-15, TFP growth n the Member States s manly drven by an mproved labour productvty growth (Graph 16). Graph 16 Average annual labour productvty growth n EU Member States between and 12% 1% 8% 6% 4% 2% % In Latva and Estona, the average annual labour productvty growth reaches about 1%, whch corresponds to a doublng of the labour productvty over the perod -. Also n Lthuana, Czech Republc and Romana labour productvty growth s hgh. Of all the Member States, none has negatve labour productvty growth snce. In the UK, total labour force remaned largely stable snce and n Italy snce whle n Ireland t even ncreased after, whch can be related to the economc crss. The low labour productvty n Slovena manly relates to a contracton n anmal, and to a lesser extent crop output, whle the total labour force also remaned stable snce. The low TFP growth n some of the old EU Member States contradcts wth ther postve labour productvty growth, ndcatng negatve productvty growths for the other factors. 27 TFP = average(,, ) and TFP = average(,, ) Average growth calculated as compound annual growth rate Countres not depcted here due to data ssues: Croata (-2.2%/y; =base), Bulgara (+1.1%/y), Malta (-2.9%/y), Cyprus (+.2%/y) Productvty n EU agrculture 11

12 The compound annual growth rate however hdes dfferences n pathways between Member States. Dfferent growth paths between Member States n the EU-15 The TFP growth paths dffer consderably across Member States both n magntude and trajectory (Graph 17). Sx Member States (Italy, France, Greece, Germany, Netherlands and Sweden) have a growth path whch closely follows the EU-15 average, especally n more recent years. Another three (Span, Portugal and Austra) are clearly ahead of the pack wth strong and rather stable growth. Three Member States (Fnland, Belgum and Luxemburg) show trend breaks over tme. In Denmark, UK and Ireland, TFP s not growng at all compared to. What explans these dfferences and what can we learn from the fast growers? Span and Portugal, two strong growers, followed a smlar trajectory, wth strong output growth (both n anmal and crops) n combnaton wth ntermedate nput growth, whle especally labour contracted, combned wth captal outflow especally n Portugal. In Austra, another strong grower, no captal outflow took place but land contracton nstead, wth a loss of about 5 thousand hectares (17%) of land, manly permanent grassland. 6 6 Member States wth dvergng growth path ES PT AT EU-15 Growers n lne wth EU-15 IT FR EL DE NL SE EU-15 In Belgum, labour outflow and captal contracton contrbuted to growth, but ths was untl offset by ncreased ntermedate nput use (manly feed for anmal producton). After feed, energy and fertlzer use decreased consderably. Output on the 6 FI BE LU EU-15 other hand pcked up agan (except for the bad crop harvest n ) explanng the TFP recovery. Luxemburg s a smlar story. Fnland lost ground due Member States wth zero growth to several years of contractng crop output volumes brngng total output growth n lne wth total nput growth. DK Graph 17 TFP growth path for the EU-15 Member States Strong growers 6 UK IE EU-15 On the other sde of the spectrum we fnd the UK, Ireland and Denmark. In the UK, there s postve output growth, but ths s matched by a smlar total nput growth, especally of ntermedate nputs and captal, whle the total labour force remaned largely Productvty n EU agrculture 12

13 stable, explanng the absence of TFP growth. In Denmark output growth s also realzed wth more ntermedate nputs (manly feed) (and not TFP). In output volume also contracted strongly especally n the anmal sector LT LV RO EU-N13 and n the EU-N13 In the EU-N13 dfferences among Member States are larger compared to the EU-15. TFP-growth compared to ranges between -15% and +4%. The EU- N13 champons n TFP-growth are Latva, Lthuana and Romana, manly propelled by steady output ncrease combned wth strong labour force reductons. Romana experenced a strong reducton n crop output volume n, not compensated by the reducton n nput factor use. It however uckly recovered n the subseuent years. 14 Medum growers BG PL EE EU-N13 Estona and Poland, both wth a TFP growth around 2% compared to, show a consstent ncrease snce. Whle Estona's growth was temporarly stopped durng the fnancal crss, after whch t pcked up agan, Poland's TFP grew wth a slower pace Low growers after the crss, as labour outflow reduced and crop and manly anmal outputs stagnated. Bulgara demonstrated steep TFP growth up to. Its man drver s strong labour outflow. At the same tme, anmal producton volumes declned drastcally, partly compensated by hgher crop producton. After a perod 14 HU SK CZ EU-N13 of stagnaton due to deteroratng captal productvty 29, ts TFP growth pcked up agan n. In the thrd group wth growth rates below 1%, encompassng Slovaka, Czech Republc and Hungary, the year was the turnng pont. In the case of Hungary and Czech Republc, a combnaton of contnued captalzaton and only moderate labour outflow n a context of stable outputs explans the stagnaton. Ths s to a lesser extent also the case for Slovaka, where a lower anmal output volume also contrbuted to the low TFP growth. 14 Zero to negatve growers after HR SI EU-N13 Graph 18 TFP growth path for EU-N13 Member States Strong growers 28 Sheep and goat and other anmal products (fur) n partcular 29 There was a strong decaptalzaton n after the crss. Due to recaptalzaton n the next years, captal productvty decreased consderably Croata and especally Slovena are laggng behnd. In Croata total output volume contracted wth 13% snce, as dd total nputs. After, especally crop output declned, explanng the drop. The labour Productvty n EU agrculture 13

14 outflow s also lmted. In Slovena output volumes contracted whle nputs remaned largely stable. A more n depth analyss could reveal whch of the drvng factors contrbutes most to explanng the dfferences between Member States. Some of the necessary data s however lackng. Gven the dstance n productvty level (Chapter 5) wth the EU-15, there s ndcaton that effcency gans (lnked to mproved management sklls), adopton of technologes already used n the EU-15 (such as machnery) and structural change (farms and labour dsappearng whle farm sze grows) are mportant explanatons for the productvty gans. 8. TFP n the world Coell and Rao () 3 examned the levels and trends n agrcultural output and productvty n 93 developed and developng countres that account for a major porton of the world populaton and agrcultural output. They make use of data drawn from the FAO and ther study covers the perod Due to the non-avalablty of relable nput prce data, the study uses data envelopment analyss (DEA) to derve Malmust productvty ndces. The study examnes trends n agrcultural productvty over the perod. Table 2 Weghted means of annual techncal effcency change, techncal change and TFP change for the contnents, 19-2 (Coell and Rao, ) Contnent Effcency Techncal TFP change change change Afrca North Amerca South Amerca Asa Europe Australasa Mean Between 19 and 2, Asa realzed the hghest annual TFP growth of 2.9% (manly due to effcency growth of 1.9% per year) followed by North Amerca (US and Canada), Australasa, Europe, Afrca and South Amerca. The latter reached the lowest growth rate of.6%, followed by Afrca wth 1.3% growth n TFP. Interestng s the predomnance of effcency change (or "catchng-up") as a source for TFP growth n some contnents, as opposed to others. Both n Asa and Afrca effcency change s the prncpal source of 3 Coell, T. and Rao, D.S. (). Total factor productvty growth n agrculture: a Malmust ndex analyss of 93 countres, Agrcultural Economcs 32(S1), TFP growth, whle n North Amerca, Australasa and Europe techncal change s the man drver. A more recent study of Fugle () 31 presents a comprehensve global and regonal pcture of agrcultural TFP growth between 1961 and, also manly based on FAO-data complemented wth data from natonal sources to obtan nput cost shares necessary for the weghtng. The author used the Tornvst-Thel growth accountng ndex of agrcultural TFP growth. Fugle does not fnd evdence for a general slow-down n agrcultural productvty. The TFP growth he notces s manly drven by rapd productvty gans n developng countres such as Brazl and Chna, as well as a more recent recovery of growth n countres from the former Sovet Unon. Other developng countres (Sub Saharan Afrca, West Asa, Carrbean, Oceana) contnue to rely on resource-led agrcultural growth rather than productvty. The evdence n ths study suggests TFP growth may n fact be slowng n developed countres whle acceleratng n developng countres, whch s n marked contrast to the early fndngs of other studes whch found developng countres to be fallng further behnd developed countres n agrcultural land and labour productvty. The numbers projected n table 3 below also confrm our fndngs of decreasng growth n the EU-15 compared to the EU-N13. Table 3 Agrcultural TFP growth across regons (average annual %), Fugle () All developng countres Transton countres All developed countres Europe (except former SU) Eastern Europe Box: TFP to measure agrcultural sustanablty 32 Most exstng metrcs of agrcultural productvty, ncludng our approach, do not fully account for the use of envronmental goods and servces n agrcultural producton, thus provde only a lmted means for assessng the longterm sustanablty of agrcultural productvty growth. Snce TFP does not fully account for the use of natural and envronmental resources n producton, t needs to be 31 Fugle, K. (). Total Factor Productvty n the Global Agrcultural Economy: Evdence from FAO Data. Chapter 4 n The Shftng Patterns of Agrcultural Producton and Productvty Worldwde. The Mdwest Agrbusness Trade Research and Informaton Center, Iowa State Unversty, Ames, Iowa. 32 Based on: Fugle et al. (216). G2 MACS Whte Paper: Metrcs of Sustanable Agrcultural Productvty. Pp 68 Productvty n EU agrculture 14

15 supplemented wth other measures n order to assess sustanablty of agrcultural producton. One approach s to develop sets of agr-envronmental ndcators and track trends n these ndcators alongsde TFP. Another approach s to extend TFP to explctly nclude envronmental goods and servces along wth market-based goods and servces, nto a broader ndex of Total Resource Productvty (TRP). The advantage of such a TRP s that, by valung envronmental goods along wth market goods, potental economc and welfare trade-offs between these outcomes are explctly consdered. To date, comprehensve sets of agr-envronmental ndcators and TRP ndces are not avalable. Whle there remans consderable uncertanty regardng how and what envronmental goods and servces should be ncluded and how they should be valued, progress has been made n recent years n assemblng prelmnary sets of agrenvronmental ndcators and developng methodologes for measurng TRP. Nonetheless, agrcultural TRP ndces that may be developed over the next several years are lkely to be selectve n ther ncluson of natural resource and envronmental, due to both scentfc and data constrants and lmtatons. For a comprehensve assessment of sustanable agrcultural productvty, there reman mportant gaps n fundamental scentfc understandng of the relatonshp between agrculture and the envronment. Wthout better scentfc understandng, we cannot be confdent that any proposed metrc of sustanable agrcultural ntensfcaton actually acheves ts goals. Contnued and enhanced support for fundamental research on sustanable agrcultural systems wll enable the development of mproved productvty metrcs at the approprate scale. change. The descrpton of factors explanng TFP growth can also be underpnned more statstcally. Ths would reure an econometrc analyss for whch we currently lack consstent data. Some further mprovements n the representaton of the nput factors could be made. Due to lack of data, we currently do not dstngush between sklled and unsklled labour, land ualty, whle the calculaton of servce flows from captal stock could also be mproved further. The tme seres length dffers between MS, makng a long term comparson hard. For Croata for example, 3-year averages are only avalable snce. The natonal data also suffer from data gaps and outlers, whch necesstates the use of assumptons to complete the tme seres. 1. Concluson TFP allows for a comprehensve measure of productvty change over tme. It measures the change n output that s not drectly orgnatng from a more ntensve nput use, but from changes n technology, effcency, manageral sklls and organsaton of the producton. It s an mportant mpact ndcator to montor the reachng of the CAPobjectve of a vable food producton. In the future, use of new data tools, lke remote sensng, and related bo-physcal and ecologcal models may sgnfcantly reduce the cost of real-tme and spatally-dsaggregated assessment of the status of envronmental resources used or affected by agrculture. Ths could contrbute to constructon of ndces lke TRP. 9. Some caveats The fndngs of the current study need to be nterpreted wth cauton as lmtatons exst n terms of data gatherng and analyss. Due to the structure of the Economc Accounts of Agrculture t s not possble to dstngush at the nput sde between dfferent sectors. Ths makes a comparson of TFP between dfferent sectors extremely dffcult. Reverson to other data sources (e.g. FADN) could allow for ths knd of analyss. Wth the growth accountng approach we also cannot easly draw a dstncton between effcency change and technologcal change as separate parts of the TFP Productvty n EU agrculture 15

16 Productvty n the EU has ncreased over tme, but at a slower rate more recently compared to the past. Whle the growth rate surpassed 1% per year between 1995 and, t slowed down to around.8% between and. Our analyss reveals that TFP growth s stronger n the EU-N13, showng consderable growth over the last decade, whle EU-15 members show moderate to negatve TFP growth numbers. The TFP growth s manly acheved by reducng the labour nput ntensty, whch s more pronounced n the EU-N13. Gven the dstance n productvty level wth the EU- 15, there s ndcaton that effcency gans (lnked to mproved management sklls), adopton of technologes already used n the EU-15 (such as machnery) and structural change (farms and labour dsappearng whle farm sze grows) are mportant explanatons for the productvty gans. TFP growth paths dffer consderably between Member States. Some are more ht by the fnancal and economc crss as opposed to others. A further comparson of Member States wth smlar structures but other TFP growth paths mght yeld addtonal nterestng lessons learnt. Ths document does not necessarly represent the offcal vews of the European Commsson Contact: DG Agrculture and Rural Development, Unt Agrcultural modellng and outlook Tel: / E-mal: Agr-E2@ec.europa.eu European Unon, 216 Reproducton authorsed provded the source s acknowledged Productvty n EU agrculture 16