The Capitalization of Area Payment into Land Rental Prices: Micro-evidence from Italy

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1 The Capalzaton of Area Payment nto Land Rental Prces: Mcro-evdence from Italy Guastella G. 1, Moro D. 2, Sckoka P. 2, and Venezan M. 1 1 Dpartmento d Economa Agroalmentare e DSES, Unversà Cattolca del Sacro Cuore, Pacenza, Italy 2 Dpartmento d Economa Agroalmentare, Pacenza, Italy maro.venezan@uncatt. Selected Poster prepared for presentaton at the Agrcultural & Appled Economcs Assocaton s 2013 AAEA & CAES Jont Annual Meetng, Washngton, DC, August 4-6, Copyrght 2013 by Guastella G., Moro D., Sckoka P., and Venezan M.. 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. 1

2 The Capalzaton of Area Payment nto Land Rental Prces: Mcro-evdence from Italy Guastella G. 1, Moro D. 2, Sckoka P. 2, and Venezan M. 1 1 Dpartmento d Economa Agroalmentare e DSES, Unversà Cattolca del Sacro Cuore, Pacenza, Italy 2 Dpartmento d Economa Agroalmentare, Pacenza, Italy maro.venezan@uncatt. Summary Ths paper analyses the extent to whch agrcultural subsdes are capalsed nto land rental prce. By usng Italan data at the farm level the analyss proposed n ths paper nnovates wh respect to exstng studes n dfferent ways. Thanks to the long tme span avalable n the FADN database s possble to compare the two tme perods, before and after the 2005 CAP reform, to test whether any change occurred as a result of the ntroducton of the decoupled payments scheme. In contrast to prevous emprcal lerature, whch has eher focused on the unobserved farm-level heterogeney ssue or on the selectvy ssue, the method proposed n ths paper accounts for both smultaneously. Fnally, the same method s extended to account for endogeney of some covarates. Overall, the results n the paper confrm prevous evdence, rejectng the hypothess that agrcultural payments are capalzed nto land prces n both perods. Keywords: Sample selecton; Panel Data; Capalzaton Effect; Italan Farms JEL Classfcaton codes: C33; Q15; Q18 1. INTRODUCTION Agrcultural subsdes are prmarly desgned to support farmers ncome. However non-neglgble secondary effects mght also emerge, nfluencng farmer s decson on amount and composon of factors (.e., labour, capal and land) to be used n producton. Such effects are documented by, among others, Lence and Mshra (2003) for what concerns land markets, Rude (2008) n relaton to farmers producton decsons and Sckoka and Moro (2009) n relaton to farmers nvestment decsons. After the 2005 Common Agrcultural Polcy (CAP) reform, that ntroduced decoupled drect payments n the EU, much attenton has been devoted to the effect of agrcultural subsdes on land prces and, n greater detal, to the so called capalsaton effect n both the sale and rental prces (Caan and Swnnen, 2006). In fact, f payments are capalsed n land prces, subsdes orgnally ntended to support farmers ncome mght be transferred to sectors other than agrculture. The decouplng reform, attachng subsdes payment to the amount of land used n producton, s expected to ncrease the lkelhood of such an effect (Roberts et al., 2003). Many exstng studes explore the capalsaton effect of agrcultural payments usng US farm data, whle only a mnory has dealt wh the topc usng EU data. Furthermore, exstng studes on EU agrculture are heterogeneous n terms of both the spatal and temporal coverage of the emprcal analyss. For nstance the study by Patton et al. (2008) examnes the capalzaton of subsdes n Ireland focusng on the perod before the 2005 reform; Klan et al. (2008) analyse data for Bavaran farms n 2005, the frst year after the 2

3 mplementaton of the reform; Breustedt and Habermann (2011) focus on German farms as well, but n the perod before the reform mplementaton; Caan and Kancs (2012) study the effect of agrcultural payments on rents n new member states, where only decoupled support has been rolled-out. Ths evdence, based on the estmated coeffcents from a regresson of rental prce on land productvy and subsdes, s rather mxed and defnvely not conclusve. Furthermore, few studes account for the several sources of endogeney bas n estmaton. Frstly, one source of endogeney s related to the cross-secton nature of the data, whch prevents from accountng for unobserved heterogeney at the farm level. Secondly, usng the rental prce per hectare as the model s dependent varable requres the ssue of selectvy to be taken nto approprate consderaton, snce the choce of rentng s lkely to be endogenous. Whereas some studes have estmated the capalsaton effect usng panel data, hence accountng for the role of tme-nvarant ndvdual unobservables, some others have focused solely on the ssue of selecton. Nonetheless, none has consdered both these effects smultaneously. Although theoretcal estmators have been developed (Wooldrdge (1995); Kyrazdou (1997); Rochna-Barrachna (1999)), ther use n appled econometrcs, n facts, has been rather lmed (Dustmann and Rochna-Barrachna, 2007). By explorng the relaton between rental prce, on the one sde, and land productvy and payments, on the other sde, ths paper provdes several contrbutons to the exstng emprcal lerature on the capalsaton effect. Frstly, we apply the Wooldrdge (1995) estmator to smultaneously account for selectvy and farm heterogeney n both the selecton and man equatons. Due to the unbalanced nature of our panel, ths estmator s to be preferred to those suggested by Kyrazdou (1997) and Rochna-Barrachna (1999). Secondly, we extend exstng model framework to take nto approprate account the potental endogeney of productvy and payments dscussed n Lence and Mshra (2003) and Patton et al. (2008). Thrdly, the long tme-span of the seres of our database allows us to estmate the capalzaton effect for both the perods before ( ) and after ( ) the decouplng reform. Ths allows to drectly test the effect of such an mportant reform by monorng changes n the capalsaton effect after the ntroducton of the Sngle Farm Payment (SFP) scheme. Fnally, we provde novel evdence for Italy where ths effect has not been nvestgated, yet. Our results are based on FADN data. Farms n the fnal dataset are selected from those specalsed n feld-croppng. After elmnatng the nconsstent values, we obtan, over a 15-year perod, a dataset of 73,342 observatons related to 29,540 unque farms wh varyng degrees of permanence n the panel. The actual ncdence of non-rentng farms s approxmately 51%, and ths ndcates the potental magnude of the selecton bas. Prelmnary results reject the hypothess of a capalzaton effect n Italy n both perods, before and after the ntroducton of the decouplng reform. In the remanng of the paper, the next secton presents a bref note on estmaton of panel data models n presence of selectvy and descrbes the dataset used for estmaton. Model results are presented and dscussed n the thrd secton comparng estmates obtaned usng the methodologes descrbed n Wooldrdge (1995) and n Semykna and Wooldrdge (2010). A bref summary of evdence concludes the work. 2. ESTIMATION OF CAPITALIZATION EFFECT 2.1. Emprcal Model and Econometrc Strategy The emprcal assessment of the capalsaton effect s carred out by eher examnng prces of land transacton or by analysng rental values of land. In the former case exstng studes refer to the Net Present Value model or to the hedonc prcng approach to derve the emprcal specfcaton (Fechtnger and 3

4 Salhofer, 2011). In the latter case, emprcal models are derved from the prof-maxmzng behavour of farmers. Lence and Mshra (2003) represent a key reference n ths type of lerature. In ther model rental prce per hectare s determned by the expected productvy of agrcultural land and by expected per hectare payments receved by government. Smlarly n Caan and Swnnen (2006) the capalsaton effect s studed n a partal equlbrum framework derved from a prof-maxmzaton settng. Also n ths case market clearng condons relate rental prce to farm subsdes and farm output. Ths framework s adopted, among others, by Patton et al. (2008) by Krwan (2009) and by Breustedt and Habermann (2011). Accordngly, n a panel data settng, a general emprcal specfcaton follows the one proposed hereby: r Y P X. (1) ' In equaton 1 r s the net rental prce per hectare of rented land, Y s the output per hectare, P s the per hectare amount of payment receved by the farmer. and t denote, respectvely, the farm and the year for whch values are observed. and are the parameters of nterest n ths study. However, whle the slope of s expected larger than zero, that of s expected to equal zero under the null that agrcultural payments are not capalzed nto land rental prces. X s a matrx of addonal control varables capable of explanng resdual varaton n the dstrbuton of land rental prces and s the vector of assocated coeffcents. s the usual vector of resduals. Three man estmaton ssues are concerned wh estmaton of both and. Frstly s lkely that unobserved farm-specfc effect are correlated wh covarates, especally wh productvy and payments. Whle many farm-specfc characterstcs affectng both rental prce and productvy and payments, such as sze, capalzaton and type of producton, can be drectly observed, some others, such as sol qualy, are unobservable. The ndvdual heterogeney bas derved from unobservable characterstcs s only consdered n studes where more than one year s observed and dfferent panel data methodologes can be appled. For nstance, the capalzaton effect s estmated employng GMM technques n Patton et al. (2008), usng the frst dfference estmator n Krwan (2009) and the long dfference estmator n Caan and Kancs (2012). Secondly only a sub-sample of farms do actually use rented land n producton, makng estmaton possble only on selected farms. As descrbed by Heckman (1979) a problem of selecton bas occurs f selecton s endogenously determned and, hence, f the probably of rentng s somehow related wh the model's rght hand sde. Whle the selecton ssue s easly tractable n the cross-secton framework, extenson to panel data s complcated by the possble correlaton between selecton and unobserved farm-level characterstcs. To the authors knowledge the study by Caan and Kancs (2012) s the only accountng for selectvy by adaptng cross-secton sample selecton methods to long-dfferenced seres. Thrdly, the use n estmaton of actual values of productvy and payments n place of the relatve expected values represents a thrd source of endogeney caused by the nfluence of expectaton errors on resduals. GMM methodologes are appled by Lence and Mshra (2003) and Patton et al. (2008) to account for the endogenous nature of productvy and payments. All these estmaton ssues have been consdered separately by the studes n whch the capalzaton effect has been estmated. The econometrc framework proposed n ths work attempts to consder all ssues smultaneously. In Wooldrdge (1995) (herenafter W95) a correcton procedure s proposed to estmate panel data models n presence of endogenous selectvy and ndvdual heterogeney. The methodology reles on a two-step procedure smlar to the one proposed by Heckman (1979). Followng Mundlak (1978), correlaton between ndvdual effects and covarates s allowed by ncludng ndvdual average of covarates among the regressors n the man equatons. The procedure requres T dfferent prob models to be 4

5 estmated, one for each year t 1,2,..., T. From prob estmates T dfferent Inverse Mll's Ratos (IMR) are computed and ncluded n the man equaton after poolng. Robust standard errors for the set of model coeffcents can be estmated usng formulas n the appendx of Wooldrdge (1995). Alternatve estmators have been proposed by Kyrazdou (1997) and Rochna-Barrachna (1999). Both estmators rely on frstdfferencng of data to elmnate ndvdual heterogeney and use only observatons for whch the selecton ndcator s constant for two consecutve tme perods. Ths generally mples a loss n effcency wh respect to W95, especally n the case of strongly unbalanced panel data. The comparson of the three estmators s dscussed n greater detal n Dustmann and Rochna-Barrachna (2007). Semykna and Wooldrdge (2010) (herenafter SW10) extend the W95 approach by allowng to correct for endogeney bas due to non-zero correlaton between explanatory varables and dosyncratc errors. The procedure agan works n two steps. In the frst step T dfferent prob equatons are estmated to derve IMRs. In the second step a pooled OLS estmator s used addng ndvdual means of frst step varables and IMRs as covarates and nstrumentng endogenous varables wh a subset of varables used n frst step. The capalzaton effect s estmated n ths paper usng the procedure descrbed n W95 to account for selectvy and ndvdual heterogeney as well as wh the SW10 procedure to account for possble correlaton of productvy and payments wh resduals, caused by expectaton errors. Consder the model n equaton 1, where r s observed only f hectares of rented land used n producton are larger than zero. Defne s the selecton ndcator followng a bnary rule and takng non-zero values when r s observed. Followng W95, for each t the prob equaton P( s 1 W ) ( W ) (2) t s estmated and, for s 1, ˆ ( W ˆ ) s computed, ( ) denotng the usual IMR. W s such t that W [ Y, P, X, Z ]. Ths ensures that varables n the second step represent only a subset of varables n the frst step and and Z are used as excluson restrctons. In the second step the equaton r Y P X Y P X ˆ (3) ' ' s estmated usng only selected observatons. Based on Chamberlan (1982) the presence of Y, X n the second step controls for unobserved heterogeney allowng correlaton between ndvdual effects and covarates n equaton 1, whle the ˆ term controls for selectvy. Accordngly parameters, and can be consstently estmated by applyng Pooled OLS to equaton 3. Usng a conservatve approach n terms of degrees of freedom, Y, P and X are replaced by Y, P and P X n the emprcal applcaton. Furthermore, nteractons between and T 1 tme dummy varables are ncluded to take nto approprate account that T values of have been used n computng ˆ. Takng nto account endogeney of productvy and payments requres mnor changes wh respect to the approach above. Followng SW10 n the frst step only strctly exogenous varables are used as explanatory varables. Thus, for each t, the equaton P( s 1 M ) ( M ) (4) t s estmated, where now M [ X, Z ]. As n the prevous case, IMR s computed based on frst step estmates of and s ncluded n the second step regresson r Y P X X ˆ (5) ' ' 1 5

6 whch s modfed accordngly. Notaton n equaton 5 corresponds to that n equaton 3 except for the fact that now ndvdual averages of endogenous varables are excluded from the rght hand sde. Dfferently from W95, equaton 5 s estmated by applyng the standard IV estmator on pooled data and usng and ˆ as nstruments. Exactly as n the prevous case, X are used n place of ˆ and T 1 tme dummy varables are ncluded to allow to be non-constant. M, M X and nteractons between 2.2. Data and Descrpton of Varables The data used n ths work come from the FADN database of the European Commsson. The sample we consder ncludes all Italan farms recorded n the database whch are specalzed n feld-croppng. The sample covers years from 1994 to 2008 and hence ncludes both perods before and after the 2003 decouplng reform. The nal database counts 77,913 farms for that perod. Producton s dvded n fve man output categores, namely cereals, gran maze, olseeds, protens and other types of crop productons and 515 observatons n the dataset are assocated to a null value of output n any of these categores. These farms cannot be consdered specalzed n feld-croppng and are therefore excluded from the database. 423 farms are excluded as well snce the reported value of producton s negatve. Although FADN documentaton provded by the Commsson explans n detal ths evdence, n fact null or negatve values of producton cannot be used for the emprcal estmaton. Snce per hectare producton and payments represent the two most mportant explanatory varables n ths work, all values causng eher per hectare producton or per hectare payment to be mssng have been excluded from the fnal database. In more detal, n 3,096 observatons was found a posve value of producton n correspondence wh a null number of hectares of land (or, by the oppose, a null value of producton n correspondence wh a posve number of hectares of land) n at least one of the fve output categores mentoned above. Consderng the same categores, n none of the observatons was found a posve value of payment n absence of elgble land (or the oppose). Furthermore there were 429 observatons for whch a coupled payment was regstered n at least one category of producton whout the relatve value of producton beng larger than zero and these observatons have been excluded as well. Fnally out of the 73,440 observaton consdered, 98 were unselected because the value of one or more of the other explcatve varables was mssng. The database used for emprcal estmaton s hence composed of 73,342 observatons, of whch 15,371 n year Table 1 summarzes mean values of the dependent varable r, the rental prce per hectare, of the selecton ndcator s and of the two man ndependent varables, per hectare output Y and per hectare payment P. In table 1 s possble to note the relevance of selecton ssues, provded than n both perod almost half of the farms n the database do not rent land for producton and hence are excluded from the estmaton sample. In the FADN database, producton and payments are recorded separately and based on dfferent aggregaton schemes. In order to produce comparable measures of per hectare output and payment, aggregaton has followed the scheme proposed n the FADN database for the classfcaton of payments. Notably, n fact, producton data are reported n the FADN database followng a more detaled classfcaton scheme. Table 4 n the appendx summarzes the procedure used to obtan comparable values. The total value of producton s computed summng up the values of producton of cereals, gran maze, olseeds and crops and hence excludng other crop productons, by-product output and output from lvestock producton. 6

7 Accordngly only land used for producton of cereals, gran maze, olseeds and crops s consdered n the denomnator of Y. The same procedure s adopted for payments, countng only the effectve number of elgble hectares n the denomnator of P. Table 1. Summary statstcs of dependent and man ndependent varables N of obs N of farms N of years 11 4 r (thousand of Euro per hectare) s (1 f rented land s used n producton) Y (thousand of Euro per hectare) P (thousand of Euro per hectare) Monetary values n the fnal database have been reconverted usng a fxed exchange rate for the years before the ntroducton of the common currency and then deflated usng Eurostat agrcultural output prce deflators (Eurostat reference: apr_p00_outa 1 ). In the case of cereals producton and of payments for cereals, a specfc deflator was avalable whle n the case of olseeds and protens the deflator for ndustral crop producton was used. The generc crop output deflator was used n all other cases, for nstance n the case of other crop output and by-product output. Fnally, output from lvestock and lvestock products was deflated wh the specfc deflator. A lst of varables used n the emprcal model s presented n table 2. Among covarates n the land prce model, productvy and payments are expected to capture the largest part of the varaton n rental prce. As dscussed by Lence and Mshra (2003) and Patton et al. (2008), wh respect to both productvy and payments, the endogeney ssues related to errors n expectatons must be carefully addressed n emprcal estmaton of the rental prce equaton. In selectng exogenous covarates for the emprcal model, prevous lerature has been consdered (Klan and Salhofer (2008); Patton et al. (2008); Breustedt and Habermann (2011); Caan and Kancs (2012)). The sze of farm s the most mportant farm-specfc characterstc whch s capable of nfluencng farm rental prce. Followng the classfcaton scheme adopted by Eurostat to present statstcs on the dstrbuton of farm sze, eght dummy varables for dfferent sze classes has been ncluded n the regresson model. Snce the focus of the paper s to estmate the capalzaton effect for farmng actves usng land as a prmary producton factor, only farms specalzed n feld-croppng are used for the estmaton. Nonetheless a non-neglgble share of farms report dfferentated sources of agrcultural ncome and, therefore, the share of output produced by actves not related to feld-croppng has been ncluded as control. Prmarly output derved from lvestock producton and from by-product actves has been consdered. Fnally, some regonal characterstcs are ncluded to account for varaton n rental prce of land related to factors external to the farm. The most relevant of these factors are the prces of nput dfferent from land, namely labour and ntermedate nputs, for whch the regonal wage and the regonal nput prce ndex have been consdered as good proxy, and the demand for rent land dervng from manure spreadng actves, as proxy by the anmal densy. Addonal varables are used as excluson restrcton and hence ncluded only n the prob equatons. Among determnants of the rent decson ths work consders the rato of famly to total labour and a measure of farm capalzaton. These are expected to capture the nfluence of a manageral approach to farmng, whch mght sgnfcantly affect the decson to rent but s unlkely related to rental prce. Furthermore 1 Snce prce deflator for 1994 s not avalable at Eurostat, the 1995 value has been used nstead. 7

8 composon of producton, as proxy by land shares for the four categores mentoned above, s consdered among excluson restrctons. Although composon of producton mght have, n fact, only a margnal or altogether neglgble role n explanng rent decson at the farm level, s worth notng that, for the purpose of estmaton of the model wh selectvy, heterogeney and endogenous regressors (Semykna and Wooldrdge, 2010), nstruments for productvy and payments must be selected among the set of varables excluded from the second step. Therefore, an extended set of varables n used as excluson restrctons n both models and the same varables are used as nstruments n the model wh endogenous covarates. The choce to use land shares as nstruments for productvy and payments s motvated by the fact that, on the one sde, both varables, at the aggregate sector level, are strongly nfluenced by composon of producton and, on the other sde, expectaton errors n productvy and payments are expected to be not systematcally correlated wh the farmer's choce about types of crop producton. Table 2. Lst of Varables for the emprcal model Varable Dependent Varable Rent Descrpton Yearly value of rental contract dvded by the number of rented has Endogenous Covarates Productvy Yearly value of cereals, maze, protens and olseeds producton dvded by the number of has used for these productons Payments_c Amount of coupled payments related to the productons of cereals, maze, protens and olseeds dvded by the relatve number of has elgble for support Payments_d Amount of decoupled payments dvded by the number of has elgble for support Exogenous Covarates Sze Sze categores based on farm has: 1 (<2) 2 (>2 and <5) 3 (>5 and <10) 4 (>10 and <20) 5 (>20 and <30) 6 (>30 and <50) 7 (>50 and <100) 8 (>100) lvestock output Rato between output from lvestock and lvestock products and total farm output by-product output Rato between output from by-product actves and total farm output Addonal controls (at the regonal level) anmal densy Regonal aggregate number of lvestock uns dvded by the regonal area Wage Average regonal wage per hour worked ntermedate nput Regonal prce ndex for ntermedate nputs (energy, fertlzers,...) expendure prce Excluson Restrcton Labour Rato between famly and total labour (n number of hours) capal Value of assets (buldngs, equpment and machnery) dvded by the number of farm has share cereals Rato between land used for producton of cereals and total farm land share maze Rato between land used for producton of maze output and total farm land share protens Rato between land used for producton of protens output and total farm land share olseeds Rato between land used for producton of olseeds output and total farm land 3. RESULTS The rental prce model s estmated by usng both the W95 methodology and the SW10 methodology, n ths second case accountng for the endogeney of productvy and payments. Estmaton results are presented n table 3 for both the perod before the decouplng reform was ntroduced and the perod after the reform. The presence of any capalsaton effect s assessed through a test on the sgnfcance of coeffcents related to Payments_c and Payments_d, respectvely for the coupled and decoupled payment schemes. 8

9 Table 3. Land Prce model Estmates - correlated farm effects and selectvy W1995 SW2010 Productvy ** ** *** *** (0.834) (1.864) (4.980) (6.094) Payments_c ** (0.055) (0.262) Payments_d (0.019) (0.443) Cash Flow ** (0.004) (0.004) (0.001) (0.002) 2 to 5 has ** (0.599) (1.260) (1.531) (1.045) 5 to 10 has ** * (0.648) (1.308) (1.761) (1.216) 10 to 20 has ** ** (0.650) (1.341) (1.759) (1.357) 20 to 30 has * * (0.654) (1.368) (1.761) (1.397) 30 to 50 has * ** (0.657) (1.377) (1.764) (1.457) 50 to 100 has * *** (0.663) (1.409) (1.765) (1.494) more than 100 has ** (0.681) (1.451) (1.776) (1.622) lvestock output * (0.083) (0.210) (0.093) (0.276) by-product output (0.275) (0.743) (0.277) (0.983) anmal densy *** *** *** *** (0.134) (1.238) (0.154) (2.142) Wage ** ** (0.014) (0.024) (0.016) (0.073) ntermedate nput prce *** *** *** (0.012) (0.012) (0.014) (0.046) ntercept *** *** ** (1.176) (2.174) (2.066) (7.312) Notes to table 3: Asymptotc SE n parenthess. ***, ** and * ndcate statstcal sgnfcance at 1%, 5% and 10% confdence levels. Estmaton wh the W95 procedure produces results n the frst two columns of table 3. For both perods there s evdence that the effect of productvy s posve and sgnfcant, larger for the perod after decouplng reform. The coeffcent related to the capalsaton effect s negatve and sgnfcant n the perod before the reform and turns out to be not sgnfcantly dfferent from zero for the perod after the reform. Many of the sze coeffcents are sgnfcantly dfferent from zero, as expected. However, s mportant to note that evdence suggest that hgher rents were pad by large farm n the perod before the reform, whle the average rent has been hgher for mddle-sze farm n the perod after the reform. There s weak evdence that non crop productons affect the rental prce of land as the only coeffcent for lvestock producton n the pre-reform perod s sgnfcant. Concernng regonal varables, the coeffcent related to anmal densy s 9

10 negatvely sloped and sgnfcantly dfferent from zero for the frst perod. The same coeffcent, however, turns posve n the second perod. Fnally evdence ndcate that land rental prces react posvely to an ncrease n prce of ntermedate nputs and negatvely to an ncrease n the prce of labour, although ths second effect seems to dsappear n the perod post reform. Estmaton wh the SW10 procedure produces smlar results. The sze of the coeffcent related to productvy s now much larger than n prevous case and contnues to be, on average, larger n the perod post reform. In both perods the coeffcent s hghly sgnfcant. Concernng payments, for both coupled and decoupled payments the related coeffcent s now correctly sloped but n neher case sgnfcantly dfferent from zero. Oppose to prevous results, none of the sze dummy varables has sgnfcant coeffcent whle the coeffcent of cash flow turns now to be sgnfcant. Concernng the effect of productons other than crop, there s no evdence ndcatng that land rental prce mght be affected by output composon. Estmates confrm prevous evdence that the densy of anmals had a negatve effect on land prce n the perod before the reform and that effect s posve n the perod after the ntroducton of decouplng reform. Fnally, prevous results are also confrmed for what concerns the prce of other nputs, but only for the frst perod, as both coeffcents are not sgnfcant n the second perod. 4. CONCLUSION Much concern has rsen n relaton to the so-called capalsaton effect n Europe after the ntroducton of decoupled agrcultural payments n Many studes attempted to test the hypothess that agrcultural subsdes are capalzed nto land rental prces and the evdence s rather mxed. Ths paper nnovates wh respect to prevous studes snce panel methodologes capable of correctng estmates for unobserved heterogeney at the farm level, selecton arsng from the endogenous decson of rentng, endogeney of productvy and payments due to expectaton errors are used. Employng Italan FADN data, the capalsaton hypothess s tested usng a sample of farms specalzed n feld-croppng n the perod Overall, the evdence n ths paper reject the hypothess that agrcultural payments are capalzed nto land rental prce at the farm level. The concluson s smlar for both perods, before and after the ntroducton of the reform. Fndngs are coherent wh evdence n prevous studes fndng a weak or altogether absent capalsaton effect and n assgnng a prmary role to land productvy. AKNOWLEDGMENTS The research was conducted as part of the FADNTOOL project, funded under the European Communy s SEVENTH FRAMEWORK PROGRAMME (Call: 7FP-KBBE ). Authors are grateful to Anastasa Semykna for her help wh estmaton code. REFERENCES Breustedt G., Habermann H. (2011). The Incdence of EU Per-Hectare Payments on Farmland Rental Rates: A Spatal Econometrc Analyss of German Farm-Level Data. Journal of Agrcultural Economcs 62: Chamberlan G. (1982). Multvarate regresson models for panel data. Journal of Econometrcs 18:5 46. Caan P., Kancs D. (2012). The Capalzaton of Area Payments nto Farmland Rents: Mcro Evdence from the New EU Member States. Canadan Journal of Agrcultural Economcs/Revue canadenne d agroeconome 60: Caan P., Swnnen J.F.M. (2006). Land Market Imperfectons and Agrcultural Polcy Impacts n the New EU Member States: A Partal Equlbrum Analyss. Amercan Journal of Agrcultural Economcs 88:

11 Dustmann C., Rochna-Barrachna M.E. (2007). Selecton correcton n panel data models: An applcaton to the estmaton of females wage equatons. Econometrcs Journal 10: Klan S., Anton J., Roder N., Salhofer K. (2008). Impacts of 2003 CAP reform on land prces: From theory to emprcal results. 109th EAAE Semnar, Verbo Italy. Klan S., Salhofer K. (2008). Sngle payments of the CAP: where do the rents go? Agrcultural Economcs Revew 9: Krwan B.E. (2009). The Incdence of U.S. Agrcultural Subsdes on Farmland Rental Rates. Journal of Polcal Economy 117: Kyrazdou E. (1997). Estmaton of a Panel Data Sample Selecton Model. Econometrca 65: Lence S.H., Mshra A.K. (2003). The Impacts of Dfferent Farm Programs on Cash Rents. Amercan Journal of Agrcultural Economcs 85: Mundlak Y. (1978). On the Poolng of Tme Seres and Cross Secton Data. Econometrca 46: Patton M., Kostov P., McErlean S., Moss J. (2008). Assessng the nfluence of drect payments on the rental value of agrcultural land. Food Polcy 33: Roberts M.J., Krwan B., Hopkns J. (2003). The Incdence of Government Program Payments on Agrcultural Land Rents: The Challenges of Identfcaton. Amercan Journal of Agrcultural Economcs 85: Rochna-Barrachna M.E. (1999). A New Estmator for Panel Data Sample Selecton Models. Annals of Economcs and Statstcs / Annales d Économe et de Statstque Rude J. (2008). Producton Effects of the European Unon s Sngle Farm Payment. Canadan Journal of Agrcultural Economcs/Revue canadenne d agroeconome 56: Sckoka P., Moro D. (2009). Modellng the mpact of the CAP Sngle Farm Payment on farm nvestment and output. European Revew of Agrcultural Economcs 36: Semykna A., Wooldrdge J.M. (2010). Estmatng panel data models n the presence of endogeney and selecton. Journal of Econometrcs 157: Wooldrdge J.M. (1995). Selecton correctons for panel data models under condonal mean ndependence assumptons. Journal of Econometrcs 68: APPENDIX Table 4. Aggregaton scheme for producton values and subsdes Payments and number of elgble hectares (table M) Productons and number of hectares (table K) Cereals Gran Maze Protens Olseeds