Determinants of the Organic Farmers Demand for Hired Farm Labor

Transcription

1 Determnants of the Organc Farmers Demand for Hred Farm Labor Carre E. Neely Unversty of Georga, Department of Agrcultural and Appled Economcs, Athens, Georga Graduate Student Cesar Escalante Unversty of Georga, Department of Agrcultural and Appled Economcs, Athens, Georga Assstant Professor Selected Paper prepared for presentaton at the Amercan Agrcultural Economcs Assocaton Annual Meetng, Long Beach, Calforna, July 23-26, 2006 Copyrght 2006 by Carre E. Neely and Cesar Escalante. 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 Ths study s desgned to determne the sgnfcance of organc (and transtonng to organc) farmng systems use of hred non-famly labor as a functon of ndvdual farm structure characterstcs, especally as the structure evolves through extensfcaton and alternate target markets. Non-famly labor was chosen as the varable of choce due to ts ndependence from organc certfcaton standards and ts prevalent use by both conventonal and organc farmng systems. Ths s not a study of natonal market demand for hred labor, but rather an ndvdual farmer s relatve demand for non-famly hred labor and the magntude by whch ther structural characterstcs affect ths need. Certfed organc food s, by defnton, produced by farmers who emphasze the use of renewable resources and conservaton of sol and water. USDA organc standards that specfy varetes of substances and farmng practces whch are barred from use n organc producton addtonally requre farm management plans whch outlne efforts for sol and water conservaton wth the specfc objectve of mprovement for future generatons (USDA 2002). As of 2003, the USDA recognzed 8,035 certfed organc farm operatons n the U.S., comprsed of cropland, pasture and lvestock productons. Over two mllon acres and 8.9 mllon head of lvestock and poultry are dedcated to organc farmng; quadruple the quantty present a decade earler. The 2003 average acreage of an organc operaton n the U.S. was 273 acres, compared wth a natonal average for conventonally operated farms of 441 acres (USDA 2003). Survey analyss showed 40% of organc operatons as beng 100 acres or less and 68% of operatons as 300 acres or less mplyng a large majorty of smaller farms and lmted large-scale operatons (OFRF 2004). Analyss also outlnes the prevalence of famly-run organc operatons, wth many surveys from the last decade all dsplayng

3 between 83% and 87% of organc operatons busness structure as beng sngle famly or famly partnershps (OFRF 1995; 1997; 1999; 2004). Despte lower average acreage, organc farms are generally accepted as dsplayng trends of more labor ntensveness than ther conventonal counter-parts. Characterstc lmted use of synthetc nputs requres organc farms to look towards alternatve technques for pest removal, sol addtons and conservaton, commonly dependng on manual practces. Fertlzers are replaced wth green manures and ntrogen fxng cover crops, cultvatons and hand weedng control nvasve plant speces, and pests are suppressed by mut-crop rotatons wthn the same year and even ecosystem management whch creates a buld-up of benefcal/predator nsect speces. Studes consstently show hgher labor demands for all spectrums of organc producton compared to conventonal methods (Klepper, et al 1977; Lockeretz, Shearer and Kohl 1981; Lockeretz 1997; Jansen 2000; Schneeberger, et al. 2002). A decomposton of natonal organc farm data shows a larger percentage of yearly hred organc farm workers (both full and part-tme) were famly labor rather than non-famly employees (OFRF 2004). In regards to the prevalng busness structure of sngle famly operatons ths s to be expected. A bt more explanaton s requred when takng nto account the number of farms hrng non-famly workers and the total number of organc farm workers hred. Almost half (45.65%) of organc operatons employed no non-famly workers for the growng season (OFRF 2004). Concurrently, the number of non-famly workers hred was more than double the amount of famly labor utlzed. Partal ratonalzaton accepts the theoretcal lmtatons of farm famly labor supply, as famly members have a fnte lmt, so do the number of laborers n a famly.

4 Addtonal concern regards the number of seasonal non-famly workers as opposed to yearly non-famly workers. As fgure 1.0 shows, seasonal organc workers from nonfamly sources were fve tmes the number hred from famly sources. The specfc objectve of ths study s to examne the current characterstcs of organc farms and how varatons n these characterstcs affect a farm s non-famly labor choces. Farm operaton nformaton for the growng season was obtaned through the Organc Farmng Research Foundaton s 4 th Natonal Organc Farmer s Survey. Analyss wll utlze a step-wse Tobt model to explan the magntude by whch each characterstc affects the number of non-famly laborers hred once that choce s made. Data for analyss s dvded nto three groups based on completeness of survey responses as well as target crop producton, determned both by level of producton and level of ncome attrbutable to target crop. Specfc structural characterstcs to be examned nclude (but are not lmted to): busness structure, number of commodtes produced (both organc and conventonal), marketng outlets and types of processng mplemented, years certfed organc, ncome from organc producton, off-farm employment, geographcal locaton and percepton of organc markets. Emprcal Model Consderng that the non-famly labor varable s censored downward, the determnants of the organc farms labor hrng decsons cannot be estmated usng ordnary least squares (OLS) regresson. Ffty four percent of the sample s censored at zero due to the absence of non-famly hred labor. The remanng porton of the sample s dstrbuted by quantty

5 of non-famly farm labor requrements, ether n leu of famly labor or as a complement to t. A common approach used to address ths ssue s to use the Tobt model, a censored regresson technque that s conducted usng maxmum lkelhood estmaton. The Tobt model s generally formulated n terms of an ndex functon (Greene) as shown below: where y y y * = β ' x + ε = 0 = y * f f y * y 0, * > 0, * * y, the ndex or latent varable, s observed as y = max(0, y ). The densty of y / x has a mass pont at 0 and s roughly contnuous from (0, ). Lnear regresson of y on x wll yeld nconsstent estmates of β and thus, β s estmated usng maxmum lkelhood. The basc form of the estmatng equaton used n ths study s: NFL = β 0 + β 1 STRUCTURAL + β 2 DEMOGRAPHIC + β 3 SIZE + β 4 INCOME + β 5 MARKETING + β 6 EXPERIENCE + β 7 PERCEPTION + β 8 LOCATION + ε. The dependent varable, NFL, s the total number of non-famly farm workers hred durng the entre producton year. Ths can nclude seasonal, yearly, part-tme or full-tme workers. Followng s a dscusson of the eght categores of explanatory varables used n ths study. Explanatory Varables

6 STRUCTURAL varables are ntended to capture the possble effects of farmland management arrangements, producton dversfcaton profle, busness set-up, extent of tme devoted to the farm busness, and nfluence of off-farm ncome generatng actvtes on the farms decsons to substtute famly labor wth the hrng of non-famly farm workers. These varables are: a. TENURERAT, the tenure rato calculated as the proporton of owned land to total acreage farmed organcally; b. CROPSGRWN, representng the number of commodtes grown; c. CONVDUM, dummy varable representng the producton of conventonal commodtes takng on a value of 1 for some conventonal acres and 0 otherwse; d. SOLEPROP, dummy varable takng on a value of 1 for sngle famly or sole propretorshps and 0 for other busness structures; e. FULLTIME, dummy varable wth value of 1 for full-tme farm managers and 0 for part-tme farmers; f. OFFFARM, dummy varable to consder tradeoffs between farm and offfarm ncome generatng actvtes where the varable s assgned a value of 1 f there s no off-farm employment or nvestments and 0 for those wth some off-farm ncome generatng actvtes; and g. VAPERDUM, dummy varable to capture the effect of ncome derved from value-added products processed by or for the farm, takes on a value of 1 f some value-added products are processed and 0 otherwse.

7 Farmland control arrangements can potentally nfluence labor hrng decsons. Farm operators that own larger portons of the land they tll are expected to be more nclned to nvest more hours workng on-farm. These operators lkewse are more nclned to engage n full-tme farmng and would have relatvely less nvolvement n offfarm ncome generatng actvtes. On the other hand, smpler busness structures (such as sngle propretorshps) are expected to be less nclned to rely on non-famly labor than partnershp or corporate farms wth perhaps larger operatons that justfy more labor hrng actvtes. Moreover, Jansen (2000) attrbutes greater dependence on labor nputs to hgher degrees of dversfcaton (mxed farmng) and more on-farm processng actvtes whch expand the product base and value added contrbutons, respectvely, of the farm, thus, resultng n hgher prce premums. DEMOGRAPHIC varables ncluded n the estmatng equaton are the farm operator s age (AGE), gender (GENDER), and an ordered dummy to capture dfferent levels of educatonal attanment (EDUDUM, 0 for educatonal attanment at hgh school level or below, 1 for junor college/trade school and some college educaton, 2 for completed bachelor s degree and some graduate study work, and 3 for a completed graduate degree). Age and educaton are crucal factors that nfluence the scale of organc farmng operatons consderng the knowledge-ntensve nature of organc farmng operatons (Jansen, 2000). Jackson s study, on the other hand, cte dfferences between men and women n ther decsons on the acquston and dsposal of ncomes, thus, suggestng that gender dvsons n access and control of ncome can nfluence the management of organc farmng operatons, ncludng labor hrng decsons (1994).

8 SIZE ndcators used n ths study are the percentages of acreage allocated to organc vegetable and gran farmng (PERACRSVEG and PERACRSGR, respectvely). These measures were chosen due to the relatve relatonshp of acreage to crops grown,.e. grans are generally spatally demandng but lax n labor demand, whereas vegetables generally requre much less acreage but are relatvely labor ntensve, even by organc producton standards. INCOME varables nclude an ordered dummy varable for ncome generated from organc farmng operatons (INCDUM) correspondng to classes of ncome representng roughly one quarter of the sample n each. (0 for organc ncome of $4,999 or less, 1 f $5,000 to $29,999, 2 for $30,000 to $99,999, and 4 for ncome contrbutons of $100,000 and above). Also consdered are proportons of total farm ncome derved from organc producton, specfcally of vegetables and grans (PERINCVEG and PERINCGR, respectvely). Income factors logcally enhance the organc farms capablty and flexblty to provde compensaton for off-farm laborers and hence offer the farm operators wth alternatves to maxmze producton effcency and vablty. MARKETING varables consder the effect of two marketng channels, drect to consumer and wholesale, on the farm labor hrng decsons. The percentage of wholesale market sales are captured by the varables PERVEGW and PERGRW for the vegetable and gran operatons, respectvely. Drect to consumer market sales are lkewse represented by PERVEGDTC and PERGRDTC for the vegetable and gran operatons, respectvely. A study by Rapp (1998) on newly transtoned farms emphaszes the nfluence of marketng channels on labor hrng decsons. Hs results ndcate that a

9 hgher relatve share of the organc farms labor force has been utlzed for drect marketng operatons. EXPERIENCE or busness maturty varables such as the total years of farmng (YRSEXP), the rato of the total number of years of organc to total farmng experence (ORGYRSRAT), and the rato of certfed organc farmng to total farmng experence (CERTYRSRAT) are ncluded n the analyses. The mportance of busness maturty on labor hrng decsons s evdent n the results obtaned by Lampkn (1994). Hs study concludes that most organc farmng operatons n the embryonc or transtonng stage often have lmted farmng sklls and are constraned by nadequate captalzaton. These constrants defne ther heavy relance on labor substtuton for captal and mechanzed nputs. PERCEPTION varables were derved from farmers responses on ther outlook for organc producton and market condtons from the growng season. Specfc perceptons of nterests are product prces (PRICEPERCEP) and market demand (DEMPERCEP). These are ordered dummy varables correspondng to the scale used n the survey questonnare where 0 s poor, 1 s far, 2 s good and 3 s excellent prospect for the current year s market condtons. LOCATION dummy varables are ncluded to capture the nfluence of geographcal locaton to the farms labor hrng decsons. The USDA s older classfcaton of producton regons whch recognzed state boundares n defnng the regons s used n ths analyss nstead of the newer scheme for classfyng countes n each state nto major farm resource regons (whch had overlappng states n certan regons). The ten USDA producton regons delneate marked dfferences n croppng

10 decsons, weather patterns and agronomc decsons across geographcal boundares. In ths analyss, the locaton dummes used are NTHEAST (Northeast), LAKE (Lake States), CORNBELT (Corn Belt Regon), NPLAINS (Northern Plans), APPAL (Appalachan), STHEAST (Southeast), DELTA (Delta States), SPLAINS (Southern Plans), and MTNS (Mountan States). The excluded geographcal category s the Pacfc Regon. Ths study wll consder three model versons of the estmatng equaton. Asde from applyng the estmatng equaton to all farm observatons, two subsets of farm data wll be developed based on producton of two target crops: vegetable and gran. The ratonale for ths approach s to solate the effects of the labor and sze requrements of these two domnant enterprses. Vegetable crops are consdered to be very labor ntensve whle gran operatons generally ental relatvely larger acreage requrements. In order to reduce the large number of the orgnal set of explanatory varables to a smaller batch of sgnfcantly mportant ndcators of off-farm labor hrng decsons, a backward elmnaton (stepwse) method under the Tobt regresson approach n Stata wll be appled to all three versons of the estmatng model. Ths procedure starts wth a general Tobt regresson procedure that consders all elgble explanatory varables. The model undergoes several teratons as one varable after another, dentfed as one that contrbutes the least to the model s explanatory power, s dropped from the estmatng equaton untl all remanng varables produce F statstcs sgnfcant at a specfed confdence lmt. In ths analyss, the qualfyng confdence lmt used s 10%. Descrptve Analyss

11 The emprcal analyss s performed wth data obtaned through the Organc Farmng Research Foundaton s (OFRF) fourth Natonal Organc Farm Survey. Ths survey was conducted n sprng 2002 collectng naton-wde data on ndvdual organc farmers growng season. The survey was dstrbuted to ndvdual farmers and certfcaton agences that n turn dspersed surveys to ther own growers. Ths survey conssts of 1034 partcpatng farmers responses from forty-four states wth an overall response rate of 18%. The survey nstrument conssts of eght sectons and ncludes seventy-sx questons, both open and close-ended, several wth sub-sectons. Questons allowed for fll-n type responses, selecton of presented categores and yes/no choces whch lead to the presence of both qualtatve and quanttatve data, as s characterstc of surveys. In ths study open-ended questons were not utlzed n the emprcal analyss. Coverage and samplng sze are estmated at 90% of the actual populaton beng studed. Errors n measurement derved from naccurate or unclear responses are varable throughout the sample, ultmately 32% (332 observatons) of orgnal data were used for the analyss. The OFRF has conducted four natonal surveys snce 1995 however there has not been an accessble record of tme-seres data on any partcular farm, therefore the most recent data s utlzed and restrcted to cross-sectonal analyss. Survey sectons of prmary nterest are those regardng structural farm profles, producton and products detals, marketng and market condtons, and farm household characterstcs. The partcular queston of relevance to ths study s dependent varable concerns the number of laborers hred by an organc operaton over the span of one year. Each farm operator was asked to gve detaled account of each employee (ncludng

12 themselves) hred for labor drectly nvolved wth organc producton. Employees were segregated by famly status (farm famly/household members or non-famly workers), tme of employment (year-round or seasonal) and hours worked per week (full-tme or part-tme). Descrptve analyses for the data used are lsted by subset n table 1.1. Econometrc Analyss The stepwse Tobt results obtaned for the three regresson models are summarzed n table 1.2., ncludng coeffcent estmates, levels of sgnfcance and pseudo R 2. As stated by Johnson and DNardo, t may not always be sensble to nterpret the coeffcents of a Tobt n the say way as one nterprets coeffcents n an uncensored lnear model (1997). Because a Tobt model s censored at the pont y,*, three dervatves are possble, wth respect to any one observaton, determned by E[ * y X], E[ y X], and E[ y X, y >0]. As such, most lterature recommends a decomposton utlzng the mean value of the ndependent varable and the expectatons of y, the observed varable, whch accounts for both the condtonal expectaton (E[ y X, y >0]) and the uncondtonal expectaton (E[ y X]) (Johnson and DNardo 1997; Wooldrdge 2000). The partcular decomposton used n ths study sets y = E[ y X, y >0], therefore the results must be nterpreted wth respect to those farms that hred a postve number of off-farm workers, rather than all farms ncluded n the sample. Ths decomposton addtonally allows Tobt results to be nterpreted as OLS estmates, the margnal effect on the dependent varable resultng from a one unt change n the explanatory varable. These margnal

13 effects as well as the decomposton factor are presented for all sgnfcant varables n table 1.3. Dscusson s separated nto categores by the dataset used. Complete Dataset Ths emprcal model utlzes all avalable observatons and contans 29 of the 33 explanatory varables, excludng those varables pertanng to marketng characterstcs of target crops. Of these varables, 15 were removed from the regresson durng the teratons due to a sgnfcance level below the 90% confdence level. The remanng varable coeffcents are all statstcally sgnfcant from zero, as shown by a two-sded t- test wth at least a 90% confdence level. No demographc characterstcs are shown to be sgnfcant. Relatve to the excluded Pacfc regon the Lake, Northeast, Cornbelt, Northern Plans and Appalachan regons are all more nclned to hre less non-famly labor for all organc operatons. Hred labor also decreases for addtonal percentages n the amount of total farmed land owned. Sngle famles are more apt to hre less labor compared wth all other busness structures, reaffrmng a farm structure dependent on famly labor. Addtonal years of experence and addtonal crops produced add to the numbers of laborers demanded. Years of experence only slghtly ncrease demand, as t mght be nferred experence leads to greater effcency wth only fant needs for nonfamly labor. Overall ncome from organc crops has a postve affect; however as the percentage of ncome derved from grans ncreases, labor demanded falls slghtly. The greatest measure of ncreased demand s from a percentage ncrease n the number of acres devoted to vegetable crops.

14 Vegetable Dataset Ten out of the 31 varables utlzed for ths analyss are found to be sgnfcant although, agan, no demographc characterstcs are ncluded n these sgnfcant varables. Locaton relatve to the Pacfc regon has created mxed margnal affects across the states. The Lake regon are more nclned to hre less labor whereas vegetable farms n the Mountan regon are just as nclned to hre more labor. Only a very slght margnal ncrease n labor s attrbuted to an ncrease n years experence, as well as the percent of vegetable crops sold on wholesale markets. In ths vegetable subset alone do both sze characterstcs have a postve effect on labor demanded, wth percentage of acres devoted to gran crops havng the larger effect. Income derved from organc operatons s consstent n ts effect on labor demand as s percentage of farmed acres owned. Income derved from value-added crops processed on or by organc farm specalzng n vegetable producton s one of the only structural characterstcs n these analyses to mply an ncrease n labor demanded. Grans Dataset Ths analyss conssts of 31 explanatory varables, nne of whch are sgnfcant and two of whch were dropped from the regresson due to constant values. The margnal effect on labor demand by the percentage of acres devoted to vegetables s greater here than n any other data subset. For each ncrease n percentage, there s an ncrease n labor hred

15 by a factor of 68. Ths can only emphasze the extreme dfferences n labor requrements among dfferent commodtes. Followng the prevous subsets, both the percentage of acres owned and the amount of ncome from organc operatons have postve nfluences on non-famly farm labor demand. The only experence characterstc whch s sgnfcant towards a decrease n demand for labor s the rato of years farmng certfed organc to total years farmng organcally on farms prmarly producng gran. Ths can mply a learnng curve assocated wth gran farmng not usually found on the large majorty of other organc farms. Four locaton characterstcs were sgnfcant, all wth the nclnaton to hre less non-famly labor than the excluded Pacfc regon. Summary and Conclusons Ths study provdes key nsghts nto factors affectng an organc farm operator s decson to hre non-famly farm labor and at what quanttes to hre ths labor. Not surprsngly ncome derved from organc producton proved to be a sgnfcant motvatonal factor n all cases. Also expected were sgnfcant levels assocated wth locaton characterstcs, however, there s dffculty n dstngushng whether these regons are sgnfcant due to some set of physcal characterstcs (sol, clmate, etc.) or whether mgrant labor pattern are more accountable. Ths dscrepancy wll requre further analyses. The results also show a negatve correlaton between non-famly labor demand and the percentage of organc acres owned by the farm operator, and although the dummy varable for sngle famly operatons was negatvely sgnfcant n only one sample, t

16 does renforce the pcture of a famly orented and famly operated farm. Concurrently, the level of dversfcaton avalable to all farmers does not seem equal. As shown n the gran subset analyss, an ncrease n producton of a contrastng commodty (vegetables) ncreases labor demand by a magntude of 68, essentally makng ths opton of dversfcaton mpossble. For those farms currently producng vegetables, the same percentage ncrease n gran producton resulted n an ncreased labor demand by a scale of only 12. Retreatng back to the orgnal sample shows a less bleak outlook. As the number of commodtes produced on a farm ncreases, the demand for non-famly labor ncreases at the exact same rate. For every addtonal percentage of ncome derved from valueadded products processed by or for the farm, labor demand doubles. Consder now the drecton of marketng of organc foods, especally the ease of pre-packaged products and extended shelf-lfe of packaged goods. The only marketng characterstc of any statstcal sgnfcance s the percent of vegetables sold wholesale wth a postve effect on labor demanded. Organc farms are ndeed famly farms but wth sgnfcant characterstcs assocated wth ncreases n non-famly labor beng very specfc to operatons of hgher acreage, or those producng more commodtes, wth hgher ncomes and not necessarly more farmng experence, there wll be an nterest n the future of organc goods.

17 Worker Dstrbuton (n=1034) Number of Workers Famly Non-Famly Full-Tme Yearly Full-Tme Seasonal Part-Tme Yearly Part-Tme Seasonal Total Fgure 1.0 Organc Farm Workers Labor Dstrbuton Table 1.0 Mean Values and Standard Errors (n Parentheses) of Explanatory Varables Varable All Vegetable Gran CONVDUM (0.3491) (0.2828) (0.3832) TENURERAT (0.3275) (0.3429) (0.3256) CROPSGRWN (1.4653) (1.6491) (1.5231) PERACRSVEG (0.3285) (0.3879) (0.1212) PERACRSGR (0.3873) (0.3031) (0.2970) PERINCVEG ( ) ( ) ( ) PERINCGR ( ) ( ) ( ) SOLEPROP (0.4482) (0.4367) (0.4653) SPLAINS (0.1626) (0.2047) (0.1324) LAKE (0.3329) (0.2932) (0.4263) STHEAST (0.0775) (0.0851) MTNS (0.3076) (0.2828) (0.3017) DELTA (0.0775) (0.1199) NTHEAST (0.4283) (0.4803) (0.4401) CORNBELT (0.3188) (0.3124) (0.3782) NPLAINS (0.2383) (0.1199) (0.3168) APPAL (0.2013) (0.2602) (0.1699) VAPERDUM (0.4941) (0.5018) (0.4781) PERVEGDTC ( ) ( ) ( ) PERVEGW ( ) ( ) ( ) PERGRDTC ( ) ( ) ( ) PERGRW ( ) ( ) ( ) DEMPERCEP (0.8294) (0.7661) (0.7904) PRICEPERCEP (0.8489) (0.7488) (0.7818) YRSEXP ( ) (9.9750) ( ) ORGYRSRAT (0.3364) (0.2633) (0.3252) CERTYRSRAT (0.2864) (0.2884) (0.2854)

18 FULLTIME (0.4568) (0.4483) (0.4401) OFFFARMDUM (0.5003) (0.5010) (0.5011) INCDUM (1.0206) (0.9538) (0.9776) EDUDUM (1.0025) (0.9838) (1.0443) AGE ( ) ( ) ( ) GENDER (0.3903) (0.4446) (0.3240) n= Table 1.2 Step-wse Tobt Regresson Results All Vegetable Gran Varable Coef. Est. Std. Err. Coef. Est. Std. Err. Coef. Est. Std. Err. AGE R R R APPAL a R R CERTYRSTAT R R b CONVDUM R R R CORNBELT a R a CROPSGRWN R R DELTA R R DD DEMPERCEP b R EDUDUM R R R FULLTIME R R R GENDER R R R INCDUM a a a LAKE a b a MTNS R a R NPLAINS b R b NTHEAST a R b OFFFARMDUM R R R ORGYRSRAT R R R PERACRSGR R R PERACRSVEG b b a PERGRDTC R PERGRW R PERINCGR b R R PERINCVEG R R R PERVEGDTC R PERVEGW b PRICEPERCEP R R R SOLEPROP a R SPLAINS R R R STHEAST R R DD TENURERAT b a b VAPERDUM b R YRSEXP a b R

19 Log lkelhood LR Ch-square Pseudo R Number of Obs R: Denotes a removed varable durng regresson due to p >.10 (not sgnfcant at the 90% confdence level) DD: Denotes a dropped varable due to constant. a, b : Denote statstcal sgnfcance at the 99% and 95%, respectvely. Shaded areas denote varables excluded from the regresson. Table 1.3 Margnal Effects and Standard Errors of Sgnfcant Varables All Vegetable Gran Varable dy/dx Std. Err. dy/dx Std. Err. dy/dx Std. Err. NPLAINS ag TENURERAT CROPSGRWN PERACRVEG CORNBELT ag APPAL a PERINCGR SOLEPROP ag VAPERDUM av LAKE avg YRSEXP INCDUM DEMPERCEP NTHEAST ag MTNS v PERACRGR PERVEGW CERTYRSRAT Y= E(yols yols>0) Y= Y= Y= a,v,g : Denotes dy/dx s for dscrete change of dummy varable from 0 to 1 for all, vegetable and gran, respectvely.

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