Decision to Adopt and Exit Best Management Practices by Dairy Farmers. Larry M. Hall. Krishna P. Paudel. Wayne M. Gauthier. John V.

Transcription

1 Decson to Adopt and Ext Best Management Practces by Dary Farmers Larry M. Hall Krshna P. Paudel Wayne M. Gauther John V. Westra Department of Agrcultural Economcs and Agrbusness 101 Agrcultural Admnstraton Buldng Lousana State Unversty Baton Rouge, LA Phone: Fax: Correspondng Author: Prelmnary Draft - Do not Quote Selected paper prepared for presentaton at the Amercan Agrcultural Economcs Assocaton Annual Meetng, Portland, Oregon, July 29 - August 1, Copyrght 2007 by [Larry M Hall, Krshna P Paudel, Wayne M Gauther, and John V Westra]. All rghts reserved. Readers may make verbatm copes of ths document for commercal purposes by any means, provded that ths copyrght notce appears on all such copes.

2 Decson to Adopt and Ext Best Management Practces by Dary Farmers Abstract Dary farmers n Lousana were surveyed to fnd out the factors leadng these farmers to termnate best management practces. Results ndcated that only few farmers have exted the practces once they adopt those. However, the longevty of best management practces adopton can be ncreased by emphaszng on educaton and targetng to operators who have already been n dary practces for a longer tme perod. Key words: Best management practces, dary, entry, ext, Lousana 2

3 Decson to Adopt and Ext Best Management Practces by Dary Farmers Best management practces (BMPs) are voluntary practces recommended by the USDA under the Envronmental Qualty Incentve Program (EQIP) to overcome nonpont source polluton. Government supports up to 95% of the total cost to mplement these practces but stll the adopton rate of the BMPs are not at the rate that the polcy makers lke to see. The man contenton regardng the adopton has been ts cost whch s prvate n nature and beneft that s publc n nature. Therefore, the adopton and thereafter contnuaton of these practces have been of a serous concern. Most of the past studes on adopton uses probt/logt model to explan the probablty of a frm adoptng a new technology at a tme. There s a lack of study explctly addressng the tme path of adopton whch s an mportant aspect for adopton of envronmental practces lke BMPs whch generally have contract oblgaton for as long as ten years. Dary Producton n Lousana s an mportant agrcultural enterprse contrbutng sgnfcantly to the ncome of farmers n the three-parsh-area of Washngton, St. Helena and Tangpahoa. Dary farmers n the regon are also blamed for envronmental polluton due to whch there has been a closure of popular recreatonal area. Addtonally, ntrogen leachng and volatlzaton and phosphorus runoff from dary operaton and land applcaton of manure have compromsed the ntegrty of ecosystem health n the watersheds encompassng these parshes. Havng stuated on the North of a very productve Lake Ponchartran Basn, dary producton n these parshes s also blamed for the elevated level of N n waterbodes n the basn. To overcome these polluton concerns, dary farmers n the regon are adoptng best management practces wth the assstance from the USDA/NRCS program and cleanng ther manure lagoon more responsbly wth the help of Lake Pontchartran Basn Foundaton fnancal support. 3

4 USDA/NRCS n collaboraton wth the Lousana State Unversty Agrcultural Center have recommended eghteen dfferent best management practces for the farmers to adopt to address envronmental concerns n the regon. Out of these eghteen best management practces, Paudel et al. report that farmers have adopted waste management lagoon and waste management practces extensvely. However, the other best management practces have not been adopted and efforts need to be put to ncrease the adopton of these BMPs n the dary farmng operaton. In addton to the low adopton of BMPs, there s also concern that farmers once adopted may not contnue these practces because some of the practces are costly and BMPs adopton s done voluntary. Addtonally, the cost share contractual agreement oblgates them to adopt these practces for maxmum of 10 years. Our objectve n ths paper s to fnd the characterstcs of the farmers who have adopted best management practces and stayed adoptng those practces. We also dentfy the characterstcs of farmers who have adopted these practces n the past but had snce exted from adoptng the BMPs. We used survey data collected from Lousana dary producers to dentfy the varables determnng the entry and ext from adoptng best management practces. Lterature Revew Adopton of BMPs may be nfluenced by market structure. Research nto adopton of nnovatve technology showed those frms not partcpatng n a concentrated market wll adopt the technology sooner than frms who do not ft that descrpton (Levn et al.). The Lousana dary ndustry may be classfed as low concentraton snce the ndustry s composed manly of many 4

5 small farms. Therefore, these producers should adopt best management practces early f there s proft to be made from adoptng the practces. Theoretcal lterature has recognzed that ncentve based polces can acheve a hgher adopton rate compared to conventonal regulatons such as technologcal or performance standards. BMP adopton s an ncentve based approach as a cost-share percentage pad by the Federal government provdes the ncentve for adopton. Kerr and Newell showed that adopton of technology ncreased as cost to the frm falls. They further added that frms wth lower benefts and hgher costs wll adopt more slowly. BMP adopton by the dary farmers should ncrease f more cost share s provded to the dary producers to adopt these envronmentally frendly practces. Socoeconomc characterstcs of the dary farm operator may have an mpact on BMP adopton. Gould and Saupe researched these factors and determned that nvestments n human captal yelded postve and measurable results. The level of educaton of the dary farm s prncpal operator may have an mpact on entry or ext of adopton. The use of a personal computer may ncrease nformatonal awareness concernng envronment benefts of adopton and thus ncreasng human captal. On-the job experence s another way to ncrease human captal concernng dary farm operaton A barrer to entry may be the cost of captal to mplement the BMP. MacDonald found that captal commtment deters both entry and ext of frms nto and from the U.S. food manufacturng ndustry and sunk physcal captal costs acts as a general barrer to moblty of resources. Even wth a substantal governmental cost-share, the dary producer may refuse BMP mplementaton. 5

6 Sze of the dary farm may play a role n entry and ext of BMP adopton. Dunne and Roberts determned n frm entry and ext patterns n U.S. manufacturng ndustres that there was sgnfcant varaton n the entry patterns and subsequent sze and ext patterns for dfferent categores of those entrants. Larger frms that enter are less lkely to ext than smaller frms. Baldwn and Goreck showed that ext s not solely a small-frm phenomenon. Larger sze frms dd not experence ext (close down) rates of zero. Ths study used estmated net farm ncome as a proxy for sze (captalzaton) to determne the relatonshp between farm sze and BMP entry and ext. Hopenhayn developed and analyzed a dynamc stochastc model for a compettve ndustry that endogenously determned entry and ext and ntroduced the term statonary equlbrum. Ths concept mples that n the steady state as many frms were enterng as extng as well as job creaton and destructon. Method To address BMPs adopton decson at frst and then ultmately decde to termnate BMPs n a farm, we employ a proportonal hazard model. A proporton hazard model helps to analyze the effect of economc and regulatory varables on adopton and ext decson by dary producers wth respect to adoptng new envronmental frendly technology. The hazard model s approprate because our focus s on the tmng of new technology. We followed Wooldgrdge (2002) to develop our theoretcal model. Indcate an ntate state as an adopton of a BMP by a dary farmer. T s the tme measured n years untl the dary farmer dscontnues the BMP n hs farm. The cumulatve dstrbuton functon of T s defned as 6

7 F(t) = P(T <t ), here t denotes a partcular value of T. The survval functon, defned as the probablty of a farmer adoptng BMP past tme t, s s(t) = 1-F(t) = P(T>t). We assume a random draw from dary producers n Lousana. Let a Є [0,b] denote the tme at whch dary farmer adopts BMP, let t * denote the length of tme whch s/he adopts a gven BMP and let x denote the vector of observed explanatory varables. Assume that t * has a contnuous condtonal densty functon f ( t x ; θ ); t 0 where θ s the vector of unknown parameters. To account for the rght sensorng, we assume that the observed duraton t s obtaned as t = mn( t *, c ). We assume that condtonal on the covarates, the true duraton s ndependent of the startng pont a and the censorng tme c. The condtonal dstrbuton D(.) * * can be wrtten as D ( t x, a, c ) = D( t x ). Lettng d be a censorng ndcator (1/0 varable), the condtonal lkelhood for observaton can be wrtten as: f ( t x, θ d 1 d θ ) [1 F( t x ; ]. If we have data on (t,d,x ) for a random sample of sze N, the maxmum lkelhood estmator of θ s obtaned by maxmzng: N = 1 { d log[ f ( t x ; θ )] + (1 d )log[1 F( t x ; θ )]} The coeffcents are then estmated usng a maxmum lkelhood approach. We estmated the parameterzed baselne hazard approach for adopton and ext decsons. For robustness of the model, we conducted senstvty analyses assumng that a hazard functon possesses exponental, lognormal, log logstc, and Webull densty functons. These assumptons allow for the possblty that the baselne hazard ncreases or decreases over tme. 7

8 Data Data were collected usng survey of dary farmers. The survey was conducted usng the talored desgn method (Dllman). A focus group, consstng of dary farmers and county agents from the three parshes n the prncpal mlk producton area of Lousana, was used to help desgn and pre-test the survey nstrument. The survey was maled to all 325 Lousana dary farmers wth an opton to complete the survey onlne. Two weeks after the ntal malng, non-respondents were contacted wth a postcard remnder request to complete the survey. A second round of surveys was maled to dary farmers three weeks after the frst round. To further encourage partcpaton, payments of $10 per survey for the frst ffty fully completed surveys were promsed along wth an opportunty for all respondents to qualfy for a $250 lottery cash prze drawng. The sze and number of payments offered were lmted by the avalablty of funds. A graduate student repeatedly contacted dary farmers by phone requestng survey completon. The twelve-page survey had four dstnct sectons ncludng dary manure dsposal, mlk reducton programs, dary best management practces (BMP) adopton, and soco-economc characterstcs of the prncpal operator. One secton of the survey asked questons related to the adopton of best management practces (BMP) n terms of: 1) cost shares and EQIP ncentve payments; 2) sources of nformaton most mportant n makng the adopt/non-adopt decson; and 3) the role of USDA-NRCS n the responder s adopton or non-adopton decson. Eghteen BMPs dentfed by USDA-NRCS as most approprate for Lousana dary farms were dentfed n terms of cost-share or EQIP ncentve payment per practce. A common format used n presentng each of the eghteen BMP practces and n elctng responses s follow: 8

9 Resdue Management or Conservaton Tllage Practces (NRCS code 329A, B, C): A system desgned to manage the amount, orentaton and dstrbuton of crop and other plant resdues on the sol surface year round (such as Notll, Strp-tll, Rdge-tll and Mulch-tll systems). Incentve payment =$10-15 per acre, 100 acre lmt, 2-3 years. Have you adopted ths BMP on your farm? [ ] YES If YES, n whch year? If stopped, n what year? Total Incentve Payment receved for ths BMP $ per acre [ ] NO If NO, would you adopt ths BMP on your farm? [ ] YES [ ] NO [ ] Not sutable for my farm The BMP was descrbed n the survey and dentfed wth ts USDA-NRCS code number and an estmated reference cost. The BMP reference cost was an average cost based on adopton nformaton of the BMP n Lousana between 1997 and Results The model specfed n the method secton s estmated usng the SAS software. We estmated the rght sensored model assumng the hazard densty functon as Webull, log logstc, logstc, log normal and gamma functons. Descrptve statstcs of the results ndcated that there were 133 observatons. Only four of these eghteen BMPs were adopted and then later on dscontnued by operators. Some of the BMPs were adopted as early as Observng closely, we found that almost half of the BMPs have been adopted by the farmers even before the start of the EQIP program n The average retenton tme for the BMPs was close to 15 years. We have also found that more than half of the farmers own computers. Almost all of the operators are male and one of the spouses worked off-farm. Ths s perhaps to supplement ncome from 9

10 dary farmng. Addtonally, twenty fve percent farmers sad ther farm s close to a subdvson. Ths ndcates contnuous development of subdvsons n these parshes probably because people from New Orleans have been movng up to these parshes. Results from survval analyss were not encouragng as almost all of the parameters estmated came out to be nsgnfcant. Therefore, we are not gong to dscuss these results. However, the results are presented n Table 2. Because of the nsgnfcance of the parameters estmated, we resorted to an OLS method to descrbe whether the tme duraton a BMP has been adopted has any relatonshp wth farm and operator characterstcs. We have seres of BMPs wth each adopted at dfferent length of tme by the dary farmers. We regressed ths duraton (or length of tme a BMP s adopted n the farm) to four explanatory varables. Most of these varables are also the varables that Paudel et al. have selected n ther study. The frst varable used s the number of years the operator has worked n the farm. If an operator has been famlar wth the dary farmng, s/he would know the practces that would help to reduce polluton and also help to abde by the exstng envronmental regulatons. Educaton s the second varable we have chosen as an explanatory varable. It s lkely that hgher educated ndvdual would be more conscous about envronment and would therefore adopt BMPs for a longer perod. Therefore, we expect ths varable to have a postve sgn. EQIP s a bnary varable wth adopton done before 1997 gettng 0 value or 1 otherwse. Ths s the year that the government has started the EQIP program. Income share s a contnuous varable ndcatng the share of ncome from a dary operaton. The more dependent s a farmer n a dary operaton, the less lkely s that he would have extra money to adopt BMPs or to that matter able to cost share the needed expenses to adopt BMPs. Therefore, we hypotheszed a negatve coeffcent assocated wth ths varable. 10

11 Our results provded sgns of the parameters consstent wth our a pror belef. However, we dd not fnd age and ncome-share to be sgnfcant. EQIP and educaton varables had postve sgns. EQIP ndcated that f a BMP has been adopted after 1997, t s less lkely to be adopted for a long tme. Ths may be because our observatons are rght sensored after Or t could be that farmers would mplement the practce and termnate the practce after they are no longer oblgated to contnue t. Educaton ncreases the longevty of BMP adopton. A farmer who has a college educaton would lke to ncrease the adopton duraton by four years. Conclusons We examned the behavor of dary farmers to adopt or ext BMP practces. We estmated rght sensored hazard model but the parameters of the model were found to be nsgnfcant. When the duraton of BMP adopton s regressed on age that operator has been n a dary farmng practce, educaton of the operator, a bnary EQIP varable and ncome share, we found consstent sgn across these parameters. We also found educaton to have a postve sgnfcant effect n the longevty of adoptng a gven BMP practce. Therefore, ths study ndcates a need to target educated farmers to promote best management practces to get the most beneft. Addtonally, longer the ndvdual has been n a dary busness, he s more receptve to adoptng these envronmental practces. 11

12 Table 1. Descrptve Statstcs: ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Varable Label N Mean Std Dev Mnmum Maxmum ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Entry Entry Ext Ext d2a d2a d3a d3a retenton age age educaton computer male offtme subdvson netncome censor ols ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 12

13 Table 2: Parameter Estmates PHREG Log- Log- Varables OLS PHREG (Hazard) Webull logstc Normal Gamma Intercept Age Educaton EQIP Income-share Scale Webull/Gamma

14 References Baldwn, J. R., and P. K. Goreck. Frm Entry and Ext n the Canadan Manufacturng Sector, The Canadan Journal of Economcs 24(1991): Dunne, T., M. J. Roberts, and L. Samuelson. Patterns of Frm Entry and Ext n U.S. Manufacturng Industres The RAND Journal of Economcs 19(1988): Gould, B. W., and W. E. Saupe. Off-Farm Labor Market Entry and Ext Amercan Journal of Agrcultural Economcs 71(1989): Hopenhayn, H. A. Entry, Ext and Frm Dynamcs n Long Run Equlbrum Econometrca 60(1992): Kerr, S., and R. Newell. Polcy-Induced Technology Adopton: Evdence from The U.S. Lead Phasedown Journal of Industral Economcs 51(2003): Levn, S.G., S. L. Levn, and J. B. Mesel. A Dynamc Analyss of the Adopton of a New Technology: The Case of Optcal Scanners The Revew of Economcs and Statstcs 69(1987): MacDonald, J. Entry and Ext on the Compettve Frnge Southern Economc Journal 52(1986): Paudel, K.P., W. Gauther, J. Westra, and L. Hall. Factors Influencng and Steps Leadng to the Adopton of Best Management Practces by Lousana Dary Farmers. Manuscrpt, Lousana State Unversty, Wooldrdge, J.M. Econometrc analyss of cross secton and panel data. The MIT Press, Cambrdge, MA,