Unversty of Kentucky UKnowledge Lews Honors College Capstone Collecton Lews Honors College 2014 The Intal Phases of a Consstent Prcng System that Reflects the Onlne Sale Value of a Horse Curran A. Prettyman Unversty of Kentucky, alexa.prettyman@gmal.com Clck here to let us know how access to ths document benefts you. Follow ths and addtonal works at: https://uknowledge.uky.edu/honprog Part of the Appled Statstcs Commons, Other Anmal Scences Commons, and the Statstcal Models Commons Recommended Ctaton Prettyman, Curran A., "The Intal Phases of a Consstent Prcng System that Reflects the Onlne Sale Value of a Horse" (2014). Lews Honors College Capstone Collecton. 13. https://uknowledge.uky.edu/honprog/13 Ths Artcle s brought to you for free and open access by the Lews Honors College at UKnowledge. It has been accepted for ncluson n Lews Honors College Capstone Collecton by an authorzed admnstrator of UKnowledge. For more nformaton, please contact UKnowledge@lsv.uky.edu.
THE INITIAL PHASES OF A CONSISTENT PRICING SYSTEM THAT REFLECTS THE ONLINE SALE VALUE OF A HORSE Prepared for Dr. Bob Coleman EQM 490 Secton 002 Unversty of Kentucky Prepared by Alexa Prettyman alexa.prettyman@uky.edu 14 December 2014
ABSTRACT Horses are one of the most unquely prced commodtes. Ths document provdes a soluton to an ndustry-wde weakness of nconsstent prcng and confuson. In the followng report, an evaluaton of the ndustry flaw s presented, an econometrc approach s descrbed n full, and a soluton s proposed usng nsght ganed from a regresson analyss. Ths report uses an econometrc approach to determne the mpact of hunter jumper horse qualtes on nternet sale prces. Data s compled from bgeq.com for seventy-eght horses n the states of Illnos, Indana, Kentucky, Mchgan, and Oho. A lnear regresson analyss for twelve varables establshes that a horse s age, breedng, athletcsm, dscplne, and mport status are statstcally sgnfcant on the 95% confdence nterval. Heght, colorng, gender, and show experence are not statstcally sgnfcant on ths nterval. Ths report provdes benefcal nformaton to breeders, traners, buyers, and sellers assocated wth the hunter jumper sport and hopefully wll be used as a reference for smlar research n other areas of the equne ndustry.
TABLE OF CONTENTS Introducton... 1 Lack of a Prcng System... 1 The Postves...2 The Negatves...2 Econometrc Analyss of Prces... 3 Varables...4 Data Sources...5 Regresson Equaton...5 Data Analyss...7 Regresson Results...9 Further Research...11 Solutons... 12 Concluson... 13 Bblography... 14 Appendxes... 15 Appendx A- Bgeq.com example advertsement...15 Appendx B- Descrptve statstcs tables generated n Excel...16 Appendx C- Regresson Analyses...17
INTRODUCTION Over the last 4500 years, the horse has been a source of proten, mode of transportaton, tool of farmng, and commodty of recreatonal actvty. When frst domestcated, horses were valued by the amount of meat they provded. Progressvely horses have become valued and bred for ther usefulness, tranablty, and compettveness. The present-day varety n breeds, confrmatons, colorngs, and abltes s the result of a large equne ndustry. The equne ndustry has numerous subgroups (or worlds, as they wll be referred to later), such as hunter jumper, dressage, eventng, Western, and racng. Varyng sports and uses result n dfferent preferences and values. The prcng system of horses s nconsstent and prmarly based on the opnons of the seller and consumer whch allows much freedom and negotaton between sports and compettors, but also creates dffculty for new people nterested n jonng the ndustry to gan an understandng of the desred characterstcs of a horse and ts value. LACK OF A PRICING SYSTEM Each sport has dstnct and unclear characterstcs that make the horse compettve and of greater value. For example, the same 16 hand, 8 year old, grey thoroughbred geldng may be worth $12,000 n the hunter jumper world, $5,000 n the dressage world, $30,000 n the eventng world, $2,000 n the Western world, and $500 n the racng world for reasons that are ambguous. Wthout a prcng system that recognzes and values tranng and breedng, these numbers seem random and made up. An equne prcng system has the potental to postvely mpact traners, consgnors, buyers, and breeders. 1
The Postves The benefts of a consstent prcng system are contngent upon the future of the equne ndustry. If ndustry expanson to a new target market s expected, then a prcng system s necessary to help people understand how horses are valued. Prces vary between sports, among traners, and wthn stables. For example, a traner at a hunter jumper faclty may be offerng a range of horses for sale that cost anywhere from $10,000 to $100,000. Wthout a method to value breedng and tranng, someone wth lttle horse knowledge or experence would be very confused as to how a faclty can offer two smlar lookng horses at dfferent prces. A prcng system provdes nformaton for people outsde the ndustry to gan knowledge. Furthermore, each equne professonal values tranng and breedng dfferently. A prcng mechansm suggests the approprate values based on current ndustry prces and trends. Attrbutng a dollar amount to coat color, number of whte markngs, and heght allows breeders to better select on the trendy characterstcs. Breeders already select for some proftable trats, but a prcng system wll allow them to better predct ther profts based on ther current and future foals. A prcng system attempts to quantfy people s opnons, whch s mportant amongst subjectvty. The Negatves Unfortunately wth every dea, there are drawbacks. A prcng system could concentrate prces too much preventng lower ncome people from partcpatng. Currently, wthout prce regulatons, people of all fnancal backgrounds are able to purchase and compete n the ndustry. Secondly, there may be less negotaton power whch results n someone beng unhappy. The buyer s dsapponted when they cannot talk the prce down, and the seller s dsapponted when they do not make the sale. In the absence of rules, unwrtten rules and expectatons emerge. 2
People decde ther own prces based on personal preferences and estmated expectatons. The freedom to determne prces may result n greater satsfacton and profts. For example, sellers can sell a horse at any prce someone s wllng to pay, and buyers can buy a horse for any prce someone s wllng to accept, although wastng tme for the perfect prce s not always the wsest choce. Lastly, an ndustry-wde prcng system may prevent horses from swtchng careers at affordable rates. After the racng career of a $1.5 mllon thoroughbred yearlng, an addtve prcng system would expect the horse s prce to ncrease even though ts experences and accomplshments are no longer relevant to ts new career. Most hunter jumper and eventng rders are not gong to pay mllons of dollars for an ex racehorse that has no jumpng experence. The prcng system must be confgured n a way that recognzes career changes and reevaluates the horse s worth n a new sport. For starters, a prce analyss should be conducted wthn each sport to more consstently value tranng and breedng and to learn whch physcal characterstcs strongly nfluence prce. A prcng system wll provde a gude as to how much people should expect to receve or pay for certan qualtes, but does not need to be the ultmate determnant of prce. ECONOMETRIC ANALYSIS OF PRICES An econometrc analyss wll be useful n ganng and promotng a better understandng of the prcng system, branstormng future resolutons, and creatng consstency. Econometrcs s the applcaton of mathematcs and statstcal models to economc data that ams to gve emprcal content to economc relatons. The purpose of ths analyss s to help horse owners, buyers, and breeders value a horse s tranng and physcal characterstcs more approprately. 3
Ths analyss wll provde a better awareness of whch equne characterstcs are and are not valuable n the hunter jumper world based on current sale advertsements. Varables An observaton n ths study s a horse lsted for sale on bgeq.com n Zone Fve durng October and November of 2014. As defned by the Unted States Hunter Jumper Assocaton (USHJA), Zone Fve conssts of Illnos, Indana, Kentucky, Mchgan, and Oho. 1 There are about 15-20 horses from each state asde from Indana, resultng n 78 observatons total. Equne characterstcs that affect a horse s usablty and possbly value, such as age, heght, gender, breed, colorng, tranng and showng experence, are recorded as the ndependent varables. Tranng further covers the horse s jump heght experence and whether the horse s capable of gettng lead changes. A lead change occurs when the horse s canterng and swtches drectons. Horses are judged on ths skll. Other ndependent varables nclude whether the horse competes n the hunter dvsons and whether the horse has been mported. These ndependent varables are expected to have some nfluence on nternet ad prces. Prce range s the dependent varable beng examned n ths analyss. There are seven possble values for the prce range varable. A value of one refers to a horse that s valued less than $9,999, two refers to a horse that s valued between $10,000 and $19,999, three refers to a horse that s valued between $20,000 and $39,999, four refers to a horse that s valued between $40,000 and $59,999, fve refers to a horse that s valued between $60,000 and $79,999, sx refers to a horse that s valued between $80,000 and $99,999, and seven refers to a horse that s valued greater than $100,000. Realstcally, a specfc prce would be the varable of nterest 1 About Zone 5, Unted States Hunter Jumper Assocaton, accessed November 2, 2014, http://www.ushja.org/zones/zone5.aspx 4
because to some buyers and sellers, the dfference between $45,000 and $55,000 s the refusal of a purchase or sale. However, due to the lack of specfcally prced horses, prce ranges wll be used as a substtuton. Data Sources Data n ths study s collected from bgeq.com, one of the frst, most well-known hunter jumper horse classfed stes. The ste allows the user to search horses by locaton, prce range, sze, breed, and even name. After enterng search crtera, advertsements are lsted n reverse chronologcal order of postng. The more recent advertsements appear at the top of the page and the older ones appear towards the bottom. Bgeq.com provdes advantages over other equne sale stes, such as horsetopa.com, dreamhorse.com, and equne.com, because many of the horses are lsted by top tranng facltes and have smlar qualtes and careers. When brefly searchng on equne.com, there are horses of all sorts of abltes, such as top dressage horses, racng prospects, and hunter jumpers. Presently, ths study s only focused on the value of hunter jumper horses. Lastly, the varables dentfed earler can be readly found on bgeq.com, but not the other stes. Appendx A provdes a screenshot of an advertsement on bgeq.com. Regresson Equaton PRICERANGE AGE HEIGHT GELDNG WARMBLD BAYGRAY WHITEMK TRAINYRS 7 0 1 SHOWEXP JUMPHT LEAD HNTR IMPORT 8 2 9 3 10 4 11 5 12 6 AGE: advertsed age n years HEIGHT: advertsed heght converted from hands to nches (4 nches n a hand) GELDNG: equals 1 f geldng and 0 f mare or stallon WARMBLD: equals 1 f warmblood breed and 0 f not (.e. Thoroughbred, Quarter Horse, Araban) BAYGRAY: equals 1 f bay or gray color and 0 f not WHITEMK: number of whte markngs TRAINYRS: equals 1 f traned and 0 f not SHOWEXP: equals 1 f 3 or more years of showng and 0 f less than 3 years of showng JUMPHT: advertsed jump heght n feet LEAD: equals 1 f lead changes and 0 f not HNTR: equals 1 f hunter and 0 f jumper or equtaton IMPORT: equals 1 f mported and 0 f not 5
Most of these varables drecton of nfluence on prce range s predctable. Expectedly, as a horse s age ncreases ther value ncreases due to addtonal tranng and experence, untl they reach a certan age that requres more mantenance n whch ther prce decreases. People have the mpresson that taller horses are more athletc, so the heght varable s expected to postvely nfluence prce. For ths analyss, pones 2 were excluded from the observatons because much of ther value depends on the kd safe factor whch s not easly measured. There s an assumpton that geldngs are valued hgher than mares because of ther easy gong temper. Ths gender varable s expected to postvely nfluence prce. Generally, warmbloods are more compettve and sought after n the hunter jumper sport than thoroughbreds and quarter horses, so ths varable s expected to postvely nfluence prce as well. People prefer certan colors and markngs, even though these trats do not contrbute to athletcsm. Accordng to Bob Avla, a professonal horseman n the quarter horse world, bays and grays are always popular even amongst the trendy colors. 3 Ths analyss wll help determne whether that assumpton s accurate by comparng bay and gray horses to other colored horses. If the assumpton s true, bay or gray horses wll be more expensve than another colored horse. The number of whte markngs, whch measures flashness, s used to determne f people prefer horses wth a lot of whte markngs over sold colored horses. Ths value s determned by lookng at the pctures posted wth the advertsement; appendx A can be used as an example. Gray horses are recorded as havng no whte markngs, unless ther markngs are easly dstngushed. The maxmum number of whte markngs a horse may have s seven. Each leg 2 Pones are rdden by chldren and are less than 14.2 hands (58 nches). They do not compete aganst horses. 3 Bob Avla and Sue Copeland, Be a $mart Horse Buyer (Gathersburg, MD: Horse and Rder Magazne, 2007), 4. 6
markng, no matter the length, counts as one, and the head could have a maxmum of three markngs. For example, a star, strp, and snp count as three separate markngs. A blaze, even though normally the entre length of the face, typcally counts as one markng but sometmes two f there s excessve whte on the muzzle. A traned and experenced show horse wll be more expensve than an untraned green horse. In Be a Smart Horse Buyer, Avla nssts that people consder nvestng ther money n a broke horse rather than a green one due to the unexpected outcome and expenses along the way, such as tranng and boardng. 4 The more athletcsm and tranng, whch s ndcated by the ablty to jump hgh and do lead changes, the more expensve the horse. The jump heght and lead change varables are predcted to have postve nfluences on prce range. Typcally, hunter horses are easer to rde than jumpers, so the hunter varable s expected to postvely nfluence prce. However, a grand prx 5 horse wll stll sell for the bg bucks. Fnally, a lot of sellers expect to get more for ther mported horses because there s a stgma that horses from Germany and Canada are traned by better professonals. Addtonally, mported horses cost more after transportaton and quarantne fees. The mport varable s predcted to postvely mpact prce range. Ths study wll reveal the valdty of the varous assumptons that exst n the hunter jumper world and wll dentfy the level of mpact these twelve characterstcs have on a horse s prce. Data Analyss A descrptve analyss of the varables for the 78 horses yelded that the average horse for sale on bgeq.com n Zone Fve s a nne year old standng at 16.1 hands wth 2.75 markngs that 4 Bob Avla, 51. 5 A grand prx s the hghest level jumper class. 7
jumps 3 3 and s lsted for sale at $30,000. In ths study, 69% are geldngs, 63% are warmbloods, 63% are ether gray or bay, 51% have three years or more of show experence, 82% have lead changes, 65% are shown n the hunters, and 12% are mported. For a more detaled analyss, refer to appendx B whch presents the descrptve statstcs charts for each varable bult n excel. Data analyses not only gve a better understandng of each varable but are conducted to dentfy potental problems of multcollnearty and lack of varaton. Multcollnearty and lack of varaton are problematc n regresson analyses because they deflate the t-statstcs, whch results n statstcal sgnfcance beng represented ncorrectly. Also, multcollnearty, meanng two varables are hghly related, falsfes the strength of the overall equaton. Multcollnearty can be recognzed by examnng the correlaton coeffcents among the ndependent varables n the fgure below. Any correlaton coeffcents over ±.75 pose a problem. The hghest pars of correlated ndependent varables are show experence and age and jump heght and hunter at values of.59 and -.48, respectvely; therefore, multcollnearty s not a concern for ths data. 8
Prce Range Prce Range Seventy sx of the 78 horses n ths sample have tranng whch lacks varaton, so the results pertanng to tranng years are not helpful. Addtonally, snce jump heght, lead changes, and show experence can be measurements of tranng, the tranng years varable s excluded from the regresson analyss. Wth mnor adjustments, a regresson analyss presents helpful nformaton to sellers, traners, buyers, and breeders. Regresson Results A total of four regresson analyses were completed wth the second test yeldng the best results. All four analyses can be found n Appendx C. Analyss one ncluded the varable tranng years. Analyss two vared from analyss one because the tranng years varable was excluded due to ts lack of varaton. Analyss three and four tred to recognze f age and heght have a quadratc relatonshp on prce range. The graphs below show the dstrbutons of the data ponts and a hand drawn curve. On the left s age versus prce range, and on the rght s heght n nches versus prce range. 8 8 6 6 4 4 2 2 0 0 5 10 15 20 0 55 60 65 70 75 Age(years) Heght n nches After runnng the thrd analyss, whch consdered both varables beng quadratc, and the fourth analyss, whch only had heght represented as a quadratc varable; the strength of the equaton dd not ncrease nor dd ether of these varables statstcal sgnfcance. In fact, analyss three further proved that wth age a horse s value decreases. 9
Regresson two results are provded to the rght and values of nterest have been hghlghted. The lnear equaton of varables s a strong representaton of the varaton n prce range, and sx ndependent varables are statstcally sgnfcant at the 95% confdence level. The F stat equalng 20.686 s hgh whch means that the regresson model explans a statstcally sgnfcant amount of varaton n prce range. Furthermore, 74% 6 of the Regresson Statstcs Multple R 0.8804 R Square 0.7752 Adjusted R Square 0.7377 Standard Error 0.9219 Observatons 78 ANOVA df SS MS F Sgnfcance F Regresson 11 193.404 17.582 20.686 2.51E-17 Resdual 66 56.096 0.850 Total 77 249.5 Coeffcents Standard Error t Stat P- value Lower 95% Upper 95% Lower 99.0% Upper 99.0% Intercept 0.84 3.95 0.21 0.83-7.04 8.72-9.63 11.31 AGE -0.15 0.05-3.28 0.00-0.24-0.06-0.28-0.03 HEIGHT -0.07 0.07-1.01 0.32-0.20 0.07-0.24 0.11 GELDNG 0.38 0.26 1.45 0.15-0.14 0.90-0.31 1.07 WARMBLD 1.47 0.26 5.74 0.00 0.96 1.98 0.79 2.14 BAYGRAY 0.31 0.25 1.26 0.21-0.18 0.80-0.34 0.96 WHITEMK 0.11 0.06 1.90 0.06-0.01 0.22-0.04 0.25 SHOWEXP 0.16 0.29 0.56 0.58-0.41 0.74-0.60 0.93 JUMPHT 1.66 0.32 5.13 0.00 1.01 2.30 0.80 2.51 LEAD 0.87 0.31 2.78 0.01 0.24 1.49 0.04 1.70 HNTR 0.60 0.28 2.18 0.03 0.05 1.15-0.13 1.33 IMPORT 1.19 0.36 3.35 0.00 0.48 1.91 0.25 2.14 varaton n prce range can be explaned by the eleven ndependent varables. The coeffcents column of the table shows how much each ndependent varable affects prce range, holdng the other varables constant. For example, jumpng one foot hgher can ncrease a horse s prce range by 1.66 ponts. Ths ncrease would make a $20,000 horse worth about $40,000, holdng all other varables constant. Another nterpretaton, for a qualtatve varable, s a horse wth three or more years of show experence wll be.16 prce ranges hgher than a horse wthout three years of show experence. 6 Adjusted R Square value 10
The characterstcs that sgnfcantly mpact prce range at the 95% confdence level, dentfed n blue, are age, warmblood, jump heght, lead change, hunter showng, and mport. The jump heght, lead change, and hunter varables are a result of effectve tranng. Ths model can be used to more accurately value and apprecate tranng. Although geldngs, bay or gray colorng, number of whte markngs, and showng experence postvely affect prce, they are not statstcally sgnfcant. In other words, havng these characterstcs does not ensure a prce ncrease 95% of the tme, but they may help seal the deal more quckly. Further Research Even wth such promsng numbers, there s much opportunty for research expanson to more confdently beleve the results. The frst step for future research wll be to examne each zone of competton as specfed by USHJA. The east coast zones have more horses lsted than Zone Fve. Increasng the sample sze yelds more power n statstcal analyses. Furthermore, states on the east coast have a hgher standard of lvng than the states n the md west. Understandng how ncome affects horse sales provdes another area of research. For the bref tme gven to complete ths analyss, bgeq.com was the easest ste to comple and record the necessary nformaton. In the future, wth more tme and newly defned varables, utlzng the other equne sale stes may potentally ncrease varaton among horses, whch provdes analytcal advantages. Lastly, ths study can be expanded across all equne sports. As a startng pont, each sport should complete ther own analyss to create consstency. Then, the next step s to combne all equne sports and analyze how prces vary between each sport. Results from ths research wll 11
provde the entre ndustry wth better value expectatons and potentally allow someone outsde the ndustry to have a better understandng of prcng technques and desrable characterstcs. SOLUTIONS In realty, ths ssue most lkely wll not be addressed. Many professonal traners probably do not recognze nconsstent prcng as a problem or have already realzed ther value of tranng. If nothng s done to create a prcng system, people wll contnue buyng and sellng horses va current tactcs. The current practces can have benefts and drawbacks dscussed earler. Indvduals wll be allowed to contnue valung characterstcs how they lke and the market wll have ultmate control over the prces. For example, f a breeder s especally nterested n chestnut horses, as long as the demand exsts, they can contnue to breed for ths characterstc wthout the fear of these horses beng less than the bay or gray horses. Alternatvely, as the ndustry grows, equestrans wll seek out more busness from the outsde world. Some salesmen wll lke the dea of a consstent prcng mechansm due to ts attractveness to buyers. For example, magne not knowng anythng about horses but wantng to try a new hobby. Where would one begn ther search? The nternet, books, and other professonals are one place to start, but a prcng system s smple, understandable, and provdes consstent feedback. In the automoble ndustry, there s a prce estmatng ste called Kelley Blue Book. Sellers can enter ther car s make, model, year, mleage, and addtonal features to get a rough estmate of the value of ther car. 7 In the future equne ndustry, wth a smlar ste, sellers can 7 Kelley Blue Book, Kbb.com, accessed November 6, 2014. 12
enter ther horse s breed, sport, age, showng experence, heght, and other characterstcs to get a rough startng prce for ther horse. A prce estmatng ste for horses provdes more consstent startng prces and a better understandng of valuable characterstcs n the equne ndustry. Ths system would be mplemented usng results ganed from the econometrc analyss. As a user enters characterstcs that are statstcally sgnfcant an algorthm runs to estmate a prce. For characterstcs that are not statstcally sgnfcant, a dollar range for the characterstcs contrbutons to prce wll be provded. Ths system s a useful tool n provdng buyers wth more realstc cost expectatons and sellers wth a reassurance that they are valung ther horses correctly. CONCLUSION The econometrc analyss shows that a traned geldng wth lead changes and show mleage s more valuable than a prospect flly. Recognzng the desrable aspects of horses wll make them easer to market and sell. Valung a horse at the rght prce and makng a fast sale s more proftable than undervalung or overvalung the horse. A consstent prcng system not only helps the sellers wthn the ndustry make fast proftable sales, but t also ensures that nterested outsders have less rsk and entry barrers. If consstency wthn the hunter jumper world proves proftable, then there s reason to beleve that a consstent prcng system across all equne sports wll allow for a more proftable ndustry. Imagne f professonals n the equne ndustry made a proft whle lovng ther work. 13
BIBLIOGRAPHY About Zone 5. Unted States Hunter Jumper Assocaton. Accessed November 2, 2014. http://www.ushja.org/zones/zone5.aspx. Avla, Bob and Sue Copeland. Be a $mart Horse Buyer. Gathersburg, MD: Horse and Rder Magazne, 2007. Bgeq.com. Kelley Blue Book. Kbb.com. 14
APPENDIXES Appendx A Bgeq.com example advertsement Usng ths advertsement, data was compled n an excel workbook as follows: Horse Name: Deuwe ZF Age: 6 Heght: 16.2 Prce: 20-39.999 Geldng: 1 Warmblood: 1 Color: bay Number of whte markngs: 5 Tranng years: 1 Show years: <1 Jump Heght: 3.25 Lead: 1 Hunter: 1 Import: 0 USA: 1 Most of these varables are attaned smply by lookng at the ad. The horse s name s recorded to make sure there are no repeat ads. Lead refers to whether the horse gets lead changes whch s mostly determned from watchng the vdeo. After collectng data for the zone, the data s reorganzed and some categores are deleted to run the regresson analyses. 15
Appendx B Descrptve statstcs tables generated n Excel Tranng years wll be removed from the regresson analyss due to the lack of varaton whch can be dentfed from the sample varance value of.025 and a sum of 76. Only two horses are untraned n ths study. 16
Appendx C Regresson Analyses The results of the four analyses performed are on the followng four pages. Statstcally sgnfcant varables at the 95% and 99% confdence ntervals for each analyss are hghlghted n blue. The adjusted R squared value vares from.7318 to.74 and the F stat vares from 17.2 to 20.7. These numbers show the strength of the models used n each regresson. Overall, analyss two provdes the best results. 17
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