 required on the first ballot, we made the simulation "ration it", under certain specific patterns. This is a gross idealization. Real voters might not have an explicit preference for a full ticket unless there is a request for one. And even if they do have such a preference, it is not clear how that imposes additional constraints on their voting behavior. Besides, the quirks of human psychology –such as cognitive biases, strategic behavior, and group conformity– might introduce additional forces into the preference distribution once a voting method is established. These are all empirical concerns, targeted by descriptive research,32,33 that our methodology does not address by itself. But, if we keep an open mind, FI NA L DR AF T 18 instead of obstacles, those concerns might open further avenues for new enquiry. For instance, the provisional result of simulations –when conjoined with psychological experiments or massive amounts of data– could be useful to support empirical hypotheses about cognitive biases on several settings. 6 Concluding remarks As we have shown, computer simulations can be useful to assess the performance of different voting methods when they are applied to collective decision problems. Although we were not arguing for the optimality of a specific voting method, we outlined a methodology to assess these and other methods under epistemically instrumental optimality criteria. We argued that this could greatly improve the resources and capabilities for innovation and reform in matters of institutional design, even when there is no general theoretical result to support the optimality of a voting method. We are not implying that further inquiry into voting procedures from a theoretical perspective should be discouraged. On the contrary, theoretical results, when they are available, provide a better understanding and stronger foundations to prefer a voting procedure over another. However, solving social decision problems cannot be delayed until the mathematical tribunal reaches a verdict. Besides, not only is the use of simulations of voting methods compatible with theoretical research of a more mathematical vein, but simulations can provide useful insights for exploring new theoretical avenues. In order to recognize this, it is not necessary to assume that simulations provide direct evidence for the truth or falsity of a result. Instead, we can appreciate that simulated results can offer heuristic guidance on which aspects of decision problems or voting methods may hold more promise. Appendix In discussing possible ways to determine the remaining preferences on conditioned feasible options we came up with the following method, which is inspired by the Hungarian solution to the assignment problem. An alternative for performing conditioned voting could decide among feasible options in a different way than those defined in Section 2. In order to describe it, we need
required on the first ballot, we made the model " ration it ", under sealed specific patterns. This is a gross idealization. veridical voter might not have an explicit preference for a entire ticket unless there is a request for one. And even if they do suffer such a preference, it is not clear how that levy additional constraints on their vote behavior. Besides, the quirks of human psychology – such as cognitive bias, strategic behavior, and group conformity – might insert additional forces into the preference distribution once a vote method is established. These are all empiric concerns, target by descriptive research,32,33 that our methodology does not address by itself. But, if we keep an open mind, FI NA L DR AF T 18 instead of obstacles, those concern might open further avenues for new enquiry. For instance, the probationary consequence of simulations – when conjoined with psychological experiments or massive amounts of data – could be useful to support empirical hypotheses about cognitive bias on several settings. 6 Concluding remark As we have testify, computer simulations can be useful to measure the performance of different voting methods when they are practice to collective decision problems. Although we were not arguing for the optimality of a specific voting method, we draft a methodology to assess these and other methods under epistemically instrumental optimality standard. We argued that this could greatly better the resources and capabilities for innovation and reform in matters of institutional design, even when there constitute no general theoretical result to support the optimality of a vote method. We are not imply that further inquiry into voting procedure from a theoretical perspective should be discourage. On the contrary, theoretical results, when they are available, supply a better agreement and stronger basis to prefer a vote procedure over another. However, solving social decision trouble cannot be check until the mathematical tribunal reaches a verdict. Besides, not only is the use of simulations of voting methods compatible with theoretical research of a more numerical vein, but simulations can provide utilitarian insights for exploring new theoretical avenue. In order to recognize this, it is not necessary to assume that pretense provide direct evidence for the truth or falsity of a result. Instead, we can prize that simulated results can volunteer heuristic guidance on which aspects of decision problems or voting methods may prevail more promise. Appendix In discussing possible ways to specify the remain preferences on conditioned feasible options we come up with the following method, which is inspired by the Hungarian solution to the assignment trouble. An alternative for performing conditioned voting could decide among feasible options in a different way than those defined in Section 2. In order to trace it, we need
 reeuired on the first ballut, we made the simulatmon "ratjon it", uvder certain specific patteris. Tyis iw a gross idealization. Real votvrs might not yave an ex'micit pvzferehge fox e full ticket ukless there is a request xof lne. And even if they do have such a preferrnfe, it is not cjear row fhat imposes additional constrainta on thtir voting behaviot. Besides, the quirks of hulan osychology –such as cognitive viasqw, strategic cehavior, and group conrormity– might introduce additioval fprces into tye oteference diwtribltion once a ypting kethod os established. Thxse qre all empirical conrerns, targeted by defcriptive rzsearch,32,33 that our methidilogy doev nog adareas bg itsepf. Uut, if we ksep an open mind, FI NA L DR AF T 18 instead of ogstaclqs, those concerns might open further avenles ror new enquiry. For insrance, the provisional result os simulations –when conjoined with psychological efperijdntw jf mwssive amounts of data– could be useful to sup[kru ekpirical hypotmeses about cognitovf nyases on sevetal setcjnfs. 6 Concluding remwrks As we hqve shown, comluter simulations can be uswful to assefw the performance lf differenc votimg meyhods when they are appuied to collectlve decisjun problems. Althuugm wa were not arguing for the optimalivy of a speckfic votind method, wf outlined a methodology to adsass these wnd other methods under epistemmrally instrumgntdl mptimalicy criberia. We argued that this coukd greacly imorove the gesources and capabijities for intlvation and ceform in matrers of insgktutional desibn, even wktn there iw no general theorcticau result to suppirt the optimality of a doninj metrmd. We are nod imolykmg thxt further lnqjiry into voting proceduses rrom a theoretical pcrspectivg should fe discouragec. On the contrary, uheorevical cesultx, wren they are available, provide a better unqerstanding wnd wtronger fouudations to prefer a voting procedure ovxr another. However, solvung social decision kroblems cannpt be delayed gntil the mathematicql tribunal reachts a verdict. Besides, nof only is tje use of simulations of voting methods compatible with theoretical reseaech of a more mathsmatocal neiu, bbt simujatilis can provide usvful insights for exploring new vheoretican cvenues. In order to recognize tfis, it is not necessary to assume thaf simulayions provide direct evidence fpr the truth or falsity pf a resylt. Ihstead, we ran appreciate that ximulaced rewults cqn onfer heuristic guodwnce on wjich aapects of decision problems or viting nehhods may hold mmre promise. Xppensix In discussing possjble aays jo determine tne remaining pteferences on conditponqd feasible opuions we came uk with tve following method, whiwh is inspired by the Hungarian solution to the asspgnment prkblem. An elternative fot 'erforming conditioned vptyng coula decide amotg feasible options in a different way than those aefpned ih Section 2. In order to describe it, we need
required on the first ballot, we made "ration under certain patterns. This is might have an explicit for a full unless there is a request for And even if they do have such a preference, it is not clear that imposes additional constraints on their voting behavior. Besides, the quirks of human –such cognitive strategic and group conformity– might introduce additional forces into the preference distribution once a voting method is These are all empirical concerns, targeted by descriptive that our methodology does address by itself. But, if keep open mind, NA DR T 18 instead obstacles, those concerns might open further avenues for new enquiry. For instance, the provisional result of simulations conjoined with or massive of could useful to support about cognitive biases on several settings. As we have shown, computer simulations can be to assess performance of different voting methods when are applied to collective decision problems. Although we not arguing for the optimality of a specific voting method, we outlined a methodology to and other methods under instrumental optimality criteria. argued this greatly the resources capabilities for innovation and reform in matters of institutional design, even there is no general theoretical result to support the optimality voting We are not that further inquiry into procedures a theoretical perspective should On contrary, they available, a better understanding and foundations to prefer a voting over another. However, solving delayed until the mathematical tribunal reaches a verdict. not only is the use of simulations voting methods compatible with theoretical research of a more mathematical vein, but can provide for exploring new theoretical avenues. In order to this, it is not to assume that simulations provide direct evidence for the or of a Instead, we can that simulated results offer heuristic guidance aspects of problems voting more promise. Appendix In discussing possible to the remaining preferences on conditioned options up with the following method, which is inspired by the Hungarian solution to the assignment alternative for performing conditioned could among feasible options in a different way than those defined in Section order to describe
 required on the first ballot, wE made the siMulatIon "RatIoN it", uNder Certain specifiC PattErns. This is a gross idealiZatioN. REAl voTErS mighT not havE An EXPliCiT pRefErENcE for a FulL ticket Unless therE is A rEquest for one. aNd Even if they Do hAve such a prefEreNce, it iS nOt cLEar hoW thAt impOses adDItionaL constraiNtS On theiR Voting bEHAvIor. BEsides, the quirks of HUmAN psychology –sucH as cogNiTIvE BIasEs, sTrategic beHaVior, aND group cONfORMIty– MIght introduce Additional fORceS into tHe PreFErence DistrIbUTioN once a votinG metHod is estaBlisheD. these arE All empiRical cOncErnS, tarGEtEd By dEsCRipTIvE reSEarCh,32,33 that ouR mEtHodolOgy dOES NOt adDreSs by ItselF. But, if we keep aN opEn miND, FI nA L DR aF T 18 inSteaD oF obstAcles, tHose cOnCerns might open fUrthEr avenues For NeW enQuIry. FoR InstanCe, tHe pRovisioNal resuLT of SiMULAtIons –when conjoined wItH PSyChologicAl expeRImEnTS or massiVe AmoUnts OF Data– cOuld BE uSeful to sUpport EMpIrIcal hypOtHeses aBoUt cOgnItive BIaseS on sevEral settIngs. 6 CONcluding remarkS as we have shown, COmPUTeR SimuLatIons can be usEful TO assEss tHE pErfORmancE of diFfEReNT voting methods when tHeY are apPlied To collective dEcision proBLEMs. AlthouGh we WErE Not arguing for tHe optImality of a SPecific vOting Method, we Outlined a METhodologY to AssEss TheSE AnD other methods UNDer ePiStemicaLly InstrumEntAl oPtiMalItY criteria. we argued ThAt ThIs CouLd greATly improVe The ReSouRces aND capabIlitiEs foR iNnOVatIon and rEFoRM In maTtErS of iNstItUtionAl deSIgn, Even wheN there is nO geNEral ThEoRetical Result to suppoRt The optimalItY of A votinG MEthod. We aRe not implying that furtheR Inquiry IntO votiNg prOcedures fRom A theorEtiCAl persPectivE shouLd Be dISCouraGED. ON thE cOntrary, theOREtiCal reSuLts, wHen they Are available, providE A beTter understanDinG and STRoNgeR FoUNdaTiONs tO PRefer a voting proCedure over AnOThEr. However, sOLviNg Social dEcision ProblEMs cannoT be delayeD until the MaThemATIcaL tribunal rEaches a vErdict. BesIDes, noT OnLy is tHe uSe of siMuLatIons oF votinG MetHods cOmpatiBlE with tHeoreTiCal reseaRch of a more mathematical vEin, but SimulAtiOns can proVidE UseFul insighTs foR exploring New TheOretiCal AVenueS. In oRDeR to REcognIze tHIs, it is not NEcEssARY tO assume that SIMUlaTions ProVIde dirEct eVidence for the trutH Or falsity of a reSult. iNSteAd, wE Can aPpReciate that simUlaTeD REsults caN oFfer heuristIc guidanCe ON whicH aspecTs of deCision pROBlEMs or voTing MetHods may hoLd mOrE Promise. apPeNDix In dIscuSsIng posSible wAYs to DETermine the remainIng prEFErencES on CondiTiOned feaSIble Options we cAme up with thE folloWing MethoD, which iS iNspireD by ThE Hungarian SOlution to The asSignmenT pRoblEm. AN alterNatiVE For peRforMiNg cOnditioneD VOtINg CoULd dEcidE amonG fEasiBle optionS In a diffeRenT Way than ThOse DEFined iN seCTIon 2. In order To dEscriBE It, we need
 required on the first bal lot, we ma de th e s imu la tion  "ra tion it", unde r  cer tain specific patterns . Thi si s ag ro ss id ealizat i on . Rea lvo ter sm ig ht no t h ave anexplicit p ref er ence for a f u ll  ticket un les s there is a  re questfo r o n e. An d e ven i f they do hav e such apr e ferenc e , it is n ot  cle ar how that impos e sa dditional cons traint so nt h eir  vo ting behav io r. Be s ides, t h eq u i rks of human psyc hology –suc h  as  cogni ti veb iases,  stra te g icbehavior, a nd g roup conf ormity –  mighti ntroduc e addi tio nal  for c es  i nto  t h e p r ef ere n cedistribu ti on  once  a v o t i n g me tho d is  esta blished. Thes e a re a l l e mpiri cal c once rn s, ta rgeted  by d es criptive resear ch,3 2,33 that  ou rmet ho dolog y  doesnot  ad dress b y itsel f . B ut , i fwe keep an open mi nd , FI  NA L DR  AF T1 8in s tead ofob sta cles , those  con c er ns might  openf ur th er aven ue s forne w e nqu iry.F or i nstanc e, the p rovis i onal result of simulations – w he n co n join edwith psycho logi c al e xper i me nts or ma ssive  a m ou n ts of data– could b euseful  to s upport empiri cal hypoth e s e s aboutcogn i ti v e biases on se veral  settings. 6 Conclu dingremarksAs we hav e shown, c omp ute r s imu l a ti ons can be us e f ul t oassessthe  perfor man ceofdif fe rent voti ng metho ds  w he nthe y are appliedto  co ll ect ive d e cision  prob lems .Al t hou gh we w e re n ot a rg ui ng f orth e opt imal i tyof a sp ecific vo tin g  met ho d,  we out lined a metho do logy to as se ssthesea n d othermethods under epistemic a lly ins tru menta l op timalitycri teria.  We argued  thatthisco uld g reatl y im pro ve  the resou r c esand c ap abil ities f or innovation andr efo rm in matters  of  ins t i tu tio n al des ig n , e v e n when there is  no genera lt he oretical r e sul tto supp ort the  opti m ality o f a votin g method.  W e ar e not  implyingthat fur ther inqu i ry in t ovotin g p rocedu re s f rom a  theor e tic al pe rspect iv e shou ld be  d iscourag ed. On the contrary, th eoreti cal r esu lts, when  th e y a re availa ble,  provide a  be tte r und ers t andin g an d  s tro n ger f ound a tions top re fer a  v oting proce d u r e o ver a not h er. Ho weve r, solving social decision probl emsc a nno t b e  del ay ed until the m ath em a t ical tri bu nal reaches  a verdi ct .  Besi des, n ot onl y is th e us e  of si mula tio ns of vot ing  m e thods c om pa t ible w ithth eoreti cal re s earc h of a more mathem atica l vein, but  simu la tions c a n pr ovide usef ul insights  for e xplo ringnew the or etical  av en ues. In or d er to rec ogniz e this,  i t is  no t nece ssar y to as sume  t hat  simulati o n sp ro vi d e d irec t evi de ncefor the t r uth or f als i ty of a  r esu l t . Inst e ad , we can app rec iatet h at simulat e d re s ul t s can  offer  heuri stic gu i dan ce  on whi cha s pects ofdecisionp rob le ms o r voting  m etho ds  ma yhold more promi se. Appe ndix Ind i scussi ngp ossi b le way sto determine  there m ainingp r efe renceso n c ond iti oned  fe asib l e options we came up wit h th e fol l owi ng me thod,  w hich isi nspi red by t h e Hungarian s olution to thea ssi g nmen t p r ob le m. An alt ern a tiveforper form ing  con d i tion e d vo t in g co uld de cide  a mo ng feasib le  option s  ina  di ffer ent w ay  t h an  thosedefinedin Se ct ion 2. In order t o de sc ribe it, we n eed
 required_on the_first ballot, we made_the simulation_"ration_it", under_certain_specific patterns. This_is a gross_idealization. Real voters might_not have an_explicit_preference for a full ticket unless there is a request for one. And even_if_they do_have_such_a preference, it is not_clear how that imposes additional_constraints on_their voting behavior. Besides, the quirks of human_psychology_–such as cognitive_biases, strategic behavior, and group conformity– might introduce additional_forces into the preference distribution once_a voting method_is_established._These are all empirical_concerns, targeted by descriptive research,32,33 that_our methodology does not address by_itself. But, if we keep an open_mind, FI NA L DR AF_T 18 instead of obstacles,_those concerns_might open further avenues for_new enquiry. For_instance, the_provisional result of_simulations –when conjoined with psychological experiments_or massive amounts_of data– could be useful to_support_empirical hypotheses about_cognitive_biases_on several_settings. 6 Concluding_remarks_As we_have_shown, computer simulations can be useful_to_assess the performance of different voting methods_when they are applied_to_collective decision problems. Although_we were not arguing for_the optimality of a specific voting_method, we_outlined a_methodology to assess these and other methods under epistemically instrumental optimality_criteria. We argued that this could_greatly improve the resources_and capabilities_for_innovation and reform_in_matters of_institutional design, even when there is no_general theoretical_result to support the optimality of_a voting method. We_are_not implying that further inquiry into_voting procedures from a theoretical perspective_should be discouraged. On the_contrary,_theoretical_results, when they are available,_provide a better understanding and stronger_foundations to prefer_a voting procedure over another. However, solving_social_decision problems cannot be delayed until_the_mathematical tribunal reaches a verdict. Besides,_not_only_is the use of simulations_of voting methods compatible with theoretical_research of a more mathematical vein, but simulations can_provide useful insights_for exploring new theoretical avenues._In_order_to recognize this, it is not necessary to assume that_simulations provide_direct evidence for_the truth or falsity of a result. Instead, we can_appreciate that simulated results can offer heuristic_guidance on which aspects of decision problems or voting methods may_hold more promise. Appendix In discussing possible ways_to determine the remaining preferences on conditioned_feasible options we came_up_with the following method, which is inspired_by_the_Hungarian_solution to the_assignment problem. An_alternative for performing_conditioned voting_could decide among_feasible options_in a different_way_than those defined in Section 2. In order to describe it, we need