Primaries and Candidate Polarization turn to the lab to distinguish between the competing were denominated in "points"and converted to cash theories.14 by dividing by 10 and rounding to the nearest quarter. -00081140 Given this conversion rate,the range of possible mone- Procedures tary payoffs for each election was between $0 and $20. The final payment was determined by randomly select- The experiment was conducted at the Pittsburgh Ex- ing one election to count from the entire session and perimental Economics Laboratory and involved a to- then adding the show-up fee. tal of 182 participants drawn primarily from the uni- At the beginning of each election period,subjects versity's undergraduate population.Each session in- first learned the position of every player's ideal point. volved 14 participants,and each subject participated Every subject then chose a policy position (referred in one session of either the 1S election treatment (six to as their "campaign promise"),and they were in- sessions)or the 2S election treatment(seven sessions) formed that if their campaign promise was selected At the beginning of each session,following standard as the winning position,it would affect every other laboratory procedures,subjects gave informed consent, subject's payoff.After subjects chose their campaign the instructions were read out loud to induce public promise,the computer then randomly selected candi- knowledge,and subjects answered a set of questions dates from each group:one candidate from each group about the rules on their computers to ensure compre- in the 1S election and two candidates from each group 4 hension.15 The interface was computerized and pro- in the 2S election,with each group member equally like grammed using the software z-Tree (Fischbacher 2007) to be selected and the selection of candidates indepen- Each session took about an hour and a half to complete, dent across election periods.The rest of the subjects and subjects earned an average of $21.05(including a were assigned to the role of a voter in that election $7 show-up fee). Thus,at the beginning of each election,every subject Subjects participated in a total of 40 elections,and was a potential candidate and did not know whether the instructions emphasized that each election was to he or she was a candidate until after submitting a cam- 4号 be treated as a"separate decision task."For each elec- paign promise.19 tion,subjects were divided into two groups of seven Once the candidates were selected,the game pro- 'asn participants,and every member of a group had the ceeded to the voting stages.In the 2S election,voters same payoff function and ideal point.6 Throughout the first chose between one of their group's two candidates experiment,the policy space was the set of integers by majority rule.Each primary(first stage)vote is held from 1 to 200.and payoffs were given by the linear loss simultaneously,and neither party knew the positions function 200-w6:.17 The parties'ideal points were of the other group's candidates while voting.Absten- located symmetrically from the median voter's ideal tions were not allowed.After each group selected its point em such that 0L=0M-d,0R =0M d,and nominee,a second round of voting took place to choose d (50,75).The numerical value of eM varied from the winning policy from the two groups'nominees.All election to election,while the exact sequence of values voters participated in this second round,which was ef- was identical across sessions and treatments.18 Payoffs fectively the "general election."20 In contrast to the 2S election treatment,the 1S election treatment fea- tured only one round of voting in which every voter 14 See Woon(2012b)for an extended discussion of why laboratory participated. experiments are well-suited for behavioral inference in the context The median voter in the general election in both the is See the Supplementary Material for the full text of the experi- IS and 2S election treatments was a computer voter mental instructions.Comprehension of the instructions was high.The who had a distinct ideal point and,as the instructions percentage of correct responses for individual questions ranged from explained to subjects,similar to Morton (1993),was 81%to 94%,and 69%answered all four questions correctly while "like a robot programmed to always vote for the candi- only 8%missed more than one question. These figures likely un date whose campaign promise gives it the higher payoff derestimate the overall degree of comprehension since subjects read of the otwers before playing thegame value."In the case of ties,the computer voted for each We can think of each group as a party,although I was careful to candidate with equal probability.The subjects were in- avoid using the term "party"when describing the game to subjects formed of the computer voter's ideal point before ev- Groups were randomly reassigned between rounds in two sessions of ery election each treatment,while the remaining sessions involved fixed groups The 40 elections within each session were divided The method of group assignment did not qualitatively affect the re- sults,so I ignore the distinction and pool the data in the analysis. into two parts,where each part varied the type of 17 Note that with a linear loss function(in contrast to quadratic loss) every possible policy outcome between the parties'ideal points gen- erates an equal amount of total social welfare,making it unlikely that and between 76 and 125 when d=75.I varied the numerical values risk neutral,altruistic subjects will want to choose the midpoint be. to encourage subjects to pay attention and think about their relative tween parties to maximize the total social monetary payoffs of both rather than absolute,positions. groups.However,to the extent that subjects'preferences for money 1This method of role assignment is similar in spirit to the strategy exhibit risk aversion(and they expect this of other subjects),tota method and maximized the number of observed positions in the ex- social welfare will be maximized at the midpoint between parties periment given that one of the primary goals of the experiment is to which would bias the results toward median convergence.Similarly. measure and test candidate positioning behavior. inequity aversion would also bias choices toward convergence to the 20 To avoid priming subjects'political attitudes regarding primaries,I Todetermine the sequence of values.I randomly selected the m avoid referring to the two rounds of voting as a"primary"and"gen eral"election but instead refer to them as the "first voting stage"and dian's position,M,from the integers between 51 and 150 for d=50 the "second voting stage." 833Primaries and Candidate Polarization turn to the lab to distinguish between the competing theories.14 Procedures The experiment was conducted at the Pittsburgh Ex￾perimental Economics Laboratory and involved a to￾tal of 182 participants drawn primarily from the uni￾versity’s undergraduate population. Each session in￾volved 14 participants, and each subject participated in one session of either the 1S election treatment (six sessions) or the 2S election treatment (seven sessions). At the beginning of each session, following standard laboratory procedures, subjects gave informed consent, the instructions were read out loud to induce public knowledge, and subjects answered a set of questions about the rules on their computers to ensure compre￾hension.15 The interface was computerized and pro￾grammed using the software z-Tree (Fischbacher 2007). Each session took about an hour and a half to complete, and subjects earned an average of $21.05 (including a $7 show-up fee). Subjects participated in a total of 40 elections, and the instructions emphasized that each election was to be treated as a “separate decision task.” For each elec￾tion, subjects were divided into two groups of seven participants, and every member of a group had the same payoff function and ideal point.16 Throughout the experiment, the policy space was the set of integers from 1 to 200, and payoffs were given by the linear loss function 200 − |w − θi|.17 The parties’ ideal points were located symmetrically from the median voter’s ideal point θM such that θL = θM − d, θR = θM + d, and d ∈ {50, 75}. The numerical value of θM varied from election to election, while the exact sequence of values was identical across sessions and treatments.18 Payoffs 14 See Woon (2012b) for an extended discussion of why laboratory experiments are well-suited for behavioral inference in the context of formal models. 15 See the Supplementary Material for the full text of the experi￾mental instructions. Comprehension of the instructions was high.The percentage of correct responses for individual questions ranged from 81% to 94%, and 69% answered all four questions correctly while only 8% missed more than one question. These figures likely un￾derestimate the overall degree of comprehension since subjects read explanations of the correct answers before playing the game. 16 We can think of each group as a party, although I was careful to avoid using the term “party” when describing the game to subjects. Groups were randomly reassigned between rounds in two sessions of each treatment, while the remaining sessions involved fixed groups. The method of group assignment did not qualitatively affect the re￾sults, so I ignore the distinction and pool the data in the analysis. 17 Note that with a linear loss function (in contrast to quadratic loss), every possible policy outcome between the parties’ ideal points gen￾erates an equal amount of total social welfare,making it unlikely that risk neutral, altruistic subjects will want to choose the midpoint be￾tween parties to maximize the total social monetary payoffs of both groups. However, to the extent that subjects’ preferences for money exhibit risk aversion (and they expect this of other subjects), total social welfare will be maximized at the midpoint between parties, which would bias the results toward median convergence. Similarly, inequity aversion would also bias choices toward convergence to the median. 18 To determine the sequence of values, I randomly selected the me￾dian’s position, θM, from the integers between 51 and 150 for d = 50 were denominated in “points” and converted to cash by dividing by 10 and rounding to the nearest quarter. Given this conversion rate, the range of possible mone￾tary payoffs for each election was between $0 and $20. The final payment was determined by randomly select￾ing one election to count from the entire session and then adding the show-up fee. At the beginning of each election period, subjects first learned the position of every player’s ideal point. Every subject then chose a policy position (referred to as their “campaign promise”), and they were in￾formed that if their campaign promise was selected as the winning position, it would affect every other subject’s payoff. After subjects chose their campaign promise, the computer then randomly selected candi￾dates from each group: one candidate from each group in the 1S election and two candidates from each group in the 2S election, with each group member equally like to be selected and the selection of candidates indepen￾dent across election periods. The rest of the subjects were assigned to the role of a voter in that election. Thus, at the beginning of each election, every subject was a potential candidate and did not know whether he or she was a candidate until after submitting a cam￾paign promise.19 Once the candidates were selected, the game pro￾ceeded to the voting stages. In the 2S election, voters first chose between one of their group’s two candidates by majority rule. Each primary (first stage) vote is held simultaneously, and neither party knew the positions of the other group’s candidates while voting. Absten￾tions were not allowed. After each group selected its nominee, a second round of voting took place to choose the winning policy from the two groups’ nominees. All voters participated in this second round, which was ef￾fectively the “general election.”20 In contrast to the 2S election treatment, the 1S election treatment fea￾tured only one round of voting in which every voter participated. The median voter in the general election in both the 1S and 2S election treatments was a computer voter who had a distinct ideal point and, as the instructions explained to subjects, similar to Morton (1993), was “like a robot programmed to always vote for the candi￾date whose campaign promise gives it the higher payoff value.” In the case of ties, the computer voted for each candidate with equal probability. The subjects were in￾formed of the computer voter’s ideal point before ev￾ery election. The 40 elections within each session were divided into two parts, where each part varied the type of and between 76 and 125 when d = 75. I varied the numerical values to encourage subjects to pay attention and think about their relative, rather than absolute, positions. 19 This method of role assignment is similar in spirit to the strategy method and maximized the number of observed positions in the ex￾periment given that one of the primary goals of the experiment is to measure and test candidate positioning behavior. 20 To avoid priming subjects’ political attitudes regarding primaries, I avoid referring to the two rounds of voting as a “primary” and “gen￾eral” election but instead refer to them as the “first voting stage” and the “second voting stage.” 833 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:04, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000515