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Last Published June 06, 2022 05:14 AM July 10, 2022 11:19 PM
Experimental Design (Public) In each treatment, subjects state their willingness-to-pay for 5 different monetary lotteries. All lotteries have the following structure: with probability 1 - q, a subject gets 0 Coins; with probability 0.01, a subject gets x Coins; and with probability q - 0.01, a subject gets 10 Coins. (At the end of the experiment, Coins will be converted to Pounds at an exchange rate of 13 Coins = 1 Pounds.) One out of every 3 subjects will be randomly selected to receive a bonus payment based on the subject's willingness-to-pay for one randomly drawn lottery. (The payment will be determined via a BDM mechanism.) The parameter tuple (x, q) is randomly drawn (without replacement) from {100, 120, 140, 160, 180} x {0.1, 0.2, 0.3, 0.4, 0.5}. In each decision, subjects learn the feasible outcomes x, 10, and 0, but we vary across four treatments how much information they receive on the corresponding probabilities. Treatment "Control": subjects observe the full reward distribution; that is, they learn the probabilities of receiving each of the three possible outcomes. Treatment "Censoring": subjects only learn the probability, q, of receiving at least 10 Coins. Treatment "Selection": subjects observe the full reward distribution and, in addition, the five highest outcomes in a random sample of 400 draws (from the underlying distribution). Treatment "Censoring and Selection": subjects learn the probability, q, of receiving at least 10 Coins, and, in addition, they observe the five highest outcomes in a random sample of 400 draws (from the underlying distribution). Before subjects state their willingness-to-pay for a given lottery, they state their belief about the probability with which the lottery pays its highest prize of x Coins. More specifically, subjects answer the following question (using a slider from 0 to 100 times): "Imagine you would play the lottery 100 times. How often do you think would you win x Coins?" At the end of the experiment, we ask for demographics and experience with loot boxes. We further include the TSCS Self Control Module and the PGSI Gambling Module. We plan to use these additional variables as controls when testing for treatment effects on our outcome variables. And we will further test whether these measures are correlated with our outcome variables. In each treatment, subjects state their willingness-to-pay for 5 different monetary lotteries. All lotteries have the following structure: with probability 1 - q, a subject gets 0 Coins; with probability 0.01, a subject gets x Coins; and with probability q - 0.01, a subject gets 10 Coins. (At the end of the experiment, Coins will be converted to Pounds at an exchange rate of 13 Coins = 1 Pounds.) One out of every 6 subjects will be randomly selected to receive a bonus payment based on the subject's willingness-to-pay for one randomly drawn lottery. (The payment will be determined via a BDM mechanism.) The parameter tuple (x, q) is randomly drawn (without replacement) from {100, 120, 140, 160, 180} x {0.1, 0.2, 0.3, 0.4, 0.5}. In each decision, subjects learn the feasible outcomes x, 10, and 0, but we vary across four treatments how much information they receive on the corresponding probabilities. Treatment "Control": subjects observe the full reward distribution; that is, they learn the probabilities of receiving each of the three possible outcomes. Treatment "Censoring": subjects only learn the probability, q, of receiving at least 10 Coins. Treatment "Selection": subjects observe the full reward distribution and, in addition, the five highest outcomes in a random sample of 400 draws (from the underlying distribution). Treatment "Censoring and Selection": subjects learn the probability, q, of receiving at least 10 Coins, and, in addition, they observe the five highest outcomes in a random sample of 400 draws (from the underlying distribution). Before subjects state their willingness-to-pay for a given lottery, they state their belief about the probability with which the lottery pays its highest prize of x Coins. More specifically, subjects answer the following question (using a slider from 0 to 100 times): "Imagine you would play the lottery 100 times. How often do you think would you win x Coins?" At the end of the experiment, we ask for demographics and experience with loot boxes. We further include the TSCS Self Control Module and the PGSI Gambling Module. We plan to use these additional variables as controls when testing for treatment effects on our outcome variables. And we will further test whether these measures are correlated with our outcome variables.
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