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University of Toronto St. George
Robert Gazzale

ECO331 Behavioural Economics Midterm ReviewExperiment Design InternalExternal ValidityHomo economicuswe are utility maximizing and selfinterested doesnt depend on other utilites no cost of cognition and our preferences are learned while our beliefs are hard to changeWe use standard assumptions because theres one way to be rational canceling out hypothesis assumptions can be highly representative of real world regression to the mean even if people are irrantionalbiased parsimonysimply things perhaps they do wellInduced Value Theoryproper use of reward to induce behaviour Must satisfy monotonictymore reward is preferred Saliencereward depends on actions Dominancechange in utility comes dominantly from the reward NUISANCE VARSaffect results things you dont want to test Block or randomize to constrainFactorial DesignVary all treatment variables independently to obtain the clearest possible evidence on their effects Factorial designAvg paymentopportunity cost simple privacy random allocation of treatments dmeographicsIndependent obvs If knowing the value of X in no way improves my ability to predict the value of Y then X and Y are independentVernon Smithlab results apply to world results Charlie PlittReduce the number of plausibilitiesSlides we cannot assign people education levels so we conduct experiments They allow a variation of a causal factor while keeping others constant Thus a theory is not rejected but assumptionscausal factor To test a theory Internal Validityextent to which the treatment differences in Experiment are due to the hypothesized mechanism How right the measurement is to the cause Assess plausibility of alternative explanations for treatment differences GNR competition Perhaps the experiment took too long the environment wasnt like a real market the subjects were not randometc If they perform better that means theyre more competitive Could mean that they took a break or got used to the experiment Arguments must be made to back up assumptionsaccount for these differences Maxed out effort for females in mixed competition So test for single gender competitionimproved so it wasnt due to abilityExternal Validityextent to which we can extrapolate experiment results to the real world If the sample is too small or only students its hard Being watchedresearched Can1 Briefly explain the distinction between a withinsubject design and a betweensubject design What is the beauty of the withinsubject design If it is so beautiful why isnt it always usedThe distinction between a withinsubject design and a betweensubject design is the number of treatments the subjects do In a withinsubject design the subject does all treatments and in a betweensubject design the subject receives one treatment The beauty of withinsubject design is that because the subjects used in each treatment are the same noise variables are reduced thereby reducing error variance It allows experimenters to measure the change in the variable within the same subjects allows for more confidence It isnt always used because of carryover effects which is when participation in one condition may affect participation in anothersuch as knowing experimenter demand order effects learning Solutions Randomly assigned orders crossovers ABA dual trial2 Consider Gneezy Niederle and Rustichini ie the competition paper we did discuss in lecture What experimenter demand effects might we be worried about Ideally you should consider both strong and weak experimenter demand effects Should we be worried about experimenter demand effects in this particular case No we should not be worried about experimenter demand effects in this particular case as the paper shows that participants were focused on completing the task at handExperimenter demand effectsthe perception or belief that the subject holds in regards to the purpose of the experiment and what the experiment is looking for Strong experimenter demand effects Does the subject know what the experimenter wants ex compliant subject vs rebel subject Weak experimenter demand effects Treatment differences make differences salient ex tell you others donate money to charity Treatment A gives you info about others Treatment B no info about otherswhen presented with info maybe I should use it GNEEZY NIEDERLE RUSTICHINI GNR Notes about this article in class T1 Piece Rateno significant gender differencesT2 Competitive Pay Mixed Tournamentperformance of men is significantly higher vs noncompetitive incentive schemes of piecerate and random Women do not significantly differ in their performance in the mixed tournament and piecerate scheme T3 Random Payno significant gender differences
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