Estimate a bivariate model of the effect of actual contact on voting. Is the model biased? Why or why not?

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ANSWER ALL QUESTIONS

In an effort to better understand the effects of get-out-the-vote (GOTV) messages on voter turnout, Gerber and Green (2005) conducted a randomized field experiment involving approximately 30,000 individuals in New Haven, Connecticut, in 1998. One of the experimental treatments was randomly assigned in-person visits where a volunteer visited the person’s home and encouraged him or her to vote.

(a) Estimate a bivariate model of the effect of actual contact on voting. Is the model biased? Why or why not?

(b) Estimate compliance by estimating what percentage of treatment-assigned people actually were contacted.

(c) Use ITT to estimate the effect of being assigned treatment on whether someone turned out to vote. Is this estimate likely to be higher or lower than the actual effect of being contacted? Is it subject to endogeneity?

(d) We can use ITT results and compliance rates to generate an unbiased estimate of the treatment effect. We first calculate how much the outcome changes due to the treatment being assigned (the ITT effect). Then we calculate the amount by which the treatment changes due to the treatment being assigned 1 (the compliance rate). Dividing the first number by the second number, we get the so-called “Wald estimator” for the treatment effect. Calculate the Wald estimator for the Get-out-the-vote experiment and compare the result to the estimates from (a) and (c).

(e) What are the conditions for “Contact Assigned” to be a valid instrument in the Get-out-the-vote experiment? Are they satisfied in this case?

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