Consider the causal effect of a policy Di ∈ {0, 1} on an outcome of interest Yi . For each unit i in the population, the potential outcomes are given by Yi(0) and Yi(1). Let ∆ be the difference in expected observed outcomes between treated and untreated units, ∆ = E[Yi |Di = 1]−E[Yi |Di = 0], and define the average treatment effect on the untreated, AT U, as AT U = E[Yi(1) − Yi(0)|Di = 0]. (a) (8 points) Show that the difference in means ∆ can be written as ∆ = AT U + B, where B is a selection bias term that you need to find. Show your steps. (b) (3 points) Suppose you have a random sample from the population for which you observe Yi and Di . Are you able to estimate the selection bias B that you found in (a) based on this sample? If your answer is yes, propose an estimator for B. If your answer is no, explain why

option a is correct.

step-by-step explanation:

scale factor: it is used to find proportional measurements.

proportions means having the same ratio.

scale factor is the ratio of the model measurement to the actual measurement in a simplest form.

or we can say that the ratio of any two corresponding lengths in two similar geometric figures

if the scale factor is more than 1, then it is an enlargement,

if the scale factor less than 1, then it is a reduction.

given the two geometric figure:

by definition of proportions, we have

answer: -10

step-by-step explanation:

s(t) = 1 - 10t

s(x) = 1 - 10x

s(x + h) = 1 - 10(x + h)

            = 1 - 10x - 10h

s(x + h) - s(x) = 1 - 10x - 10h - (1 - 10x)

                      = 1 - 10x - 10h - 1 + 10x

                      = -10h

= -10

no it isn’t   i believe it is

step-by-step explanation:

answer:

the product of -35 and -625 is positive.