Compute DID estimate and pretrend flag

Q: Compute DID estimate and pretrend flag

This Analytics & Experimentation question evaluates basic causal-inference and data-manipulation skills by requiring computation of a difference-in-differences (DID) estimate and a binary pretrend flag from panel-like arrays, at an implementation-level focused on summary statistics and edge-case handling.

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Question

You are given three equal-length arrays describing observations from a panel-like dataset:

period[i] ∈ {0,1}: 0 = pre period, 1 = post period
treat[i] ∈ {0,1}: 1 = treated group, 0 = control group
y[i] (float): outcome

Tasks:

A) Compute the difference-in-differences (DID) estimate of the treatment effect:

$\text{DID} = (\bar y_{post,treated} - \bar y_{pre,treated}) - (\bar y_{post,control} - \bar y_{pre,control})$

B) Compute a simple pretrend flag:

Let $d_{pre} = \bar y_{pre,treated} - \bar y_{pre,control}$ .
Given a scalar threshold ≥ 0, return pretrend=True if $|d_{pre}| > threshold$ , else False .

Assumptions/requirements:

Use simple means over the subsets implied by ( period , treat ).
Describe how you would handle missing cells (e.g., no treated observations in pre period).

Compute DID estimate and pretrend flag

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