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Please give a brief explanation to each of these causal model assumptions: The data-generating process for an outcome, Y, can be expressed as: Yi =

Please give a brief explanation to each of these causal model assumptions:

  1. The data-generating process for an outcome, Y, can be expressed as:

Yi = + 1X1i + . . . + KXKi + Ui

2. {Yi, X1i, . . . , XKi} i=1 N is a random sample.

3. E[U] = E[U X1] = . . . = E[U XK] = 0

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