Question

Consider the Tobit model: $y^* = x\beta + u$, $u \sim N(0, \sigma^2)$, $y = max\{y^*, 0\}$, where we can observe $(y, x)$. Suppose that $(b, s^2)$ are the maximum likelihood estimators of $(\beta, \sigma^2)$ respectively. Then the model's fitted value is defined as: Oa. $xb$. Ob. $xb/s$. Oc. $y - xb/s$. Od. none of the other alternatives.

          Consider the Tobit model: $y^* = x\beta + u$, $u \sim N(0, \sigma^2)$, $y = max\{y^*, 0\}$, where we can observe $(y, x)$. Suppose that $(b, s^2)$ are the maximum likelihood estimators of $(\beta, \sigma^2)$ respectively. Then the model's fitted value is defined as:

Oa. $xb$.
Ob. $xb/s$.
Oc. $y - xb/s$.
Od. none of the other alternatives.

$Consider the Tobit model: y^* = xβ + u, u ∼ N(0, σ^2), y = max{y^*, 0}, where we can observe (y, x). Suppose that (b, s^2) are the maximum likelihood estimators of (β, σ^2) respectively. Then the model's fitted value is defined as: Oa. xb. Ob. xb/s. Oc. y - xb/s. Od. none of the other alternatives.$

Added by Kirk A.

Principles of Economics

Gregory Mankiw 8th Edition

Instant Answer

Solved by Expert Sri K

06/13/2023

Step 1

Step 1: In the Tobit model, the fitted value is the predicted value of y, denoted as y-hat, which is the conditional mean of y given x. Show more…

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Consider the Tobit model: y* = xB + u, u ~ N(0, o'), y = max(y* 0), where we canobserve (y, x). Suppose that (b, s') are the maximum likelihood estimators of (B, )respectively.Then the model's fitted value is defined as. a. xb. b. xb/s. c. y-xb/s. d. none of the other alternatives Consider the Tobit model: y* = x + u, u ~ N(0, o2), y = max{y*, 0}, where we can observe (y, x). Suppose that (b, s2) are the maximum likelihood estimators of (3, o2 respectively. Then the model's fitted value is defined as: a. xb. b. xb/s. 0 c. y - xb/s. d. none of the other alternatives