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2. Multiple Choice The influence of a variable $X_i$ on the the binary dependent variable $D_i$ should be investigated. For this purpose the linear probability model $D_i = \beta_0 + \beta_1 X_i + \epsilon_i$ is estimated. In addition, the relationship is also estimated via a logit model, which for $X_i$ has the estimated coefficient $\hat{\alpha}_1$. For $\hat{\alpha}_1$ and $\hat{\beta}_1$ then holds, ... a) ... $\hat{\beta}_1$ and $\hat{\alpha}_1$ measure respectively the marginal effect of an increase of $X_i$ by one unit on the probability that $D_i = 1$. b) ... if $\hat{\alpha}_1 < 0$, then the probability of $D_i = 1$ decreases with increasing values of $X_i$. c) ... $\hat{\alpha}_1 \approx \hat{\beta}_1$. d) ... $\hat{\alpha}_1 + \hat{\beta}_1 = 1$.

          2. Multiple Choice
The influence of a variable $X_i$ on the the binary dependent variable $D_i$ should be
investigated. For this purpose the linear probability model $D_i = \beta_0 + \beta_1 X_i + \epsilon_i$ is
estimated. In addition, the relationship is also estimated via a logit model, which for
$X_i$ has the estimated coefficient $\hat{\alpha}_1$. For $\hat{\alpha}_1$ and $\hat{\beta}_1$ then holds, ...
a) ... $\hat{\beta}_1$ and $\hat{\alpha}_1$ measure respectively the marginal effect of an increase of $X_i$ by one
unit on the probability that $D_i = 1$.
b) ... if $\hat{\alpha}_1 < 0$, then the probability of $D_i = 1$ decreases with increasing values of
$X_i$.
c) ... $\hat{\alpha}_1 \approx \hat{\beta}_1$.
d) ... $\hat{\alpha}_1 + \hat{\beta}_1 = 1$.

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2. Multiple Choice
The influence of a variable Xi on the the binary dependent variable Di should be
investigated. For this purpose the linear probability model Di = β0 + β1 Xi + is
estimated. In addition, the relationship is also estimated via a logit model, which for
Xi has the estimated coefficient α̂1. For α̂1 and β̂1 then holds, ...
a) ... β̂1 and α̂1 measure respectively the marginal effect of an increase of Xi by one
unit on the probability that Di = 1.
b) ... if α̂1 < 0, then the probability of Di = 1 decreases with increasing values of
Xi.
c) ... α̂1 ≈β̂1.
d) ... α̂1 + β̂1 = 1.

Added by Laura L.

Principles of Economics

Gregory Mankiw 8th Edition

Instant Answer

Solved by Expert Sri K

06/12/2023

Step 1

Step 1: In the linear probability model D_(i)=\beta _(0)+\beta _(1)x_(i)+\epsi _(i), the coefficient \beta _(1) measures the change in the probability of D_(i)=1 for a one-unit increase in x_(i). Show more…

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Multiple Choice The influence of a variable x_(i) on the the binary dependent variable D_(i) should be investigated. For this purpose the linear probability model D_(i)=eta _(0)+eta _(1)x_(i)+epsi _(i) is estimated. In addition, the relationship is also estimated via a logit model, which for x_(i) has the estimated coefficient hat(alpha )_(1). For hat(alpha )_(1) and hat(eta )_(1) then holds, ... a) dotshat(eta )_(1) and hat(alpha )_(1) measure respectively the marginal effect of an increase of x_(i) by one unit on the probability that D_(i)=1. b) dots if hat(alpha )_(1)<0, then the probability of D_(i)=1 decreases with increasing values of x_(i). c) dotshat(alpha )_(1) d) dotshat(alpha )_(1) 2. Multiple Choice The influence of a variable X; on the the binary dependent variable D; should be estimated. In addition, the relationship is also estimated via a logit model, which for X; has the estimated coefficient &. For and i then holds, : : a) .. . 1 and a1 measure respectively the marginal effect of an increase of X, by one unit on the probability that D; = 1. b) ... if a < 0, then the probability of D; = 1 decreases with increasing values of Xi. c)...a1 ~ 31. d)...a1+31=1.

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