The Fixed Effects regression model:
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In the panel regression analysis of beer taxes on traffic deaths, the estimation period is 1982-1988 for the 48 contiguous U.S. states. To test for the significance of time fixed effects, you should calculate the F-statistic and compare it to the critical value from your Fq,∞ distribution, where q equals:
The binary dependent variable model is an example of a:limited dependent variable model.In the binary dependent variable model, a predicted value of 0.6 means that:given the values for the explanatory variables, there is a 60 percent probability that the dependent variable will equal one.E(Y|X1,..., Xk) = Pr(Y = 1| X1,..., Xk) means that:for a binary variable model, the predicted value from the population regression is the probability that Y=1, given X.The linear probability model is:the application of the linear multiple regression model to a binary dependent variable.In the linear probability model, the interpretation of the slope coefficient is:the change in probability that Y=1 associated with a unit change in X, holding others regressors constant.The following tools from multiple regression analysis carry over in a meaningful manner to the linear probability model, with the exception of the:regression R2.The major flaw of the linear probability model is that:the predicted values can lie above 1 and below 0.An alternative method of estimating Binary Outcome Models is the Logit Model.TrueProvide an example of a Binary Outcome (Limited Dependent Variable).Will a person be approved for a mortgage or no.