How Much Should We Trust Estimates from Multiplicative Interaction
... the marginal effect will essentially rely on interpolation or extrapolation of at least one of the functions to an area where there is no or only very few observations. It is well known that such interpolation or extrapolation purely based on the functional form results in fragile and highly model d ...
... the marginal effect will essentially rely on interpolation or extrapolation of at least one of the functions to an area where there is no or only very few observations. It is well known that such interpolation or extrapolation purely based on the functional form results in fragile and highly model d ...
Socioeconomic Impact of Broadband in Latin American and
... analyzed year over year from 2003 to 2009. It shows that, in our sample, a 10 percent increase in broadband penetration brought about an average increase of 3.19 percent in per capita GDP. In other words, we determined the function that best fit the available dataset and measured, at the end of the ...
... analyzed year over year from 2003 to 2009. It shows that, in our sample, a 10 percent increase in broadband penetration brought about an average increase of 3.19 percent in per capita GDP. In other words, we determined the function that best fit the available dataset and measured, at the end of the ...
Homework #2 - Emerson Statistics
... concentration. When the squared LDL concentration increases by one unit, the risk of death is 1.000076 times as likely in the group with higher LDL concentration. The 95% confidence interval suggests that this observation would not be unusual if a group that had one unit squared higher LDL concentra ...
... concentration. When the squared LDL concentration increases by one unit, the risk of death is 1.000076 times as likely in the group with higher LDL concentration. The 95% confidence interval suggests that this observation would not be unusual if a group that had one unit squared higher LDL concentra ...
The problem of determining estimators for the different structural
... because then ẑj is dependent of Mj and M0 , j = 1, k. Of course, the attractive property of unbiasedness is lost in this way, but we can still expect the resulting estimators to be good. For instance, when an estimator is a maximum likelihood estimator for a parameter, so are functions of it for th ...
... because then ẑj is dependent of Mj and M0 , j = 1, k. Of course, the attractive property of unbiasedness is lost in this way, but we can still expect the resulting estimators to be good. For instance, when an estimator is a maximum likelihood estimator for a parameter, so are functions of it for th ...
Structural Econometric Modeling: Rationales and Examples from
... BLP (y | x), the best linear predictor (BLP) of y given x. In practice, descriptive researchers can choose from a vast array of parametric statistical distributions when they want to describe f (x, y) (or related objects). A common issue that arises in making this choice is whether the chosen distri ...
... BLP (y | x), the best linear predictor (BLP) of y given x. In practice, descriptive researchers can choose from a vast array of parametric statistical distributions when they want to describe f (x, y) (or related objects). A common issue that arises in making this choice is whether the chosen distri ...
