How is the slope coefficient interpreted in a log-linear model,
where the dependent variable is (i)...
How is the slope coefficient interpreted in a log-linear model,
where the dependent variable is (i) in logarithms but the
independent variable is not (i.e. a log-linear model), (ii) in a
linear-log model and (iii) in a log-logmodel?
how to interpret log-linear coefficient? Follow is the
independent variables and their coefficient
Dependent variable: EXPORT
Constant= 11.96
Adoption rate=0.03
approval process=5.12
risk assessment=-3.6
labeling = -2.03
international agreement= 0.44
Suppose you estimate a simple linear regression model and obtain
a t-value for the slope coefficient of -3.1. Based on this, explain
which of the following statements are correct or wrong:
a) A 95% confidence interval for the true slope would exclude
0.
b) It is possible that the point estimate for the slope is
b_1=4.
c) At the 10% level of significance you fail to reject the null
hypothesis that the true slope is equal to 0.
d) The...
Having data of two independent variables and a dependent
variable, how do I plot a linear graph (trendline fit)? (Linear
equation) Possible to use excel.
I have to do a simple linear regression project. The dependent
variable that I chose is international tourist receipts (US$
billions) and the independent variable I chose is International
tourist arrivals in (billions). Did I set up my variables
correctly? I am using data from the World Bank. The main trouble I
am having is why testing the correlation between these two
variables is important and need some ideas on answering the few
questions in the introduction of the essay,...
How
do you interpret a regression coefficient, which has log
differences as both independent and dependent variable.
For example, log(y_t+1)-log(y_t) =
alpha+beta{log(x_t+1)-log(x_t)}+......
Is it “1 percent increase in the growth rate of x affects the
growth rate of y by beta percent.”?
1. Explain why the linear probability model is inadequate as a
specification for binary dependent variable estimation.
2. How can we measure whether the probit and logit model that we
have estimated fits the data well or not?
3. How does R-square for the OLS differ frmo the pseduo R-square
for binary models?
Your experience tells you that an independent variable is positively correlated to the dependent variable but a multiple regression model give it a negative coefficient. What could cause this? Your judgement is wrong. Statistics don't lie The software package made an error The homoscedasticity assumption has been violated The model may have correlated independent variables The heteroscedasticity assumption has been violated
For a regression with log(bweight) as the dependent variable, we
have
Variable
Estimate
Standard Error
Constant/Intercept
4.66
0.029
Male
0.03
0.010
Motheduc
0.002
0.002
lfaminc
0.02
0.006
You expect an increase in family income to increase birth
weight. Test this hypothesis at the 1% level of significance. Make
sure you explicitly include all of the steps.