1. Belarus has a GDP per capita of $4,860. Use the model above to predict its in
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Question
1. Belarus has a GDP per capita of $4,860. Use the model above to predict its infant mortality rate. Enter your answer in deaths per 1,000 live births.
2. Suppose you wished to estimate a log-linear model: ln(infmort) = 0 + 1 gdppc + u. Which of the following best describes the procedure you would take in Stata?
Use the "reg" command with the infmort and gdppc variables.
You must use a specialized command for nonlinear models.
Create a new variable for ln(infmort), then use the "reg" command.
Create a new variable for ln(infmort), then use a specialized command for nonlinear models.
Use the "reg" command with the infmort and gdppc variables.
You must use a specialized command for nonlinear models.
Create a new variable for ln(infmort), then use the "reg" command.
Create a new variable for ln(infmort), then use a specialized command for nonlinear models.
The Stata output below shows a linear-log model Inf mort-0 + 1 In gdppc) + u where int mort is the infant mortality rate number of deaths per 1,000 live births and gdppc s the GDP per capita 2005 dollars) reg infmort ingdppc Source df MS Number of obs F 1, 207)301.76 Prob F R-squared Adj R-squared = 0.5912 Root MSE 209 Model 70738.6499 48525.4685 207 234.422553 1 70738.6499 -0.0000 -0.5931 Residual Total 119264.118 208 573.385185 -15.311 infmort Coef. Std. Err. (95% conf . Interval] Ingdppc12.13944.6988275 -17.37 0.000-13.51717 -10.76171 137.8823 cons 126.3775 5.835595 21.66 0.000 114.8727Explanation / Answer
1)
Based on the output and the regression coefficients we see that the regression equation can be formed as
deaths = 126.3775 -12.13944*lngpppc
now we are given gdp = 4860
so ln(gdp) is 8.48
so we put the value in the equation
126.3775 -12.13944*8.48 = 23.43 ~ 23 deaths per 1000 live births approx
Without data 2nd question cant be answered, also please note that we can answer only 1 question at a time as per the answering guidelines
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