If you have a regression which is; lnw= alpha + edu + hours + age +...

If you have a regression which is;

lnw= alpha + edu + hours + age + u,

and you wish to say that the returns to education are increasing or decreasing by a certain percentage, how would you say it?

These are my coefficients:

Intercept; -165.854

Education; 65.47584

Hours; 14.38593

Age; -197.859

How would i interpret them? Are they to be timsed by 100?

For example 65.45584*100 = 6,545,584% returns per year?

The number seems very big but the equation is in logs.

Please answer exactly what my question asks and explain how you recieved the answer.

Solutions

Expert Solution

orchestra answered 1 year ago

Next > < Previous

Related Solutions

Suppose you have a regression that is; lnw= alpha + edu + age + white. When...

Suppose you have a regression that is; lnw= alpha + edu + age + white. When you say ‘when controlling for age’ does it mean that you will only check for ‘age’ whilst the other factors (edu and white and alpha) are held contant? Please provide an easy to understand and clear answer. Please do not write on paper and then upload it as an answer if it is unclear, it does not help.

A researcher estimates the following regression using 1000 observations: W=-3.13+1.47*EDU &n

A researcher estimates the following regression using 1000 observations: W=-3.13+1.47*EDU (0.93) (0.07) Where W is wage, EDU is years of education and the numbers in parentheses are standard errors of the coefficients. Calculate a 95% confidence interval for the coefficient on EDU. A high school graduate is contemplating whether to obtain a 4-year college degree. How much is his/her wage expected to rise? A high school counselor tells a student that college graduates earn a wage $12...

Researchers have collected data on the hours of television watched in a day and the age...

Researchers have collected data on the hours of television watched in a day and the age of a person. You are given the data below. Hours of Television Age (in years) 1 45 3 30 4 22 3 25 6 5 a. Determine the dependent variable. b. Compute the least squares estimated regression equation. c. Is there a significant relationship between the two variables? Use a t test and a .05 level of significance. Be sure to state the...

Researchers have collected data on the hours of television watched in a day and the age...

Researchers have collected data on the hours of television watched in a day and the age of a person. They have taken 6 samples. A linear regression analysis has already been run on this data. Here are the partial results: Analysis of variance (Hours of Television): Source DF Sum of squares Mean squares F Pr > F Model 10.939 Error Total 13.333 Model parameters (Hours of Television): Source Value Standard error t Pr > |t| Lower...

With respect to alpha which is true. Alpha is the level of probability at which the...

With respect to alpha which is true. Alpha is the level of probability at which the null hypothesis can be reached with confidence

(3) Suppose that you run a regression of wage on a set of independent variables: age,...

(3) Suppose that you run a regression of wage on a set of independent variables: age, years of education, experience, and a dummy variable married. There are 100 observations, i.e., n=100. You want to test whether all the coefficient and intercept estimates in the equation for married and unmarried are equal to each other. i.e., Married: wage = β0 + β1*age + β2*educ + β3*exper + uUnmarried: wage = α0 + α1*age + α2*educ + α3*exper + v (a) Write...

In forward stepwise regression, why should the alpha-to-enter value for adding variables never exceed the alpha-to-remove...

In forward stepwise regression, why should the alpha-to-enter value for adding variables never exceed the alpha-to-remove value for deleting variables?

QUESTION A: A regression was run to determine if there is a relationship between hours of...

QUESTION A: A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=a+bx a=26.695 b=-0.65 r2=0.531441 r=-0.729 Assume the correlation is significant (p-value < α), and use this to predict the number of situps a person who watches 13.5 hours of TV can do (to one decimal place) QUESTION PART B: Run a regression analysis on...

Suppose you are interested in estimating the relationship between edu (number of years of university education)...

Suppose you are interested in estimating the relationship between edu (number of years of university education) and the inc (annual income measured in ten thousand) and you run the following regression: ??? = ?? + ?? ??? + ? 4.A Suppose ?? = ???? , ?? = ???? , ??? ? = 8. Further, if you know, ?̅ = 3.2125, ?̅= 25.875, ∑ (?? − ?̅ ? ?=1 ) (?? − ?̅) = 5.8125 and ∑ (?? − ?̅) 2...

You have estimated the effects of the age of children, women’s age in years, years of...

You have estimated the effects of the age of children, women’s age in years, years of schooling, unemployment rate in the county of residence, and whether the woman lives in metropolitan area on the woman’s probability of being in labor force. In Table 2, column 1 shows the coefficients from the linear probability model, column 2 shows the coefficients from a probit model, and column 3 shows the coefficients from a logit model. Interpret coefficients on variables: # kids <...

Subjects