本次英国代写是stata计量经济的一个coursework

1.Using data from the U.S. in 1999 the salary of 447 Chief Executive
Officers (CEOs) was modelled as a double logarithmic function of
firm profit, a quadratic in CEO tenure (years with the firm) and a
quadratic in CEO age:

where 𝑝𝑝 is the unit of observation (CEO) and log denotes the natural
logarithm. The following Stata output shows the estimates.

Interpret the results.

Draw a diagram in salary and year space to roughly plot the shape
and relative positions of the tenure and age functions based upon
the above.

Calculate the value of tenure at which salary is maximised.
Similarly, calculate the value of age at which salary is maximised.

For the explanatory variables calculate the slope and elasticity,
based at the sample mean.

Calculate the value of the RSS and the degrees of freedom
associated with the ESS, RSS and TSS.

Test whether the parameters on the explanatory variables are
jointly statistically significant at the 5 per cent level.

Calculate the adjusted R-squared and explain why it is preferred
to the R-squared.

STATA ASSIGNMENT

2. The following data set wages.dta is cross sectional based upon
2,320 individuals in 2002 from the U.S. The variables in the data
are:

wage = hourly wage rate in cents
educ = years of schooling of the individual
fatheduc = father’s years of schooling
motheduc = mother’s years of schooling
black = dummy variable (0 white, 1 black)
IQ = Intelligence score
married = dummy variable (0 unmarried, 1 married)
exper = years of labour market experience

Using an appropriate semi log wage specification estimate a wage equation where
YOU choose the independent variables BUT MUST include, “fatheduc” and
“motheduc” as independent variables.

Interpret the estimated parameters of your model.

Test whether the individual parameters estimated are individually statistically
significant and jointly statistically significant BY HAND and then compare to the Stata
output.

Test your estimated model for heteroscedasticity using the WHITE test BY HAND
(without using any inbuilt Stata test commands).

Test whether the parameters associated with “fatheduc” and “motheduc” are equal to
each other BY HAND using Stata to construct the appropriate RSS.

Provide the text from your Stata *.do file.