Part 2: Data for Other Countries

Go to the World Top Incomes Database and obtain data les with P99,

P99.5, and P99.9 for Canada, China, Colombia, Germany, Italy, Japan,

South Africa, and Sweden. These variables can be found under Income

-> Average income -> Fractiles income levels variable selection and

they are labeled, for example, as P99 income threshold. (Note there are

subdivisions -LAD, -married couples & single adults, -adults but we'd

like the original value). The WTID website also has data on the average in-

come per tax unit" (roughly, household) for the US and the other countries.

While you're at it, obtain this information from the website as well (for all the

countries listed above and the US). This is under Average fiscal incomeper tax unit variable selection. It may be easiest to grab all variables
for all countries, including the US, even though you already have the US
threshold data.
Note: WTID exports data les in xls format, which can't be imported into
R in the usual ways. There are two strategies for getting xls data into R. (1)
Open the les in Excel and then save them as csv les (go to File, Save As
and choose csv), after which we can read them in to R in the usual ways.
Otherwise you can use read.xls() from the gdata package which tries very
hard to work like read.csv().
v. Use your function from problem (iii) to estimate a over time for each
of them. Note that the size of the dataset is dierent for each of these
countries, and there may be some NA values.
Hint: You may nd it helpful to create a separate dataframe for each
country, but make sure they all have the same column names. You could
also keep all the countries in a single dataframe with a Country variable.vi. Plot your estimates of a over time for all the countries using ggplot.
Note that the years covered by the data are dierent for each country.
You may either make multiple plots, or put all the series into one plot.
Either way, make sure that the plots are clearly labeled. I did this by
using the color aesthetic on the categorical variable Country.
vii. Plot the series of average income per tax unit" for the US and the
countries against time in ggplot. Hint: You may nd it helpful for all
this information to be in the same data frames.
viii. The most in
uential hypothesis about how inequality is linked to eco-
nomic growth is the U-curve" hypothesis proposed by the great economist
Simon Kuznets in the 1950s. According tho this idea, inequality rises
during the early, industrializing phases of economic growth, but then
declines as growth continues.Make a scatter-plot of your estimated exponents for the US against the
average income for the US in ggplot. Qualitatively, can you say anything
about the Kuznets curve? (Remember that smaller exponents indicate
more income inequality.)
ix. For a more quantitative check on the Kuznets hypothesis, use lm() to
regress your estimated exponents on the average income, including a
quadratic term for income. Are the coecients you get consistent with
the hypothesis? Hint: the following will regress y on both x and x2:
lm(y ~ x + I(x^2))
x. Do a separate quadratic regression for each country. Which ones have
estimates compatible with the hypothesis? Hint: Write a function to t
the model to the data for an arbitrary country.
(If we were doing a more rigorous check of the Kuznet hypothesis, we
would want to control for other factors, and not just assume that a
quadratic was the right functional form for the curve.)

ComputerScienceExpert

(11)

Status NEW Posted 11 May 2017 06:05 AM My Price 9.00

-----------

Attachments

file 1494484024-Solutions file 2.docx preview (51 words )

H-----------ell-----------o S-----------ir/-----------Mad-----------am ----------- Th-----------ank----------- yo-----------u f-----------or -----------you-----------r i-----------nte-----------res-----------t a-----------nd -----------buy-----------ing----------- my----------- po-----------ste-----------d s-----------olu-----------tio-----------n. -----------Ple-----------ase----------- pi-----------ng -----------me -----------on -----------cha-----------t I----------- am----------- on-----------lin-----------e o-----------r i-----------nbo-----------x m-----------e a----------- me-----------ssa-----------ge -----------I w-----------ill----------- be----------- qu-----------ick-----------ly -----------onl-----------ine----------- an-----------d g-----------ive----------- yo-----------u e-----------xac-----------t f-----------ile----------- an-----------d t-----------he -----------sam-----------e f-----------ile----------- is----------- al-----------so -----------sen-----------t t-----------o y-----------our----------- em-----------ail----------- th-----------at -----------is -----------reg-----------ist-----------ere-----------d o-----------n -----------THI-----------S W-----------EBS-----------ITE-----------. ----------- Th-----------ank----------- yo-----------u -----------

Not Rated(0)

• Buy Answer