Project Assignment 2020
MG4F7

1.检查结果变量（人均GDP）。

b。什么意思
C。中位数和均值之间的差异是否表明存在

2.检查解释变量。

……”。研发支出与收入之间有什么关系？

b。现在检查收入与研发之间的单变量相关性

C。创建一个变量，该变量指示所有变量都不丢失。

d。检查并报告解释之间的每对相关性

corr x3 x4）。您在哪里看到最大的潜在共线性

3.接下来，我们检查每个解释变量之间的简单关系

b。估计预测人均收入的简单回归

c. What is the y-intercept in the simple regression of income per capita
on the cost of business start up procedures? What does it mean in
practice? Is it a “realistic” y-intercept in the sense of describing a
potential reality?
d. What is the slope in the simple regression of income per capita on the
cost of business start up procedures? How is income predicted to
change if a country were to see a decline in the cost of opening a
business from 60% of national income per capita to 10%?
e. Based on the simple regression of income per capita on the cost of
business start up procedures, what is the predicted level of income
per capita in a country with start up costs equal to 100% of national
income per capita? What is the approximate 95% prediction interval
for income in a country with start up costs equal to 100% of national
income per capita? Is this level of start up costs an outlier in the data?
f. What is the y-intercept in the simple regression of income per capita
on R&D expenditures? What does it mean in practice? Is it a “realistic”
y-intercept in the sense of describing a potential reality?
g. What is the slope in the simple regression of income per capita on
R&D expenditures? Suppose a government minister proposes an
ambitious policy increasing R&D expenditures by 0.5% of national
income (GDP). The minister argues that this will increase income per
capita by \$10,000. Do you think this is likely? Explain.
h. What is the y-intercept in the simple regression of income per capita
on life expectancy? What does it mean in practice? Is it a “realistic” yintercept in the sense of describing a potential reality?
i. What is the R-squared in the simple regression of income per capita
on life expectancy? How does it compare to the R-squared in the other
simple regressions?
j. Based on part 4(i), do you think that life expectancy has an important
role in causing higher incomes? Propose a mechanism that would
produce such a causal relationship.
k. Suppose you were skeptical that the observed relationship between
income per capita and life expectancy is causal. Propose one reverse
causality mechanism and one omitted variables mechanism that
would produce the positive relationship observed.
4. Let’s see what we would observe if we happened to draw particular
subsamples for our estimates. Make sure your data are sorted by country
name. Generate a country code that is increasing as you go down the dataset
(so Afghanistan is 1, Albania 2, etc., down to Zimbabwe at 217).
a. Estimate the regression line predicting income using R&D
expenditure for country code 1-50; 51-100; 101-150; and, 151-217.
Report the estimated slopes. Why do the slopes differ from one
regression to the next?
b. If you were trying to infer the relationship between R&D spending
and income per capita for the entire set of 217 countries from just one
of these subsamples, how would you do it (hint: you can think of this
as having a few different “sample” signals, and you are trying to
estimate where a “population” parameter is likely to be)? Would each
of the subsamples allow you to produce a reasonable inference about
the relationship present in all 217 countries? EasyDue™ 支持PayPal, AliPay, WechatPay, Taobao等各种付款方式!

E-mail: easydue@outlook.com  微信:easydue

EasyDue™是一个服务全球中国留学生的专业代写公司