这个作业是对人均GDP进行均值、回归等数据分析

Project Assignment 2020
MG4F7

1.检查结果变量(人均GDP)。
一种。中位数是多少?
b。什么意思
C。中位数和均值之间的差异是否表明存在
分布中的偏斜-如果是这样,朝哪个方向?做一个
绘制国民收入的直方图(保存图表并将其包括在
您的回应–请在任何时候要求您
图或表格)。看起来是否如您所愿?
2.检查解释变量。
一种。制作一个包含结果变量(y)和所有变量的相关表
变量(x1,x2,x3等)的状态是“ corr y x1 x2 x3
……”。研发支出与收入之间有什么关系?
它会让您感到惊讶吗?
b。现在检查收入与研发之间的单变量相关性
支出(Corr y x1)。您现在看到的相关性是什么?任何
知道会发生什么?
C。创建一个变量,该变量指示所有变量都不丢失。
检查收入与研发之间的单变量相关性
如果非缺失指标等于1,则为支出(corr y x1)。
您看到什么相关性?这是否澄清了3(a)中的发现
和3(b)?它对您应该如何运行有什么建议?
多元回归?
d。检查并报告解释之间的每对相关性
变量(corr x1 x2,corr x1 x3,corr x1 x4,corr x2 x3,corr x2 x4,
corr x3 x4)。您在哪里看到最大的潜在共线性
问题?
3.接下来,我们检查每个解释变量之间的简单关系
和结果变量(人均GDP)。
一种。请制作散点图,其中绘制人均收入
针对每个感兴趣的解释变量。什么键
在图表中可以看到政府质量的局限性
机构是解释变量吗?您看到什么关键问题
在图表中,其中创业费用是解释性的
变量?您如何解决这个问题?
b。估计预测人均收入的简单回归
每个感兴趣的解释变量。请报告坡度
并针对每个回归进行拦截(或仅合并回归)
输出到您的项目提交中)。
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?


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