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Basic Econometrics Individual Assignment: Cross-Sectional Regression Analysis, Model Interpretation, and Gauss-Markov Assumptions

Basic Econometrics Individual Assignment

QUESTIONS:

ย 1) Use R to run the following cross-sectional regression. (Please note the natural logs and construct these in R as needed):

๐‹๐ข๐Ÿ๐ž๐ž๐ฑ๐ฉ = ๐œท๐ŸŽ + ๐œท๐Ÿ๐ฅ๐จ๐ (๐†๐ƒ๐๐ฉ๐œ) + ๐œท๐Ÿ๐”๐ง๐๐ž๐ซ๐๐จ๐ฎ๐ซ๐ข๐ฌ๐ก๐ž๐ + ๐œท๐Ÿ‘๐ƒ๐ซ๐ข๐ง๐ค๐ข๐ง๐ ๐–๐š๐ญ๐ž๐ซ + ๐œท๐Ÿ’๐ฅ๐จ๐ (๐“๐) + ๐œท๐Ÿ“๐’๐’๐’ˆ(๐ˆ๐ฆ๐ฆ๐ฎ๐ง๐ข๐ณ๐š๐ญ๐ข๐จ๐ง) + ๐’–ย ย ย 

a) Present your regression results in a table below (R output):

2 marksย 

b) Interpret the constant (2.5 marks) and its p-value (1.5 marks).

4 marks

c) Interpret the coefficient on GDP per capita (2.5 marks) and its p-value (1.5 marks).

4 marks ย 

ย d) Interpret the coefficient on the % of people using at least basic drinking water services (2.5 marks) and its p-value (1.5 marks).

4 marksย 

ย e) Interpret the coefficient on Incidence of tuberculosis (per 100,000 people) (2.5 marks) and its pvalue (1.5 marks).

4 marks ย 

f) Interpret the coefficient on Immunization, DPT (% of children ages 12-23 months) (2.5 marks) and calculate its t-stat. Interpret the calculated t-statistic (1.5 marks).

4 marksย ย 

ย g) Interpret the R2 of the regression.

2 marksย 

h) One of the explanatory variables is in a functional form that is not usually recommended. Which one is it, and how would you change it?

2 marksย 

ย 2) Specify if the Gauss-Markov assumptions are likely to hold for the regression in Question 1 or not and explain why (each assumption).

5 marks

ย 3) Run the following regression with a quadratic drinking water term added to the original regression:

๐‹๐ข๐Ÿ๐žย ย ย  ๐„๐ฑ๐ฉ๐ž๐œ๐ญ๐š๐ง๐œ๐ฒ = ๐œท๐ŸŽ + ๐œท๐Ÿ๐ฅ๐จ๐ (๐†๐ƒ๐๐ฉ๐œ) + ๐œท๐Ÿ๐”๐ง๐๐ž๐ซ๐๐จ๐ฎ๐ซ๐ข๐ฌ๐ก๐ž๐ + ๐œท๐Ÿ‘๐ƒ๐ซ๐ข๐ง๐ค๐ข๐ง๐ ๐–๐š๐ญ๐ž๐ซย  ย  ย  ย  ย  ย  + ๐œท๐Ÿ’๐ƒ๐ซ๐ข๐ง๐ค๐ข๐ง๐ ๐–๐š๐ญ๐ž๐ซ๐Ÿย  ย  ย  ย  + ๐œท๐Ÿ’๐ฅ๐จ๐ (๐“๐) + ๐œท๐Ÿ“ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย  ๐ฅ๐จ๐ (๐ˆ๐ฆ๐ฆ๐ฎ๐ง๐ข๐ณ๐š๐ญ๐ข๐จ๐ง) + ๐’–ย ย ย 

2 marks

ย a) Is the relationship U-shaped or inverted U shaped? Is this a significant relationship?

2 marksย 

b) Calculate the turning point of the quadratic relationship, and please analyse the result.

4 marksย 

ย 

4) Present a functioning R code reproducing the results below. This is a critical part of the assignment without which weโ€™ll initiate a plagiarism check.

1 mark

Assignment Total: 40 marksย 

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FORMULA SHEET

Critical values for the standard normal distribution (z)

Confidence level

(1-ฮฑ)

Level of

Significance (ฮฑ)

Twoโ€“Sided

Critical Value cฮฑ/2

One-Sided,

Upper-Tail

Critical Value cฮฑ

One-Sided,

Lower-Tail

Critical Value -cฮฑ

90% 10% 1.645 1.28 -1.28
95% 5% 1.96 1.645 -1.645
99% 1% 2.58 2.33 -2.33

ย 

Formula for a t-statistic

๐‘กย ย ย ย ย  = ๐‘’๐‘ ๐‘ก๐‘–๐‘š๐‘Ž๐‘ก๐‘’ โˆ’ โ„Ž๐‘ฆ๐‘๐‘œ๐‘กโ„Ž๐‘’๐‘ ๐‘–๐‘ ๐‘’๐‘‘ย ย ย ย ย ย ย ย ย ย ย ย  ๐‘ฃ๐‘Ž๐‘™๐‘ข๐‘’ / ๐‘ ๐‘ก๐‘Ž๐‘›๐‘‘๐‘Ž๐‘Ÿ๐‘‘ย ย ย ย ย ย ย ย ย ย ย ย  ๐‘’๐‘Ÿ๐‘Ÿ๐‘œ๐‘Ÿ

Formula for a (1-ฮฑ)% confidence interval

๐ถ๐ผ+,- = ^๐›ฝโ€˜ โˆ’ ๐‘-// โˆ— ๐‘ ๐‘’c๐›ฝโ€˜d, ๐›ฝโ€˜ + ๐‘-// โˆ— ๐‘ ๐‘’c๐›ฝโ€˜df

Logarithmic/Quadratic/Interaction specifications

For the model ๐‘™๐‘œ๐‘”(๐‘ฆ) = ๐›ฝโ€˜0 + ๐›ฝโ€˜+๐‘ฅ+ + ๐›ฝโ€˜/๐‘ฅ/, the exact effect of a change in explanatory variable x2 is: %โˆ†๐‘ฆk = 100nexpc๐›ฝโ€˜/โˆ†๐‘ฅ/d โˆ’ 1r

For a quadratic specification of the form:

๐‘ฆ = ๐›ฝ0 + ๐›ฝ+๐‘ฅ + ๐›ฝ/๐‘ฅ/ + ๐‘ข

The turning point (maximum/minimum) is given by:

๐‘ฅโˆ— = s๐›ฝโ€˜+/(2๐›ฝโ€˜/)s

The approximation of the marginal effect of x on y is given by:

โˆ†โˆ†๐‘ฆ๐‘ฅkย ย  โ€˜+ + 2๐›ฝโ€˜/๐‘ฅ โ‰ˆ ๐›ฝ

For a interaction specification of the form:

๐‘ฆ = ๐›ฝ0 + ๐›ฝ+๐‘ฅ+ + ๐›ฝ/๐‘ฅ+ โˆ— ๐‘ฅ/ + ๐‘ข

The approximation of the marginal effect of x1 on y is given by:

โ€‹ฮ”y/ฮ”๐‘ฅ/ โ‰ˆ ๐›ฝ/ย โˆ—ย ๐›ฝ/ย ๐‘ฅ/

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