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stata代写-220Y5Y

时间：2021-04-13

ECO220Y5Y: Introduction to Data Analysis and Applied

Econometrics

Data Project Two

Winter Term 2021

Is COVID-19 likely to increase educational inequality amongst less de-

veloped countries? Does cross-country evidence indicate some countries

are at greater risk of an educational crisis?

0.1 Project Overview

Your goal is to describe the variation in COVID-19 related educational inequality and risks facing the

education sector across countries. You should comment on the articles which discuss the severity of

the situation for many countries and what COVID-19 might mean for educational vulnerabilities. You

will do this using the ‘projectdata Fall2020.xlsx’ file provided. Continuing from your previous analysis

you will produce additional evidence using your knowledge from linear regression. You must now

include and discuss results using multivariate regression techniques, for example: output

tables, interpretation of coefficients, goodness of fit statistics, plots of residuals, etc. You should

consider carefully the best specification and provide evidence (formal testing or analysis of plots) to

support your model selection. You should consider creating indicator variables that might be used

to impact the intercept or as interaction terms. You should look for common violations of the OLS

assumptions in your regressions such as heteroskedasticity, serial correlation and non-normality. You

should conclude using your model to determine whether COVID has increased educational inequality

for developing countries. You should comment on how significant your variables of interest are

and what economic significance you can uncover relating COVID to educational outcomes amongst

different countries.

As with data project one, the data are a set of variables downloaded and combined from the

Federal Reserve Economic Data, OurWorldinData.org, the OECD data repository and UNICEF.

The file comprises cross sectional data for various countries measured on similar dates (ex. data on

the severity of COVID-19 and its response are from April 1, 2020). A brief description of the available

variables is given in the excel file (further description is available on the corresponding websites).

Using suitable quantitative techniques from ECO220 describe some interesting characteristics of the

variables of interest to you. In interpreting, explaining and assessing validity of your output, you

should read the articles provided. Try to pick out variables that might be related in some way to

the question and discuss these. You can also search out your own literature to guide your discussion

but be sure to include any other sources in a bibliography.

0.2 Project Submission

As with project 1, project 2 will not be marked based on length but rather how well you addressed

the question. Your submission should not exceed 1200 words of text and 4 pages of graphs and tables.

If it is written in a clear and concise style, and you have a good handle on generating useful graphs,

this limit will be sufficient for a full mark. Write an assessment that is smart, not long. Highlight

the findings that are puzzling, practically useful, thought provoking or seem to be counter-intuitive.

Try to deliver a submission that is interesting and easy to follow, a short piece of statistical analysis

that you yourself would like to read.

This Data Project is worth 7.5% of your final mark. All statistical analysis should be done using

either Stata or R. The final report should be submitted as a single written document in .pdf format

and you must also include your DO file for Stata or SCRIPT file for R. The submission deadline is

Monday April 19th.

0.3 Software Help

Several videos on how to use econometrics software are available online. An additional help lecture

will be provided. Alternatively there are some good handbooks available for Stata.

学霸联盟

Econometrics

Data Project Two

Winter Term 2021

Is COVID-19 likely to increase educational inequality amongst less de-

veloped countries? Does cross-country evidence indicate some countries

are at greater risk of an educational crisis?

0.1 Project Overview

Your goal is to describe the variation in COVID-19 related educational inequality and risks facing the

education sector across countries. You should comment on the articles which discuss the severity of

the situation for many countries and what COVID-19 might mean for educational vulnerabilities. You

will do this using the ‘projectdata Fall2020.xlsx’ file provided. Continuing from your previous analysis

you will produce additional evidence using your knowledge from linear regression. You must now

include and discuss results using multivariate regression techniques, for example: output

tables, interpretation of coefficients, goodness of fit statistics, plots of residuals, etc. You should

consider carefully the best specification and provide evidence (formal testing or analysis of plots) to

support your model selection. You should consider creating indicator variables that might be used

to impact the intercept or as interaction terms. You should look for common violations of the OLS

assumptions in your regressions such as heteroskedasticity, serial correlation and non-normality. You

should conclude using your model to determine whether COVID has increased educational inequality

for developing countries. You should comment on how significant your variables of interest are

and what economic significance you can uncover relating COVID to educational outcomes amongst

different countries.

As with data project one, the data are a set of variables downloaded and combined from the

Federal Reserve Economic Data, OurWorldinData.org, the OECD data repository and UNICEF.

The file comprises cross sectional data for various countries measured on similar dates (ex. data on

the severity of COVID-19 and its response are from April 1, 2020). A brief description of the available

variables is given in the excel file (further description is available on the corresponding websites).

Using suitable quantitative techniques from ECO220 describe some interesting characteristics of the

variables of interest to you. In interpreting, explaining and assessing validity of your output, you

should read the articles provided. Try to pick out variables that might be related in some way to

the question and discuss these. You can also search out your own literature to guide your discussion

but be sure to include any other sources in a bibliography.

0.2 Project Submission

As with project 1, project 2 will not be marked based on length but rather how well you addressed

the question. Your submission should not exceed 1200 words of text and 4 pages of graphs and tables.

If it is written in a clear and concise style, and you have a good handle on generating useful graphs,

this limit will be sufficient for a full mark. Write an assessment that is smart, not long. Highlight

the findings that are puzzling, practically useful, thought provoking or seem to be counter-intuitive.

Try to deliver a submission that is interesting and easy to follow, a short piece of statistical analysis

that you yourself would like to read.

This Data Project is worth 7.5% of your final mark. All statistical analysis should be done using

either Stata or R. The final report should be submitted as a single written document in .pdf format

and you must also include your DO file for Stata or SCRIPT file for R. The submission deadline is

Monday April 19th.

0.3 Software Help

Several videos on how to use econometrics software are available online. An additional help lecture

will be provided. Alternatively there are some good handbooks available for Stata.

学霸联盟