Reference no: EM132732270 , Length: word count:1500

EC3017 Applied Econometrics - City University of London

Project

Introduction

This project is an individual piece of assessment that requires you to apply your learning of econometrics analysis to the investigation of the COVID-19 pandemic. The "Our World in Data" website gives you access to a large set of time series and cross-country data related to the pandemic. The datasets are updated daily when new data from countries' statistical agencies become available. A copy of the dataset collected on 10th December 2020 is available on Moodle (Covid-19 Dataset.xlsx). The dataset also contains a description of all variables. You are asked to use this data to write an economic report based on a statistical investigation of the data outlined in the sections below.

The Dataset
At the beginning of 2020 the organisation "Our World in Data" started the regular (daily) collection of data concerning the Covid-19 pandemic across countries. The data is available for public use and the dataset "Covid-19 Dataset.xlsx" (available on Moodle) was downloaded from the "Our World in Data" website on 10th December 2020. On the same site you can also find a detailed codebook with details of each variable in the dataset and its source (please notice that details about each variable are also contained in a separate tab in the excel dataset). You are asked to use this dataset in order to complete the tasks below.

The Tasks
The World Health Organisation has asked you to carry out an analysis of the determinants of COVID-19 cases across a given continent and a given country. On Moodle you will find details of the continent and the country that has been allocated to you. You are required to write a 1,800-word economic report in which you report on your findings. Your report is expected to be organised to include the following analysis.

1. For your allocated continent construct a panel dataset that, for each country, includes one observation per month, starting from March 2020, taken at the end of each month (i.e. the 30th of each month). Once you have set up your dataset you are asked to complete the two following tasks:

a. With the help of graphs and statistics provide a brief analysis of the evolution of COVID-19 cases and deaths across the continent. (approx. 200 words; 10 marks)

b. Carry out an econometrics investigation of the determinants of new COVID-19 cases across the continent. Select the variables you plan to use in your econometric model, justify your selection, produce some summary statistics for each variable and carry out your analysis.
(approx. 500 words, 20 marks)

2. A "reproduction rate" (R) greater than one is regarded as the threshold beyond which the pandemic becomes ‘explosive' with sharp increases in cases. The WHO is interested in investigating what factors are affecting the likelihood of the "reproduction rate" being greater than one. By using the observations from the countries in your continent on 25th November 2020, explain how you would go about evaluating such a likelihood and carefully present the findings of your analysis. In presenting your findings briefly reflect on whether you believe that modelling R in this way is appropriate and whether you would consider alternative modelling strategies.
(approx. 400 words; 30 marks)

3. The WHO is also interested in supplying each individual member country with a detailed analysis of the pandemic in the country. You have been asked to provide an analysis for the country allocated to you over the period 1st April 2020 to 9th December 2020 and your analysis should contain:
a. A brief summary of the evolution of the pandemic over time in your allocated country. The analysis should be supported by appropriate graphs and summary statistics. (approx. 200 words; 10 marks)
b. A regression analysis aimed at estimating the determinants of new COVID-19 cases in the country over time. (approx. 500 words; 30 marks)
Project Guidelines
The aim of this project is to test your understanding of and ability to apply the statistical concepts and methodologies discussed throughout the module as well as your ability to analyse and evaluate the
outcome of your analysis. The project is deliberately ‘open ended' or, in other words, not very prescriptive in what and how you should conduct your analysis. You should refer to the material covered in the module and the activities carried out during the term to decide how to answer the questions and shape your investigation. To help your thinking, you can find the following guidelines of some help.

Task 1

In constructing your dataset and in commenting on the data try to think about questions such as: what type of data do you have in the original and in your adjusted dataset? How many variables do you have? What are the types of variables you have? How many countries and observations do you have? Are there variables containing missing observations? How do you handle the missing information? Overall, how would you regard the quality of your data? In investigating the COVID-19 cases and deaths across your continent can you see any pattern or trend?

In addressing the regression analysis make sure to explain how you construct your econometric model by specifying its functional form and its estimated outcome. Make sure to interpret the estimated model, the significance of each individual estimation and the overall goodness of fit of the regression. Produce a clear account of your findings in such a way that WHO officials, who are not necessarily economist and/or statisticians, can understand the meaning of your analysis.

Task 2

The "reproduction rate" is also commonly referred to as the R number. An R number greater than 1 leads to an explosive behaviour in the reproduction of new cases. The dataset contains estimates of the R number for all countries over time. You are asked to carry out an investigation on the ‘likelihood' that the "reproduction rate" is greater than one. In other words, what factors are likely to influence the probability that the R number will be greater than one? This should be the focus of your analysis: identify those factors that are most likely to make the R number greater than one. Please notice that for this task you are asked to use a cross-section of your database i.e. one observation for each country in your continent at the specified date (25th November 2020).

Task 3

In addressing this question reflect on what type of data and analysis you are asked to carry out. How does it differ from the analysis you carried out in the previous two parts? Make sure to provide a brief but informative analysis of the COVID-19 cases and deaths for the country assigned to you. You should set up your econometrics model and estimate it. Are you, perhaps, considering more than one model because of data availability? As in the previous two parts make sure to comment on your findings both in terms of the estimated coefficient and the goodness of fit. Can you reassure the reader that your estimates are unbiased and efficient? Can you use your model for some forecasting of future COVID-19 cases? Make sure to check that your estimation is providing you with accurate and valid estimates.

Attachment:- Applied Econometrics.rar