Q1. Briefly explain theoretically the association between economic growth with carbon emissions. Also, in the light of theory, briefly discuss the association of other variables listed above with carbon emissions. Obtain data on all variables list above from WDI for a specific year (choose any one year between 2014-18) and at least 50 countries observations. Produce histogram of per capita income and analysis and discuss the shape of histogram. Label it and provide a title for it.
Q2. Obtain data required to compute the association between GDP per capita and CO2 emission/capita. Produce a scatter plots of CO2 emission per capita (y-axis) against per capita income (x-axis), renewable energy consumption and trade openness. Based on visual inspection, discuss any pattern and outliers in the data that emerge. Identify the outliers and discuss the impact of outliers on the regression.
Q3. Present and discuss the table of summary statistics. This table should contain at least number of observations, mean, standard deviation, minimum, and maximum values for your chosen variables
Q4. Compute and present a correlation matrix. Discuss correlation between CO2 emission/ capita, GDP per capita, Renewable energy consumption (% of total final energy consumption) and trade openness.
Q5. (5a) Specify a regression model that explains how C02 emissions/ capita depends on explanatory variables in the light of theoretical association of independent variables with dependent variable and test an appropriate hypotheses. Estimate the model by applying an appropriate econometric method. Interpret your estimated results following theoretical associations between variables/hypotheses testing and by choosing an appropriate level of significance. Reflect your understanding on the overall degree of fit of the model. Present your estimated results in a table and discuss your findings.
(5b) Based on the regression results in Q5(a), what are the marginal effects of GDP/ Capita, and renewable energy consumption (% of total final energy consumption).
Q6. In the model specified in Q5, you decide to test the possibility that explanatory variable (s) is (are) irrelevant by dropping one or more variables from model and rerunning the equation. Discuss the reason why the variable(s) should and or should have not be included in your model. Specify a final regression model which includes all relevant variable(s) that you identified as relevant explanatory variable(s) (Hint: be sure to use our four specification criteria). Present the results in a table and discuss them.
Q7. Explain a distinction between an equation that is linear in the coefficients and one that is linear in variables. Examine whether log transformation of dependent and independent variables provides better estimates compared to regression analysis conducted using level-level regression model estimated in Q6. Furthermore, can you compare R-squared estimated results of level-level model with the estimated regression results of double log regression model? If not, explain the rationale behind it. Present your estimated results using double log model in a table and discuss your findings.
Q8. (8a) Specify your final choice of estimated model following analysis conducted at Q6 and Q7. What do we mean by heteroskedasticity? Apply an alternate method of testing for heteroskedasticity in your model. Discuss the strengths and weaknesses of those alternate methods for heteroskedasticity. Present your estimated model results in a table 4 and discuss the heteroskedasticity implications for estimated coefficients in your model.
(8b) What are the remedies for heteroskedasticity? Use an alternate test to correct for heteroskedasticity in estimated model and reproduce the estimated results based on the heteroskedasticity corrected standard errors in a table. Compare this estimated model with your estimated model results obtained in 8(a) and discuss your findings.
CS 340 Milestone One Guidelines and Rubric Overview: For this assignment, you will implement the fundamental operations of create, read, update,
Retail Transaction Programming Project Project Requirements: Develop a program to emulate a purchase transaction at a retail store. This
7COM1028 Secure Systems Programming Referral Coursework: Secure
Create a GUI program that:Accepts the following from a user:Item NameItem QuantityItem PriceAllows the user to create a file to store the sales receip
CS 340 Final Project Guidelines and Rubric Overview The final project will encompass developing a web service using a software stack and impleme
