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Environmental Economics

Homework 4

Data and Commodities Markets:

For this homework, I want you to perform some data analysis in R. For this homework, we will be using data from the datasets package in R. The first dataset is a C02 time-series using observations of Mauna Loa atmospheric C02 concentration and can be accessed by loading the package and typing c02. Plot the data. Do you observe any seasonal patterns? Do you observe an overall trend? The second dataset is called mtcars and can be accessed through the command mtcars. A description of the variables in the dataset can be found here. Choose two variables to plot against one another from the dataset. Make an argument for why these variables are useful in theory. What do you observe from the plot? Choose variables from the dataset that might impact mpg. Run a regression using those variables. Writeup findings and state whether relationships were as suggested.

Find one or multiple time series on the Energy Information Agency’s website related to oil, natural gas, or another energy commodity. Explain why you picked this time series and what the time series means. Plot the time series in R. Use a linear regression or time-series regression to predict the time series. Provide the work of the prediction. Discuss the implications of your plot or prediction for the value of either the series or some part of the balance sheet related to oil.

Submit either a word document, PDF, or HTML. Unless you use Rmarkdown, you must also submit your codes.

Additionally, submit the following problems:

Commodities Markets:

1. Find and read three articles related to oil and natural Gas. For each article, provide a one to three sentence writeup of the article’s main point. Provide one paragraph predicting the direction of the price of oil based on these articles.

2. Provide three long run scenarios about the adoption of renewable energy. State the assumptions of each scenario and how likely you think each scenario is in plain English. State implications for the price of at least two commodities