Due date: Friday, Sep 30 at 5pm on Canvas.

Items due: Write-up (article), R code, and data files. Submit all these files in one zipped folder.

Guidelines: For your project you will do a simple test of uncovered interest parity (UIP). While you are encouraged to discuss with classmates any issues you have with coding in R, the actual write up and    analysis is expected to be your work only.

You are free to choose any two currencies except for the JPY-USD combination. (You may choose the    USD with any non-JPY currency, or the JPY with any non-USD currency.) You will need to collect data on the nominal exchange rate between the currencies as well as interest rates on both currencies. For the interest rates, you should use yields on government bonds.

All of the analysis of the data must be completed using R. I will provide a template code for starting with R, but you will be expected to do add more to the code. There are many useful resources online for         doing things in R.

In terms of data, you must provide enough information so that anyone can look at your article and be   able to easily retrieve the same exact data. You may store your data using any standard file (Excel, text file, csv file, etc.). However, all analysis must be done using R (such as figures and any calculations). You will need to submit the R code as well. I should be able to run your code and generate the figures and   results that are in your article.

Your write up should look like a short policy report. There is no restriction on page limit, although a          sharp, clear piece should end up being between 2-4 pages, with up to three figures and up to two tables. You can break it into the following sections:

1.   Which currencies are being studied and why you chose them?

2.    Description of data

o Where the data come from along with a link to the data source(s).

o Specify the frequency of the exchange rate data (monthly, quarterly, annual, etc.) as well as the duration of the interest payments on the bonds (are the yields monthly,  quarterly, annual, etc.)

o A description of patterns in the data supported with figures. For instance, a time series plot of each of the three pieces of data: the exchange rate and the two interest rates.

3.   Test for UIP.

o What the regression specification you will use? What is the null hypothesis?

o Summarize regression results using a clean table. The table should be clear and should contain estimates of the intercept and the coefficient along with either standard errors or p-values or t statistics. Do not just copy-paste the results from R and drop them in    your summary – that is not clean.

o Interpret your regression results in terms of whether or not they are consistent with   UIP. If they are not consistent, offer an explanation as to why they might not be based on specific characteristics of the countries involved (riskiness, or other issues that we  discussed in class and in the notes).