# Interest Parity Condition

You are also required to write a longer paper that analyzes one of the economic concepts covered in class.  You should collect data relating to a monetary economics issue, and then analyze the data using theories developed in class.  For instance, you might look at how monetary policy affects other macro variables such as interest rates, prices, output, or exchange rates.  You may want to take an important course concept such as the quantity theory of money, the Philips curve, purchasing power parity, the interest parity theorem, or the Fisher effect, and test that concept using real world data.  You can use U.S. data, or data for one or more foreign countries.  You can use time series data or cross sectional data.  Those who don’t have a good background in statistical analysis should use graphical analysis.

Organization of Paper:

1. Discuss the theory that you plan to test.  Why is it expected to hold true?
2. Discuss the country or countries that you plan to examine, and the time period.
3. Discuss the data you plan to use.  What are your data sources?
4. How is the data modified?  Real or nominal variables?  Levels or rates of change?
5. What statistical tests will you use?  Eyeball examination of graph?  Regression analysis?
6. What does the test show?  Is that consistent with your hypothesis?
7. What might explain discrepancies between your findings and the theory’s predictions.

The following suggestions may also prove helpful:

1.  You should clearly distinguish between real and nominal variables.  You need to think about which is more appropriate for your model.  If you generate real data, explain how this was done.

2.  You need to clearly distinguish between levels and rates of change.  Here again, you need to think about which is more appropriate for your model.  For instance, most macroeconomic aggregates show an upward trend, and thus a time series analysis may show a significant correlation even where the variables are actually unrelated.  This problem can be reduced (but not always eliminated), by using rates of change rather than levels.

3.  You should clearly discuss the issue of causality.  If two variables are statistically related, discuss what causes that relationship.

4.  Please be aware of the identification problem.  For instance, the correlation between price and quantity will depend on whether the market is impacted by demand shifts or supply shifts.

Topic: Interest Parity Condition

Key variables:

1. Interest rates (real, nominal, long term, short term)
2. Inflation and the price level
3. The money supply and its growth rate (MB, M1, M2, MZM, etc.)
4. Real and nominal GDP, levels and growth rates, unemployment rate.
5. Exchange rates, and rates of change in E

Sources of data:

2. Web sites (World Bank, St. Louis Fred, Global Insight, etc.)
3. Library

Types of data sets:

1.  Time series (watch out for serial correlation—use rates of change where possible)
2. Cross-sectional  (try to get at least 25 observations)

Types of statistical analysis:

1. Regression analysis (simple, multiple.) Only if you feel comfortable interpreting the output.
2. Graphical analysis (Label completely.)  If the theory involves three variables, combine two of them for a two dimensional presentation.  And don’t test tautologies like MV=PY or i = ir + inflation.

Event studies.  This tests the immediate market reaction to news events

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